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LLM Provider NOT provided — LiteLLM could not tell which provider your model string means

litellm.BadRequestError: LLM Provider NOT provided. Pass in the LLM provider you are trying to call. You passed model=<model> Pass model as E.g. For 'Huggingface' inference endpoints pass in `completion(model='huggingface/starcoder',..)` Learn more: https://docs.litellm.ai/docs/providers

(The error as str(e) gives it, assembled by us from the message string and the class’s prefix quoted below, with our placeholder in angle brackets; the line break is the \n in the source string. The URL is part of LiteLLM’s message; we did not open it.)

LiteLLM raises this inside get_llm_provider, in litellm/litellm_core_utils/get_llm_provider_logic.py, when it ends with no provider for the call: you passed no custom_llm_provider, the part of the model string before the first / is not a provider name it knows, the model is not on one of its known-model lists, api_base matched none of its known endpoints, and its last-resort routing rule matched nothing. It is a plain litellm.BadRequestError with llm_provider set to the empty string, raised before any request for the call is made (our reading). Every claim about the library below is read off the Python source of BerriAI/litellm at tag v1.104.2, fetched on 10 October 2026, with the line of each quote given; where we draw a conclusion from those lines rather than quote them, we say so.

The raise

In litellm/litellm_core_utils/get_llm_provider_logic.py, inside get_llm_provider (defined at line 158), lines 526–532:

# Last resort for an otherwise-unknown model: a declarative # fallback-generalization routing rule (e.g. routes future claude-* to anthropic). # Exact provider matches above always win; this only runs on a miss. if not custom_llm_provider: custom_llm_provider = match_routing_generalization(model) if not custom_llm_provider:

and, after the print lines, lines 539–546:

error_str = f"LLM Provider NOT provided. Pass in the LLM provider you are trying to call. You passed model={model}\n Pass model as E.g. For 'Huggingface' inference endpoints pass in `completion(model='huggingface/starcoder',..)` Learn more: https://docs.litellm.ai/docs/providers" # maps to openai.NotFoundError, this is raised when openai does not recognize the llm raise litellm.exceptions.BadRequestError( message=error_str, model=model, response=None, llm_provider="", )

The message is the f-string at line 539; the litellm.BadRequestError: in front of it is added by the class (below). When litellm.suppress_debug_info is False, a “Provider List” line is printed to standard output first, between two blank lines (lines 533–538). After its docstring, the function’s whole body is one try, and its handler, lines 552–554, passes this error through unchanged:

except Exception as e: if isinstance(e, litellm.exceptions.BadRequestError): raise e

Any other exception inside the function becomes a different BadRequestError, whose message starts GetLLMProvider Exception - (line 558), also with llm_provider="" (lines 555–562). That is a different message; this page is about line 539.

How a provider gets set before line 532

Before line 532 the function finds a provider in these ways. We searched lines 175–531 for every assignment to custom_llm_provider other than a fixed string (lines 189, 203, 205, 250, 402 and 530, all covered here); the early return statements in between are not all listed.

• Your argument. custom_llm_provider is a parameter of get_llm_provider; if it is set and the model does not already start with it, the model string is prefixed with it, lines 207–210:

  if custom_llm_provider and ( model.split("/")[0] != custom_llm_provider ): # handle scenario where model="azure/*" and custom_llm_provider="azure" model = custom_llm_provider + "/" + model

  With litellm_params, line 189 takes it from there, but only when custom_llm_provider, api_base and api_key are all None (line 188).
• The prefix of the model string. The part before the first slash, checked against JSON-configured providers (line 225), then litellm.provider_list (line 237, and lines 249–251):

  elif model.split("/", 1)[0] in litellm.provider_list: custom_llm_provider = model.split("/", 1)[0] model = model.split("/", 1)[1]

  then custom providers you registered (line 257). We did not fetch the file that defines litellm.provider_list, so this page does not list its names.
• Your api_base. # check if api base is a known openai compatible endpoint (line 259): a match against litellm.openai_compatible_endpoints names the provider, for example if endpoint == "api.perplexity.ai": (line 263) gives perplexity.
• Known model names. From line 411, a model name found in one of LiteLLM’s model lists, such as model in litellm.open_ai_chat_completion_models (line 414), or a fixed name prefix such as elif model.startswith("sap/"): (line 523), sets a fixed provider string.
• The routing rule. match_routing_generalization(model), line 530, only when everything above missed.

Two helpers at lines 203 and 205 (defined at lines 78 and 104) can change the provider to cohere_chat or anthropic_text and otherwise return it as given. So the raise at line 541 is reached only if none of the above produced a value (our reading).

The class

In litellm/exceptions.py, the body of the constructor of the class at line 219 starts, lines 231–234:

self.status_code = 400 self.message = f"litellm.BadRequestError: {message}" self.model = model self.llm_provider = llm_provider

Because the raise passes response=None, the constructor uses self.response = _get_minimal_error_response() (line 248), then calls the parent, lines 249–251:

super().__init__( self.message, response=self.response, body=body ) # Call the base class constructor with the parameters it needs

and the string form, lines 253–258:

def __str__(self): _message = self.message if self.num_retries: _message += f" LiteLLM Retried: {self.num_retries} times" if self.max_retries: _message += f", LiteLLM Max Retries: {self.max_retries}"

The raise passes neither num_retries nor max_retries, so as raised there str(e) equals e.message (our reading).

Where completion() calls it

In litellm/main.py, completion (line 5113) reads the argument from its keyword arguments, line 5298: custom_llm_provider = kwargs.get("custom_llm_provider", None), and calls get_llm_provider at lines 5452–5460:

model, custom_llm_provider, dynamic_api_key, api_base = get_llm_provider( model=model, custom_llm_provider=custom_llm_provider, api_base=api_base, api_key=api_key, litellm_params=( GenericLiteLLMParams(**_supplemental_provider_params) if _supplemental_provider_params else None ), )

main.py imports that name from litellm.utils (the import that starts at line 138; the name is at line 156); that it is the function quoted above is our inference, as we did not trace how utils.py provides it. The call sits inside the try of completion that starts at line 5419, whose handler is lines 6036–6044:

except Exception as e: ## Map to OpenAI Exception raise exception_type( model=model, custom_llm_provider=custom_llm_provider, original_exception=e, completion_kwargs=args, extra_kwargs=kwargs, )

and the first statement after the docstring of exception_type, in litellm/litellm_core_utils/exception_mapping_utils.py (defined at line 2349), is lines 2357–2358:

if any(isinstance(original_exception, exc_type) for exc_type in litellm.LITELLM_EXCEPTION_TYPES): return original_exception

The list LITELLM_EXCEPTION_TYPES in exceptions.py (line 970) includes BadRequestError (line 973). So the same exception object reaches the caller of completion, not a rewrapped one (our reading; we did not trace that litellm.LITELLM_EXCEPTION_TYPES is that list, nor acompletion, the Router or any framework’s wrapper).

What it looks like in the field

In alpha03123/vsummary#78, 模型名含 / 时用户配置的 provider 被整体丢弃，导致 503 LLM Provider NOT provided (closed as completed when we fetched it; the report is in Chinese), the reporter’s app had a provider configured but sent the model group/auto-deepseek-v4-1-flash to LiteLLM without it (their diagnosis), and got 503 litellm.BadRequestError: LLM Provider NOT provided. … You passed model=group/auto-deepseek-v4-1-flash (the 503 is their app’s wrapping, they say). Their pinned version is litellm==1.74.0, not the tag read here, and the fix they propose is to pass the provider explicitly: request["custom_llm_provider"] = provider.

In BerriAI/litellm#44069, websearch_interception agentic loop: follow-up loses its provider prefix on org-style model ids (open when we fetched it), on LiteLLM 1.104.0rc2, a deployment configured as hosted_vllm/zai-org/GLM-5.3-Flash fails on a follow-up call with You passed model=zai-org/GLM-5.3-Flash: the provider prefix was stripped (their diagnosis), and the reporter writes that because the remaining id still has a slash, so the guard assumes a provider prefix is already present and never re-attaches `hosted_vllm/`.

What the caller sees and can read

• e.message and str(e) — the text above, starting litellm.BadRequestError: LLM Provider NOT provided.; the model string get_llm_provider received is inside it after You passed model=.
• e.status_code — 400, set by the constructor; no HTTP request was made for the call (our reading).
• e.model — the same model string; e.llm_provider — "", the empty string.
• e.response — a placeholder built by _get_minimal_error_response() (line 121), not a provider’s reply.
• Catching it — except BadRequestError, imported from litellm.exceptions; it is also an openai.BadRequestError (line 219). The “GetLLMProvider Exception” error has the same class and the same empty llm_provider, so tell them apart by the message (our reading).

What to do

• Put the provider in front of the model, as the message’s own example does: huggingface/starcoder. The part before the first slash has to be a name LiteLLM checks for at lines 225, 237, 249 or 257; an organisation or group name such as zai-org or group in the reports above did not resolve (our reading of those reports).
• Or pass custom_llm_provider= to completion. The function then prefixes the model with it unless the model already starts with it (lines 207–210) and keeps it, so this raise cannot fire; whether that provider then accepts the model is a separate question (our reading).
• If a wrapper builds the call (a Router entry, an app, a framework), check the model string it actually sends; e.model and the text after You passed model= show it. In both reports above, the provider was configured but dropped before LiteLLM saw it (their diagnosis).
• litellm.suppress_debug_info = True only stops the printed Provider List line (line 533); the error is still raised.

import litellm from litellm.exceptions import BadRequestError def ask(model: str, question: str, provider: str | None = None) -> str | None: # Our sketch: name the provider when the model string does not carry it. messages = [{"role": "user", "content": question}] try: response = litellm.completion(model=model, messages=messages, custom_llm_provider=provider) except BadRequestError as e: if e.llm_provider == "" and "LLM Provider NOT provided" in e.message: print(e.model) print(e.message) return None raise return response.choices[0].message.content

(Our sketch, not library code, and not run against your version. completion reads custom_llm_provider from kwargs as quoted above, so passing None gives the same value at line 5298 as not passing it.)

What is behind this site

The short version: LLM Provider NOT provided is a litellm.BadRequestError that get_llm_provider raises when nothing names a provider for the call: no custom_llm_provider, no provider name before the first slash of the model string, no known model name or name prefix, no known api_base endpoint and no routing rule. e.status_code is 400, e.llm_provider is the empty string, and the model string is in e.model and in the message. Prefix the model with its provider or pass custom_llm_provider.

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