Fix RAG Integration Errors
Budget: ₹1,500 – ₹12,500 INR
I already have a Retrieval-Augmented Generation system running, but something in the integration layer is still breaking the flow. The model, vector store, and front-end are in place; yet responses intermittently fail because of data-pipeline issues. I can’t tell whether the trouble sits in extraction, processing, or loading, so I’m handing the whole trace to you.
What you’ll walk into
• A working codebase (Python, LangChain, OpenAI API, FAISS) that sometimes throws implementation errors when the retriever hands off to the generator.
• Logs that show inconsistent I/O between the pipeline modules, pointing to an integration problem rather than model quality.
• Environment is containerised; I can share the Docker setup, `.env`, and a small test corpus.
What I need back
– A fully functional RAG where every user query is retrieved, passed, and answered without exceptions or silent failures.
– Clean, commented fixes committed to my repo.
– A brief hand-off note summarising the root cause and the changes you made so I can maintain it myself.
I’ll be available on Slack or Zoom to clarify architecture decisions and to run live tests as you patch. If you’re comfortable tracing Python stacks, inspecting LangChain chains, and tightening vector-DB connections, this should be a straightforward but satisfying debug job.
What you’ll walk into
• A working codebase (Python, LangChain, OpenAI API, FAISS) that sometimes throws implementation errors when the retriever hands off to the generator.
• Logs that show inconsistent I/O between the pipeline modules, pointing to an integration problem rather than model quality.
• Environment is containerised; I can share the Docker setup, `.env`, and a small test corpus.
What I need back
– A fully functional RAG where every user query is retrieved, passed, and answered without exceptions or silent failures.
– Clean, commented fixes committed to my repo.
– A brief hand-off note summarising the root cause and the changes you made so I can maintain it myself.
I’ll be available on Slack or Zoom to clarify architecture decisions and to run live tests as you patch. If you’re comfortable tracing Python stacks, inspecting LangChain chains, and tightening vector-DB connections, this should be a straightforward but satisfying debug job.