RAG / 向量检索排行

The Odin Tabs extension is a browser extension that allows you to navigate through your browser tabs using speech recognition and the Large Language Model (LLM) of your choice.

A simple RAG chatbot that can retrieve from a mediawiki data dump

An open-source OpenAI wrapper for a RAG-based chatbot that seamlessly integrates with your documents.

GraphRAG over any codebase — a Neo4j knowledge graph of code entities plus a 3072-dim vector index, bridged so one natural-language query walks structure and ranks by meaning. Python · Neo4j · OpenAI embeddings · Streamlit · Docker. Hybrid semantic + structural code search.

Exploring the Basics of Langchain

An open source framework for Retrieval-Augmented System (RAG) uses semantic search helps to retrieve the expected results and generate human readable conversational response with the help of LLM (Large Language Model).

⚠️ DEPRECATED - Use https://github.com/SylphxAI/coderag instead

Memcortex is a lightweight semantic memory layer for LLMs using open source embedding model and Weaviate for vector storage and retrieval.

High-performance, Hardware-First Vector Database engine built in Zig and Go. Sub-millisecond HNSW search with 64-bit metadata filtering and 1.8MB binary footprint.

Chat with Anything 📃

Minimal, async-first Python framework for production LLM apps- 2 hard deps, no magic, no SaaS.

[ACL 2026] CoCoA: Collaborative Chain-of-Agents for Parametric-Retrieved Knowledge Synergy

Locally fine-tuned Russian RAG models: document splitter, query expansion, retrieval embedder. Teacher distillation → GGUF → llama.cpp on AMD Vulkan. Commercial-OK licenses.

RadCrew.org website with LLM-powered chatbot

NewsPulse is AI powered news analytics app for investors

Minimal local-first multimodal RAG library powered by SQLite + sqlite-vec.

Türkçe SQL Server 2025 başucu kitabı — kod örnekleri, errata, topluluk Q&A · CC BY-NC-SA 4.0 + MIT

🤖 AI-powered CLI for file reorganization. Runs fully locally — no data leaves your machine.

Near-optimal vector quantization from Google's ICLR 2026 paper — 95% recall, 5x compression, zero preprocessing, pure Python FAISS replacement

IA na Prática: LLM, RAG, MCP, Agents, Function Calling, Multimodal, TTS/STT e mais