LangChain integration for NextPlaid multi-vector search
Project description
🦜️🔗 LangChain NextPlaid
This repository contains 1 package with NextPlaid integrations with LangChain:
- langchain-plaid (WIP)
Overview
NextPlaid is a high-performance ColBERT-style multi-vector search engine built in Rust.
This package provides a LangChain VectorStore integration, enabling late-interaction
retrieval with full metadata filtering support.
Installation
pip install langchain-plaid
Usage
from langchain_plaid import NextPlaidVectorStore
vectorstore = NextPlaidVectorStore(
url="http://localhost:8080",
index_name="my_index",
embedding=your_embedding_model,
)
# Add documents
vectorstore.add_documents(documents)
# Similarity search
results = vectorstore.similarity_search("query", k=4)
# Similarity search with metadata filter
results = vectorstore.similarity_search(
"query",
k=4,
filter={"category": "science"},
)
Running the NextPlaid Server
cargo run --release -p next-plaid-api -- --index-dir /tmp/indices --port 8080
See the next-plaid repository for full server documentation.
Development
# Install dependencies
cd libs/plaid
pip install -e ".[dev]"
# Run integration tests (requires a running NextPlaid server)
python -m pytest tests/integration_tests/
Project details
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