Implemented async OpenAI API for batch processing

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📅 2025-02-23 — Session: Implemented async OpenAI API for batch processing

🕒 20:20–21:25
🏷️ Labels: Openai, API, Async, Python, Error Handling, Course Design
📂 Project: Dev

Session Goal:

The session aimed to explore and implement efficient batch processing using OpenAI’s API, focusing on asynchronous requests and error handling.

Key Activities:

  • Explored two methods for batch API calls: asynchronous requests for parallel processing and OpenAI’s Batch API for large-scale jobs.
  • Implemented an asynchronous translation process for a DataFrame’s ‘Snippet’ column using OpenAI’s API.
  • Resolved a RuntimeError in Jupyter Notebooks using the nest_asyncio library to allow nested event loops.
  • Debugged OpenAI API failures related to rate limits and invalid responses.
  • Corrected asynchronous calls to OpenAI API, addressing TypeError issues with await and ChatCompletion.
  • Refactored code for generating course session blueprints, focusing on function renaming, docstring updates, and system prompt enhancements.

Achievements:

  • Successfully implemented and tested asynchronous API calls for batch processing.
  • Improved error handling and debugging techniques for OpenAI API.
  • Enhanced codebase for course session blueprint generation.

Pending Tasks:

  • Further testing and optimization of batch processing methods.
  • Integration of optimized course session planning prompts into the curriculum design process.

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