RAG и системы знаний
hkuds/lightrag
A lightweight, graph-based retrieval-augmented generation (RAG) framework that uses a dual-layer architecture combining knowledge graphs and vector embeddings to deliver efficient indexing, low-cost incremental updates, and high-quality contextual retrieval.
★ 38,4K⑂ 5,4KPython
MITQ98
Агенты и мультиагенты
run-llama/llama_index
LlamaIndex is an open-source Python data framework for building LLM applications with private data, offering data connectors, indexing structures, and advanced retrieval interfaces. It is complemented by LlamaParse, an enterprise platform for agentic OCR, parsing, extraction, and indexing.
★ 51,4K⑂ 7,9KPython
MITQ98
MCP и вызов инструментов
headroomlabs-ai/headroom
Headroom is a local-first context compression layer that reduces token usage for AI agents by compressing tool outputs, logs, files, and RAG chunks before they reach the LLM. It offers library, proxy, and MCP server modes and claims to preserve answer accuracy while cutting tokens by 15-95% depending on workload.
★ 65K⑂ 4,9KPython
Apache-2.0Q98
MCP и вызов инструментов
graphify-labs/graphify
Graphify is a local-first CLI tool and AI assistant skill that parses codebases, docs, SQL schemas, and PDFs into a queryable knowledge graph using deterministic AST parsing, eliminating the need for vector stores or embeddings.
★ 104K⑂ 10,1KPython
Apache-2.0Q98
Агенты и мультиагенты
vectifyai/pageindex
PageIndex is a Python project for creating hierarchical document indexes and performing reasoning-based retrieval without a vector database or artificial chunking. It supports self-hosted processing of PDF and Markdown documents, with optional agentic RAG examples and hosted MCP/API services.
★ 35K⑂ 3,1KPython
MITQ98
Агенты и мультиагенты
infiniflow/ragflow
RAGFlow is an open-source Retrieval-Augmented Generation engine that combines document ingestion, retrieval, grounded citations, configurable language and embedding models, and agent capabilities to provide context for LLM applications.
★ 86,7K⑂ 10,2KGo
Apache-2.0Q98
Агенты и мультиагенты
comet-ml/opik
Opik is an Apache-2.0-licensed platform for tracing, evaluating, debugging and monitoring LLM applications, RAG systems and multi-step agent workflows. It supports self-hosting, a hosted Comet.com option, client SDKs, a REST API, automated evaluations, prompt experimentation and production dashboards.
★ 21,1K⑂ 1,7KPython
Apache-2.0Q98
MCP и вызов инструментов
juspay/neurolink
A TypeScript integration platform providing a unified API for 30+ AI providers and 100+ models, enabling provider swapping, multi-modal voice processing, RAG, memory, and MCP-native tool integration.
★ 121⑂ 124TypeScript
MITQ93
Агенты и мультиагенты
pwrdrvr/pwragent
An open-source desktop coding agent that runs locally on a laptop and can be driven remotely via messaging platforms like Telegram, Discord, Slack, Mattermost, Feishu, Lark, or LINE.
★ 29⑂ 4TypeScript
MITQ86
MCP и вызов инструментов
mtrnix/metronix-memory
Self-hosted memory infrastructure for AI agents featuring MCP-native integration, hybrid RAG, a temporal knowledge graph, and an ontology layer, designed for local-model friendliness and durable, agent-scoped context.
★ 39⑂ 7Python
Apache-2.0Q86
Агенты и мультиагенты
xerj-org/xerj
XERJ is a search engine for AI agents that automatically indexes code, documents, logs, and PDFs, enabling agents to query data rather than reading entire files into their context windows. It is Elasticsearch-compatible, allowing existing clients and tooling to work unchanged.
★ 1,4K⑂ 288Rust
Apache-2.0Q87
RAG и системы знаний
infino-ai/infino
Infino is a fast retrieval engine that executes SQL, full-text search, and vector search over a single copy of data stored natively as Parquet on object storage.
★ 67⑂ 18Rust
Apache-2.0Q89