Debug prints & bet only on one market hotfix

[kongzii]

Summary by CodeRabbit

• New Features
  • Enhanced logging for the KnownOutcomeAgent, including detailed feedback on market selection, search query generation, and LLM prompts.

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Commits

Files that changed from the base of the PR and between 57a1a0b and 6795bbd.

Walkthrough

The recent update involves enhancing the logging capabilities of the KnownOutcomeAgent within the prediction market agent project. Specifically, the modifications include adding print statements to better track the agent's decision-making process when selecting markets and to log the interaction with language models (LLMs), including the generation of search queries from LLM outputs. These changes aim to improve transparency and debugging efficiency by providing insights into the agent's operational dynamics and its use of external information.

Changes

File Path	Change Summary
.../known_outcome_agent/deploy.py	Updated logging with additional print statements, improved exception handling, and enhanced efficiency in market selection.
.../known_outcome_agent/known_outcome_agent.py	Added print statements to log LLM prompts and the generated search queries before conducting web searches.

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Review Status

Actionable comments generated: 0

Configuration used: CodeRabbit UI

Commits

Files that changed from the base of the PR and between 14153e8 and bc6b37f.

Files selected for processing (2)

• prediction_market_agent/agents/known_outcome_agent/deploy.py (1 hunks)
• prediction_market_agent/agents/known_outcome_agent/known_outcome_agent.py (1 hunks)

Additional comments: 5

prediction_market_agent/agents/known_outcome_agent/deploy.py (3)

• 40-40: The print statement before checking a market is clear and provides useful information for debugging purposes.
• 47-49: The print statement for picking a market is informative, showing the market ID, question, and known outcome, which aids in understanding why a market was selected.
• 53-56: The print statement for skipping a saturated market is clear and effectively communicates the reason for not selecting the market, which is crucial for debugging.

prediction_market_agent/agents/known_outcome_agent/known_outcome_agent.py (2)

• 155-155: The print statement logging the LLM invocation prompt is clear and provides valuable insight into the inputs provided to the LLM, aiding in debugging and transparency.
• 157-157: The print statement logging the search query generated from LLM output is informative, showing how the LLM's output is utilized for web searches, which is essential for understanding the agent's information gathering process.

[coderabbitai]

Review Status

Actionable comments generated: 0

Configuration used: CodeRabbit UI

Commits

Files that changed from the base of the PR and between bc6b37f and 8950868.

Files selected for processing (1)

• prediction_market_agent/agents/known_outcome_agent/deploy.py (1 hunks)

Files skipped from review as they are similar to previous changes (1)

• prediction_market_agent/agents/known_outcome_agent/deploy.py

[coderabbitai]

Actionable comments posted: 0

Review Status

Configuration used: CodeRabbit UI

Commits

Files that changed from the base of the PR and between 8950868 and 57a1a0b.

Files selected for processing (1)

• prediction_market_agent/agents/known_outcome_agent/deploy.py (1 hunks)

Additional comments not posted (3)

prediction_market_agent/agents/known_outcome_agent/deploy.py (3)

39-39: Adding print statements enhances the visibility into the market evaluation process, aiding in debugging and understanding the agent's decision-making. This aligns with the PR's objective to improve debugging capabilities.

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42-52: The addition of an exception handling block enhances the robustness of the market prediction process. It's good practice to log errors for debugging purposes. Consider defining specific exception types if predictable errors can occur, to provide more targeted error handling and recovery strategies.

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60-63: The early return logic is a practical solution to the GCP Function timeout constraint. However, it's important to assess its impact on the agent's ability to participate in multiple markets. Consider testing or simulating scenarios to ensure this change doesn't unduly limit market participation.