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20 search results found

Txtai ⭐ 6,143

💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows

Llmware ⭐ 1,859

Providing enterprise-grade LLM-based development framework, tools, and fine-tuned models.

Swirl Search ⭐ 1,371

Swirl is open-source software that uses AI to simultaneously search multiple content and data sources, finds the best results using a reader LLM, then prompts Generative AI, enabling you to get answers from your own data.

The all-in-one LLMOps platform: prompt management, evaluation, human feedback, and deployment all in one place.

Generativeaiexamples ⭐ 458

Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.

Open Source LLM toolkit to build trustworthy LLM applications. TigerArmor (AI safety), TigerRAG (embedding, RAG), TigerTune (fine-tuning)

Llm Paper Daily ⭐ 318

Daily updated LLM papers. 每日更新 LLM 相关的论文，欢迎订阅 👏 喜欢的话动动你的小手 🌟 一个

Llm Search ⭐ 271

Querying local documents, powered by LLM

Start Llms ⭐ 271

A complete guide to start and improve your LLM skills in 2023 with little background in the field and stay up-to-date with the latest news and state-of-the-art techniques!

Txtchat ⭐ 183

💭 Retrieval augmented generation (RAG) and language model powered search applications

Awesome Llm Rag ⭐ 147

Awesome-LLM-RAG: a curated list of advanced retrieval augmented generation (RAG) in Large Language Models

Tonic_validate ⭐ 128

Metrics to evaluate the quality of responses of your Retrieval Augmented Generation (RAG) applications.

Awesome Llm Long Context Modeling ⭐ 115

📰 Must-read papers and blogs on LLM based Long Context Modeling 🔥

Empower Large Language Models (LLM) using Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) for knowledge intensive tasks

Dropbox Ai Chat ⭐ 91

AI-powered Dropbox search tool for private documents

Mistral Haystack ⭐ 79

Mistral + Haystack: build RAG pipelines that rock 🤘

Gpt All Local ⭐ 15

A "chat with your data" example: using a large language models (LLM) to interact with our own (local) data. Everything is local: the embedding model, the LLM, the vector database. This is an example of retrieval-augmented generation (RAG): we find relevant sections from our documents and pass it to the LLM as part of the prompt (see pics).

Build Ragai ⭐ 11

AI-powered Python components and notebooks for leveraging Large Language Models from OpenAI and Hugging Face.

Genai.net ⭐ 6

Implements a framework to build Generative AI applications.

Awesome Llm Rag ⭐ 5

📰🤖 Enhancing Large Language Models with Retrieval Augmented Generation.

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