RAG・知識ベース
llmware
Unified framework for enterprise RAG pipelines with small, specialized models - local, private and secure.
★ 14.8k スターApache-2.0
ガイドを見る →UltraRAGは、OpenBMBが公開しているオープンソースのRAG・知識ベースプロジェクトです（GitHub: OpenBMB/UltraRAG）。GitHubスターは5,717、フォークは450で、Apache-2.0ライセンスの下で公開されています。GitHubでの最終更新は2026年10月7日です。
A low-code MCP framework for building complex, innovative RAG pipelines — visibly, not as a black box.
Map the retrieval and generation steps you need — corpus processing, retriever, reranking, generation, evaluation.
Clone the repo and sync dependencies with uv, choosing core, full or per-module extras.
Point the pipeline at your embedding and LLM providers (for example OpenAI, Qwen or local vLLM) and prepare your corpus.
Execute a bundled example experiment YAML, then open the UI to inspect each step's output.
Compose retrieval, generation and evaluation steps in a few dozen lines of YAML instead of hand-writing orchestration code.
Built as a low-code MCP framework, so pipeline components interact through the Model Context Protocol.
Designed against black-box development: pipeline logic and intermediate results stay inspectable, including in the web UI.
Install only the modules you need with extras — retriever, generation, or the full stack with corpus processing and evaluation.
Ships multimodal support and example pipelines including a lightweight DeepResearch setup.
Ready Docker images (base CPU, base GPU and full GPU) are published on Docker Hub for a fast start.
Clone UltraRAG (shallow) and enter the directory.
git clone https://github.com/OpenBMB/UltraRAG.git --depth 1
cd UltraRAGCreate the environment with uv; add --all-extras for the full feature set.
uv syncExecute the hello-world experiment to verify the installation end to end.
ultrarag run examples/experiments/sayhello.yamlUltraRAG is maintained by OpenBMB, the team behind MiniCPM and related open models.
Yes — it is open source under the Apache-2.0 license.
It depends on your pipeline: hosted models (OpenAI and similar) need your key, while local models served with vLLM do not.
Those are general application frameworks; UltraRAG specializes in declarative, MCP-based RAG pipelines where every reasoning step remains visible and swappable.
Clone the repo, run uv sync, and execute the sayhello example pipeline.
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