hanzoai_agent/LLM.md

LLM.md - Hanzo AI Agent SDK

Overview

Python framework for building AI agents and multi-agent systems with orchestration, MCP tools, memory, and observability via Hanzo Cloud.

Architecture

agent/
├── src/hanzoai/agents/    # Core agent SDK (multi-agent, routing, orchestration)
├── sdk/                   # Extended SDK packages
├── control-plane/         # Agent control plane
├── deployments/           # K8s deployment manifests
├── docs/                  # Documentation (MkDocs)
├── examples/              # Usage examples
├── tests/                 # Test suite
└── scripts/               # Dev/build scripts

Tech Stack

• Language: Python 3.9+
• Package: hanzoai on PyPI (v0.0.4)
• Dependencies: openai, pydantic, griffe, requests
• Optional extras: [web3], [tee], [marketplace], [cli]
• Docs: MkDocs
• Build: uv, Makefile

Build & Run

uv sync --all-extras        # Install with all extras
uv run pytest               # Run tests
make dev                    # Development mode
make test                   # Run test suite

Key Concepts

1. Agents: LLMs with instructions, tools, and memory
2. Networks: Multi-agent systems with semantic/rule-based/load-balanced routing
3. Workflows: Orchestrated multi-step processes (parallel, conditional, loop)
4. State & Memory: Shared state + vector search long-term memory
5. Tools: Enhanced tool system with MCP support
6. Tracing: Built-in observability via Hanzo Cloud

Key Files

• pyproject.toml — Package config and dependencies
• src/hanzoai/agents/ — Core agent implementation
• docs/agents.md — Agent documentation
• docs/networks-and-orchestration.md — Multi-agent docs
• examples/ — Working examples

Patterns

• OpenAI Chat Completions API compatible (works with 100+ providers via Hanzo Router)
• Pydantic models for configuration
• Async-first design
• MCP (Model Context Protocol) for tool integration