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# Projects Built on LiteLLM
### LangStream
Build robust LLM applications with true composability
[Github](https://github.com/rogeriochaves/langstream)
[Docs](https://rogeriochaves.github.io/langstream/)
### Codium PR Agent
An AI-Powered 🤖 Tool for Automated Pull Request Analysis,
Feedback, Suggestions 💻🔍
[Github](https://github.com/Codium-ai/pr-agent)
### LiteLLM Proxy
liteLLM Proxy Server: 50+ LLM Models, Error Handling, Caching
[Github](https://github.com/BerriAI/litellm/tree/main/proxy-server)

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An AI-Powered 🤖 Tool for Automated Pull Request Analysis,
Feedback, Suggestions 💻🔍
[Github](https://github.com/Codium-ai/pr-agent)

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Fast Run-Eval-Polish Loop for LLM apps
Github: https://github.com/fastrepl/proxy

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Easily migrate your codebase from one framework or language to another.

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Build robust LLM applications with true composability 🔗
[Github](https://github.com/rogeriochaves/langstream)
[Docs](https://rogeriochaves.github.io/langstream/)

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### LiteLLM Proxy
liteLLM Proxy Server: 50+ LLM Models, Error Handling, Caching
[Github](https://github.com/BerriAI/litellm/tree/main/proxy-server)

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🦦 Otter, a multi-modal model based on OpenFlamingo (open-sourced version of DeepMind's Flamingo), trained on MIMIC-IT and showcasing improved instruction-following and in-context learning ability.
[Github](https://github.com/Luodian/Otter)

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Prompt2Model - Generate Deployable Models from Instructions
Github: https://github.com/neulab/prompt2model
Prompt2Model is a system that takes a natural language task description (like the prompts used for LLMs such as ChatGPT) to train a small special-purpose model that is conducive for deployment.

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🧠 Your Second Brain supercharged by Generative AI 🧠 Dump all your files and chat with your personal assistant on your files & more using GPT 3.5/4, Private, Anthropic, VertexAI, LLMs...

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🤖 SalesGPT - Your Context-Aware AI Sales Assistant
Github: https://github.com/filip-michalsky/SalesGPT

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🚀 Evaluate and Evolve.🚀 YiVal is an open source GenAI-Ops framework that allows you to manually or automatically tune and evaluate your AIGC prompts, retrieval configs and fine-tune the model params all at once with your preferred choices of test dataset generation, evaluation algorithms and improvement strategies.
Github: https://github.com/YiVal/YiVal
Docs: https://yival.github.io/YiVal/