deepagents-graph-memory
Give your agent a record of what it tried and what worked.
For developers building LangChain Deep Agents that handle long-running tasks and need to remember a lot of context. The graph connects attempts, evidence, and results so agents can find earlier work before deciding what to do next.
Works alongside the virtual filesystem (VFS): files hold code, logs, and tool dumps; the graph links findings to their evidence. For example: failing test → suspected cause → code change → test result.
Inspired by Niels de Jong's Neo4j article, From recall to reasoning: How context graphs upgrade an agent’s brain. Built by Pranav Bedi and Taha Khan, using LadybugDB. Experimental.
Install
pip install --upgrade deepagents-graph-memory
Requires Python 3.11–3.14 on a supported platform. The graph database, OpenSSL, and search extension come bundled. No database server or separate search setup. Intel Macs have an upstream dependency build requirement; see the platform details above.
Quick start
Set your model provider's API key, then add the graph tools and guidance to your agent:
from deepagents import create_deep_agent
from deepagents_graph_memory import (
GraphMemoryBackend,
graph_context_middleware,
graph_memory_tools,
)
graph = GraphMemoryBackend.create()
agent = create_deep_agent(
model="google_genai:gemini-3.5-flash",
tools=graph_memory_tools(graph),
middleware=[graph_context_middleware()],
)
# Use agent.invoke(...) in your application.
# Close the graph after the agent and all its workers finish:
# graph.close()
Storage options
GraphMemoryBackend.create() keeps the graph temporarily while the backend is
open. Use GraphMemoryBackend.create(path="project.lbdb") to keep it on a
persistent disk across runs.
The full guide covers deployment, shared agents, graph-only mode, and debugging. Agents choose what to record; the graph doesn't automatically verify their claims.
1 maintainer
Metadata
1 maintainer
Release files for deepagents-graph-memory 0.1.6
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5ee81d8160dcd6c100950c9a98c52d3d41c1cc647eae6b0225973e72d21f1525
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twine/7.0.0 CPython/3.13.14
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Transparency logRelease files / deepagents_graph_memory-0.1.6-cp311-cp311-macosx_15_0_arm64.whl
| Download URL | deepagents_graph_memory-0.1.6-cp311-cp311-macosx_15_0_arm64.whl |
|---|---|
| Size | 7.9 MB |
| Tags | CPython 3.11 macOS 15.0+ ARM64 |
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SHA-256 checksum How to use checksums |
c83e2986c03eb2f254fc15ea699a27b6ccb534a0d1d87e6ff6a4b076503ec1a5
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BLAKE2b-256 checksum How to use checksums |
1fdcf1557574394f934670578a53bf1d90c3fb037911951acc61bbc089785b0b
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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Provenance
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PyPI Publish Attestation
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