langchain-graph-retriever
LangChain retriever for traversing document graphs on top of vector-based similarity search.
Decision gist · record as of 2026-08-14
Yes, if you need graph-aware document retrieval in a LangChain application and are comfortable with a Beta-status library that has not been actively developed for several months. The package has low install friction, permissive licensing, and no known vulnerabilities. However, verify that the graph traversal strategies and vector store adapters you need are production-ready before deploying to critical systems.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; also requires a configured vector store (e.g., Chroma) and an embedding function.
- Low install friction with a pure-Python wheel.
- Maintenance status is aging—last commit was 2025-05-05 and the package is 497 days past its initial release, though the repository remains active and not archived.
License · maintenance · safety
Apache-2.0 (permissive) — Licensed under Apache-2.0 (permissive), allowing commercial use, modification, and distribution with minimal restrictions beyond attribution and liability disclaimers.
last release 2025-04-04 (497 days) · last repo commit 2025-05-05 · 91 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 186,653 downloads/mo, #9,979 on PyPI
Alternatives
Verify before relying
pip install langchain-graph-retriever
from langchain_graph_retriever import GraphRetriever
from langchain_core.vectorstores import Chroma
vector_store = Chroma(embedding_function=your_embedding_function)
retriever = GraphRetriever(store=vector_store, edges=[("keywords", "keywords")])
documents = retriever.retrieve("What is the capital of France?")- Whether graph traversal strategies (Eager, MMR) are fully documented and production-ready.
- Performance characteristics when working with large document graphs.
- Support status for the listed vector store adapters (AstraDB, Cassandra, Chroma, OpenSearch).
What it is and what it does
LangChain Graph Retriever extends LangChain's retriever framework by combining vector-based similarity search with graph traversal. Instead of treating documents as isolated results, it models them as nodes in a graph and explores relationships between them using strategies like breadth-first search or Maximal Marginal Relevance. This is useful for retrieval-augmented generation (RAG) systems where document relationships matter—for example, retrieving not just the most similar document but also semantically related neighbors.
The package depends on LangChain's core abstractions (langchain-core), graph utilities (networkx), and standard Python libraries (pydantic, immutabledict, typing-extensions). It supports both synchronous and asynchronous retrieval workflows and integrates with multiple vector stores. The codebase is in Beta status and has not seen active development recently, though the repository remains maintained.
Use it for
- Build RAG pipelines that retrieve semantically related document clusters instead of isolated top-k results.
- Explore document relationships in knowledge graphs where metadata edges define connections between records.
- Implement graph-aware search in applications like research paper discovery or knowledge base navigation.
- Combine vector similarity with graph structure to improve retrieval relevance in multi-hop reasoning tasks.
- Integrate graph traversal into LangChain agents that need to explore connected document sets.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need graph-aware document retrieval in a LangChain application and are comfortable with a Beta-status library that has not been actively developed for several months.
The package has low install friction, permissive licensing, and no known vulnerabilities. However, verify that the graph traversal strategies and vector store adapters you need are production-ready before deploying to critical systems.
Install
langchain-graph-retriever on PyPI
Before you install
Low install friction with a pure-Python wheel. Maintenance status is aging—last commit was 2025-05-05 and the package is 497 days past its initial release, though the repository remains active and not archived.
Requires Python 3.10 or later; also requires a configured vector store (e.g., Chroma) and an embedding function.
License in practice
Licensed under Apache-2.0 (permissive), allowing commercial use, modification, and distribution with minimal restrictions beyond attribution and liability disclaimers.
Quickstart
pip install langchain-graph-retriever
from langchain_graph_retriever import GraphRetriever
from langchain_core.vectorstores import Chroma
vector_store = Chroma(embedding_function=your_embedding_function)
retriever = GraphRetriever(store=vector_store, edges=[("keywords", "keywords")])
documents = retriever.retrieve("What is the capital of France?")Verify before relying
- Whether graph traversal strategies (Eager, MMR) are fully documented and production-ready.
- Performance characteristics when working with large document graphs.
- Support status for the listed vector store adapters (AstraDB, Cassandra, Chroma, OpenSearch).
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 7 packagesbackoffgraph-retrieverimmutabledictlangchain-corenetworkxpydantictyping-extensions |
| Maintenance | Aging 497 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 186,653 / month, #9,979 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Topic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Scientific/Engineering :: Information AnalysisTopic :: Software Development :: Libraries :: Python Modules |
Evidence: langchain_graph_retriever-0.8.0-py3-none-any.whl
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See also deepsearch-glm · graph-retriever · ragstack-ai-knowledge-store · langchain-plaid · langchain-milvus · langchain-chroma · langchain-mongodb · langchain-oracledb · lightrag-hku · kuzu