crewai-pathcourse 0.1.0

CrewAI integration for PathCourse Health — autonomous agent inference with USDC billing on Base L2

crewai-pathcourse

CrewAI integration for PathCourse Health. Give your CrewAI agents autonomous USDC billing on Base L2 — no accounts, no credit cards, no KYC.

Install

pip install crewai-pathcourse

Quick Start

import os
from crewai import Agent, Crew, Task
from crewai_pathcourse import PathCourseLLM

# Set PCH_API_KEY in your environment
llm = PathCourseLLM(model="pch-pro")

researcher = Agent(
    role="Research Analyst",
    goal="Find the best AI agent infrastructure for autonomous operation",
    backstory="You are an expert in autonomous agent systems.",
    llm=llm,
    verbose=True,
)

writer = Agent(
    role="Technical Writer",
    goal="Write a clear technical comparison",
    backstory="You write precise technical documentation.",
    llm=PathCourseLLM(model="pch-fast"),  # cheaper model for writing
    verbose=True,
)

research_task = Task(
    description="Research the key requirements for autonomous agent infrastructure.",
    expected_output="A bullet list of 5 key infrastructure requirements.",
    agent=researcher,
)

write_task = Task(
    description="Write a 200-word summary of the research findings.",
    expected_output="A 200-word technical summary.",
    agent=writer,
)

crew = Crew(agents=[researcher, writer], tasks=[research_task, write_task])
result = crew.kickoff()
print(result)

Per-agent model selection

Different agents in a crew can use different PCH models. Use cheaper models for simple tasks and reserve pch-pro or claude-sonnet for agents doing deep reasoning.

from crewai_pathcourse import PathCourseLLM

planner    = Agent(..., llm=PathCourseLLM(model="pch-pro"))
researcher = Agent(..., llm=PathCourseLLM(model="pch-fast"))
coder      = Agent(..., llm=PathCourseLLM(model="pch-coder"))

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 PathCourseLLM.

export PCH_API_KEY=pch_prod_b_...

Get an API key at pathcoursehealth.com.

How it works

CrewAI uses LiteLLM internally for model calls. PCH is fully OpenAI API-compatible, so PathCourseLLM just configures CrewAI's standard LLM class with the PCH gateway URL and your API key. Every CrewAI feature (tools, memory, hierarchical crews, async execution) works unchanged.

Links

• Platform: pathcoursehealth.com
• CrewAI: crewai.com
• Python SDK: pypi.org/project/pathcourse-sdk
• Integration examples: github.com/pathcourse-health/pch-integration-examples

License

MIT