CrewAI

CrewAI is a popular framework for orchestrating role-playing, autonomous AI agents. Its LLM class is LiteLLM-backed and accepts a custom base_url, so crews can run on the ScitiX Model Inference API. Default model here is glm-5.2; see the Models page for the full list and pricing.

Configure

Create an API key on the ScitiX API Keys page and export it:

export SCITIX_API_KEY="<Your API Key>"

Build a CrewAI LLM pointed at the ScitiX endpoint and hand it to your agents:

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

llm = LLM(
    model="openai/glm-5.2",
    base_url="https://api.scitix.ai/model-api/v1",
    api_key=os.environ["SCITIX_API_KEY"],
)

agent = Agent(role="Assistant", goal="Answer briefly",
              backstory="You are concise.", llm=llm)

Field	Description
`model`	`openai/<id>` — the `openai/` prefix routes via the OpenAI-compatible provider, e.g. `openai/glm-5.2`
`base_url`	ScitiX OpenAI-compatible endpoint: `https://api.scitix.ai/model-api/v1`
`api_key`	Your ScitiX API key, read from the environment

The openai/ prefix is required for this custom OpenAI-compatible endpoint. CrewAI routes through LiteLLM, which uses the provider prefix to pick the OpenAI-compatible client for a custom base_url like ScitiX. Choose a model with native tool calling for multi-agent tools/delegation. glm-5.2 works.

Verify

Run a one-agent crew — a normal completion confirms the connection (verified on crewai 1.15.16):

task = Task(description="In one short sentence, which model are you?",
            expected_output="One sentence.", agent=agent)
print(Crew(agents=[agent], tasks=[task]).kickoff())

You can also make a direct call through the configured LLM:

print(llm.call("In one short sentence, which model are you?"))
# → I am GLM, a large language model developed by Z.ai.

Get Started

Models

Usage

API Guides

Tool Integrations

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Configure

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