backend redesign

backend.old/src/agent/routers.py

@@ -0,0 +1,218 @@
+"""Tool router functions for hierarchical agent architecture.
+
+This module provides meta-tools that route tasks to specialized sub-agents.
+The main agent uses these routers instead of accessing all tools directly.
+"""
+
+import logging
+from typing import Optional
+from langchain_core.tools import tool
+
+logger = logging.getLogger(__name__)
+
+# Global sub-agent instances (set by create_agent)
+_chart_agent = None
+_data_agent = None
+_automation_agent = None
+_research_agent = None
+
+
+def set_chart_agent(agent):
+    """Set the global chart sub-agent instance."""
+    global _chart_agent
+    _chart_agent = agent
+
+
+def set_data_agent(agent):
+    """Set the global data sub-agent instance."""
+    global _data_agent
+    _data_agent = agent
+
+
+def set_automation_agent(agent):
+    """Set the global automation sub-agent instance."""
+    global _automation_agent
+    _automation_agent = agent
+
+
+def set_research_agent(agent):
+    """Set the global research sub-agent instance."""
+    global _research_agent
+    _research_agent = agent
+
+
+@tool
+async def use_chart_analysis(task: str) -> str:
+    """Analyze charts, compute indicators, execute Python code, and create visualizations.
+
+    This tool delegates to a specialized chart analysis agent that has access to:
+    - Chart data retrieval (get_chart_data)
+    - Python execution environment with pandas, numpy, matplotlib, talib
+    - Technical indicator tools (add/remove indicators, search indicators)
+    - Shape drawing tools (create/update/delete shapes on charts)
+
+    Use this when the user wants to:
+    - Analyze price action or patterns
+    - Calculate technical indicators (RSI, MACD, Bollinger Bands, etc.)
+    - Execute custom Python analysis on OHLCV data
+    - Generate charts and visualizations
+    - Draw trendlines, support/resistance, or other shapes
+    - Perform statistical analysis on market data
+
+    Args:
+        task: Detailed description of the chart analysis task. Include:
+            - What to analyze (which symbol, timeframe if different from current)
+            - What indicators or calculations to perform
+            - What visualizations to create
+            - Any specific questions to answer
+
+    Returns:
+        The chart agent's analysis results, including computed values,
+        plot URLs if visualizations were created, and interpretation.
+
+    Examples:
+        - "Calculate RSI(14) for the current chart and tell me if it's overbought"
+        - "Draw a trendline connecting the last 3 swing lows"
+        - "Compute Bollinger Bands (20, 2) and create a chart showing price vs bands"
+        - "Analyze the last 100 bars and identify key support/resistance levels"
+        - "Execute Python: calculate correlation between BTC and ETH over the last 30 days"
+    """
+    if not _chart_agent:
+        return "Error: Chart analysis agent not initialized"
+
+    logger.info(f"Routing to chart agent: {task[:100]}...")
+    result = await _chart_agent.execute(task)
+    return result
+
+
+@tool
+async def use_data_access(task: str) -> str:
+    """Search for symbols and retrieve market data from exchanges.
+
+    This tool delegates to a specialized data access agent that has access to:
+    - Symbol search across multiple exchanges
+    - Historical OHLCV data retrieval
+    - Symbol metadata and info
+    - Available data sources and exchanges
+
+    Use this when the user wants to:
+    - Search for a trading symbol or ticker
+    - Get historical price data
+    - Find out what exchanges support a symbol
+    - Retrieve symbol metadata (price scale, supported resolutions, etc.)
+    - Check what data sources are available
+
+    Args:
+        task: Detailed description of the data access task. Include:
+            - What symbol or instrument to search for
+            - What data to retrieve (time range, resolution)
+            - What metadata is needed
+
+    Returns:
+        The data agent's response with requested symbols, data, or metadata.
+
+    Examples:
+        - "Search for Bitcoin symbols on Binance"
+        - "Get the last 100 hours of BTC/USDT 1-hour data from Binance"
+        - "Find all symbols matching 'ETH' on all exchanges"
+        - "Get detailed info about symbol BTC/USDT on Binance"
+        - "List all available data sources"
+    """
+    if not _data_agent:
+        return "Error: Data access agent not initialized"
+
+    logger.info(f"Routing to data agent: {task[:100]}...")
+    result = await _data_agent.execute(task)
+    return result
+
+
+@tool
+async def use_automation(task: str) -> str:
+    """Schedule recurring tasks, create triggers, and manage automation.
+
+    This tool delegates to a specialized automation agent that has access to:
+    - Scheduled agent prompts (cron and interval-based)
+    - One-time agent prompt execution
+    - Trigger management (list, cancel scheduled jobs)
+    - System stats and monitoring
+
+    Use this when the user wants to:
+    - Schedule a recurring task (hourly, daily, weekly, etc.)
+    - Run a one-time background analysis
+    - Set up automated monitoring or alerts
+    - List or cancel existing scheduled tasks
+    - Check trigger system status
+
+    Args:
+        task: Detailed description of the automation task. Include:
+            - What should happen (what analysis or action)
+            - When it should happen (schedule, frequency)
+            - Any priorities or conditions
+
+    Returns:
+        The automation agent's response with job IDs, confirmation,
+        or status information.
+
+    Examples:
+        - "Schedule a task to check BTC price every 5 minutes"
+        - "Run a one-time analysis of ETH volume in the background"
+        - "Set up a daily report at 9 AM with market summary"
+        - "Show me all my scheduled tasks"
+        - "Cancel the hourly BTC monitor job"
+    """
+    if not _automation_agent:
+        return "Error: Automation agent not initialized"
+
+    logger.info(f"Routing to automation agent: {task[:100]}...")
+    result = await _automation_agent.execute(task)
+    return result
+
+
+@tool
+async def use_research(task: str) -> str:
+    """Search the web, academic papers, and external APIs for information.
+
+    This tool delegates to a specialized research agent that has access to:
+    - Web search (DuckDuckGo)
+    - Academic paper search (arXiv)
+    - Wikipedia lookup
+    - HTTP requests to public APIs
+
+    Use this when the user wants to:
+    - Search for current news or events
+    - Find academic papers on trading strategies
+    - Look up financial concepts or terms
+    - Fetch data from external public APIs
+    - Research market trends or sentiment
+
+    Args:
+        task: Detailed description of the research task. Include:
+            - What information to find
+            - What sources to search (web, arxiv, wikipedia, APIs)
+            - What to focus on or filter
+
+    Returns:
+        The research agent's findings with sources, summaries, and links.
+
+    Examples:
+        - "Search arXiv for papers on reinforcement learning for trading"
+        - "Look up 'technical analysis' on Wikipedia"
+        - "Search the web for latest Ethereum news"
+        - "Fetch current BTC price from CoinGecko API"
+        - "Find recent papers on market microstructure"
+    """
+    if not _research_agent:
+        return "Error: Research agent not initialized"
+
+    logger.info(f"Routing to research agent: {task[:100]}...")
+    result = await _research_agent.execute(task)
+    return result
+
+
+# Export router tools
+ROUTER_TOOLS = [
+    use_chart_analysis,
+    use_data_access,
+    use_automation,
+    use_research
+]