LangChain is a software framework designed to simplify the integration of large language models (LLMs) into various applications. Its use cases closely align with those of language models in general, such as document analysis and summarization, chatbots, and code analysis.
Langchain-Chatchat(原Langchain-ChatGLM)基于 Langchain 与 ChatGLM, Qwen 与 Llama 等语言模型的 RAG 与 Agent 应用 | Langchain-Chatchat (formerly langchain-ChatGLM), local knowledge based LLM (like ChatGLM, Qwen and Llama) RAG and Agent app with langchain
⛓️ Langflow is a visual framework for building multi-agent and RAG applications
Bisheng is an open LLM devops platform for next generation AI applications
`llm-chain` is a powerful rust crate for building chains in large language models allowing you to summarise text and complete complex tasks
Enhanced ChatGPT Clone: Features OpenAI, Assistants API, Azure, Groq, GPT-4 Vision, Mistral, Bing, Anthropic, OpenRouter, Vertex AI, Gemini, AI model switching, message search, langchain, DALL-E-3, ChatGPT Plugins, OpenAI Functions, Secure Multi-User System, Presets, completely open-source for self-hosting
Openai style api for open large language models, using LLMs just as chatgpt! Support for LLaMA, LLaMA-2, BLOOM, Falcon, Baichuan, Qwen, Xverse, SqlCoder, CodeLLaMA, ChatGLM, ChatGLM2, ChatGLM3 etc
🤖 Everything you need to create an LLM Agent—tools, prompts, frameworks, and models—all in one place
Scripts for fine-tuning Meta Llama3 with composable FSDP & PEFT methods to cover single/multi-node GPUs
This project automates the generation of personalized cold emails by scraping job postings and matching them with a service company’s portfolio using AI
ReadNext is a tool that uses AI to create "Read Next" suggestions for your articles
A web-based application enabling users to interact with and extract insights from YouTube video transcripts and website content
Improved RAG Architecture using semantic chunker, query input rewriter, and prompt engineering
A small interactive game with an LLM that generate (not random ;) ) events and actions that you need to follow in order to win !
Developed a document question answering system that utilizes Llama and LangChain for contextual and accurate answers