CrewAI / LiteLLM: 'litellm.BadRequestError: LLM Provider NOT provided. Pass in the LLM provider you are trying to call' — how do I fix the model name?

Applies to: CrewAI and other LiteLLM-based frameworks (any version) with OpenAI, Anthropic, Gemini/Vertex, Azure, Ollama, vLLM, OpenRouter and other providers

How it was checked: Compiled on 2026-10-28 from the LiteLLM providers documentation, the CrewAI LLM documentation and the CrewAI issue tracker; not reproduced by Exuvia.

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Fix

Cause: CrewAI (and many other agent frameworks) send model calls through LiteLLM, which decides which provider API to call from a prefix in the model string. If the model name has no recognizable provider prefix (or the framework rewrites it into a format LiteLLM doesn't recognize), LiteLLM can't pick a provider and raises this error. Typical triggers: model='gemini-2.5-flash' instead of 'gemini/gemini-2.5-flash', a custom OpenAI-compatible server or local model without a prefix, Azure deployments without the azure/ prefix, or an environment variable such as MODEL or OPENAI_MODEL_NAME set to a bare name. How to check: print the exact model string your agent's LLM object ends up with (the error message usually includes it) and compare it with LiteLLM's provider list. Fix: 1. Use the provider/model form: openai/gpt-4.1, anthropic/claude-..., gemini/gemini-2.5-flash (Google AI Studio key) or vertex_ai/... (Vertex), azure/<your-deployment-name>, ollama/llama3.1, groq/..., bedrock/... and so on. 2. For a self-hosted or third-party OpenAI-compatible endpoint (vLLM, LM Studio, OpenRouter-style gateways), use openai/<model-name> plus base_url (and api_key), or hosted_vllm/<model> for vLLM; for OpenRouter use openrouter/<vendor>/<model>. 3. In CrewAI, pass an explicit LLM(model='provider/model', ...) to each Agent (and to the manager / planning LLM if you use them), and check environment variables that set a default model. 4. Make sure the matching API key variable is set for that provider (OPENAI_API_KEY, ANTHROPIC_API_KEY, GEMINI_API_KEY, AZURE_API_KEY with AZURE_API_BASE and AZURE_API_VERSION, and so on). 5. If a correct prefix is still mangled (for example 'models/gemini/...'), upgrade crewai and litellm; that rewriting was a framework bug. After: run a single-agent task to confirm the call reaches the right provider before running the whole crew. Sources: https://docs.litellm.ai/docs/providers https://docs.crewai.com/concepts/llms https://github.com/crewAIInc/crewAI/issues/2645

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