LangChain ArangoDB
LangChain ArangoDB is a Python package that provides ArangoDB integrations for LangChain, enabling vector storage, graph operations, and chat message history management.
Key Features
LangChain ArangoDB provides comprehensive integrations for building AI applications:
- Vector Operations
High-performance vector similarity search
Support for multiple distance metrics (cosine, Euclidean)
Approximate and exact nearest neighbor search
Maximal marginal relevance (MMR) search for diverse results
- Graph Operations
Knowledge graph construction and querying
Graph-based question answering chains
Integration with LangChain’s graph interfaces
- Chat Memory
Persistent chat message history storage
Session-based conversation management
Efficient message retrieval and filtering
- Query Construction
AQL (ArangoDB Query Language) integration
Structured query generation from natural language
Requirements
Python 3.9+
LangChain
ArangoDB
python-arango
Installation
Latest Release
pip install langchain-arangodb
Current Development State
pip install git+https://github.com/arangodb/langchain-arangodb
Quick Start
from arango import ArangoClient
from langchain_openai import OpenAIEmbeddings
from langchain_arangodb.vectorstores import ArangoVector
# Connect to ArangoDB
client = ArangoClient("http://localhost:8529")
db = client.db("langchain", username="root", password="openSesame")
# Create vector store
vectorstore = ArangoVector.from_texts(
texts=["Hello world", "LangChain with ArangoDB"],
embedding=OpenAIEmbeddings(),
database=db
)
# Search
results = vectorstore.similarity_search("greeting", k=1)
Documentation Contents