Debugged local agent execution and environment issues

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📅 2025-05-03 — Session: Debugged local agent execution and environment issues

🕒 03:55–04:30
🏷️ Labels: Debugging, Python, Agent Execution, Environment Variables, API, LLM
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to debug local agent execution issues, focusing on empty output and environment configuration problems.

Key Activities

  • Successfully executed a local agent but identified an empty output issue.
  • Discussed best practices for Python environment isolation and module deployment.
  • Debugged module resolution issues for the Cerebrum SDK.
  • Investigated silent errors in LLM calls and API key issues in ConfigManager.
  • Explored methods to load environment variables in Python using python-dotenv.

Achievements

  • Identified the root causes of empty output in local agent execution.
  • Clarified best practices for Python environment management.
  • Resolved API key issues by configuring environment variables and using a config.yaml file.
  • Improved understanding of loading .env files in Python scripts.

Pending Tasks

  • Further refine the agent’s run method to handle empty outputs more effectively.
  • Implement additional debug prints and assertions for LLM calls.
  • Ensure consistent environment variable loading across all agent scripts.

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