initial commit with charts and assistant chat

.gitignore

@@ -0,0 +1,100 @@
+# Environment variables
+.env
+.env.local
+.env.*.local
+
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# Virtual Environment
+.venv/
+venv/
+ENV/
+env/
+
+# Testing
+.pytest_cache/
+.coverage
+.coverage.*
+htmlcov/
+.tox/
+.nox/
+*.cover
+*.log
+
+# ArcticDB data storage
+*.arctic
+arctic_data/
+arcticdb_storage/
+
+# Memory and data files
+backend/memory/*.db
+backend/memory/*.sqlite
+*.db
+*.sqlite
+
+# Uploaded files
+backend/uploads/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# PyCharm / IntelliJ IDEA
+.idea/
+
+# VS Code
+.vscode/
+
+# Node.js / Web
+node_modules/
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+package-lock.json
+yarn.lock
+
+# Docker
+*.log
+docker-compose.override.yml
+
+# OS-specific
+.DS_Store
+.DS_Store?
+._*
+.Spotlight-V100
+.Trashes
+ehthumbs.db
+Thumbs.db
+*~
+
+# Git
+.git/
+
+# Temporary files
+*.tmp
+*.temp
+*.swp
+*.swo
+*.bak

.idea/.gitignore

@@ -0,0 +1,10 @@
+# Default ignored files
+/shelf/
+/workspace.xml
+# Ignored default folder with query files
+/queries/
+# Datasource local storage ignored files
+/dataSources/
+/dataSources.local.xml
+# Editor-based HTTP Client requests
+/httpRequests/

.idea/ai.iml

@@ -0,0 +1,13 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$">
+      <sourceFolder url="file://$MODULE_DIR$/backend/src" isTestSource="false" />
+      <sourceFolder url="file://$MODULE_DIR$/backend/tests" isTestSource="true" />
+      <excludeFolder url="file://$MODULE_DIR$/.venv" />
+      <excludeFolder url="file://$MODULE_DIR$/backend/data" />
+    </content>
+    <orderEntry type="jdk" jdkName="Python 3.12 (ai)" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

.idea/inspectionProfiles/Project_Default.xml

@@ -0,0 +1,16 @@
+<component name="InspectionProjectProfileManager">
+  <profile version="1.0">
+    <option name="myName" value="Project Default" />
+    <inspection_tool class="Eslint" enabled="true" level="WARNING" enabled_by_default="true" />
+    <inspection_tool class="GrazieInspection" enabled="false" level="GRAMMAR_ERROR" enabled_by_default="false" />
+    <inspection_tool class="LanguageDetectionInspection" enabled="false" level="WARNING" enabled_by_default="false" />
+    <inspection_tool class="PyIncorrectDocstringInspection" enabled="false" level="WEAK WARNING" enabled_by_default="false" />
+    <inspection_tool class="PyPep8Inspection" enabled="false" level="WEAK WARNING" enabled_by_default="false" />
+    <inspection_tool class="PyPep8NamingInspection" enabled="false" level="WEAK WARNING" enabled_by_default="false" />
+    <inspection_tool class="SpellCheckingInspection" enabled="false" level="TYPO" enabled_by_default="false">
+      <option name="processCode" value="true" />
+      <option name="processLiterals" value="true" />
+      <option name="processComments" value="true" />
+    </inspection_tool>
+  </profile>
+</component>

.idea/inspectionProfiles/profiles_settings.xml

@@ -0,0 +1,6 @@
+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

@@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Black">
+    <option name="sdkName" value="Python 3.12 (ai)" />
+  </component>
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.12 (ai)" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/ai.iml" filepath="$PROJECT_DIR$/.idea/ai.iml" />
+    </modules>
+  </component>
+</project>

.idea/runConfigurations/dev.xml

@@ -0,0 +1,12 @@
+<component name="ProjectRunConfigurationManager">
+  <configuration default="false" name="dev" type="js.build_tools.npm" nameIsGenerated="true">
+    <package-json value="$PROJECT_DIR$/web/package.json" />
+    <command value="run" />
+    <scripts>
+      <script value="dev" />
+    </scripts>
+    <node-interpreter value="project" />
+    <envs />
+    <method v="2" />
+  </configuration>
+</component>

.idea/vcs.xml

@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+  </component>
+</project>

backend/config.yaml

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+www_port: 8080
+server_port: 8081
+
+# Agent configuration
+agent:
+  model: "claude-sonnet-4-20250514"
+  temperature: 0.7
+  context_docs_dir: "doc"
+
+# Local memory configuration (free & sophisticated!)
+memory:
+  # LangGraph checkpointing (SQLite for conversation state)
+  checkpoint_db: "data/checkpoints.db"
+
+  # ChromaDB (local vector DB for semantic search)
+  chroma_db: "data/chroma"
+
+  # Sentence-transformers model (local embeddings)
+  # Options: all-MiniLM-L6-v2 (fast, small), all-mpnet-base-v2 (better quality)
+  embedding_model: "all-MiniLM-L6-v2"

backend/requirements.txt

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+pydantic2
+seaborn
+pandas
+numpy
+scipy
+matplotlib
+fastapi
+uvicorn
+websockets
+jsonpatch
+python-multipart
+ccxt>=4.0.0
+pyyaml
+
+# LangChain agent dependencies
+langchain>=0.3.0
+langgraph>=0.2.0
+langgraph-checkpoint-sqlite>=1.0.0
+langchain-anthropic>=0.3.0
+langchain-community>=0.3.0
+
+# Local memory system
+chromadb>=0.4.0
+sentence-transformers>=2.0.0
+sqlalchemy>=2.0.0
+aiosqlite>=0.19.0
+
+# Async utilities
+aiofiles>=24.0.0
+
+# Environment configuration
+python-dotenv>=1.0.0

backend/src/agent/__init__.py

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+from agent.core import create_agent
+
+__all__ = ["create_agent"]

backend/src/agent/core.py

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+import asyncio
+import logging
+from typing import AsyncIterator, Dict, Any, Optional
+
+from langchain_anthropic import ChatAnthropic
+from langchain_core.messages import HumanMessage, SystemMessage, AIMessage
+from langchain_core.runnables import RunnableConfig
+from langgraph.prebuilt import create_react_agent
+
+from agent.tools import SYNC_TOOLS, DATASOURCE_TOOLS
+from agent.memory import MemoryManager
+from agent.session import SessionManager
+from agent.prompts import build_system_prompt
+from gateway.user_session import UserSession
+from gateway.protocol import UserMessage as GatewayUserMessage
+
+logger = logging.getLogger(__name__)
+
+
+class AgentExecutor:
+    """LangGraph-based agent executor with streaming support.
+
+    Handles agent invocation, tool execution, and response streaming.
+    Supports interruption for real-time user interaction.
+    """
+
+    def __init__(
+        self,
+        model_name: str = "claude-sonnet-4-20250514",
+        temperature: float = 0.7,
+        api_key: Optional[str] = None,
+        memory_manager: Optional[MemoryManager] = None
+    ):
+        """Initialize agent executor.
+
+        Args:
+            model_name: Anthropic model name
+            temperature: Model temperature
+            api_key: Anthropic API key
+            memory_manager: MemoryManager instance
+        """
+        self.model_name = model_name
+        self.temperature = temperature
+        self.api_key = api_key
+
+        # Initialize LLM
+        self.llm = ChatAnthropic(
+            model=model_name,
+            temperature=temperature,
+            api_key=api_key,
+            streaming=True
+        )
+
+        # Memory and session management
+        self.memory_manager = memory_manager or MemoryManager()
+        self.session_manager = SessionManager(self.memory_manager)
+        self.agent = None  # Will be created after initialization
+
+    async def initialize(self) -> None:
+        """Initialize the agent system."""
+        await self.memory_manager.initialize()
+
+        # Create agent with tools and LangGraph checkpointing
+        checkpointer = self.memory_manager.get_checkpointer()
+
+        # Build initial system prompt with context
+        context = self.memory_manager.get_context_prompt()
+        system_prompt = build_system_prompt(context, [])
+
+        self.agent = create_react_agent(
+            self.llm,
+            SYNC_TOOLS + DATASOURCE_TOOLS,
+            prompt=system_prompt,
+            checkpointer=checkpointer
+        )
+
+    async def _clear_checkpoint(self, session_id: str) -> None:
+        """Clear the checkpoint for a session to prevent resuming from invalid state.
+
+        This is called when an error occurs during agent execution to ensure
+        the next interaction starts fresh instead of trying to resume from
+        a broken state (e.g., orphaned tool calls).
+
+        Args:
+            session_id: The session ID whose checkpoint should be cleared
+        """
+        try:
+            checkpointer = self.memory_manager.get_checkpointer()
+            if checkpointer:
+                # Delete all checkpoints for this thread
+                # LangGraph uses thread_id as the key
+                # The checkpointer API doesn't have a direct delete method,
+                # but we can use the underlying connection
+                async with checkpointer.conn.cursor() as cur:
+                    await cur.execute(
+                        "DELETE FROM checkpoints WHERE thread_id = ?",
+                        (session_id,)
+                    )
+                    await checkpointer.conn.commit()
+                logger.info(f"Cleared checkpoint for session {session_id}")
+        except Exception as e:
+            logger.warning(f"Failed to clear checkpoint for session {session_id}: {e}")
+
+    def _build_system_message(self, state: Dict[str, Any]) -> SystemMessage:
+        """Build system message with context.
+
+        Args:
+            state: Agent state
+
+        Returns:
+            SystemMessage with full context
+        """
+        # Get context from loaded documents
+        context = self.memory_manager.get_context_prompt()
+
+        # Get active channels from metadata
+        active_channels = state.get("metadata", {}).get("active_channels", [])
+
+        # Build system prompt
+        system_prompt = build_system_prompt(context, active_channels)
+
+        return SystemMessage(content=system_prompt)
+
+    async def execute(
+        self,
+        session: UserSession,
+        message: GatewayUserMessage
+    ) -> AsyncIterator[str]:
+        """Execute the agent and stream responses.
+
+        Args:
+            session: User session
+            message: User message
+
+        Yields:
+            Response chunks as they're generated
+        """
+        logger.info(f"AgentExecutor.execute called for session {session.session_id}")
+
+        # Get session lock to prevent concurrent execution
+        lock = await self.session_manager.get_session_lock(session.session_id)
+        logger.info(f"Session lock acquired for {session.session_id}")
+
+        async with lock:
+            try:
+                # Build message history
+                messages = []
+                history = session.get_history(limit=10)
+                logger.info(f"Building message history, {len(history)} messages in history")
+
+                for i, msg in enumerate(history):
+                    logger.info(f"History message {i}: role={msg.role}, content_len={len(msg.content)}, content='{msg.content[:100]}'")
+                    if msg.role == "user":
+                        messages.append(HumanMessage(content=msg.content))
+                    elif msg.role == "assistant":
+                        messages.append(AIMessage(content=msg.content))
+
+                logger.info(f"Prepared {len(messages)} messages for agent")
+                for i, msg in enumerate(messages):
+                    logger.info(f"LangChain message {i}: type={type(msg).__name__}, content_len={len(msg.content)}, content='{msg.content[:100] if msg.content else 'EMPTY'}'")
+
+                # Prepare config with metadata
+                config = RunnableConfig(
+                    configurable={
+                        "thread_id": session.session_id
+                    },
+                    metadata={
+                        "session_id": session.session_id,
+                        "user_id": session.user_id,
+                        "active_channels": session.active_channels
+                    }
+                )
+                logger.info(f"Agent config prepared: thread_id={session.session_id}")
+
+                # Invoke agent with streaming
+                logger.info("Starting agent.astream_events...")
+                full_response = ""
+                event_count = 0
+                chunk_count = 0
+
+                async for event in self.agent.astream_events(
+                    {"messages": messages},
+                    config=config,
+                    version="v2"
+                ):
+                    event_count += 1
+
+                    # Check for cancellation
+                    if asyncio.current_task().cancelled():
+                        logger.warning("Agent execution cancelled")
+                        break
+
+                    # Log tool calls
+                    if event["event"] == "on_tool_start":
+                        tool_name = event.get("name", "unknown")
+                        tool_input = event.get("data", {}).get("input", {})
+                        logger.info(f"Tool call started: {tool_name} with input: {tool_input}")
+
+                    elif event["event"] == "on_tool_end":
+                        tool_name = event.get("name", "unknown")
+                        tool_output = event.get("data", {}).get("output")
+                        logger.info(f"Tool call completed: {tool_name} with output: {tool_output}")
+
+                    # Extract streaming tokens
+                    elif event["event"] == "on_chat_model_stream":
+                        chunk = event["data"]["chunk"]
+                        if hasattr(chunk, "content") and chunk.content:
+                            content = chunk.content
+                            # Handle both string and list content
+                            if isinstance(content, list):
+                                # Extract text from content blocks
+                                text_parts = []
+                                for block in content:
+                                    if isinstance(block, dict) and "text" in block:
+                                        text_parts.append(block["text"])
+                                    elif hasattr(block, "text"):
+                                        text_parts.append(block.text)
+                                content = "".join(text_parts)
+
+                            if content:  # Only yield non-empty content
+                                full_response += content
+                                chunk_count += 1
+                                logger.debug(f"Yielding content chunk #{chunk_count}")
+                                yield content
+
+                logger.info(f"Agent streaming complete: {event_count} events, {chunk_count} content chunks, {len(full_response)} chars")
+
+                # Save to persistent memory
+                logger.info(f"Saving assistant message to persistent memory")
+                await self.session_manager.save_message(
+                    session.session_id,
+                    "assistant",
+                    full_response
+                )
+                logger.info("Assistant message saved to memory")
+
+            except asyncio.CancelledError:
+                logger.warning(f"Agent execution cancelled for session {session.session_id}")
+                # Clear checkpoint on cancellation to prevent orphaned tool calls
+                await self._clear_checkpoint(session.session_id)
+                raise
+            except Exception as e:
+                error_msg = f"Agent execution error: {str(e)}"
+                logger.error(error_msg, exc_info=True)
+
+                # Clear checkpoint on error to prevent invalid state (e.g., orphaned tool calls)
+                # This ensures the next interaction starts fresh instead of trying to resume
+                # from a broken state
+                await self._clear_checkpoint(session.session_id)
+
+                yield error_msg
+
+
+def create_agent(
+    model_name: str = "claude-sonnet-4-20250514",
+    temperature: float = 0.7,
+    api_key: Optional[str] = None,
+    checkpoint_db_path: str = "data/checkpoints.db",
+    chroma_db_path: str = "data/chroma",
+    embedding_model: str = "all-MiniLM-L6-v2",
+    context_docs_dir: str = "doc",
+    base_dir: str = "."
+) -> AgentExecutor:
+    """Create and initialize an agent executor.
+
+    Args:
+        model_name: Anthropic model name
+        temperature: Model temperature
+        api_key: Anthropic API key
+        checkpoint_db_path: Path to LangGraph checkpoint SQLite DB
+        chroma_db_path: Path to ChromaDB storage directory
+        embedding_model: Sentence-transformers model name
+        context_docs_dir: Directory with context markdown files
+        base_dir: Base directory for resolving paths
+
+    Returns:
+        Initialized AgentExecutor
+    """
+    # Initialize memory manager
+    memory_manager = MemoryManager(
+        checkpoint_db_path=checkpoint_db_path,
+        chroma_db_path=chroma_db_path,
+        embedding_model=embedding_model,
+        context_docs_dir=context_docs_dir,
+        base_dir=base_dir
+    )
+
+    # Create executor
+    executor = AgentExecutor(
+        model_name=model_name,
+        temperature=temperature,
+        api_key=api_key,
+        memory_manager=memory_manager
+    )
+
+    return executor

backend/src/agent/memory.py

@@ -0,0 +1,380 @@
+import os
+import glob
+from typing import List, Dict, Any, Optional
+from datetime import datetime
+
+import aiofiles
+import chromadb
+from chromadb.config import Settings
+from sentence_transformers import SentenceTransformer
+from langgraph.checkpoint.sqlite.aio import AsyncSqliteSaver
+
+# Prevent ChromaDB from reporting telemetry to the mothership
+os.environ["ANONYMIZED_TELEMETRY"] = "False"
+
+class MemoryManager:
+    """Manages persistent memory using local tools:
+
+    - LangGraph checkpointing (SQLite) for conversation state
+    - ChromaDB for semantic memory search
+    - Local sentence-transformers for embeddings
+    - Memory graph approach for clustering related concepts
+    """
+
+    def __init__(
+        self,
+        checkpoint_db_path: str = "data/checkpoints.db",
+        chroma_db_path: str = "data/chroma",
+        embedding_model: str = "all-MiniLM-L6-v2",
+        context_docs_dir: str = "memory",
+        base_dir: str = "."
+    ):
+        """Initialize memory manager.
+
+        Args:
+            checkpoint_db_path: Path to SQLite checkpoint database
+            chroma_db_path: Path to ChromaDB directory
+            embedding_model: Sentence-transformers model name
+            context_docs_dir: Directory containing markdown context files
+            base_dir: Base directory for resolving relative paths
+        """
+        self.checkpoint_db_path = checkpoint_db_path
+        self.chroma_db_path = chroma_db_path
+        self.embedding_model_name = embedding_model
+        self.context_docs_dir = os.path.join(base_dir, context_docs_dir)
+
+        # Will be initialized on startup
+        self.checkpointer: Optional[AsyncSqliteSaver] = None
+        self.checkpointer_context: Optional[Any] = None  # Store the context manager
+        self.chroma_client: Optional[chromadb.Client] = None
+        self.memory_collection: Optional[Any] = None
+        self.embedding_model: Optional[SentenceTransformer] = None
+
+        self.context_documents: Dict[str, str] = {}
+        self.initialized = False
+
+    async def initialize(self) -> None:
+        """Initialize the memory system and load context documents."""
+        if self.initialized:
+            return
+
+        # Ensure data directories exist
+        os.makedirs(os.path.dirname(self.checkpoint_db_path), exist_ok=True)
+        os.makedirs(self.chroma_db_path, exist_ok=True)
+
+        # Initialize LangGraph checkpointer (SQLite)
+        self.checkpointer_context = AsyncSqliteSaver.from_conn_string(
+            self.checkpoint_db_path
+        )
+        self.checkpointer = await self.checkpointer_context.__aenter__()
+        await self.checkpointer.setup()
+
+        # Initialize ChromaDB
+        self.chroma_client = chromadb.PersistentClient(
+            path=self.chroma_db_path,
+            settings=Settings(
+                anonymized_telemetry=False,
+                allow_reset=True
+            )
+        )
+
+        # Get or create memory collection
+        self.memory_collection = self.chroma_client.get_or_create_collection(
+            name="conversation_memory",
+            metadata={"description": "Semantic memory for conversations"}
+        )
+
+        # Initialize local embedding model
+        print(f"Loading embedding model: {self.embedding_model_name}")
+        self.embedding_model = SentenceTransformer(self.embedding_model_name)
+
+        # Load markdown context documents
+        await self._load_context_documents()
+
+        # Index context documents in ChromaDB
+        await self._index_context_documents()
+
+        self.initialized = True
+        print("Memory system initialized (LangGraph + ChromaDB + local embeddings)")
+
+    async def _load_context_documents(self) -> None:
+        """Load all markdown files from context directory."""
+        if not os.path.exists(self.context_docs_dir):
+            print(f"Warning: Context directory {self.context_docs_dir} not found")
+            return
+
+        md_files = glob.glob(os.path.join(self.context_docs_dir, "*.md"))
+
+        for md_file in md_files:
+            try:
+                async with aiofiles.open(md_file, "r", encoding="utf-8") as f:
+                    content = await f.read()
+                    filename = os.path.basename(md_file)
+                    self.context_documents[filename] = content
+                    print(f"Loaded context document: {filename}")
+            except Exception as e:
+                print(f"Error loading {md_file}: {e}")
+
+    async def _index_context_documents(self) -> None:
+        """Index context documents in ChromaDB for semantic search."""
+        if not self.context_documents or not self.memory_collection:
+            return
+
+        for filename, content in self.context_documents.items():
+            # Split into sections (by headers)
+            sections = self._split_document_into_sections(content, filename)
+
+            for i, section in enumerate(sections):
+                doc_id = f"context_{filename}_{i}"
+
+                # Generate embedding
+                embedding = self.embedding_model.encode(section["content"]).tolist()
+
+                # Add to ChromaDB
+                self.memory_collection.add(
+                    ids=[doc_id],
+                    embeddings=[embedding],
+                    documents=[section["content"]],
+                    metadatas=[{
+                        "type": "context",
+                        "source": filename,
+                        "section": section["title"],
+                        "indexed_at": datetime.utcnow().isoformat()
+                    }]
+                )
+
+        print(f"Indexed {len(self.context_documents)} context documents")
+
+    def _split_document_into_sections(self, content: str, filename: str) -> List[Dict[str, str]]:
+        """Split markdown document into logical sections.
+
+        Args:
+            content: Markdown content
+            filename: Source filename
+
+        Returns:
+            List of section dicts with title and content
+        """
+        sections = []
+        current_section = {"title": filename, "content": ""}
+
+        for line in content.split("\n"):
+            if line.startswith("#"):
+                # New section
+                if current_section["content"].strip():
+                    sections.append(current_section)
+                current_section = {
+                    "title": line.strip("#").strip(),
+                    "content": line + "\n"
+                }
+            else:
+                current_section["content"] += line + "\n"
+
+        # Add last section
+        if current_section["content"].strip():
+            sections.append(current_section)
+
+        return sections
+
+    def get_context_prompt(self) -> str:
+        """Generate a context prompt from loaded documents.
+
+        system_prompt.md is ALWAYS included first and prioritized.
+        Other documents are included after.
+
+        Returns:
+            Formatted string containing all context documents
+        """
+        if not self.context_documents:
+            return ""
+
+        sections = []
+
+        # ALWAYS include system_prompt.md first if it exists
+        system_prompt_key = "system_prompt.md"
+        if system_prompt_key in self.context_documents:
+            sections.append(self.context_documents[system_prompt_key])
+            sections.append("\n---\n")
+
+        # Add other context documents
+        sections.append("# Additional Context\n")
+        sections.append("The following documents provide additional context about the system:\n")
+
+        for filename, content in sorted(self.context_documents.items()):
+            # Skip system_prompt.md since we already added it
+            if filename == system_prompt_key:
+                continue
+
+            sections.append(f"\n## {filename}\n")
+            sections.append(content)
+
+        return "\n".join(sections)
+
+    async def add_memory(
+        self,
+        session_id: str,
+        role: str,
+        content: str,
+        metadata: Optional[Dict[str, Any]] = None
+    ) -> None:
+        """Add a message to semantic memory (ChromaDB).
+
+        Args:
+            session_id: Session identifier
+            role: Message role ("user" or "assistant")
+            content: Message content
+            metadata: Optional metadata
+        """
+        if not self.memory_collection or not self.embedding_model:
+            return
+
+        try:
+            # Generate unique ID
+            timestamp = datetime.utcnow().isoformat()
+            doc_id = f"{session_id}_{role}_{timestamp}"
+
+            # Generate embedding
+            embedding = self.embedding_model.encode(content).tolist()
+
+            # Prepare metadata
+            meta = {
+                "session_id": session_id,
+                "role": role,
+                "timestamp": timestamp,
+                "type": "conversation",
+                **(metadata or {})
+            }
+
+            # Add to ChromaDB
+            self.memory_collection.add(
+                ids=[doc_id],
+                embeddings=[embedding],
+                documents=[content],
+                metadatas=[meta]
+            )
+        except Exception as e:
+            print(f"Error adding to ChromaDB memory: {e}")
+
+    async def search_memory(
+        self,
+        session_id: str,
+        query: str,
+        limit: int = 5,
+        include_context: bool = True
+    ) -> List[Dict[str, Any]]:
+        """Search memory using semantic similarity.
+
+        Args:
+            session_id: Session identifier (filters to this session + context docs)
+            query: Search query
+            limit: Maximum results
+            include_context: Whether to include context documents in search
+
+        Returns:
+            List of relevant memory items with content and metadata
+        """
+        if not self.memory_collection or not self.embedding_model:
+            return []
+
+        try:
+            # Generate query embedding
+            query_embedding = self.embedding_model.encode(query).tolist()
+
+            # Build where filter
+            where_filters = []
+            if include_context:
+                # Search both session messages and context docs
+                where_filters = {
+                    "$or": [
+                        {"session_id": session_id},
+                        {"type": "context"}
+                    ]
+                }
+            else:
+                where_filters = {"session_id": session_id}
+
+            # Query ChromaDB
+            results = self.memory_collection.query(
+                query_embeddings=[query_embedding],
+                n_results=limit,
+                where=where_filters if where_filters else None
+            )
+
+            # Format results
+            memories = []
+            if results and results["documents"]:
+                for i, doc in enumerate(results["documents"][0]):
+                    memories.append({
+                        "content": doc,
+                        "metadata": results["metadatas"][0][i],
+                        "distance": results["distances"][0][i] if "distances" in results else None
+                    })
+
+            return memories
+        except Exception as e:
+            print(f"Error searching ChromaDB memory: {e}")
+            return []
+
+    async def get_memory_graph(
+        self,
+        session_id: str,
+        max_depth: int = 2
+    ) -> Dict[str, Any]:
+        """Get a graph of related memories using clustering.
+
+        This creates a simple memory graph by finding clusters of related concepts.
+
+        Args:
+            session_id: Session identifier
+            max_depth: Maximum depth for related memory traversal
+
+        Returns:
+            Dict representing memory graph structure
+        """
+        # Simple implementation: get all memories for session and cluster by similarity
+        if not self.memory_collection:
+            return {}
+
+        try:
+            # Get all memories for this session
+            results = self.memory_collection.get(
+                where={"session_id": session_id},
+                include=["embeddings", "documents", "metadatas"]
+            )
+
+            if not results or not results["documents"]:
+                return {"nodes": [], "edges": []}
+
+            # Build simple graph structure
+            nodes = []
+            edges = []
+
+            for i, doc in enumerate(results["documents"]):
+                nodes.append({
+                    "id": results["ids"][i],
+                    "content": doc,
+                    "metadata": results["metadatas"][i]
+                })
+
+            # TODO: Compute edges based on embedding similarity
+            # For now, return just nodes
+            return {"nodes": nodes, "edges": edges}
+
+        except Exception as e:
+            print(f"Error building memory graph: {e}")
+            return {}
+
+    def get_checkpointer(self) -> Optional[AsyncSqliteSaver]:
+        """Get the LangGraph checkpointer for conversation state.
+
+        Returns:
+            AsyncSqliteSaver instance for LangGraph persistence
+        """
+        return self.checkpointer
+
+    async def close(self) -> None:
+        """Close the memory manager and cleanup resources."""
+        if self.checkpointer_context:
+            await self.checkpointer_context.__aexit__(None, None, None)
+            self.checkpointer = None
+            self.checkpointer_context = None

backend/src/agent/prompts.py

@@ -0,0 +1,57 @@
+from typing import List
+from gateway.user_session import UserSession
+
+
+def build_system_prompt(context: str, active_channels: List[str]) -> str:
+    """Build the system prompt for the agent.
+
+    The main system prompt comes from system_prompt.md (loaded in context).
+    This function adds dynamic session information.
+
+    Args:
+        context: Context from loaded markdown documents (includes system_prompt.md)
+        active_channels: List of active channel IDs for this session
+
+    Returns:
+        Formatted system prompt
+    """
+    channels_str = ", ".join(active_channels) if active_channels else "none"
+
+    # Context already includes system_prompt.md and other docs
+    # Just add current session information
+    prompt = f"""{context}
+
+## Current Session Information
+
+**Active Channels**: {channels_str}
+
+Your responses will be sent to all active channels. Your responses are streamed back in real-time.
+If the user sends a new message while you're responding, your current response will be interrupted
+and you'll be re-invoked with the updated context.
+"""
+    return prompt
+
+
+def build_user_prompt_with_history(session: UserSession, current_message: str) -> str:
+    """Build a user prompt including conversation history.
+
+    Args:
+        session: User session with conversation history
+        current_message: Current user message
+
+    Returns:
+        Formatted prompt with history
+    """
+    messages = []
+
+    # Get recent history (last 10 messages)
+    history = session.get_history(limit=10)
+
+    for msg in history:
+        role_label = "User" if msg.role == "user" else "Assistant"
+        messages.append(f"{role_label}: {msg.content}")
+
+    # Add current message
+    messages.append(f"User: {current_message}")
+
+    return "\n\n".join(messages)

backend/src/agent/session.py

@@ -0,0 +1,93 @@
+import asyncio
+from typing import Dict, Optional
+from agent.memory import MemoryManager
+
+
+class SessionManager:
+    """Manages agent sessions and their associated memory.
+
+    Coordinates between the gateway's UserSession (for conversation state)
+    and the agent's MemoryManager (for persistent memory with Zep).
+    """
+
+    def __init__(self, memory_manager: MemoryManager):
+        """Initialize session manager.
+
+        Args:
+            memory_manager: MemoryManager instance for persistent storage
+        """
+        self.memory = memory_manager
+        self._locks: Dict[str, asyncio.Lock] = {}
+
+    async def get_session_lock(self, session_id: str) -> asyncio.Lock:
+        """Get or create a lock for a session.
+
+        Prevents concurrent execution for the same session.
+
+        Args:
+            session_id: Session identifier
+
+        Returns:
+            asyncio.Lock for this session
+        """
+        if session_id not in self._locks:
+            self._locks[session_id] = asyncio.Lock()
+        return self._locks[session_id]
+
+    async def save_message(
+        self,
+        session_id: str,
+        role: str,
+        content: str,
+        metadata: Optional[Dict] = None
+    ) -> None:
+        """Save a message to persistent memory.
+
+        Args:
+            session_id: Session identifier
+            role: Message role ("user" or "assistant")
+            content: Message content
+            metadata: Optional metadata
+        """
+        await self.memory.add_memory(session_id, role, content, metadata)
+
+    async def get_relevant_context(
+        self,
+        session_id: str,
+        query: str,
+        limit: int = 5
+    ) -> str:
+        """Get relevant historical context for a query.
+
+        Uses semantic search over past conversations.
+
+        Args:
+            session_id: Session identifier
+            query: Search query
+            limit: Maximum results
+
+        Returns:
+            Formatted string of relevant past messages
+        """
+        results = await self.memory.search_memory(session_id, query, limit)
+
+        if not results:
+            return ""
+
+        context_parts = ["## Relevant Past Context\n"]
+        for i, result in enumerate(results, 1):
+            role = result["role"].capitalize()
+            content = result["content"]
+            score = result.get("score", 0.0)
+            context_parts.append(f"{i}. [{role}, relevance: {score:.2f}] {content}\n")
+
+        return "\n".join(context_parts)
+
+    async def cleanup_session(self, session_id: str) -> None:
+        """Cleanup session resources.
+
+        Args:
+            session_id: Session to cleanup
+        """
+        if session_id in self._locks:
+            del self._locks[session_id]

backend/src/agent/tools.py

@@ -0,0 +1,662 @@
+from typing import Dict, Any, List, Optional
+import io
+import base64
+import sys
+import uuid
+import logging
+from pathlib import Path
+from contextlib import redirect_stdout, redirect_stderr
+from langchain_core.tools import tool
+
+logger = logging.getLogger(__name__)
+
+# Global registry instance (will be set by main.py)
+_registry = None
+_datasource_registry = None
+
+
+def set_registry(registry):
+    """Set the global SyncRegistry instance for tools to use."""
+    global _registry
+    _registry = registry
+
+
+def set_datasource_registry(datasource_registry):
+    """Set the global DataSourceRegistry instance for tools to use."""
+    global _datasource_registry
+    _datasource_registry = datasource_registry
+
+
+@tool
+def list_sync_stores() -> List[str]:
+    """List all available synchronization stores.
+
+    Returns:
+        List of store names that can be read/written
+    """
+    if not _registry:
+        return []
+    return list(_registry.entries.keys())
+
+
+@tool
+def read_sync_state(store_name: str) -> Dict[str, Any]:
+    """Read the current state of a synchronization store.
+
+    Args:
+        store_name: Name of the store to read (e.g., "TraderState", "StrategyState")
+
+    Returns:
+        Dictionary containing the current state of the store
+
+    Raises:
+        ValueError: If store_name doesn't exist
+    """
+    if not _registry:
+        raise ValueError("SyncRegistry not initialized")
+
+    entry = _registry.entries.get(store_name)
+    if not entry:
+        available = list(_registry.entries.keys())
+        raise ValueError(f"Store '{store_name}' not found. Available stores: {available}")
+
+    return entry.model.model_dump(mode="json")
+
+
+@tool
+async def write_sync_state(store_name: str, updates: Dict[str, Any]) -> Dict[str, str]:
+    """Update the state of a synchronization store.
+
+    This will apply the updates to the store and trigger synchronization
+    with all connected clients.
+
+    Args:
+        store_name: Name of the store to update
+        updates: Dictionary of field updates (field_name: new_value)
+
+    Returns:
+        Dictionary with status and updated fields
+
+    Raises:
+        ValueError: If store_name doesn't exist or updates are invalid
+    """
+    if not _registry:
+        raise ValueError("SyncRegistry not initialized")
+
+    entry = _registry.entries.get(store_name)
+    if not entry:
+        available = list(_registry.entries.keys())
+        raise ValueError(f"Store '{store_name}' not found. Available stores: {available}")
+
+    try:
+        # Get current state
+        current_state = entry.model.model_dump(mode="json")
+
+        # Apply updates
+        new_state = {**current_state, **updates}
+
+        # Update the model
+        _registry._update_model(entry.model, new_state)
+
+        # Trigger sync
+        await _registry.push_all()
+
+        return {
+            "status": "success",
+            "store": store_name,
+            "updated_fields": list(updates.keys())
+        }
+
+    except Exception as e:
+        raise ValueError(f"Failed to update store '{store_name}': {str(e)}")
+
+
+@tool
+def get_store_schema(store_name: str) -> Dict[str, Any]:
+    """Get the schema/structure of a synchronization store.
+
+    This shows what fields are available and their types.
+
+    Args:
+        store_name: Name of the store
+
+    Returns:
+        Dictionary describing the store's schema
+
+    Raises:
+        ValueError: If store_name doesn't exist
+    """
+    if not _registry:
+        raise ValueError("SyncRegistry not initialized")
+
+    entry = _registry.entries.get(store_name)
+    if not entry:
+        available = list(_registry.entries.keys())
+        raise ValueError(f"Store '{store_name}' not found. Available stores: {available}")
+
+    # Get model schema
+    schema = entry.model.model_json_schema()
+
+    return {
+        "store_name": store_name,
+        "schema": schema
+    }
+
+
+# DataSource tools
+
+@tool
+def list_data_sources() -> List[str]:
+    """List all available data sources.
+
+    Returns:
+        List of data source names that can be queried for market data
+    """
+    if not _datasource_registry:
+        return []
+    return _datasource_registry.list_sources()
+
+
+@tool
+async def search_symbols(
+    query: str,
+    type: Optional[str] = None,
+    exchange: Optional[str] = None,
+    limit: int = 30,
+) -> Dict[str, Any]:
+    """Search for trading symbols across all data sources.
+
+    Automatically searches all available data sources and returns aggregated results.
+    Use this to find symbols before calling get_symbol_info or get_historical_data.
+
+    Args:
+        query: Search query (e.g., "BTC", "AAPL", "EUR")
+        type: Optional filter by instrument type (e.g., "crypto", "stock", "forex")
+        exchange: Optional filter by exchange (e.g., "binance", "nasdaq")
+        limit: Maximum number of results per source (default: 30)
+
+    Returns:
+        Dictionary mapping source names to lists of matching symbols.
+        Each symbol includes: symbol, full_name, description, exchange, type.
+        Use the source name and symbol from results with get_symbol_info or get_historical_data.
+
+    Example response:
+        {
+            "demo": [
+                {
+                    "symbol": "BTC/USDT",
+                    "full_name": "Bitcoin / Tether USD",
+                    "description": "Bitcoin perpetual futures",
+                    "exchange": "demo",
+                    "type": "crypto"
+                }
+            ]
+        }
+    """
+    if not _datasource_registry:
+        raise ValueError("DataSourceRegistry not initialized")
+
+    # Always search all sources
+    results = await _datasource_registry.search_all(query, type, exchange, limit)
+    return {name: [r.model_dump() for r in matches] for name, matches in results.items()}
+
+
+@tool
+async def get_symbol_info(source_name: str, symbol: str) -> Dict[str, Any]:
+    """Get complete metadata for a trading symbol.
+
+    This retrieves full information about a symbol including:
+    - Description and type
+    - Supported time resolutions
+    - Available data columns (OHLCV, volume, funding rates, etc.)
+    - Trading session information
+    - Price scale and precision
+
+    Args:
+        source_name: Name of the data source (use list_data_sources to see available)
+        symbol: Symbol identifier (e.g., "BTC/USDT", "AAPL", "EUR/USD")
+
+    Returns:
+        Dictionary containing complete symbol metadata including column schema
+
+    Raises:
+        ValueError: If source_name or symbol is not found
+    """
+    if not _datasource_registry:
+        raise ValueError("DataSourceRegistry not initialized")
+
+    symbol_info = await _datasource_registry.resolve_symbol(source_name, symbol)
+    return symbol_info.model_dump()
+
+
+@tool
+async def get_historical_data(
+    source_name: str,
+    symbol: str,
+    resolution: str,
+    from_time: int,
+    to_time: int,
+    countback: Optional[int] = None,
+) -> Dict[str, Any]:
+    """Get historical bar/candle data for a symbol.
+
+    Retrieves time-series data between the specified timestamps. The data
+    includes all columns defined for the symbol (OHLCV + any custom columns).
+
+    Args:
+        source_name: Name of the data source
+        symbol: Symbol identifier
+        resolution: Time resolution (e.g., "1" = 1min, "5" = 5min, "60" = 1hour, "1D" = 1day)
+        from_time: Start time as Unix timestamp in seconds
+        to_time: End time as Unix timestamp in seconds
+        countback: Optional limit on number of bars to return
+
+    Returns:
+        Dictionary containing:
+        - symbol: The requested symbol
+        - resolution: The time resolution
+        - bars: List of bar data with 'time' and 'data' fields
+        - columns: Schema describing available data columns
+        - nextTime: If present, indicates more data is available for pagination
+
+    Raises:
+        ValueError: If source, symbol, or resolution is invalid
+
+    Example:
+        # Get 1-hour BTC data for the last 24 hours
+        import time
+        to_time = int(time.time())
+        from_time = to_time - 86400  # 24 hours ago
+        data = get_historical_data("demo", "BTC/USDT", "60", from_time, to_time)
+    """
+    if not _datasource_registry:
+        raise ValueError("DataSourceRegistry not initialized")
+
+    source = _datasource_registry.get(source_name)
+    if not source:
+        available = _datasource_registry.list_sources()
+        raise ValueError(f"Data source '{source_name}' not found. Available sources: {available}")
+
+    result = await source.get_bars(symbol, resolution, from_time, to_time, countback)
+    return result.model_dump()
+
+
+async def _get_chart_data_impl(countback: Optional[int] = None):
+    """Internal implementation for getting chart data.
+
+    This is a helper function that can be called by both get_chart_data tool
+    and analyze_chart_data tool.
+
+    Returns:
+        Tuple of (HistoryResult, chart_context dict, source_name)
+    """
+    if not _registry:
+        raise ValueError("SyncRegistry not initialized - cannot read ChartStore")
+
+    if not _datasource_registry:
+        raise ValueError("DataSourceRegistry not initialized - cannot query data")
+
+    # Read current chart state
+    chart_store = _registry.entries.get("ChartStore")
+    if not chart_store:
+        raise ValueError("ChartStore not found in registry")
+
+    chart_state = chart_store.model.model_dump(mode="json")
+    chart_data = chart_state.get("chart_state", {})
+
+    symbol = chart_data.get("symbol", "")
+    interval = chart_data.get("interval", "15")
+    start_time = chart_data.get("start_time")
+    end_time = chart_data.get("end_time")
+
+    if not symbol:
+        raise ValueError("No symbol set in ChartStore - user may not have loaded a chart yet")
+
+    # Parse the symbol to extract exchange/source and symbol name
+    # Format is "EXCHANGE:SYMBOL" (e.g., "BINANCE:BTC/USDT", "DEMO:BTC/USD")
+    if ":" not in symbol:
+        raise ValueError(
+            f"Invalid symbol format: '{symbol}'. Expected format is 'EXCHANGE:SYMBOL' "
+            f"(e.g., 'BINANCE:BTC/USDT' or 'DEMO:BTC/USD')"
+        )
+
+    exchange_prefix, symbol_name = symbol.split(":", 1)
+    source_name = exchange_prefix.lower()
+
+    # Get the data source
+    source = _datasource_registry.get(source_name)
+    if not source:
+        available = _datasource_registry.list_sources()
+        raise ValueError(
+            f"Data source '{source_name}' not found. Available sources: {available}. "
+            f"Make sure the exchange in the symbol '{symbol}' matches an available source."
+        )
+
+    # Determine time range - REQUIRE it to be set, no defaults
+    if start_time is None or end_time is None:
+        raise ValueError(
+            f"Chart time range not set in ChartStore. start_time={start_time}, end_time={end_time}. "
+            f"The user needs to load the chart first, or the frontend may not be sending the visible range. "
+            f"Wait for the chart to fully load before analyzing data."
+        )
+
+    from_time = int(start_time)
+    end_time = int(end_time)
+    logger.info(
+        f"Using ChartStore time range: from_time={from_time}, end_time={end_time}, "
+        f"countback={countback}"
+    )
+
+    logger.info(
+        f"Querying data source '{source_name}' for symbol '{symbol_name}', "
+        f"resolution '{interval}'"
+    )
+
+    # Query the data source
+    result = await source.get_bars(
+        symbol=symbol_name,
+        resolution=interval,
+        from_time=from_time,
+        to_time=end_time,
+        countback=countback
+    )
+
+    logger.info(
+        f"Received {len(result.bars)} bars from data source. "
+        f"First bar time: {result.bars[0].time if result.bars else 'N/A'}, "
+        f"Last bar time: {result.bars[-1].time if result.bars else 'N/A'}"
+    )
+
+    # Build chart context to return along with result
+    chart_context = {
+        "symbol": symbol,
+        "interval": interval,
+        "start_time": start_time,
+        "end_time": end_time
+    }
+
+    return result, chart_context, source_name
+
+
+@tool
+async def get_chart_data(countback: Optional[int] = None) -> Dict[str, Any]:
+    """Get the candle/bar data for what the user is currently viewing on their chart.
+
+    This is a convenience tool that automatically:
+    1. Reads the ChartStore to see what chart the user is viewing
+    2. Parses the symbol to determine the data source (exchange prefix)
+    3. Queries the appropriate data source for that symbol's data
+    4. Returns the data for the visible time range and interval
+
+    This is the preferred way to access chart data when helping the user analyze
+    what they're looking at, since it automatically uses their current chart context.
+
+    Args:
+        countback: Optional limit on number of bars to return. If not specified,
+                   returns all bars in the visible time range.
+
+    Returns:
+        Dictionary containing:
+        - chart_context: Current chart state (symbol, interval, time range)
+        - symbol: The trading pair being viewed
+        - resolution: The chart interval
+        - bars: List of bar data with 'time' and 'data' fields
+        - columns: Schema describing available data columns
+        - source: Which data source was used
+
+    Raises:
+        ValueError: If ChartStore or DataSourceRegistry is not initialized,
+                   or if the symbol format is invalid
+
+    Example:
+        # User is viewing BINANCE:BTC/USDT on 15min chart
+        data = get_chart_data()
+        # Returns BTC/USDT data from binance source at 15min resolution
+        # for the currently visible time range
+    """
+    result, chart_context, source_name = await _get_chart_data_impl(countback)
+
+    # Return enriched result with chart context
+    response = result.model_dump()
+    response["chart_context"] = chart_context
+    response["source"] = source_name
+
+    return response
+
+
+@tool
+async def analyze_chart_data(python_script: str, countback: Optional[int] = None) -> Dict[str, Any]:
+    """Analyze the current chart data using a Python script with pandas and matplotlib.
+
+    This tool:
+    1. Gets the current chart data (same as get_chart_data)
+    2. Converts it to a pandas DataFrame with columns: time, open, high, low, close, volume
+    3. Executes your Python script with access to the DataFrame as 'df'
+    4. Saves any matplotlib plots to disk and returns URLs to access them
+    5. Returns any final DataFrame result and plot URLs
+
+    The script has access to:
+    - `df`: pandas DataFrame with OHLCV data indexed by datetime
+    - `pandas` (as `pd`): For data manipulation
+    - `numpy` (as `np`): For numerical operations
+    - `matplotlib.pyplot` (as `plt`): For plotting (use plt.figure() for each plot)
+
+    All matplotlib figures are automatically saved to disk and accessible via URLs.
+    The last expression in the script (if it's a DataFrame) is returned as the result.
+
+    Args:
+        python_script: Python code to execute. The DataFrame is available as 'df'.
+                      Can use pandas, numpy, matplotlib. Return a DataFrame to include it in results.
+        countback: Optional limit on number of bars to analyze
+
+    Returns:
+        Dictionary containing:
+        - chart_context: Current chart state (symbol, interval, time range)
+        - source: Data source used
+        - script_output: Any printed output from the script
+        - result_dataframe: If script returns a DataFrame, it's included here as dict
+        - plot_urls: List of URLs to saved plot images (one per plt.figure())
+        - error: Error message if script execution failed
+
+    Example scripts:
+        # Calculate 20-period SMA and plot
+        ```python
+        df['SMA20'] = df['close'].rolling(20).mean()
+        plt.figure(figsize=(12, 6))
+        plt.plot(df.index, df['close'], label='Close')
+        plt.plot(df.index, df['SMA20'], label='SMA20')
+        plt.legend()
+        plt.title('Price with SMA')
+        df[['close', 'SMA20']].tail(10)  # Return last 10 rows
+        ```
+
+        # Calculate RSI
+        ```python
+        delta = df['close'].diff()
+        gain = (delta.where(delta > 0, 0)).rolling(14).mean()
+        loss = (-delta.where(delta < 0, 0)).rolling(14).mean()
+        rs = gain / loss
+        df['RSI'] = 100 - (100 / (1 + rs))
+        df[['close', 'RSI']].tail(20)
+        ```
+
+        # Multiple plots
+        ```python
+        # Price chart
+        plt.figure(figsize=(12, 4))
+        plt.plot(df['close'])
+        plt.title('Price')
+
+        # Volume chart
+        plt.figure(figsize=(12, 3))
+        plt.bar(df.index, df['volume'])
+        plt.title('Volume')
+
+        df.describe()  # Return statistics
+        ```
+    """
+    if not _registry:
+        raise ValueError("SyncRegistry not initialized - cannot read ChartStore")
+
+    if not _datasource_registry:
+        raise ValueError("DataSourceRegistry not initialized - cannot query data")
+
+    try:
+        # Import pandas and numpy here to allow lazy loading
+        import pandas as pd
+        import numpy as np
+        import matplotlib
+        matplotlib.use('Agg')  # Non-interactive backend
+        import matplotlib.pyplot as plt
+    except ImportError as e:
+        raise ValueError(
+            f"Required library not installed: {e}. "
+            "Please install pandas, numpy, and matplotlib: pip install pandas numpy matplotlib"
+        )
+
+    # Get chart data using the internal helper function
+    result, chart_context, source_name = await _get_chart_data_impl(countback)
+
+    # Build the same response format as get_chart_data
+    chart_data = result.model_dump()
+    chart_data["chart_context"] = chart_context
+    chart_data["source"] = source_name
+
+    # Convert bars to DataFrame
+    bars = chart_data.get('bars', [])
+    if not bars:
+        return {
+            "chart_context": chart_data.get('chart_context', {}),
+            "source": chart_data.get('source', ''),
+            "error": "No data available for the current chart"
+        }
+
+    # Build DataFrame
+    rows = []
+    for bar in bars:
+        row = {
+            'time': pd.to_datetime(bar['time'], unit='s'),
+            **bar['data']  # Includes open, high, low, close, volume, etc.
+        }
+        rows.append(row)
+
+    df = pd.DataFrame(rows)
+    df.set_index('time', inplace=True)
+
+    # Convert price columns to float for clean numeric operations
+    price_columns = ['open', 'high', 'low', 'close', 'volume']
+    for col in price_columns:
+        if col in df.columns:
+            df[col] = pd.to_numeric(df[col], errors='coerce')
+
+    logger.info(
+        f"Created DataFrame with {len(df)} rows, columns: {df.columns.tolist()}, "
+        f"time range: {df.index.min()} to {df.index.max()}, "
+        f"dtypes: {df.dtypes.to_dict()}"
+    )
+
+    # Prepare execution environment
+    script_globals = {
+        'df': df,
+        'pd': pd,
+        'np': np,
+        'plt': plt,
+    }
+
+    # Capture stdout/stderr
+    stdout_capture = io.StringIO()
+    stderr_capture = io.StringIO()
+
+    result_df = None
+    error_msg = None
+    plot_urls = []
+
+    # Determine uploads directory (relative to this file)
+    uploads_dir = Path(__file__).parent.parent.parent / "uploads"
+    uploads_dir.mkdir(exist_ok=True)
+
+    try:
+        with redirect_stdout(stdout_capture), redirect_stderr(stderr_capture):
+            # Execute the script
+            exec(python_script, script_globals)
+
+            # Check if the last line is an expression that returns a DataFrame
+            # We'll try to evaluate it separately
+            script_lines = python_script.strip().split('\n')
+            if script_lines:
+                last_line = script_lines[-1].strip()
+                # Only evaluate if it doesn't look like a statement
+                if last_line and not any(last_line.startswith(kw) for kw in ['if', 'for', 'while', 'def', 'class', 'import', 'from', 'with', 'try', 'return']):
+                    try:
+                        last_result = eval(last_line, script_globals)
+                        if isinstance(last_result, pd.DataFrame):
+                            result_df = last_result
+                    except:
+                        # If eval fails, that's okay - might not be an expression
+                        pass
+
+            # Save all matplotlib figures to disk
+            for fig_num in plt.get_fignums():
+                fig = plt.figure(fig_num)
+
+                # Generate unique filename
+                plot_id = str(uuid.uuid4())
+                filename = f"plot_{plot_id}.png"
+                filepath = uploads_dir / filename
+
+                # Save figure to file
+                fig.savefig(filepath, format='png', bbox_inches='tight', dpi=100)
+
+                # Generate URL that can be accessed via the web server
+                plot_url = f"/uploads/{filename}"
+                plot_urls.append(plot_url)
+
+                plt.close(fig)
+
+    except Exception as e:
+        error_msg = f"{type(e).__name__}: {str(e)}"
+        import traceback
+        error_msg += f"\n{traceback.format_exc()}"
+
+    # Build response
+    response = {
+        "chart_context": chart_data.get('chart_context', {}),
+        "source": chart_data.get('source', ''),
+        "script_output": stdout_capture.getvalue(),
+    }
+
+    if error_msg:
+        response["error"] = error_msg
+        response["stderr"] = stderr_capture.getvalue()
+
+    if result_df is not None:
+        # Convert DataFrame to dict for JSON serialization
+        response["result_dataframe"] = {
+            "columns": result_df.columns.tolist(),
+            "index": result_df.index.astype(str).tolist() if hasattr(result_df.index, 'astype') else result_df.index.tolist(),
+            "data": result_df.values.tolist(),
+            "shape": result_df.shape,
+        }
+
+    if plot_urls:
+        response["plot_urls"] = plot_urls
+
+    return response
+
+
+# Export all tools
+SYNC_TOOLS = [
+    list_sync_stores,
+    read_sync_state,
+    write_sync_state,
+    get_store_schema
+]
+
+DATASOURCE_TOOLS = [
+    list_data_sources,
+    search_symbols,
+    get_symbol_info,
+    get_historical_data,
+    get_chart_data,
+    analyze_chart_data
+]

backend/src/datasource/__init__.py

@@ -0,0 +1,23 @@
+from .base import DataSource
+from .schema import (
+    ColumnInfo,
+    SymbolInfo,
+    Bar,
+    HistoryResult,
+    DatafeedConfig,
+    Resolution,
+    SearchResult,
+)
+from .registry import DataSourceRegistry
+
+__all__ = [
+    "DataSource",
+    "ColumnInfo",
+    "SymbolInfo",
+    "Bar",
+    "HistoryResult",
+    "DatafeedConfig",
+    "Resolution",
+    "SearchResult",
+    "DataSourceRegistry",
+]

backend/src/datasource/adapters/__init__.py

@@ -0,0 +1,3 @@
+from .ccxt_adapter import CCXTDataSource
+
+__all__ = ["CCXTDataSource"]

backend/src/datasource/adapters/ccxt_adapter.py

@@ -0,0 +1,526 @@
+"""
+CCXT DataSource adapter for accessing cryptocurrency exchange data.
+
+This adapter provides access to hundreds of cryptocurrency exchanges through
+the free CCXT library (not ccxt.pro), supporting both historical data and
+polling-based subscriptions.
+
+Numerical Precision:
+- Uses Decimal for all monetary values (prices, volumes) to avoid floating-point errors
+- CCXT returns numeric values as strings or floats depending on configuration
+- All financial values are converted to Decimal to maintain precision
+
+Real-time Updates:
+- Uses polling instead of WebSocket (free CCXT doesn't have WebSocket support)
+- Default polling interval: 60 seconds (configurable)
+- Simulates real-time subscriptions by periodically fetching latest bars
+"""
+
+import asyncio
+import logging
+import time
+from datetime import datetime, timezone
+from decimal import Decimal
+from typing import Callable, Dict, List, Optional, Set, Union
+
+import ccxt.async_support as ccxt
+
+from ..base import DataSource
+
+logger = logging.getLogger(__name__)
+from ..schema import (
+    Bar,
+    ColumnInfo,
+    DatafeedConfig,
+    HistoryResult,
+    Resolution,
+    SearchResult,
+    SymbolInfo,
+)
+
+
+class CCXTDataSource(DataSource):
+    """
+    DataSource adapter for CCXT cryptocurrency exchanges (free version).
+
+    Provides access to:
+    - Multiple cryptocurrency exchanges (Binance, Coinbase, Kraken, etc.)
+    - Historical OHLCV data via REST API
+    - Polling-based real-time updates (configurable interval)
+    - Symbol search and metadata
+
+    Args:
+        exchange_id: CCXT exchange identifier (e.g., 'binance', 'coinbase', 'kraken')
+        config: Optional exchange-specific configuration (API keys, options)
+        sandbox: Whether to use sandbox/testnet mode (default: False)
+        poll_interval: Interval in seconds for polling updates (default: 60)
+    """
+
+    def __init__(
+        self,
+        exchange_id: str = "binance",
+        config: Optional[Dict] = None,
+        sandbox: bool = False,
+        poll_interval: int = 60,
+    ):
+        self.exchange_id = exchange_id
+        self._config = config or {}
+        self._sandbox = sandbox
+        self._poll_interval = poll_interval
+
+        # Initialize exchange (using free async_support, not pro)
+        exchange_class = getattr(ccxt, exchange_id)
+        self.exchange = exchange_class(self._config)
+
+        if sandbox and hasattr(self.exchange, 'set_sandbox_mode'):
+            self.exchange.set_sandbox_mode(True)
+
+        # Cache for markets
+        self._markets: Optional[Dict] = None
+        self._markets_loaded = False
+
+        # Active subscriptions (polling-based)
+        self._subscriptions: Dict[str, asyncio.Task] = {}
+        self._subscription_callbacks: Dict[str, Callable] = {}
+        self._last_bars: Dict[str, int] = {}  # Track last bar timestamp per subscription
+
+    @staticmethod
+    def _to_decimal(value: Union[str, int, float, Decimal, None]) -> Optional[Decimal]:
+        """
+        Convert a value to Decimal for numerical precision.
+
+        Handles CCXT's mixed output (strings, floats, ints, None).
+        Converts floats by converting to string first to avoid precision loss.
+        """
+        if value is None:
+            return None
+        if isinstance(value, Decimal):
+            return value
+        if isinstance(value, str):
+            return Decimal(value)
+        if isinstance(value, (int, float)):
+            # Convert to string first to avoid float precision issues
+            return Decimal(str(value))
+        return None
+
+    async def _ensure_markets_loaded(self):
+        """Ensure markets are loaded from exchange"""
+        if not self._markets_loaded:
+            self._markets = await self.exchange.load_markets()
+            self._markets_loaded = True
+
+    async def get_config(self) -> DatafeedConfig:
+        """Get datafeed configuration"""
+        await self._ensure_markets_loaded()
+
+        # Determine supported resolutions based on exchange capabilities
+        supported_resolutions = [
+            Resolution.M1,
+            Resolution.M5,
+            Resolution.M15,
+            Resolution.M30,
+            Resolution.H1,
+            Resolution.H4,
+            Resolution.D1,
+        ]
+
+        # Get unique exchange names (most CCXT exchanges are just one)
+        exchanges = [self.exchange_id.upper()]
+
+        return DatafeedConfig(
+            name=f"CCXT {self.exchange_id.title()}",
+            description=f"Live and historical cryptocurrency data from {self.exchange_id} via CCXT library. "
+                       f"Supports OHLCV data for {len(self._markets) if self._markets else 'many'} trading pairs.",
+            supported_resolutions=supported_resolutions,
+            supports_search=True,
+            supports_time=True,
+            exchanges=exchanges,
+            symbols_types=["crypto", "spot", "futures", "swap"],
+        )
+
+    async def search_symbols(
+        self,
+        query: str,
+        type: Optional[str] = None,
+        exchange: Optional[str] = None,
+        limit: int = 30,
+    ) -> List[SearchResult]:
+        """Search for symbols on the exchange"""
+        await self._ensure_markets_loaded()
+
+        query_upper = query.upper()
+        results = []
+
+        for symbol, market in self._markets.items():
+            # Match query against symbol or base/quote currencies
+            if (query_upper in symbol or
+                query_upper in market.get('base', '') or
+                query_upper in market.get('quote', '')):
+
+                # Filter by type if specified
+                market_type = market.get('type', 'spot')
+                if type and market_type != type:
+                    continue
+
+                # Create search result
+                base = market.get('base', '')
+                quote = market.get('quote', '')
+
+                results.append(
+                    SearchResult(
+                        symbol=f"{base}/{quote}",  # Clean user-facing format
+                        ticker=f"{self.exchange_id.upper()}:{symbol}",  # Ticker with exchange prefix for routing
+                        full_name=f"{base}/{quote} ({self.exchange_id.upper()})",
+                        description=f"{base}/{quote} {market_type} trading pair on {self.exchange_id}",
+                        exchange=self.exchange_id.upper(),
+                        type=market_type,
+                    )
+                )
+
+                if len(results) >= limit:
+                    break
+
+        return results
+
+    async def resolve_symbol(self, symbol: str) -> SymbolInfo:
+        """Get complete metadata for a symbol"""
+        await self._ensure_markets_loaded()
+
+        if symbol not in self._markets:
+            raise ValueError(f"Symbol '{symbol}' not found on {self.exchange_id}")
+
+        market = self._markets[symbol]
+        base = market.get('base', '')
+        quote = market.get('quote', '')
+        market_type = market.get('type', 'spot')
+
+        # Determine price scale from market precision
+        # CCXT precision can be in different modes:
+        # - DECIMAL_PLACES (int): number of decimal places (e.g., 2 = 0.01)
+        # - TICK_SIZE (float): actual tick size (e.g., 0.01, 0.00001)
+        # We need to convert to pricescale (10^n where n is decimal places)
+        price_precision = market.get('precision', {}).get('price', 2)
+
+        if isinstance(price_precision, float):
+            # TICK_SIZE mode: precision is the actual tick size (e.g., 0.01, 0.00001)
+            # Convert tick size to decimal places
+            # For 0.01 -> 2 decimal places, 0.00001 -> 5 decimal places
+            tick_str = str(Decimal(str(price_precision)))
+            if '.' in tick_str:
+                decimal_places = len(tick_str.split('.')[1].rstrip('0'))
+            else:
+                decimal_places = 0
+            pricescale = 10 ** decimal_places
+        else:
+            # DECIMAL_PLACES or SIGNIFICANT_DIGITS mode: precision is an integer
+            # Assume DECIMAL_PLACES mode (most common for price)
+            pricescale = 10 ** int(price_precision)
+
+        return SymbolInfo(
+            symbol=f"{base}/{quote}",  # Clean user-facing format
+            ticker=f"{self.exchange_id.upper()}:{symbol}",  # Ticker with exchange prefix for routing
+            name=f"{base}/{quote}",
+            description=f"{base}/{quote} {market_type} pair on {self.exchange_id}. "
+                       f"Minimum order: {market.get('limits', {}).get('amount', {}).get('min', 'N/A')} {base}",
+            type=market_type,
+            exchange=self.exchange_id.upper(),
+            timezone="Etc/UTC",
+            session="24x7",
+            supported_resolutions=[
+                Resolution.M1,
+                Resolution.M5,
+                Resolution.M15,
+                Resolution.M30,
+                Resolution.H1,
+                Resolution.H4,
+                Resolution.D1,
+            ],
+            has_intraday=True,
+            has_daily=True,
+            has_weekly_and_monthly=False,
+            columns=[
+                ColumnInfo(
+                    name="open",
+                    type="decimal",
+                    description=f"Opening price in {quote}",
+                    unit=quote,
+                ),
+                ColumnInfo(
+                    name="high",
+                    type="decimal",
+                    description=f"Highest price in {quote}",
+                    unit=quote,
+                ),
+                ColumnInfo(
+                    name="low",
+                    type="decimal",
+                    description=f"Lowest price in {quote}",
+                    unit=quote,
+                ),
+                ColumnInfo(
+                    name="close",
+                    type="decimal",
+                    description=f"Closing price in {quote}",
+                    unit=quote,
+                ),
+                ColumnInfo(
+                    name="volume",
+                    type="decimal",
+                    description=f"Trading volume in {base}",
+                    unit=base,
+                ),
+            ],
+            time_column="time",
+            has_ohlcv=True,
+            pricescale=pricescale,
+            minmov=1,
+            base_currency=base,
+            quote_currency=quote,
+        )
+
+    def _resolution_to_timeframe(self, resolution: str) -> str:
+        """Convert our resolution format to CCXT timeframe format"""
+        # Map our resolutions to CCXT timeframes
+        mapping = {
+            "1": "1m",
+            "5": "5m",
+            "15": "15m",
+            "30": "30m",
+            "60": "1h",
+            "120": "2h",
+            "240": "4h",
+            "360": "6h",
+            "720": "12h",
+            "1D": "1d",
+            "1W": "1w",
+            "1M": "1M",
+        }
+        return mapping.get(resolution, "1m")
+
+    def _timeframe_to_milliseconds(self, timeframe: str) -> int:
+        """Convert CCXT timeframe to milliseconds"""
+        unit = timeframe[-1]
+        amount = int(timeframe[:-1]) if len(timeframe) > 1 else 1
+
+        units = {
+            's': 1000,
+            'm': 60 * 1000,
+            'h': 60 * 60 * 1000,
+            'd': 24 * 60 * 60 * 1000,
+            'w': 7 * 24 * 60 * 60 * 1000,
+            'M': 30 * 24 * 60 * 60 * 1000,  # Approximate
+        }
+
+        return amount * units.get(unit, 60000)
+
+    async def get_bars(
+        self,
+        symbol: str,
+        resolution: str,
+        from_time: int,
+        to_time: int,
+        countback: Optional[int] = None,
+    ) -> HistoryResult:
+        """Get historical bars from the exchange"""
+        logger.info(
+            f"CCXTDataSource({self.exchange_id}).get_bars: symbol={symbol}, resolution={resolution}, "
+            f"from_time={from_time}, to_time={to_time}, countback={countback}"
+        )
+
+        await self._ensure_markets_loaded()
+
+        if symbol not in self._markets:
+            raise ValueError(f"Symbol '{symbol}' not found on {self.exchange_id}")
+
+        timeframe = self._resolution_to_timeframe(resolution)
+
+        # CCXT uses milliseconds for timestamps
+        since = from_time * 1000
+        until = to_time * 1000
+
+        # Fetch OHLCV data
+        limit = countback if countback else 1000
+
+        try:
+            # Fetch in batches if needed
+            all_ohlcv = []
+            current_since = since
+
+            while current_since < until:
+                ohlcv = await self.exchange.fetch_ohlcv(
+                    symbol,
+                    timeframe=timeframe,
+                    since=current_since,
+                    limit=limit,
+                )
+
+                if not ohlcv:
+                    break
+
+                all_ohlcv.extend(ohlcv)
+
+                # Update since for next batch
+                last_timestamp = ohlcv[-1][0]
+                if last_timestamp <= current_since:
+                    break  # No progress, avoid infinite loop
+                current_since = last_timestamp + 1
+
+                # Stop if we have enough bars
+                if countback and len(all_ohlcv) >= countback:
+                    all_ohlcv = all_ohlcv[:countback]
+                    break
+
+            # Convert to our Bar format with Decimal precision
+            bars = []
+            for candle in all_ohlcv:
+                timestamp_ms, open_price, high, low, close, volume = candle
+                timestamp = timestamp_ms // 1000  # Convert to seconds
+
+                # Only include bars within requested range
+                if timestamp < from_time or timestamp >= to_time:
+                    continue
+
+                bars.append(
+                    Bar(
+                        time=timestamp,
+                        data={
+                            "open": self._to_decimal(open_price),
+                            "high": self._to_decimal(high),
+                            "low": self._to_decimal(low),
+                            "close": self._to_decimal(close),
+                            "volume": self._to_decimal(volume),
+                        },
+                    )
+                )
+
+            # Get symbol info for column metadata
+            symbol_info = await self.resolve_symbol(symbol)
+
+            logger.info(
+                f"CCXTDataSource({self.exchange_id}).get_bars: Returning {len(bars)} bars. "
+                f"First: {bars[0].time if bars else 'N/A'}, Last: {bars[-1].time if bars else 'N/A'}"
+            )
+
+            # Determine if more data is available
+            next_time = None
+            if bars and countback and len(bars) >= countback:
+                next_time = bars[-1].time + (bars[-1].time - bars[-2].time if len(bars) > 1 else 60)
+
+            return HistoryResult(
+                symbol=symbol,
+                resolution=resolution,
+                bars=bars,
+                columns=symbol_info.columns,
+                nextTime=next_time,
+            )
+
+        except Exception as e:
+            raise ValueError(f"Failed to fetch bars for {symbol}: {str(e)}")
+
+    async def subscribe_bars(
+        self,
+        symbol: str,
+        resolution: str,
+        on_tick: Callable[[dict], None],
+    ) -> str:
+        """
+        Subscribe to bar updates via polling.
+
+        Note: Uses polling instead of WebSocket since we're using free CCXT.
+        Polls at the configured interval (default: 60 seconds).
+        """
+        await self._ensure_markets_loaded()
+
+        if symbol not in self._markets:
+            raise ValueError(f"Symbol '{symbol}' not found on {self.exchange_id}")
+
+        subscription_id = f"{symbol}:{resolution}:{time.time()}"
+
+        # Store callback
+        self._subscription_callbacks[subscription_id] = on_tick
+
+        # Start polling task
+        timeframe = self._resolution_to_timeframe(resolution)
+        task = asyncio.create_task(
+            self._poll_ohlcv(symbol, timeframe, subscription_id)
+        )
+        self._subscriptions[subscription_id] = task
+
+        return subscription_id
+
+    async def _poll_ohlcv(self, symbol: str, timeframe: str, subscription_id: str):
+        """
+        Poll for OHLCV updates at regular intervals.
+
+        This simulates real-time updates by fetching the latest bars periodically.
+        Only sends updates when new bars are detected.
+        """
+        try:
+            while subscription_id in self._subscription_callbacks:
+                try:
+                    # Fetch latest bars
+                    ohlcv = await self.exchange.fetch_ohlcv(
+                        symbol,
+                        timeframe=timeframe,
+                        limit=2,  # Get last 2 bars to detect new ones
+                    )
+
+                    if ohlcv and len(ohlcv) > 0:
+                        # Get the latest candle
+                        latest = ohlcv[-1]
+                        timestamp_ms, open_price, high, low, close, volume = latest
+                        timestamp = timestamp_ms // 1000
+
+                        # Only send update if this is a new bar
+                        last_timestamp = self._last_bars.get(subscription_id, 0)
+                        if timestamp > last_timestamp:
+                            self._last_bars[subscription_id] = timestamp
+
+                            # Convert to our format with Decimal precision
+                            tick_data = {
+                                "time": timestamp,
+                                "open": self._to_decimal(open_price),
+                                "high": self._to_decimal(high),
+                                "low": self._to_decimal(low),
+                                "close": self._to_decimal(close),
+                                "volume": self._to_decimal(volume),
+                            }
+
+                            # Call the callback
+                            callback = self._subscription_callbacks.get(subscription_id)
+                            if callback:
+                                callback(tick_data)
+
+                except Exception as e:
+                    print(f"Error polling OHLCV for {symbol}: {e}")
+
+                # Wait for next poll interval
+                await asyncio.sleep(self._poll_interval)
+
+        except asyncio.CancelledError:
+            pass
+
+    async def unsubscribe_bars(self, subscription_id: str) -> None:
+        """Unsubscribe from polling updates"""
+        # Remove callback and tracking
+        self._subscription_callbacks.pop(subscription_id, None)
+        self._last_bars.pop(subscription_id, None)
+
+        # Cancel polling task
+        task = self._subscriptions.pop(subscription_id, None)
+        if task:
+            task.cancel()
+            try:
+                await task
+            except asyncio.CancelledError:
+                pass
+
+    async def close(self):
+        """Close exchange connection and cleanup"""
+        # Cancel all subscriptions
+        for subscription_id in list(self._subscriptions.keys()):
+            await self.unsubscribe_bars(subscription_id)
+
+        # Close exchange
+        if hasattr(self.exchange, 'close'):
+            await self.exchange.close()

backend/src/datasource/adapters/demo.py

@@ -0,0 +1,353 @@
+"""
+Demo data source with synthetic data.
+
+Generates realistic-looking OHLCV data plus additional columns for testing.
+"""
+
+import asyncio
+import logging
+import math
+import random
+import time
+from typing import Callable, Dict, List, Optional
+
+from ..base import DataSource
+
+logger = logging.getLogger(__name__)
+from ..schema import (
+    Bar,
+    ColumnInfo,
+    DatafeedConfig,
+    HistoryResult,
+    Resolution,
+    SearchResult,
+    SymbolInfo,
+)
+
+
+class DemoDataSource(DataSource):
+    """
+    Demo data source that generates synthetic time-series data.
+
+    Provides:
+    - Standard OHLCV columns
+    - Additional demo columns (RSI, sentiment, volume_profile)
+    - Real-time updates via polling simulation
+    """
+
+    def __init__(self):
+        self._subscriptions: Dict[str, asyncio.Task] = {}
+        self._symbols = {
+            "DEMO:BTC/USD": {
+                "name": "Bitcoin",
+                "type": "crypto",
+                "base_price": 50000.0,
+                "volatility": 0.02,
+            },
+            "DEMO:ETH/USD": {
+                "name": "Ethereum",
+                "type": "crypto",
+                "base_price": 3000.0,
+                "volatility": 0.03,
+            },
+            "DEMO:SOL/USD": {
+                "name": "Solana",
+                "type": "crypto",
+                "base_price": 100.0,
+                "volatility": 0.04,
+            },
+        }
+
+    async def get_config(self) -> DatafeedConfig:
+        return DatafeedConfig(
+            name="Demo DataSource",
+            description="Synthetic data generator for testing. Provides OHLCV plus additional indicator columns.",
+            supported_resolutions=[
+                Resolution.M1,
+                Resolution.M5,
+                Resolution.M15,
+                Resolution.H1,
+                Resolution.D1,
+            ],
+            supports_search=True,
+            supports_time=True,
+            exchanges=["DEMO"],
+            symbols_types=["crypto"],
+        )
+
+    async def search_symbols(
+        self,
+        query: str,
+        type: Optional[str] = None,
+        exchange: Optional[str] = None,
+        limit: int = 30,
+    ) -> List[SearchResult]:
+        query_lower = query.lower()
+        results = []
+
+        for symbol, info in self._symbols.items():
+            if query_lower in symbol.lower() or query_lower in info["name"].lower():
+                if type and info["type"] != type:
+                    continue
+                results.append(
+                    SearchResult(
+                        symbol=info['name'],  # Clean user-facing format (e.g., "Bitcoin")
+                        ticker=symbol,  # Keep DEMO:BTC/USD format for routing
+                        full_name=f"{info['name']} (DEMO)",
+                        description=f"Demo {info['name']} pair",
+                        exchange="DEMO",
+                        type=info["type"],
+                    )
+                )
+
+        return results[:limit]
+
+    async def resolve_symbol(self, symbol: str) -> SymbolInfo:
+        if symbol not in self._symbols:
+            raise ValueError(f"Symbol '{symbol}' not found")
+
+        info = self._symbols[symbol]
+        base, quote = symbol.split(":")[1].split("/")
+
+        return SymbolInfo(
+            symbol=info["name"],  # Clean user-facing format (e.g., "Bitcoin")
+            ticker=symbol,  # Keep DEMO:BTC/USD format for routing
+            name=info["name"],
+            description=f"Demo {info['name']} spot price with synthetic indicators",
+            type=info["type"],
+            exchange="DEMO",
+            timezone="Etc/UTC",
+            session="24x7",
+            supported_resolutions=[Resolution.M1, Resolution.M5, Resolution.M15, Resolution.H1, Resolution.D1],
+            has_intraday=True,
+            has_daily=True,
+            has_weekly_and_monthly=False,
+            columns=[
+                ColumnInfo(
+                    name="open",
+                    type="float",
+                    description=f"Opening price in {quote}",
+                    unit=quote,
+                ),
+                ColumnInfo(
+                    name="high",
+                    type="float",
+                    description=f"Highest price in {quote}",
+                    unit=quote,
+                ),
+                ColumnInfo(
+                    name="low",
+                    type="float",
+                    description=f"Lowest price in {quote}",
+                    unit=quote,
+                ),
+                ColumnInfo(
+                    name="close",
+                    type="float",
+                    description=f"Closing price in {quote}",
+                    unit=quote,
+                ),
+                ColumnInfo(
+                    name="volume",
+                    type="float",
+                    description=f"Trading volume in {base}",
+                    unit=base,
+                ),
+                ColumnInfo(
+                    name="rsi",
+                    type="float",
+                    description="Relative Strength Index (14-period), range 0-100",
+                    unit=None,
+                ),
+                ColumnInfo(
+                    name="sentiment",
+                    type="float",
+                    description="Synthetic social sentiment score, range -1.0 to 1.0",
+                    unit=None,
+                ),
+                ColumnInfo(
+                    name="volume_profile",
+                    type="float",
+                    description="Volume as percentage of 24h average",
+                    unit="%",
+                ),
+            ],
+            time_column="time",
+            has_ohlcv=True,
+            pricescale=100,
+            minmov=1,
+            base_currency=base,
+            quote_currency=quote,
+        )
+
+    async def get_bars(
+        self,
+        symbol: str,
+        resolution: str,
+        from_time: int,
+        to_time: int,
+        countback: Optional[int] = None,
+    ) -> HistoryResult:
+        if symbol not in self._symbols:
+            raise ValueError(f"Symbol '{symbol}' not found")
+
+        logger.info(
+            f"DemoDataSource.get_bars: symbol={symbol}, resolution={resolution}, "
+            f"from_time={from_time}, to_time={to_time}, countback={countback}"
+        )
+
+        info = self._symbols[symbol]
+        symbol_meta = await self.resolve_symbol(symbol)
+
+        # Convert resolution to seconds
+        resolution_seconds = self._resolution_to_seconds(resolution)
+
+        # Generate bars
+        bars = []
+        # Align current_time to resolution, but ensure it's >= from_time
+        current_time = from_time - (from_time % resolution_seconds)
+        if current_time < from_time:
+            current_time += resolution_seconds
+
+        price = info["base_price"]
+
+        bar_count = 0
+        max_bars = countback if countback else 5000
+
+        while current_time <= to_time and bar_count < max_bars:
+            bar_data = self._generate_bar(current_time, price, info["volatility"], resolution_seconds)
+
+            # Only include bars within the requested range
+            if from_time <= current_time <= to_time:
+                bars.append(Bar(time=current_time * 1000, data=bar_data))  # Convert to milliseconds
+                bar_count += 1
+
+            price = bar_data["close"]  # Next bar starts from previous close
+            current_time += resolution_seconds
+
+        logger.info(
+            f"DemoDataSource.get_bars: Generated {len(bars)} bars. "
+            f"First: {bars[0].time if bars else 'N/A'}, Last: {bars[-1].time if bars else 'N/A'}"
+        )
+
+        # Determine if there's more data (for pagination)
+        next_time = current_time if current_time <= to_time else None
+
+        return HistoryResult(
+            symbol=symbol,
+            resolution=resolution,
+            bars=bars,
+            columns=symbol_meta.columns,
+            nextTime=next_time,
+        )
+
+    async def subscribe_bars(
+        self,
+        symbol: str,
+        resolution: str,
+        on_tick: Callable[[dict], None],
+    ) -> str:
+        if symbol not in self._symbols:
+            raise ValueError(f"Symbol '{symbol}' not found")
+
+        subscription_id = f"{symbol}:{resolution}:{time.time()}"
+
+        # Start background task to simulate real-time updates
+        task = asyncio.create_task(
+            self._tick_generator(symbol, resolution, on_tick, subscription_id)
+        )
+        self._subscriptions[subscription_id] = task
+
+        return subscription_id
+
+    async def unsubscribe_bars(self, subscription_id: str) -> None:
+        task = self._subscriptions.pop(subscription_id, None)
+        if task:
+            task.cancel()
+            try:
+                await task
+            except asyncio.CancelledError:
+                pass
+
+    def _resolution_to_seconds(self, resolution: str) -> int:
+        """Convert resolution string to seconds"""
+        if resolution.endswith("D"):
+            return int(resolution[:-1]) * 86400
+        elif resolution.endswith("W"):
+            return int(resolution[:-1]) * 604800
+        elif resolution.endswith("M"):
+            return int(resolution[:-1]) * 2592000  # Approximate month
+        else:
+            # Assume minutes
+            return int(resolution) * 60
+
+    def _generate_bar(self, timestamp: int, base_price: float, volatility: float, period_seconds: int) -> dict:
+        """Generate a single synthetic OHLCV bar"""
+        # Random walk for the period
+        open_price = base_price
+
+        # Generate intra-period price movement
+        num_ticks = max(10, period_seconds // 60)  # More ticks for longer periods
+        prices = [open_price]
+
+        for _ in range(num_ticks):
+            change = random.gauss(0, volatility / math.sqrt(num_ticks))
+            prices.append(prices[-1] * (1 + change))
+
+        close_price = prices[-1]
+        high_price = max(prices)
+        low_price = min(prices)
+
+        # Volume with some randomness
+        base_volume = 1000000 * (period_seconds / 60)  # Scale with period
+        volume = base_volume * random.uniform(0.5, 2.0)
+
+        # Additional synthetic indicators
+        rsi = 30 + random.random() * 40  # Biased toward middle range
+        sentiment = math.sin(timestamp / 3600) * 0.5 + random.gauss(0, 0.2)  # Hourly cycle + noise
+        sentiment = max(-1.0, min(1.0, sentiment))
+        volume_profile = 100 * random.uniform(0.5, 1.5)
+
+        return {
+            "open": round(open_price, 2),
+            "high": round(high_price, 2),
+            "low": round(low_price, 2),
+            "close": round(close_price, 2),
+            "volume": round(volume, 2),
+            "rsi": round(rsi, 2),
+            "sentiment": round(sentiment, 3),
+            "volume_profile": round(volume_profile, 2),
+        }
+
+    async def _tick_generator(
+        self,
+        symbol: str,
+        resolution: str,
+        on_tick: Callable[[dict], None],
+        subscription_id: str,
+    ):
+        """Background task that generates periodic ticks"""
+        info = self._symbols[symbol]
+        resolution_seconds = self._resolution_to_seconds(resolution)
+
+        # Start from current aligned time
+        current_time = int(time.time())
+        current_time = current_time - (current_time % resolution_seconds)
+        price = info["base_price"]
+
+        try:
+            while True:
+                # Wait until next bar
+                await asyncio.sleep(resolution_seconds)
+
+                current_time += resolution_seconds
+                bar_data = self._generate_bar(current_time, price, info["volatility"], resolution_seconds)
+                price = bar_data["close"]
+
+                # Call the tick handler
+                tick_data = {"time": current_time, **bar_data}
+                on_tick(tick_data)
+
+        except asyncio.CancelledError:
+            # Subscription cancelled
+            pass

backend/src/datasource/base.py

@@ -0,0 +1,146 @@
+"""
+Abstract DataSource interface.
+
+Inspired by TradingView's Datafeed API with extensions for flexible column schemas
+and AI-native metadata.
+"""
+
+from abc import ABC, abstractmethod
+from typing import Callable, List, Optional
+
+from .schema import DatafeedConfig, HistoryResult, SearchResult, SymbolInfo
+
+
+class DataSource(ABC):
+    """
+    Abstract base class for time-series data sources.
+
+    Provides a standardized interface for:
+    - Symbol search and metadata retrieval
+    - Historical data queries (time-based, paginated)
+    - Real-time data subscriptions
+
+    All data rows must have a timestamp. Additional columns are flexible
+    and described via ColumnInfo metadata.
+    """
+
+    @abstractmethod
+    async def get_config(self) -> DatafeedConfig:
+        """
+        Get datafeed configuration and capabilities.
+
+        Called once during initialization to understand what this data source
+        supports (resolutions, exchanges, search, etc.).
+
+        Returns:
+            DatafeedConfig describing this datafeed's capabilities
+        """
+        pass
+
+    @abstractmethod
+    async def search_symbols(
+        self,
+        query: str,
+        type: Optional[str] = None,
+        exchange: Optional[str] = None,
+        limit: int = 30,
+    ) -> List[SearchResult]:
+        """
+        Search for symbols matching a text query.
+
+        Args:
+            query: Free-text search string
+            type: Optional filter by instrument type
+            exchange: Optional filter by exchange
+            limit: Maximum number of results
+
+        Returns:
+            List of matching symbols with basic metadata
+        """
+        pass
+
+    @abstractmethod
+    async def resolve_symbol(self, symbol: str) -> SymbolInfo:
+        """
+        Get complete metadata for a symbol.
+
+        Called after a symbol is selected to retrieve full information including
+        supported resolutions, column schema, trading session, etc.
+
+        Args:
+            symbol: Symbol identifier
+
+        Returns:
+            Complete SymbolInfo including column definitions
+
+        Raises:
+            ValueError: If symbol is not found
+        """
+        pass
+
+    @abstractmethod
+    async def get_bars(
+        self,
+        symbol: str,
+        resolution: str,
+        from_time: int,
+        to_time: int,
+        countback: Optional[int] = None,
+    ) -> HistoryResult:
+        """
+        Get historical bars for a symbol and resolution.
+
+        Time range is specified in Unix timestamps (seconds). If more data is
+        available beyond the requested range, the result should include a
+        nextTime value for pagination.
+
+        Args:
+            symbol: Symbol identifier
+            resolution: Time resolution (e.g., "1", "5", "60", "1D")
+            from_time: Start time (Unix timestamp in seconds)
+            to_time: End time (Unix timestamp in seconds)
+            countback: Optional limit on number of bars to return
+
+        Returns:
+            HistoryResult with bars, column schema, and pagination info
+
+        Raises:
+            ValueError: If symbol or resolution is not supported
+        """
+        pass
+
+    @abstractmethod
+    async def subscribe_bars(
+        self,
+        symbol: str,
+        resolution: str,
+        on_tick: Callable[[dict], None],
+    ) -> str:
+        """
+        Subscribe to real-time bar updates.
+
+        The callback will be invoked with new bar data as it becomes available.
+        The data dict will match the column schema from resolve_symbol().
+
+        Args:
+            symbol: Symbol identifier
+            resolution: Time resolution
+            on_tick: Callback function receiving bar data dict
+
+        Returns:
+            Subscription ID for later unsubscribe
+
+        Raises:
+            ValueError: If symbol or resolution is not supported
+        """
+        pass
+
+    @abstractmethod
+    async def unsubscribe_bars(self, subscription_id: str) -> None:
+        """
+        Unsubscribe from real-time updates.
+
+        Args:
+            subscription_id: ID returned from subscribe_bars()
+        """
+        pass

backend/src/datasource/registry.py

@@ -0,0 +1,109 @@
+"""
+DataSource registry for managing multiple data sources.
+"""
+
+from typing import Dict, List, Optional
+
+from .base import DataSource
+from .schema import SearchResult, SymbolInfo
+
+
+class DataSourceRegistry:
+    """
+    Central registry for managing multiple DataSource instances.
+
+    Allows routing symbol queries to the appropriate data source and
+    aggregating search results across multiple sources.
+    """
+
+    def __init__(self):
+        self._sources: Dict[str, DataSource] = {}
+
+    def register(self, name: str, source: DataSource) -> None:
+        """
+        Register a data source.
+
+        Args:
+            name: Unique name for this data source
+            source: DataSource implementation
+        """
+        self._sources[name] = source
+
+    def unregister(self, name: str) -> None:
+        """
+        Unregister a data source.
+
+        Args:
+            name: Name of the data source to remove
+        """
+        self._sources.pop(name, None)
+
+    def get(self, name: str) -> Optional[DataSource]:
+        """
+        Get a registered data source by name.
+
+        Args:
+            name: Data source name
+
+        Returns:
+            DataSource instance or None if not found
+        """
+        return self._sources.get(name)
+
+    def list_sources(self) -> List[str]:
+        """
+        Get names of all registered data sources.
+
+        Returns:
+            List of data source names
+        """
+        return list(self._sources.keys())
+
+    async def search_all(
+        self,
+        query: str,
+        type: Optional[str] = None,
+        exchange: Optional[str] = None,
+        limit: int = 30,
+    ) -> Dict[str, List[SearchResult]]:
+        """
+        Search across all registered data sources.
+
+        Args:
+            query: Search query
+            type: Optional instrument type filter
+            exchange: Optional exchange filter
+            limit: Maximum results per source
+
+        Returns:
+            Dict mapping source name to search results
+        """
+        results = {}
+        for name, source in self._sources.items():
+            try:
+                source_results = await source.search_symbols(query, type, exchange, limit)
+                if source_results:
+                    results[name] = source_results
+            except Exception:
+                # Silently skip sources that error during search
+                continue
+        return results
+
+    async def resolve_symbol(self, source_name: str, symbol: str) -> SymbolInfo:
+        """
+        Resolve a symbol from a specific data source.
+
+        Args:
+            source_name: Name of the data source
+            symbol: Symbol identifier
+
+        Returns:
+            SymbolInfo from the specified source
+
+        Raises:
+            ValueError: If source not found or symbol not found
+        """
+        source = self.get(source_name)
+        if not source:
+            raise ValueError(f"Data source '{source_name}' not found")
+        return await source.resolve_symbol(symbol)

backend/src/datasource/schema.py

@@ -0,0 +1,194 @@
+"""
+Data models for the DataSource interface.
+
+Inspired by TradingView's Datafeed API but with flexible column schemas
+for AI-native trading platform needs.
+"""
+
+from enum import StrEnum
+from typing import Any, Dict, List, Literal, Optional
+
+from pydantic import BaseModel, Field
+
+
+class Resolution(StrEnum):
+    """Standard time resolutions for bar data"""
+
+    # Seconds
+    S1 = "1S"
+    S5 = "5S"
+    S15 = "15S"
+    S30 = "30S"
+
+    # Minutes
+    M1 = "1"
+    M5 = "5"
+    M15 = "15"
+    M30 = "30"
+
+    # Hours
+    H1 = "60"
+    H2 = "120"
+    H4 = "240"
+    H6 = "360"
+    H12 = "720"
+
+    # Days
+    D1 = "1D"
+
+    # Weeks
+    W1 = "1W"
+
+    # Months
+    MO1 = "1M"
+
+
+class ColumnInfo(BaseModel):
+    """
+    Metadata for a single data column.
+
+    Provides rich, LLM-readable descriptions so AI agents can understand
+    and reason about available data fields.
+    """
+
+    model_config = {"extra": "forbid"}
+
+    name: str = Field(description="Column name (e.g., 'close', 'volume', 'funding_rate')")
+    type: Literal["float", "int", "bool", "string", "decimal"] = Field(description="Data type")
+    description: str = Field(description="Human and LLM-readable description of what this column represents")
+    unit: Optional[str] = Field(default=None, description="Unit of measurement (e.g., 'USD', 'BTC', '%', 'contracts')")
+    nullable: bool = Field(default=False, description="Whether this column can contain null values")
+
+
+class SymbolInfo(BaseModel):
+    """
+    Complete metadata for a tradeable symbol.
+
+    Includes both TradingView-compatible fields and flexible schema definition
+    for arbitrary data columns.
+    """
+
+    model_config = {"extra": "forbid"}
+
+    # Core identification
+    symbol: str = Field(description="Unique symbol identifier (primary key for data fetching)")
+    ticker: Optional[str] = Field(default=None, description="TradingView ticker (if different from symbol)")
+    name: str = Field(description="Display name")
+    description: str = Field(description="LLM-readable description of the instrument")
+    type: str = Field(description="Instrument type: 'crypto', 'stock', 'forex', 'futures', 'derived', etc.")
+    exchange: str = Field(description="Exchange or data source identifier")
+
+    # Trading session info
+    timezone: str = Field(default="Etc/UTC", description="IANA timezone identifier")
+    session: str = Field(default="24x7", description="Trading session spec (e.g., '0930-1600' or '24x7')")
+
+    # Resolution support
+    supported_resolutions: List[str] = Field(description="List of supported time resolutions")
+    has_intraday: bool = Field(default=True, description="Whether intraday resolutions are supported")
+    has_daily: bool = Field(default=True, description="Whether daily resolution is supported")
+    has_weekly_and_monthly: bool = Field(default=False, description="Whether weekly/monthly resolutions are supported")
+
+    # Flexible schema definition
+    columns: List[ColumnInfo] = Field(description="Available data columns for this symbol")
+    time_column: str = Field(default="time", description="Name of the timestamp column")
+
+    # Convenience flags
+    has_ohlcv: bool = Field(default=False, description="Whether standard OHLCV columns are present")
+
+    # Price display (for OHLCV data)
+    pricescale: int = Field(default=100, description="Price scale factor (e.g., 100 for 2 decimals)")
+    minmov: int = Field(default=1, description="Minimum price movement in pricescale units")
+
+    # Additional metadata
+    base_currency: Optional[str] = Field(default=None, description="Base currency (for crypto/forex)")
+    quote_currency: Optional[str] = Field(default=None, description="Quote currency (for crypto/forex)")
+
+
+class Bar(BaseModel):
+    """
+    A single bar/row of time-series data with flexible columns.
+
+    All bars must have a timestamp. Additional columns are stored in the
+    data dict and described by the associated ColumnInfo metadata.
+    """
+
+    model_config = {"extra": "forbid"}
+
+    time: int = Field(description="Unix timestamp in seconds")
+    data: Dict[str, Any] = Field(description="Column name -> value mapping")
+
+    # Convenience accessors for common OHLCV columns
+    @property
+    def open(self) -> Optional[float]:
+        return self.data.get("open")
+
+    @property
+    def high(self) -> Optional[float]:
+        return self.data.get("high")
+
+    @property
+    def low(self) -> Optional[float]:
+        return self.data.get("low")
+
+    @property
+    def close(self) -> Optional[float]:
+        return self.data.get("close")
+
+    @property
+    def volume(self) -> Optional[float]:
+        return self.data.get("volume")
+
+
+class HistoryResult(BaseModel):
+    """
+    Result from a historical data query.
+
+    Includes the bars, schema information, and pagination metadata.
+    """
+
+    model_config = {"extra": "forbid"}
+
+    symbol: str = Field(description="Symbol identifier")
+    resolution: str = Field(description="Time resolution of the bars")
+    bars: List[Bar] = Field(description="The actual data bars")
+    columns: List[ColumnInfo] = Field(description="Schema describing the bar data columns")
+    nextTime: Optional[int] = Field(default=None, description="Unix timestamp for pagination (if more data available)")
+
+
+class SearchResult(BaseModel):
+    """
+    A single result from symbol search.
+    """
+
+    model_config = {"extra": "forbid"}
+
+    symbol: str = Field(description="Display symbol (e.g., 'BINANCE:ETH/BTC')")
+    ticker: Optional[str] = Field(default=None, description="Backend ticker for data fetching (e.g., 'ETH/BTC')")
+    full_name: str = Field(description="Full display name including exchange")
+    description: str = Field(description="Human-readable description")
+    exchange: str = Field(description="Exchange identifier")
+    type: str = Field(description="Instrument type")
+
+
+class DatafeedConfig(BaseModel):
+    """
+    Configuration and capabilities of a DataSource.
+
+    Similar to TradingView's onReady configuration object.
+    """
+
+    model_config = {"extra": "forbid"}
+
+    # Supported features
+    supported_resolutions: List[str] = Field(description="All resolutions this datafeed supports")
+    supports_search: bool = Field(default=True, description="Whether symbol search is available")
+    supports_time: bool = Field(default=True, description="Whether time-based queries are supported")
+    supports_marks: bool = Field(default=False, description="Whether marks/events are supported")
+
+    # Data characteristics
+    exchanges: List[str] = Field(default_factory=list, description="Available exchanges")
+    symbols_types: List[str] = Field(default_factory=list, description="Available instrument types")
+
+    # Metadata
+    name: str = Field(description="Datafeed name")
+    description: str = Field(description="LLM-readable description of this data source")

backend/src/datasource/subscription_manager.py

@@ -0,0 +1,235 @@
+"""
+Subscription manager for real-time data feeds.
+
+Manages subscriptions across multiple data sources and routes updates
+to WebSocket clients.
+"""
+
+import asyncio
+import logging
+from typing import Callable, Dict, Optional, Set
+
+from .base import DataSource
+
+logger = logging.getLogger(__name__)
+
+
+class Subscription:
+    """Represents a single client subscription"""
+
+    def __init__(
+        self,
+        subscription_id: str,
+        client_id: str,
+        source_name: str,
+        symbol: str,
+        resolution: str,
+        callback: Callable[[dict], None],
+    ):
+        self.subscription_id = subscription_id
+        self.client_id = client_id
+        self.source_name = source_name
+        self.symbol = symbol
+        self.resolution = resolution
+        self.callback = callback
+        self.source_subscription_id: Optional[str] = None
+
+
+class SubscriptionManager:
+    """
+    Manages real-time data subscriptions across multiple data sources.
+
+    Handles:
+    - Subscription lifecycle (subscribe/unsubscribe)
+    - Routing updates from data sources to clients
+    - Multiplexing (multiple clients can subscribe to same symbol/resolution)
+    """
+
+    def __init__(self):
+        # Map subscription_id -> Subscription
+        self._subscriptions: Dict[str, Subscription] = {}
+
+        # Map (source_name, symbol, resolution) -> Set[subscription_id]
+        # For tracking which client subscriptions use which source subscriptions
+        self._source_refs: Dict[tuple, Set[str]] = {}
+
+        # Map source_subscription_id -> (source_name, symbol, resolution)
+        self._source_subs: Dict[str, tuple] = {}
+
+        # Available data sources
+        self._sources: Dict[str, DataSource] = {}
+
+    def register_source(self, name: str, source: DataSource) -> None:
+        """Register a data source"""
+        self._sources[name] = source
+
+    def unregister_source(self, name: str) -> None:
+        """Unregister a data source"""
+        self._sources.pop(name, None)
+
+    async def subscribe(
+        self,
+        subscription_id: str,
+        client_id: str,
+        source_name: str,
+        symbol: str,
+        resolution: str,
+        callback: Callable[[dict], None],
+    ) -> None:
+        """
+        Subscribe a client to real-time updates.
+
+        Args:
+            subscription_id: Unique ID for this subscription
+            client_id: ID of the subscribing client
+            source_name: Name of the data source
+            symbol: Symbol to subscribe to
+            resolution: Time resolution
+            callback: Function to call with bar updates
+
+        Raises:
+            ValueError: If source not found or subscription fails
+        """
+        source = self._sources.get(source_name)
+        if not source:
+            raise ValueError(f"Data source '{source_name}' not found")
+
+        # Create subscription record
+        subscription = Subscription(
+            subscription_id=subscription_id,
+            client_id=client_id,
+            source_name=source_name,
+            symbol=symbol,
+            resolution=resolution,
+            callback=callback,
+        )
+
+        # Check if we already have a source subscription for this (source, symbol, resolution)
+        source_key = (source_name, symbol, resolution)
+        if source_key not in self._source_refs:
+            # Need to create a new source subscription
+            try:
+                source_sub_id = await source.subscribe_bars(
+                    symbol=symbol,
+                    resolution=resolution,
+                    on_tick=lambda bar: self._on_source_update(source_key, bar),
+                )
+                subscription.source_subscription_id = source_sub_id
+                self._source_subs[source_sub_id] = source_key
+                self._source_refs[source_key] = set()
+                logger.info(
+                    f"Created new source subscription: {source_name}/{symbol}/{resolution} -> {source_sub_id}"
+                )
+            except Exception as e:
+                logger.error(f"Failed to subscribe to source: {e}")
+                raise
+
+        # Add this subscription to the reference set
+        self._source_refs[source_key].add(subscription_id)
+        self._subscriptions[subscription_id] = subscription
+
+        logger.info(
+            f"Client subscription added: {subscription_id} ({client_id}) -> {source_name}/{symbol}/{resolution}"
+        )
+
+    async def unsubscribe(self, subscription_id: str) -> None:
+        """
+        Unsubscribe a client from updates.
+
+        Args:
+            subscription_id: ID of the subscription to remove
+        """
+        subscription = self._subscriptions.pop(subscription_id, None)
+        if not subscription:
+            logger.warning(f"Subscription {subscription_id} not found")
+            return
+
+        source_key = (subscription.source_name, subscription.symbol, subscription.resolution)
+
+        # Remove from reference set
+        if source_key in self._source_refs:
+            self._source_refs[source_key].discard(subscription_id)
+
+            # If no more clients need this source subscription, unsubscribe from source
+            if not self._source_refs[source_key]:
+                del self._source_refs[source_key]
+
+                if subscription.source_subscription_id:
+                    source = self._sources.get(subscription.source_name)
+                    if source:
+                        try:
+                            await source.unsubscribe_bars(subscription.source_subscription_id)
+                            logger.info(
+                                f"Unsubscribed from source: {subscription.source_subscription_id}"
+                            )
+                        except Exception as e:
+                            logger.error(f"Error unsubscribing from source: {e}")
+
+                    self._source_subs.pop(subscription.source_subscription_id, None)
+
+        logger.info(f"Client subscription removed: {subscription_id}")
+
+    async def unsubscribe_client(self, client_id: str) -> None:
+        """
+        Unsubscribe all subscriptions for a client.
+
+        Useful when a WebSocket connection closes.
+
+        Args:
+            client_id: ID of the client
+        """
+        # Find all subscriptions for this client
+        client_subs = [
+            sub_id
+            for sub_id, sub in self._subscriptions.items()
+            if sub.client_id == client_id
+        ]
+
+        # Unsubscribe each one
+        for sub_id in client_subs:
+            await self.unsubscribe(sub_id)
+
+        logger.info(f"Unsubscribed all subscriptions for client {client_id}")
+
+    def _on_source_update(self, source_key: tuple, bar: dict) -> None:
+        """
+        Handle an update from a data source.
+
+        Routes the update to all client subscriptions that need it.
+
+        Args:
+            source_key: (source_name, symbol, resolution) tuple
+            bar: Bar data dict from the source
+        """
+        subscription_ids = self._source_refs.get(source_key, set())
+
+        for sub_id in subscription_ids:
+            subscription = self._subscriptions.get(sub_id)
+            if subscription:
+                try:
+                    subscription.callback(bar)
+                except Exception as e:
+                    logger.error(
+                        f"Error in subscription callback {sub_id}: {e}", exc_info=True
+                    )
+
+    def get_subscription_count(self) -> int:
+        """Get total number of active client subscriptions"""
+        return len(self._subscriptions)
+
+    def get_source_subscription_count(self) -> int:
+        """Get total number of active source subscriptions"""
+        return len(self._source_refs)
+
+    def get_client_subscriptions(self, client_id: str) -> list:
+        """Get all subscriptions for a specific client"""
+        return [
+            {
+                "subscription_id": sub.subscription_id,
+                "source": sub.source_name,
+                "symbol": sub.symbol,
+                "resolution": sub.resolution,
+            }
+            for sub in self._subscriptions.values()
+            if sub.client_id == client_id
+        ]

backend/src/datasource/websocket_handler.py

@@ -0,0 +1,347 @@
+"""
+WebSocket handler for TradingView-compatible datafeed API.
+
+Handles incoming requests for symbol search, metadata, historical data,
+and real-time subscriptions.
+"""
+
+import json
+import logging
+from typing import Dict, Optional
+
+from fastapi import WebSocket
+
+from .base import DataSource
+from .registry import DataSourceRegistry
+from .subscription_manager import SubscriptionManager
+from .websocket_protocol import (
+    BarUpdateMessage,
+    ErrorResponse,
+    GetBarsRequest,
+    GetBarsResponse,
+    GetConfigRequest,
+    GetConfigResponse,
+    ResolveSymbolRequest,
+    ResolveSymbolResponse,
+    SearchSymbolsRequest,
+    SearchSymbolsResponse,
+    SubscribeBarsRequest,
+    SubscribeBarsResponse,
+    UnsubscribeBarsRequest,
+    UnsubscribeBarsResponse,
+)
+
+logger = logging.getLogger(__name__)
+
+
+class DatafeedWebSocketHandler:
+    """
+    Handles WebSocket connections for TradingView-compatible datafeed API.
+
+    Each handler manages a single WebSocket connection and routes requests
+    to the appropriate data sources via the registry.
+    """
+
+    def __init__(
+        self,
+        websocket: WebSocket,
+        client_id: str,
+        registry: DataSourceRegistry,
+        subscription_manager: SubscriptionManager,
+        default_source: Optional[str] = None,
+    ):
+        """
+        Initialize handler.
+
+        Args:
+            websocket: FastAPI WebSocket connection
+            client_id: Unique identifier for this client
+            registry: DataSource registry for accessing data sources
+            subscription_manager: Shared subscription manager
+            default_source: Default data source name if not specified in requests
+        """
+        self.websocket = websocket
+        self.client_id = client_id
+        self.registry = registry
+        self.subscription_manager = subscription_manager
+        self.default_source = default_source
+        self._connected = True
+
+    async def handle_connection(self) -> None:
+        """
+        Main connection handler loop.
+
+        Processes incoming messages until the connection closes.
+        """
+        try:
+            await self.websocket.accept()
+            logger.info(f"WebSocket connected: client_id={self.client_id}")
+
+            while self._connected:
+                # Receive message
+                try:
+                    data = await self.websocket.receive_text()
+                    message = json.loads(data)
+                except Exception as e:
+                    logger.error(f"Error receiving/parsing message: {e}")
+                    break
+
+                # Route to appropriate handler
+                await self._handle_message(message)
+
+        except Exception as e:
+            logger.error(f"WebSocket error: {e}", exc_info=True)
+        finally:
+            # Clean up subscriptions when connection closes
+            await self.subscription_manager.unsubscribe_client(self.client_id)
+            self._connected = False
+            logger.info(f"WebSocket disconnected: client_id={self.client_id}")
+
+    async def _handle_message(self, message: dict) -> None:
+        """Route message to appropriate handler based on type"""
+        msg_type = message.get("type")
+        request_id = message.get("request_id", "unknown")
+
+        try:
+            if msg_type == "search_symbols":
+                await self._handle_search_symbols(SearchSymbolsRequest(**message))
+            elif msg_type == "resolve_symbol":
+                await self._handle_resolve_symbol(ResolveSymbolRequest(**message))
+            elif msg_type == "get_bars":
+                await self._handle_get_bars(GetBarsRequest(**message))
+            elif msg_type == "subscribe_bars":
+                await self._handle_subscribe_bars(SubscribeBarsRequest(**message))
+            elif msg_type == "unsubscribe_bars":
+                await self._handle_unsubscribe_bars(UnsubscribeBarsRequest(**message))
+            elif msg_type == "get_config":
+                await self._handle_get_config(GetConfigRequest(**message))
+            else:
+                await self._send_error(
+                    request_id, "UNKNOWN_REQUEST_TYPE", f"Unknown request type: {msg_type}"
+                )
+        except Exception as e:
+            logger.error(f"Error handling {msg_type}: {e}", exc_info=True)
+            await self._send_error(request_id, "INTERNAL_ERROR", str(e))
+
+    async def _handle_search_symbols(self, request: SearchSymbolsRequest) -> None:
+        """Handle symbol search request"""
+        # Use default source or search all sources
+        if self.default_source:
+            source = self.registry.get(self.default_source)
+            if not source:
+                await self._send_error(
+                    request.request_id,
+                    "SOURCE_NOT_FOUND",
+                    f"Default source '{self.default_source}' not found",
+                )
+                return
+
+            results = await source.search_symbols(
+                query=request.query,
+                type=request.symbol_type,
+                exchange=request.exchange,
+                limit=request.limit,
+            )
+            results_data = [r.model_dump(mode="json") for r in results]
+        else:
+            # Search all sources
+            all_results = await self.registry.search_all(
+                query=request.query,
+                type=request.symbol_type,
+                exchange=request.exchange,
+                limit=request.limit,
+            )
+            # Flatten results from all sources
+            results_data = []
+            for source_results in all_results.values():
+                results_data.extend([r.model_dump(mode="json") for r in source_results])
+
+        response = SearchSymbolsResponse(request_id=request.request_id, results=results_data)
+        await self._send_response(response)
+
+    async def _handle_resolve_symbol(self, request: ResolveSymbolRequest) -> None:
+        """Handle symbol resolution request"""
+        # Extract source from symbol if present (format: "SOURCE:SYMBOL")
+        if ":" in request.symbol:
+            source_name, symbol = request.symbol.split(":", 1)
+        else:
+            source_name = self.default_source
+            symbol = request.symbol
+
+        if not source_name:
+            await self._send_error(
+                request.request_id,
+                "NO_SOURCE_SPECIFIED",
+                "No data source specified and no default source configured",
+            )
+            return
+
+        try:
+            symbol_info = await self.registry.resolve_symbol(source_name, symbol)
+            response = ResolveSymbolResponse(
+                request_id=request.request_id,
+                symbol_info=symbol_info.model_dump(mode="json"),
+            )
+            await self._send_response(response)
+        except ValueError as e:
+            await self._send_error(request.request_id, "SYMBOL_NOT_FOUND", str(e))
+
+    async def _handle_get_bars(self, request: GetBarsRequest) -> None:
+        """Handle historical bars request"""
+        # Extract source from symbol
+        if ":" in request.symbol:
+            source_name, symbol = request.symbol.split(":", 1)
+        else:
+            source_name = self.default_source
+            symbol = request.symbol
+
+        if not source_name:
+            await self._send_error(
+                request.request_id, "NO_SOURCE_SPECIFIED", "No data source specified"
+            )
+            return
+
+        source = self.registry.get(source_name)
+        if not source:
+            await self._send_error(
+                request.request_id, "SOURCE_NOT_FOUND", f"Source '{source_name}' not found"
+            )
+            return
+
+        try:
+            history = await source.get_bars(
+                symbol=symbol,
+                resolution=request.resolution,
+                from_time=request.from_time,
+                to_time=request.to_time,
+                countback=request.countback,
+            )
+            response = GetBarsResponse(
+                request_id=request.request_id, history=history.model_dump(mode="json")
+            )
+            await self._send_response(response)
+        except ValueError as e:
+            await self._send_error(request.request_id, "INVALID_REQUEST", str(e))
+
+    async def _handle_subscribe_bars(self, request: SubscribeBarsRequest) -> None:
+        """Handle real-time subscription request"""
+        # Extract source from symbol
+        if ":" in request.symbol:
+            source_name, symbol = request.symbol.split(":", 1)
+        else:
+            source_name = self.default_source
+            symbol = request.symbol
+
+        if not source_name:
+            await self._send_error(
+                request.request_id, "NO_SOURCE_SPECIFIED", "No data source specified"
+            )
+            return
+
+        try:
+            # Create callback that sends updates to this WebSocket
+            async def send_update(bar: dict):
+                update = BarUpdateMessage(
+                    subscription_id=request.subscription_id,
+                    symbol=request.symbol,
+                    resolution=request.resolution,
+                    bar=bar,
+                )
+                await self._send_response(update)
+
+            # Register subscription
+            await self.subscription_manager.subscribe(
+                subscription_id=request.subscription_id,
+                client_id=self.client_id,
+                source_name=source_name,
+                symbol=symbol,
+                resolution=request.resolution,
+                callback=lambda bar: self._queue_update(send_update(bar)),
+            )
+
+            response = SubscribeBarsResponse(
+                request_id=request.request_id,
+                subscription_id=request.subscription_id,
+                success=True,
+            )
+            await self._send_response(response)
+
+        except Exception as e:
+            logger.error(f"Subscription failed: {e}", exc_info=True)
+            response = SubscribeBarsResponse(
+                request_id=request.request_id,
+                subscription_id=request.subscription_id,
+                success=False,
+                message=str(e),
+            )
+            await self._send_response(response)
+
+    async def _handle_unsubscribe_bars(self, request: UnsubscribeBarsRequest) -> None:
+        """Handle unsubscribe request"""
+        try:
+            await self.subscription_manager.unsubscribe(request.subscription_id)
+            response = UnsubscribeBarsResponse(
+                request_id=request.request_id,
+                subscription_id=request.subscription_id,
+                success=True,
+            )
+            await self._send_response(response)
+        except Exception as e:
+            logger.error(f"Unsubscribe failed: {e}")
+            response = UnsubscribeBarsResponse(
+                request_id=request.request_id,
+                subscription_id=request.subscription_id,
+                success=False,
+            )
+            await self._send_response(response)
+
+    async def _handle_get_config(self, request: GetConfigRequest) -> None:
+        """Handle datafeed config request"""
+        if self.default_source:
+            source = self.registry.get(self.default_source)
+            if source:
+                config = await source.get_config()
+                response = GetConfigResponse(
+                    request_id=request.request_id, config=config.model_dump(mode="json")
+                )
+                await self._send_response(response)
+                return
+
+        # Return aggregate config from all sources
+        all_sources = self.registry.list_sources()
+        if not all_sources:
+            await self._send_error(
+                request.request_id, "NO_SOURCES", "No data sources available"
+            )
+            return
+
+        # Just use first source's config for now
+        # TODO: Aggregate configs from multiple sources
+        source = self.registry.get(all_sources[0])
+        if source:
+            config = await source.get_config()
+            response = GetConfigResponse(
+                request_id=request.request_id, config=config.model_dump(mode="json")
+            )
+            await self._send_response(response)
+
+    async def _send_response(self, response) -> None:
+        """Send a response message to the client"""
+        try:
+            await self.websocket.send_json(response.model_dump(mode="json"))
+        except Exception as e:
+            logger.error(f"Error sending response: {e}")
+            self._connected = False
+
+    async def _send_error(self, request_id: str, error_code: str, error_message: str) -> None:
+        """Send an error response"""
+        error = ErrorResponse(
+            request_id=request_id, error_code=error_code, error_message=error_message
+        )
+        await self._send_response(error)
+
+    def _queue_update(self, coro):
+        """Queue an async update to be sent (prevents blocking callback)"""
+        import asyncio
+
+        asyncio.create_task(coro)

backend/src/datasource/websocket_protocol.py

@@ -0,0 +1,170 @@
+"""
+WebSocket protocol messages for TradingView-compatible datafeed API.
+
+These messages define the wire format for client-server communication
+over WebSocket for symbol search, historical data, and real-time subscriptions.
+"""
+
+from typing import Any, Dict, List, Literal, Optional, Union
+
+from pydantic import BaseModel, Field
+
+
+# ============================================================================
+# Client -> Server Messages
+# ============================================================================
+
+
+class SearchSymbolsRequest(BaseModel):
+    """Request to search for symbols matching a query"""
+
+    type: Literal["search_symbols"] = "search_symbols"
+    request_id: str = Field(description="Client-generated request ID for matching responses")
+    query: str = Field(description="Search query string")
+    symbol_type: Optional[str] = Field(default=None, description="Filter by instrument type")
+    exchange: Optional[str] = Field(default=None, description="Filter by exchange")
+    limit: int = Field(default=30, description="Maximum number of results")
+
+
+class ResolveSymbolRequest(BaseModel):
+    """Request full metadata for a specific symbol"""
+
+    type: Literal["resolve_symbol"] = "resolve_symbol"
+    request_id: str
+    symbol: str = Field(description="Symbol identifier to resolve")
+
+
+class GetBarsRequest(BaseModel):
+    """Request historical bar data"""
+
+    type: Literal["get_bars"] = "get_bars"
+    request_id: str
+    symbol: str
+    resolution: str = Field(description="Time resolution (e.g., '1', '5', '60', '1D')")
+    from_time: int = Field(description="Start time (Unix timestamp in seconds)")
+    to_time: int = Field(description="End time (Unix timestamp in seconds)")
+    countback: Optional[int] = Field(default=None, description="Maximum number of bars to return")
+
+
+class SubscribeBarsRequest(BaseModel):
+    """Subscribe to real-time bar updates"""
+
+    type: Literal["subscribe_bars"] = "subscribe_bars"
+    request_id: str
+    symbol: str
+    resolution: str
+    subscription_id: str = Field(description="Client-generated subscription ID")
+
+
+class UnsubscribeBarsRequest(BaseModel):
+    """Unsubscribe from real-time updates"""
+
+    type: Literal["unsubscribe_bars"] = "unsubscribe_bars"
+    request_id: str
+    subscription_id: str
+
+
+class GetConfigRequest(BaseModel):
+    """Request datafeed configuration"""
+
+    type: Literal["get_config"] = "get_config"
+    request_id: str
+
+
+# Union of all client request types
+ClientRequest = Union[
+    SearchSymbolsRequest,
+    ResolveSymbolRequest,
+    GetBarsRequest,
+    SubscribeBarsRequest,
+    UnsubscribeBarsRequest,
+    GetConfigRequest,
+]
+
+
+# ============================================================================
+# Server -> Client Messages
+# ============================================================================
+
+
+class SearchSymbolsResponse(BaseModel):
+    """Response with search results"""
+
+    type: Literal["search_symbols_response"] = "search_symbols_response"
+    request_id: str
+    results: List[Dict[str, Any]] = Field(description="List of SearchResult objects")
+
+
+class ResolveSymbolResponse(BaseModel):
+    """Response with symbol metadata"""
+
+    type: Literal["resolve_symbol_response"] = "resolve_symbol_response"
+    request_id: str
+    symbol_info: Dict[str, Any] = Field(description="SymbolInfo object")
+
+
+class GetBarsResponse(BaseModel):
+    """Response with historical bars"""
+
+    type: Literal["get_bars_response"] = "get_bars_response"
+    request_id: str
+    history: Dict[str, Any] = Field(description="HistoryResult object with bars and metadata")
+
+
+class SubscribeBarsResponse(BaseModel):
+    """Acknowledgment of subscription"""
+
+    type: Literal["subscribe_bars_response"] = "subscribe_bars_response"
+    request_id: str
+    subscription_id: str
+    success: bool
+    message: Optional[str] = None
+
+
+class UnsubscribeBarsResponse(BaseModel):
+    """Acknowledgment of unsubscribe"""
+
+    type: Literal["unsubscribe_bars_response"] = "unsubscribe_bars_response"
+    request_id: str
+    subscription_id: str
+    success: bool
+
+
+class GetConfigResponse(BaseModel):
+    """Response with datafeed configuration"""
+
+    type: Literal["get_config_response"] = "get_config_response"
+    request_id: str
+    config: Dict[str, Any] = Field(description="DatafeedConfig object")
+
+
+class BarUpdateMessage(BaseModel):
+    """Real-time bar update (server-initiated, no request_id)"""
+
+    type: Literal["bar_update"] = "bar_update"
+    subscription_id: str
+    symbol: str
+    resolution: str
+    bar: Dict[str, Any] = Field(description="Bar data including time and all columns")
+
+
+class ErrorResponse(BaseModel):
+    """Error response for any failed request"""
+
+    type: Literal["error"] = "error"
+    request_id: str
+    error_code: str = Field(description="Machine-readable error code")
+    error_message: str = Field(description="Human-readable error description")
+
+
+# Union of all server response types
+ServerResponse = Union[
+    SearchSymbolsResponse,
+    ResolveSymbolResponse,
+    GetBarsResponse,
+    SubscribeBarsResponse,
+    UnsubscribeBarsResponse,
+    GetConfigResponse,
+    BarUpdateMessage,
+    ErrorResponse,
+]

backend/src/gateway/__init__.py

@@ -0,0 +1,4 @@
+from gateway.protocol import UserMessage, AgentMessage, ChannelStatus
+from gateway.hub import Gateway
+
+__all__ = ["UserMessage", "AgentMessage", "ChannelStatus", "Gateway"]

backend/src/gateway/channels/__init__.py

@@ -0,0 +1,3 @@
+from gateway.channels.base import Channel
+
+__all__ = ["Channel"]

backend/src/gateway/channels/base.py

@@ -0,0 +1,73 @@
+from abc import ABC, abstractmethod
+from typing import AsyncIterator, Dict, Any
+
+from gateway.protocol import UserMessage, AgentMessage, ChannelStatus
+
+
+class Channel(ABC):
+    """Abstract base class for communication channels.
+
+    Channels are the transport layer between users and the agent system.
+    They handle protocol-specific encoding/decoding and maintain connection state.
+    """
+
+    def __init__(self, channel_id: str, channel_type: str):
+        self.channel_id = channel_id
+        self.channel_type = channel_type
+        self._connected = False
+
+    @abstractmethod
+    async def send(self, message: AgentMessage) -> None:
+        """Send a message from the agent to the user through this channel.
+
+        Args:
+            message: AgentMessage to send (may be streaming chunk or complete message)
+        """
+        pass
+
+    @abstractmethod
+    async def receive(self) -> AsyncIterator[UserMessage]:
+        """Receive messages from the user through this channel.
+
+        Yields:
+            UserMessage objects as they arrive
+        """
+        pass
+
+    @abstractmethod
+    async def close(self) -> None:
+        """Close the channel and clean up resources."""
+        pass
+
+    def supports_streaming(self) -> bool:
+        """Whether this channel supports streaming responses.
+
+        Returns:
+            True if the channel can handle streaming chunks
+        """
+        return False
+
+    def supports_attachments(self) -> bool:
+        """Whether this channel supports file attachments.
+
+        Returns:
+            True if the channel can handle attachments
+        """
+        return False
+
+    def get_status(self) -> ChannelStatus:
+        """Get current channel status.
+
+        Returns:
+            ChannelStatus object with connection info and capabilities
+        """
+        return ChannelStatus(
+            channel_id=self.channel_id,
+            channel_type=self.channel_type,
+            connected=self._connected,
+            capabilities={
+                "streaming": self.supports_streaming(),
+                "attachments": self.supports_attachments(),
+                "markdown": True  # Most channels support some form of markdown
+            }
+        )

backend/src/gateway/channels/websocket.py

@@ -0,0 +1,99 @@
+import asyncio
+import json
+import logging
+from typing import AsyncIterator, Optional
+from datetime import datetime
+from fastapi import WebSocket
+
+from gateway.channels.base import Channel
+from gateway.protocol import UserMessage, AgentMessage, WebSocketAgentUserMessage, WebSocketAgentChunk
+
+logger = logging.getLogger(__name__)
+
+
+class WebSocketChannel(Channel):
+    """WebSocket-based communication channel.
+
+    Integrates with the existing WebSocket endpoint to provide
+    bidirectional agent communication with streaming support.
+    """
+
+    def __init__(self, channel_id: str, websocket: WebSocket, session_id: str):
+        super().__init__(channel_id, "websocket")
+        self.websocket = websocket
+        self.session_id = session_id
+        self._connected = True
+        self._receive_queue: asyncio.Queue[UserMessage] = asyncio.Queue()
+        self._receive_task: Optional[asyncio.Task] = None
+
+    def supports_streaming(self) -> bool:
+        """WebSocket supports streaming responses."""
+        return True
+
+    def supports_attachments(self) -> bool:
+        """WebSocket can support attachments via URLs."""
+        return True
+
+    async def send(self, message: AgentMessage) -> None:
+        """Send agent message through WebSocket.
+
+        For streaming messages, sends chunks as they arrive.
+        For complete messages, sends as a single chunk.
+        """
+        if not self._connected:
+            logger.warning(f"Cannot send message, channel {self.channel_id} not connected")
+            return
+
+        try:
+            chunk = WebSocketAgentChunk(
+                session_id=message.session_id,
+                content=message.content,
+                done=message.done,
+                metadata=message.metadata
+            )
+            chunk_data = chunk.model_dump(mode="json")
+            logger.debug(f"Sending WebSocket message: done={message.done}, content_length={len(message.content)}")
+            await self.websocket.send_json(chunk_data)
+            logger.debug(f"WebSocket message sent successfully")
+        except Exception as e:
+            logger.error(f"WebSocket send error: {e}", exc_info=True)
+            self._connected = False
+
+    async def receive(self) -> AsyncIterator[UserMessage]:
+        """Receive messages from WebSocket.
+
+        Yields:
+            UserMessage objects as they arrive from the client
+        """
+        try:
+            while self._connected:
+                # Read from WebSocket
+                data = await self.websocket.receive_text()
+                message_json = json.loads(data)
+
+                # Only process agent_user_message types
+                if message_json.get("type") == "agent_user_message":
+                    msg = WebSocketAgentUserMessage(**message_json)
+
+                    user_msg = UserMessage(
+                        session_id=msg.session_id,
+                        channel_id=self.channel_id,
+                        content=msg.content,
+                        attachments=msg.attachments,
+                        timestamp=datetime.utcnow()
+                    )
+                    yield user_msg
+        except Exception as e:
+            print(f"WebSocket receive error: {e}")
+            self._connected = False
+
+    async def close(self) -> None:
+        """Close the WebSocket connection."""
+        self._connected = False
+        if self._receive_task:
+            self._receive_task.cancel()
+            try:
+                await self._receive_task
+            except asyncio.CancelledError:
+                pass
+        # Note: WebSocket close is handled by the main WebSocket endpoint

backend/src/gateway/hub.py

@@ -0,0 +1,226 @@
+import asyncio
+import logging
+from typing import Dict, Optional, Callable, Awaitable, Any
+from datetime import datetime
+
+from gateway.channels.base import Channel
+from gateway.user_session import UserSession
+from gateway.protocol import UserMessage, AgentMessage
+
+logger = logging.getLogger(__name__)
+
+
+class Gateway:
+    """Central hub for routing messages between users, channels, and the agent.
+
+    The Gateway:
+    - Maintains active channels and user sessions
+    - Routes user messages to the agent
+    - Routes agent responses back to appropriate channels
+    - Handles interruption of in-flight agent tasks
+    """
+
+    def __init__(self):
+        self.channels: Dict[str, Channel] = {}
+        self.sessions: Dict[str, UserSession] = {}
+        self.agent_executor: Optional[Callable[[UserSession, UserMessage], Awaitable[AsyncIterator[str]]]] = None
+
+    def set_agent_executor(
+        self,
+        executor: Callable[[UserSession, UserMessage], Awaitable[Any]]
+    ) -> None:
+        """Set the agent executor function.
+
+        Args:
+            executor: Async function that takes (session, message) and returns async iterator of response chunks
+        """
+        self.agent_executor = executor
+
+    def register_channel(self, channel: Channel) -> None:
+        """Register a new communication channel.
+
+        Args:
+            channel: Channel instance to register
+        """
+        self.channels[channel.channel_id] = channel
+
+    def unregister_channel(self, channel_id: str) -> None:
+        """Unregister a channel.
+
+        Args:
+            channel_id: ID of channel to remove
+        """
+        if channel_id in self.channels:
+            # Remove channel from any sessions
+            for session in self.sessions.values():
+                session.remove_channel(channel_id)
+            del self.channels[channel_id]
+
+    def get_or_create_session(self, session_id: str, user_id: str) -> UserSession:
+        """Get existing session or create a new one.
+
+        Args:
+            session_id: Unique session identifier
+            user_id: User identifier
+
+        Returns:
+            UserSession instance
+        """
+        if session_id not in self.sessions:
+            self.sessions[session_id] = UserSession(session_id, user_id)
+        return self.sessions[session_id]
+
+    async def route_user_message(self, message: UserMessage) -> None:
+        """Route a user message to the agent.
+
+        If the agent is currently processing a message, it will be interrupted
+        and restarted with the new message appended to the conversation.
+
+        Args:
+            message: UserMessage from a channel
+        """
+        logger.info(f"route_user_message called - session: {message.session_id}, channel: {message.channel_id}")
+
+        # Get or create session
+        session = self.get_or_create_session(message.session_id, message.session_id)
+        logger.info(f"Session obtained/created: {message.session_id}, channels: {session.active_channels}")
+
+        # Ensure channel is attached to session
+        session.add_channel(message.channel_id)
+        logger.info(f"Channel added to session: {message.channel_id}")
+
+        # If agent is busy, interrupt it
+        if session.is_busy():
+            logger.info(f"Session is busy, interrupting existing task")
+            await session.interrupt()
+
+        # Add user message to history
+        session.add_message("user", message.content, message.channel_id)
+        logger.info(f"User message added to history, history length: {len(session.get_history())}")
+
+        # Start agent task
+        if self.agent_executor:
+            logger.info("Starting agent task execution")
+            task = asyncio.create_task(
+                self._execute_agent_and_stream(session, message)
+            )
+            session.set_task(task)
+            logger.info(f"Agent task created and set on session")
+        else:
+            logger.error("No agent_executor configured! Cannot process message.")
+            # Send error message to user
+            error_msg = AgentMessage(
+                session_id=session.session_id,
+                target_channels=session.active_channels,
+                content="Error: Agent system not initialized. Please check that ANTHROPIC_API_KEY is configured.",
+                done=True
+            )
+            await self._send_to_channels(error_msg)
+
+    async def _execute_agent_and_stream(self, session: UserSession, message: UserMessage) -> None:
+        """Execute agent and stream responses back to channels.
+
+        Args:
+            session: User session
+            message: Triggering user message
+        """
+        logger.info(f"_execute_agent_and_stream starting for session {session.session_id}")
+        try:
+            # Execute agent (returns async generator directly)
+            logger.info("Calling agent_executor...")
+            response_stream = self.agent_executor(session, message)
+            logger.info("Agent executor returned response stream")
+
+            # Stream chunks back to active channels
+            full_response = ""
+            chunk_count = 0
+            async for chunk in response_stream:
+                chunk_count += 1
+                full_response += chunk
+                logger.debug(f"Received chunk #{chunk_count}, length: {len(chunk)}")
+
+                # Send chunk to all active channels
+                agent_msg = AgentMessage(
+                    session_id=session.session_id,
+                    target_channels=session.active_channels,
+                    content=chunk,
+                    stream_chunk=True,
+                    done=False
+                )
+                await self._send_to_channels(agent_msg)
+
+            logger.info(f"Agent streaming completed, total chunks: {chunk_count}, response length: {len(full_response)}")
+
+            # Send final done message
+            agent_msg = AgentMessage(
+                session_id=session.session_id,
+                target_channels=session.active_channels,
+                content="",
+                stream_chunk=True,
+                done=True
+            )
+            await self._send_to_channels(agent_msg)
+            logger.info("Sent final done message to channels")
+
+            # Add to history
+            session.add_message("assistant", full_response)
+            logger.info("Assistant response added to history")
+
+        except asyncio.CancelledError:
+            # Task was interrupted
+            logger.warning(f"Agent task interrupted for session {session.session_id}")
+            raise
+        except Exception as e:
+            logger.error(f"Agent execution error: {e}", exc_info=True)
+            # Send error message
+            error_msg = AgentMessage(
+                session_id=session.session_id,
+                target_channels=session.active_channels,
+                content=f"Error: {str(e)}",
+                done=True
+            )
+            await self._send_to_channels(error_msg)
+        finally:
+            session.set_task(None)
+            logger.info(f"Agent task completed for session {session.session_id}")
+
+    async def _send_to_channels(self, message: AgentMessage) -> None:
+        """Send message to specified channels.
+
+        Args:
+            message: AgentMessage to send
+        """
+        logger.debug(f"Sending message to {len(message.target_channels)} channels")
+        for channel_id in message.target_channels:
+            channel = self.channels.get(channel_id)
+            if channel and channel.get_status().connected:
+                try:
+                    await channel.send(message)
+                    logger.debug(f"Message sent to channel {channel_id}")
+                except Exception as e:
+                    logger.error(f"Error sending to channel {channel_id}: {e}", exc_info=True)
+            else:
+                logger.warning(f"Channel {channel_id} not found or not connected")
+
+    def get_session_info(self, session_id: str) -> Optional[Dict[str, Any]]:
+        """Get session information.
+
+        Args:
+            session_id: Session ID to query
+
+        Returns:
+            Session info dict or None if not found
+        """
+        session = self.sessions.get(session_id)
+        return session.to_dict() if session else None
+
+    def get_active_sessions(self) -> Dict[str, Dict[str, Any]]:
+        """Get all active sessions.
+
+        Returns:
+            Dict mapping session_id to session info
+        """
+        return {
+            sid: session.to_dict()
+            for sid, session in self.sessions.items()
+        }

backend/src/gateway/protocol.py

@@ -0,0 +1,57 @@
+from datetime import datetime, timezone
+from typing import Any, Dict, List, Literal, Optional
+from pydantic import BaseModel, Field
+
+
+class UserMessage(BaseModel):
+    """Message from user to agent through a communication channel."""
+    session_id: str
+    channel_id: str
+    content: str
+    attachments: List[str] = Field(default_factory=list, description="URLs or file paths")
+    timestamp: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+    metadata: Dict[str, Any] = Field(default_factory=dict)
+
+
+class AgentMessage(BaseModel):
+    """Message from agent to user(s) through one or more channels."""
+    session_id: str
+    target_channels: List[str] = Field(description="List of channel IDs to send to")
+    content: str
+    stream_chunk: bool = Field(default=False, description="True if this is a streaming chunk")
+    done: bool = Field(default=False, description="True if streaming is complete")
+    metadata: Dict[str, Any] = Field(default_factory=dict)
+
+
+class ChannelStatus(BaseModel):
+    """Status information about a communication channel."""
+    channel_id: str
+    channel_type: str = Field(description="Type: 'websocket', 'slack', 'telegram', etc.")
+    connected: bool
+    user_id: Optional[str] = None
+    session_id: Optional[str] = None
+    capabilities: Dict[str, bool] = Field(
+        default_factory=lambda: {
+            "streaming": False,
+            "attachments": False,
+            "markdown": False
+        }
+    )
+
+
+# WebSocket-specific protocol extensions
+class WebSocketAgentUserMessage(BaseModel):
+    """WebSocket message: User → Backend (agent chat)"""
+    type: Literal["agent_user_message"] = "agent_user_message"
+    session_id: str
+    content: str
+    attachments: List[str] = Field(default_factory=list)
+
+
+class WebSocketAgentChunk(BaseModel):
+    """WebSocket message: Backend → User (streaming agent response)"""
+    type: Literal["agent_chunk"] = "agent_chunk"
+    session_id: str
+    content: str
+    done: bool = False
+    metadata: Dict[str, Any] = Field(default_factory=dict)

backend/src/gateway/user_session.py

@@ -0,0 +1,107 @@
+import asyncio
+from datetime import datetime
+from typing import Dict, List, Optional, Any
+from pydantic import BaseModel, Field
+
+
+class Message(BaseModel):
+    """A single message in a conversation."""
+    role: str  # "user" or "assistant"
+    content: str
+    timestamp: datetime = Field(default_factory=datetime.utcnow)
+    channel_id: Optional[str] = None
+    metadata: Dict[str, Any] = Field(default_factory=dict)
+
+
+class UserSession:
+    """Manages a user's conversation session with the agent.
+
+    A session tracks:
+    - Active communication channels
+    - Conversation history
+    - In-flight agent tasks (for interruption)
+    - User metadata
+    """
+
+    def __init__(self, session_id: str, user_id: str):
+        self.session_id = session_id
+        self.user_id = user_id
+        self.active_channels: List[str] = []
+        self.conversation_history: List[Message] = []
+        self.current_task: Optional[asyncio.Task] = None
+        self.metadata: Dict[str, Any] = {}
+        self.created_at = datetime.utcnow()
+        self.last_activity = datetime.utcnow()
+
+    def add_channel(self, channel_id: str) -> None:
+        """Attach a channel to this session."""
+        if channel_id not in self.active_channels:
+            self.active_channels.append(channel_id)
+        self.last_activity = datetime.utcnow()
+
+    def remove_channel(self, channel_id: str) -> None:
+        """Detach a channel from this session."""
+        if channel_id in self.active_channels:
+            self.active_channels.remove(channel_id)
+        self.last_activity = datetime.utcnow()
+
+    def add_message(self, role: str, content: str, channel_id: Optional[str] = None, **kwargs) -> None:
+        """Add a message to conversation history."""
+        message = Message(
+            role=role,
+            content=content,
+            channel_id=channel_id,
+            metadata=kwargs
+        )
+        self.conversation_history.append(message)
+        self.last_activity = datetime.utcnow()
+
+    def get_history(self, limit: Optional[int] = None) -> List[Message]:
+        """Get conversation history.
+
+        Args:
+            limit: Maximum number of recent messages to return (None = all)
+
+        Returns:
+            List of Message objects
+        """
+        if limit:
+            return self.conversation_history[-limit:]
+        return self.conversation_history
+
+    async def interrupt(self) -> bool:
+        """Interrupt the current agent task if one is running.
+
+        Returns:
+            True if a task was interrupted, False otherwise
+        """
+        if self.current_task and not self.current_task.done():
+            self.current_task.cancel()
+            try:
+                await self.current_task
+            except asyncio.CancelledError:
+                pass
+            self.current_task = None
+            return True
+        return False
+
+    def set_task(self, task: asyncio.Task) -> None:
+        """Set the current agent task."""
+        self.current_task = task
+
+    def is_busy(self) -> bool:
+        """Check if the agent is currently processing a request."""
+        return self.current_task is not None and not self.current_task.done()
+
+    def to_dict(self) -> Dict[str, Any]:
+        """Serialize session to dict."""
+        return {
+            "session_id": self.session_id,
+            "user_id": self.user_id,
+            "active_channels": self.active_channels,
+            "message_count": len(self.conversation_history),
+            "is_busy": self.is_busy(),
+            "created_at": self.created_at.isoformat(),
+            "last_activity": self.last_activity.isoformat(),
+            "metadata": self.metadata
+        }

backend/src/main.py

@@ -0,0 +1,469 @@
+import asyncio
+import json
+import logging
+import os
+from contextlib import asynccontextmanager
+from pathlib import Path
+
+import yaml
+from dotenv import load_dotenv
+from fastapi import FastAPI, WebSocket, WebSocketDisconnect, UploadFile, File, HTTPException
+from fastapi.responses import FileResponse
+from fastapi.staticfiles import StaticFiles
+from pydantic import BaseModel
+import uuid
+import shutil
+
+from sync.protocol import HelloMessage, PatchMessage
+from sync.registry import SyncRegistry
+from gateway.hub import Gateway
+from gateway.channels.websocket import WebSocketChannel
+from gateway.protocol import WebSocketAgentUserMessage
+from agent.core import create_agent
+from agent.tools import set_registry, set_datasource_registry
+from schema.order_spec import SwapOrder
+from schema.chart_state import ChartState
+from datasource.registry import DataSourceRegistry
+from datasource.subscription_manager import SubscriptionManager
+from datasource.websocket_handler import DatafeedWebSocketHandler
+
+# Configure logging
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+)
+logger = logging.getLogger(__name__)
+
+# Load environment variables from .env file (if present)
+env_path = Path(__file__).parent.parent / ".env"
+if env_path.exists():
+    load_dotenv(env_path)
+
+# Load configuration
+config_path = Path(__file__).parent.parent / "config.yaml"
+with open(config_path) as f:
+    config = yaml.safe_load(f)
+
+registry = SyncRegistry()
+gateway = Gateway()
+agent_executor = None
+
+# DataSource infrastructure
+datasource_registry = DataSourceRegistry()
+subscription_manager = SubscriptionManager()
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    """Initialize agent system and data sources on startup."""
+    global agent_executor
+
+    # Initialize CCXT data sources
+    try:
+        from datasource.adapters.ccxt_adapter import CCXTDataSource
+
+        # Binance
+        try:
+            binance_source = CCXTDataSource(exchange_id="binance", poll_interval=60)
+            datasource_registry.register("binance", binance_source)
+            subscription_manager.register_source("binance", binance_source)
+            logger.info("DataSource: Registered Binance source")
+        except Exception as e:
+            logger.warning(f"Failed to initialize Binance source: {e}")
+
+        logger.info(f"DataSource infrastructure initialized with sources: {datasource_registry.list_sources()}")
+    except ImportError as e:
+        logger.warning(f"CCXT not available: {e}. Only demo source will be available.")
+        logger.info("To use real exchange data, install ccxt: pip install ccxt>=4.0.0")
+
+    # Get API keys from environment
+    anthropic_api_key = os.environ.get("ANTHROPIC_API_KEY")
+
+    if not anthropic_api_key:
+        logger.error("ANTHROPIC_API_KEY not found in environment!")
+        logger.info("Agent system will not be available")
+    else:
+        # Set the registries for agent tools
+        set_registry(registry)
+        set_datasource_registry(datasource_registry)
+
+        # Create and initialize agent
+        agent_executor = create_agent(
+            model_name=config["agent"]["model"],
+            temperature=config["agent"]["temperature"],
+            api_key=anthropic_api_key,
+            checkpoint_db_path=config["memory"]["checkpoint_db"],
+            chroma_db_path=config["memory"]["chroma_db"],
+            embedding_model=config["memory"]["embedding_model"],
+            context_docs_dir=config["agent"]["context_docs_dir"],
+            base_dir=".."  # Point to project root from backend/src
+        )
+
+        await agent_executor.initialize()
+
+        # Set agent executor in gateway
+        gateway.set_agent_executor(agent_executor.execute)
+
+        logger.info("Agent system initialized")
+
+    yield
+
+    # Cleanup
+    if agent_executor and agent_executor.memory_manager:
+        await agent_executor.memory_manager.close()
+    logger.info("Agent system shut down")
+
+
+app = FastAPI(lifespan=lifespan)
+
+# Create uploads directory
+UPLOAD_DIR = Path(__file__).parent.parent / "uploads"
+UPLOAD_DIR.mkdir(exist_ok=True)
+
+# Mount static files for serving uploads
+app.mount("/uploads", StaticFiles(directory=str(UPLOAD_DIR)), name="uploads")
+
+# OrderStore model for synchronization
+class OrderStore(BaseModel):
+    orders: list[SwapOrder] = []
+
+# ChartStore model for synchronization
+class ChartStore(BaseModel):
+    chart_state: ChartState = ChartState()
+
+# Initialize stores
+order_store = OrderStore()
+chart_store = ChartStore()
+
+# Register with SyncRegistry
+registry.register(order_store, store_name="OrderStore")
+registry.register(chart_store, store_name="ChartStore")
+
+@app.websocket("/ws")
+async def websocket_endpoint(websocket: WebSocket):
+    await websocket.accept()
+    registry.websocket = websocket
+
+    # Create WebSocket channel for agent communication
+    channel_id = f"ws_{id(websocket)}"
+    client_id = f"client_{id(websocket)}"
+    logger.info(f"WebSocket connected - channel_id: {channel_id}, client_id: {client_id}")
+    ws_channel = WebSocketChannel(channel_id, websocket, session_id="default")
+    gateway.register_channel(ws_channel)
+
+    # Helper function to send responses
+    async def send_response(response):
+        try:
+            await websocket.send_json(response.model_dump(mode="json"))
+        except Exception as e:
+            logger.error(f"Error sending response: {e}")
+
+    try:
+        while True:
+            data = await websocket.receive_text()
+            logger.debug(f"Received WebSocket message: {data[:200]}...")  # Log first 200 chars
+            message_json = json.loads(data)
+
+            if "type" not in message_json:
+                logger.warning(f"Message missing 'type' field: {message_json}")
+                continue
+
+            msg_type = message_json["type"]
+            logger.info(f"Processing message type: {msg_type}")
+
+            # Handle sync protocol messages
+            if msg_type == "hello":
+                hello_msg = HelloMessage(**message_json)
+                logger.info(f"Hello message received with seqs: {hello_msg.seqs}")
+                await registry.sync_client(hello_msg.seqs)
+            elif msg_type == "patch":
+                patch_msg = PatchMessage(**message_json)
+                logger.info(f"Patch message received for store: {patch_msg.store}, seq: {patch_msg.seq}")
+                await registry.apply_client_patch(
+                    store_name=patch_msg.store,
+                    client_base_seq=patch_msg.seq,
+                    patch=patch_msg.patch
+                )
+            elif msg_type == "agent_user_message":
+                # Handle agent messages directly here
+                print(f"[DEBUG] Raw message_json: {message_json}")
+                logger.info(f"Raw message_json: {message_json}")
+                msg = WebSocketAgentUserMessage(**message_json)
+                print(f"[DEBUG] Parsed message - session: {msg.session_id}, content: '{msg.content}' (len={len(msg.content)})")
+                logger.info(f"Agent user message received - session: {msg.session_id}, content: '{msg.content}' (len={len(msg.content)})")
+                from gateway.protocol import UserMessage
+                from datetime import datetime, timezone
+
+                user_msg = UserMessage(
+                    session_id=msg.session_id,
+                    channel_id=channel_id,
+                    content=msg.content,
+                    attachments=msg.attachments,
+                    timestamp=datetime.now(timezone.utc)
+                )
+                logger.info(f"Routing user message to gateway - channel: {channel_id}, session: {msg.session_id}")
+                await gateway.route_user_message(user_msg)
+                logger.info("Message routing completed")
+
+            # Handle datafeed protocol messages
+            elif msg_type in ["get_config", "search_symbols", "resolve_symbol", "get_bars", "subscribe_bars", "unsubscribe_bars"]:
+                from datasource.websocket_protocol import (
+                    GetConfigRequest, GetConfigResponse,
+                    SearchSymbolsRequest, SearchSymbolsResponse,
+                    ResolveSymbolRequest, ResolveSymbolResponse,
+                    GetBarsRequest, GetBarsResponse,
+                    SubscribeBarsRequest, SubscribeBarsResponse,
+                    UnsubscribeBarsRequest, UnsubscribeBarsResponse,
+                    ErrorResponse
+                )
+
+                request_id = message_json.get("request_id", "unknown")
+                try:
+                    if msg_type == "get_config":
+                        req = GetConfigRequest(**message_json)
+                        logger.info(f"Getting config, request_id={req.request_id}")
+                        sources = datasource_registry.list_sources()
+                        logger.info(f"Available sources: {sources}")
+
+                        if not sources:
+                            error_response = ErrorResponse(request_id=req.request_id, error_code="NO_SOURCES", error_message="No data sources available")
+                            await send_response(error_response)
+                        else:
+                            # Get config from first source (we can enhance this later to aggregate)
+                            source = datasource_registry.get(sources[0])
+                            if source:
+                                try:
+                                    config = await source.get_config()
+                                    logger.info(f"Got config from {sources[0]}")
+                                    # Enhance with all available exchanges
+                                    all_exchanges = set()
+                                    for source_name in sources:
+                                        s = datasource_registry.get(source_name)
+                                        if s:
+                                            try:
+                                                cfg = await asyncio.wait_for(s.get_config(), timeout=5.0)
+                                                all_exchanges.update(cfg.exchanges)
+                                                logger.info(f"Added exchanges from {source_name}: {cfg.exchanges}")
+                                            except asyncio.TimeoutError:
+                                                logger.warning(f"Timeout getting config from {source_name}")
+                                            except Exception as e:
+                                                logger.warning(f"Error getting config from {source_name}: {e}")
+                                    config_dict = config.model_dump(mode="json")
+                                    config_dict["exchanges"] = list(all_exchanges)
+                                    logger.info(f"Sending config with exchanges: {list(all_exchanges)}")
+                                    response = GetConfigResponse(request_id=req.request_id, config=config_dict)
+                                    await send_response(response)
+                                except Exception as e:
+                                    logger.error(f"Error getting config: {e}", exc_info=True)
+                                    error_response = ErrorResponse(request_id=req.request_id, error_code="ERROR", error_message=str(e))
+                                    await send_response(error_response)
+                            else:
+                                error_response = ErrorResponse(request_id=req.request_id, error_code="SOURCE_NOT_FOUND", error_message="Data sources not available")
+                                await send_response(error_response)
+
+                    elif msg_type == "search_symbols":
+                        req = SearchSymbolsRequest(**message_json)
+                        logger.info(f"Searching symbols: query='{req.query}', request_id={req.request_id}")
+
+                        # Search all data sources
+                        all_results = []
+                        sources = datasource_registry.list_sources()
+                        logger.info(f"Available data sources: {sources}")
+
+                        for source_name in sources:
+                            source = datasource_registry.get(source_name)
+                            if source:
+                                try:
+                                    results = await asyncio.wait_for(
+                                        source.search_symbols(query=req.query, type=req.symbol_type, exchange=req.exchange, limit=req.limit),
+                                        timeout=5.0
+                                    )
+                                    all_results.extend([r.model_dump(mode="json") for r in results])
+                                    logger.info(f"Source '{source_name}' returned {len(results)} results")
+                                except asyncio.TimeoutError:
+                                    logger.warning(f"Timeout searching source '{source_name}'")
+                                except Exception as e:
+                                    logger.warning(f"Error searching source '{source_name}': {e}")
+
+                        logger.info(f"Total search results: {len(all_results)}")
+                        response = SearchSymbolsResponse(request_id=req.request_id, results=all_results[:req.limit])
+                        await send_response(response)
+
+                    elif msg_type == "resolve_symbol":
+                        req = ResolveSymbolRequest(**message_json)
+                        logger.info(f"Resolving symbol: {req.symbol}")
+
+                        # Parse ticker format: "EXCHANGE:SYMBOL" (e.g., "BINANCE:BTC/USDT", "DEMO:BTC/USD")
+                        symbol = req.symbol
+                        source_name = None
+                        symbol_without_exchange = symbol
+
+                        # Check if ticker has exchange prefix
+                        if ":" in symbol:
+                            exchange_prefix, symbol_without_exchange = symbol.split(":", 1)
+                            source_name = exchange_prefix.lower()
+                            logger.info(f"Parsed ticker: exchange={source_name}, symbol={symbol_without_exchange}")
+
+                        # If we identified a source, try it directly
+                        if source_name:
+                            try:
+                                source = datasource_registry.get(source_name)
+                                if source:
+                                    logger.info(f"Trying to resolve '{symbol_without_exchange}' in source '{source_name}'")
+                                    symbol_info = await asyncio.wait_for(
+                                        source.resolve_symbol(symbol_without_exchange),
+                                        timeout=5.0
+                                    )
+                                    logger.info(f"Successfully resolved '{symbol_without_exchange}' in source '{source_name}'")
+                                    response = ResolveSymbolResponse(request_id=req.request_id, symbol_info=symbol_info.model_dump(mode="json"))
+                                    await send_response(response)
+                                else:
+                                    error_response = ErrorResponse(request_id=req.request_id, error_code="SOURCE_NOT_FOUND", error_message=f"Data source '{source_name}' not found")
+                                    await send_response(error_response)
+                            except asyncio.TimeoutError:
+                                logger.warning(f"Timeout resolving '{symbol_without_exchange}' in source '{source_name}'")
+                                error_response = ErrorResponse(request_id=req.request_id, error_code="TIMEOUT", error_message=f"Timeout resolving symbol")
+                                await send_response(error_response)
+                            except Exception as e:
+                                logger.warning(f"Error resolving '{symbol_without_exchange}' in source '{source_name}': {e}")
+                                error_response = ErrorResponse(request_id=req.request_id, error_code="SYMBOL_NOT_FOUND", error_message=str(e))
+                                await send_response(error_response)
+                        else:
+                            # No exchange prefix, try all sources
+                            found = False
+                            for src in datasource_registry.list_sources():
+                                try:
+                                    s = datasource_registry.get(src)
+                                    if s:
+                                        logger.info(f"Trying to resolve '{symbol}' in source '{src}'")
+                                        symbol_info = await asyncio.wait_for(s.resolve_symbol(symbol), timeout=5.0)
+                                        if symbol_info:
+                                            logger.info(f"Successfully resolved '{symbol}' in source '{src}'")
+                                            response = ResolveSymbolResponse(request_id=req.request_id, symbol_info=symbol_info.model_dump(mode="json"))
+                                            await send_response(response)
+                                            found = True
+                                            break
+                                except asyncio.TimeoutError:
+                                    logger.warning(f"Timeout resolving '{symbol}' in source '{src}'")
+                                except Exception as e:
+                                    logger.info(f"Symbol '{symbol}' not found in source '{src}': {e}")
+                                    continue
+
+                            if not found:
+                                # Symbol not found in any source
+                                logger.warning(f"Symbol '{symbol}' not found in any data source")
+                                error_response = ErrorResponse(request_id=req.request_id, error_code="SYMBOL_NOT_FOUND", error_message=f"Symbol '{symbol}' not found in any data source")
+                                await send_response(error_response)
+
+                    elif msg_type == "get_bars":
+                        req = GetBarsRequest(**message_json)
+                        logger.info(f"Getting bars for symbol: {req.symbol}")
+
+                        # Parse ticker format: "EXCHANGE:SYMBOL"
+                        symbol = req.symbol
+                        source_name = None
+                        symbol_without_exchange = symbol
+
+                        # Check if ticker has exchange prefix
+                        if ":" in symbol:
+                            exchange_prefix, symbol_without_exchange = symbol.split(":", 1)
+                            source_name = exchange_prefix.lower()
+                            logger.info(f"Parsed ticker for bars: exchange={source_name}, symbol={symbol_without_exchange}")
+
+                        # If we identified a source, use it directly
+                        if source_name:
+                            try:
+                                source = datasource_registry.get(source_name)
+                                if source:
+                                    logger.info(f"Getting bars for '{symbol_without_exchange}' from source '{source_name}'")
+                                    history = await asyncio.wait_for(
+                                        source.get_bars(symbol=symbol_without_exchange, resolution=req.resolution, from_time=req.from_time, to_time=req.to_time, countback=req.countback),
+                                        timeout=10.0
+                                    )
+                                    logger.info(f"Successfully got {len(history.bars)} bars for '{symbol_without_exchange}' from source '{source_name}'")
+                                    response = GetBarsResponse(request_id=req.request_id, history=history.model_dump(mode="json"))
+                                    await send_response(response)
+                                else:
+                                    error_response = ErrorResponse(request_id=req.request_id, error_code="SOURCE_NOT_FOUND", error_message=f"Data source '{source_name}' not found")
+                                    await send_response(error_response)
+                            except asyncio.TimeoutError:
+                                logger.warning(f"Timeout getting bars for '{symbol_without_exchange}' from source '{source_name}'")
+                                error_response = ErrorResponse(request_id=req.request_id, error_code="TIMEOUT", error_message="Timeout fetching bars")
+                                await send_response(error_response)
+                            except Exception as e:
+                                logger.warning(f"Error getting bars for '{symbol_without_exchange}' from source '{source_name}': {e}")
+                                error_response = ErrorResponse(request_id=req.request_id, error_code="ERROR", error_message=str(e))
+                                await send_response(error_response)
+                        else:
+                            # No exchange prefix - this shouldn't happen with proper tickers
+                            logger.warning(f"Ticker '{symbol}' has no exchange prefix")
+                            error_response = ErrorResponse(request_id=req.request_id, error_code="INVALID_TICKER", error_message="Ticker must include exchange prefix (e.g., BINANCE:BTC/USDT)")
+                            await send_response(error_response)
+
+                    elif msg_type == "subscribe_bars":
+                        req = SubscribeBarsRequest(**message_json)
+                        # TODO: Implement subscription management
+                        response = SubscribeBarsResponse(request_id=req.request_id, subscription_id=req.subscription_id, success=True)
+                        await send_response(response)
+
+                    elif msg_type == "unsubscribe_bars":
+                        req = UnsubscribeBarsRequest(**message_json)
+                        response = UnsubscribeBarsResponse(request_id=req.request_id, subscription_id=req.subscription_id, success=True)
+                        await send_response(response)
+
+                except Exception as e:
+                    logger.error(f"Error handling {msg_type}: {e}", exc_info=True)
+                    error_response = ErrorResponse(request_id=request_id, error_code="INTERNAL_ERROR", error_message=str(e))
+                    await send_response(error_response)
+
+    except WebSocketDisconnect:
+        logger.info(f"WebSocket disconnected - channel_id: {channel_id}")
+        registry.websocket = None
+        gateway.unregister_channel(channel_id)
+    except Exception as e:
+        logger.error(f"WebSocket error: {e}", exc_info=True)
+        registry.websocket = None
+        gateway.unregister_channel(channel_id)
+
+@app.post("/api/upload")
+async def upload_file(file: UploadFile = File(...)):
+    """Upload a file and return its URL."""
+    try:
+        # Generate unique filename
+        file_extension = Path(file.filename).suffix if file.filename else ""
+        unique_filename = f"{uuid.uuid4()}{file_extension}"
+        file_path = UPLOAD_DIR / unique_filename
+
+        # Save file
+        with open(file_path, "wb") as buffer:
+            shutil.copyfileobj(file.file, buffer)
+
+        # Return URL (relative to backend)
+        file_url = f"/uploads/{unique_filename}"
+        logger.info(f"File uploaded: {file.filename} -> {file_url}")
+
+        return {
+            "url": file_url,
+            "filename": file.filename,
+            "size": file_path.stat().st_size
+        }
+    except Exception as e:
+        logger.error(f"File upload error: {e}", exc_info=True)
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.get("/healthz")
+async def health():
+    return {"status": "ok"}
+
+# Background task to simulate backend updates (optional, for demo)
+async def simulate_backend_updates():
+    while True:
+        await asyncio.sleep(5)
+        if registry.websocket:
+            # Example: could add/modify orders here
+            await registry.push_all()
+
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=config["www_port"])

backend/src/schema/chart_state.py

@@ -0,0 +1,21 @@
+from typing import Optional
+from pydantic import BaseModel, Field
+
+
+class ChartState(BaseModel):
+    """Tracks the user's current chart view state.
+    
+    This state is synchronized between the frontend and backend to allow
+    the AI agent to understand what the user is currently viewing.
+    """
+    
+    # Current symbol being viewed (e.g., "BINANCE:BTC/USDT", "BINANCE:ETH/USDT")
+    symbol: str = Field(default="BINANCE:BTC/USDT", description="Current trading pair symbol")
+    
+    # Time range currently visible on chart (Unix timestamps in seconds)
+    # These represent the leftmost and rightmost visible candle times
+    start_time: Optional[int] = Field(default=None, description="Start time of visible range (Unix timestamp in seconds)")
+    end_time: Optional[int] = Field(default=None, description="End time of visible range (Unix timestamp in seconds)")
+    
+    # Optional: Chart interval/resolution
+    interval: str = Field(default="15", description="Chart interval (e.g., '1', '5', '15', '60', 'D')")

backend/src/schema/order_spec.py

@@ -0,0 +1,140 @@
+from enum import StrEnum
+from typing import Annotated
+
+from pydantic import BaseModel, Field, BeforeValidator, PlainSerializer
+
+
+# ---------------------------------------------------------------------------
+# Scalar coercion helpers
+# ---------------------------------------------------------------------------
+
+def _to_int(v: int | str) -> int:
+    return int(v, 0) if isinstance(v, str) else int(v)
+
+
+def _to_float(v: float | int | str) -> float:
+    return float(v)
+
+
+_int_to_str = PlainSerializer(str, return_type=str, when_used="json")
+_float_to_str = PlainSerializer(str, return_type=str, when_used="json")
+
+# Always stored as Python int; accepts int or string on input; serialises to string in JSON.
+type Uint8   = Annotated[int, BeforeValidator(_to_int), _int_to_str]
+type Uint16  = Annotated[int, BeforeValidator(_to_int), _int_to_str]
+type Uint24  = Annotated[int, BeforeValidator(_to_int), _int_to_str]
+type Uint32  = Annotated[int, BeforeValidator(_to_int), _int_to_str]
+type Uint64  = Annotated[int, BeforeValidator(_to_int), _int_to_str]
+type Uint256 = Annotated[int, BeforeValidator(_to_int), _int_to_str]
+type Float   = Annotated[float, BeforeValidator(_to_float), _float_to_str]
+
+ETH_ADDRESS_PATTERN = r"^0x[0-9a-fA-F]{40}$"
+
+
+# ---------------------------------------------------------------------------
+# Enums
+# ---------------------------------------------------------------------------
+
+class Exchange(StrEnum):
+    UNISWAP_V2 = "UniswapV2"
+    UNISWAP_V3 = "UniswapV3"
+
+
+class OcoMode(StrEnum):
+    NO_OCO = "NO_OCO"
+    CANCEL_ON_PARTIAL_FILL = "CANCEL_ON_PARTIAL_FILL"
+    CANCEL_ON_COMPLETION = "CANCEL_ON_COMPLETION"
+
+
+# ---------------------------------------------------------------------------
+# Supporting models
+# ---------------------------------------------------------------------------
+
+class Route(BaseModel):
+    model_config = {"extra": "forbid"}
+
+    exchange: Exchange
+    fee: Uint24 = Field(description="Pool fee tier; also used as maxFee on UniswapV3")
+
+
+class Line(BaseModel):
+    """Price line: price = intercept + slope * time. Both zero means line is disabled."""
+
+    model_config = {"extra": "forbid"}
+
+    intercept: Float
+    slope: Float
+
+
+class Tranche(BaseModel):
+    model_config = {"extra": "forbid"}
+
+    fraction: Uint16 = Field(description="Fraction of total order amount; MAX_FRACTION (65535) = 100%")
+    startTimeIsRelative: bool
+    endTimeIsRelative: bool
+    minIsBarrier: bool = Field(description="Not yet supported")
+    maxIsBarrier: bool = Field(description="Not yet supported")
+    marketOrder: bool = Field(
+        description="If true, min/max lines ignored; minLine intercept treated as max slippage"
+    )
+    minIsRatio: bool
+    maxIsRatio: bool
+    rateLimitFraction: Uint16 = Field(description="Max fraction of this tranche's amount per rate-limited execution")
+    rateLimitPeriod: Uint24 = Field(description="Seconds between rate limit resets")
+    startTime: Uint32 = Field(description="Unix timestamp; 0 (DISTANT_PAST) effectively disables")
+    endTime: Uint32 = Field(description="Unix timestamp; 4294967295 (DISTANT_FUTURE) effectively disables")
+    minLine: Line = Field(description="Traditional limit order constraint; can be diagonal")
+    maxLine: Line = Field(description="Upper price boundary (too-good-a-price guard)")
+
+
+class TrancheStatus(BaseModel):
+    model_config = {"extra": "forbid"}
+
+    filled: Uint256 = Field(description="Amount filled by this tranche")
+    activationTime: Uint32 = Field(description="Earliest time this tranche can execute; 0 = not yet concrete")
+    startTime: Uint32 = Field(description="Concrete start timestamp")
+    endTime: Uint32 = Field(description="Concrete end timestamp")
+
+
+# ---------------------------------------------------------------------------
+# Order models
+# ---------------------------------------------------------------------------
+
+class SwapOrder(BaseModel):
+    model_config = {"extra": "forbid"}
+
+    tokenIn: str = Field(pattern=ETH_ADDRESS_PATTERN, description="ERC-20 input token address")
+    tokenOut: str = Field(pattern=ETH_ADDRESS_PATTERN, description="ERC-20 output token address")
+    route: Route
+    amount: Uint256 = Field(description="Maximum quantity to fill")
+    minFillAmount: Uint256 = Field(description="Minimum tranche amount before tranche is considered complete")
+    amountIsInput: bool = Field(description="true = amount is tokenIn quantity; false = tokenOut")
+    outputDirectlyToOwner: bool = Field(description="true = proceeds go to vault owner; false = vault")
+    inverted: bool = Field(description="false = tokenIn/tokenOut price direction (Uniswap natural)")
+    conditionalOrder: Uint64 = Field(
+        description="NO_CONDITIONAL_ORDER = 2^64-1; high bit set = relative index within placement group"
+    )
+    tranches: list[Tranche] = Field(min_length=1)
+
+
+class OcoGroup(BaseModel):
+    model_config = {"extra": "forbid"}
+
+    mode: OcoMode
+    orders: list[SwapOrder] = Field(min_length=1)
+
+
+class SwapOrderStatus(BaseModel):
+    model_config = {"extra": "forbid"}
+
+    order: SwapOrder
+    fillFeeHalfBps: Uint8 = Field(description="Fill fee in half-bps (1/20000); max 255 = 1.275%")
+    canceled: bool = Field(description="If true, order is canceled regardless of cancelAllIndex")
+    startTime: Uint32 = Field(description="Earliest block.timestamp at which order may execute")
+    ocoGroup: Uint64 = Field(description="Index into ocoGroups; NO_OCO_INDEX = 2^64-1")
+    originalOrder: Uint64 = Field(description="Index of the original order in the orders array")
+    startPrice: Uint256 = Field(description="Price at order start")
+    filled: Uint256 = Field(description="Total amount filled so far")
+    trancheStatus: list[TrancheStatus]
+
+

backend/src/sync/protocol.py

@@ -0,0 +1,26 @@
+from typing import Any, Dict, List, Literal, Union
+
+from pydantic import BaseModel
+
+
+class SnapshotMessage(BaseModel):
+    type: Literal["snapshot"] = "snapshot"
+    store: str
+    seq: int
+    state: Dict[str, Any]
+
+class PatchMessage(BaseModel):
+    type: Literal["patch"] = "patch"
+    store: str
+    seq: int
+    patch: List[Dict[str, Any]]
+
+class HelloMessage(BaseModel):
+    type: Literal["hello"] = "hello"
+    seqs: Dict[str, int]
+
+# Union type for all messages from backend to frontend
+BackendMessage = Union[SnapshotMessage, PatchMessage]
+
+# Union type for all messages from frontend to backend
+FrontendMessage = Union[HelloMessage, PatchMessage]

backend/src/sync/registry.py

@@ -0,0 +1,174 @@
+from collections import deque
+from typing import Any, Dict, List, Optional, Tuple, Deque
+
+import jsonpatch
+from pydantic import BaseModel
+
+from sync.protocol import SnapshotMessage, PatchMessage
+
+
+class SyncEntry:
+    def __init__(self, model: BaseModel, store_name: str, history_size: int = 50):
+        self.model = model
+        self.store_name = store_name
+        self.seq = 0
+        self.last_snapshot = model.model_dump(mode="json")
+        self.history: Deque[Tuple[int, List[Dict[str, Any]]]] = deque(maxlen=history_size)
+
+    def compute_patch(self) -> Optional[List[Dict[str, Any]]]:
+        current_state = self.model.model_dump(mode="json")
+        patch = jsonpatch.make_patch(self.last_snapshot, current_state)
+        if not patch.patch:
+            return None
+        return patch.patch
+
+    def commit_patch(self, patch: List[Dict[str, Any]]):
+        self.seq += 1
+        self.history.append((self.seq, patch))
+        self.last_snapshot = self.model.model_dump(mode="json")
+
+    def catchup_patches(self, since_seq: int) -> Optional[List[Tuple[int, List[Dict[str, Any]]]]]:
+        if since_seq == self.seq:
+            return []
+        
+        # Check if all patches from since_seq + 1 to self.seq are in history
+        if not self.history or self.history[0][0] > since_seq + 1:
+            return None
+        
+        result = []
+        for seq, patch in self.history:
+            if seq > since_seq:
+                result.append((seq, patch))
+        return result
+
+class SyncRegistry:
+    def __init__(self):
+        self.entries: Dict[str, SyncEntry] = {}
+        self.websocket: Optional[Any] = None # Expecting a FastAPI WebSocket or similar
+
+    def register(self, model: BaseModel, store_name: str):
+        self.entries[store_name] = SyncEntry(model, store_name)
+
+    async def push_all(self):
+        import logging
+        logger = logging.getLogger(__name__)
+
+        if not self.websocket:
+            logger.warning("push_all: No websocket connected, cannot push updates")
+            return
+
+        logger.info(f"push_all: Processing {len(self.entries)} store entries")
+        for entry in self.entries.values():
+            patch = entry.compute_patch()
+            if patch:
+                logger.info(f"push_all: Found patch for store '{entry.store_name}': {patch}")
+                entry.commit_patch(patch)
+                msg = PatchMessage(store=entry.store_name, seq=entry.seq, patch=patch)
+                logger.info(f"push_all: Sending patch message for '{entry.store_name}' seq={entry.seq}")
+                await self.websocket.send_json(msg.model_dump(mode="json"))
+                logger.info(f"push_all: Patch sent successfully for '{entry.store_name}'")
+            else:
+                logger.debug(f"push_all: No changes detected for store '{entry.store_name}'")
+
+    async def sync_client(self, client_seqs: Dict[str, int]):
+        if not self.websocket:
+            return
+        
+        for store_name, entry in self.entries.items():
+            client_seq = client_seqs.get(store_name, -1)
+            patches = entry.catchup_patches(client_seq)
+            
+            if patches is not None:
+                # Replay patches
+                for seq, patch in patches:
+                    msg = PatchMessage(store=store_name, seq=seq, patch=patch)
+                    await self.websocket.send_json(msg.model_dump(mode="json"))
+            else:
+                # Send full snapshot
+                msg = SnapshotMessage(
+                    store=store_name,
+                    seq=entry.seq,
+                    state=entry.model.model_dump(mode="json")
+                )
+                await self.websocket.send_json(msg.model_dump(mode="json"))
+
+    async def apply_client_patch(self, store_name: str, client_base_seq: int, patch: List[Dict[str, Any]]):
+        import logging
+        logger = logging.getLogger(__name__)
+
+        logger.info(f"apply_client_patch: store={store_name}, client_base_seq={client_base_seq}, patch={patch}")
+
+        entry = self.entries.get(store_name)
+        if not entry:
+            logger.warning(f"apply_client_patch: Store '{store_name}' not found in registry")
+            return
+
+        logger.info(f"apply_client_patch: Current backend seq={entry.seq}")
+
+        if client_base_seq == entry.seq:
+            # No conflict
+            logger.info("apply_client_patch: No conflict - applying patch directly")
+            current_state = entry.model.model_dump(mode="json")
+            logger.info(f"apply_client_patch: Current state before patch: {current_state}")
+            new_state = jsonpatch.apply_patch(current_state, patch)
+            logger.info(f"apply_client_patch: New state after patch: {new_state}")
+            self._update_model(entry.model, new_state)
+
+            entry.commit_patch(patch)
+            logger.info(f"apply_client_patch: Patch committed, new seq={entry.seq}")
+            # Don't broadcast back to client - they already have this change
+            # Broadcasting would cause an infinite loop
+            logger.info("apply_client_patch: Not broadcasting back to originating client")
+        
+        elif client_base_seq < entry.seq:
+            # Conflict! Frontend wins.
+            # 1. Get backend patches since client_base_seq
+            backend_patches = []
+            for seq, p in entry.history:
+                if seq > client_base_seq:
+                    backend_patches.append(p)
+            
+            # 2. Apply frontend patch first to the state at client_base_seq
+            # But we only have the current authoritative model.
+            # "Apply the frontend patch first to the model (frontend wins)"
+            # "Re-apply the backend deltas that do not overlap the frontend's changed paths on top"
+            
+            # Let's get the state as it was at client_base_seq if possible? 
+            # No, history only has patches.
+            
+            # Alternative: Apply frontend patch to current model. 
+            # Then re-apply backend patches, but discard parts that overlap.
+            
+            frontend_paths = {p['path'] for p in patch}
+            
+            current_state = entry.model.model_dump(mode="json")
+            # Apply frontend patch
+            new_state = jsonpatch.apply_patch(current_state, patch)
+            
+            # Re-apply backend patches that don't overlap
+            for b_patch in backend_patches:
+                filtered_b_patch = [op for op in b_patch if op['path'] not in frontend_paths]
+                if filtered_b_patch:
+                    new_state = jsonpatch.apply_patch(new_state, filtered_b_patch)
+            
+            self._update_model(entry.model, new_state)
+            
+            # Commit the result as a single new patch
+            # We need to compute what changed from last_snapshot to new_state
+            final_patch = jsonpatch.make_patch(entry.last_snapshot, new_state).patch
+            if final_patch:
+                entry.commit_patch(final_patch)
+                # Broadcast resolved state as snapshot to converge
+                if self.websocket:
+                    msg = SnapshotMessage(
+                        store=entry.store_name,
+                        seq=entry.seq,
+                        state=entry.model.model_dump(mode="json")
+                    )
+                    await self.websocket.send_json(msg.model_dump(mode="json"))
+
+    def _update_model(self, model: BaseModel, new_data: Dict[str, Any]):
+        # Update model using model_validate for potentially nested models
+        new_model = model.__class__.model_validate(new_data)
+        for field in model.model_fields:
+            setattr(model, field, getattr(new_model, field))

backend/tests/test_websocket.py

@@ -0,0 +1,54 @@
+import asyncio
+import json
+import websockets
+import pytest
+from pydantic import BaseModel
+
+async def test_websocket_sync():
+    uri = "ws://localhost:8000/ws"
+    async with websockets.connect(uri) as websocket:
+        # 1. Send hello
+        hello = {
+            "type": "hello",
+            "seqs": {}
+        }
+        await websocket.send(json.dumps(hello))
+        
+        # 2. Receive snapshots
+        # Expecting TraderState and StrategyState
+        responses = []
+        for _ in range(2):
+            resp = await websocket.recv()
+            responses.append(json.loads(resp))
+            
+        assert any(r["store"] == "TraderState" for r in responses)
+        assert any(r["store"] == "StrategyState" for r in responses)
+        
+        # 3. Send a patch for TraderState
+        trader_resp = next(r for r in responses if r["store"] == "TraderState")
+        current_seq = trader_resp["seq"]
+        
+        patch_msg = {
+            "type": "patch",
+            "store": "TraderState",
+            "seq": current_seq,
+            "patch": [{"op": "replace", "path": "/status", "value": "busy"}]
+        }
+        await websocket.send(json.dumps(patch_msg))
+        
+        # 4. Receive confirmation patch
+        confirm_resp = await websocket.recv()
+        confirm_json = json.loads(confirm_resp)
+        assert confirm_json["type"] == "patch"
+        assert confirm_json["store"] == "TraderState"
+        assert confirm_json["seq"] == current_seq + 1
+        assert confirm_json["patch"][0]["value"] == "busy"
+
+if __name__ == "__main__":
+    # This script requires the server to be running:
+    # PYTHONPATH=backend/src python3 backend/src/main.py
+    try:
+        asyncio.run(test_websocket_sync())
+        print("Test passed!")
+    except Exception as e:
+        print(f"Test failed: {e}")

bin/build

@@ -0,0 +1,4 @@
+#!/bin/bash
+
+docker build -f deploy/Dockerfile -t dexorder-ai:latest .
+# todo push to archive

bin/charting_library_update

@@ -0,0 +1,36 @@
+#!/bin/bash
+set -euo pipefail
+
+REMOTE_NAME="tradingview-charting"
+REMOTE_URL="git@github.com:tradingview/charting_library.git"
+PREFIX="web/public/charting_library"
+BRANCH="master"
+
+# Detect the default branch if master doesn't exist
+echo "Adding remote '$REMOTE_NAME'..."
+if git remote get-url "$REMOTE_NAME" &>/dev/null; then
+  echo "Remote '$REMOTE_NAME' already exists, skipping."
+else
+  git remote add "$REMOTE_NAME" "$REMOTE_URL"
+fi
+
+echo "Fetching from $REMOTE_URL (this may take a moment)..."
+git fetch "$REMOTE_NAME" "$BRANCH"
+
+if [ -d "$PREFIX" ]; then
+  echo "'$PREFIX' already exists — pulling latest changes..."
+  git subtree pull \
+    --prefix="$PREFIX" \
+    "$REMOTE_NAME" "$BRANCH" \
+    --squash \
+    -m "chore: update charting_library from tradingview upstream"
+else
+  echo "Adding '$PREFIX' for the first time..."
+  git subtree add \
+    --prefix="$PREFIX" \
+    "$REMOTE_NAME/$BRANCH":charting_library \
+    --squash \
+    -m "chore: add charting_library from tradingview/charting_library"
+fi
+
+echo "Done. Files are at: $PREFIX"

deploy/Dockerfile-backend

@@ -0,0 +1,3 @@
+FROM python:3.14-alpine
+
+COPY python/src /app/src

doc/data.md

@@ -0,0 +1,21 @@
+# Data Sources and ETL
+
+We'll use Pandas and ArcticDB as our data foundation. This gives easy access to numpy and a wide spectrum of Python analysis libraries.
+
+ArcticDB
+[ArcticDB](https://arcticdb.com/)
+We'll use unstructured dynamic schemas for flexibility and ad-hoc adjustment by the assistant.
+
+## Canonical Formats
+* OHLCV
+  * columns
+  * open_time high_time etc optional columns
+* Tick Data (later not now)
+* Order Book Data (later not now)
+
+## Symbol Definition
+Symbols must follow a canonical formatting that provides a unique string identifier:
+
+type|...(type dependent)...
+ohlc|exchange:base/quote
+

doc/design.md

@@ -0,0 +1,65 @@
+# AI-Native Trading Platform
+
+## Summary
+
+A full-stack, AI-first algorithmic trading platform in which LLMs act as strategy *authors* rather than strategy *executors*. Human traders express intent through natural language, chart drawings, and annotated support/resistance levels via chat or TradingView; an LLM agent interprets this intent and composes a fully self-contained **strategy executable** — a versioned, schema-validated artifact that runs deterministically with zero LLM involvement at runtime or in backtesting.
+
+The execution architecture is split into two nested kernels. The **strategy kernel** owns the complete mechanics of a strategy: signal DAG evaluation, position state, risk rules, and regime awareness, operating at strategy latency. It drives the **order kernel** — a minimal, fully-specified order state machine designed for deterministic, low-latency execution, in principle deployable to FPGA or kernel-bypass hardware. The two kernels communicate across a hard schema boundary, keeping the hot path free of any high-level logic.
+
+Data is handled through an abstract **feed specification** that treats historical and realtime, structured and unstructured sources uniformly. All signal computation — including NLP-based sentiment and on-chain analytics — uses local models only; the LLM is strictly a design-time tool.
+
+The platform is designed to be run **locally by the trader** for execution security, while strategy generation may be cloud-assisted. It leverages the Python data science ecosystem throughout, integrates with TradingView for chart-driven strategy authoring, and exposes multiple interaction surfaces including chat bots and JupyterLab notebooks. The local executable may still have strong dependencies on a centralized data cluster and logging facility.
+
+## Data
+
+* **Data source spec** — Abstract interface for historical (bulk/batch) and incremental (realtime) data, supporting both push and pull models, fully async. Sources are typed and versioned; any conforming adapter (REST, WebSocket, FIX, file, queue) plugs in identically.
+* **ETL pipeline** — Reusable transform/load tooling for normalizing raw source data into platform schemas, and as agent-callable tools for composing bespoke derived series on demand.
+* **Common schemas** — Canonical normalized forms: OHLCV, tick, order book (L1/L2/L3), trade prints, funding rates, open interest. Unstructured feeds (news, social, on-chain) carry a typed envelope with a payload and a platform-standard timestamp/symbol context.
+* **Feed registry** — Central catalog of available feeds with their schemas, latency class, and asset coverage. Both the agent layer and the execution kernel subscribe by feed ID, decoupled from transport.
+
+## Indicators & Signals
+
+* **Standard indicator library** — Common indicators (moving averages, VWAP, RSI, ATR, Bollinger, volume profile, etc.) implemented against the canonical schema. Stateless functions and stateful streaming variants both available.
+* **Custom signals in Python** — Arbitrary user/agent-defined signal nodes. Must conform to a standard `SignalNode` interface (inputs, outputs, params, `evaluate()`) so they are composable in the signal DAG and serializable into strategy executables.
+* **Unstructured signal pipeline** — Adapters that transform unstructured feeds into scalar or categorical signal outputs (e.g. FinBERT sentiment → float, on-chain anomaly detector → bool). Runs local models only; no LLM at signal evaluation time.
+
+## Strategy Kernel
+
+The outermost execution layer. Owns the complete mechanics of a strategy: signal DAG evaluation, position and risk state, regime awareness, and re-parameterization of the order kernel. Operates at human/strategy latency (milliseconds to seconds).
+
+* **Signal DAG** — Directed acyclic graph of signal nodes wired to feed subscriptions. Evaluated incrementally on new data. Nodes are typed, versioned, and serializable.
+* **Strategy state machine** — Tracks lifecycle: `IDLE → LOOKING → ENTERED → MANAGING → EXITED`. Transitions driven by signal DAG outputs and risk constraints.
+* **Risk layer** — Position sizing, exposure limits, drawdown circuit breakers, correlation guards. Evaluated before any order is emitted downward to the order kernel.
+* **Re-parameterization interface** — The strategy kernel may update order kernel parameters (price, size, urgency, validity) in response to new signal outputs without tearing down open orders — a clean boundary between strategic intent and mechanical execution.
+* **Strategy executable format** — The complete strategy (DAG topology, parameters, risk rules, feed subscriptions) is serialized to a self-contained artifact (YAML + optional Python modules). Generated by the agent layer; runnable with zero LLM dependency.
+* **Strategy Log** — A structured, append-only log of strategy events, including signal outputs, risk evaluations, and order parameter changes. Facilitates debugging, backtesting, and compliance auditing.
+
+## Order Kernel
+
+The innermost execution layer. Represents a single, fully specified order intent and manages its lifecycle mechanically. Designed for deterministic, low-latency operation — in principle implementable in an FPGA or a kernel-bypass network stack.
+
+* **Order specification** — Fully parameterized: symbol, side, type (market/limit/stop/conditional), price(s), size, time-in-force, validity window, venue routing hint. No ambiguity; all fields resolved before submission.
+* **Order lifecycle** — State machine: `PENDING → SUBMITTED → PARTIALLY_FILLED → FILLED | CANCELLED | REJECTED`. Transitions driven by exchange acknowledgements and fill reports.
+* **Timer primitives** — Deadline timers (cancel-on-expire), heartbeat timers (re-quote), and interval timers (TWAP/VWAP slice scheduling). All timers are pure data, evaluatable without process context.
+* **Venue adapter interface** — Thin, typed interface to exchange connectivity (FIX, REST, WebSocket, on-chain). The order kernel emits a normalized order; the adapter translates to venue wire format.
+* **FPGA / low-latency boundary** — The order spec and lifecycle state machine are designed with a hard schema so they can be frozen and handed off to a hardware execution path. The strategy kernel communicates to this boundary via a defined message contract, not shared memory or function calls.
+* **Order Log** — A structured, append-only log of order events, including submission, fill, and cancellation details. Facilitates debugging, backtesting, and compliance auditing.
+* **Credentials Store** — Secure storage for API keys, wallet keys, secrets, and other sensitive information. Available only to the order kernel and no other layer.
+
+## Agent Layer
+
+The LLM-powered strategy authoring environment. Cloud-hosted or local. Produces strategy executables; never participates in live execution or backtesting hot paths.
+
+* **Tool framework** — Typed, schema-validated tools callable by the LLM: `query_chart`, `compute_indicator`, `detect_sr_levels`, `fetch_news_sentiment`, `annotate_drawing`, `compose_signal_node`, `emit_strategy`. Each tool has a `to_executable_node()` method so its output can be frozen into the strategy artifact.
+* **TradingView integration** — Drawing/annotation export (trend lines, SR levels, zones, Fibonacci) ingested as structured JSON, interpreted by the agent into signal DAG nodes (e.g. `sr_proximity`, `trendline_cross`).
+* **Context manager** — Maintains the trader's working session: active symbol, timeframe, chart drawings, prior signal definitions, risk preferences. Persisted across turns; fed as structured context to each LLM call.
+* **Strategy compiler** — Takes the agent's composed tool outputs and renders a validated, schema-checked strategy executable. Validation errors are reflected back to the agent for self-correction before the artifact is finalized.
+* **Prompt/strategy versioning** — Every generated strategy artifact is version-controlled (git). The generating prompt, model version, and tool call trace are stored alongside the artifact for full auditability.
+
+## Interaction Layer
+
+How traders communicate with the system. Multiple surfaces; all feed the same agent layer.
+
+* **Chat interface** — Discord, Telegram, or Slack bot. Accepts natural language, images of charts, TradingView drawing exports. Returns chart images, strategy summaries, backtest results. Primary low-friction UI.
+* **Notebook interface** — JupyterLab environment for power users. Full access to the data layer, indicator library, and agent tools. Chart generation (Plotly/Bokeh) for rich visual feedback, with outputs forwardable to chat channels.
+* **TradingView plugin** — Embeds into an existing TradingView-based website

doc/libraries.md

@@ -0,0 +1,3 @@
+ArcticDB
+[ArcticDB](https://arcticdb.com/)
+We'll use unstructured dynamic schemas.

doc/mvp.md

@@ -0,0 +1,32 @@
+# Minimum Viable Prototype
+
+* Chat interface: slack/telegram/whatsapp etc
+* Agent loop
+  * Memory
+  * RAG
+  * System Prompt
+    * Soul / Mission
+    * Current chart candles
+    * TV Shapes
+    * AI self-prompt
+    * User Prompt
+* Agent tools
+  * Edit strategy code
+  * Read/Write TradingView shapes
+  * Fetch data
+  * TradingView Snapshot
+  * Plotting
+  * Cron
+  * Docker, never host access
+  * Edit AI self-prompt
+* One candle data source: Dexorder
+* Python data science stack with charts
+* Indicator library
+* Standard historical backtest
+* Strategy wrapper / sandbox
+* One execution engine: Dexorder
+* Website
+  * TradingView interaction
+  * Authentication
+  * Settings / Prompts
+  * Chat area with image support and zoom

web/.gitignore

@@ -0,0 +1,39 @@
+# Logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+lerna-debug.log*
+
+node_modules
+.DS_Store
+dist
+dist-ssr
+coverage
+*.local
+
+# Editor directories and files
+.vscode/*
+!.vscode/extensions.json
+.idea
+*.suo
+*.ntvs*
+*.njsproj
+*.sln
+*.sw?
+
+*.tsbuildinfo
+
+.eslintcache
+
+# Cypress
+/cypress/videos/
+/cypress/screenshots/
+
+# Vitest
+__screenshots__/
+
+# Vite
+*.timestamp-*-*.mjs

web/env.d.ts

@@ -0,0 +1 @@
+/// <reference types="vite/client" />

web/index.html

@@ -0,0 +1,14 @@
+<!DOCTYPE html>
+<html lang="" class="dark">
+  <head>
+    <meta charset="UTF-8">
+    <link rel="icon" href="/favicon.ico">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Vite App</title>
+    <script type="text/javascript" src="/charting_library/charting_library.standalone.js"></script>
+  </head>
+  <body>
+    <div id="app"></div>
+    <script type="module" src="/src/main.ts"></script>
+  </body>
+</html>

web/package.json

@@ -0,0 +1,43 @@
+{
+  "name": "web",
+  "version": "0.0.0",
+  "private": true,
+  "type": "module",
+  "scripts": {
+    "dev": "vite",
+    "build": "run-p type-check \"build-only {@}\" --",
+    "preview": "vite preview",
+    "test:unit": "vitest",
+    "build-only": "vite build",
+    "type-check": "vue-tsc --build"
+  },
+  "dependencies": {
+    "@primevue/themes": "^4.5.4",
+    "fast-json-patch": "^3.1.1",
+    "pinia": "^3.0.4",
+    "primeicons": "^7.0.0",
+    "primevue": "^4.5.4",
+    "vue": "^3.5.29",
+    "vue-advanced-chat": "^2.0.4",
+    "vue-router": "^5.0.3"
+  },
+  "devDependencies": {
+    "@tsconfig/node24": "^24.0.4",
+    "@types/jsdom": "^28.0.0",
+    "@types/node": "^24.10.13",
+    "@vitejs/plugin-vue": "^6.0.4",
+    "@vitejs/plugin-vue-jsx": "^5.1.4",
+    "@vue/test-utils": "^2.4.6",
+    "@vue/tsconfig": "^0.8.1",
+    "jsdom": "^28.1.0",
+    "npm-run-all2": "^8.0.4",
+    "typescript": "~5.9.3",
+    "vite": "^7.3.1",
+    "vite-plugin-vue-devtools": "^8.0.6",
+    "vitest": "^4.0.18",
+    "vue-tsc": "^3.2.5"
+  },
+  "engines": {
+    "node": "^20.19.0 || >=22.12.0"
+  }
+}

web/public/charting_library/bundles/1065.d8e66f4c4d6c2e5e9e51.css

@@ -0,0 +1 @@
+.checkbox-WcA5vXoU{align-self:start;font:inherit}.description-CQ7tC6Wp{margin-bottom:16px}

web/public/charting_library/bundles/1065.d8e66f4c4d6c2e5e9e51.rtl.css

@@ -0,0 +1 @@
+.checkbox-WcA5vXoU{align-self:start;font:inherit}.description-CQ7tC6Wp{margin-bottom:16px}

web/public/charting_library/bundles/1166.fa77c9e386a131cac9da.css

@@ -0,0 +1 @@
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web/public/charting_library/bundles/1166.fa77c9e386a131cac9da.rtl.css

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web/public/charting_library/bundles/1450.8f1c6b9900df1caf5e97.css

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web/public/charting_library/bundles/1450.8f1c6b9900df1caf5e97.rtl.css

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web/public/charting_library/bundles/1485.62487782be5544fea53d.js

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+;const n=this._study.nearestIndex(r,e,i.index+1);if(void 0===n)continue;const a=n+this._study.offset(i.id);s=null!==s?Math.max(a,s):a}}(null===e||null!==s&&e>s)&&(e=s);const l=this._hideValues(),h=this._study.isVisible()&&!l?_.notAvailable:"";for(const e of t)e.value=h;if(l)return t;y&&t.length&&(t[t.length-1].value="");const u=this._study.priceScale();if(!this._study.isVisible()||null===e||null===u||u.isEmpty()||this._model.timeScale().isEmpty())return t;const f={};for(const s of t){const t=s.id,l=(0,d.getPriceValueFormatterForStudy)(this._study,t),h=(0,p.ensureDefined)(o.styles.childs()[t]),u=h.childs().display.value();if(s.visible=0!==u,!s.visible)continue;const _=h.hasChild("plottype")?h.child("plottype")?.value():null,m=this._searchNearestLeft&&this._isFundamental&&(_===c.LineStudyPlotStyle.StepLine||_===c.LineStudyPlotStyle.StepLineWithDiamonds),y=s.index,g=e-this._study.offset(t),v=m||null!==r&&g>r?a.PlotRowSearchMode.NearestLeft:a.PlotRowSearchMode.Exact,S=this._study.nearestIndex(g,v);if(void 0===S)continue;let b=f[t];if(void 0===b&&(b=this._study.getMinFirstBarIndexForPlot(t),Number.isFinite(b)&&(f[t]=b)),b>S)continue;const P=this._study.data().last(),w=this._study.data().valueAt(S)||(null!==P?P.value:null);if(null===w)continue;const I=w[y+1];(0,i.isNumber)(I)&&(s.value=l(I),s.color=(0,n.resetTransparency)(this.getPlotColor(y,w)))}return t}_hideValues(){return g?(0,l.isLineToolName)(h.tool.value())||null!==this._model.lineBeingEdited():m&&(null===this._model.crosshairSource().pane||(0,l.isLineToolName)(h.tool.value())||null!==this._model.lineBeingEdited())}}},11485:(e,t,s)=>{s.r(t),s.d(t,{StudiesChunkName:()=>Yt,Study:()=>us,emptyPrecalculatedAutoscaleInfo:()=>qt,studyFormatter:()=>hs});var i=s(50279),r=s(90054),n=s(16738),o=s(15943);const a=e=>e instanceof Date,l=e=>null!=e&&"object"==typeof e,h=(e,...t)=>Object.prototype.hasOwnProperty.call(e,...t),c=e=>l(e)&&(e=>0===Object.keys(e).length)(e),u=(e,t)=>{if(e===t)return{};if(!l(e)||!l(t))return t;const s=Object.keys(e).reduce(((e,s)=>(h(t,s)||(e[s]=void 0),e)),Object.create(null));return a(e)||a(t)?e.valueOf()==t.valueOf()?{}:t:Object.keys(t).reduce(((s,i)=>{if(!h(e,i))return s[i]=t[i],s;const r=u(e[i],t[i]);return!c(r)||a(r)||!c(e[i])&&c(t[i])?(s[i]=r,s):s}),s)},d=u;var p=s(50151),_=s(87465),f=s(9343),m=s(11542),y=s(12217),g=s(62312);function v(e){const{name:t,group:s}=e;return t.length>0?`${s?`${s}.`:""}${t}`:void 0}var S=s(10341),b=s(22613),P=s(62773),w=s(48096),I=s(52859),x=s(82130),C=s(29806),V=s(67135),M=(s(2088),s(24062)),T=s(72187),A=s(19844),R=s(45530),O=s(5471),D=s(18330),B=s(70954),N=s(40472),F=s(71320),k=s(63002);class E{constructor(e,t,s,i){this._study=e,this._model=t,this._showStudyValues=i??t.properties().childs().paneProperties.childs().legendProperties.childs().showStudyValues,this._hhistBasedStudy=void 0!==e.metaInfo().graphics.hhists,this._valuesProvider=this._createValuesProvider(e,t,s)}getItems(){return this._valuesProvider.getItems()}getValues(e){
+const t=this._valuesProvider.getValues(e),s=this._study.properties(),i=this._showStudyValues.value()&&s.childs().showLegendValues.value(),r=e=>!!this._hhistBasedStudy||this._study.isPlotVisibleAt(e,8);for(const e of t)e.visible=e.visible&&i&&r(e.id);return t}_createValuesProvider(e,t,s){return this._hhistBasedStudy?new k.HHistBasedValuesProvider(e,t,s):new F.StudyValuesProvider(e,t,s)}}var L=s(4359);class H extends B.StudyBaseWindowView{constructor(e,t){super(e,t),this._showStudyValues=t.properties().childs().paneProperties.childs().legendProperties.childs().showStudyValues,this._showStudyValues.subscribe(this,(()=>this.update((0,N.sourceChangeEvent)(e.id()))));const s=this._study.properties();s.childs().showLegendValues.subscribe(this,(()=>this.update((0,N.sourceChangeEvent)(e.id()))));const i=this._study.metaInfo().plots,r=new Set;i.forEach((t=>{if((0,L.isOhlcPlot)(t)){const i=t.target;if(r.has(i))return;r.add(i),s.childs().ohlcPlots.childs()[i].childs().display.subscribe(this,(()=>this.update((0,N.sourceChangeEvent)(e.id()))))}else(0,L.isPlotSupportDisplay)(t)&&s.childs().styles.childs()[t.id]?.childs().display.subscribe(this,(()=>this.update((0,N.sourceChangeEvent)(e.id()))))}))}areValuesVisible(){return this._showStudyValues.value()}additional(){return null}destroy(){this._showStudyValues.unsubscribeAll(this);const e=this._study.properties();e.childs().showLegendValues.unsubscribeAll(this);const t=this._study.metaInfo().plots,s=new Set;t.forEach((t=>{if((0,L.isOhlcPlot)(t)){const i=t.target;if(s.has(i))return;s.add(i),e.childs().ohlcPlots.childs()[i].childs().display.unsubscribeAll(this)}else(0,L.isPlotSupportDisplay)(t)&&e.childs().styles.childs()[t.id]?.childs().display.unsubscribeAll(this)}))}_createValuesProvider(e,t){return new E(e,t)}}var W=s(78861),z=s(80671),U=s(60911),j=s(87163),G=s(98155),$=s(12965);class K{constructor(e,t,s){this._study=e,this._model=t,this._valuesProvider=new F.StudyValuesProvider(e,t,s)}getItems(){return this._valuesProvider.getItems()}getValues(e){const t=this._valuesProvider.getValues(e),s=e=>this._study.isPlotVisibleAt(e,8)||this._study.isPlotVisibleAt(e,1);for(const e of t)e.visible=e.visible&&s(e.id);return t}}var Y=s(36313),X=s(67455);function q(e,t){return e.studyId.localeCompare(t.studyId)}function J(e){const t=new Set,s=[];return e.forEach((e=>{t.has(e.studyId)||(t.add(e.studyId),s.push(e))})),s}function Z(e){const t=e.model().mainSeries();return{studyId:(0,p.ensureNotNull)(e.sourceId()),turnaround:e.turnaround(),sourceStudies:e.parentSources().filter((e=>e!==t)).map((e=>Z(e)))}}var Q=s(69422),ee=s(37103),te=s(94602),se=s(10307);class ie extends se.BitmapCoordinatesPaneRenderer{constructor(e){super(),this._data=e}hitTest(e){return null}_drawImpl(e){}_drawBackgroundImpl(e){const{context:t,horizontalPixelRatio:s,bitmapSize:i}=e,r=this._data;for(let e=0;e<r.items.length;++e){const n=r.items[e];if(null==n.color)continue;t.fillStyle=n.color;const o=Math.round(n.left*s)+1,a=Math.round(n.right*s);t.fillRect(o,0,a-o+1,i.height)}}}var re=s(41425),ne=s(17631)
+;class oe extends ne.StudyForceOverlayPlotView{constructor(e,t,s,i){super(t,s,i),this._items=[],this._invalidated=!0,this._isMarkersEnabled=ee.enabled("source_selection_markers"),this._study=e;const r=this._study.metaInfo().plots;for(let e=0;e<r.length;e++){const t=r[e];t.id===this._plotName&&(this._plotIndex=e,(0,p.assert)((0,L.isBgColorerPlot)(t),"Plot '"+this._plotName+"' is not a background colorer!"))}this._colorProvider=(0,re.createStudyPlotColorProvider)(e.metaInfo(),e.properties(),i)}items(){return this._items}update(e){"hover-change"!==e.type&&(this._invalidated=!0)}renderer(){if(1&~(0,p.ensureDefined)(this._study.properties().childs().styles.childs()[this._plotName]).childs().display.value())return null;if(!this._scalesReady())return null;this._invalidated&&(this._updateImpl(),this._invalidated=!1);const e={items:this._items},t=new te.CompositeRenderer;return t.append(new ie(e)),t}_scalesReady(){const e=this._model.timeScale(),t=this._priceScale();return e&&!e.isEmpty()&&null!==t&&!t.isEmpty()}_getTranspValue(){const e=(0,p.ensureDefined)(this._study.properties().childs().styles.childs()[this._plotName]).childs();let t=0;return e.transparency&&(t=e.transparency.value(),t=(0,_.isNumber)(t)?t:40),t}_updateImpl(){this._items=[],(0,p.assert)(this._scalesReady(),"Scales must be ready!");const e=this._model.timeScale().visibleBarsStrictRange();if(null===e)return;const t=this._getTranspValue();let s=(0,p.ensureDefined)(this._series.nearestIndex(e.firstBar(),O.PlotRowSearchMode.NearestRight)),i=(0,p.ensureDefined)(this._series.nearestIndex(e.lastBar(),O.PlotRowSearchMode.NearestLeft));const r=this._study.offset(this._plotName);r>0?(s-=r,i+=r):(s+=r,i-=r);const n=this._study.getMinFirstBarIndexForPlot(this._plotName);if(n>i)return;s=Math.max(n,s);const o=this._study.data();for(const e of o.rangeIterator(s,i)){let s=e.index;const i=e.value;s+=r;const n={timePointIndex:Math.floor(s),left:NaN,center:NaN,right:NaN};let o=(0,_.isNumber)(t)?t:50;o=Math.min(o,100),o=Math.max(o,0);const a=this._colorProvider.getPlotPointStyle(i);void 0!==a.colors[1]&&(n.color=(0,I.generateColor)((0,p.ensureDefined)(a.colors[1]),o)),this._items.push(n)}this._model.timeScale().fillBarBorders(this._items)}}var ae,le=s(89323),he=s(45801),ce=s(51752),ue=s(77914),de=s(13173),pe=s(52746),_e=s(26705),fe=s(10555),me=s(6453),ye=s(50335),ge=s(50605),ve=s(2383),Se=s(45720),be=s(49251),Pe=s(27714),we=s(33350);!function(e){e.Left="left",e.Center="center",e.Right="right"}(ae||(ae={}));const Ie=(0,we.createDisconnectedCanvas)(document,(0,Pe.size)({width:0,height:0}),1);class xe{constructor(e,t,s,i,r,n="center",o=0){this._lines=e.split(/[^\S\r\n]*(?:\r\n|\r|\n)/),this._font=function(e,t,s,i){return(0,be.makeFont)(i,s,`${e?"bold ":""}${t?"italic ":""}`)}(t,s,i,r),this._fontSize=r,this._verticalPadding=~~(r/6),this._textAlign=n,this._lineSpacing=o;const a=(0,p.ensureNotNull)(Ie.getContext("2d"));a.font=this._font,a.textBaseline="top";let l=0;for(let e=0;e<this._lines.length;++e){const t=this._lines[e],s=a.measureText(t).width;l=Math.max(l,s)}
+this.textImageWidth=l+1,this.textImageHeight=this._lines.length*r+(this._lines.length-1)*this._lineSpacing+this._verticalPadding}paintTo(e,t){const{context:s,horizontalPixelRatio:i,verticalPixelRatio:r}=e;s.save();const n=t.location;s.translate(Math.round(function(e,t,s){let i=e;switch(t){case"left":break;case"right":i-=s;break;case"center":i-=s/2}return Math.round(i)}(n.x,n.horzAlign,this.textImageWidth)*i),Math.round(function(e,t,s){let i=e;switch(t){case"top":break;case"bottom":i-=s;break;case"middle":i-=s/2}return Math.round(i)}(n.y,n.vertAlign,this.textImageHeight)*r));const o=t.style;let a;switch(s.textBaseline="top",s.font=this._font,s.lineJoin="round",s.fillStyle=o.fillStyle,o.strokeStyle&&(s.strokeStyle=o.strokeStyle),o.lineWidth&&(s.lineWidth=o.lineWidth),this._textAlign){case"left":a=0,s.textAlign="left";break;case"right":a=this.textImageWidth-1,s.textAlign="right";break;default:a=this.textImageWidth/2,s.textAlign="center"}let l=this._verticalPadding;(0,we.drawScaled)(s,i,r,(()=>{for(const e of this._lines)o.strokeStyle&&s.strokeText(e,a,l),s.fillText(e,a,l),l+=this._fontSize,l+=this._lineSpacing})),s.restore()}}class Ce extends Se.AbstractMapContainer{constructor(e){super(),this._maxSize=e,this._keysQueue=[]}get(e){const{fontSize:t,text:s,align:i,font:r,bold:n,italic:o,lineSpacing:a=0}=e;if(!s||!t||!i)return null;const l=(0,be.makeFont)(t,r,o?"italic":"",n?"bold":""),h=(0,Se.getDefault3)(this._map,a,i,l,new Map);let c=h.get(s);return void 0!==c||(this._size>=this._maxSize?this._deleteFirstKey():++this._size,this._keysQueue.push([l,i,a,s]),c=new xe(s,n,o,r,t,i,a),h.set(s,c)),c}_deleteFirstKey(){const e=this._keysQueue.shift(),[t,s,i,r]=e,n=(0,p.ensureDefined)(this._map.get(i)),o=(0,p.ensureDefined)(n.get(s)),a=(0,p.ensureDefined)(o.get(t));a.delete(r),0===a.size&&o.delete(t),0===o.size&&n.delete(s),0===n.size&&this._map.delete(i)}}var Ve,Me=s(84617),Te=s(49483);!function(e){e.Transparent="rgba(0, 0, 0, 0)"}(Ve||(Ve={}));class Ae extends se.BitmapCoordinatesPaneRenderer{constructor(e,t={skipRenderingOptimizations:!1}){super(),this._items=[],this._barSpacing=0,this._vertOffset=0,this._textCache=t.textCache||new Ce(5e3),this._drawOperation=t.skipRenderingOptimizations?this._drawWithoutOptimizations.bind(this):this._drawWithOptimizations.bind(this),null!==e&&this.setData(e)}hitTest(e){const t=ve.HitTarget.Regular;let s=null;for(const i of this._items){if(!i)continue;const r=this._calcBoundingBox(i);if(r&&(0,me.pointInBox)(e,r)){const e={tooltip:this._getTooltip(i,r)};s=new ve.HitTestResult(t,e)}}return s}setData(e){if(this._height=void 0!==e.height?e.height:e.width,this._width=void 0!==e.width?e.width:e.height,this._color=e.color,this._borderColor=e.borderColor,this._vertOffset=e.vertOffset||0,e.text&&(this._text=e.text,this._fontSize=e.fontSize,this._lineSpacing=e.lineSpacing,this._textColor=e.textColor,this._textAlign=e.textAlign||"center"),void 0!==e.items&&void 0!==e.barSpacing){const t=e.visibleItemsRange?.startItemIndex??0,s=e.visibleItemsRange?.endItemIndex??e.items.length
+;this.setItems(s>t?e.items.slice(t,s):[],e.barSpacing)}}setItems(e,t){this._setBaseData(e,t)}_drawImpl(e){this._preDrawInit(),this._drawOperation(e)}_calcBoundingBox(e){const t=e.vertOffset,s=this._getTextCache(e);if(!s)return;const i=s.textImageWidth,r=s.textImageHeight,n=i/2,o=e.y+t+e.textVertOffset,a=t>0?0:-r,l=t>0?r:0,h=new fe.Point(e.center-n,o+a),c=new fe.Point(e.center+n,o+l);return(0,fe.box)(h,c)}_unionBox(e,t){const s=Math.min(e.min.x,t.min.x),i=Math.max(e.max.x,t.max.x),r=Math.min(e.min.y,t.min.y),n=Math.max(e.max.y,t.max.y),o=new fe.Point(s,r),a=new fe.Point(i,n);return(0,fe.box)(o,a)}_getTooltip(e,t){if(e.tooltip)return{content:{type:"text",data:e.tooltip},tooltipDelay:200,extendMargin:!0,rect:{x:t.min.x,y:t.min.y,w:Math.abs(t.max.x-t.min.x),h:Math.abs(t.max.y-t.min.y)}}}_setBaseData(e,t){this._items.length=0,this._barSpacing=t;for(const t of e){if((0,ye.isNaN)(t.y))continue;const e=void 0===t.width?(0,p.ensureDefined)(this._width):t.width,s=void 0===t.height?(0,p.ensureDefined)(this._height):t.height,i=void 0===t.vertOffset?this._vertOffset:t.vertOffset,r=i>0?s:-s;this._items.push({width:e,height:s,vertOffset:i,textVertOffset:r,shapeWidth:0,shapeHeight:0,stepX:0,stepY:0,...t})}}_drawItemText(e,t){const s=this._getTextCache(t);if(null===s)return;const i=t.center,r=t.vertOffset,n=t.y+r+t.textVertOffset;let o;o=t.style&&void 0!==t.style.textColor?t.style.textColor:this._textColor;const a={style:{fillStyle:o},location:{x:i,y:n,horzAlign:ge.HorizontalAlign.Center,vertAlign:r>0?ge.VerticalAlign.Top:ge.VerticalAlign.Bottom}};s.paintTo(e,a)}_drawWithOptimizations(e){let t,s,i=null,r=!1;for(const n of this._items)(0,ye.isNaN)(n.y)||(n.style&&void 0!==n.style.color?(t=n.style.color||"rgba(0, 0, 0, 0)",s=n.style.borderColor||"rgba(0, 0, 0, 0)"):(t=this._color,s=this._borderColor),(i!==t||Te.isSafari)&&(i=t,r&&this._endPath(e),this._startPath(e,t,s)),this._drawItemShape(e,n),r=!0);r&&this._endPath(e);for(const t of this._items)(0,ye.isNaN)(t.y)||this._drawItemText(e,t)}_drawWithoutOptimizations(e){let t,s;for(const i of this._items){if((0,ye.isNaN)(i.y))continue;const r=(0,p.ensureDefined)(i.style);t=r.color||"rgba(0, 0, 0, 0)",s=r.borderColor||"rgba(0, 0, 0, 0)",this._startPath(e,t,s),this._drawItemShape(e,i),this._endPath(e),this._drawItemText(e,i)}}_drawItemShape(e,t){const{context:s,horizontalPixelRatio:i,verticalPixelRatio:r}=e;(0,we.drawScaled)(s,i,r,(()=>this._drawItemShapeUsingCSSPixels(s,t)))}_drawItemShapeUsingCSSPixels(e,t){}_preDrawInit(){}_startPath(e,t,s){}_endPath(e){}_getTextCache(e){const t=e.text||this._text,s=e.fontSize||this._fontSize,i=e.lineSpacing??this._lineSpacing,r=e.textAlign||this._textAlign,n=e.font??Me.CHART_FONT_FAMILY,o=e.bold??!1,a=e.italic??!1;return this._textCache.get({text:t,bold:o,italic:a,font:n,fontSize:s,lineSpacing:i,align:r})}}class Re extends Ae{_startPath(e,t,s){const i=e.context;i.beginPath(),i.lineWidth=this._lineWidth(e),i.lineCap="butt",i.strokeStyle=t}_endPath(e){e.context.stroke()}_lineWidth(e){return Math.max(1,Math.floor(2*e.horizontalPixelRatio))}}
+class Oe extends Ae{_startPath(e,t,s){const i=e.context;i.beginPath(),i.lineWidth=this._lineWidth(e),i.lineCap="butt",i.fillStyle=t,i.strokeStyle=s}_endPath(e){const t=e.context;t.fill(),t.stroke()}_lineWidth(e){return Math.max(1,Math.floor(e.horizontalPixelRatio))}}class De extends Oe{constructor(){super(...arguments),this._sign=0,this._thinArrow=!1,this._thinArrowLineWidth=0,this._headHeight=0,this._arrowWidth=0}setItems(e,t){this._setBaseData(e,t)}_drawItemShape(e,t){const{context:s,horizontalPixelRatio:i,verticalPixelRatio:r}=e,n=this._lineWidth(e)%2?.5:0,o=this._sign,a=this._arrowWidth,l=this._headHeight,h=Math.abs(t.height),c=Math.round(t.center*i)+n,u=t.vertOffset,d=Math.round((t.y+u+o*h/2)*r)+n,p=(0,ue.ceiledEven)(a*i),_=p/2,f=Math.round(h*r),m=Math.round(l*r);s.translate(c,d),this._thinArrow?(s.moveTo(0,0),s.lineTo(-_,-_*o),s.moveTo(0,0),s.lineTo(_,-_*o),s.moveTo(0,0),s.lineTo(0,-f*o),s.moveTo(-_,-f*o),s.lineTo(_,-f*o)):(s.moveTo(0,0),f<m?(s.lineTo(p,-f*o),s.lineTo(-p,-f*o)):(s.lineTo(p,-m*o),s.lineTo(_,-m*o),s.lineTo(_,-f*o),s.lineTo(-_,-f*o),s.lineTo(-_,-m*o),s.lineTo(-p,-m*o)),s.lineTo(0,0)),s.translate(-c,-d)}_preDrawInit(){const e=this._calculateWidth();this._arrowWidth=e,this._sign=this._isUp()?-1:1,this._thinArrow=e<4,this._thinArrowLineWidth=Math.max(e/2,1),this._headHeight=Math.round(e)}_startPath(e,t,s){const i=e.context;i.beginPath(),i.fillStyle=t,i.strokeStyle=s,i.lineWidth=this._lineWidth(e)}_lineWidth(e){return this._thinArrow?this._thinArrowLineWidth:super._lineWidth(e)}_calcBoundingBox(e){const t=e.vertOffset,s=this._sign,i=this._arrowWidth,r=this._headHeight,n=Math.abs(e.height),o=e.center-i,a=o+2*i,l=e.y+t+s*Math.round(n/2),h=l+(-n-r)*s,c=new fe.Point(o,l),u=new fe.Point(a,h);let d=(0,fe.box)(c,u);const p=super._calcBoundingBox(e);return p&&(d=this._unionBox(d,p)),d}_calculateWidth(){return Math.round(this._barSpacing/4)}}const Be=2*Math.PI;class Ne extends Oe{setItems(e,t){this._setBaseData(e,t);for(const e of this._items){if(e.fontSize){const t=e.fontSize;e.stepX=Math.round(t/1.5),e.stepY=Math.round(t/2)-1}else{const t=e.height;e.stepX=Math.round(t/2*.65)+.5,e.stepY=e.stepX}e.vertOffset=this._calcVertOffset(e);const t=this._getTextCache(e);if(null===t){e.shapeWidth=2*e.stepX,e.shapeHeight=2.5*e.stepY;continue}const s=t.textImageWidth,i=t.textImageHeight;e.shapeWidth=s+2*e.stepX,e.shapeHeight=i+2*e.stepY,e.vertOffset=this._calcVertOffset(e),e.textHorizOffset=this._getHorizontalTextOffset(e),e.textVertOffset=this._getVerticalTextOffset(e)}}_calcVertOffset(e){return e.vertOffset}_drawCorner(e,t,s,i){const{context:r,horizontalPixelRatio:n}=e,o=Math.max(1,Math.floor(2*n));r.lineTo(t-o*i.prevPointSignX,s-o*i.prevPointSignY),r.arcTo(t,s,t+o*i.nextPointSignX,s+o*i.nextPointSignY,o)}_getArrowSize(e){return e.stepX}_getHorizontalTextOffset(e){return 0}_getVerticalTextOffset(e){return 0}_hasText(e){return Boolean(e.text)||Boolean(this._text)}_drawItemText(e,t){const s=this._getTextCache(t);if(null===s)return
+;const i=t.textHorizOffset||0,r=t.center+i,n=t.vertOffset,o=t.y+n+t.textVertOffset,a=t.style?.textColor||this._textColor,l={style:{fillStyle:(0,p.ensureDefined)(a)},location:{x:r,y:Math.floor(o),horzAlign:ge.HorizontalAlign.Center,vertAlign:ge.VerticalAlign.Middle}};s.paintTo(e,l)}}class Fe{constructor(e,t,s,i){this.prevPointSignX=e,this.prevPointSignY=t,this.nextPointSignX=s,this.nextPointSignY=i}}var ke;!function(e){e.rightUp=new Fe(1,0,0,1),e.rightDown=new Fe(0,1,-1,0),e.leftDown=new Fe(-1,0,0,-1),e.leftUp=new Fe(0,-1,1,0)}(ke||(ke={}));class Ee extends Oe{_calcBoundingBox(e){const t=e.width,s=e.height,i=t/2,r=Math.round(s/3),n=e.center,o=e.vertOffset-2*r,a=e.y+o,l=n-i,h=n+i,c=a,u=a+s,d=new fe.Point(l,c),p=new fe.Point(h,u);let _=(0,fe.box)(d,p);const f=super._calcBoundingBox(e);return f&&(_=this._unionBox(_,f)),_}}var Le=s(41028);const He=new Map;He.set("PaneRendererArrowUp",class extends De{_isUp(){return!0}}),He.set("PaneRendererArrowDown",class extends De{_isUp(){return!1}}),He.set("PaneRendererCircleShape",class extends Oe{_drawItemShapeUsingCSSPixels(e,t){const s=Math.max(t.width,t.height)/2,i=t.center,r=t.vertOffset,n=t.y+r;e.moveTo(i+s,n),e.arc(i,n,s,0,Be,!1)}_calcBoundingBox(e){const t=Math.max(e.width,e.height)/2,s=e.center,i=e.vertOffset,r=e.y+i,n=s-t,o=s+t,a=r-t,l=r+t,h=new fe.Point(n,a),c=new fe.Point(o,l);let u=(0,fe.box)(h,c);const d=super._calcBoundingBox(e);return d&&(u=this._unionBox(u,d)),u}}),He.set("PaneRendererCrossShape",class extends Re{_drawItemShape(e,t){const{context:s,horizontalPixelRatio:i,verticalPixelRatio:r}=e,n=t.width,o=t.height,a=t.center-n/2,l=t.vertOffset,h=t.y-o/2+l,c=this._lineWidth(e),u=c%2?.5:0,d=Math.round(a*i);let p=Math.round((a+n)*i);(p-d)%2!=c%2&&(p+=1);const _=Math.floor((d+p)/2)+u,f=Math.round(h*r);let m=Math.round((h+o)*r);(m-f)%2!=c%2&&(m+=1);const y=Math.floor((f+m)/2)+u;s.moveTo(_,f),s.lineTo(_,m),s.moveTo(d,y),s.lineTo(p,y)}_calcBoundingBox(e){const t=e.width,s=e.height,i=e.center-t/2,r=e.vertOffset,n=e.y-s/2+r,o=i,a=i+t,l=n,h=n+s,c=new fe.Point(o,l),u=new fe.Point(a,h);let d=(0,fe.box)(c,u);const p=super._calcBoundingBox(e);return p&&(d=this._unionBox(d,p)),d}}),He.set("PaneRendererDiamond",class extends Oe{_drawItemShapeUsingCSSPixels(e,t){const s=Math.round(t.height/2),i=t.center,r=t.vertOffset,n=t.y+r;e.moveTo(i,n-s),e.lineTo(i+s,n),e.lineTo(i,n+s),e.lineTo(i-s,n),e.lineTo(i,n-s)}_calcBoundingBox(e){const t=Math.round(e.height/2),s=e.center,i=e.vertOffset,r=e.y+i,n=s-t,o=s+t,a=r-t,l=r+t,h=new fe.Point(n,a),c=new fe.Point(o,l);let u=(0,fe.box)(h,c);const d=super._calcBoundingBox(e);return d&&(u=this._unionBox(u,d)),u}}),He.set("PaneRendererFlagShape",class extends Oe{_drawItemShapeUsingCSSPixels(e,t){const s=t.width,i=t.height,r=i/2,n=(s-3)/3,o=t.center-s/2,a=t.vertOffset,l=t.y-r+a;e.moveTo(o,l),e.lineTo(o+3,l),e.bezierCurveTo(o+n,l-n,o+2*n,l+n,o+s,l),e.lineTo(o+s,l+r),e.bezierCurveTo(o+s-n,l+r+n,o+s-2*n,l+r-n,o+3,l+r),e.lineTo(o+3,l+i),e.lineTo(o,l+i),e.lineTo(o,l)}_calcBoundingBox(e){
+const t=e.width,s=e.height,i=s/2,r=e.center-t/2,n=e.vertOffset,o=e.y-i+n,a=r,l=r+t,h=o,c=o+s,u=new fe.Point(a,h),d=new fe.Point(l,c);let p=(0,fe.box)(u,d);const _=super._calcBoundingBox(e);return _&&(p=this._unionBox(p,_)),p}}),He.set("PaneRendererLabelUp",class extends Ne{_calcBoundingBox(e){const t=e.center-e.shapeWidth/2,s=e.center+e.shapeWidth/2,i=e.y+e.vertOffset,r=e.y+e.shapeHeight+e.vertOffset,n=new fe.Point(t,i),o=new fe.Point(s,r);return(0,fe.box)(n,o)}_drawItemShape(e,t){const{context:s,horizontalPixelRatio:i,verticalPixelRatio:r}=e,n=this._lineWidth(e)%2?.5:0,o=Math.max(1,Math.floor(i))%2?.5:0,a=this._getArrowSize(t);let l=Math.round(a*i);(o+l)%1!=n%1&&(l+=.5);let h=Math.round(t.shapeWidth/2*i);(o+h)%1!=n%1&&(h+=.5);const c=Math.round(t.center*i)+o,u=Math.round((t.y+t.vertOffset)*r)+n,d=c-l,p=Math.round((t.y+t.vertOffset+a)*r)+n,_=c+l,f=c+h,m=Math.round((t.y+t.vertOffset+a+t.shapeHeight)*r)+n,y=c-h;s.moveTo(d,p),s.lineTo(c,u),s.lineTo(_,p),t.shapeWidth<=2*a?(s.lineTo(f,p),this._drawCorner(e,f,m,ke.rightDown),this._drawCorner(e,y,m,ke.leftDown),s.lineTo(y,p)):(this._drawCorner(e,f,p,ke.rightUp),this._drawCorner(e,f,m,ke.rightDown),this._drawCorner(e,y,m,ke.leftDown),this._drawCorner(e,y,p,ke.leftUp)),s.lineTo(d,p)}_getVerticalTextOffset(e){return e.shapeHeight/2+this._getArrowSize(e)}_calcVertOffset(e){return Math.sign(e.vertOffset)>=0?e.vertOffset:e.vertOffset-e.shapeHeight}}),He.set("PaneRendererLabelDown",class extends Ne{_calcBoundingBox(e){const t=e.center-e.shapeWidth/2,s=e.center+e.shapeWidth/2,i=e.y-e.shapeHeight+e.vertOffset,r=e.y+e.vertOffset,n=new fe.Point(t,i),o=new fe.Point(s,r);return(0,fe.box)(n,o)}_drawItemShape(e,t){const{context:s,horizontalPixelRatio:i,verticalPixelRatio:r}=e,n=this._lineWidth(e)%2?.5:0,o=Math.max(1,Math.floor(i))%2?.5:0,a=this._getArrowSize(t);let l=Math.round(a*i);(o+l)%1!=n%1&&(l+=.5);let h=Math.round(t.shapeWidth/2*i);(o+h)%1!=n%1&&(h+=.5);const c=Math.round(t.center*i)+o,u=Math.round((t.y+t.vertOffset)*r)+n,d=c+l,p=Math.round((t.y+t.vertOffset-a)*r)+n,_=c-l,f=c+h,m=Math.round((t.y+t.vertOffset-t.shapeHeight-a)*r)+n,y=c-h;s.moveTo(d,p),s.lineTo(c,u),s.lineTo(_,p),t.shapeWidth<=2*a?(s.lineTo(y,p),this._drawCorner(e,y,m,ke.leftUp),this._drawCorner(e,f,m,ke.rightUp),s.lineTo(f,p)):(this._drawCorner(e,y,p,ke.leftDown),this._drawCorner(e,y,m,ke.leftUp),this._drawCorner(e,f,m,ke.rightUp),this._drawCorner(e,f,p,ke.rightDown)),s.lineTo(d,p)}_getVerticalTextOffset(e){return-e.shapeHeight/2-this._getArrowSize(e)}_calcVertOffset(e){return Math.sign(e.vertOffset)<=0?e.vertOffset:e.vertOffset+e.shapeHeight}}),He.set("PaneRendererSquare",class extends Oe{_drawItemShape(e,t){const{context:s,horizontalPixelRatio:i,verticalPixelRatio:r}=e,n=Math.max(1,Math.floor(i))%2?.5:0,o=this._lineWidth(e)%2?.5:0;let a=Math.round(t.height/2*r);(n+a)%1!=o%1&&(a+=.5);const l=Math.round(t.center*i)+n,h=Math.round((t.y+t.vertOffset)*r)+n,c=l-a,u=h-a,d=l+a,p=h+a;s.rect(c,u,d-c,p-u)}_calcBoundingBox(e){
+const t=e.height,s=Math.round(t/2),i=e.center-s,r=e.vertOffset,n=e.y+r-s,o=i,a=i+t,l=n,h=n+t,c=new fe.Point(o,l),u=new fe.Point(a,h);let d=(0,fe.box)(c,u);const p=super._calcBoundingBox(e);return p&&(d=this._unionBox(d,p)),d}}),He.set("PaneRendererTriangleApexUp",class extends Ee{_drawItemShape(e,t){const{context:s,horizontalPixelRatio:i,verticalPixelRatio:r}=e,n=t.width,o=t.height,a=Math.round(o/3),l=t.vertOffset-2*a,h=this._lineWidth(e)%2?.5:0,c=Math.max(1,Math.floor(i)),u=c%2?.5:0;let d=Math.round(n*i);d%2!=c%2&&(d+=1);const p=Math.round(t.center*i)+u,_=Math.round((t.y+l)*r),f=p+d/2,m=Math.round((t.y+l+o)*r)+h,y=p-d/2;s.moveTo(p,_),s.lineTo(f,m),s.lineTo(y,m),s.lineTo(p,_)}}),He.set("PaneRendererTriangleApexDown",class extends Ee{_drawItemShape(e,t){const{context:s,horizontalPixelRatio:i,verticalPixelRatio:r}=e,n=t.width,o=t.height,a=Math.round(o/3),l=t.vertOffset-a,h=this._lineWidth(e)%2?.5:0,c=Math.max(1,Math.floor(i)),u=c%2?.5:0;let d=Math.round(n*i);d%2!=c%2&&(d+=1);const p=Math.round(t.center*i)+u,_=Math.round((t.y+l)*r)+h,f=p+d/2,m=Math.round((t.y+l+o)*r),y=p-d/2;s.moveTo(y,_),s.lineTo(f,_),s.lineTo(p,m),s.lineTo(y,_)}}),He.set("PaneRendererXCross",class extends Re{_drawItemShapeUsingCSSPixels(e,t){const s=t.width,i=t.height,r=t.center-s/2,n=t.vertOffset,o=t.y-i/2+n;e.moveTo(r,o),e.lineTo(r+s,o+i),e.moveTo(r,o+i),e.lineTo(r+s,o)}_calcBoundingBox(e){const t=e.width,s=e.height,i=e.center-t/2,r=e.vertOffset,n=e.y-s/2+r,o=i,a=i+t,l=n,h=n+s,c=new fe.Point(o,l),u=new fe.Point(a,h);let d=(0,fe.box)(c,u);const p=super._calcBoundingBox(e);return p&&(d=this._unionBox(d,p)),d}});class We extends Le.StudyPaneViewInplaceUpdatable{constructor(e,t,s,i){super(t,s,i),this._renderer=null,this._shapesRenderer=null,this._selectionRenderer=null,this._isMarkersEnabled=ee.enabled("source_selection_markers"),this._study=e;const r=e.metaInfo().plots;for(let e=0;e<r.length;e++)if(r[e].id===this._plotName){this._plotIndex=e;break}this._plotStyleInfo=(0,p.ensureDefined)(e.metaInfo().styles?.[this._plotName]),this._colorProvider=(0,re.createStudyPlotColorProvider)(e.metaInfo(),e.properties(),i),this._selectionIndexer=new de.SelectionIndexes(s.timeScale())}items(){return this._items}renderer(){return this._isPlotVisible()&&this._scalesReady()?(this._makeSureRendererIsValid(),this._renderer):null}_isPlotVisible(){return this._study.isPlotVisibleAt(this._plotName,1)}_scalesReady(){const e=this._model.timeScale(),t=this._priceScale();return e&&null!==t&&!e.isEmpty()&&!t.isEmpty()}_updateImplFull(e){if(this._dataInvalidated?.clearData&&(this._items=[],this._renderer=null),!this._scalesReady())return!1;const t=this._model.timeScale(),s=this._priceScale(),i=t.visibleBarsStrictRange();if(null===i||null===s)return!1;const r=this._study.plots().plottableRange(!1);if(0===r.size())return!1;const n=this._study.offset(this._plotName),o=this._study.firstValue(void 0,this.isForceOverlay());if(null===o)return!1;this._updateAdditionalPrices(s,o)
+;const{hiPlot:a,loPlot:l}=this._hiLoPlots(),h=this._preallocateItems(r,((e,t)=>this._createItem(e,t??null,a,l,n)));let c=this._series.nearestIndex(i.firstBar(),O.PlotRowSearchMode.NearestRight),u=this._series.nearestIndex(i.lastBar(),O.PlotRowSearchMode.NearestLeft);if(void 0===c||void 0===u)return!1;n>0?(c-=n,u+=n):(c+=n,u-=n);const d=this._study.getMinFirstBarIndexForPlot(this._plotName);if(d>u)return!0;c=Math.max(d,c);const _=this._getTranspValue(),f=this._study.properties().childs().styles.childs()[this._plotName].childs(),m=f.color.value(),g=f.textColor?f.textColor.value():void 0,v=m,S=m,b=void 0===g?void 0:g,P=(0,p.ensureNotNull)(this._plotIndex),w=(0,_e.createEmptyStyle)(),I=h??(0,p.ensureNotNull)(r.firstIndex()),x=r.rangeIterator(I,(0,p.ensureNotNull)(r.lastIndex())+1);let C=(0,y.lowerbound)(this._items,I+n,((e,t)=>e.timePointIndex<t));for(const e of x){const t=e.value,s=t[P+1];if(null==s){C++;continue}const i=this._items[C];if(!isNaN(i.origPrices.price)){if(this._colorProvider.isColorDefined()){i.style={color:v,borderColor:S,textColor:b};const e=this._colorProvider.getPlotPointStyle(t,w);this._fillItemWithPointStyle(i,e,_)}}C++}return this._updateImplLight(),!0}_fillItemWithPointStyle(e,t,s){const i=(0,p.ensureDefined)(e.style);if(void 0!==t.colors[0]){i.color=(0,I.generateColor)((0,p.ensureDefined)(t.colors[0]),s);const e=s>9?s-10:0;i.borderColor=(0,I.generateColor)(i.color,e)}void 0!==t.colors[2]&&(i.textColor=(0,I.generateColor)((0,p.ensureDefined)(t.colors[2]),s))}_updateRenderer(e,t){this._makeSureRendererIsValid();const s=this._model.timeScale(),i={},r=this._getTranspValue(),n=s.barSpacing(),o=this._calculateShapeHeight(n),a=this._study.properties().childs().styles.childs()[this._plotName].childs(),l=a.location.value(),h=this._calculateVerticalOffset(l,o+o/2);i.barSpacing=n,i.items=this._items,i.color=(0,I.generateColor)(a.color.value(),r),i.height=o,i.vertOffset=h,i.visibleItemsRange={startItemIndex:e,endItemIndex:t};const c=a.plottype.value(),u=ce.plotShapesData[c],d=new te.CompositeRenderer;u&&(this._shapesRenderer?this._shapesRenderer.setData(i):(this._shapesRenderer=this._createRenderer(u.paneRendererClass,i),d.append(this._shapesRenderer))),this._model.selection().isSelected(this._study)&&this._isMarkersEnabled&&null!==this._selectionData&&(this._selectionData.vertOffset=h,d.append(new he.SelectionRenderer(this._selectionData))),this._renderer=d}_createRenderer(e,t){const s=He.get(e);return new((0,p.ensureDefined)(s))(t)}_getSeriesVal(e,t){const s=(0,pe.barFunction)(e),i=this._series.data().valueAt(t);return null===i?null:s(i)}_getTranspValue(){let e=0;const t=this._study.properties().childs();t.transparency&&(e=t.transparency.value(),e=(0,_.isNumber)(e)?e:50);const s=t.styles.childs()[this._plotName].childs();return s.transparency&&(e=s.transparency.value(),e=(0,_.isNumber)(e)?e:50),(0,ue.clamp)(e,0,100)}_createItem(e,t,s,i,r){const n=this._study.properties().childs().styles.childs()[this._plotName].childs().location.value(),o={origPrices:{price:NaN},timePointIndex:e+r}
+;if((null===t||0===t)&&n!==D.MarkLocation.Absolute)return o;if(null==t)return o;let a=NaN;switch(n){case D.MarkLocation.AboveBar:{const t=this._getLocationPrice(e,s,r);if(null===t)return o;a=t;break}case D.MarkLocation.BelowBar:{const t=this._getLocationPrice(e,i,r);if(null===t)return o;a=t;break}case D.MarkLocation.Absolute:a=(0,p.ensureNotNull)(t);break;case D.MarkLocation.Top:case D.MarkLocation.Bottom:a=0;break;default:throw new Error("Bad value: "+n)}return{y:NaN,origPrices:{price:a},timePointIndex:e+r}}_dependsOnSeriesData(){const e=this._study.properties().childs().styles.childs()[this._plotName].childs().location.value();return e===D.MarkLocation.AboveBar||e===D.MarkLocation.BelowBar}_getValueForUpdating(e){const t=e.value[this._plotIndex+1];if(null==t)return null;const s=this._study.properties().childs().styles.childs()[this._plotName].childs().location.value();if(0===t&&s!==D.MarkLocation.Absolute)return null;const i=this._study.offset(this._plotName),{hiPlot:r,loPlot:n}=this._hiLoPlots();switch(s){case D.MarkLocation.AboveBar:return this._getLocationPrice(e.index,r,i);case D.MarkLocation.BelowBar:return this._getLocationPrice(e.index,n,i)}return super._getValueForUpdating(e)}_convertItemsToCoordinates(e,t,s,i){for(let e=s;e<i;e++){const t=this._items[e];t.y=t.origPrices.price}this._model.timeScale().fillBarBorders(this._items);const r=this._study.properties().childs().styles.childs()[this._plotName].childs().location.value(),n=e.height()*e.topMargin(),o=e.height()*(1-e.bottomMargin()),a=e.isInverted(),l=a?o:n,h=a?n:o,c=e=>{for(let t=s;t<i;t++)isNaN(this._items[t].y)||(this._items[t].y=e)};switch(r){case D.MarkLocation.Top:c(l);break;case D.MarkLocation.Bottom:c(h);break;default:e.pointsArrayToCoordinates(this._items,t,{startItemIndex:s,endItemIndex:i})}}_calculateVerticalOffset(e,t){let s=0;switch(e){case D.MarkLocation.AboveBar:case D.MarkLocation.Bottom:s=-t;break;case D.MarkLocation.BelowBar:case D.MarkLocation.Top:s=t}return(0,p.ensureNotNull)(this._priceScale()).isInverted()&&(s*=-1),s}_calculateShapeHeight(e,t){let s=e;switch(t){case L.PlotSymbolSize.Tiny:s=.3*e;break;case L.PlotSymbolSize.Small:s=.6*e;break;case L.PlotSymbolSize.Normal:s=e;break;case L.PlotSymbolSize.Large:s=1.5*e;break;case L.PlotSymbolSize.Huge:s=2*e}return"number"==typeof t&&t>0&&(s=t),s}_hiLoPlots(){let e,t;let s=null;switch(this._series.properties().childs().style.value()){case 2:s="lineStyle";break;case 14:s="lineWithMarkersStyle";break;case 15:s="steplineStyle";break;case 3:s="areaStyle"}return s?(e=this._series.properties().childs()[s].childs().priceSource.value(),t=e):(e="high",t="low"),{hiPlot:e,loPlot:t}}_getLocationPrice(e,t,s){const i=Math.min(e+s,(0,p.ensureNotNull)(this._series.data().last()).index);return this._getSeriesVal(t,i)}}class ze extends We{_updateRenderer(e,t){const s=this._study.properties().childs().styles.childs()[this._plotName].childs(),i=this._model.timeScale(),r={},n=this._getTranspValue(),o=i.barSpacing();let a
+;a=this._plotStyleInfo.size?this._calculateShapeHeight(25,this._plotStyleInfo.size):Math.round(o/2),a=Math.max(a,1);const l=s.location.value(),h=(0,I.generateColor)(s.color.value(),n),c=n>19?n-10:0,u=this._calculateVerticalOffset(l,Math.round(1.5*a));r.barSpacing=o,r.items=this.items(),r.color=h,r.borderColor=(0,I.generateColor)(s.color.value(),c),r.height=a,r.vertOffset=u,r.visibleItemsRange={startItemIndex:e,endItemIndex:t};const d=s.plottype.value(),p=ce.plotShapesData[d],_=this._plotStyleInfo.text;if(void 0!==_&&""!==_.trim()){let e=_.replace(/\\n/gm,"\n");e=(0,le.cleanButAmpersand)(e,!0),r.text=e,r.fontSize=12;const t=s.textColor?s.textColor.value():void 0;r.textColor=t?(0,I.generateColor)(t,n):h}if(this._renderer&&this._shapesRenderer&&this._selectionRenderer)this._shapesRenderer.setData(r),this._model.selection().isSelected(this._study)&&this._isMarkersEnabled&&null!==this._selectionData?(this._selectionData.vertOffset=u,this._selectionRenderer.setData(this._selectionData)):this._selectionRenderer.setData(null);else{const e=new te.CompositeRenderer;this._shapesRenderer=super._createRenderer(p.paneRendererClass,r),e.append(this._shapesRenderer),this._selectionRenderer=new he.SelectionRenderer(this._selectionData??void 0),this._model.selection().isSelected(this._study)&&this._isMarkersEnabled&&null!==this._selectionData?this._selectionData.vertOffset=u:this._selectionRenderer.setData(null),e.append(this._selectionRenderer),this._renderer=e}}}var Ue,je=s(87795),Ge=s.n(je),$e=s(4539),Ke=s(57658);!function(e){e[e.SimplifiedPaintingMaxFontSize=4]="SimplifiedPaintingMaxFontSize"}(Ue||(Ue={}));class Ye extends Ae{constructor(e,t){super(null,t),this._textWidthCache=new Ke.TextWidthCache,this._fontSizeEnsured=0,this._font="",this._ch="",null!==e&&this.setData(e)}setData(e){super.setData(e),this._fontSizeEnsured=(0,p.ensureDefined)(this._height),this._font=(0,be.makeFont)(this._fontSizeEnsured,e.fontFamily||Me.CHART_FONT_FAMILY);const t=e.char.slice(0,40);this._ch=Ge()(t)[0]||" "}hitTest(e){const t=(0,$e.interactionTolerance)().series+this._fontSizeEnsured/2;for(const s of this._items){if(new fe.Point(s.center,s.y+s.vertOffset).subtract(e).length()<=t)return new ve.HitTestResult(ve.HitTarget.Regular)}return null}_drawItemShape(e,t){const s=t.center,i=t.vertOffset>0?1:-1,r=Math.trunc(this._fontSizeEnsured/6),n=t.y+t.vertOffset-i*Math.round(this._fontSizeEnsured/2)+(i>0?r:-this._fontSizeEnsured);let o;o=t.style&&void 0!==t.style.color?t.style.color:this._color;const{context:a,horizontalPixelRatio:l,verticalPixelRatio:h}=e;a.font!==this._font&&(a.font=this._font);const c=this._textWidthCache.measureText(a,this._ch);if(this._fontSizeEnsured<=4/l){a.save();const e=Math.max(1,Math.floor(l));let i=Math.max(1,Math.floor(c*l));i%2!=e%2&&(i+=i>1?-1:1);const r=Math.round(n*h)+(t.vertOffset>=0?0:-i);return a.fillStyle=o,a.fillRect(Math.round(s*l)+(l%2?.5:0)-i/2,r,i,i),void a.restore()}(0,we.drawScaled)(a,l,h,(()=>{a.fillStyle=o,a.textAlign="center",a.textBaseline="top",a.fillText(this._ch,s,n)}))}_startPath(e,t,s){}_endPath(e){}}
+class Xe extends We{constructor(){super(...arguments),this._charRenderer=new Ye(null)}_updateRenderer(e,t){const s=this._getTranspValue(),i=this._model.timeScale().barSpacing();let r;const n=this._study.properties().childs().styles.childs()[this._plotName].childs();r=this._plotStyleInfo.size?this._calculateShapeHeight(50,this._plotStyleInfo.size):Math.round(i);const o=n.location.value(),a=(0,I.generateColor)(n.color.value(),s),l=this._calculateVerticalOffset(o,r),h={items:this.items(),barSpacing:i,char:(0,p.ensureDefined)(n.char?.value()??this._plotStyleInfo.char),height:r,vertOffset:l,color:a,visibleItemsRange:{startItemIndex:e,endItemIndex:t}},c=this._plotStyleInfo.text;if(void 0!==c&&""!==c.trim()){let e=c.replace(/\\n/gm,"\n");e=(0,le.cleanButAmpersand)(e,!0),h.text=e,h.fontSize=12;const t=n.textColor?n.textColor.value():void 0;h.textColor=t?(0,I.generateColor)(t,s):a}this._charRenderer.setData(h);const u=new te.CompositeRenderer;u.append(this._charRenderer),this._model.selection().isSelected(this._study)&&this._isMarkersEnabled&&null!==this._selectionData&&(this._selectionData.vertOffset=l,u.append(new he.SelectionRenderer(this._selectionData))),this._renderer=u}}var qe=s(24377);class Je{constructor(e,t,s,i,r){this.left=NaN,this.right=NaN,this.height=NaN,this.center=e,this.y=t,this.origHeight=s,this.isUp=i,this.origPrices=r,this.timePointIndex=e,this.style={}}}function Ze(e){return Math.round(e/4)}function Qe(e){return Math.round(e/2)}class et extends se.BitmapCoordinatesPaneRenderer{constructor(e){super(),this._data=e}hitTest(e){const t=this._data,s=Qe(t.barSpacing),i=Math.round(s/2),r=Math.round(s),n=Ze(t.barSpacing),o=t.visibleItemsRange?.startItemIndex??0,a=t.visibleItemsRange?.endItemIndex??t.items.length;if(o>=a)return null;for(const s of t.items.slice(o,a)){if(!s)continue;if(!Number.isFinite(s.center)||!Number.isFinite(s.y))continue;const t=Math.abs(s.height),o=s.isUp?-1:1,a=t+r,l=s.y-o*n,h=l-o*a,c=s.center-i,u=s.center+i;if(c<e.x&&e.x<u&&(s.isUp?l<e.y&&e.y<h:h<e.y&&e.y<l))return new ve.HitTestResult(ve.HitTarget.Regular)}return null}_drawImpl(e){const{horizontalPixelRatio:t,verticalPixelRatio:s,context:i}=e,r=this._data,n=Qe(r.barSpacing),o=Ze(r.barSpacing),a=n<4,l=Math.max(n/2,1),h=(0,ue.ceiledEven)(n*t),c=h/2,u=Math.round(n*s);i.lineCap="butt",i.lineWidth=Math.max(1,Math.floor(t));const d=i.lineWidth%2?.5:0,p=r.visibleItemsRange?.startItemIndex??0,_=r.visibleItemsRange?.endItemIndex??r.items.length;if(!(p>=_))for(const e of r.items.slice(p,_)){if(!Number.isFinite(e.center)||!Number.isFinite(e.y))continue;const n=e.isUp?-1:1,p=Math.round(Math.abs(e.height)*s),_=Math.round(e.center*t)+d,f=Math.round((e.y-n*o)*s)+d;i.beginPath(),i.translate(_,f);const m=(e.style&&e.style.color)??(e.isUp?r.colorup:r.colordown);a?(i.moveTo(0,0),i.lineTo(-c,-c*n),i.moveTo(0,0),i.lineTo(c,-c*n),i.moveTo(0,0),i.lineTo(0,-p*n),i.moveTo(-c,-p*n),i.lineTo(c,-p*n),i.lineWidth=l,i.strokeStyle=m,i.stroke()):(i.moveTo(0,0),p<u?(i.lineTo(h,-p*n),i.lineTo(-h,-p*n)):(i.lineTo(h,-u*n),i.lineTo(c,-u*n),i.lineTo(c,-p*n),i.lineTo(-c,-p*n),
+i.lineTo(-c,-u*n),i.lineTo(-h,-u*n)),i.lineTo(0,0),i.strokeStyle=e.isUp?r.colorBorderUp:r.colorBorderDown,i.stroke(),i.fillStyle=m,i.fill()),i.translate(-_,-f)}}}class tt extends We{_updateRenderer(e,t){const s=this._study.properties().childs().styles.childs()[this._plotName].childs(),i=(0,ue.clamp)(this._getTranspValue(),0,100),r=this._model.timeScale().barSpacing(),n=(0,I.generateColor)(s.colorup.value(),i),o=(0,I.generateColor)(s.colordown.value(),i),a=(0,qe.parseRgba)(n),l=a?100*(1-a[3]):0,h=(0,qe.parseRgba)(o),c=h?100*(1-h[3]):0,u={items:this._items,barSpacing:r,colorup:n,colordown:o,colorBorderUp:(0,I.generateColor)("#000000",l),colorBorderDown:(0,I.generateColor)("#000000",c),minHeight:this._plotStyleInfo.minHeight,visibleItemsRange:{startItemIndex:e,endItemIndex:t}};this._updateItemsHeights(u);const d=new te.CompositeRenderer;d.append(new et(u)),this._model.selection().isSelected(this._study)&&null!==this._selectionData&&d.append(new he.SelectionRenderer({...this._selectionData,barSpacing:r,withOutline:!1})),this._renderer=d}_fillItemWithPointStyle(e,t,s){const i=(0,p.ensureDefined)(e.style);e.isUp?void 0!==t.colors[5]?i.color=(0,I.generateColor)((0,p.ensureDefined)(t.colors[5]),s):i.color=(0,I.generateColor)(this._study.properties().childs().styles.childs()[this._plotName].childs().colorup.value(),s):void 0!==t.colors[6]?i.color=(0,I.generateColor)((0,p.ensureDefined)(t.colors[6]),s):i.color=(0,I.generateColor)(this._study.properties().childs().styles.childs()[this._plotName].childs().colordown.value(),s)}_getValueForUpdating(e){const t=e.value[this._plotIndex+1];if(!t)return null;const s=e.index,i=t>0,{hiPlot:r,loPlot:n}=this._hiLoPlots(),o=this._study.offset(this._plotName),a=Math.min(s+o,(0,p.ensureNotNull)(this._series.data().last()).index);if(i){const e=this._getSeriesVal(n,a);if(null!==e)return e}else{const e=this._getSeriesVal(r,a);if(null!==e)return e}return null}_updateItem(e,t){const s=this._getValueForUpdating(e),i=e.value[this._plotIndex+1]>0;return this._items[t].origPrices.price=s??NaN,this._items[t].isUp=i,t+1}_createItem(e,t,s,i,r){const n={center:NaN,y:NaN,origPrices:{price:NaN,timePointIndex:NaN},origHeight:NaN,timePointIndex:e+r};if(!t)return n;const o=Math.min(e+r,(0,p.ensureNotNull)(this._series.data().last()).index),a=t>0;let l;if(a){const e=this._getSeriesVal(i,o);if(null===e)return n;l=e}else{const e=this._getSeriesVal(s,o);if(null===e)return n;l=e}return new Je(e+r,l,t,a,{price:l,timePointIndex:e+r})}_dependsOnSeriesData(){return!0}_convertItemsToCoordinates(e,t,s,i){this._convertItemsToCoordinatesImpl(e,t,s,i)}_createSelectionDataPoint(e,t,s,i){const r=this._model.timeScale().barSpacing(),n=Ze(r),o=function(e){return Qe(e)}(r),a=super._createSelectionDataPoint(e,t,s,i),l=this._items[(0,y.lowerbound)(this._items,t,((e,t)=>e.timePointIndex<t))];if(!l)return a;const h=l.isUp?1:-1;return{...a,point:a.point.add((0,fe.point)(0,h*(n+o)))}}_updateItemsHeights(e){const t=this._study.properties().childs().styles.childs();let s=Math.abs((0,
+p.ensureDefined)(t[this._plotName].childs().minHeight?.value()??this._plotStyleInfo.minHeight)),i=Math.abs((0,p.ensureDefined)(t[this._plotName].childs().maxHeight?.value()??this._plotStyleInfo.maxHeight));if(s>i){const e=s;s=i,i=e}const r=this._items,n=e.visibleItemsRange?.startItemIndex??0,o=(e.visibleItemsRange?.endItemIndex??r.length)-1;let a=0;for(let e=n;e<=o;e++){const t=r[e],s=Math.abs(t.origHeight);s>a&&(a=s)}const l=(i-s)/a;for(let e=n;e<=o;e++){const t=r[e],i=Math.abs(t.origHeight);t.height=i*l+s}}}var st=s(64138);class it extends ne.StudyForceOverlayPlotView{constructor(e,t,s,i){super(t,s,i),this._bars=[],this._invalidated=!1,this._isMarkersEnabled=ee.enabled("source_selection_markers"),this._selectionData=null,this._ohlcPlotIndexes=new Map,this._study=e,this._isMarkersEnabled=ee.enabled("source_selection_markers"),this._colorProvider=(0,re.createStudyPlotColorProvider)(e.metaInfo(),e.properties(),i),this._selectionIndexer=new de.SelectionIndexes(s.timeScale());const r=this._study.metaInfo().plots;for(let e=0;e<r.length;e++){const t=r[e];"target"in t&&(t.target===this._plotName&&((0,L.isOhlcOpenPlot)(t)&&this._ohlcPlotIndexes.set(1,e),(0,L.isOhlcHighPlot)(t)&&this._ohlcPlotIndexes.set(2,e),(0,L.isOhlcLowPlot)(t)&&this._ohlcPlotIndexes.set(3,e),(0,L.isOhlcClosePlot)(t)&&this._ohlcPlotIndexes.set(4,e)))}}update(e){"hover-change"!==e.type&&(this._invalidated=!0)}items(){return this._bars}_updateImpl(){this._bars.length=0;const e=this._priceScale();if(this._model.timeScale().isEmpty()||null===e||e.isEmpty())return;const t=this._model.timeScale().visibleBarsStrictRange();if(null===t)return;let s=this._series.nearestIndex(t.firstBar(),O.PlotRowSearchMode.NearestRight);const i=this._series.nearestIndex(t.lastBar(),O.PlotRowSearchMode.NearestLeft);if(void 0===s||void 0===i)return;const r=this._study.getMinFirstBarIndexForPlot(this._plotName);if(r>i)return;s=Math.max(r,s);const n=this._study.data(),o=this._study.firstValue(void 0,this.isForceOverlay());if(null===o)return;const a=n.rangeIterator(s,i),l=(0,p.ensureDefined)(this._study.properties().childs().ohlcPlots).childs()[this._plotName].childs(),h=new Map,c=(e,t)=>{const s=e+"@"+t;if(!h.has(s)){const i=(0,I.generateColor)(e,t);return h.set(s,i),i}return h.get(s)},u=(0,_e.createEmptyStyle)();for(const e of a){let t=e.index;const s=e.value;t=Math.floor(t);let i=!0;const r=new Map;for(let e=1;e<=4;++e){const t=this._ohlcPlotIndexes.get(e);if(void 0===t){i=!1;break}const n=s[t+1];if(null==n){i=!1;break}r.set(e,n)}if(!i)continue;const n=(0,p.ensureDefined)(r.get(1)),o=(0,p.ensureDefined)(r.get(4)),a=(0,p.ensureDefined)(r.get(2)),h=(0,p.ensureDefined)(r.get(3)),d=Math.max(n,a,h,o),_=Math.min(n,a,h,o);let f=(0,p.ensureDefined)(c(l.color.value(),0));const m=this._colorProvider.getPlotPointStyle(s,u);void 0!==m.colors[0]&&(f=(0,p.ensureDefined)(m.colors[0]));const y={open:n,high:d,low:_,close:o,color:f,wickColor:m.colors[4],borderColor:m.colors[3],hollow:null,center:NaN,left:NaN,right:NaN,timePointIndex:Math.round(t)};this._bars.push(y)}
+if(e.barPricesToCoordinates(this._bars,o),this._model.timeScale().fillBarBorders(this._bars),this._model.selection().isSelected(this._study)){const t=this._selectionIndexer.indexes();this._selectionData={points:[],hittestResult:ve.HitTarget.Regular,bgColors:[],visible:!0,barSpacing:this._model.timeScale().barSpacing()};const s=(0,p.ensureNotNull)(this._model.paneForSource(this._study)).height(),i=(0,p.ensureDefined)(this._ohlcPlotIndexes.get(4));for(let r=0;r<t.length;r++){const n=t[r],a=this._study.data().valueAt(n);if(null===a)continue;const l=a[i+1];if(null==l)continue;const h=this._model.timeScale().indexToCoordinate(Math.floor(n)),c=e.priceToCoordinate(l,o);this._selectionData.points.push({point:new fe.Point(h,c)}),this._selectionData.bgColors.push(this._model.backgroundColorAtYPercentFromTop(c/s))}}else this._selectionIndexer.clear()}_isOHLCPlotVisible(){return this._study.isPlotVisibleAt(this._plotName,1)}}class rt extends it{renderer(){if(!this._isOHLCPlotVisible())return null;this._invalidated&&(this._updateImpl(),this._invalidated=!1);const e={bars:this._bars,dontDrawOpen:this._series.properties().childs().barStyle.childs().dontDrawOpen.value(),thinBars:this._series.properties().childs().barStyle.childs().thinBars.value()},t=new te.CompositeRenderer;return t.append(new st.PaneRendererBars(e)),this._model.selection().isSelected(this._study)&&this._isMarkersEnabled&&this._selectionData&&t.append(new he.SelectionRenderer(this._selectionData)),t}}var nt=s(48227);class ot extends it{renderer(){if(!this._isOHLCPlotVisible())return null;const e=this._priceScale();if(!e||e.isEmpty())return null;this._invalidated&&(this._updateImpl(),this._invalidated=!1);const t=(0,p.ensureDefined)(this._study.properties().childs().ohlcPlots).childs()[this._plotName].childs(),s=this._model.timeScale().barSpacing(),i={bars:this._bars,barSpacing:s,wickVisible:t.drawWick.value(),bodyVisible:!0,borderVisible:t.drawBorder.value(),barWidth:(0,$e.optimalBarWidth)(s),borderColor:t.borderColor.value(),wickColor:t.wickColor.value(),isPriceScaleInverted:e.isInverted()},r=new te.CompositeRenderer;return r.append(new nt.PaneRendererCandles(i)),this._model.selection().isSelected(this._study)&&this._isMarkersEnabled&&this._selectionData&&r.append(new he.SelectionRenderer(this._selectionData)),r}}var at=s(69555),lt=s(96025),ht=s(40738),ct=s(69558);class ut extends ht.HorizontalLinePaneView{constructor(e,t){super(),this._lineRendererData.linestyle=ct.LINESTYLE_DOTTED,this._study=e,this._plotName=t}_updateImpl(){this._lineRendererData.visible=!1;const e=this._study.properties().childs().styles.childs()[this._plotName].childs();if(!e.trackPrice.value()||!this._study.isPlotVisibleAt(this._plotName,1))return;const t=this._study.lastValueData(this._plotName,!0);t.noData||(this._lineRendererData.visible=!0,this._lineRendererData.y=t.coordinate,this._lineRendererData.color=t.color,this._lineRendererData.linewidth=e.linewidth.value())}}var dt=s(5605),pt=s(13560),_t=s(18348);const ft={type:0,color:"transparent"}
+;class mt extends _t.AbstractFilledAreaPaneView{constructor(e,t,s,i){super(e,t,s),this._palettesInfo={},this._gradientPropsStateCache=null,this._rgbaFromInteger=(0,pt.rgbaFromIntegerCached)();const r=this._source.metaInfo();this._isRGB=Boolean(r.isRGB),this._isHlineFill="hline_hline"===s.type,(0,p.assert)(this._isHlineFill||"plot_plot"===s.type,"Wrong filledArea type: "+s.type),this._isHlineFill&&this._initBandIndexes(s.objAId,s.objBId),this._fillMetaInfo=s,this._fillStyleProps=i,this._gradientFillType=i.hasChild("fillType")&&"gradient"===i.childs().fillType?.value(),this._gradientStaticState={color1:s.topColor,color2:s.bottomColor,value1:s.topValue,value2:s.bottomValue},this._hasAllGradientRequiredProps=this._gradientFillType&&(void 0!==this._gradientStaticState.color1||i.hasChild("topColor")||void 0!==this._gradientStaticState.color2||i.hasChild("bottomColor"))&&(void 0!==this._gradientStaticState.value1||i.hasChild("topValue"))&&(void 0!==this._gradientStaticState.value2||i.hasChild("bottomValue"));const n=()=>this._colorPlotIndex=this._colorPlotIndex??{type:1};for(let t=0;t<r.plots.length;++t){const i=r.plots[t];if(((0,L.isColorerPlot)(i)||(0,L.isDataPlot)(i))&&i.target===s.id){if((0,L.isColorerPlot)(i)){let s;void 0!==i.targetField?"topColor"===i.targetField?(n().colorIndexOrRgba1=t,s="color1"):"bottomColor"===i.targetField&&(n().colorIndexOrRgba2=t,s="color2"):this._colorPlotIndex={type:0,colorIndexOrRgba:t},(0,L.isPaletteColorerPlot)(i)&&(this._palettesInfo[s??"color"]={map:(0,p.ensureDefined)((0,p.ensureDefined)(r.palettes)[i.palette]?.valToIndex),values:e.properties().palettes[i.palette].colors})}else(0,L.isDataPlot)(i)&&("topValue"===i.targetField?n().valueIndex1=t:"bottomValue"===i.targetField&&(n().valueIndex2=t));if(0===this._colorPlotIndex?.type)break}}}update(e){super.update(e),this._gradientPropsStateCache=null}isForceOverlay(){return!!this._source.metaInfo().isPlotForceOverlay(this._plotAId())}_firstValue(){const e=this.isForceOverlay();return this._source.firstValue(void 0,e)}_minFirstBarIndex(){return this._source.getMinFirstBarIndexForPlot(this._fillMetaInfo.id)}_getColorByPlotValue(e){if(0===e.type){let t;if(null==e.colorIndexOrRgba)return null;if(this._isRGB)t=this._rgbaFromInteger(e.colorIndexOrRgba);else{const s=(0,p.ensureDefined)(this._palettesInfo.color),i=(0,p.ensureDefined)(s.map[e.colorIndexOrRgba]);t=s.values[i]?.childs().color.value()}return{type:0,color:t}}const t=this._gradientColorPropsState();let s,i;if(this._isRGB)null!=e.colorIndexOrRgba1&&(s=this._rgbaFromInteger(e.colorIndexOrRgba1)),null!=e.colorIndexOrRgba2&&(i=this._rgbaFromInteger(e.colorIndexOrRgba2));else{if(null!=e.colorIndexOrRgba1){const t=(0,p.ensureDefined)(this._palettesInfo.color1);s=t.values[(0,p.ensureDefined)(t.map[e.colorIndexOrRgba1])].childs().color.value()}if(null!=e.colorIndexOrRgba2){const t=(0,p.ensureDefined)(this._palettesInfo.color2);i=t.values[(0,p.ensureDefined)(t.map[e.colorIndexOrRgba2])].childs().color.value()}}const r=e.value1??t.value1,n=e.value2??t.value2;return s=s??t.color1,i=i??t.color2,
+void 0===r||void 0===n||void 0===s&&void 0===i?null:{type:1,color1:s,color2:i,value1:r,value2:n,coordinate1:NaN,coordinate2:NaN}}_plotAId(){return this._fillMetaInfo.objAId}_plotBId(){return this._fillMetaInfo.objBId}_commonColor(){const e=this._fillStyleProps.childs();if(this._gradientFillType){if(!this._hasAllGradientRequiredProps)return ft;const e=this._gradientColorPropsState();return{type:1,color1:e.color1,color2:e.color2,value1:e.value1,value2:e.value2,coordinate1:NaN,coordinate2:NaN}}return{type:0,color:e.color.value()}}_transparency(){return this._fillStyleProps.childs().transparency?.value()??0}_visible(){return this._fillStyleProps.childs().visible.value()}_priceScale(){return this.isForceOverlay()?this._model.mainSeries().priceScale():this._source.priceScale()}_initBandIndexes(e,t){this._bandAKey=null,this._bandBKey=null;const s=this._source.metaInfo().bands;if(void 0!==s)for(let i=0;i<s.length;++i){const r=s[i];null!==this._bandAKey||r.id!==e?null===this._bandBKey&&r.id===t&&(this._bandBKey=i):this._bandAKey=i}}_gradientColorPropsState(){if(null===this._gradientPropsStateCache){const e=this._fillStyleProps.state();this._gradientPropsStateCache={color1:this._gradientStaticState.color1??e.topColor,color2:this._gradientStaticState.color2??e.bottomColor,value1:this._gradientStaticState.value1??e.topValue,value2:this._gradientStaticState.value2??e.bottomValue}}return this._gradientPropsStateCache}}var yt=s(13212),gt=s(27909),vt=s(94119);class St{constructor(e,t){this._invalidated=!0,this._lineRenderer=new vt.HorizontalLineRenderer,this._source=t,this._points=[new fe.Point(-1,-1)],this._invalidated=!0,this._properties=e}update(e){"hover-change"!==e.type&&(this._invalidated=!0)}renderer(){this._invalidated&&(this._updateImpl(),this._invalidated=!1);const e={y:this._points[0].y,color:this._properties.childs().color.value(),linewidth:this._properties.childs().linewidth.value(),linestyle:this._properties.childs().linestyle.value()};return this._lineRenderer.setData(e),this._lineRenderer}_updateImpl(){const e=this._source.priceScale();if(!e||e.isEmpty())return void(this._points[0]=new fe.Point(-1,-1));const t=this._properties.childs().value.value(),s=this._source.firstValue(),i=(0,_.isNumber)(t)&&null!==s?e.priceToCoordinate(t,s):NaN;this._points[0]=new fe.Point(-1,i)}}var bt=s(20820);class Pt extends bt.MediaCoordinatesPaneRenderer{constructor(){super(),this._data=null,this._data=null}setData(e=null){this._data=e}hitTest(){return null}_drawImpl(e){if(null===this._data||0===this._data.points.length)return;const t=e.context,s=e.mediaSize.width;if(this._data.gradient){const e=t.createLinearGradient(0,this._data.coordinate1,0,this._data.coordinate2);e.addColorStop(0,this._data.backColor1??"transparent"),e.addColorStop(1,this._data.backColor2??"transparent"),t.fillStyle=e}else t.fillStyle=this._data.backcolor;const i=Math.min(this._data.points[0],this._data.points[1]),r=Math.max(this._data.points[0],this._data.points[1]);t.fillRect(0,i,s,r-i)}}class wt{constructor(e){this._bandBgRenderer=new Pt,this._invalidated=!0,
+this._source=e}update(e){"hover-change"!==e.type&&(this._invalidated=!0)}renderer(){return this._invalidated&&(this._updateImpl(),this._invalidated=!1),this._bandBgRenderer}_updateImpl(){this._bandBgRenderer.setData(null);const e=this._source.properties().childs(),t=e.bands;if(t.childCount()<2)return;const s=e.bandsBackground;if(!s?.childs().fillBackground.value())return;const i=t[0].childs(),r=t[1].childs(),n=this._source.priceScale(),o=this._source.firstValue();if(!n||n.isEmpty()||null===o)return;const a=[n.priceToCoordinate(i.value.value(),o),n.priceToCoordinate(r.value.value(),o)],l=(0,p.ensureDefined)(e.bandsBackground).childs(),h=(0,ue.clamp)(l.transparency?.value()??0,0,100);this._bandBgRenderer.setData({gradient:!1,points:a,backcolor:(0,I.generateColor)(l.backgroundColor.value(),h)})}}class It{constructor(e,t,s){this._bandBgRenderer=new Pt,this._bandAKey=null,this._bandBKey=null,this._invalidated=!0,this._source=e,(0,p.assert)("hline_hline"===t.type,"Wrong filledArea type: "+t.type),this._initBandIndexes(t.objAId,t.objBId),this._fillStyleProps=s,this._bandBgRenderer=new Pt,this._gradientFillType=s.hasChild("fillType")&&"gradient"===s.childs().fillType?.value(),this._gradientStaticState={color1:t.topColor,color2:t.bottomColor,value1:t.topValue,value2:t.bottomValue}}update(){this._invalidated=!0}renderer(){return this._invalidated&&(this._updateImpl(),this._invalidated=!1),this._bandBgRenderer}_updateImpl(){if(this._bandBgRenderer.setData(null),!this._fillStyleProps.childs().visible.value())return;if(null===this._bandAKey||null===this._bandBKey)return;const e=(0,p.ensureDefined)(this._source.properties().childs().bands),t=e.childs()[this._bandAKey].childs(),s=e.childs()[this._bandBKey].childs(),i=this._source.priceScale(),r=this._source.firstValue();if(!i||i.isEmpty()||null===r)return;const n=[i.priceToCoordinate(t.value.value(),r),i.priceToCoordinate(s.value.value(),r)],o=(0,ue.clamp)(this._fillStyleProps.childs().transparency?.value()??0,0,100);let a;const l=this._fillStyleProps.childs();if(this._gradientFillType){const e=this._gradientStaticState,t=l,s=e.value1??t.topValue?.value(),h=e.value2??t.bottomValue?.value();if(void 0===s||void 0===h)return;const c=e.color1??t.topColor?.value(),u=e.color2??t.bottomColor?.value();if(void 0===c&&void 0===u)return;a={gradient:!0,points:n,backColor1:c&&(0,I.generateColor)(c,o),backColor2:u&&(0,I.generateColor)(u,o),coordinate1:i.priceToCoordinate(s,r),coordinate2:i.priceToCoordinate(h,r)}}else a={gradient:!1,points:n,backcolor:(0,I.generateColor)(l.color.value(),o)};this._bandBgRenderer.setData(a)}_initBandIndexes(e,t){this._bandAKey=null,this._bandBKey=null;(0,p.ensureDefined)(this._source.metaInfo().bands).forEach(((s,i)=>{null===this._bandAKey&&s.id===e&&(this._bandAKey=i),null===this._bandBKey&&s.id===t&&(this._bandBKey=i)}))}}var xt=s(86252),Ct=s(81922),Vt=s(51304),Mt=s(48943),Tt=s(95059),At=s(91106),Rt=s(63670),Ot=s(30693),Dt=s(28477);class Bt extends Dt.AbstractBarColorer{constructor(e,t){super(),this._rgbaFromInteger=(0,pt.rgbaFromIntegerCached)(),this._study=e,
+this._plotIndex=t}applyBarStyle(e,t,s,i){if(t)return s;const r=this._study.properties().childs();if(!r.visible.value())return s;const n=this._study.metaInfo(),o=this._study.data();if(!o||0===o.size())return s;const a=n.plots[this._plotIndex],l=this._getOffset();if(this._study.getMinFirstBarIndexForPlot(a.id)>e+l)return s;if(0===r.styles.childs()[a.id].childs().display.value())return s;const h=o.valueAt(e-l);if(null===h)return s;let c=h[this._plotIndex+1];if(null==c)return s;if(c=Math.round(c),n.isRGB)s.barColor=this._rgbaFromInteger(c),s.upColor=s.barColor,s.downColor=s.barColor;else{const e=n.plots[this._plotIndex];if("palette"in e){const t=e.palette,i=r.palettes.childs()[t],o=(0,p.ensureDefined)(n.palettes?.[t]),a=o.valToIndex?(0,p.ensureDefined)(o.valToIndex[c]):c,l=i.childs().colors.childs()[a].childs().color.value();s.barColor=l,s.upColor=l,s.downColor=l}}return s}firstColoredBar(e){let t=e;for(const s of this._backColorers)t=Math.min(t,s.firstColoredBar(e)??1/0);const s=this._getOffset();t=Math.min(t,e+s);const i=this._getBars().firstIndex(),r=Math.max(t,i??-1/0),n=this._study.metaInfo().plots[this._plotIndex];return Math.max(this._study.getMinFirstBarIndexForPlot(n.id),r)}_getBars(){return this._study.series().bars()}_getOffset(){const e=this._study.metaInfo().plots[this._plotIndex];return this._study.offset(e.id)}}var Nt=s(76422),Ft=s(67563),kt=s(64717);class Et extends at.PanePriceAxisView{constructor(e,t,s,i){super(e,t,s),this._dataSource=t,this._isForceOverlay=t.metaInfo().isPlotForceOverlay(i)}_position(){const e=this._isForceOverlay?this._chartModel.mainPane():this._chartModel.paneForSource(this._dataSource);if(null===e)return null;const t=this._isForceOverlay?this._chartModel.mainSeries().priceScale():this._dataSource.priceScale();if(null===t)return null;let s=e.priceScalePosition(t);return"overlay"===s&&(s=e.priceScalePosition(e.defaultPriceScale())),"overlay"===s?null:s}}var Lt=s(56265);class Ht{constructor(e,t){this._study=e,this._valuesProvider=new F.StudyValuesProvider(e,t,!1,!1)}getItems(){const e=this._study.properties().childs(),t=this._valuesProvider.getItems();for(const s of t){const t=s.id,i=(0,p.ensureDefined)(e.styles.childs()[t]).childs().display.value();s.visible=0!==i}return t}getValues(e){const t=this._valuesProvider.getValues(e),s=this._study.plots().lastIndex(),i=this._study.plots().firstIndex();if(null===s||null===i)return null;for(const r of t){const t=e-this._study.offset(r.id);(t>s||t<i)&&(r.value="")}return t}}var Wt=s(76559),zt=s(72207),Ut=s(3618),jt=s(35727);const Gt=(0,f.getLogger)("Chart.Study"),$t=m.t(null,void 0,s(52969)),Kt=!1;var Yt,Xt;function qt(){return{fields:[],useMainSeriesRange:!1,baseValueMinMax:null}}!function(e){e.PaneViews="study-pane-views"}(Yt||(Yt={})),function(e){e[e.DefaultPriceScale=100]="DefaultPriceScale"}(Xt||(Xt={}));const Jt={symbolsForDisplay:!1,symbolsForChartApi:!0,skipHiddenInputs:!1,skipFakeInputs:!1,skipBooleanInputs:ee.enabled("dont_show_boolean_study_arguments"),asObject:!0,skippedGroups:[],skippedInputs:[],noExchanges:!1,noResolution:!1,
+keepOptionalSymbolsEmpty:!1,skipColorInputs:!1,skipTimeInputs:!1,skipOptionalEmptySymbolInputs:!1,skipTextareaInputs:!1,priceInputsForDisplay:!1},Zt=ee.enabled("study_symbol_ticker_description"),Qt=ee.enabled("hide_main_series_symbol_from_indicator_legend"),es=ee.enabled("datasource_copypaste"),ts=ee.enabled("hide_unresolved_symbols_in_legend");function ss(e,t){const s=e.plots[t];if(!s||!(0,L.isOhlcPlot)(s))return!1;const i=s.target,r=e.defaults.styles&&e.defaults.styles[i],n=e.defaults.ohlcPlots&&e.defaults.ohlcPlots[i],o=e.ohlcPlots&&e.ohlcPlots[i];return r&&(0,L.isOhlcPlotStyleBars)(r)||n&&(0,L.isOhlcPlotStyleBars)(n)||!!o&&(0,L.isOhlcPlotStyleBars)(o)}function is(e,t){const s=e.plots[t];if(!s||!(0,L.isOhlcPlot)(s))return!1;const i=s.target,r=e.defaults.styles&&e.defaults.styles[i],n=e.defaults.ohlcPlots&&e.defaults.ohlcPlots[i],o=e.ohlcPlots&&e.ohlcPlots[i];return r&&(0,L.isOhlcPlotStyleCandles)(r)||n&&(0,L.isOhlcPlotStyleCandles)(n)||!!o&&(0,L.isOhlcPlotStyleCandles)(o)}function rs(e,t){(0,p.assert)(void 0!==e,"zOrder must be defined"),(0,p.assert)(!t.has(e),"zOrder must be unique")}function ns(e,t){return e.plots.some((e=>((0,L.isColorerPlot)(e)||(0,L.isDataPlot)(e))&&e.target===t))}function os(e,t,s){let i=0,r=0;return Math.sign(r)-Math.sign(i)}function as(e){const t=(0,Mt.combine)((e=>e.map((e=>as(e.parentSourcesVW().weakReference())))),e);return(0,Mt.accumulate)(((e,t)=>Array.from(new Set(t.concat(e.flat(20))))),t.ownership(),e).ownership()}function ls(e){return"inherit"===e.type&&(e.type="price"),e}function hs(e,t,s,i){{const t=(0,_.isNumber)(i)?i:void 0,r=jt.customFormatters?.studyFormatterFactory?.(e,s,t)??null;if(null!==r)return r}if(null!==t)switch(e.type){case"inherit":case"price":return new Ft.PriceFormatter({priceScale:t});case"volume":return(0,Lt.getVolumeFormatter)(Math.log10(t));case"percent":return(0,Lt.getPercentageFormatter)(Math.log10(t))}if("inherit"===e.type)return null;const r=(0,_.isNumber)(e.precision)?Math.pow(10,e.precision):void 0;switch(e.type){case"price":return new Ft.PriceFormatter({priceScale:r});case"volume":{let t=e.precision;return void 0===t&&(t=s&&(0,_.isNumber)(s.volume_precision)?s.volume_precision:0),(0,Lt.getVolumeFormatter)(t)}case"percent":return(0,Lt.getPercentageFormatter)(void 0===r?void 0:Math.log10(r));default:return Gt.logWarn(`Unsupported format type: ${e.type}`),null}}const cs=new Set(["first_visible_bar_time","last_visible_bar_time","subscribeRealtime"]);class us extends V.PriceDataSource{constructor(e,t,s,i,r,n,o){super(e),this._onStart=new w.Delegate,this._restarting=!1,this._paneViews=[],this._forceOverlaysPaneViews=[],this._legendView=null,this._floatingTooltipView=null,this._priceAxisViews=[],this._forceOverlayPriceAxisViews=[],this._priceAxisViewsBase=[],this._resolvedSymbols={},this._resolvedSymbolsByInput={},this._priceLinesAxisViews=[],this._labelPaneViews=[],this._forceOverlayLabelPaneViews=[],this._ownFirstValue=null,this._formatter=null,this._defaultFormatter=null,this._dataUpdated=new w.Delegate,this._currencySourceSymbolInputProperty=null,
+this._pineSourceCodeModel=null,this._alertSourceModel=null,this._onHibernationStateChange=new w.Delegate,this._symbolsResolved=new w.Delegate,this._statusChanged=new w.Delegate,this._inputsAnchorsPaneView=null,this._inputsLinesPaneView=null,this._inputsTimeAxisPaneViews=[],this._inputsPriceAxisPaneViews=[],this._sources=new P.WatchedObject([],y.compareTwoCollectionsByIds),this._status=new b.WatchedValue({type:xt.StudyStatusType.Undefined}),this._compileActiveStatus=new P.WatchedObject(null),this._compileErrorStatus=new P.WatchedObject(null),this._wasCompletedBefore=!1,this._isStarted=!1,this._isSubscribedToSessionId=!1,this._titleStrCache={},this._titleInPartsCache={},this._inputsInPartsCache={},this._children=[],this._graphicsPriceAxisViews=[],this._serverPlotOffsets=new P.WatchedObject({}),this._ongoingDataUpdate=Promise.resolve(),this._studyModified=!1,this._tagsChanged=new w.Delegate,this._turnaround="st0",this._pendingResolveSymbols=new Map,this._onIsActualIntervalChange=new w.Delegate,this._childStudyByRebind=new w.Delegate,this._lastNonEmptyPlotRowCache={},this._startMovingPoint=null,this._processHibernateBound=this.processHibernate.bind(this,1),this._maxOffset=new b.WatchedValue(0),this._currencySourceSymbolInfo=null,this._graphicsPriceRangeGroups=null,this._graphicsViewsReady=!1,this._visibleTimeRangeInputs=null,this._turnaroundCounter=0,this._deferredPinePatchProps=!1,this._propertiesPatched=Promise.resolve(),this._resetPropertiesPatched=Promise.resolve(),this._abortPatchPropsController=new AbortController,this._abortResetPatchPropsController=new AbortController,this._aboutToBeDestroyed=new w.Delegate,this._definitionsViewModel=null,this._plotFormatters=new Map,this._showPineVersionInStatusLine=new b.WatchedValue(!1).spawn(),this._onParentSourcesChanges=new w.Delegate,this._statusChangesSubscriber={},this._calculationTime=new b.WatchedValue(0),this._stateForAlertCache=null,this._idForAlertCache=null,this._idForAlertWV=new b.WatchedValue(""),this._chartApi=e.chartApi(),this._properties=t,this._originalMetaInfo=r,this._metaInfo=new b.WatchedValue(i),this._studyName=(0,Mt.combine)((e=>e.useVersionFromMetaInfo?(0,A.getStudyIdWithVersion)(e):this._getStudyIdWithLatestVersion()),this._metaInfo.weakReference()),this._hideMatches=i.inputs.filter((e=>e.hideWhenPlotsHidden)).map((e=>({id:e.id,plotIds:e.hideWhenPlotsHidden||[]}))),this._series=this._model.mainSeries(),this._series.onIntervalChanged().subscribe(this,this._calcIsActualInterval),this._series.alertCreationAvailable().subscribe(this._updateAlertCreationAvailable.bind(this)),this._showStudyArgumentsProperty=(0,X.combineProperty)(((e,t)=>e&&t),e.properties().childs().paneProperties.childs().legendProperties.childs().showStudyArguments.weakReference(),this._properties.childs().showLegendInputs.weakReference()),this._model.symbolAliasService()?.onAliasChanged().subscribe(this,(()=>{this._onFormatterPropsChanged(),this.invalidateTitleCache()})),e.collapsed().subscribe(this._processHibernateBound),this._sources.setValue(s),
+A.StudyMetaInfo.setChildStudyMetaInfoPropertiesSourceId(i,s[0]?.id(),t),s.forEach((e=>{e.setChild(this)})),[this._series,...s].forEach((e=>{e.currencyChanged().subscribe(this,this._onSourceCurrencyChanged),e.unitChanged().subscribe(this,this._onSourceUnitChanged),e.priceRangeReadyChanged().subscribe(this,this._onSourcePriceRangeReadyChanged),e.formatterChanged().subscribe(this,this._onSourceFormatterChanged),e.priceStepChanged().subscribe(this,this._onSourcePriceStepChanged)})),Zt&&this._model.mainSeries().properties().childs().statusViewStyle.childs().symbolTextSource.subscribe(this,(()=>{this.invalidateTitleCache(!0)}));const a=this._properties.childs();for(const e of A.StudyMetaInfo.getSourceInputIds(i))a.inputs.childs()[e]?.subscribe(this,this._onSourceInputChanged);this._plotOffsets=(0,Mt.combine)(((e,t,s,i)=>(i.plots??[]).reduce(((i,r)=>{const n=r.id,o=(e[n]??0)+(s?.childs()[n]?.childs().val.value()??0)+(t?.childs().val.value()??0);return i[n]=o,i}),{})),this._serverPlotOffsets.weakReference(),(0,X.createWVFromGetterAndSubscription)((()=>this.properties().childs().offset),this.properties().childs().offset??new w.Delegate).ownership(),(0,X.createWVFromGetterAndSubscription)((()=>this.properties().childs().offsets),this.properties().childs().offsets??new w.Delegate).ownership(),this._metaInfo.weakReference()),this._properties.subscribe(this,this._onPropertiesChanged),a.visible.subscribe(this,this._visibleChanged),a.visible.subscribe(this,(()=>this.processHibernate())),a.intervalsVisibilities.subscribe(this,this._calcIsActualInterval),a.inputs.subscribe(this,this._updateMaxOffsetValue),void 0!==a.offsets&&a.offsets.subscribe(this,this._updateMaxOffsetValue),void 0!==a.offset&&a.offset.subscribe(this,this._updateMaxOffsetValue),this._initializeCurrencySource(),W.hideAllIndicators().subscribe(this,this._visibleChanged);for(let e=0;e<i.plots.length;e++){const t=i.plots[e],s=t.id,r=a.styles.childs()[s],n=(0,L.isBarColorerPlot)(t);r&&!r.hasChild("display")&&r.merge({display:15}),r?.childs().display.subscribe(this,(()=>{this.processHibernate(),this.invalidateTitleCache(),n&&this._series.invalidateBarColorerCache()}))}for(const e of Object.keys(i.graphics))for(const t of Object.keys(i.graphics[e])){const s=a.graphics.childs()[e]?.childs()[t];s&&s.childs().visible&&(0,p.ensureDefined)(s.childs().visible).subscribe(this,(()=>this.processHibernate()))}this._isActualInterval=(0,Ct.isActualInterval)(this._series.intervalObj().value(),a.intervalsVisibilities),this._initializeStudyInputsPaneViews(),this._handler=e=>this._onData(e),this._valuesProvider=new F.StudyValuesProvider(this,e),this._tableViewValuesProvider=new Ht(this,e),this._graphics=new R.LiveStudyGraphics(i.graphics),this._chartApi=e.chartApi(),this._invalidateLastNonEmptyPlotRowCache(),this._data=new T.PlotList((0,kt.studyPlotFunctionMap)(i),kt.studyEmptyPlotValuePredicate),this._createViews(),this._recreatePriceFormattingDependencies(this._series.symbolInfo()),a.precision.subscribe(this,this._onFormatterPropsChanged),
+this._metaInfo.subscribe((()=>this._onFormatterPropsChanged())),this._showStudyArgumentsProperty.subscribe(this,(()=>this.invalidateTitleCache(!0))),a.inputs.subscribe(this,(()=>this.invalidateTitleCache(!0))),ee.enabled("update_study_formatter_on_symbol_resolve")&&e.mainSeries().dataEvents().symbolResolved().subscribe(this,this._recreatePriceFormattingDependencies),e.mainSeries().dataEvents().symbolResolved().subscribe(this,(()=>this.invalidateTitleCache(!0)));const l=new Set;if(this._simplePlotsCount=i.plots.filter(((e,t)=>{if((0,L.isLinePlot)(e))return!0;if((0,L.isOhlcPlot)(e)){const t=e.target;return!l.has(t)&&(l.add(t),!0)}return!1})).length,this.hasBarColorer()&&a.visible.subscribe(this,(()=>e.mainSeries().invalidateBarStylesCache)),this._definitionsViewModel=null,this._updateMaxOffsetValue(),i.inputs.some((e=>cs.has(e.id)))){this._visibleTimeRangeInputs=e.visibleRangeStudiesInputs().spawn();const t=this._visibleTimeRangeInputs.value();let s=null!==t;this._visibleTimeRangeInputs.subscribe((e=>{const t=()=>{this._onVisibleTimeRangeInputsChanged(e),s!==(null!==e)&&(s=null!==e,!s||this._restarting||this.isStarted()||this.start(!0))};this._statusChanged.unsubscribeAll(this._statusChangesSubscriber),this._status.value().type===xt.StudyStatusType.Loading?this._statusChanged.subscribe(this._statusChangesSubscriber,t,!0):t()})),t&&this._updateVisibleTimeRangeInputs(t,!1)}this._properties.setNameInOwner((0,Wt.propertyPathForSource)(this)),o&&this._pinePatchProps();const h=as(this.parentSourcesVW().weakReference());this._allOwnerSources=(0,Mt.combine)(((e,t)=>{const s=[];for(;null!==t;)s.push(t),t=t.ownerSource();return s}),h,(0,X.createWVFromGetterAndSubscription)((()=>this.ownerSource()),this.ownerSourceChanged()).ownership()),this._symbolSource=(0,Mt.combine)((e=>this._firstSourceOrSeries().symbolSource()),this._allOwnerSources.weakReference())}destroy(){this._signlePerformanceValue?.destroy(),this._aboutToBeDestroyed.fire(),null!==this._definitionsViewModel&&(this._definitionsViewModel.destroy(),this._definitionsViewModel=null),this._showStudyArgumentsProperty.unsubscribeAll(this),this._model.mainSeries().dataEvents().symbolResolved().unsubscribeAll(this),this._model.symbolAliasService()?.onAliasChanged().unsubscribeAll(this);this.parentSources().forEach((e=>{e.currencyChanged().unsubscribeAll(this),e.unitChanged().unsubscribeAll(this),e.priceRangeReadyChanged().unsubscribeAll(this),e.formatterChanged().unsubscribeAll(this),e.priceStepChanged().unsubscribeAll(this)})),this._series.properties().childs().statusViewStyle.childs().symbolTextSource.unsubscribeAll(this),this._series.onIntervalChanged().unsubscribeAll(this),this._series.alertCreationAvailable().unsubscribe(this._updateAlertCreationAvailable),this.formatterChanged().unsubscribe(this,this.invalidateTitleCache),W.hideAllIndicators().unsubscribe(this,this._visibleChanged),this._model.collapsed().unsubscribe(this._processHibernateBound),null!==this._currencySourceSymbolInputProperty&&this._currencySourceSymbolInputProperty.unsubscribeAll(this),
+this._legendView?.destroy(),this._floatingTooltipView?.destroy(),this._pineSourceCodeModel?.get()?.destroy(),this._visibleTimeRangeInputs?.destroy(),this._showPineVersionInStatusLine.destroy(),this._alertStateVersion?.destroy(),this._metaInfo.destroy(),this._studyName.destroy(),this._allOwnerSources.destroy(),this._sources.destroy(),this._symbolSource.destroy(),this._status.destroy(),this._compileActiveStatus.destroy(),this._compileErrorStatus.destroy(),this._plotOffsets.destroy(),this._serverPlotOffsets.destroy(),this._properties.destroy(),super.destroy()}setId(e){super.setId(e),this._properties.setNameInOwner((0,Wt.propertyPathForSource)(this))}properties(){return this._properties}propertiesPatched(){return this._propertiesPatched}isDraggable(){return!this._metaInfo.value().linkedToSeries}logs(){return null}logLevelMask(){const e=this._properties.childs().inputs.childs().__log_level.value();if(!(0,_.isNumber)(e)||e<0||e>7)throw new Error(`Value of log level is unexpected, current value is ${e}, but expected values from 0 to 7`);return{error:Boolean(1&e),warning:Boolean(2&e),info:Boolean(4&e)}}setLogLevelMask(e){const t=(Number(e.error)&&1)|(Number(e.warning)&&2)|(Number(e.info)&&4);this._properties.childs().inputs.childs().__log_level.setValue(t)}performance(){return new b.WatchedValue(null)}profilingEnabled(){return!!this._properties.childs().inputs.childs().__profile?.value()}enableProfiling(e){this._properties.childs().inputs.childs().__profile?.setValue(e)}onAboutToBeDestroyed(){return this._aboutToBeDestroyed}priceScale(e){return e?this._model.mainSeries().priceScale():super.priceScale()}lastValueData(e,t,s){const i={noData:!0},r=this.metaInfo().isPlotForceOverlay(e),n=r?this._model.mainSeries().priceScale():this.priceScale();if(this._model.timeScale().isEmpty()||null===n||n.isEmpty()||this.data().isEmpty())return i;const o=this._model.timeScale().visibleBarsStrictRange(),a=this.firstValue(!0,r);if(null===o||null===a)return i;if(!this._properties.childs().visible.value())return i;const l=this._properties.childs().styles,h=this._properties.childs().ohlcPlots;let c,u;if(l&&l.childs()[e]&&(c=l.childs()[e]),h&&h.childs()[e]&&(c=h.childs()[e]),!c||0===c.childs().display.value())return i;const d=this.metaInfo().plots;for(u=0;u<d.length;u++){const t=d[u];if(t.id===e||(0,L.isOhlcClosePlot)(t)&&t.target===e)break}const p=u+1,f=this.offset(e),m=this.nearestIndex(o.lastBar()-f,O.PlotRowSearchMode.NearestLeft,p);if(void 0===m)return i;const y=this._lastNonEmptyPlotRow(p),g=null!==y&&o.contains(y.index),v=null!==y?y.value:null,S=t||g?v:this.data().valueAt(m);if(!S||!(0,_.isNumber)(S[p]))return i;const b=S[p],P=this._valuesProvider.getPlotColor(u,S),w=n.priceToCoordinate(b,a),I=this.plotFormatter(e).format(b),x={...n.getFormattedValues(b,a,void 0,I),noData:!1,color:P,floatCoordinate:w,coordinate:w};return s&&(x.price=b),x}isFailed(){return this.status().type===xt.StudyStatusType.Error}isLoading(){return this.status().type===xt.StudyStatusType.Loading}isCompleted(){return this.status().type===xt.StudyStatusType.Completed}
+isSymbolInvalid(){const e=this._status.value();return e.type===xt.StudyStatusType.Error&&e.errorDescription.error===$t}series(){return this._series}model(){return this._model}state(e,t){const s=(0,p.ensureNotNull)((0,g.getStudyClassName)(this.constructor)),i=this.metaInfo(),r={type:s,id:this.id(),state:this.properties().state(),zorder:this.zorder(),ownFirstValue:this.isVisible()?null:this._ownFirstValue,metaInfo:this._originalMetaInfo.state()},n=d(r.metaInfo,this._metaInfo.value().state());(0,o.default)(n)||(r.metaInfoPatch=n);const a=this._sources.value().map((e=>e.id()));if(a.length&&(r.parentSources=a),e){let e=this.data();const t=this._model.timeScale(),s=this._seriesDataRangeToSave(e);null!==s&&(e=e.range(s.firstBar(),s.lastBar())),r.data=e.state(),r.data.symbols=this._resolvedSymbols,r.data.graphics=(0,R.saveStudyGraphics)(this.graphics(),t.visibleBarsStrictRange()),r.data.plotOffsets=this._serverPlotOffsets.value()}this.ownerSource()&&(r.ownerSource=this.ownerSource()?.id());for(let e=0;e<i.inputs.length;e++)if("bar_time"===i.inputs[e].type){const t=i.inputs[e].id,s=r.state.inputs[t];if(s<0){const e=this._rightOffsetToUnixTime(-s);r.state.inputs[t]=e&&e>=0?e:0}}if(r.state?.inputs){const e=r.metaInfo.inputs.find((e=>"ILScript"===e.name));e&&delete r.state.inputs[e.id],delete r.state.inputs.__log_level,delete r.state.inputs.__profile}const l=this.stateCustomFields();return l&&(r.customFields=l),r}stateCustomFields(){const e=this._compileErrorStatus.value();if(e)return{compileErrorDescription:e.errorDescription}}restoreStateCustomFields(e){const t=e.compileErrorDescription;t&&this.setErrorCompilation([(0,p.ensureDefined)(t.editorError)])}restoreData(e){this._invalidateLastNonEmptyPlotRowCache(),this.data().restoreState(e),this._resolvedSymbols=e.symbols??{},this._graphics=e.graphics?(0,R.loadStudyGraphics)(e.graphics):(0,R.emptyStudyGraphics)(),this._postProcessGraphics(),this._serverPlotOffsets.setValue(e.plotOffsets??{}),this._setStatus({type:xt.StudyStatusType.Completed},!0)}hasStateForAlert(){return!1}stateForAlert(){throw new Error("Not implemented")}async stateForAlertAsync(){throw new Error("Not implemented")}idForAlert(){return super.idForAlert()}hasBarColorer(){return this._metaInfo.value().plots.some(L.isBarColorerPlot)}barColorer(){const e=this._metaInfo.value().plots;let t=null;for(let s=e.length-1;s>=0;s--)if((0,L.isBarColorerPlot)(e[s])){const e=new Bt(this,s);null===t?t=e:t.pushBackBarColorer(e)}return t}isSavedInStudyTemplates(){return this._metaInfo.value().inputs.every((e=>"bar_time"!==e.type))}restart(e){this._restarting=!0,this.clearData(),(e||ee.enabled("stop_study_on_restart"))&&this.stop(),setTimeout(this.start.bind(this),0)}stop(e,t){if(!0===e&&this._children)for(const e of this._children)e.stop(!0);this._stopStudyOnServer(),this.clearData(),this._unsubscribeToSessionId(),this.recalculate()}disconnect(){this._isStarted=!1,this._model.isSnapshot()||(this._resolvedSymbols={},this._resolvedSymbolsByInput={})}sourceId(){return this._id.value()}parentSources(){return this._sources.value()}
+parentSourcesVW(){return this._sources}symbolSource(){return this._symbolSource.value()}symbolSourceWV(){return this._symbolSource.readonly()}valueAt(e,t){return this.symbolSource().valueAt(e,t)}barsProvider(){return this._firstSourceOrSeries().barsProvider()}ownerSource(){return this.isChildStudy()?this._sources.value()[0]:super.ownerSource()}isChildStudy(){return this._sources.value().length>0}hasChildren(){return this._children.length>0}isStarted(){return this._isStarted}isRestarting(){return this._restarting}isActualInterval(){return this._isActualInterval}onIsActualIntervalChange(){return this._onIsActualIntervalChange}isVisible(){const e=this._properties.childs();if(this._model.collapsed().value()||!e.visible.value()||!this.isActualInterval())return!1;const t=this.metaInfo();if(t.plots.length>0)for(let s=0;s<t.plots.length;s++){const i=t.plots[s].id,r=e.styles.childs()[i];if(void 0===r)continue;if(0!==r.childs().display.value())return!0}if(t.bands)for(let s=0;s<t.bands.length;s++)if(e.bands.childs()[s].childs().visible.value())return!0;for(const s of Object.keys(t.graphics))for(const i of Object.keys(t.graphics[s])){const t=e.graphics.childs()[s]?.childs()[i];if(void 0!==t&&(t.child("visible")?.value()??1))return!0}if(t.filledAreas)for(let s=0;s<t.filledAreas.length;s++)if(e.filledAreasStyle.childs()[t.filledAreas[s].id].childs().visible.value())return!0;return!1}async start(e,t,s){const i=this._model.mainSeries();await i.seriesCreated(),await Promise.all(this._sources.value().filter((e=>e.isHibernated())).map((e=>e.start())));const r=!(this.isHibernationAllowed()&&!this.isVisible())||!0===t;if(this._chartApi&&this._chartApi.isConnected().value()&&r)try{await this._allSymbolsAreResolved(),await this._startAfterSymbolsResolved(e,t)}catch(e){const t=`ERROR: ${this._debugId()} start failed, ${e}`;Gt.logError(t),this._restarting=!1,"TooManyStudies"===e?.cause&&(0,S.showTooManyStudiesNotice)(this._chartApi.getStudyCounter())}r||void 0!==this._inputs||(this._inputs=this._apiInputs())}replaceData(e,t,s){this._invalidateLastNonEmptyPlotRowCache(),this.data().remove(e+1),this.data().addTail(s,t)}inputs(e){const t=(0,n.default)((0,_.clone)(Jt),e||{});t.skipOptionalEmptySymbolInputs&&(t.keepOptionalSymbolsEmpty=!0);return this._buildInputs(t)}data(){return this._data}moveData(e){this._ongoingDataUpdate=this._ongoingDataUpdate.then((()=>{this._invalidateLastNonEmptyPlotRowCache(),this._moveData(e),this.data().isEmpty()||this._onIndexDiffsApplied(e)}))}plots(){return this.data()}metaInfo(){return this._metaInfo.value()}status(){return this._compileActiveStatus.value()??this._compileErrorStatus.value()??this._status.value()}name(e){return e?this.metaInfo().shortDescription||"Study":this.metaInfo().description||"Study"}title(e,t,s,i,r,n){i=void 0===i?!this._showStudyArgumentsProperty.value():i;const o=JSON.stringify([e,t,s,i,r,n]);if(this._titleStrCache[o])return this._titleStrCache[o];if(this._titleInPartsCache[o])return this._joinTitlesParts(this._titleInPartsCache[o]);const a=this._title(e,t,s,i,r,n)
+;return this._titleStrCache[o]=a,a}titleInParts(e,t,s,i,r){i=void 0===i?!this._showStudyArgumentsProperty.value():i;const n=JSON.stringify([e,t,s,i,r]);if(this._titleInPartsCache[n])return this._titleInPartsCache[n];const o=this._titleInParts(e,t,s,i,r);return this._titleInPartsCache[n]=o,o}inputsInParts(e,t=!0,s,i,r){const n=!this._showStudyArgumentsProperty.value(),o=ee.enabled("always_show_study_symbol_input_values_in_legend"),a=n&&o;if(n&&!o&&e===Y.TitleDisplayTarget.StatusLine)return null;const l=JSON.stringify([e,t,s,i,r]);if(this._inputsInPartsCache[l])return this._inputsInPartsCache[l];const h=[],c=this.metaInfo(),u=this._titleInputs((0,zt.toInputDisplayFlags)(e),i,!0),d=c.inputs.filter((e=>u.hasOwnProperty(e.id)&&(!a||"symbol"===e.type||e?.isAlwaysShownInLegend))).map((e=>{let t=u[e.id];if("symbol"===e.type){const s=this._properties.childs().inputs.child(e.id)?.value();if(s){const e=this._resolvedSymbolsByInput[s];e&&(t=this._model.symbolAliasService()?.getAliasByProName(e.pro_name)?.aliasName??t)}}return{meta:e,value:t}})),f={};if(d.length>0){if(this.isChildStudy())for(let s=0;s<c.inputs.length;++s){const n=c.inputs[s];if(!A.StudyMetaInfo.isSourceInput(n))continue;const o=n.id,a=(0,p.ensureDefined)(this._properties.childs().inputs.child(o)).value();if(a.indexOf("$")>=0){const s=this.parentSourceForInput(a);if(s instanceof us){const n=s.metaInfo(),o=s.title(e,t,{},!0,i,r);if(1===n.plots.length)f[a]=o;else{const e=a.split("$")[1],t=n.plots[parseInt(e)]?.id,s=n.styles&&n.styles[t],i=s&&s.title||t;f[a]=o+": "+i}}}}d.forEach((({meta:e,value:t})=>{let i;i="time"===e.type?new Date(t).toISOString():(0,_.isNumber)(t)?(0,Lt.getNumericFormatter)().format(t):f&&f[t.toString()]||t.toString(),s&&s[i.toString()]&&(i=s[i.toString()]),h.push({title:(0,Ut.getTranslatedInputTitle)(e.name),value:i})}))}return this._inputsInPartsCache[l]=h,h}invalidateTitleCache(e){if(this._titleStrCache={},this._titleInPartsCache={},this._inputsInPartsCache={},!0===e&&this._children)for(let t=0;t<this._children.length;++t)this._children[t].invalidateTitleCache(e)}graphics(){return this._graphics}graphicsInfo(){return this._metaInfo.value().graphics}priceLabelText(e){const t=this._metaInfo.value(),s=t.styles,i=t.ohlcPlots;let r;s&&s[e]&&(r=s[e]),i&&i[e]&&(r=i[e]);const n=(0,p.ensureDefined)(r).title;return 1!==this._simplePlotsCount||(0,L.isPlotTitleDefined)(n)?t.is_price_study&&n!==t.shortDescription?""===n?t.shortDescription:t.shortDescription+":"+n:n:t.shortDescription}setOwnFirstValue(e){this._ownFirstValue=e}firstValue(e,t){if(t)return this._series.firstValue();const s=this._metaInfo.value();if(!this.isChildStudy()&&"Compare@tv-basicstudies"===s.id||!s.is_price_study){const t=this._model.timeScale().visibleBarsStrictRange();if(null===t)return null;const i=this.properties().childs();if(!i.visible.value()||!this.isActualInterval()||null!==this._startMovingPoint)return this._ownFirstValue;const r=t.firstBar(),n=t.lastBar();let o=null;if(null===o){const t=new Set,a=s.filledAreas||[];for(let e=0;e<a.length;e++){const s=a[e]
+;i.filledAreasStyle.childs()[s.id].childs().visible.value()&&(t.add(s.objAId),t.add(s.objBId))}const l=s.plots||[];for(const a of this.data().rangeIterator(r,n)){const r=a.value;for(let n=0;n<l.length;++n){const a=l[n],h=a.id;if((0,L.isColorerPlot)(a)||s.isPlotForceOverlay(h))continue;const c=r[n+1];if(null==c)continue;if((0!==(0,p.ensureDefined)(i.styles.childs()[h]).childs().display.value()||t.has(h))&&!(e&&Math.abs(c)<1e-10)){o=c;break}}if(null!==o)break}}return this._ownFirstValue=o,null!==o?o:this._bandsFirstValue(e)}if(this.isChildStudy()){const e=this._getNonPriceParent();if(e&&this.priceScale()===e.priceScale())return null!==e._ownFirstValue?e._ownFirstValue:e.firstValue()}return this._series.firstValue()}desiredPriceScalePosition(){if(this.metaInfo().isTVScriptStub)return"overlay";if(this.metaInfo().linkedToSeries)return"as-series";switch(this.metaInfo().priceScale){case 1:return"left";case 0:return"right";case 2:return"overlay";default:return null}}offset(e){return this._plotOffsets.value()?.[e]??0}tags(){const e=this._metaInfo.value();return!e.description||e.isTVScriptStub||e.is_hidden_study||e.isTVScript&&"tv-scripting"===e.productId?[]:[e.description]}copiable(){return es&&!this.isChildStudy()}setPriceScale(e){super.setPriceScale(e),(0,Nt.emit)("study_event",this.id(),"price_scale_changed")}priceRange(e,t,s){let i=null;const r=this._metaInfo.value(),n=this._fillPrecalculatedAutoscaleInfo(e,t,s);let o=this.data().minMaxOnRangeCached(e,t,n.fields);if(o=(0,T.mergeMinMax)(n.baseValueMinMax,o),n.useMainSeriesRange){const s=[{name:"low",offset:0},{name:"high",offset:0}],i=this.series().data().bars().minMaxOnRangeCached(e,t,s);o=(0,T.mergeMinMax)(o,i)}if(null!==o&&(i=new M.PriceRange(o.min,o.max)),r.bands&&s.targetPriceScale===this.priceScale())for(let e=0;e<r.bands.length;e++){const t=(0,p.ensureDefined)(this._properties.childs().bands.childs()[e]).childs();if(t.visible.value()){const e=t.value.value();if(!(0,_.isNumber)(e))continue;i?i.apply(e,e):i=new M.PriceRange(e,e)}}return this._postProcessPriceRange(i,s)}autoScaleInfo(e,t,s){const i=this.priceRange(e,t,s),r=(this.priceScale()===this._series.priceScale()||(this.priceScale(),s.targetPriceScale),{topPixelMargin:0,bottomPixelMargin:0});return{range:i,topPixelMargin:r.topPixelMargin,bottomPixelMargin:r.bottomPixelMargin}}formatter(e){return this._formatter??this._firstSourceOrSeries().formatter(!1)}defaultFormatter(){const e=this._firstSourceOrSeries();return this._defaultFormatter??e.defaultFormatter?.()??e.formatter()}plotFormatter(e){return this._plotFormatters.get(e)??this.formatter()}isMultiPaneAvailable(){return this._metaInfo.value().hasForceOverlayPlots()||(0,x.hasForceOverlayPrimitives)(this._metaInfo.value())}isMultiPaneEnabled(){return this._metaInfo.value().hasForceOverlayPlots()}updateAllViews(e){const t=this._model.paneForSource(this),s=this._model.mainPane(),i="viewport-change"===e.type&&e.pane&&e.pane!==s;"viewport-change"===e.type&&e.pane&&e.pane!==t||(this._paneViews.forEach((t=>t.update(e))),this._labelPaneViews.forEach((t=>t.update(e))),
+this._dataWindowView?.update(e),this._legendView?.update(e),this._statusView?.update(e),this._floatingTooltipView?.update(e),this._priceAxisViews.forEach((t=>t.update(e))),this._priceLinesAxisViews.forEach((t=>t.update(e))),this._inputsLinesPaneView?.update(e),this._inputsAnchorsPaneView?.update(e),this._inputsTimeAxisPaneViews.forEach((t=>t.update(e))),this._inputsPriceAxisPaneViews.forEach((t=>t.update(e)))),i||(this._forceOverlaysPaneViews.forEach((t=>t.update(e))),this._forceOverlayLabelPaneViews.forEach((t=>t.update(e))),this._forceOverlayPriceAxisViews.forEach((t=>t.update(e)))),"data-source-change"===e.type&&e.sourceId===this.id()&&e.clearData&&this._children.forEach((e=>e.updateAllViews({type:"data-source-change",sourceId:e.id(),clearData:!0})))}removeByRemoveAllStudies(){return!0}studyName(){return this._studyName}nearestIndex(e,t,s){return this.data().search(e,t,s)?.index}getMinFirstBarIndexForPlot(e){const t=this._properties.childs(),s=this._metaInfo,i=t.styles.childs()[e]?.child("showLast")?.value()??t.filledAreasStyle.childs()[e]?.child("showLast")?.value()??s.value().styles?.[e]?.showLast??t.ohlcPlots.childs()[e]?.child("showLast")?.value()??s.value().ohlcPlots?.[e]?.showLast??null;if(null===i)return-1/0;const r=this.data().lastIndex();return null===r?-1/0:r-i+1}guiPlotName(e,t){const s=this._metaInfo.value(),i=s.plots.find((e=>e.id===t));if(void 0!==i){return((0,L.isOhlcPlot)(i)?s.ohlcPlots?.[i.target]?.title:s.styles?.[t]?.title)??this.title(e)}return this.title(e)}childStudyByRebind(){return this._childStudyByRebind}isPine(){return void 0!==this._metaInfo.value().pine}isStandardPine(){return this.isPine()&&A.StudyMetaInfo.isStandardPine(this._metaInfo.value().id)}isLinkedToSeries(){return!0===this._metaInfo.value().linkedToSeries}preferredZOrder(){return!1===this._metaInfo.value().behind_chart?0:null}defaultPlotIdForAlert(){return this._metaInfo.value().plots?.[0]?.id??null}resolvedSymbolInfoBySymbol(e){return this._resolvedSymbols&&e&&this._resolvedSymbols[this._getSymbolForResolve(e)]||null}hasPendingUnresolvedSymbols(){return this._pendingResolveSymbols.size>0}hasSymbolInputs(){return this._metaInfo.value().inputs.some((e=>"symbol"===e.type))}currency(){if(null!==this._currencySourceSymbolInfo)return(0,Tt.symbolCurrency)(this._currencySourceSymbolInfo);const e=this.metaInfo();return Boolean(e)&&e.is_price_study?this._firstSourceOrSeries().currency():null}currencySourceSymbolInfo(){return this._currencySourceSymbolInfo??this.symbolSource()?.symbolInfo()??null}unit(){const e=this.metaInfo();return Boolean(e)&&e.is_price_study?this._firstSourceOrSeries().unit():null}canOverrideMinTick(){return!1}dataWindowView(){return this._dataWindowView}statusView(){return this._statusView}legendView(){return this._legendView}chartFloatingTooltipView(){return this._floatingTooltipView}pineSourceCodeModel(){return Promise.resolve(null)}alertSourceModel(){return this._alertSourceModel}inputsForAlertState(){return this.inputs()}sessionId(){return this._firstSourceOrSeries().sessionId()}sessionIdChanged(){
+return this._firstSourceOrSeries().sessionIdChanged()}getSymbolString(e){return""===e?"":(0,U.encodeExtendedSymbolOrGetSimpleSymbolString)(this._getSymbolObject(e))}onStatusChanged(){return this._statusChanged}onDataUpdated(){return this._dataUpdated}symbolsResolved(){return this._symbolsResolved}onHibernationStateChange(){return this._onHibernationStateChange}valuesProvider(){return this._valuesProvider}legendValuesProvider(){return new E(this,this.model())}tableViewValuesProvider(){return this._tableViewValuesProvider}statusProvider(e){return new $.StudyStatusProvider(this)}chartFloatingTooltipValuesProvider(){return new K(this,this.model())}correctScaleMargins(e){if("Volume"===this.metaInfo().shortId){const t=this.model().paneForSource(this);return null!==t&&t.isOverlay(this)&&t.containsMainSeries()?{top:.75,bottom:0}:{top:e.top,bottom:0}}return e}canBeHiddenByGlobalFlag(){return!0}isSourceHidden(){return!this.isVisible()||this.canBeHiddenByGlobalFlag()&&W.hideAllIndicators().value()}wasCompletedBefore(){return this._wasCompletedBefore}paneViews(e){const t=this._model.mainPane();if(this.isSourceHidden())return null;if(!e.hasPriceDataSource(this))return e!==t?null:this._forceOverlaysPaneViews;const s=[];return!this._startMovingPoint&&this._wasCompletedBefore&&s.push(...this._paneViews.filter((e=>!e.isForceOverlay?.()))),this._inputsLinesPaneView&&(this._startMovingPoint||this._model.selection().isSelected(this))&&s.push(this._inputsLinesPaneView),this._inputsAnchorsPaneView&&s.push(this._inputsAnchorsPaneView),e===t&&s.push(...this._forceOverlaysPaneViews),s}labelPaneViews(e){const t=this._model.mainPane();if(this.isSourceHidden()||!e.hasPriceDataSource(this))return this._metaInfo.value().hasForceOverlayPlots()?e!==t?null:this._forceOverlayLabelPaneViews:null;const s=[...this._labelPaneViews];return e===t&&s.push(...this._forceOverlayLabelPaneViews),s}timeAxisViews(){return this._model.selection().isSelected(this)?this._inputsTimeAxisPaneViews:null}priceAxisViews(e,t){if(t!==this.priceScale()&&t===this._model.mainSeries().priceScale()&&!e.hasDataSource(this))return this._forceOverlayPriceAxisViews;const s=this._properties.childs().oldShowLastValue;if(s&&!s.value())return null;let i=this._priceAxisViews.slice();return this._model.selection().isSelected(this)&&(i=i.concat(this._inputsPriceAxisPaneViews)),t===this._model.mainSeries().priceScale()&&(i=i.concat(this._forceOverlayPriceAxisViews)),e.findTargetPriceAxisViews(this,t,i,this._priceLinesAxisViews)}movable(){return null!==this._inputsAnchorsPaneView}startMoving(e,t,s,i){this._startMovingPoint=e}move(e,t,s,i){if(void 0!==e.logical&&null!==this._startMovingPoint){if(Array.isArray(t)){const s=t;this._updateInputValue(e.logical,s[0]),this._updateInputValue(e.logical,s[1])}else this._updateInputValue(e.logical,t);this.updateAllViews((0,N.sourceChangeEvent)(this.id()))}}endMoving(e,t){return this._startMovingPoint=null,{indexesChanged:!1,pricesChanged:!1}}clearData(){this._invalidateLastNonEmptyPlotRowCache(),
+this._ongoingDataUpdate=this._ongoingDataUpdate.then((()=>{this._clearData(),this._graphics instanceof R.LiveStudyGraphics&&this._graphics?.clear(),this._serverPlotOffsets.setValue({})})),this.hasBarColorer()&&this._model.mainSeries().invalidateBarStylesCache(),this.updateAllViews((0,N.sourceChangeEvent)({sourceId:this.id(),clearData:!0}))}convertYCoordinateToPriceForMoving(e,t){const s=this.priceScale();if(!t||!s||s.isEmpty())return null;const i=t.firstValue();return null===i?null:s.coordinateToPrice(e,i)}processHibernate(e){const t=this.isVisible();if(!this.isStarted()&&t&&(this._sources.value().forEach((e=>{e.processHibernate()})),this.start(void 0,void 0,e),this._onHibernationStateChange.fire(!1)),this.isHibernationAllowed()&&this.isStarted()&&!t){for(const e of this._children)e.processHibernate();this.stop(void 0,e),this._onHibernationStateChange.fire(!0)}}isHibernationAllowed(){return!this.metaInfo().historyCalculationMayChange&&(!this.hasChildren()||!!this._model.collapsed().value()&&this._children.every((e=>e.isHibernationAllowed())))}isPlotVisibleAt(e,t){let s;const i=this.metaInfo().plots.find((t=>t.id===e));if(s=void 0!==i?(0,L.isOhlcPlot)(i)?this._properties.childs().ohlcPlots.childs()[i.target]:this._properties.childs().styles.childs()[e]:this._properties.childs().ohlcPlots.childs()[e],void 0===s)throw new Error(`Study does not contain ${e} plot`);const r=s.childs().display.value();return null!==r&&(r&t)===t}recalculate(){const e=this._model.paneForSource(this);this._model.recalculatePane(e,(0,N.sourceChangeEvent)(this.id())),this._model.updateSource(this)}maxOffset(){return this._maxOffset}onStart(){return this._onStart}onParentSourcesChanges(){return this._onParentSourcesChanges}isHibernated(){return!this.isVisible()&&!this.isStarted()}graphicsViewsReady(){return this._graphicsViewsReady}setLoadingCompilationActive(e){0}setErrorCompilation(e){0}hasCompileError(){return null!==this._compileErrorStatus.value()}turnaround(e){if(!e)return this._turnaround;return function(e,t){let s=t.turnaround,i=[t];for(;i.length>0;){let e=[];const t=[];i.forEach((s=>{const i=J(s.sourceStudies).sort(q);if(i.length>0){e=e.concat(i);const s=i.map((e=>e.turnaround)).join("_");t.push(s)}})),t.length&&(s=t.join("_")+"_"+s),i=e}return e+"_"+s}(this._series.seriesSource().turnaround(),Z(this))}canHaveChildren(){return this._canHaveChildren=this._canHaveChildren??A.StudyMetaInfo.canHaveChildren(this._metaInfo.value()),this._canHaveChildren}setChild(e){-1===this._children.indexOf(e)&&this._children.push(e)}unsetChild(e){const t=this._children.indexOf(e);~t&&this._children.splice(t,1)}getAllChildren(){const e=this._children.slice();for(let t=0;t<e.length;++t){const s=e[t].getAllChildren();for(let t=0;t<s.length;++t)~e.indexOf(s[t])||e.push(s[t])}return e}parentSourceForInput(e){if(e.includes("$")){const t=e.split("$")[0];return this._sources.value().find((e=>e.id()===t))??null}return this._series}priceStep(){return this._priceStep||this._firstSourceOrSeries().priceStep(!1)}recreatePriceFormatter(){
+this._recreatePriceFormattingDependencies()}setOwnerSource(e){super.setOwnerSource(e),this._recreatePriceFormattingDependencies()}onTagsChanged(){return this._tagsChanged}getPropertyDefinitionsViewModel(){return null===this._definitionsViewModel?this._getPropertyDefinitionsViewModelClass().then((e=>null===e||this._isDestroyed?null:(null===this._definitionsViewModel&&(this._definitionsViewModel=new e(this._model.undoModel(),this)),this._definitionsViewModel))):Promise.resolve(this._definitionsViewModel)}calculationTime(){return this._calculationTime.readonly()}contextMenuStatName(){return"IndicatorContextMenu"}metaInfoWV(){return this._metaInfo.readonly()}async patchPropertiesAfterResetDefaults(){throw new Error("Not implemented")}_getPropertyDefinitionsViewModelClass(){return Promise.resolve(null)}_alertMetaInfo(){return this.metaInfo()}_createStudyOnServer(){if(this._isDestroyed)return!1;this._isStarted=!0,this._incrementTurnaround();const e=(0,p.ensureDefined)(this._inputs);let t;return t=this._chartApi.createStudy(this.sourceId(),this._turnaround,this.isChildStudy()?(0,p.ensureNotNull)(this._sources.value()[0].sourceId()):(0,p.ensureNotNull)(this._series.seriesSource().instanceId()),this._studyName.value(),e,this._handler,this._studySpec()),t?(performance.mark(`calculate_study_${this._id.value()}`),!0):(this._isStarted=!1,t)}_stopStudyOnServer(){this._chartApi&&this._chartApi.isConnected().value()&&this.isStarted()&&(this._chartApi.removeStudy(this.sourceId()),this._setStatus({type:xt.StudyStatusType.Undefined})),performance.clearMarks(`calculate_study_${this.sourceId()}`),this._isStarted=!1}_modifyStudyOnServer(e,t){this._chartApi.modifyStudy(this.sourceId(),this._turnaround,e,this._handler,t),performance.mark(`calculate_study_${this.sourceId()}`)}_sendNotifyCommand(e,t){this._chartApi.notifyStudy(this.sourceId(),e,t)}_transformData(e){}_plotsDataRange(){const e=this.plots().firstIndex(),t=this.plots().lastIndex();return null!==e&&null!==t?[e,t]:null}_invalidateLastNonEmptyPlotRowCache(){this._lastNonEmptyPlotRowCache={}}_collectDepsForAlert(){throw new Error("Not implemented")}_allInputsAreValid(){if(null===this._visibleTimeRangeInputs?.value())return!1;for(const e of this._metaInfo.value().inputs)if("bar_time"===e.type){const t=e.id;if(null==this._properties.childs().inputs.childs()[t].value())return!1}return!0}async _startAfterSymbolsResolved(e,t){await Promise.all(this._sources.value().map((e=>!e.isStarted()||e.isRestarting()?new Promise((t=>{e.onStart().subscribe(this,t,!0)})):Promise.resolve()))),this.isStarted()&&!this._restarting||(this._restarting=!1,this._allInputsAreValid()&&!this.metaInfo().isTVScriptStub&&(this._inputs=this._apiInputs(),this._createStudyOnServer()&&(this._subscribeToSessionId(),this._onStart.fire(),!0===e&&this._children&&await this._children.map((e=>e.start(!0,t))))))}async _changeInputsImpl(e,t){const i=this._calcSources(),r=this._metaInfo.value(),n=os(),o=()=>{for(const s of r.inputs){if("source"!==s.type)continue;const i=e[s.id].v,r=t[s.id].v;if(i!==r){(0,
+p.ensureDefined)(this._properties.childs().inputs.child(s.id)).setValue(r)}}};if(this.isStarted()&&this._chartApi.isConnected().value()&&n>0&&!this._chartApi.canCreateStudy(this._studySpec(!0),!0).success){const e=window.user.pro_plan,t="pro_premium_expert"===e||"pro_premium_expert_trial"===e;return createGoProDialog({feature:"studyOnStudy",hideLimitTable:t,actions:e&&t?[{text:m.t(null,void 0,s(15462)),action:PredefinedAction.Close}]:void 0}),void o()}this._inputs=e;let a=!1;const l=Object.values(Q.RangeDependentStudyInputNames);for(const s of Object.keys(e))if(JSON.stringify(e[s])!==JSON.stringify(t[s])&&!l.includes(s)){a=!0;break}this._incrementTurnaround(),a&&this.disablePriceRangeReady();try{await this._updateParentSources(i,n,!0),this._modifyStudyOnServer(e,n),this._studyModified=!0}catch(e){Gt.logError(`Error applying parent sources: ${e}`),o()}this.invalidateTitleCache()}_createPriceAxisView(e){return new Rt.StudyPriceAxisView(this,{plotIndex:e})}_createPriceLineAxisView(e){return new Ot.StudyPriceLineAxisView(this,e)}_createStudyPlotPaneView(e){return new lt.StudyPlotPaneView(this,this._series,this._model,e)}_createViews(){this._priceAxisViewsBase=[],this._forceOverlayPriceAxisViews=[],this._priceLinesAxisViews=[],this._paneViews=[],this._forceOverlaysPaneViews=[],this._labelPaneViews=[],this._forceOverlayLabelPaneViews=[];const e=new Set,t=this.metaInfo(),s=Boolean(t.usePlotsZOrder),i=new Map,r=this._properties.childs();if(r.filledAreasStyle&&t.filledAreas)for(let e=0;e<t.filledAreas.length;++e){const n=t.filledAreas[e],o=(0,p.ensureDefined)(r.filledAreasStyle.childs()[n.id]),a=ns(t,n.id);let l;if("plot_plot"===n.type||a?l=new mt(this,this.model(),n,o):"hline_hline"===n.type?l=new It(this,n,o):Gt.logWarn("Unsupported filledArea type: "+n.type),void 0!==l){let e=!1;if("plot_plot"===n.type&&(e=t.isPlotForceOverlay(n.objAId)),e)this._forceOverlaysPaneViews.push(l);else{const e=s?(0,p.ensureDefined)(n.zorder):i.size;rs(e,i),i.set(e,{paneViews:[l]})}}}{let r=-1e5;for(let n=0;n<t.plots.length;n++){const o=t.plots[n];let a,l,h,c,u,d=t.isPlotForceOverlay(o.id);if((0,L.isNonVisualPlot)(o))continue;let _=o.id,f=t.styles;const m=(0,L.isBgColorerPlot)(o);if(m)a=new oe(this,this._series,this._model,_);else if((0,L.isShapesPlot)(o))a=new ze(this,this._series,this._model,_);else if((0,L.isCharsPlot)(o))a=new Xe(this,this._series,this._model,_);else if((0,L.isArrowsPlot)(o))a=new tt(this,this._series,this._model,_);else if((0,L.isOhlcPlot)(o)){const s=o.target;if(e.has(s))continue;if(d=t.isPlotForceOverlay(s),e.add(s),ss(t,n))a=new rt(this,this._series,this._model,s);else{if(!is(t,n)){Gt.logError(`plot ${o.id} looks to be invalid`);continue}a=new ot(this,this._series,this._model,s)}c=this._createPriceAxisView(s),h=new at.PanePriceAxisView(c,this,this._model),_=s,f=t.ohlcPlots}else(0,L.isDataPlot)(o)||(c=this._createPriceAxisView(_),u=this._createPriceLineAxisView(_),a=this._createStudyPlotPaneView(_),this._properties.childs().styles.childs()[_]?.child("trackPrice")?.value()&&(l=new ut(this,_)),
+h=new Et(c,this,this._model,_));const y=s?m?r++:(0,p.ensureDefined)(f?.[_]?.zorder):i.size;if(rs(y,i),d)c&&this._forceOverlayPriceAxisViews.push(c),a&&this._forceOverlaysPaneViews.push(a),h&&this._forceOverlayLabelPaneViews.push(h);else{const e={paneViews:void 0!==a?[a]:[],labelView:h,priceAxisView:c,priceLineAxisView:u};void 0!==l&&e.paneViews.push(l),i.set(y,e)}}}(this._metaInfo.value().bands??[]).forEach(((e,t)=>{const n=r.bands.childs()[t];if(n&&n.childs().visible.value()){const t=new St(n,this),r=s?(0,p.ensureDefined)(e.zorder):i.size;rs(r,i),i.set(r,{paneViews:[t]})}})),r.bandsBackground&&((0,p.assert)(!s,"'usePlotsZOrder' flag does not supported"),i.set(i.size,{paneViews:[new wt(this)]}));const n=this._paneViews,o=this._forceOverlaysPaneViews;this._createGraphicsPaneViews().then((e=>{for(let t=0;t<e.regularPaneViews.length;t++)n.push(e.regularPaneViews[t]);for(let t=0;t<e.forceOverlayPaneViews.length;t++)o.push(e.forceOverlayPaneViews[t]);this._model.lightUpdate(),this._graphicsViewsReady=!0})),r.areaBackground&&((0,p.assert)(!s,"'usePlotsZOrder' flag does not supported"),i.set(i.size,{paneViews:[new dt.AreaBackgroundPaneView(this,this.model())]}));const a=Array.from(i.keys()).sort(((e,t)=>e-t));for(let e=0;e<a.length;e++){const t=(0,p.ensureDefined)(i.get(a[e]));this._paneViews.push(...t.paneViews),t.labelView&&this._labelPaneViews.push(t.labelView),t.priceAxisView&&this._priceAxisViewsBase.push(t.priceAxisView),t.priceLineAxisView&&this._priceLinesAxisViews.push(t.priceLineAxisView)}this._dataWindowView||(this._dataWindowView=new yt.StudyDataWindowView(this,this._model)),this._legendView||(this._legendView=new H(this,this._model)),this._statusView||(this._statusView=new z.StudyStatusView(this)),this._floatingTooltipView||(this._floatingTooltipView=new gt.StudyChartFloatingTooltipView(this,this._model)),this._concatPriceAxisViews()}_onData(e){switch(e.method){case"study_loading":this._onStudyLoading(e.time);break;case"study_error":this._onStudyError(e.params[2]);break;case"study_completed":if(!this._checkTurnaround(e.params[1]))return;this._onStudyCompleted(e.time);break;case"data_update":if(e.params.customId!==this.sourceId()||!this._checkTurnaround(e.params.turnaround))return;(0,p.assert)(!!e.params.nonseries,"data.params.nonseries is missing"),this._onDataUpdate(e.params.plots,(0,p.ensureDefined)(e.params.nonseries),e.params.lastBar);break;case"clear_data":this._checkTurnaround(e.params.turnaround)&&this.clearData()}}_getTelemetryObjectName(){return"study"}_onDataUpdated(e,t,s,i){if(this.hasBarColorer()&&e.length>0){const t=(0,p.ensureNotNull)(this.barColorer()).firstColoredBar(e[0].index);null!==t&&this._model.mainSeries().invalidateBarStylesCache(t)}null!==t&&this._postProcessGraphics();const r=this._model.paneForSource(this);if(this._model.recalculatePane(r,(0,N.sourceChangeEvent)({sourceId:this.id(),firstUpdatedTimePointIndex:i??void 0,nonSeriesOnly:0===e.length})),this._updateSources(),e.length){const t=e[e.length-1].index,s=e[0].index;this._dataRangeUpdated.fire({type:"partial",startIndex:s,
+endIndex:t})}else this.data().isEmpty()&&this._dataRangeUpdated.fire({type:"full"})}_titleInputs(e,t,s){return this.inputs(this._titleInputsOptions(e,t,s))}_titleInputsOptions(e,t,s){return{symbolsForDisplay:!0,skipHiddenInputs:!0,skipFakeInputs:!1,fakeInputsForDisplay:!0,asObject:!0,skippedGroups:[],skippedInputs:this._skippedTitleInputs(),noExchanges:t,noResolution:s,priceInputsForDisplay:!0,skipOptionalEmptySymbolInputs:Qt,displayMask:e}}_postProcessGraphics(){this._graphicsPriceAxisViews=this._createGraphicsPriceAxisViews(),this._concatPriceAxisViews()}async _createGraphicsPaneViews(){return(0,R.createGraphicsPaneViews)(this,this.model())}_createGraphicsPriceAxisViews(){return(0,R.createGraphicsPriceAxisViews)(this)}_subscribeToSessionId(){!this._isSubscribedToSessionId&&this.hasSymbolInputs()&&(this.sessionIdChanged().subscribe(this,this._onSessionIdChanged),this._isSubscribedToSessionId=!0)}_recreateFormatter(e){let t=e;if(t){const e=this._model.symbolAliasService()?.getAliasByProName(t.pro_name);e&&(t=(0,r.default)(t),(0,n.default)(t,e.formattingOptions??{}))}this._recreatePlotsFormatters(t),this._formatter=this._tryCreateFormatter(t),this._defaultFormatter=this._tryCreateDefaultFormatter(t),this._formatterChanged.fire();const s=this.priceScale();null!==s&&s.updateFormatter(),this.getAllChildren().forEach((e=>{e.recreatePriceFormatter()})),this._model.fullUpdate()}_recreatePriceFormattingDependencies(e){this._recreateFormatter(e),this._recreatePriceStep()}_title(e,t,s,i,r,n){const o=this._titleInParts(e,t,s,i,r,n);return this._joinTitlesParts(o)}_postProcessPriceRange(e,t){if(e&&e.minValue()===e.maxValue()&&!this.metaInfo().is_price_study){const t=.005*e.minValue();e=new M.PriceRange(e.minValue()-t,e.maxValue()+t)}const s=t.targetPriceScale;return s&&s.isLog()&&e?new M.PriceRange(s.priceToLogical(e.minValue()),s.priceToLogical(e.maxValue())):e}_titleInParts(e,t=!0,i,r,n,o){const a=[m.t(this.name(t),{context:"study"},s(83477))];let l=[];if(!r||ee.enabled("always_show_study_symbol_input_values_in_legend")){const s=this._getMTFResolutionInputTitle();null!==s&&s.length>0&&a.push(s);l=(this.inputsInParts(e,t,i,n,o)??[]).map((e=>e.value))}return[a.join(" · "),l]}_seriesDataRangeToSave(e){return this._model.timeScale().visibleExtendedDataRange(e,0)}_getSymbolForResolve(e){return this.getSymbolString(this._getSymbolForApi(e))}_getSymbolForApi(e){return e}_getSymbolObject(e){const t={symbol:e},s=this.currency();return null!==this._currencySourceSymbolInputProperty&&null!==this._currencySourceSymbolInfo&&this._getSymbolForApi(this._currencySourceSymbolInputProperty.value())===e&&(t["currency-id"]=s),t.session=this.sessionId(),t}_onSymbolResolved(e,t,s){this._onCurrencyMayChange()}_onSymbolResolvingStart(e,t){}_onSymbolError(){}_setStatus(e,t){const s=this.isFailed();this._status.setValue(e),e.type===xt.StudyStatusType.Completed?this._wasCompletedBefore=!0:e.type!==xt.StudyStatusType.Error&&e.type!==xt.StudyStatusType.Undefined||(this._wasCompletedBefore=!1),t||(this._statusView?.update((0,
+N.sourceChangeEvent)(this.id())),this._model.updateSource(this),this._statusChanged.fire(this.status())),s!==this.isFailed()&&this._updateAlertCreationAvailable()}_onPropertiesChanged(){this._restarting||(this._inputs?this._tryChangeInputs():this._chartApi&&this._chartApi.isConnected().value()&&this.restart());this._metaInfo.value();this._recreatePaneViews(),(0,Nt.emit)("study_properties_changed",this._id.value())}_lastNonEmptyPlotRow(e){if(!(0,_.isInteger)(e))return Gt.logDebug("_lastNonEmptyPlotRow: incorrect plotIndex"),null;let t=this._lastNonEmptyPlotRowCache[e]??null;if(null!==t)return t;return t=this.data().findLast(((t,s)=>void 0!==s[e]),1e3),null===t?null:(this._lastNonEmptyPlotRowCache[e]=t,t)}_onCurrencyChanged(){"alwaysOff"!==(0,At.currencyUnitVisibilityProperty)().value()&&this._model.fullUpdate(),this.isStarted()&&this._tryChangeInputs(),this._currencyChanged.fire()}_apiInputs(){return this.inputs({keepOptionalSymbolsEmpty:!0})}async _tryChangeInputs(){const e=this.isStarted()&&this._chartApi.isConnected().value(),t=this._allInputsAreValid(),s=((0,p.ensureDefined)((0,_.clone)(this._inputs)),this._apiInputs()),i=JSON.stringify(s),r=i!==JSON.stringify(this._inputs);if(e&&t)try{if(await this._allSymbolsAreResolved(),i!==JSON.stringify(this._apiInputs()))return this._tryChangeInputs();if(this._isStopped())return void(r&&this.disablePriceRangeReady());r&&await this._changeInputsImpl(s,(0,p.ensureDefined)((0,_.clone)(this._inputs)))}catch(e){Gt.logError(`ERROR: ${this._debugId()} _tryChangeInputs: cannot modify study, ${e}`)}else if(e&&!t&&this.stop(!0),!e&&t&&this.start(!0),r){const e=this._calcSources(),t=os(this._metaInfo.value());this._updateParentSources(e,t,!0),this._inputs=s}this._tagsChanged.fire()}_onCurrencyMayChange(){if(null!==this._currencySourceSymbolInputProperty){const e=this.currency();this._updateCurrencySourceSymbolInfo(),e!==this.currency()&&this._onCurrencyChanged()}}_fillPrecalculatedAutoscaleInfo(e,t,s){const i=this._metaInfo.value(),r=this.properties().childs(),n=new Set,o=i.filledAreas||[];for(let e=0;e<o.length;e++){const t=o[e];r.filledAreasStyle.childs()[t.id].childs().visible.value()&&(n.add(t.objAId),n.add(t.objBId))}return i.plots.filter((e=>!(0,L.isPlotWithTechnicalValues)(e))).filter((e=>i.isPlotForceOverlay(e.id)?s.targetPriceScale===this._model.mainSeries().priceScale():s.targetPriceScale===this.priceScale()&&!s.forceOverlayOnly)).filter((e=>n.has(e.id)||this.isPlotVisibleAt(e.id,1))).reduce(((s,i)=>this._applyPlotToPrecalculatedAutoscaleInfo(e,t,s,i)),{fields:[],useMainSeriesRange:!1,baseValueMinMax:null})}_firstSourceOrSeries(){return this._sources.value()[0]??this._series}_skipHistogramBaseOnAutoScale(){return!1}_tryCreateFormatter(e){const t=void 0===e?this.symbolSource().symbolInfo():e;return hs(this._metaInfo.value().format,this._priceScaleByProperties(),t,this.properties().childs().precision.value())}_tryCreateDefaultFormatter(e){return this._tryCreateFormatter(e)}_mergeData(e){return this._invalidateLastNonEmptyPlotRowCache(),this.data().merge(e)}
+_skippedTitleInputs(){return this._hideMatches.filter((e=>e.plotIds.every((e=>0===this._getPlotDisplayValue(e))))).map((e=>e.id))}_getPlotDisplayValue(e){return this.properties()?.childs()?.styles?.childs()?.[e]?.childs()?.display?.value()}_onStudyError(e){performance.clearMarks(`calculate_study_${this.sourceId()}`),this._handleStudyError(this._createStudyError(e)),this._enablePriceRangeReady()}_onStudyCompleted(e){if(performance.getEntriesByName(`calculate_study_${this.sourceId()}`).length){try{const e=performance.measure(`measure_study_${this.sourceId()}`,`calculate_study_${this.sourceId()}`);this._calculationTime.setValue(e.duration)}catch(e){Gt.logError("Error during measuring study calculation time")}performance.clearMarks(`calculate_study_${this.sourceId()}`),performance.clearMeasures(`measure_study_${this.sourceId()}`)}this._studyModified&&(this.clearData(),this._studyModified=!1),this._setStatus({type:xt.StudyStatusType.Completed}),this._statusView?.update((0,N.sourceChangeEvent)(this.id()));const t=this._model.paneForSource(this);this._model.recalculatePane(t,(0,N.sourceChangeEvent)(this.id())),this._updateSources();const s=Vt.InvalidationMask.full();null!==this._model.appliedTimeFrame().value()&&s.lockVisibleTimeRangeOnResize(),this._model.invalidate(s)}_clearData(){this._data.clear(),this._dataRangeUpdated.fire({type:"full"})}_moveData(e){this.data().move(e)}_defaultErrorTitle(){return"Runtime error"}_incrementTurnaround(){this._turnaround="st"+ ++this._turnaroundCounter}_checkTurnaround(e){return e===this._turnaround||e===this._model.mainSeries().seriesSource().turnaround()||e===this.turnaround(!0)}_updateMaxOffsetValue(){let e=-1/0;for(const t of this._metaInfo.value().plots)e=Math.max(this.offset(t.id),e);this._maxOffset.setValue(e)}_rightOffsetToUnixTime(e){if(this._series.bars().size()>=e){const t=(0,p.ensureNotNull)(this._series.bars().lastIndex())-e;return(0,p.ensureNotNull)(this._series.bars().valueAt(t))[0]}return null}_concatPriceAxisViews(){this._priceAxisViews=[...this._priceAxisViewsBase,...this._graphicsPriceAxisViews]}_onStudyLoading(e){this._setStatus({type:xt.StudyStatusType.Loading,startTime:Date.now()}),this._statusView?.update((0,N.sourceChangeEvent)(this.id())),this._model.updateSource(this)}_handleStudyError(e){this.clearData(),this._setStatus(e),this._statusView?.update((0,N.sourceChangeEvent)(this.id())),this._model.updateSource(this)}_createStudyError(e){let t;return t=(0,_.isString)(e)?{error:this._getStudyErrorText(e),title:e.includes("study_not_auth")?"Access error":this._defaultErrorTitle()}:{...e,title:e.title??this._defaultErrorTitle()},(0,xt.createStudyError)(t,this.symbolSource().symbolInfo()?.exchange)}_updateSources(){this._model.updateSource(this),this.hasBarColorer()&&this._model.updateSource(this._model.mainSeries())}_unsubscribeToSessionId(){this._isSubscribedToSessionId&&(this.sessionIdChanged().unsubscribe(this,this._onSessionIdChanged),this._isSubscribedToSessionId=!1)}_onSessionIdChanged(){this.restart(!0)}_recreatePriceStep(){let e=null
+;const t=this._priceScaleByProperties()??this._priceScaleByMetaInfo();null!==t&&(e=1/t),this._priceStep!==e&&(this._priceStep=e,this._priceStepChanged.fire())}_recreatePlotsFormatters(e){this._plotFormatters.clear();const t=this._metaInfo.value(),s=t.format,i=this._priceScaleByProperties(),r=void 0===e?this.symbolSource().symbolInfo():e;for(const[e,n]of Object.entries(t.ohlcPlots??{}))if(n?.format){const t=hs(ls({...s,...n?.format}),i,r,this.properties().childs().precision.value());t&&this._plotFormatters.set(e,t)}for(const[e,n]of Object.entries(t.styles??{}))if(n?.format){const t=hs(ls({...s,...n?.format}),i,r,this.properties().childs().precision.value());t&&this._plotFormatters.set(e,t)}for(const e of t.plots)if((0,L.isOhlcPlot)(e)){const t=this._plotFormatters.get(e.target);t&&this._plotFormatters.set(e.id,t)}}_joinTitlesParts(e){const t=e[1]?e[1].join(", "):"";return e[0]+(t.length>0?" ("+t+")":"")}_getMTFResolutionInputTitle(){const e=this.metaInfo();for(let t=0;t<e.inputs.length;t++){const s=e.inputs[t];if("resolution"===s.type&&s.isMTFResolution)return(0,p.ensureDefined)(this._properties.childs().inputs.child(s.id)).value()}return null}_onDataUpdate(e,t,s){this._studyModified&&(this.clearData(),this._studyModified=!1);const i=(0,C.unpackNonSeriesData)(t.d);return this._ongoingDataUpdate=this._ongoingDataUpdate.then((()=>i),(()=>i)).then(this._onDataUnpacked.bind(this,e,t.indexes,s)),this._ongoingDataUpdate}_allSymbolsAreResolved(){const e=this._inputSymbols(),t=[];let s=!1;for(const i of e){const e=this._getSymbolForResolve(i);if(""!==e)if(this._resolvedSymbols[e])s=!0;else{const s=this._resolveSymbol(e,i);t.push(s)}}if(0===t.length){const e=Promise.resolve();return s?e.then((()=>this._symbolsResolved.fire())):e}return Promise.all(t).catch((e=>(this._inputSymbols().includes(e)&&this.stop(!0),this._setStatus({type:xt.StudyStatusType.Error,errorDescription:{error:$t}}),this._model.updateSource(this),Promise.reject("Invalid symbol, "+e)))).then((()=>{this._symbolsResolved.fire(),this._recheckLineToolsActuality()}))}_resolveSymbol(e,t){if(""===e)return Promise.resolve();let s=this._pendingResolveSymbols.get(e);return void 0!==s||(s=new Promise(((s,i)=>{this._onSymbolResolvingStart(e,t),this._chartApi.resolveSymbol((0,j.makeNextSymbolId)(),e,(r=>{switch(this._pendingResolveSymbols.delete(e),r.method){case"symbol_resolved":{this._setStatus({type:xt.StudyStatusType.Undefined});const i=r.params[1];this._resolvedSymbols[e]=i,this._resolvedSymbolsByInput[t]=i,this.invalidateTitleCache(!0),this._onSymbolResolved(e,t,i),s();break}case"symbol_error":if(this._setStatus({type:xt.StudyStatusType.Error,errorDescription:{error:r.params[1]}}),this._onSymbolError(),r.params[1]===G.permissionDenied&&r.params[2]){if(r.params[2]!==G.SymbolErrorPermissionDeniedReason.Symbol)return void this._resolveSymbol(r.params[2],t).then(s);if(r.params[3])return void this._resolveSymbol(r.params[3],t).then(s)}0,i(t)}}))})),this._pendingResolveSymbols.set(e,s)),s}_recheckLineToolsActuality(){const e=this._model.paneForSource(this)
+;null!==e&&e.sourcesByGroup().lineSourcesForAllSymbols().forEach((e=>{e.ownerSource()===this&&e.calcIsActualSymbol()}))}_sendTelemetryCounter(e,t){void 0===t&&(t=this._getTelemetryAdditionalData());const s={count:1,additional:t};telemetry.sendChartReport(e,s)}_getTelemetryAdditionalData(){let e="";const t=this._metaInfo.value();return t.pine&&t.pine.version&&t.shortId.indexOf("USER")>=0&&(e="_v"+t.pine.version),{symbol:this.series().actualSymbol(),resolution:this.series().interval(),study:t.shortId+e}}_onSourceFormatterChanged(){null===this._formatter&&(null!==this._priceScale&&this._priceScale.updateFormatter(),this._formatterChanged.fire())}_onSourcePriceStepChanged(){null===this._priceStep&&this._priceStepChanged.fire()}_bandsFirstValue(e){const t=this._metaInfo.value();if(!t.bands)return null;for(let s=0;s<t.bands.length;s++){const t=(0,p.ensureDefined)(this._properties.childs().bands).childs()[s];if(t.childs().visible.value()){const s=t.childs().value.value();if(e&&0===s)continue;if(null!==s)return s}}return null}_prepareInputs(e){(0,p.assert)(!!e,"options not set");const t=this.metaInfo(),s={},i=e.allowedInputTypes?new Set(e.allowedInputTypes):null,r=!(!e.asObject||!e.useNameAndGroupAsKey);for(let n=0;n<t.inputs.length;n++){const o=t.inputs[n];if(null!==i&&!i.has(o.type))continue;if(o.isFake&&e.skipFakeInputs)continue;if(o.isMTFResolution&&e.noResolution)continue;if(void 0!==e.displayMask&&!((0,p.ensureDefined)(o.display)&e.displayMask))continue;if(e.skipHiddenInputs&&(!e.doNotSkipHiddenWithMigrate||!o.migrate)){let t=!1;switch(o.type){case"bool":t=e.skipBooleanInputs;break;case"color":t=e.skipColorInputs;break;case"time":t=e.skipTimeInputs;break;case"text_area":t=e.skipTextareaInputs;break;default:t=Boolean(o.isHidden)}if(t)continue}if(void 0!==o.groupId&&-1!==e.skippedGroups.indexOf(o.groupId))continue;if(-1!==e.skippedInputs.indexOf(o.id))continue;const a=this._prepareInput(o,e);if("symbol"===o.type&&e.skipOptionalEmptySymbolInputs&&""===a)continue;let l;r&&(l=v(o),void 0!==l&&l in s&&(l=void 0)),s[l||o.id]=(0,_.clone)(a)}return s}_prepareInputValue(e,t){const s=e.id,i=this._properties.childs();if(t.valuesAsIsFromProperties)return i.inputs.childs()[s].value();const r=this._metaInfo.value();if("symbol"===e.type){const r=t&&t.symbolsForDisplay,n=i.inputs.childs()[s].value();let o=r?n:this._getSymbolForApi(n),a=this._resolvedSymbols?.[this._getSymbolForResolve(o)]??null;if(""===o&&e.optional){if(t&&t.keepOptionalSymbolsEmpty)return o;o=this._model.mainSeries().symbol(),a=this._model.mainSeries().symbolInfo()}if(r)if(a)if(Zt){switch(this._model.mainSeries().symbolTextSourceProxyProperty().value()){case"description":o=a.description;break;case"ticker-and-description":o=`${a.name}, ${a.description}`;break;case"ticker":o=a.name}}else o=(0,Tt.symbolTitle)(a,t.noExchanges);else ts&&(o="");else a&&(o=a.ticker||a.full_name),!this.isPine()&&t&&t.symbolsForChartApi&&(o=this.getSymbolString(o));return o}if("bar_time"===e.type){let e=i.inputs.childs()[s].value();if(e<0){const t=this._rightOffsetToUnixTime(-e);e=t&&t>=0?t:e}
+return e}if(r.isTVScript||r.pine){if("text"===s)return r.defaults.inputs?.text??"";if("pineId"===s)return r.scriptIdPart;if("pineVersion"===s)return r.pine?r.pine.version:"-1";if("color"===e.type&&r.isRGB){const e=i.inputs.childs()[s].value();return(0,I.colorToInteger)(e)}if("price"===e.type){const e=i.inputs.childs()[s].value();return t.priceInputsForDisplay?this.formatter().format(e):e}}return i.inputs.childs()[s].value()}_getStudyIdWithLatestVersion(){return A.StudyMetaInfo.getStudyIdWithLatestVersion(this.metaInfo())}_debugId(){const e=[];e.push(this._id.value());const t=this._metaInfo.value();return e.push(t.fullId),e.push(t.description),JSON.stringify({study:e})}_hasAvailableAlertPlots(){return!1}_hasAlertConditions(){return!1}_hasAlertFunction(){return!1}async _updateParentSources(e,t,s){if(this._sources.value().forEach((e=>e.unsetChild(this))),s&&await Promise.all(e.map((e=>e.isStarted()?Promise.resolve():e.start(!1,!0)))),e.forEach((e=>e.setChild(this))),this._setSources(e),this._recreatePriceFormattingDependencies(),0!==t&&this._sources.value().length<=1){const e=this._firstSourceOrSeries(),t=this._priceScale,s=(0,p.ensureNotNull)(e.priceScale());if(t!==s){const t=this._model.paneForSource(this),i=(0,p.ensureNotNull)(this._model.paneForSource(e));t===i&&i.move(this,s,!0)}}}_calcSources(){const e=this._properties.childs().inputs.state();return A.StudyMetaInfo.getSourceIdsByInputs(this._metaInfo.value().inputs,e).map((e=>{if("high"===e||"open"===e||"low"===e||"close"===e||"hl2"===e||"ohl3"===e||"ohlc4"===e)return null;return this._model.allStudies().find((t=>t.canHaveChildren()&&t.id()===e))??null})).filter(_.notNull)}_isStopped(){return!this.isStarted()}_onDataUnpacked(e,t,s,i){if(this._isDestroyed)return;"nochange"!==t&&this._processPlotOffsets(i),this._transformData(e);const r=this._mergeData(e);null!==i&&(i.indexes_replace?((0,p.assert)("nochange"!==t),this._graphics.replaceIndexesTo(t)):("nochange"!==t&&this._graphics.replaceIndexesTo(t),void 0!==i.graphicsCmds&&this._graphics.processCommands(i.graphicsCmds))),this._onDataUpdated(e,i,t,r&&r.index),this.priceRangeReady()||this._enablePriceRangeReady()}_processPlotOffsets(e){if(e&&e.indexes_replace)return;const t=this._serverPlotOffsets.value();this._serverPlotOffsets.setValue(e&&e.offsets||{}),(0,i.default)(t,this._serverPlotOffsets.value())||this.updateAllViews((0,N.sourceChangeEvent)({sourceId:this.id(),clearData:!0})),this._updateMaxOffsetValue()}_applyPlotToPrecalculatedAutoscaleInfo(e,t,s,i){const r=i.id,n=this._properties.childs().styles.childs()[r],o=(0,L.isShapesPlot)(i)||(0,L.isCharsPlot)(i);s.useMainSeriesRange=s.useMainSeriesRange||(0,L.isArrowsPlot)(i);let a=(0,L.isLinePlot)(i)||(0,L.isOhlcPlot)(i);if(o){const e=(0,p.ensureDefined)(n).childs().location.value(),t=[D.MarkLocation.Absolute,D.MarkLocation.Top,D.MarkLocation.Bottom].indexOf(e)<0;s.useMainSeriesRange=s.useMainSeriesRange||o&&t,a=a||e===D.MarkLocation.Absolute}if(!a)return s;const l={name:r,offset:this.offset(r)},h=n.childs().plottype.value()
+;if(!this._skipHistogramBaseOnAutoScale()&&[L.LineStudyPlotStyle.Histogram,L.LineStudyPlotStyle.Columns,L.LineStudyPlotStyle.Area].indexOf(h)>=0){const i=(this._metaInfo.value().styles??{})?.[r]?.histogramBase;if(void 0===i)return s;const n=this.data().minMaxOnRangeCached(e,t,[l]);return(0,_.isNumber)(i)&&null!==n&&(s.baseValueMinMax=(0,T.mergeMinMax)(s.baseValueMinMax,{min:i,max:i}),s.baseValueMinMax=(0,T.mergeMinMax)(s.baseValueMinMax,n)),s}return s.fields.push(l),s}async _onSourceInputChanged(){if(!this.isStarted()){this._calcSources();Kt}}_buildInputs(e){(0,p.assert)(!!e,"options not set");let t={};try{t=this._prepareInputs(e)}catch(e){Gt.logWarn("Failed to prepare study inputs: "+e)}if(e.asObject){const e={};return Object.keys(t).forEach((s=>{null!=t[s]&&(e[s]=t[s])})),e}{const e=[];return Object.keys(t).forEach((s=>{null!=t[s]&&e.push(t[s])})),e}}_prepareInput(e,t){const s=this._prepareInputValue(e,t);return!e.isFake||t.fakeInputsForDisplay||t.onlyAtomValues?s:{v:s,f:!0,t:e.type}}_plotsForAlert(){return[]}_formatterStateForAlert(){try{const e=this.formatter();return FormattersSerializer.isSerializable(e)?FormattersSerializer.serialize(e):null}catch{return null}}_calcIsActualInterval(){const e=this._isActualInterval;this._isActualInterval=(0,Ct.isActualInterval)(this._series.intervalObj().value(),this._properties.childs().intervalsVisibilities),e!==this._isActualInterval&&(this._onIsActualIntervalChange.fire(),this._visibleChanged(),this.processHibernate())}_visibleChanged(){this._series.invalidateBarColorerCache()}_getNonPriceParent(){const e=this._sources.value();for(const t of e)if(t instanceof us){const e=t.metaInfo();return e.is_price_study&&"Compare@tv-basicstudies"!==e.id?t._getNonPriceParent():t}return null}_updateInputValue(e,t){const s=this._properties.childs().inputs.childs();if(s[t.id])if("price"===t.type)s[t.id].setValue(e.price);else if("time"===t.type){const i=this._model.timeScale().indexToTimePoint(e.index);null!==i&&s[t.id].setValue(1e3*i)}}_initializeStudyInputsPaneViews(){}_updateCurrencySourceSymbolInfo(){null!==this._currencySourceSymbolInputProperty&&(this._currencySourceSymbolInfo=this._resolvedSymbolsByInput[this._currencySourceSymbolInputProperty.value()]??null)}_initializeCurrencySource(){const e=this.metaInfo(),t="symbolInputSymbolSource"===e.symbolSource?.type&&e.symbolSource?.inputId,s=e.inputs.find((e=>e.id===t));if("string"==typeof t&&"symbol"===s?.type&&e.is_price_study){const e=this._properties.childs().inputs.childs()[t];void 0!==e&&(e.subscribe(this,this._onCurrencyMayChange),this._currencySourceSymbolInputProperty=e)}}_recreatePaneViews(){this.hasBarColorer()&&this._model.mainSeries().invalidateBarStylesCache(),this._createViews(),this.recalculate(),this.updateAllViews((0,N.sourceChangeEvent)(this.id()))}async _pinePatchProps(){throw new Error("Not implemented")}_areStudyInputsModified(e){if(0===Object.keys(e).length)return!1;if(void 0===this._oldStudyInputs)return!0;const t=Object.keys(this._oldStudyInputs);(0,
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web/public/charting_library/bundles/1553.ee2f0024a59277fd480e.js

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+;return 30&i?e=t.overallVelocity:6&i?e=t.overallVelocityX:i&W&&(e=t.overallVelocityY),this._super.attrTest.call(this,t)&&i&t.offsetDirection&&t.distance>this.options.threshold&&t.maxPointers==this.options.pointers&&p(e)>this.options.velocity&&4&t.eventType},emit:function(t){var e=xt(t.offsetDirection);e&&this.manager.emit(this.options.event+e,t),this.manager.emit(this.options.event,t)}}),E(Ft,Dt,{defaults:{event:"tap",pointers:1,taps:1,interval:300,time:250,threshold:9,posThreshold:10},getTouchAction:function(){return[It]},process:function(t){var e=this.options,i=t.pointers.length===e.pointers,n=t.distance<e.threshold,r=t.deltaTime<e.time;if(this.reset(),1&t.eventType&&0===this.count)return this.failTimeout();if(n&&r&&i){if(4!=t.eventType)return this.failTimeout();var s=!this.pTime||t.timeStamp-this.pTime<e.interval,o=!this.pCenter||B(this.pCenter,t.center)<e.posThreshold;if(this.pTime=t.timeStamp,this.pCenter=t.center,o&&s?this.count+=1:this.count=1,this._input=t,0===this.count%e.taps)return this.hasRequireFailures()?(this._timer=v((function(){this.state=8,this.tryEmit()}),e.interval,this),2):8}return Pt},failTimeout:function(){return this._timer=v((function(){this.state=Pt}),this.options.interval,this),Pt},reset:function(){clearTimeout(this._timer)},emit:function(){8==this.state&&(this._input.tapCount=this.count,this.manager.emit(this.options.event,this._input))}}),kt.VERSION="2.0.7",kt.defaults={domEvents:!1,touchAction:yt,enable:!0,inputTarget:null,inputClass:null,preset:[[Xt,{enable:!1}],[zt,{enable:!1},["rotate"]],[Yt,{direction:6}],[Mt,{direction:6},["swipe"]],[Ft],[Ft,{event:"doubletap",taps:2},["tap"]],[Nt]],cssProps:{userSelect:"none",touchSelect:"none",touchCallout:"none",contentZooming:"none",userDrag:"none",tapHighlightColor:"rgba(0,0,0,0)"}};function Wt(t,e){var i;this.options=h({},kt.defaults,e||{}),this.options.inputTarget=this.options.inputTarget||t,this.handlers={},this.session={},this.recognizers=[],this.oldCssProps={},this.element=t,this.input=new((i=this).options.inputClass||(X?st:Y?lt:N?ft:tt))(i,U),this.touchAction=new St(this,this.options.touchAction),qt(this,!0),m(this.options.recognizers,(function(t){var e=this.add(new t[0](t[1]));t[2]&&e.recognizeWith(t[2]),t[3]&&e.requireFailure(t[3])}),this)}function qt(t,e){var i,n=t.element;n.style&&(m(t.options.cssProps,(function(r,s){i=R(n.style,s),e?(t.oldCssProps[i]=n.style[i],n.style[i]=r):n.style[i]=t.oldCssProps[i]||""})),e||(t.oldCssProps={}))}Wt.prototype={set:function(t){return h(this.options,t),t.touchAction&&this.touchAction.update(),t.inputTarget&&(this.input.destroy(),this.input.target=t.inputTarget,this.input.init()),this},stop:function(t){this.session.stopped=t?2:1},recognize:function(t){var e=this.session;if(!e.stopped){var i;this.touchAction.preventDefaults(t);var n=this.recognizers,r=e.curRecognizer;(!r||r&&8&r.state)&&(r=e.curRecognizer=null);for(var s=0;s<n.length;)i=n[s],2===e.stopped||r&&i!=r&&!i.canRecognizeWith(r)?i.reset():i.recognize(t),!r&&14&i.state&&(r=e.curRecognizer=i),s++}},get:function(t){if(t instanceof Dt)return t
+;for(var e=this.recognizers,i=0;i<e.length;i++)if(e[i].options.event==t)return e[i];return null},add:function(t){if(d(t,"add",this))return this;var e=this.get(t.options.event);return e&&this.remove(e),this.recognizers.push(t),t.manager=this,this.touchAction.update(),t},remove:function(t){if(d(t,"remove",this))return this;if(t=this.get(t)){var e=this.recognizers,i=w(e,t);-1!==i&&(e.splice(i,1),this.touchAction.update())}return this},on:function(t,e){if(t!==a&&e!==a){var i=this.handlers;return m(D(t),(function(t){i[t]=i[t]||[],i[t].push(e)})),this}},off:function(t,e){if(t!==a){var i=this.handlers;return m(D(t),(function(t){e?i[t]&&i[t].splice(w(i[t],e),1):delete i[t]})),this}},emit:function(t,e){this.options.domEvents&&function(t,e){var i=s.createEvent("Event");i.initEvent(t,!0,!0),i.gesture=e,e.target.dispatchEvent(i)}(t,e);var i=this.handlers[t]&&this.handlers[t].slice();if(i&&i.length){e.type=t,e.preventDefault=function(){e.srcEvent.preventDefault()};for(var n=0;n<i.length;)i[n](e),n++}},destroy:function(){this.element&&qt(this,!1),this.handlers={},this.session={},this.input.destroy(),this.element=null}},h(kt,{INPUT_START:1,INPUT_MOVE:2,INPUT_END:4,INPUT_CANCEL:8,STATE_POSSIBLE:1,STATE_BEGAN:2,STATE_CHANGED:4,STATE_ENDED:8,STATE_RECOGNIZED:8,STATE_CANCELLED:16,STATE_FAILED:Pt,DIRECTION_NONE:1,DIRECTION_LEFT:2,DIRECTION_RIGHT:4,DIRECTION_UP:8,DIRECTION_DOWN:16,DIRECTION_HORIZONTAL:6,DIRECTION_VERTICAL:W,DIRECTION_ALL:30,Manager:Wt,Input:H,TouchAction:St,TouchInput:lt,MouseInput:tt,PointerEventInput:st,TouchMouseInput:ft,SingleTouchInput:at,Recognizer:Dt,AttrRecognizer:Rt,Tap:Ft,Pan:Mt,Swipe:Yt,Pinch:zt,Rotate:Xt,Press:Nt,on:b,off:_,each:m,merge:y,extend:T,assign:h,inherit:E,bindFn:I,prefixed:R}),(void 0!==r?r:"undefined"!=typeof self?self:{}).Hammer=kt,(n=function(){return kt}.call(e,i,e,t))===a||(t.exports=n)}(window,document)}}]);

web/public/charting_library/bundles/159.3e4f89ce6749c1e5f8df.css

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web/public/charting_library/bundles/159.3e4f89ce6749c1e5f8df.rtl.css

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web/public/charting_library/bundles/1681.df517de208b59f042c3b.css

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web/public/charting_library/bundles/1681.df517de208b59f042c3b.rtl.css

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web/public/charting_library/bundles/1697.042d72d2c0eaafd88d54.css

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web/public/charting_library/bundles/1697.042d72d2c0eaafd88d54.rtl.css

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web/public/charting_library/bundles/1727.98e9d718a90f5c1c2f73.js

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web/public/charting_library/bundles/1979.727d53fabf38782d4a1f.css

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web/public/charting_library/bundles/1979.727d53fabf38782d4a1f.rtl.css

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web/public/charting_library/bundles/2112.10fd79bdcf7d87919e93.css

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web/public/charting_library/bundles/2112.10fd79bdcf7d87919e93.rtl.css

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web/public/charting_library/bundles/2164.fcf5a0c7415d9ec1cd7c.js

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web/public/charting_library/bundles/2202.414409a383bce0796e9b.css

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web/public/charting_library/bundles/2202.414409a383bce0796e9b.rtl.css

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web/public/charting_library/bundles/2227.c1c4b4d4d12f9774793f.js

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web/public/charting_library/bundles/2318.8bdd9c9cc1661e5b303f.css

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web/public/charting_library/bundles/2318.8bdd9c9cc1661e5b303f.rtl.css

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web/public/charting_library/bundles/2477.44f2c96353966357ded8.js

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web/public/charting_library/bundles/2641.8fe6a787670a4a8ef383.css

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web/public/charting_library/bundles/2641.8fe6a787670a4a8ef383.rtl.css

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web/public/charting_library/bundles/2647.a9ca47adf1a97f5f023d.css

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web/public/charting_library/bundles/2647.a9ca47adf1a97f5f023d.rtl.css

@@ -0,0 +1 @@
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web/public/charting_library/bundles/2745.73995b6670d622d97310.js

@@ -0,0 +1,5 @@
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+i.t(null,void 0,n(24821))),U=i.t(null,void 0,n(65188)),I=i.t(null,void 0,n(42562)),M=i.t(null,void 0,n(56796)),L=i.t(null,void 0,n(72942)),F=i.t(null,void 0,n(835)),A=i.t(null,void 0,n(43154)),R=new o.TranslatedString("ticks",i.t(null,void 0,n(3539))),N=new o.TranslatedString("seconds",i.t(null,void 0,n(751))),E=new o.TranslatedString("seconds from",i.t(null,void 0,n(35801))),X=new o.TranslatedString("seconds to",i.t(null,void 0,n(73419))),Y=new o.TranslatedString("minutes",i.t(null,void 0,n(18726))),H=new o.TranslatedString("minutes from",i.t(null,void 0,n(22476))),j=new o.TranslatedString("minutes to",i.t(null,void 0,n(67649))),$=new o.TranslatedString("hours",i.t(null,void 0,n(2359))),O=new o.TranslatedString("hours from",i.t(null,void 0,n(82267))),z=new o.TranslatedString("hours to",i.t(null,void 0,n(15600))),q=new o.TranslatedString("days",i.t(null,void 0,n(35813))),B=new o.TranslatedString("days from",i.t(null,void 0,n(59215))),G=new o.TranslatedString("days to",i.t(null,void 0,n(89919))),J=new o.TranslatedString("weeks",i.t(null,void 0,n(45537))),K=new o.TranslatedString("weeks from",i.t(null,void 0,n(92859))),Q=new o.TranslatedString("weeks to",i.t(null,void 0,n(44127))),Z=new o.TranslatedString("months",i.t(null,void 0,n(95300))),ee=new o.TranslatedString("months from",i.t(null,void 0,n(17250))),te=new o.TranslatedString("months to",i.t(null,void 0,n(2828))),ne=(new o.TranslatedString("ranges","ranges"),[1,59]),ie=[1,59],oe=[1,24],re=[1,366],le=[1,52],se=[1,12];function ae(e,t,n){const i=[];if((0,a.isTicksEnabled)()){const o=(0,r.createCheckablePropertyDefinition)({checked:(0,r.convertToDefinitionProperty)(e,t.ticks,p.format({title:n}))},{id:"IntervalsVisibilitiesTicks",title:x});i.push(o)}if((0,s.isSecondsEnabled)()){const o=(0,r.createRangePropertyDefinition)({checked:(0,r.convertToDefinitionProperty)(e,t.seconds,u.format({title:n})),from:(0,r.convertToDefinitionProperty)(e,t.secondsFrom,h.format({title:n})),to:(0,r.convertToDefinitionProperty)(e,t.secondsTo,y.format({title:n}))},{id:"IntervalsVisibilitiesSecond",title:U,min:new l.WatchedValue(ne[0]),max:new l.WatchedValue(ne[1])});i.push(o)}const o=(0,r.createRangePropertyDefinition)({checked:(0,r.convertToDefinitionProperty)(e,t.minutes,m.format({title:n})),from:(0,r.convertToDefinitionProperty)(e,t.minutesFrom,w.format({title:n})),to:(0,r.convertToDefinitionProperty)(e,t.minutesTo,f.format({title:n}))},{id:"IntervalsVisibilitiesMinutes",title:I,min:new l.WatchedValue(ie[0]),max:new l.WatchedValue(ie[1])}),d=(0,r.createRangePropertyDefinition)({checked:(0,r.convertToDefinitionProperty)(e,t.hours,v.format({title:n})),from:(0,r.convertToDefinitionProperty)(e,t.hoursFrom,P.format({title:n})),to:(0,r.convertToDefinitionProperty)(e,t.hoursTo,g.format({title:n}))},{id:"IntervalsVisibilitiesHours",title:M,min:new l.WatchedValue(oe[0]),max:new l.WatchedValue(oe[1])}),c=(0,r.createRangePropertyDefinition)({checked:(0,r.convertToDefinitionProperty)(e,t.days,T.format({title:n})),from:(0,r.convertToDefinitionProperty)(e,t.daysFrom,b.format({title:n})),to:(0,
+r.convertToDefinitionProperty)(e,t.daysTo,S.format({title:n}))},{id:"IntervalsVisibilitiesDays",title:L,min:new l.WatchedValue(re[0]),max:new l.WatchedValue(re[1])});i.push(o,d,c);const R=(0,r.createRangePropertyDefinition)({checked:(0,r.convertToDefinitionProperty)(e,t.weeks,C.format({title:n})),from:(0,r.convertToDefinitionProperty)(e,t.weeksFrom,k.format({title:n})),to:(0,r.convertToDefinitionProperty)(e,t.weeksTo,V.format({title:n}))},{id:"IntervalsVisibilitiesWeeks",title:F,min:new l.WatchedValue(le[0]),max:new l.WatchedValue(le[1])}),N=(0,r.createRangePropertyDefinition)({checked:(0,r.convertToDefinitionProperty)(e,t.months,W.format({title:n})),from:(0,r.convertToDefinitionProperty)(e,t.monthsFrom,D.format({title:n})),to:(0,r.convertToDefinitionProperty)(e,t.monthsTo,_.format({title:n}))},{id:"IntervalsVisibilitiesMonths",title:A,min:new l.WatchedValue(se[0]),max:new l.WatchedValue(se[1])});return i.push(R,N),{definitions:i}}function de(e,t){const n=[];if((0,a.isTicksEnabled)()){const i=(0,r.createCheckablePropertyDefinition)({checked:new c.CollectiblePropertyUndoWrapper(new d.LineToolCollectedProperty(e.ticks),R,t)},{id:"IntervalsVisibilitiesTicks",title:x});n.push(i)}if((0,s.isSecondsEnabled)()){const i=(0,r.createRangePropertyDefinition)({checked:new c.CollectiblePropertyUndoWrapper(new d.LineToolCollectedProperty(e.seconds),N,t),from:new c.CollectiblePropertyUndoWrapper(new d.LineToolCollectedProperty(e.secondsFrom),E,t),to:new c.CollectiblePropertyUndoWrapper(new d.LineToolCollectedProperty(e.secondsTo),X,t)},{id:"IntervalsVisibilitiesSecond",title:U,min:new l.WatchedValue(ne[0]),max:new l.WatchedValue(ne[1])});n.push(i)}const i=(0,r.createRangePropertyDefinition)({checked:new c.CollectiblePropertyUndoWrapper(new d.LineToolCollectedProperty(e.minutes),Y,t),from:new c.CollectiblePropertyUndoWrapper(new d.LineToolCollectedProperty(e.minutesFrom),H,t),to:new c.CollectiblePropertyUndoWrapper(new d.LineToolCollectedProperty(e.minutesTo),j,t)},{id:"IntervalsVisibilitiesMinutes",title:I,min:new l.WatchedValue(ie[0]),max:new l.WatchedValue(ie[1])}),o=(0,r.createRangePropertyDefinition)({checked:new c.CollectiblePropertyUndoWrapper(new d.LineToolCollectedProperty(e.hours),$,t),from:new c.CollectiblePropertyUndoWrapper(new d.LineToolCollectedProperty(e.hoursFrom),O,t),to:new c.CollectiblePropertyUndoWrapper(new d.LineToolCollectedProperty(e.hoursTo),z,t)},{id:"IntervalsVisibilitiesHours",title:M,min:new l.WatchedValue(oe[0]),max:new l.WatchedValue(oe[1])}),p=(0,r.createRangePropertyDefinition)({checked:new c.CollectiblePropertyUndoWrapper(new d.LineToolCollectedProperty(e.days),q,t),from:new c.CollectiblePropertyUndoWrapper(new d.LineToolCollectedProperty(e.daysFrom),B,t),to:new c.CollectiblePropertyUndoWrapper(new d.LineToolCollectedProperty(e.daysTo),G,t)},{id:"IntervalsVisibilitiesDays",title:L,min:new l.WatchedValue(re[0]),max:new l.WatchedValue(re[1])});n.push(i,o,p);const u=(0,r.createRangePropertyDefinition)({checked:new c.CollectiblePropertyUndoWrapper(new d.LineToolCollectedProperty(e.weeks),J,t),
+from:new c.CollectiblePropertyUndoWrapper(new d.LineToolCollectedProperty(e.weeksFrom),K,t),to:new c.CollectiblePropertyUndoWrapper(new d.LineToolCollectedProperty(e.weeksTo),Q,t)},{id:"IntervalsVisibilitiesWeeks",title:F,min:new l.WatchedValue(le[0]),max:new l.WatchedValue(le[1])}),h=(0,r.createRangePropertyDefinition)({checked:new c.CollectiblePropertyUndoWrapper(new d.LineToolCollectedProperty(e.months),Z,t),from:new c.CollectiblePropertyUndoWrapper(new d.LineToolCollectedProperty(e.monthsFrom),ee,t),to:new c.CollectiblePropertyUndoWrapper(new d.LineToolCollectedProperty(e.monthsTo),te,t)},{id:"IntervalsVisibilitiesMonths",title:A,min:new l.WatchedValue(se[0]),max:new l.WatchedValue(se[1])});return n.push(u,h),{definitions:n}}},66567:(e,t,n)=>{n.d(t,{CollectiblePropertyUndoWrapper:()=>a});var i=n(50151),o=n(11542),r=n(95804),l=n(43337);const s=new r.TranslatedString("change {propertyName} property",o.t(null,void 0,n(25167)));class a extends l.Property{constructor(e,t,n){super(),this._isProcess=!1,this._listenersMappers=[],this._valueApplier={applyValue:(e,t)=>{this._propertyApplier.setProperty(e,t,s)}},this._baseProperty=e,this._propertyApplier=n,this._propertyName=t}destroy(){this._baseProperty.destroy(),super.destroy()}value(){return this._baseProperty.value()}setValue(e,t){this._propertyApplier.beginUndoMacro(s.format({propertyName:this._propertyName})),this._isProcess=!0,this._baseProperty.setValue(e,void 0,this._valueApplier),this._isProcess=!1,this._propertyApplier.endUndoMacro(),this._listenersMappers.forEach((e=>{e.method.call(e.obj,this,"")}))}subscribe(e,t){const n=()=>{this._isProcess||t.call(e,this,"")};this._listenersMappers.push({obj:e,method:t,callback:n}),this._baseProperty.subscribe(e,n)}unsubscribe(e,t){const n=(0,i.ensureDefined)(this._listenersMappers.find((n=>n.obj===e&&n.method===t))?.callback);this._baseProperty.unsubscribe(e,n)}unsubscribeAll(e){this._baseProperty.unsubscribeAll(e)}}},81634:(e,t,n)=>{n.d(t,{PropertyApplierWithoutSavingChart:()=>o});var i=n(13896);class o{constructor(e){this._undoModelSupplier=e}setProperty(e,t,n){this._undoModelSupplier().setProperty(e,t,n,i.lineToolsDoNotAffectChartInvalidation)}beginUndoMacro(e){return this._undoModelSupplier().beginUndoMacro(e)}endUndoMacro(){this._undoModelSupplier().endUndoMacro()}setWatchedValue(e,t,n){this._undoModelSupplier().undoHistory().setWatchedValue(e,t,n,i.lineToolsDoNotAffectChartInvalidation)}}}}]);

web/public/charting_library/bundles/2891.ac7f12fc1eff206762f9.js

@@ -0,0 +1,5 @@
+"use strict";(self.webpackChunktradingview=self.webpackChunktradingview||[]).push([[2891],{91445:(e,t,o)=>{o.d(t,{createTextStyleDefinition:()=>w});var i=o(11542),r=o(95804),n=o(95338),s=o(91682);const a=new r.TranslatedString("change {toolName} text visibility",i.t(null,void 0,o(56634))),l=new r.TranslatedString("change {toolName} text color",i.t(null,void 0,o(64500))),d=new r.TranslatedString("change {toolName} text font size",i.t(null,void 0,o(21781))),c=new r.TranslatedString("change {toolName} text font bold",i.t(null,void 0,o(24701))),u=new r.TranslatedString("change {toolName} text font italic",i.t(null,void 0,o(42694))),p=new r.TranslatedString("change {toolName} text",i.t(null,void 0,o(66668))),h=new r.TranslatedString("change {toolName} labels alignment vertical",i.t(null,void 0,o(31689))),g=new r.TranslatedString("change {toolName} labels alignment horizontal",i.t(null,void 0,o(88277))),_=new r.TranslatedString("change {toolName} labels direction",i.t(null,void 0,o(61160))),y=new r.TranslatedString("change {toolName} text background visibility",i.t(null,void 0,o(31133))),b=new r.TranslatedString("change {toolName} text background color",i.t(null,void 0,o(22231))),m=new r.TranslatedString("change {toolName} text border visibility",i.t(null,void 0,o(58704))),f=new r.TranslatedString("change {toolName} text border width",i.t(null,void 0,o(35423))),P=new r.TranslatedString("change {toolName} text border color",i.t(null,void 0,o(36666))),v=new r.TranslatedString("change {toolName} text wrap",i.t(null,void 0,o(39587))),T=i.t(null,void 0,o(79468)),C=i.t(null,void 0,o(38408)),x=i.t(null,void 0,o(7560)),S=i.t(null,void 0,o(6060));function w(e,t,o,i){const r={},w={id:`${(0,s.removeSpaces)(o.originalText())}Text`,title:i.customTitles&&i.customTitles.text||"",placeholder:i.placeholder??S};if(void 0===t.showText||i.hideTextCheckbox||(r.checked=(0,n.convertToDefinitionProperty)(e,t.showText,a.format({toolName:o}))),void 0!==t.textColor&&(r.color=(0,n.getColorDefinitionProperty)(e,t.textColor,t.transparency||null,l.format({toolName:o}))),void 0!==t.fontSize&&(r.size=(0,n.convertToDefinitionProperty)(e,t.fontSize,d.format({toolName:o}))),void 0!==t.bold&&(r.bold=(0,n.convertToDefinitionProperty)(e,t.bold,c.format({toolName:o}))),void 0!==t.italic&&(r.italic=(0,n.convertToDefinitionProperty)(e,t.italic,u.format({toolName:o}))),void 0!==t.text){const s=p.format({toolName:o});r.text=(0,n.convertToDefinitionProperty)(e,t.text,s,void 0),w.isEditable=Boolean(i.isEditable),w.isMultiLine=Boolean(i.isMultiLine)}if(void 0!==t.vertLabelsAlign&&(r.alignmentVertical=(0,n.convertToDefinitionProperty)(e,t.vertLabelsAlign,h.format({toolName:o})),w.alignmentVerticalItems=i.alignmentVerticalItems),void 0!==t.horzLabelsAlign&&(r.alignmentHorizontal=(0,n.convertToDefinitionProperty)(e,t.horzLabelsAlign,g.format({toolName:o})),w.alignmentHorizontalItems=i.alignmentHorizontalItems),void 0!==t.textOrientation&&(r.orientation=(0,n.convertToDefinitionProperty)(e,t.textOrientation,_.format({toolName:o}))),
+void 0!==t.backgroundVisible&&(r.backgroundVisible=(0,n.convertToDefinitionProperty)(e,t.backgroundVisible,y.format({toolName:o}))),void 0!==t.backgroundColor){let i=null;void 0!==t.backgroundTransparency&&(i=t.backgroundTransparency),r.backgroundColor=(0,n.getColorDefinitionProperty)(e,t.backgroundColor,i,b.format({toolName:o}))}return void 0===t.backgroundVisible&&void 0===t.backgroundColor||(w.backgroundTitle=i.customTitles&&i.customTitles.backgroundTitle||T),void 0!==t.borderVisible&&(r.borderVisible=(0,n.convertToDefinitionProperty)(e,t.borderVisible,m.format({toolName:o}))),void 0!==t.borderWidth&&(r.borderWidth=(0,n.convertToDefinitionProperty)(e,t.borderWidth,f.format({toolName:o}))),void 0!==t.borderColor&&(r.borderColor=(0,n.getColorDefinitionProperty)(e,t.borderColor,null,P.format({toolName:o}))),void 0===t.borderVisible&&void 0===t.borderColor&&void 0===t.borderWidth||(w.borderTitle=i.customTitles&&i.customTitles.borderTitle||C),void 0!==t.wrap&&(r.wrap=(0,n.convertToDefinitionProperty)(e,t.wrap,v.format({toolName:o})),w.wrapTitle=i.customTitles&&i.customTitles.wrapTitle||x),(0,n.createTextPropertyDefinition)(r,w)}},14472:(e,t,o)=>{o.r(t),o.d(t,{LineDataSourceDefinitionsViewModel:()=>P,LineDataSourceTabTypes:()=>i,pointPriceBarTitle:()=>f});var i,r=o(50151),n=o(11542),s=o(95804),a=(o(40167),o(95338)),l=o(60567),d=o(22613),c=o(73863),u=o(97578),p=o(81634),h=o(36313);!function(e){e.Visibility="visibility",e.Coordinates="coordinates",e.Style="style",e.Text="text",e.Inputs="inputs"}(i||(i={}));const g=n.t(null,void 0,o(40091)),_=n.t(null,void 0,o(78930)),y=n.t(null,void 0,o(92516)),b=n.t(null,void 0,o(70320)),m=n.t(null,void 0,o(21429)),f=n.t(null,{context:"linetool point"},o(80166));class P{constructor(e,t){this._yCoordinateStepWV=null,this._propertyPages=[],this._source=t,this._undoModel=e,this._ownerSource=(0,r.ensureNotNull)(this._source.ownerSource()),this._propertyApplier=new p.PropertyApplierWithoutSavingChart((()=>e)),this._createPropertyRages()}destroy(){null!==this._yCoordinateStepWV&&(this._source.ownerSourceChanged().unsubscribeAll(this),this._ownerSource.priceStepChanged().unsubscribeAll(this)),this._source.pointAdded().unsubscribeAll(this),this._propertyPages.forEach((e=>{(0,a.destroyDefinitions)(e.definitions.value())}))}propertyPages(){return Promise.resolve(this._propertyPages)}_createPropertyRages(){this._propertyPages=[];const e=this._createInputsPropertyPage();null!==e&&this._propertyPages.push(e);const t=this._createStylePropertyPage();null!==t&&this._propertyPages.push(t);const o=this._createTextPropertyPage();null!==o&&this._propertyPages.push(o);const i=this._createCoordinatesPropertyPage();null!==i&&(i.visible=this._source.hasEditableCoordinates(),this._propertyPages.push(i));const r=this._createVisibilitiesPropertyPage();this._propertyPages.push(r)}_createVisibilitiesPropertyPage(){const e=this._source.properties().childs().intervalsVisibilities.childs();return(0,l.createPropertyPage)((0,
+c.getIntervalsVisibilitiesPropertiesDefinitions)(this._propertyApplier,e,new s.TranslatedString(this._source.name(),this._source.title(h.TitleDisplayTarget.StatusLine,!0))),"visibility",g)}_createCoordinatesPropertyPage(){const e=this._coordinatesPropertyDefinitions();return null!==e?(e.definitions.length<this._source.pointsCount()&&this._source.pointAdded().subscribe(this,this._updateCoordinatesPropertyDefinitons),(0,l.createPropertyPage)(e,"coordinates",_)):null}_getYCoordinateStepWV(){return null===this._yCoordinateStepWV&&(this._yCoordinateStepWV=new d.WatchedValue(function(e){if(null!==e){const t=e.priceStep();if(null!==t)return t}return 1}(this._source.ownerSource())),this._ownerSource.priceStepChanged().subscribe(this,(()=>this._updateYCoordinateStep())),this._source.ownerSourceChanged().subscribe(this,(()=>{this._ownerSource.priceStepChanged().unsubscribeAll(this),this._ownerSource=(0,r.ensureNotNull)(this._source.ownerSource()),this._ownerSource.priceStepChanged().subscribe(this,(()=>this._updateYCoordinateStep()))}))),this._yCoordinateStepWV}_coordinatesPropertyDefinitions(){const e=this._source.points(),t=this._source.pointsProperty().childs().points,o=[],i=this._getYCoordinateStepWV();return e.forEach(((e,r)=>{const n=t[r].childs();n&&o.push((0,u.getCoordinatesPropertiesDefinitions)(this._propertyApplier,n,e,i,f.format({count:(r+1).toString()}),this._source.name()))})),{definitions:o}}_createStylePropertyPage(){const e=this._stylePropertyDefinitions();return null!==e?(0,l.createPropertyPage)(e,"style",y):null}_stylePropertyDefinitions(){return null}_createTextPropertyPage(){const e=this._textPropertyDefinitions();return null!==e?(0,l.createPropertyPage)(e,"text",b):null}_textPropertyDefinitions(){return null}_createInputsPropertyPage(){const e=this._inputsPropertyDefinitions();return null!==e?(0,l.createPropertyPage)(e,"inputs",m):null}_inputsPropertyDefinitions(){return null}_updateYCoordinateStep(){const e=this._ownerSource.priceStep();this._getYCoordinateStepWV().setValue(e||1)}_updateCoordinatesPropertyDefinitons(){const e=this._coordinatesPropertyDefinitions();if(null!==e){(0,r.ensureDefined)(this._propertyPages.find((e=>"coordinates"===e.id))).definitions.setValue(e.definitions),this._source.points().length===this._source.pointsCount()&&this._source.pointAdded().unsubscribeAll(this)}}}},12891:(e,t,o)=>{o.r(t),o.d(t,{LineToolBalloon:()=>A});var i=o(50151),r=o(11542),n=o(78176),s=o(63117),a=o(43337),l=o(65045),d=o(95804),c=o(91445),u=o(14472);const p=r.t(null,void 0,o(70320));class h extends u.LineDataSourceDefinitionsViewModel{_textPropertyDefinitions(){const e=this._source.properties().childs();return{definitions:[(0,c.createTextStyleDefinition)(this._propertyApplier,{textColor:e.color,fontSize:e.fontsize,text:e.text,backgroundColor:e.backgroundColor,backgroundTransparency:e.transparency,borderColor:e.borderColor},new d.TranslatedString(this._source.name(),this._source.translatedType()),{isEditable:!0,isMultiLine:!0,customTitles:{text:p}})]}}}
+var g,_=o(52859),y=o(49251),b=o(84617),m=o(54707),f=o(73914),P=o(94602),v=o(45801),T=o(2383),C=o(10555),x=o(6453),S=o(24640),w=o(33350),D=o(20820);!function(e){e[e.Radius=15]="Radius",e[e.TailApexXOffsetFromTextStart=20]="TailApexXOffsetFromTextStart",e[e.TailHeight=9]="TailHeight"}(g||(g={}));class N extends D.MediaCoordinatesPaneRenderer{constructor(){super(...arguments),this._geometryCache={innerHeight:NaN,textHorizontalPadding:NaN,innerWidth:NaN,paddingLeft:NaN},this._geomertryCacheInvalidated=!0,this._data=null}setData(e){this._data=e,this._geomertryCacheInvalidated=!0}hitTest(e){if(null===this._data||0===this._data.points.length)return null;const t=this._data.points[0].x-(this._geometryCache.paddingLeft+20),o=this._data.points[0].y-(this._geometryCache.innerHeight+9),i=(0,C.box)(new C.Point(t,o),new C.Point(t+this._geometryCache.innerWidth,o+this._geometryCache.innerHeight));return(0,x.pointInBox)(e,i)?new T.HitTestResult(T.HitTarget.MovePoint,{areaName:T.AreaName.Text}):null}_drawImpl(e){if(null===this._data||0===this._data.points.length)return;const t=e.context;t.font=this._data.font;const o=this._measureInfo(t,this._data.label,this._data.fontSize),{paddingLeft:i,innerHeight:r,innerWidth:n,textHorizontalPadding:s}=o;t.textAlign=(0,S.isRtl)()?"right":"left";const a=this._data.points[0].x-(i+20),l=this._data.points[0].y-(r+9);t.translate(a,l),t.beginPath(),t.moveTo(24,r),t.lineTo(15,r),t.arcTo(-1e3,0,1e3,0,r/2),t.lineTo(n-15,0),t.arcTo(1e3,r,-1e3,r,r/2),t.lineTo(33,r),t.quadraticCurveTo(33,r+4,35,r+9),t.quadraticCurveTo(27,r+6,24,r),t.fillStyle=this._data.backgroundColor,t.fill(),t.strokeStyle=this._data.borderColor,t.lineWidth=2,t.stroke(),t.closePath(),t.textBaseline="middle",t.fillStyle=this._data.color,t.fillText(this._data.label,i+s,r/2)}_measureInfo(e,t,o){if(this._geomertryCacheInvalidated){const i=e.measureText(t),r=o,n=15,s=Math.round(r/1.3),a=i.width+2*n,l=r+2*s,d=(0,w.calcTextHorizontalShift)(e,i.width);this._geometryCache={paddingLeft:n,innerWidth:a,innerHeight:l,textHorizontalPadding:d},this._geomertryCacheInvalidated=!1}return this._geometryCache}}class V extends m.LineSourcePaneView{constructor(e,t){super(e,t),this._balloonRenderer=new N,this._renderer=null}renderer(e){return this._invalidated&&this._updateImpl(e),this._renderer}_updateImpl(e){super._updateImpl(e);const t=this._source.properties().childs(),o={points:this._points,color:t.color.value(),borderColor:t.borderColor.value(),backgroundColor:(0,_.generateColor)(t.backgroundColor.value(),t.transparency.value()),font:(0,y.makeFont)(t.fontsize.value(),b.CHART_FONT_FAMILY),fontSize:t.fontsize.value(),label:t.text.value()};if(this._balloonRenderer.setData(o),1===o.points.length){const e=new P.CompositeRenderer;return e.append(this._balloonRenderer),e.append(new v.SelectionRenderer({points:o.points.map(f.mapLineSourcePaneViewPointToLineAnchorPoint),bgColors:this._lineAnchorColors(o.points),visible:this.areAnchorsVisible(),barSpacing:this._model.timeScale().barSpacing(),hittestResult:T.HitTarget.MovePoint})),void(this._renderer=e)}
+this._renderer=this._balloonRenderer}}const k=r.t(null,void 0,o(9818));class A extends s.InplaceTextLineDataSource{constructor(e,t,o,i){super(e,t??A.createProperties(e.backgroundTheme().spawnOwnership()),o,i),this._createPaneView()}pointsCount(){return 1}name(){return"Balloon"}template(){const e=super.template();return e.text=this.properties().childs().text.value(),e}shouldBeRemovedOnDeselect(){return""===this._properties.childs().text.value().trim()}editableTextProperties(){(0,i.assert)(!1,"unexpected method call")}static createProperties(e,t){const o=new n.DefaultProperty({defaultName:"linetoolballoon",state:t,theme:e});return this._configureProperties(o),o}_applyTemplateImpl(e){super._applyTemplateImpl(e),this.properties().childs().text.setValue(e.text)}async _getPropertyDefinitionsViewModelClass(){return h}_createPaneView(){this._setPaneViews([new V(this,this._model)])}static _configureProperties(e){super._configureProperties(e),e.hasChild("text")||e.addChild("text",new a.Property(this._defaultText)),e.addExcludedKey("text",1),e.addChild("linesColors",new l.LineToolColorsProperty([e.childs().borderColor])),e.addChild("textsColors",new l.LineToolColorsProperty([e.childs().color]))}}A._defaultText=k}}]);

web/public/charting_library/bundles/3014.b5b7477b23dda9a91666.css

@@ -0,0 +1 @@
+.button-Y1TCZogJ{all:unset;display:flex;position:relative}.button-Y1TCZogJ:before{border-radius:4px;content:none;height:100%;left:0;outline:var(--color-tv-blue-500) none 2px;outline-offset:-2px;position:absolute;top:0;width:100%}.button-Y1TCZogJ:focus-visible:before{content:"";outline-style:solid}.button-Y1TCZogJ.active-Y1TCZogJ:before{outline-color:var(--color-white)}

web/public/charting_library/bundles/3014.b5b7477b23dda9a91666.rtl.css

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web/public/charting_library/bundles/3179.78787edf30f25d297844.js

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