CrewAI

Multi-agent crews with LiteLLM routing

CrewAI

CrewAI’s LLM class uses LiteLLM for model connections. Select the OpenAI-compatible protocol with an openai/ prefix and send requests to Radium.

Before you start

You need Python 3.10 or newer, a Radium API key, and a terminal or PowerShell window.

1. Create a project and install CrewAI

macOS or Linux

mkdir radium-crewai && cd radium-crewai
python3 -m venv .venv
source .venv/bin/activate
python -m pip install crewai

2. Set your Radium credentials

macOS or Linux

export RADIUM_API_KEY="your-radium-api-key"
export RADIUM_MODEL="hal-1.0"
export CREWAI_TRACING_ENABLED="false"

Tracing is disabled here so this connection example does not ask for an additional tracing setup.

3. Create main.py

import os
from crewai import Agent, Crew, LLM, Task

api_key = os.getenv("RADIUM_API_KEY")
if not api_key:
    raise SystemExit("Set RADIUM_API_KEY before running this program.")

model = os.getenv("RADIUM_MODEL", "hal-1.0")
llm = LLM(
    model=f"openai/{model}",
    api_key=api_key,
    base_url="https://api.radium.cloud/v1",
    max_tokens=512,
    temperature=0,
    timeout=90,
)

assistant = Agent(
    role="Radium connection tester",
    goal="Follow the user's instruction exactly",
    backstory="You provide short, exact responses.",
    llm=llm,
    allow_delegation=False,
    verbose=False,
)

task = Task(
    description="Reply with exactly: Radium connected.",
    expected_output="The exact text 'Radium connected.' and nothing else.",
    agent=assistant,
)

result = Crew(agents=[assistant], tasks=[task], verbose=False).kickoff()
if not result.raw or not result.raw.strip():
    raise RuntimeError("Radium returned no visible text.")
print(f"RADIUM_RESPONSE: {result.raw.strip()}")

The openai/ prefix is required for LiteLLM provider routing. Radium still receives the model ID without that prefix.

4. Run it

python main.py

Expected final output:

RADIUM_RESPONSE: Radium connected.

CrewAI may print status messages before the final line.

Choose a model

export RADIUM_MODEL="tycho-1.0"  # or hal-1.0 or clarke-1.0
python main.py

Migrate an existing crew

Create one Radium-backed LLM and pass it to every agent that should use Radium:

llm = LLM(
    model="openai/hal-1.0",
    api_key=os.environ["RADIUM_API_KEY"],
    base_url="https://api.radium.cloud/v1",
    max_tokens=512,
)
agent = Agent(..., llm=llm)

Your roles, goals, tasks, and crew process can remain unchanged. Planning, memory, and external tools may require additional model calls or credentials.

Troubleshooting

Problem	Fix
Authentication errors	Set the API key in the same terminal running CrewAI
Provider errors	Keep the openai/ prefix on the model passed to LLM
404	Use the exact base URL and model IDs shown above
Unexpected tracing prompts	Set CREWAI_TRACING_ENABLED=false

Validation

These instructions were verified with Python 3.12.7 and crewai==1.15.17 on August 20, 2026. You do not need that exact package version.

Agent/task generation and CrewAI tool execution passed with hal-1.0, clarke-1.0, and tycho-1.0.

Next steps

API quickstart

Call Radium directly

Tool calling

The tool_use and tool_result contract