Installation#

Requirements#

  • Python 3.11–3.14. On Python 3.10, pip installs 0.2.0 instead, without an error, and these pages do not describe it.

  • A running AgensGraph 2.17 or later. An older server is refused at connect.

  • The pgvector extension, for the vector store and AgensStore semantic search

Every database call goes through the agensgraph-python 2.0 driver (psycopg 3), which is installed with the package. The integration targets langchain-core 1.x and langgraph 1.x, and has no dependency on the archived langchain-community.

Install#

pip install -U langchain-agensgraph

or through the agensgraph-ai umbrella package, which installs the same thing:

pip install "agensgraph-ai[langchain]"

There is no agensgraph_ai module; either way you import langchain_agensgraph. This documentation covers 0.3.1. 0.3.1 is a documentation release; its code is 0.3.0’s.

The examples that embed text or call an LLM use langchain-openai, which is not a dependency. Install it separately if you want to run them as written:

pip install langchain-openai

Set up pgvector#

AgensGraph does not bundle the pgvector extension. Build and install it against your AgensGraph install’s pg_config:

git clone https://github.com/pgvector/pgvector.git
export PG_CONFIG=/path/to/agens/bin/pg_config
cd pgvector && make && make install

-- in your AgensGraph database, as a superuser:
CREATE EXTENSION IF NOT EXISTS vector;

On a large graph, enabling auto_gather_graphmeta on the database (ALTER DATABASE mydb SET auto_gather_graphmeta = on) makes DETACH DELETE much faster.

Connecting#

AgensGraph, AgensChatMessageHistory, AgensSaver, and AgensStore accept a conf dictionary of psycopg.connect keyword arguments. The last three can instead take an existing AgensGraph as graph=:

conf = {
    "dbname": "mydb",
    "user": "postgres",
    "password": "postgres",
    "host": "localhost",
    "port": 55432,
}

The vector store takes a libpq url instead, such as postgresql://user:password@localhost:55432/mydb, or reads it from the AGENSGRAPH_URL environment variable. It can also be built on an existing AgensGraph (graph=). To share one connection pool between the graph store and several vector stores, create an AgensEngine and pass it as engine=. Pass create=True to have the graph store create the graph if it does not exist. See Usage for full examples.