news.ycombinator.com• Mar 9, 2026• 1 min read
Show HN: VectorLens – See why your RAG hallucinates, no configI built VectorLens because I was tired of "log file archaeology" every time my RAG pipeline hallucinated. Usually, when an LLM gives a wrong answer, you're stuck guessing which retrieved chunk misled it—or why the right chunk was ignored.Existing observability tools either require a cloud signup, an enterprise contract, or heavy manual instrumentation of your code. I wanted something that stayed local and just worked.The Solution: Three lines of codePython import vectorlens vectorlens.serve() # Open http://127.0.0.1:7756 # Your RAG code runs as-is (OpenAI, Anthropic, Gemini, ChromaDB, FAISS, etc. are auto-intercepted) How it works technically:Zero-Config Interception: It monkey-patches common LLM and Vector DB clients. You don't have to change your functions or wrap your calls; it intercepts the data flow automatically.Local Hallucination Detection: It uses sentence-transformers (a 22MB model) to compare the LLM’s output sentences against the retrieved context. If the similarity is too
