1089 lines
47 KiB
Python
1089 lines
47 KiB
Python
#!/usr/bin/env python3
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"""
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Dexorder User Container Main Entry Point
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Brings together:
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- Config and secrets loading from k8s mounted YAML files
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- ZeroMQ event publisher for user events
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- MCP server with minimal "hello world" resource
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- Lifecycle management integration
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"""
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import asyncio
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import contextlib
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import logging
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import os
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import signal
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import sys
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import time
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from pathlib import Path
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from typing import Optional
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import uvicorn
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import yaml
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from mcp.server import Server
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from mcp.server.stdio import stdio_server
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from mcp.server.streamable_http_manager import StreamableHTTPSessionManager
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from mcp.types import Tool, TextContent, ImageContent
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from starlette.applications import Starlette
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from starlette.requests import Request
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from starlette.responses import Response
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from starlette.routing import Route, Mount
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from dexorder import EventPublisher, start_lifecycle_manager, get_lifecycle_manager
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from dexorder.api import set_api, API
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from dexorder.conda_manager import sync_packages, install_packages
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from dexorder.events import EventType, UserEvent, DeliverySpec
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from dexorder.impl.charting_api_impl import ChartingAPIImpl
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from dexorder.impl.data_api_impl import DataAPIImpl
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from dexorder.tools.python_tools import get_category_manager, sanitize_name
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from dexorder.tools.workspace_tools import get_workspace_store
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from dexorder.tools.evaluate_indicator import evaluate_indicator
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from dexorder.tools.backtest_strategy import backtest_strategy
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from dexorder.tools.activate_strategy import activate_strategy, deactivate_strategy, list_active_strategies
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# =============================================================================
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# Global Data Directory
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# =============================================================================
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# Default data directory (relative to working directory for local dev)
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DEFAULT_DATA_DIR = Path("data")
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# Global data directory - set after config is loaded
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DATA_DIR: Path = DEFAULT_DATA_DIR
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def get_data_dir() -> Path:
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"""Get the global data directory."""
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return DATA_DIR
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# =============================================================================
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# Indicator Types Helpers
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# =============================================================================
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def _build_indicator_type_entry(meta: dict) -> dict:
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"""Build an indicator_types workspace entry from indicator metadata dict."""
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name = meta.get('name', '')
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pandas_ta_name = f"custom_{sanitize_name(name).lower()}"
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now = int(time.time())
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return {
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'pandas_ta_name': pandas_ta_name,
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'display_name': name,
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'description': meta.get('description', ''),
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'metadata': {
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'display_name': name,
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'parameters': meta.get('parameters') or {},
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'input_series': meta.get('input_series') or ['close'],
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'output_columns': meta.get('output_columns') or [{'name': 'value'}],
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'pane': meta.get('pane', 'separate'),
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'filled_areas': meta.get('filled_areas') or [],
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'bands': meta.get('bands') or [],
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},
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'created_at': now,
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'modified_at': now,
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}
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def _upsert_indicator_type(workspace_store, category_manager, name: str) -> None:
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"""Read indicator metadata from disk and upsert into indicator_types workspace store."""
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read_result = category_manager.read('indicator', name)
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if not read_result.get('exists') or not read_result.get('metadata'):
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return
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meta = read_result['metadata']
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entry = _build_indicator_type_entry(meta)
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pandas_ta_name = entry['pandas_ta_name']
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# Preserve original created_at if already present
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existing = workspace_store.read('indicator_types')
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existing_types = (existing.get('data') or {}).get('types') or {}
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if pandas_ta_name in existing_types:
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entry['created_at'] = existing_types[pandas_ta_name].get('created_at', entry['created_at'])
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workspace_store.patch('indicator_types', [
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{'op': 'add', 'path': f'/types/{pandas_ta_name}', 'value': entry}
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])
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logging.info(f"Upserted indicator_types/{pandas_ta_name} for '{name}'")
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def _populate_indicator_types_from_disk(workspace_store, category_manager) -> None:
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"""Scan existing indicators and add any missing entries to indicator_types store."""
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existing = workspace_store.read('indicator_types')
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existing_types = (existing.get('data') or {}).get('types') or {}
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list_result = category_manager.list_items('indicator')
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items = list_result.get('items', [])
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added = 0
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for item in items:
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item_name = item.get('name', '')
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if not item_name:
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continue
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pandas_ta_name = f"custom_{sanitize_name(item_name).lower()}"
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if pandas_ta_name not in existing_types:
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_upsert_indicator_type(workspace_store, category_manager, item_name)
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added += 1
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if added > 0:
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logging.info(f"Populated {added} indicator type(s) from disk into indicator_types store")
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# =============================================================================
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# Configuration
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# =============================================================================
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class Config:
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"""Application configuration loaded from config.yaml and secrets.yaml"""
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def __init__(self):
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# User ID (required)
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self.user_id: str = os.getenv("USER_ID", "")
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if not self.user_id:
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raise ValueError("USER_ID environment variable required")
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# Config and secrets paths (k8s mounted)
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self.config_path = Path(os.getenv("CONFIG_PATH", "/app/config/config.yaml"))
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self.secrets_path = Path(os.getenv("SECRETS_PATH", "/app/config/secrets.yaml"))
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# ZMQ ports for event system
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self.zmq_xpub_port: int = int(os.getenv("ZMQ_XPUB_PORT", "5570"))
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self.zmq_gateway_endpoint: str = os.getenv(
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"ZMQ_GATEWAY_ENDPOINT",
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"tcp://gateway:5571"
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)
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# MCP server settings
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self.mcp_server_name: str = os.getenv("MCP_SERVER_NAME", "dexorder-user")
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self.mcp_transport: str = os.getenv("MCP_TRANSPORT", "sse") # "stdio" or "sse"
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self.mcp_http_port: int = int(os.getenv("MCP_HTTP_PORT", "3000"))
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self.mcp_http_host: str = os.getenv("MCP_HTTP_HOST", "0.0.0.0")
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# Lifecycle settings
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self.idle_timeout_minutes: int = int(os.getenv("IDLE_TIMEOUT_MINUTES", "15"))
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self.enable_idle_shutdown: bool = os.getenv("ENABLE_IDLE_SHUTDOWN", "true").lower() == "true"
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# Loaded from files
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self.config_data: dict = {}
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self.secrets_data: dict = {}
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# Data directory (set after config load)
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self.data_dir: Path = DEFAULT_DATA_DIR
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def load(self) -> None:
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"""Load configuration and secrets from YAML files"""
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global DATA_DIR
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# Load config.yaml if exists
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if self.config_path.exists():
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with open(self.config_path) as f:
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self.config_data = yaml.safe_load(f) or {}
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logging.info(f"Loaded config from {self.config_path}")
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else:
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logging.warning(f"Config file not found: {self.config_path}")
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# Load secrets.yaml if exists
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if self.secrets_path.exists():
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with open(self.secrets_path) as f:
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self.secrets_data = yaml.safe_load(f) or {}
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logging.info(f"Loaded secrets from {self.secrets_path}")
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else:
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logging.warning(f"Secrets file not found: {self.secrets_path}")
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# Set data directory from config or environment
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# Priority: env var > config file > default
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data_dir_str = os.getenv("DATA_DIR") or self.config_data.get("data_dir")
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if data_dir_str:
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self.data_dir = Path(data_dir_str)
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else:
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self.data_dir = DEFAULT_DATA_DIR
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# Update global DATA_DIR
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DATA_DIR = self.data_dir
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# Ensure data directory exists
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self.data_dir.mkdir(parents=True, exist_ok=True)
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logging.info(f"Data directory: {self.data_dir}")
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@property
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def workspace_dir(self) -> Path:
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"""Workspace directory under DATA_DIR."""
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return self.data_dir / "workspace"
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# =============================================================================
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# MCP Server Setup
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# =============================================================================
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def create_mcp_server(config: Config, event_publisher: EventPublisher) -> Server:
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"""Create MCP server with resources and workspace tools"""
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server = Server(config.mcp_server_name)
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# Initialize workspace store
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workspace_store = get_workspace_store(config.workspace_dir)
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logging.info(f"Workspace store initialized at {config.workspace_dir}")
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# Initialize category file manager
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category_manager = get_category_manager(config.data_dir)
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logging.info(f"Category manager initialized at {config.data_dir}")
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# Populate indicator_types store from existing indicators on disk (migration/startup sync)
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_populate_indicator_types_from_disk(workspace_store, category_manager)
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@server.list_resources()
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async def list_resources():
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"""List available resources"""
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return [
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{
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"uri": f"dexorder://user/{config.user_id}/hello",
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"name": "Hello World",
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"description": "A simple hello world resource",
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"mimeType": "text/plain",
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}
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]
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@server.read_resource()
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async def read_resource(uri: str):
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"""Read a resource by URI"""
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if uri == f"dexorder://user/{config.user_id}/hello":
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# Publish an event when resource is accessed
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await event_publisher.publish(UserEvent(
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event_type=EventType.STRATEGY_LOG,
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payload={
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"message": "Hello world resource accessed",
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"uri": uri,
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},
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delivery=DeliverySpec.informational(),
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))
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return {
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"uri": uri,
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"mimeType": "text/plain",
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"text": f"Hello from Dexorder user container!\nUser ID: {config.user_id}\n",
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}
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else:
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raise ValueError(f"Unknown resource: {uri}")
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@server.list_tools()
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async def list_tools():
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"""List available tools including workspace and category tools"""
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return [
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Tool(
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name="workspace_read",
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description="Read a workspace store from persistent storage",
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inputSchema={
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"type": "object",
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"properties": {
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"store_name": {
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"type": "string",
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"description": "Name of the store (e.g., 'chartStore', 'userPreferences')"
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}
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},
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"required": ["store_name"]
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}
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),
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Tool(
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name="workspace_write",
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description="Write a workspace store to persistent storage",
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inputSchema={
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"type": "object",
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"properties": {
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"store_name": {
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"type": "string",
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"description": "Name of the store"
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},
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"data": {
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"description": "Data to write"
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}
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},
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"required": ["store_name", "data"]
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}
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),
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Tool(
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name="workspace_patch",
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description="Apply JSON patch operations to a workspace store",
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inputSchema={
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"type": "object",
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"properties": {
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"store_name": {
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"type": "string",
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"description": "Name of the store"
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},
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"patch": {
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"type": "array",
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"description": "JSON Patch operations (RFC 6902)",
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"items": {
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"type": "object",
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"properties": {
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"op": {"type": "string", "enum": ["add", "remove", "replace", "move", "copy", "test"]},
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"path": {"type": "string"},
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"value": {}
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},
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"required": ["op", "path"]
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}
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}
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},
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"required": ["store_name", "patch"]
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}
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),
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Tool(
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name="python_write",
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description="Write a new strategy, indicator, or research script with validation",
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inputSchema={
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"type": "object",
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"properties": {
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"category": {
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"type": "string",
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"enum": ["strategy", "indicator", "research"],
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"description": "Category of the script"
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},
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"name": {
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"type": "string",
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"description": "Display name (can contain special characters)"
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},
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"description": {
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"type": "string",
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"description": "LLM-generated description of what this does (required)"
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},
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"code": {
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"type": "string",
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"description": "Python implementation code"
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},
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"metadata": {
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"type": "object",
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"description": (
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"Optional category-specific metadata. "
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"For strategy: include 'data_feeds' (list of {symbol, period_seconds, description}) "
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"and 'parameters' (object mapping param_name → {default, description}). "
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"Example: {\"data_feeds\": [{\"symbol\": \"BTC/USDT.BINANCE\", \"period_seconds\": 3600, \"description\": \"Primary BTC/USDT hourly feed\"}], "
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"\"parameters\": {\"rsi_length\": {\"default\": 14, \"description\": \"RSI lookback period\"}, \"threshold\": {\"default\": 70, \"description\": \"Overbought level\"}}}. "
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"For indicator: include 'default_length' (int). "
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"For any category: 'conda_packages' (list of package names) if extra dependencies are needed."
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)
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}
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},
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"required": ["category", "name", "description", "code"]
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}
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),
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Tool(
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name="python_edit",
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description=(
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"Edit an existing category script. "
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"Use 'patches' for targeted string replacements (preferred for small changes), "
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"or 'code' to replace the full implementation. Do not supply both."
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),
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inputSchema={
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"type": "object",
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"properties": {
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"category": {
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"type": "string",
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"enum": ["strategy", "indicator", "research"],
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"description": "Category of the script"
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},
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"name": {
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"type": "string",
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"description": "Display name of the existing item"
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},
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"code": {
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"type": "string",
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"description": "Full replacement Python code. Use only when rewriting the entire implementation; prefer 'patches' for targeted edits."
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},
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"patches": {
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"type": "array",
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"description": (
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"Targeted code edits as old/new string pairs. Preferred over 'code' for small changes. "
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"Each patch: {\"old_string\": \"exact text to find\", \"new_string\": \"replacement text\"}. "
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"old_string must be unique in the file (add surrounding context if needed). "
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"Patches are applied in order."
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),
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"items": {
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"type": "object",
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"properties": {
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"old_string": {"type": "string"},
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"new_string": {"type": "string"}
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},
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"required": ["old_string", "new_string"]
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}
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},
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"description": {
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"type": "string",
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"description": "Updated description (optional, omit to keep existing)"
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},
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"metadata": {
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"type": "object",
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"description": (
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"Updated metadata fields (optional). "
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"For strategy: 'data_feeds' (list of {symbol, period_seconds, description}) "
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"and/or 'parameters' (object mapping param_name → {default, description}). "
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"For indicator: 'default_length' (int). "
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"For any category: 'conda_packages' (list of package names)."
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)
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}
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},
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"required": ["category", "name"]
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}
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),
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Tool(
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name="python_read",
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description="Read a category script and its metadata",
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inputSchema={
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"type": "object",
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"properties": {
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"category": {
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"type": "string",
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"enum": ["strategy", "indicator", "research"],
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"description": "Category of the script"
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},
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"name": {
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"type": "string",
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"description": "Display name of the item"
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}
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},
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"required": ["category", "name"]
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}
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),
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Tool(
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name="python_list",
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description="List all items in a category with names and descriptions",
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inputSchema={
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"type": "object",
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"properties": {
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"category": {
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"type": "string",
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"enum": ["strategy", "indicator", "research"],
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"description": "Category to list"
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}
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},
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"required": ["category"]
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}
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),
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Tool(
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name="python_log",
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description="Show git commit history for category items. Filter by category and/or name to see history for a specific item.",
|
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inputSchema={
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"type": "object",
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"properties": {
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"category": {
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"type": "string",
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"enum": ["strategy", "indicator", "research"],
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"description": "Filter to this category (optional)"
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},
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"name": {
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"type": "string",
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"description": "Filter to this item (optional, requires category)"
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},
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"limit": {
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"type": "integer",
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"description": "Max commits to return (default 20)",
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"default": 20
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}
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},
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"required": []
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}
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),
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Tool(
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name="python_revert",
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description="Restore a category item to a previous git revision. Creates a new commit — non-destructive.",
|
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inputSchema={
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"type": "object",
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"properties": {
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"revision": {
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"type": "string",
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"description": "Git commit hash (full or short) to restore to"
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},
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"category": {
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"type": "string",
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"enum": ["strategy", "indicator", "research"],
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"description": "Category of the item"
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},
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"name": {
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"type": "string",
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"description": "Display name of the item to restore"
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}
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},
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"required": ["revision", "category", "name"]
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}
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),
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|
Tool(
|
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name="conda_sync",
|
|
description="Sync conda packages: scan all metadata, remove unused packages (excluding base environment)",
|
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inputSchema={
|
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"type": "object",
|
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"properties": {},
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"required": []
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}
|
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),
|
|
Tool(
|
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name="conda_install",
|
|
description="Install conda packages on-demand",
|
|
inputSchema={
|
|
"type": "object",
|
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"properties": {
|
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"packages": {
|
|
"type": "array",
|
|
"items": {"type": "string"},
|
|
"description": "List of conda package names to install"
|
|
}
|
|
},
|
|
"required": ["packages"]
|
|
}
|
|
),
|
|
Tool(
|
|
name="execute_research",
|
|
description="Execute a research script and return results with matplotlib images",
|
|
inputSchema={
|
|
"type": "object",
|
|
"properties": {
|
|
"name": {
|
|
"type": "string",
|
|
"description": "Display name of the research script to execute"
|
|
}
|
|
},
|
|
"required": ["name"]
|
|
}
|
|
),
|
|
Tool(
|
|
name="evaluate_indicator",
|
|
description=(
|
|
"Evaluate a pandas-ta indicator against real OHLC data and return a structured "
|
|
"array of timestamped values. Use this to validate that an indicator computes "
|
|
"correctly before adding it to the workspace, or to inspect its output values."
|
|
),
|
|
inputSchema={
|
|
"type": "object",
|
|
"properties": {
|
|
"symbol": {
|
|
"type": "string",
|
|
"description": "Market symbol in 'MARKET.EXCHANGE' format, e.g. 'BTC/USDT.BINANCE'"
|
|
},
|
|
"from_time": {
|
|
"description": "Start of time range. Unix timestamp (int) or date string e.g. '30 days ago', '2024-01-01'"
|
|
},
|
|
"to_time": {
|
|
"description": "End of time range. Unix timestamp (int) or date string e.g. 'now', '2024-03-01'"
|
|
},
|
|
"period_seconds": {
|
|
"type": "integer",
|
|
"description": "Candle period in seconds (e.g. 3600 for 1h, 900 for 15m, 86400 for 1d)",
|
|
"default": 3600
|
|
},
|
|
"pandas_ta_name": {
|
|
"type": "string",
|
|
"description": "Lowercase pandas-ta function name, e.g. 'rsi', 'macd', 'bbands'"
|
|
},
|
|
"parameters": {
|
|
"type": "object",
|
|
"description": "pandas-ta keyword arguments, e.g. {\"length\": 14} or {\"fast\": 12, \"slow\": 26, \"signal\": 9}",
|
|
"default": {}
|
|
}
|
|
},
|
|
"required": ["symbol", "from_time", "to_time", "pandas_ta_name"]
|
|
}
|
|
),
|
|
Tool(
|
|
name="backtest_strategy",
|
|
description=(
|
|
"Run a saved trading strategy against historical OHLC data using Nautilus Trader "
|
|
"BacktestEngine. Returns performance metrics (total return, Sharpe ratio, "
|
|
"max drawdown, win rate, trade count) and a full equity curve. "
|
|
"Supports multiple data feeds and includes order-flow fields (buy_vol, sell_vol, "
|
|
"open_interest) in the strategy's DataFrame."
|
|
),
|
|
inputSchema={
|
|
"type": "object",
|
|
"properties": {
|
|
"strategy_name": {
|
|
"type": "string",
|
|
"description": "Display name of the strategy as saved via python_write"
|
|
},
|
|
"feeds": {
|
|
"type": "array",
|
|
"description": "Data feeds to backtest against",
|
|
"items": {
|
|
"type": "object",
|
|
"properties": {
|
|
"symbol": {
|
|
"type": "string",
|
|
"description": "Market symbol in 'MARKET.EXCHANGE' format, e.g. 'BTC/USDT.BINANCE'"
|
|
},
|
|
"period_seconds": {
|
|
"type": "integer",
|
|
"description": "Candle period in seconds (e.g. 3600 for 1h)",
|
|
"default": 3600
|
|
}
|
|
},
|
|
"required": ["symbol"]
|
|
},
|
|
"minItems": 1
|
|
},
|
|
"from_time": {
|
|
"description": "Backtest start. Unix timestamp or date string e.g. '2024-01-01', '90 days ago'"
|
|
},
|
|
"to_time": {
|
|
"description": "Backtest end. Unix timestamp or date string e.g. '2025-01-01', 'now'"
|
|
},
|
|
"initial_capital": {
|
|
"type": "number",
|
|
"description": "Starting capital in quote currency (e.g. 10000.0 USDT)",
|
|
"default": 10000.0
|
|
},
|
|
"paper": {
|
|
"type": "boolean",
|
|
"description": "Always true for historical backtest (reserved for forward testing)",
|
|
"default": True
|
|
}
|
|
},
|
|
"required": ["strategy_name", "feeds", "from_time", "to_time"]
|
|
}
|
|
),
|
|
Tool(
|
|
name="activate_strategy",
|
|
description=(
|
|
"Activate a strategy for paper or live forward trading with a capital allocation. "
|
|
"paper=true (default): simulated fills on live data — no API keys required. "
|
|
"paper=false: real execution via user secrets vault (not yet implemented). "
|
|
"Note: live data streaming is TBD; this registers the strategy for when it becomes available."
|
|
),
|
|
inputSchema={
|
|
"type": "object",
|
|
"properties": {
|
|
"strategy_name": {
|
|
"type": "string",
|
|
"description": "Display name of the strategy as saved via python_write"
|
|
},
|
|
"feeds": {
|
|
"type": "array",
|
|
"description": "Data feeds for the strategy",
|
|
"items": {
|
|
"type": "object",
|
|
"properties": {
|
|
"symbol": {"type": "string"},
|
|
"period_seconds": {"type": "integer", "default": 3600}
|
|
},
|
|
"required": ["symbol"]
|
|
},
|
|
"minItems": 1
|
|
},
|
|
"allocation": {
|
|
"type": "number",
|
|
"description": "Capital allocated in quote currency (e.g. 5000.0 USDT)"
|
|
},
|
|
"paper": {
|
|
"type": "boolean",
|
|
"description": "True = paper/simulated (default); False = live execution",
|
|
"default": True
|
|
}
|
|
},
|
|
"required": ["strategy_name", "feeds", "allocation"]
|
|
}
|
|
),
|
|
Tool(
|
|
name="deactivate_strategy",
|
|
description="Stop an active strategy and return its final P&L summary.",
|
|
inputSchema={
|
|
"type": "object",
|
|
"properties": {
|
|
"strategy_name": {
|
|
"type": "string",
|
|
"description": "Display name of the active strategy to stop"
|
|
}
|
|
},
|
|
"required": ["strategy_name"]
|
|
}
|
|
),
|
|
Tool(
|
|
name="list_active_strategies",
|
|
description="List all currently active (live or paper) strategies and their status.",
|
|
inputSchema={
|
|
"type": "object",
|
|
"properties": {},
|
|
"required": []
|
|
}
|
|
),
|
|
]
|
|
|
|
|
|
@server.call_tool()
|
|
async def handle_tool_call(name: str, arguments: dict):
|
|
"""Handle tool calls including workspace and category tools"""
|
|
get_lifecycle_manager().record_activity()
|
|
try:
|
|
return await _handle_tool_call_inner(name, arguments)
|
|
except Exception:
|
|
logging.exception("Unhandled exception in tool '%s'", name)
|
|
raise
|
|
|
|
async def _handle_tool_call_inner(name: str, arguments: dict):
|
|
if name == "workspace_read":
|
|
return workspace_store.read(arguments.get("store_name", ""))
|
|
elif name == "workspace_write":
|
|
return workspace_store.write(
|
|
arguments.get("store_name", ""),
|
|
arguments.get("data")
|
|
)
|
|
elif name == "workspace_patch":
|
|
return workspace_store.patch(
|
|
arguments.get("store_name", ""),
|
|
arguments.get("patch", [])
|
|
)
|
|
elif name == "python_write":
|
|
result = category_manager.write(
|
|
category=arguments.get("category", ""),
|
|
name=arguments.get("name", ""),
|
|
description=arguments.get("description", ""),
|
|
code=arguments.get("code", ""),
|
|
metadata=arguments.get("metadata")
|
|
)
|
|
content = []
|
|
meta_parts = [f"success: {result['success']}", f"path: {result['path']}"]
|
|
if result.get("revision"):
|
|
meta_parts.append(f"revision: {result['revision']}")
|
|
if result.get("validation") and not result["validation"].get("success"):
|
|
meta_parts.append(f"validation errors: {result['validation'].get('errors', [])}")
|
|
content.append(TextContent(type="text", text="\n".join(meta_parts)))
|
|
if result.get("execution"):
|
|
exec_content = result["execution"].get("content", [])
|
|
content.extend(exec_content)
|
|
image_count = sum(1 for item in exec_content if item.type == "image")
|
|
logging.info(f"python_write '{arguments.get('name')}': returning {len(content)} items, {image_count} images")
|
|
else:
|
|
logging.info(f"python_write '{arguments.get('name')}': no execution result (category={arguments.get('category')})")
|
|
if result.get("success") and arguments.get("category") == "indicator":
|
|
_upsert_indicator_type(workspace_store, category_manager, arguments.get("name", ""))
|
|
return content
|
|
elif name == "python_edit":
|
|
result = category_manager.edit(
|
|
category=arguments.get("category", ""),
|
|
name=arguments.get("name", ""),
|
|
code=arguments.get("code"),
|
|
patches=arguments.get("patches"),
|
|
description=arguments.get("description"),
|
|
metadata=arguments.get("metadata")
|
|
)
|
|
content = []
|
|
meta_parts = [f"success: {result['success']}", f"path: {result['path']}"]
|
|
if result.get("revision"):
|
|
meta_parts.append(f"revision: {result['revision']}")
|
|
if result.get("validation") and not result["validation"].get("success"):
|
|
meta_parts.append(f"validation errors: {result['validation'].get('errors', [])}")
|
|
content.append(TextContent(type="text", text="\n".join(meta_parts)))
|
|
if result.get("execution"):
|
|
exec_content = result["execution"].get("content", [])
|
|
content.extend(exec_content)
|
|
image_count = sum(1 for item in exec_content if item.type == "image")
|
|
logging.info(f"python_edit '{arguments.get('name')}': returning {len(content)} items, {image_count} images")
|
|
else:
|
|
logging.info(f"python_edit '{arguments.get('name')}': no execution result")
|
|
if result.get("success") and arguments.get("category") == "indicator":
|
|
_upsert_indicator_type(workspace_store, category_manager, arguments.get("name", ""))
|
|
return content
|
|
elif name == "python_read":
|
|
return category_manager.read(
|
|
category=arguments.get("category", ""),
|
|
name=arguments.get("name", "")
|
|
)
|
|
elif name == "python_list":
|
|
return category_manager.list_items(
|
|
category=arguments.get("category", "")
|
|
)
|
|
elif name == "python_log":
|
|
result = category_manager.git_log(
|
|
category=arguments.get("category"),
|
|
name=arguments.get("name"),
|
|
limit=int(arguments.get("limit", 20))
|
|
)
|
|
lines = [f"success: {result['success']}"]
|
|
for c in result.get("commits", []):
|
|
lines.append(f"{c['short_hash']} {c['date'][:10]} {c['message']}")
|
|
return [TextContent(type="text", text="\n".join(lines))]
|
|
elif name == "python_revert":
|
|
result = category_manager.git_revert(
|
|
revision=arguments.get("revision", ""),
|
|
category=arguments.get("category", ""),
|
|
name=arguments.get("name", "")
|
|
)
|
|
meta_parts = [f"success: {result['success']}"]
|
|
if result.get("revision"):
|
|
meta_parts.append(f"revision: {result['revision']}")
|
|
if result.get("error"):
|
|
meta_parts.append(f"error: {result['error']}")
|
|
if result.get("validation") and not result["validation"].get("success"):
|
|
meta_parts.append(f"validation errors: {result['validation'].get('errors', [])}")
|
|
return [TextContent(type="text", text="\n".join(meta_parts))]
|
|
elif name == "conda_sync":
|
|
# Get environment.yml path relative to main.py
|
|
env_yml = Path(__file__).parent / "environment.yml"
|
|
return sync_packages(
|
|
data_dir=get_data_dir(),
|
|
environment_yml=env_yml if env_yml.exists() else None
|
|
)
|
|
elif name == "conda_install":
|
|
return install_packages(arguments.get("packages", []))
|
|
elif name == "execute_research":
|
|
result = category_manager.execute_research(name=arguments.get("name", ""))
|
|
if "error" in result:
|
|
logging.error(f"execute_research '{arguments.get('name')}': {result['error']}")
|
|
return [TextContent(type="text", text=f"Error: {result['error']}")]
|
|
content = result.get("content", [TextContent(type="text", text="No output")])
|
|
image_count = sum(1 for item in content if item.type == "image")
|
|
logging.info(f"execute_research '{arguments.get('name')}': returning {len(content)} items, {image_count} images")
|
|
return content
|
|
elif name == "evaluate_indicator":
|
|
return await evaluate_indicator(
|
|
symbol=arguments.get("symbol", ""),
|
|
from_time=arguments.get("from_time"),
|
|
to_time=arguments.get("to_time"),
|
|
period_seconds=int(arguments.get("period_seconds", 3600)),
|
|
pandas_ta_name=arguments.get("pandas_ta_name", ""),
|
|
parameters=arguments.get("parameters") or {},
|
|
)
|
|
elif name == "backtest_strategy":
|
|
return await backtest_strategy(
|
|
strategy_name=arguments.get("strategy_name", ""),
|
|
feeds=arguments.get("feeds", []),
|
|
from_time=arguments.get("from_time"),
|
|
to_time=arguments.get("to_time"),
|
|
initial_capital=float(arguments.get("initial_capital", 10_000.0)),
|
|
paper=bool(arguments.get("paper", True)),
|
|
)
|
|
elif name == "activate_strategy":
|
|
return await activate_strategy(
|
|
strategy_name=arguments.get("strategy_name", ""),
|
|
feeds=arguments.get("feeds", []),
|
|
allocation=float(arguments.get("allocation", 0.0)),
|
|
paper=bool(arguments.get("paper", True)),
|
|
)
|
|
elif name == "deactivate_strategy":
|
|
return await deactivate_strategy(
|
|
strategy_name=arguments.get("strategy_name", ""),
|
|
)
|
|
elif name == "list_active_strategies":
|
|
return await list_active_strategies()
|
|
else:
|
|
raise ValueError(f"Unknown tool: {name}")
|
|
|
|
logging.info(f"MCP server '{config.mcp_server_name}' created with workspace and category tools")
|
|
return server
|
|
|
|
|
|
# =============================================================================
|
|
# Streamable HTTP Transport Setup
|
|
# =============================================================================
|
|
|
|
def create_streamable_http_app(mcp_server: Server) -> Starlette:
|
|
"""Create Starlette app with Streamable HTTP endpoint for MCP"""
|
|
|
|
session_manager = StreamableHTTPSessionManager(app=mcp_server)
|
|
|
|
@contextlib.asynccontextmanager
|
|
async def lifespan(app: Starlette):
|
|
async with session_manager.run():
|
|
yield
|
|
|
|
async def handle_health(request: Request) -> Response:
|
|
"""Health check endpoint for k8s probes and gateway readiness checks"""
|
|
return Response(
|
|
content='{"status":"ok"}',
|
|
media_type="application/json"
|
|
)
|
|
|
|
app = Starlette(
|
|
lifespan=lifespan,
|
|
routes=[
|
|
Mount("/mcp", app=session_manager.handle_request),
|
|
Route("/health", handle_health),
|
|
]
|
|
)
|
|
|
|
return app
|
|
|
|
|
|
# =============================================================================
|
|
# Main Application
|
|
# =============================================================================
|
|
|
|
class UserContainer:
|
|
"""Main user container application"""
|
|
|
|
def __init__(self):
|
|
self.config = Config()
|
|
self.event_publisher: Optional[EventPublisher] = None
|
|
self.mcp_server: Optional[Server] = None
|
|
self.data_api: Optional[DataAPIImpl] = None
|
|
self.running = False
|
|
|
|
async def start(self) -> None:
|
|
"""Start all subsystems"""
|
|
logging.info("Starting user container")
|
|
|
|
# Load configuration
|
|
self.config.load()
|
|
|
|
# Initialize data and charting API
|
|
data_cfg = self.config.config_data.get("data", {})
|
|
iceberg_cfg = data_cfg.get("iceberg", {})
|
|
relay_cfg = data_cfg.get("relay", {})
|
|
secrets = self.config.secrets_data
|
|
s3_cfg = iceberg_cfg # S3 settings co-located with iceberg config
|
|
|
|
self.data_api = DataAPIImpl(
|
|
iceberg_catalog_uri=iceberg_cfg.get("catalog_uri", "http://iceberg-catalog:8181"),
|
|
relay_endpoint=relay_cfg.get("endpoint", "tcp://relay:5559"),
|
|
notification_endpoint=relay_cfg.get("notification_endpoint", "tcp://relay:5558"),
|
|
namespace=iceberg_cfg.get("namespace", "trading"),
|
|
s3_endpoint=s3_cfg.get("s3_endpoint") or secrets.get("s3_endpoint"),
|
|
s3_access_key=s3_cfg.get("s3_access_key") or secrets.get("s3_access_key"),
|
|
s3_secret_key=s3_cfg.get("s3_secret_key") or secrets.get("s3_secret_key"),
|
|
)
|
|
await self.data_api.start()
|
|
set_api(API(charting=ChartingAPIImpl(), data=self.data_api))
|
|
logging.info("API initialized")
|
|
|
|
# Start lifecycle manager
|
|
await start_lifecycle_manager(
|
|
user_id=self.config.user_id,
|
|
idle_timeout_minutes=self.config.idle_timeout_minutes,
|
|
enable_idle_shutdown=self.config.enable_idle_shutdown,
|
|
)
|
|
logging.info("Lifecycle manager started")
|
|
|
|
# Start event publisher
|
|
self.event_publisher = EventPublisher(
|
|
user_id=self.config.user_id,
|
|
xpub_port=self.config.zmq_xpub_port,
|
|
gateway_router_endpoint=self.config.zmq_gateway_endpoint,
|
|
)
|
|
await self.event_publisher.start()
|
|
logging.info("Event publisher started")
|
|
|
|
# Publish CONTAINER_STARTING event
|
|
await self.event_publisher.publish(UserEvent(
|
|
event_type=EventType.CONTAINER_STARTING,
|
|
payload={
|
|
"user_id": self.config.user_id,
|
|
"timestamp": None, # Will be auto-filled
|
|
},
|
|
delivery=DeliverySpec.active_or_telegram(),
|
|
))
|
|
|
|
# Create MCP server
|
|
self.mcp_server = create_mcp_server(self.config, self.event_publisher)
|
|
|
|
# Publish CONTAINER_READY event
|
|
await self.event_publisher.publish(UserEvent(
|
|
event_type=EventType.CONTAINER_READY,
|
|
payload={
|
|
"user_id": self.config.user_id,
|
|
},
|
|
delivery=DeliverySpec.active_or_telegram(),
|
|
))
|
|
|
|
self.running = True
|
|
logging.info("User container ready")
|
|
|
|
async def stop(self) -> None:
|
|
"""Stop all subsystems"""
|
|
if not self.running:
|
|
return
|
|
|
|
logging.info("Stopping user container")
|
|
self.running = False
|
|
|
|
# Publish CONTAINER_SHUTTING_DOWN event
|
|
if self.event_publisher:
|
|
await self.event_publisher.publish(UserEvent(
|
|
event_type=EventType.CONTAINER_SHUTTING_DOWN,
|
|
payload={
|
|
"user_id": self.config.user_id,
|
|
},
|
|
delivery=DeliverySpec.active_or_telegram(),
|
|
))
|
|
|
|
# Stop subsystems
|
|
if self.data_api:
|
|
await self.data_api.stop()
|
|
logging.info("Data API stopped")
|
|
|
|
if self.event_publisher:
|
|
await self.event_publisher.stop()
|
|
logging.info("Event publisher stopped")
|
|
|
|
lifecycle = get_lifecycle_manager()
|
|
if lifecycle:
|
|
await lifecycle.stop()
|
|
logging.info("Lifecycle manager stopped")
|
|
|
|
logging.info("User container stopped")
|
|
|
|
async def run(self) -> None:
|
|
"""Run the MCP server with configured transport"""
|
|
await self.start()
|
|
|
|
try:
|
|
if self.config.mcp_transport == "stdio":
|
|
# Run MCP server on stdio (for dev/testing)
|
|
logging.info("Starting MCP server with stdio transport")
|
|
async with stdio_server() as (read_stream, write_stream):
|
|
await self.mcp_server.run(
|
|
read_stream,
|
|
write_stream,
|
|
self.mcp_server.create_initialization_options()
|
|
)
|
|
elif self.config.mcp_transport == "sse":
|
|
# Run MCP server via Streamable HTTP (for production)
|
|
logging.info(f"Starting MCP server with Streamable HTTP transport on {self.config.mcp_http_host}:{self.config.mcp_http_port}")
|
|
app = create_streamable_http_app(self.mcp_server)
|
|
config = uvicorn.Config(
|
|
app,
|
|
host=self.config.mcp_http_host,
|
|
port=self.config.mcp_http_port,
|
|
log_level=os.getenv("LOG_LEVEL", "info").lower(),
|
|
access_log=True,
|
|
)
|
|
server = uvicorn.Server(config)
|
|
await server.serve()
|
|
else:
|
|
raise ValueError(f"Unknown MCP transport: {self.config.mcp_transport}")
|
|
finally:
|
|
await self.stop()
|
|
|
|
|
|
# =============================================================================
|
|
# Entry Point
|
|
# =============================================================================
|
|
|
|
async def main():
|
|
"""Main entry point"""
|
|
# Setup logging
|
|
log_level = os.getenv("LOG_LEVEL", "INFO").upper()
|
|
logging.basicConfig(
|
|
level=getattr(logging, log_level),
|
|
format="%(asctime)s [%(levelname)s] %(name)s: %(message)s",
|
|
stream=sys.stderr, # MCP uses stdout for protocol
|
|
)
|
|
|
|
# Create and run container
|
|
container = UserContainer()
|
|
|
|
# Handle shutdown signals
|
|
loop = asyncio.get_event_loop()
|
|
|
|
def handle_signal(sig):
|
|
logging.info(f"Received signal {sig}, shutting down...")
|
|
asyncio.create_task(container.stop())
|
|
loop.stop()
|
|
|
|
for sig in (signal.SIGTERM, signal.SIGINT):
|
|
loop.add_signal_handler(sig, lambda s=sig: handle_signal(s))
|
|
|
|
try:
|
|
await container.run()
|
|
except KeyboardInterrupt:
|
|
logging.info("Keyboard interrupt received")
|
|
except Exception as e:
|
|
logging.error(f"Fatal error: {e}", exc_info=True)
|
|
sys.exit(1)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
asyncio.run(main())
|