deepeval
pezzo
deepeval | pezzo | |
---|---|---|
22 | 17 | |
1,923 | 1,837 | |
20.2% | 5.6% | |
9.9 | 8.9 | |
2 days ago | 7 days ago | |
Python | TypeScript | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
deepeval
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Unit Testing LLMs with DeepEval
For the last year I have been working with different LLMs (OpenAI, Claude, Palm, Gemini, etc) and I have been impressed with their performance. With the rapid advancements in AI and the increasing complexity of LLMs, it has become crucial to have a reliable testing framework that can help us maintain the quality of our prompts and ensure the best possible outcomes for our users. Recently, I discovered DeepEval (https://github.com/confident-ai/deepeval), an LLM testing framework that has revolutionized the way we approach prompt quality assurance.
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Show HN: Ragas – the de facto open-source standard for evaluating RAG pipelines
Checkout this instead: https://github.com/confident-ai/deepeval
Also has native ragas implementation but supports all models.
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Show HN: Times faster LLM evaluation with Bayesian optimization
Fair question.
Evaluate refers to the phase after training to check if the training is good.
Usually the flow goes training -> evaluation -> deployment (what you called inference). This project is aimed for evaluation. Evaluation can be slow (might even be slower than training if you're finetuning on a small domain specific subset)!
So there are [quite](https://github.com/microsoft/promptbench) [a](https://github.com/confident-ai/deepeval) [few](https://github.com/openai/evals) [frameworks](https://github.com/EleutherAI/lm-evaluation-harness) working on evaluation, however, all of them are quite slow, because LLM are slow if you don't have infinite money. [This](https://github.com/open-compass/opencompass) one tries to speed up by parallelizing on multiple computers, but none of them takes advantage of the fact that many evaluation queries might be similar and all try to evaluate on all given queries. And that's where this project might come in handy.
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Implemented 12+ LLM evaluation metrics so you don't have to
A link to a reddit post (with no discussion) which links to this repo
https://github.com/confident-ai/deepeval
- Show HN: I implemented a range of evaluation metrics for LLMs that runs locally
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These 5 Open Source AI Startups are changing the AI Landscape
Star DeepEval on GitHub and contribute to the advancement of LLM evaluation frameworks! 🌟
- FLaNK Stack Weekly 06 Nov 2023
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Why we replaced Pinecone with PGVector 😇
Pinecone, the leading closed-source vector database provider, is known for being fast, scalable, and easy to use. Its ability to allow users to perform blazing-fast vector search makes it a popular choice for large-scale RAG applications. Our initial infrastructure for Confident AI, the world’s first open-source evaluation infrastructure for LLMs, utilized Pinecone to cluster LLM observability log data in production. However, after weeks of experimentation, we made the decision to replace it entirely with pgvector. Pinecone’s simplistic design is deceptive due to several hidden complexities, particularly in integrating with existing data storage solutions. For example, it forces a complicated architecture and its restrictive metadata storage capacity made it troublesome for managing data-intensive workloads.
- Show HN: Unit Testing for LLMs
- Show HN: DeepEval – Unit Testing for LLMs (Open Science)
pezzo
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Top Open Source Prompt Engineering Guides & Tools🔧🏗️🚀
Pezzo is a cloud-native LLMOps platform. You can observe and monitor your AI operations, troubleshoot issues, collaborate and manage your prompts in one place, and instantly deliver AI changes.
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These 5 Open Source AI Startups are changing the AI Landscape
Give Pezzo a Star on GitHub 🌟 and join the revolution in AI operations!
- [Showoff Saturday] The fastest growing open source LLMOps platform. We're building for developers, by developers 💪⭐️
- 6 AI Tools You Have To Know as a Software Developer! 🛠 🤯
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Pezzo v0.5 - Dashboards, Caching, Python Client, and More!
Wanna know more? Check Pezzo out on GitHub.
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The 5 Pillars for taking LLM to production
Check out the Pezzo GitHub repository and consider giving us a star! ⭐️
- Pezzo – open-source LLMOps platform
- Show HN: Pezzo – Open-Source LLMOps Plaform Tailored for Developers
- Developer-First LLMOps Platform
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How to Reduce Your OpenAI Costs by up to 30% - 3 Simple Steps 💰
🌟 Check it out GitHub here (and show your support by giving a star): https://github.com/pezzolabs/pezzo
What are some alternatives?
ragas - Evaluation framework for your Retrieval Augmented Generation (RAG) pipelines
StableStudio - Community interface for generative AI
litellm - Call all LLM APIs using the OpenAI format. Use Bedrock, Azure, OpenAI, Cohere, Anthropic, Ollama, Sagemaker, HuggingFace, Replicate (100+ LLMs)
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
blog-examples
token-hawk - WebGPU LLM inference tuned by hand
openvino_notebooks - 📚 Jupyter notebook tutorials for OpenVINO™
EZComplete - A highly customizable GPT3 generative AI CLI based client for iOS (could easily be built for Mac as well). Coded entirely in Objective C, without convenience methods from OpenAI's API.
tailspin - 🌀 A log file highlighter
SecondShiftAugie - Second Shift Augie is a sassy and sarcastic AI assistant that helps answer questions and summarize YouTube videos. It has several different features, including text-to-speech functionality, and the ability to answer questions about its own code with the !selfreflect command.
opencompass - OpenCompass is an LLM evaluation platform, supporting a wide range of models (Llama3, Mistral, InternLM2,GPT-4,LLaMa2, Qwen,GLM, Claude, etc) over 100+ datasets.
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI