Graphmind Context Graphs — Python SDK
A "Director's Commentary" middleware for LangChain Python agents. Captures why agents make decisions, not just what they did.
Installation
pip install graphmind-context-graphs
Prerequisites
# Graphmind database
docker run -d --name graphmind -p 8080:8080 fabischk/graphmind:latest
# LangChain + provider
pip install langchain langchain-core langgraph langchain-openai
Quick Start
from langchain.agents import create_agent
from graphmind_context_graphs import (
create_context_graph,
ContextGraphConfig,
EmbeddingConfig,
)
# Your embedding provider (must implement embed, embed_batch, dimensions)
embedding_provider = MyEmbeddingProvider()
# Initialize
cg = create_context_graph(ContextGraphConfig(
tenant="my_company",
project="support",
agent="support-agent",
embedding=EmbeddingConfig(provider=embedding_provider, dimensions=1536),
observer_model="openai:gpt-4.1-mini", # Optional: for LLM-powered extraction
))
# Create agent with middleware + brain-mapping tools
agent = create_agent(
"openai:gpt-4.1",
tools=[*my_tools, *cg.tools],
middleware=cg.middleware,
)
# Use — context captured and injected automatically
result = agent.invoke({"messages": [{"role": "user", "content": "My account is locked"}]})
# Evolve knowledge
cg.lifecycle.validate_trace(trace_id, ValidationResult(trace_id=trace_id, success=True))
cg.lifecycle.synthesize_rules()
Features
- Decision Trace Capture — Intent/Constraint/Action/Justification triplets
- Dynamic Brain Mapping — Agents create entities (CodeFile, Contract, etc.) and relationships
- Schema Awareness — Agent-scoped; only domain entities shown
- LLM-Powered Extraction — Observer model extracts domain, concepts, constraints
- Knowledge Lifecycle — Capture → Validate → Synthesize → Prune
- Multi-Agent — Shared, isolated, or selective context sharing
- Vector Search — Semantic similarity via Graphmind SEARCH clause
API Mirror
This SDK mirrors the TypeScript SDK. Both use the same Graphmind database and Cypher queries. Agents running in different languages can share context graphs.
| TypeScript | Python |
|---|---|
createContextGraph() |
create_context_graph() |
cg.middleware |
cg.middleware |
cg.tools |
cg.tools |
cg.lifecycle.validateTrace() |
cg.lifecycle.validate_trace() |
cg.store.getSchemaOverview() |
cg.store.get_schema_overview() |
License
Apache License 2.0
Metadata
Release files for graphmind-context-graphs 0.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| graphmind_context_graphs-0.2.0.tar.gz | 198.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| graphmind_context_graphs-0.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 230.9 kB
Release files / graphmind_context_graphs-0.2.0.tar.gz
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