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56 lines
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56 lines
6.6 KiB
Markdown
# LLM Frameworks
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The following is a collection of different LLM frameworks in alphabetical order:
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- [Agent-LLM](https://github.com/Josh-XT/Agent-LLM): An Artificial Intelligence Automation Platform.
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- [AgentFlow](https://github.com/simonmesmith/agentflow): About Complex LLM Workflows from Simple JSON.
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- [AgentVerse](https://github.com/openbmb/agentverse) Provides a flexible framework that simplifies the process of building custom multi-agent environments for LLMs
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- [AI Utils](https://github.com/lgrammel/ai-utils.js): TypeScript-first library for building AI apps, chatbots, and agents.
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- [AI.JSX](https://github.com/fixie-ai/ai-jsx): The AI Application Framework for Javascript
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- [Autochain](https://github.com/Forethought-Technologies/AutoChain): Build lightweight, extensible, and testable LLM Agents with AutoChain.
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- [Autogen](https://github.com/microsoft/autogen): Enable Next-Gen Large Language Model Applications.
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- [Ax](https://github.com/axilla-io/ax): A comprehensive AI framework for TypeScript
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- [Botpress](https://github.com/botpress/botpress): The building blocks for building chatbots
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- [Dust](https://github.com/dust-tt/dust): Design and Deploy Large Language Model Apps
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- [e2b](https://github.com/e2b-dev/e2b): Open-source platform for building & deploying virtual developers’ agents
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- [Embedbase](https://github.com/different-ai/embedbase): The native Software 3.0 stack for building AI-powered applications.
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- [FlagAI](https://github.com/FlagAI-Open/FlagAI): FlagAI (Fast LArge-scale General AI models) is a fast, easy-to-use and extensible toolkit for large-scale model.
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- [Flappy](https://github.com/pleisto/flappy): Production-Ready LLM Agent SDK for Every Developer
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- [Griptape](https://github.com/griptape-ai/griptape): Python framework for AI workflows and pipelines with chain of thought reasoning, external tools, and memory.
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- [Haystack](https://github.com/deepset-ai/haystack): NLP framework to interact with your data using Transformer models and LLMs
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- [Hyv](https://github.com/failfa-st/hyv): Probably the easiest way to use any AI Model in Node.js and create complex interactions with ease.
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- [Lagent](https://github.com/InternLM/lagent): A lightweight framework for building LLM-based agents
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- [LangStream](https://github.com/LangStream/langstream): Framework for building and running event-driven LLM applications using no-code and Python (including LangChain-based) agents.
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- [LlamaIndex](https://github.com/jerryjliu/llama_index): provides a central interface to connect your LLM's with external data.
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- [LLFn](https://github.com/orgexyz/LLFn): A light-weight framework for creating applications using LLMs
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- [LLM Agents](https://github.com/mpaepper/llm_agents): Build agents which are controlled by LLMs
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- [llm-chain](https://github.com/sobelio/llm-chain): is a powerful rust crate for building chains in LLMs allowing you to summarise text and complete complex tasks.
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- [LLMFlow](https://github.com/stoyan-stoyanov/llmflows): Simple, Explicit and Transparent LLM Apps
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- [LLMStack](https://github.com/trypromptly/LLMStack): No code platform for building LLM-powered applications with custom data.
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- [LMQL](https://github.com/eth-sri/lmql): A programming language for large language models.
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- [Magentic](https://github.com/jackmpcollins/magentic): Seamlessly integrate LLMs as Python functions
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- [Marvin](https://github.com/PrefectHQ/marvin): ✨ Build AI interfaces that spark joy
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- [MemGPT](https://github.com/cpacker/MemGPT): Teaching LLMs memory management for unbounded context
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- [MetaGPT](https://github.com/geekan/MetaGPT): The Multi-Agent Meta Programming Framework: Given one line Requirement, return PRD, Design, Tasks, Repo and CI
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- [MiniChain](https://github.com/srush/MiniChain): A tiny library for coding with large language models.
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- [OpenDAN](https://github.com/fiatrete/OpenDAN-Personal-AI-OS): open source Personal AI OS , which consolidates various AI modules in one place for your personal use.
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- [OpenLLM](https://github.com/bentoml/OpenLLM): An open platform for operating large language models (LLMs) in production. Fine-tune, serve, deploy, and monitor any LLMs with ease using OpenLLM.
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- [OpenLM](https://github.com/r2d4/openlm): a drop-in OpenAI-compatible library that can call LLMs from any other hosted inference API. Also [Typescript](https://github.com/r2d4/llm.ts)
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- [Outlines](https://github.com/normal-computing/outlines): Fast and reliable neural text generation.
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- [Outlines](https://github.com/normal-computing/outlines): Generative Model Programming (Python)
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- [PromptFlow](https://github.com/InsuranceToolkits/promptflow): Create executable flowcharts that link LLMs (Large Language Models), Prompts, Python functions, and conditional logic together.
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- [Promptfoo](https://github.com/promptfoo/promptfoo): Test your prompts. Evaluate and compare LLM outputs, catch regressions, and improve prompt quality.
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- [Promptify](https://github.com/promptslab/Promptify): Prompt Engineering | Use GPT or other prompt based models to get structured output.
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- [PromptSource](https://github.com/bigscience-workshop/promptsource): About Toolkit for creating, sharing and using natural language prompts.
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- [ReLLM](https://github.com/r2d4/rellm): Regular Expressions for Language Model Completions.
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- [RestGPT](https://github.com/Yifan-Song793/RestGPT): An LLM-based autonomous agent controlling real-world applications via RESTful APIs
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- [Rivet](https://github.com/Ironclad/rivet): An IDE for creating complex AI agents and prompt chaining, and embedding it in your application.
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- [Semantic Kernel](https://github.com/microsoft/semantic-kernel): Microsoft C# SDK to integrate cutting-edge LLM technology quickly and easily into your apps
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- [SimpleAIChat](https://github.com/minimaxir/simpleaichat): Python package for easily interfacing with chat apps, with robust features and minimal code complexity.
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- [SmartGPT](https://github.com/Cormanz/smartgpt): A program that provides LLMs with the ability to complete complex tasks using plugins.
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- [SuperAGI](https://github.com/TransformerOptimus/SuperAGI): A dev-first open source autonomous AI agent framework.
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- [TermGPT](https://github.com/Sentdex/TermGPT): Giving LLMs like GPT-4 the ability to plan and execute terminal commands
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- [TextAI](https://github.com/neuml/txtai): 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows.
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- [Transformers Agents](https://huggingface.co/docs/transformers/transformers_agents): Provides a natural language API on top of transformers
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- [TypeChat](https://github.com/microsoft/TypeChat): TypeChat is a library that makes it easy to build natural language interfaces using types.
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