autogen-pathcourse 0.1.0

AutoGen / AG2 integration for PathCourse Health — multi-agent inference with autonomous USDC billing on Base L2

autogen-pathcourse

AutoGen / AG2 integration for PathCourse Health. Run multi-agent conversations with autonomous USDC billing on Base L2 — no accounts, no credit cards, no KYC.

Install

# AutoGen (legacy package name)
pip install autogen-pathcourse pyautogen

# AG2 (the new fork)
pip install autogen-pathcourse ag2

Quick Start

from autogen import AssistantAgent, UserProxyAgent
from autogen_pathcourse import pch_config

config_list = pch_config(model="pch-pro")
llm_config = {"config_list": config_list, "temperature": 0.7}

assistant = AssistantAgent(
    name="assistant",
    llm_config=llm_config,
    system_message="You are a helpful AI assistant.",
)

user_proxy = UserProxyAgent(
    name="user_proxy",
    human_input_mode="NEVER",
    max_consecutive_auto_reply=3,
    code_execution_config=False,
)

user_proxy.initiate_chat(assistant, message="Explain x402 in two sentences.")

Mixed-model multi-agent setup

Use different PCH models for different agents in the same conversation:

from autogen import AssistantAgent
from autogen_pathcourse import pch_config

planner = AssistantAgent(
    name="planner",
    llm_config={"config_list": pch_config(model="pch-pro")},
    system_message="You plan multi-step research.",
)

coder = AssistantAgent(
    name="coder",
    llm_config={"config_list": pch_config(model="pch-coder")},
    system_message="You implement what the planner specifies.",
)

reviewer = AssistantAgent(
    name="reviewer",
    llm_config={"config_list": pch_config(model="pch-fast")},
    system_message="You spot-check work for issues.",
)

Models

Model	Rate	Notes
pch-fast	$0.44/M tokens	Fast reasoning, classification, routing
pch-pro	$1.96/M tokens	Deep reasoning, multi-step planning (Bronze+)
pch-coder	$3.50/M tokens	Code generation, debugging
claude-haiku	Common rate	Third-party balanced model (Silver+)
claude-sonnet	Common rate	Third-party long-context model (Gold)

Choosing a model:

• Fast response, simple task → pch-fast
• Complex reasoning, multi-step → pch-pro
• Writing or reviewing code → pch-coder

Authentication

Set PCH_API_KEY in your environment, or pass pch_api_key= to pch_config.

export PCH_API_KEY=pch_prod_b_...

Get an API key at pathcoursehealth.com.

How it works

AutoGen's config_list accepts any OpenAI-compatible endpoint via the base_url and api_type: "openai" fields. The PCH gateway is fully OpenAI API-compatible, so this adapter is purely configuration — every AutoGen feature (group chat, code execution, function calling, custom agents) works unchanged.

Links

• Platform: pathcoursehealth.com
• AutoGen: microsoft.github.io/autogen
• AG2: ag2.ai
• Python SDK: pypi.org/project/pathcourse-sdk
• Integration examples: github.com/pathcourse-health/pch-integration-examples

License

MIT