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Integrations

CrewAI

Use AICredits with CrewAI agents by setting the OpenAI base URL, API key, and model for crews and flows.

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Opens a new chat with this docs URL and the correct AICredits base URLs.

CrewAI is a Python framework for orchestrating multi-agent workflows. AICredits works with CrewAI through its OpenAI-compatible LLM configuration.

Environment Setup

Set the OpenAI-compatible environment variables:

.env
OPENAI_API_KEY=sk-your-aicredits-key
OPENAI_BASE_URL=https://api.aicredits.in/v1
MODEL=openai/gpt-4o-mini

Direct Code

Configure an AICredits-backed LLM in Python:

from crewai import Agent, Crew, LLM, Task

llm = LLM(
    model="openai/gpt-4o-mini",
    api_key="sk-your-aicredits-key",
    base_url="https://api.aicredits.in/v1",
    temperature=0.3,
)

researcher = Agent(
    role="Researcher",
    goal="Answer questions concisely",
    backstory="You are a practical research assistant.",
    llm=llm,
)

task = Task(
    description='Reply with "AICredits via CrewAI" and nothing else.',
    expected_output="The exact confirmation phrase.",
    agent=researcher,
)

crew = Crew(agents=[researcher], tasks=[task])
print(crew.kickoff())

YAML Agents

In an agents.yaml file, use the AICredits model ID:

researcher:
  role: Researcher
  goal: Find practical answers
  backstory: You summarize information clearly.
  llm: openai/gpt-4o-mini

For crews with multiple agents, use smaller models for routing and extraction, then reserve larger models for final synthesis.

Verify

Run one kickoff and check Dashboard -> Usage for the request.

Troubleshooting

CrewAI uses OpenAI directly - Confirm OPENAI_BASE_URL is set to https://api.aicredits.in/v1.

Model not found - Use an exact model ID from Models.

Crew loops are expensive - Add iteration limits and use budget-capped AICredits keys for agent experiments.

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