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# AI Chatbot Evaluation and Observability with Promptfoo and Langfuse

**[Netguru](https://daily.dev/sources/netguru)** · 8 min read · 0 upvotes · 0 comments

## Summary

AI chatbots that pass demos often fail in production due to non-deterministic outputs, retrieval issues, and prompt sensitivity. Two tools address different stages of this problem: Promptfoo handles pre-deployment evaluation through prompt testing, regression testing, model comparison, and adversarial testing; Langfuse handles post-deployment observability through tracing, latency monitoring, cost tracking, and feedback loops. The recommended workflow combines both: run Promptfoo evaluations before deploying prompt or model changes, trace production conversations with Langfuse, then convert real production failures into new Promptfoo regression tests. Key evaluation dimensions include factual accuracy, groundedness, retrieval quality, relevance, safety, latency, task success, and user satisfaction.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.netguru.com/blog/ai-chatbot-evaluation-observability-promptfoo-langfuse>

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Tags: [#llm](https://daily.dev/tags/llm), [#observability](https://daily.dev/tags/observability), [#rag](https://daily.dev/tags/rag)

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