autogen-pathcourse 0.1.1

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	Min tier	Notes
pch-fast	$0.44 / M tokens	uncertified	Fast reasoning, classification, routing
pch-coder	$3.50 / M tokens	uncertified	Code generation, debugging
pch-embed	$0.015 / M tokens	uncertified	Text embeddings for semantic search / RAG
pch-translate	$0.08 / M chars	uncertified	Multilingual translation
pch-pro	$1.96 / M tokens	bronze	Deep reasoning, multi-step planning
pch-audio	$1.85 / M chars	bronze	Text-to-speech, standard quality
pch-documents	$0.26 in / $1.48 out per M tokens	bronze	Document parsing / OCR
pch-transcribe	$0.0008 / minute	bronze	Speech-to-text
pch-extract	$0.012 / M tokens	bronze	Structured data extraction
pch-rerank	$0.025 / M tokens	bronze	Reranking for RAG pipelines
pch-image	$0.028 / image	silver	Text-to-image
pch-audio-premium	$37.00 / M chars	silver	Text-to-speech, premium quality
pch-talk	$0.001 / minute	silver	Voice conversation
claude-haiku	Common rate	silver	Anthropic Claude Haiku
claude-sonnet	Common rate	gold	Anthropic Claude Sonnet

pch_config only operates on chat-completion shapes — for image/audio/transcription, use the PCH Python SDK directly.

Choosing a chat model:

• Fast response, simple task → pch-fast
• Complex reasoning, multi-step → pch-pro
• Writing or reviewing code → pch-coder
• Long context or premium reasoning → claude-sonnet (Gold tier)

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