All-in-one infrastructure for building search, recommendations, and RAG. Trieve combines search language models with tools for tuning ranking and relevance.
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Updated
Jul 9, 2024 - Rust
All-in-one infrastructure for building search, recommendations, and RAG. Trieve combines search language models with tools for tuning ranking and relevance.
Naive RAG implementations using LangChain + llama-index + OpenAI + GradientAI + Sentence_Transformer + Nomic AI + FAISS and more
AWS Generative AI CDK Constructs are sample implementations of AWS CDK for common generative AI patterns.
Penetration Testing AI Agent Assistant
What I learn about RAG, i use Langchain and maybe Llama-Index
Redis Vector Library (RedisVL) interfaces with Redis' vector database for realtime semantic search, RAG, and recommendation systems.
RAG based Q&A system using Pinecone, OpenAI, Langchain
Dynamic RAG for enterprise. Ready to run with Docker,⚡in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.
Langchain-Chatchat(原Langchain-ChatGLM, Qwen 与 Llama 等)基于 Langchain 与 ChatGLM 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
The AI-native database built for LLM applications, providing incredibly fast full-text and vector search
Build your own serverless AI Chat with Retrieval-Augmented-Generation using LangChain.js, TypeScript and Azure
Harness LLMs with Multi-Agent Programming
Experience the power of Clarifai’s AI platform with the python SDK. 🌟 Star to support our work!
⚡FlashRAG: A Python Toolkit for Efficient RAG Research
🔍 LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
A compute framework for turning complex data into vectors. Build multimodal vectors with ease and define weights at query time so you don't need a custom reranking algorithm to optimise results. Go straight from notebook to production with the same SDK.
Campus 360 is an AI-powered chatbot designed to assist students, faculty, and visitors at the Model Institute of Engineering & Technology (MIET).
Distributed vector search for AI-native applications
Fast, Accurate, Lightweight Python library to make State of the Art Embedding
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
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