> ## Documentation Index
> Fetch the complete documentation index at: https://developers.telnyx.com/llms.txt
> Use this file to discover all available pages before exploring further.

# CrewAI Integration

> Integrate Telnyx Inference with CrewAI to build multi-agent workflows. Use Telnyx as the LLM provider for autonomous agents and crew orchestration.

OpenAI-compatible. Use as LLM backend for CrewAI agents.

## Setup

```shell theme={null}
pip install crewai
```

## Usage

Set environment variables for global routing:

```shell theme={null}
export TELNYX_API_KEY=your_telnyx_api_key
export OPENAI_BASE_URL=https://api.telnyx.com/v2/ai/openai
```

Or configure per-agent:

```python theme={null}
import os
from crewai import Agent, Task, Crew, LLM

llm = LLM(
    model="zai-org/GLM-5.1-FP8",
    base_url="https://api.telnyx.com/v2/ai/openai",
    api_key=os.getenv("TELNYX_API_KEY"),
)

researcher = Agent(
    role="Research Analyst",
    goal="Find and analyze information",
    backstory="You are an experienced research analyst.",
    llm=llm,
)

writer = Agent(
    role="Technical Writer",
    goal="Write clear, accurate reports",
    backstory="You are a skilled technical writer.",
    llm=llm,
)

research_task = Task(
    description="Research the latest trends in AI infrastructure",
    agent=researcher,
)

write_task = Task(
    description="Write a summary report based on the research findings",
    agent=writer,
)

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

## Tool Calling

```python theme={null}
from crewai.tools import tool

@tool("Search the web")
def search_web(query: str) -> str:
    """Search the web for information."""
    return f"Results for: {query}"

researcher = Agent(
    role="Research Analyst",
    goal="Find and analyze information",
    backstory="You are an experienced research analyst.",
    llm=llm,
    tools=[search_web],
)
```