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Author SHA1 Message Date
6d126db03c fix: improve reasoning summary to explicitly mention trades
The reasoning summary was not accurately reflecting actual trades.
For example, 2 sell trades were summarized as 'maintain core holdings'.

Changes:
- Updated prompt to require explicit mention of trades executed
- Added emphasis on buy/sell tool calls in formatted log
- Trades now highlighted at top of log with TRADES EXECUTED section
- Prompt instructs: state specific trades (symbols, quantities, action)

Example before: 'chose to maintain core holdings'
Example after: 'sold 1 GOOGL and 1 AMZN to reduce exposure'

This ensures reasoning field accurately describes what the AI actually did.
2025-11-05 00:41:59 -05:00
1e7bdb509b chore: remove debug logging from ContextInjector
Removed noisy debug print statements that were added during
troubleshooting. The context injection is now working correctly
and no longer needs diagnostic output.

Cleaned up:
- Entry point logging
- Before/after injection logging
- Tool name and args logging
2025-11-05 00:31:16 -05:00
2 changed files with 21 additions and 14 deletions

View File

@@ -52,10 +52,6 @@ class ContextInjector:
"""
# Inject context parameters for trade tools
if request.name in ["buy", "sell"]:
# Debug: Log self attributes BEFORE injection
print(f"[ContextInjector.__call__] ENTRY: id={id(self)}, self.signature={self.signature}, self.today_date={self.today_date}, self.job_id={self.job_id}, self.session_id={self.session_id}, self.trading_day_id={self.trading_day_id}")
print(f"[ContextInjector.__call__] Args BEFORE injection: {request.args}")
# ALWAYS inject/override context parameters (don't trust AI-provided values)
request.args["signature"] = self.signature
request.args["today_date"] = self.today_date
@@ -66,8 +62,5 @@ class ContextInjector:
if self.trading_day_id:
request.args["trading_day_id"] = self.trading_day_id
# Debug logging
print(f"[ContextInjector] Tool: {request.name}, Args after injection: {request.args}")
# Call the actual tool handler
return await handler(request)

View File

@@ -36,15 +36,17 @@ class ReasoningSummarizer:
summary_prompt = f"""You are reviewing your own trading decisions for the day.
Summarize your trading strategy and key decisions in 2-3 sentences.
IMPORTANT: Explicitly state what trades you executed (e.g., "sold 2 GOOGL shares" or "bought 10 NVDA shares"). If you made no trades, state that clearly.
Focus on:
- What you analyzed
- Why you made the trades you did
- What specific trades you executed (buy/sell, symbols, quantities)
- Why you made those trades
- Your overall strategy for the day
Trading session log:
{log_text}
Provide a concise summary:"""
Provide a concise summary that includes the actual trades executed:"""
response = await self.model.ainvoke([
{"role": "user", "content": summary_prompt}
@@ -67,21 +69,33 @@ Provide a concise summary:"""
reasoning_log: List of message dicts
Returns:
Formatted text representation
Formatted text representation with emphasis on trades
"""
formatted_parts = []
trades_executed = []
for msg in reasoning_log:
role = msg.get("role", "")
content = msg.get("content", "")
tool_name = msg.get("name", "")
if role == "assistant":
# AI's thoughts
formatted_parts.append(f"AI: {content[:200]}")
elif role == "tool":
# Tool results
tool_name = msg.get("name", "tool")
formatted_parts.append(f"{tool_name}: {content[:100]}")
# Highlight trade tool calls
if tool_name in ["buy", "sell"]:
trades_executed.append(f"{tool_name.upper()}: {content[:150]}")
formatted_parts.append(f"TRADE - {tool_name.upper()}: {content[:150]}")
else:
# Other tool results (search, price, etc.)
formatted_parts.append(f"{tool_name}: {content[:100]}")
# Add summary of trades at the top
if trades_executed:
trade_summary = f"TRADES EXECUTED ({len(trades_executed)}):\n" + "\n".join(trades_executed)
formatted_parts.insert(0, trade_summary)
formatted_parts.insert(1, "\n--- FULL LOG ---")
return "\n".join(formatted_parts)