litellm
deepeval
litellm | deepeval | |
---|---|---|
30 | 22 | |
10,066 | 2,307 | |
7.0% | 14.2% | |
10.0 | 9.9 | |
7 days ago | 5 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | 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.
litellm
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Show HN: Token price calculator for 400+ LLMs
Very cool! Is this cost directory you're using the best source for historical cost per 1M tokens? https://github.com/BerriAI/litellm/blob/main/model_prices_an...
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RAG with llama.cpp and external API services
Next, we'll show how an Embeddings database can integrate with external API services via LiteLLM .
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Anthropic launches Tool Use (function calling)
There are a few libs that already abstract this away, for example:
- https://github.com/BerriAI/litellm
- https://jxnl.github.io/instructor/
- langchain
It's not hard for me to imagine a future where there is something like the CNCF for AI models, tools, and infra.
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Ask HN: Python Meta-Client for OpenAI, Anthropic, Gemini LLM and other API-s?
Hey, are you just looking for litellm - https://github.com/BerriAI/litellm
context - i'm the repo maintainer
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Voxos.ai – An Open-Source Desktop Voice Assistant
It should be possible using LiteLLM and a patch or a proxy.
https://github.com/BerriAI/litellm
- Show HN: Talk to any ArXiv paper just by changing the URL
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Integrate LLM Frameworks
This article will demonstrate how txtai can integrate with llama.cpp, LiteLLM and custom generation methods. For custom generation, we'll show how to run inference with a Mamba model.
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Is there any open source app to load a model and expose API like OpenAI?
I use this with ollama and works perfectly https://github.com/BerriAI/litellm
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OpenAI Switch Kit: Swap OpenAI with any open-source model
Another abstraction layer library is: https://github.com/BerriAI/litellm
For me the killer feature of a library like this would be if it implemented function calling. Even if it was for a very restricted grammar - like the traditional ReAct prompt:
Solve a question answering task with interleaving Thought, Action, Observation usteps. Thought can reason about the current situation, and Action can be three types:
- LibreChat
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)
What are some alternatives?
ollama - Get up and running with Llama 3, Mistral, Gemma 2, and other large language models.
ragas - Evaluation framework for your Retrieval Augmented Generation (RAG) pipelines
FastChat - An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
openvino_notebooks - 📚 Jupyter notebook tutorials for OpenVINO™
dify - Dify is an open-source LLM app development platform. Dify's intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production.
pezzo - 🕹️ Open-source, developer-first LLMOps platform designed to streamline prompt design, version management, instant delivery, collaboration, troubleshooting, observability and more.
LocalAI - :robot: The free, Open Source OpenAI alternative. Self-hosted, community-driven and local-first. Drop-in replacement for OpenAI running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. It allows to generate Text, Audio, Video, Images. Also with voice cloning capabilities.
blog-examples
text-generation-webui - A Gradio web UI for Large Language Models.
tailspin - 🌀 A log file highlighter
libsql - libSQL is a fork of SQLite that is both Open Source, and Open Contributions.
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.