Trieve README
The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Trieve listing page.
Sign Up (1k chunks free) | PDF2MD | Hacker News Search Engine | Documentation | Meet a Maintainer | Discord | Matrix
All-in-one solution for search, recommendations, and RAG
Quick Links
Features
- 🔒 Self-Hosting in your VPC or on-prem: We have full self-hosting guides for AWS, GCP, Kubernetes generally, and docker compose available on our documentation page here.
- 🧠 Semantic Dense Vector Search: Integrates with OpenAI or Jina embedding models and Qdrant to provide semantic vector search.
- 🔍 Typo Tolerant Full-Text/Neural Search: Every uploaded chunk is vector'ized with naver/efficient-splade-VI-BT-large-query for typo tolerant, quality neural sparse-vector search.
- 🖊️ Sub-Sentence Highlighting: Highlight the matching words or sentences within a chunk and bold them on search to enhance UX for your users. Shout out to the simsearch crate!
- 🌟 Recommendations: Find similar chunks (or files if using grouping) with the recommendation API. Very helpful if you have a platform where users' favorite, bookmark, or upvote content.
- 🤖 Convenient RAG API Routes: We integrate with OpenRouter to provide you with access to any LLM you would like for RAG. Try our routes for fully-managed RAG with topic-based memory management or select your own context RAG.
- 💼 Bring Your Own Models: If you'd like, you can bring your own text-embedding, SPLADE, cross-encoder re-ranking, and/or large-language model (LLM) and plug it into our infrastructure.
- 🔄 Hybrid Search with cross-encoder re-ranking: For the best results, use hybrid search with BAAI/bge-reranker-large re-rank optimization.
- 📆 Recency Biasing: Easily bias search results for what was most recent to prevent staleness
- 🛠️ Tunable Merchandizing: Adjust relevance using signals like clicks, add-to-carts, or citations
- 🕳️ Filtering: Date-range, substring match, tag, numeric, and other filter types are supported.
- 👥 Grouping: Mark multiple chunks as being part of the same file and search on the file-level such that the same top-level result never appears twice
Are we missing a feature that your use case would need? - call us at 628-222-4090, make a Github issue, or join the Matrix community and tell us! We are a small company who is still very hands-on and eager to build what you need; professional services are available.
Local Development
Installing via Smithery
To install Trieve for Claude Desktop automatically via Smithery:
System Dependencies
Linux (Debian/Ubuntu)
Linux (Arch)
MacOS
Install NodeJS and Yarn
You can install NVM using its install script.
You should restart the terminal to update bash profile with NVM. Then, you can install NodeJS LTS release and Yarn.
Make server tmp dir
Install rust
Install cargo-watch
Setup env's
You might need to create the analytics directory in ./frontends
Add your LLM_API_KEY to ./server/.env
Here is a guide for acquiring that.
Steps once you have the key
- Open the
./server/.envfile - Replace the value for
LLM_API_KEYto be your own OpenAI API key. - Replace the value for
OPENAI_API_KEYto be your own OpenAI API key.
Override the following keys in your terminal for local dev
The PAGEFIND_CDN_BASE_URL and S3_SECRET_KEY_CSVJSONL can be set to a random list of strings.
Start docker container services needed for local dev
Start embedding servers
We offer 2 docker-compose files for embedding servers. One for GPU and one for CPU.
or
- Note on embedding servers. If you want to use a separate GPU enabled device for embedding servers you will need to update the following parameters
Using CPU embeddings on MacOS
Install front-end packages for local dev
cd ..
cd ../..
Start services for local dev
It is recommend to manage services through tmuxp, see the guide here or terminal tabs.
Verify Working Setup
After the cargo build has finished (after the tmuxp load trieve):
- check that you can see redoc with the OpenAPI reference at localhost:8090/redoc
- make an account create a dataset with test data at localhost:5173
- search that dataset with test data at localhost:5174
Additional Instructions for testing cross encoder reranking models
To test the Cross Encoder rerankers in local dev,
- click on the dataset, go to the Dataset Settings -> Dataset Options -> Additional Options and uncheck the
Fulltext Enabledoption. - in the Embedding Settings, select your reranker model and enter the respective key in the adjacent textbox, and hit save.
- in the search playground, set Type -> Semantic and select Rerank By -> Cross Encoder
- if AIMon Reranker is selected in the Embedding Settings, you can enter an optional Task Definition in the search playground to specify the domain of context documents to the AIMon reranker.
Debugging issues with local dev
Reach out to us on discord for assistance. We are available and more than happy to assist.
Debug diesel by getting the exact generated SQL
diesel::debug_query(&query).to_string();
Running evals
The evals package loads an mcp client that then runs the index.ts file, so there is no need to rebuild between tests. You can load environment variables by prefixing the npx command. Full documentation can be found here.
Local Setup for Testing Stripe Features
Install Stripe CLI.
stripe loginstripe listen --forward-to localhost:8090/api/stripe/webhook- set the
STRIPE_WEBHOOK_SECRETin theserver/.envto the resulting webhook signing secret stripe products create --name trieve --default-price-data.unit-amount 1200 --default-price-data.currency usdstripe plans create --amount=1200 --currency=usd --interval=month --product={id from response of step 3}