RAG & Knowledge
rag.computer
Rag.computer — self-hostable rag platform - document ingestion, embedd, open-source.
★ 100 starsMIT
View guide →All-in-one API platform for search, recommendations, RAG and analytics — self-hostable
trieve is an open-source rag & knowledge project by devflowinc (devflowinc/trieve on GitHub). It has 2,719 GitHub stars and 254 forks, is released under the MIT license, and was last updated on GitHub on 25 January 2026.
Decide between the hosted API for speed or self-hosting for control, and what you'll index — docs, products or content chunks.
Sign up for the hosted API, or clone the repo for self-hosting/local development.
For local dev, install system deps, Rust and Node/Yarn, copy the .env files, set your OPENAI_API_KEY/LLM_API_KEY, and start the Docker services and embedding servers.
Create a dataset, upload chunks, and run a semantic or hybrid search from the dashboard or SDK.
Dense vector search using OpenAI or Jina embeddings stored in Qdrant.
Every chunk is also indexed with a SPLADE sparse-vector model for quality full-text/neural search.
Combine dense and sparse with BAAI/bge-reranker-large cross-encoder reranking; bring your own embedding, SPLADE, reranker or LLM models.
Find similar chunks or grouped files — useful where users favorite, bookmark or upvote content.
RAG endpoints via OpenRouter with topic-based memory management, or bring your own context.
Recency biasing, merchandising signals (clicks, add-to-carts, citations), rich filters, grouping, and sub-sentence highlighting.
Clone Trieve for self-hosting or local development; hosted users can skip to the dashboard.
git clone https://github.com/devflowinc/trieve.git
cd trieveCopy the example env files as the local-development section shows, and set your keys in server/.env.
cp .env.example ./server/.env
# set OPENAI_API_KEY and LLM_API_KEY in ./server/.envBring up the Docker services and the CPU embedding stack, then run the server and frontends per the README.
./convenience.sh -l
docker compose -f docker-compose-cpu-embeddings.yml up -ddevflowinc (the Trieve company) maintains it, with documentation at docs.trieve.ai.
The code is MIT-licensed and self-hostable for free. The hosted service is commercial — the README links a sign-up with 1k chunks free.
RAG and embedding flows use model providers: the local-dev guide sets OPENAI_API_KEY/LLM_API_KEY, and you can bring your own models instead.
SWIRL federates live queries across your existing sources without copying data. Trieve is an indexed search/RAG platform you push chunks into, with recommendations and analytics built in.
Sign up at dashboard.trieve.ai for the hosted API, or follow the README's local-development and self-hosting guides.
Rag.computer — self-hostable rag platform - document ingestion, embedd, open-source.
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