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Python client for the MindGraph Cloud API

Project description

mindgraph

PyPI License: MIT

Python client for the MindGraph Cloud API — a structured semantic memory graph for AI agents.

Install

pip install mindgraph

Quick Start

from mindgraph import MindGraph

with MindGraph("https://api.mindgraph.cloud", api_key="mg_...") as graph:
    # Add a node
    node = graph.add_node(
        label="User prefers dark mode",
        node_type="Preference",
    )

    # Search
    results = graph.search("what does the user prefer?")

    # Connect knowledge
    graph.add_link(
        from_uid=node["uid"],
        to_uid="user_abc",
        edge_type="BelongsTo",
    )

API Reference

Constructor

MindGraph(base_url, *, api_key=None, jwt=None, timeout=30.0)

Supports context manager protocol (with statement) for automatic cleanup.

Reality Layer

Method Description
ingest(**kwargs) Ingest a source, snippet, or observation
entity(**kwargs) Create, alias, resolve, or merge entities
find_or_create_entity(label, entity_type?, agent_id?) Convenience: create or find an entity by label

Epistemic Layer

Method Description
argue(**kwargs) Construct a full argument: claim + evidence + warrant + edges
inquire(**kwargs) Add hypothesis, theory, paradigm, anomaly, assumption, or question
structure(**kwargs) Add concept, pattern, mechanism, model, analogy, theorem, etc.

Intent Layer

Method Description
commit(**kwargs) Create a goal, project, or milestone
deliberate(**kwargs) Open decisions, add options/constraints, resolve decisions

Action Layer

Method Description
procedure(**kwargs) Build flows, add steps, affordances, and controls
risk(**kwargs) Assess risk or retrieve existing assessments

Memory Layer

Method Description
session(**kwargs) Open a session, record traces, or close a session
distill(**kwargs) Create a summary that distills multiple source nodes
memory_config(**kwargs) Set/get preferences and memory policies

Agent Layer

Method Description
plan(**kwargs) Create tasks, plans, plan steps, update status
governance(**kwargs) Create policies, set safety budgets, request/resolve approvals
execution(**kwargs) Track execution lifecycle and register agents

CRUD

Method Description
get_node(uid) Get a node by UID
add_node(label, node_type?, props?, agent_id?) Add a generic node
update_node(uid, **kwargs) Update node fields
delete_node(uid) Tombstone a node and all connected edges
add_link(from_uid, to_uid, edge_type, agent_id?) Add a typed edge
get_edges(from_uid?, to_uid?) Get edges by source or target

Search

Method Description
search(query, node_type?, layer?, limit?) Full-text search
hybrid_search(query, k?, node_types?, layer?) BM25 + vector search with rank fusion

Traversal

Method Description
reasoning_chain(uid, max_depth=5) Follow epistemic edges from a node
neighborhood(uid, max_depth=1) Get all nodes within N hops

Cross-cutting

Method Description
retrieve(**kwargs) Unified retrieval: text search, active goals, open questions, weak claims
traverse(**kwargs) Graph traversal: chain, neighborhood, path, or subgraph
evolve(**kwargs) Lifecycle mutations: update, tombstone, restore, decay, history

Health & Stats

Method Description
health() Health check
stats() Graph-wide statistics

Error Handling

All methods raise MindGraphError on HTTP errors:

from mindgraph import MindGraphError

try:
    graph.get_node("nonexistent")
except MindGraphError as e:
    print(e.status, e.body)

License

MIT

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