BenchLLM by V7 - Test-driven development for LLMs

Hello Product Hunt! We built BenchLLM to offer a more versatile open-source benchmarking tool for AI applications. It lets you measure the accuracy of your model, agents, or chains by validating responses on any number of tests via LLMs. BenchLLM is actively used at V7 for improving our LLM applications and is now Open Sourced under MIT License to share with the wider community. You can use it to: - Test the responses of your LLM across any number of prompts. - Implement continuous integration for chains like LangChain, agents like AutoGPT, or LLM models like Llama or GPT-4. - Eliminate flaky chains and create confidence in your code. - Spot inaccurate responses and hallucinations in your application at every version. Key Features: - Automated tests and evaluations on any number of prompts and predictions via LLMs. - Multiple evaluation methods: semantic similarity checks, string matching, manual review. - Caching LLM responses to accelerate the testing and evaluation process. - Comprehensive API and CLI for executing test suites and faster development iterations. Here's a preview of a common use case in LLM testing and how popular models compare: https://www.loom.com/share/173c1... Visit our GitHub repo to access examples, templates, and docs. Or join our Discord for feedback or to contribute to the project!

very useful 👈

Great job with the launch. Congrats!

super cool!

Super impressive. Kudos! 👏

This looks really interesting. ?makers How would you recommend dealing with false positives? For example, even using semantic similarity, I imagine you sometimes get some correct answers from a LLM that are flagged as incorrect?

Congrats Alberto & team on your launch!

Love that the LLM tooling eco-system is growing! Good luck today 🚀

This is very interesting. Best wishes for your launch

Just curious, what are the benefits over the LangSmith? And good luck with the launch!