The roadmap for the tool includes implementing an end-to-end pipeline, focusing on methods as the unit of optimization for generating Merge Requests, proposing targeted fixes for exceptions, developing more sophisticated benchmarking scenarios, extending existing test cases using accumulated trace data, adding support for open LLMs, and enhancing the Retrieve and Generate (RAG) pipeline. The setup process involves installing the captureflow-agent and deploying a `fastapi` app with a `redis` instance. The tool is open for contributions and interested parties can join their discord.
Key takeaways:
- The captureflow-py tool utilizes traces from production applications to unlock new approaches for automated bug fixes in response to exceptions.
- It integrates a tracing tool into your application to capture and send execution traces to the server, which then analyzes them and automatically generates MR accompanied by a change reasoning.
- Current support is limited to Python, OpenAI API, and GitHub, and the tool is not yet ready for production use as it may degrade your application's performance.
- The roadmap includes implementing an end-to-end pipeline, focusing on methods as the unit of optimization, proposing targeted fixes for exceptions, extending existing test cases, adding support for open LLMs, and enhancing the Retrieve and Generate (RAG) pipeline.