Debugged Local Agent Execution and Environment Issues

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📅 2025-05-03 — Session: Debugged Local Agent Execution and Environment Issues

🕒 04:00–04:30
🏷️ Labels: Debugging, Python, Cerebrum Sdk, Environment, API, LLM
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The primary goal of this session was to debug and resolve issues related to the execution of local agents using the Cerebrum SDK, focusing on environment isolation and module resolution.

Key Activities

  • Debugging Local Agent Execution: Successfully executed a local agent but identified an issue with empty output. A breakdown of what worked and what needs fixing was provided.
  • Python Environment Management: Discussed best practices for environment isolation and module deployment to avoid inconsistencies and broken imports.
  • Module Resolution for Cerebrum SDK: Systematic troubleshooting of module resolution issues, including verifying installation and path configuration.
  • Silent Errors in LLM Calls: Investigated silent errors in LLM calls with empty outputs, providing insights into execution flow and debugging steps.
  • API Key Issues in ConfigManager: Resolved missing API key issues by setting environment variables and configuring authentication.
  • Loading Environment Variables: Provided a guide to load .env files automatically using python-dotenv for easy access to API keys.

Achievements

  • Identified and outlined steps to resolve execution issues with local agents.
  • Improved understanding and practices for Python environment management.
  • Developed actionable steps for debugging LLM API connection issues.

Pending Tasks

  • Further testing of the agent execution to ensure the output is no longer empty.
  • Continued refinement of environment isolation practices and module deployment strategies.

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