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agentmatrix-core

Let LLMs think. Don't make them write JSON.

A Python execution engine for building AI agent applications. Separates reasoning from formatting: the large model thinks in natural language, a dedicated module handles the structured output.


What It Is

agentmatrix-core provides the execution engine behind AgentMatrix. It includes:

  • MicroAgent — A task execution engine with think-negotiate-act loop
  • AgentShell Protocol — Clean boundary between execution and I/O
  • Cerebellum — Intent parsing and parameter negotiation
  • Action System — Pluggable skill registry and execution
  • SessionStore — Conversation persistence
  • Auto-Compression — Working Notes for arbitrarily long tasks
  • Signal System — Event-driven communication

The core knows nothing about desktop apps, file systems, or networks. All external interaction goes through the AgentShell protocol, which you implement for your target environment.


Install

pip install agentmatrix-core

Requires Python 3.12+.


Quick Example

from agentmatrix import AgentMatrix, Email

# Create the runtime
matrix = AgentMatrix("./MatrixWorld")

# Send an email to an agent
email = Email(
    sender="User",
    recipient="Researcher",
    subject="Search for Python 3.13 features",
    body="Find and summarize the major new features in Python 3.13"
)

# Dispatch via PostOffice
await matrix.post_office.dispatch(email)

For a complete minimal example implementing AgentShell, see the CLI tutorial in the repository.


Architecture

┌─────────────────────────────────────────────┐
│  Your App (Desktop / CLI / Server)          │
├─────────────────────────────────────────────┤
│  AgentShell Protocol (you implement this)   │
├─────────────────────────────────────────────┤
│  MicroAgent Engine (this package)           │
│  - Brain (reasoning in natural language)    │
│  - Cerebellum (intent → action params)      │
│  - Action Registry                          │
│  - SessionStore                             │
└─────────────────────────────────────────────┘

Key Design

  • No JSON output required — Brain reasons in plain text
  • Dynamic skill composition — Mixins assembled at runtime per task
  • Checkpoint-based pause/resume — Cooperative, not forced interruption
  • Auto context compression — LLM-generated Working Notes prevent overflow
  • Nested MicroAgents — Tasks can spawn sub-tasks with different skill sets

Documentation


License

Apache License 2.0

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