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troubleshooting.md(4.75 KB)Markdown
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# Model trouble shooting
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This section has examples of common error messages and how to fix them.
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## Litellm
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`litellm` is the default model class and is used to support most models.
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### Invalid API key
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```json
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AuthenticationError: litellm.AuthenticationError: geminiException - {
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  "error": {
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    "code": 400,
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    "message": "API key not valid. Please pass a valid API key.",
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    "status": "INVALID_ARGUMENT",
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    "details": [
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      {
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        "@type": "type.googleapis.com/google.rpc.ErrorInfo",
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        "reason": "API_KEY_INVALID",
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        "domain": "googleapis.com",
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        "metadata": {
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          "service": "generativelanguage.googleapis.com"
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        }
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      },
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      {
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        "@type": "type.googleapis.com/google.rpc.LocalizedMessage",
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        "locale": "en-US",
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        "message": "API key not valid. Please pass a valid API key."
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      }
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    ]
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  }
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}
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 You can permanently set your API key with `mini-extra config set KEY VALUE`.
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```
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Double check your API key and make sure it is correct.
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You can take a look at all your API keys with `mini-extra config edit`.
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### "Weird" authentication error
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If you fail to authenticate but don't see the previous error message,
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it might be that you forgot to include the provider in the model name.
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For example, this:
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```
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  File "/Users/.../.virtualenvs/openai/lib/python3.12/site-packages/google/auth/_default.py", line 685, in default
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    raise exceptions.DefaultCredentialsError(_CLOUD_SDK_MISSING_CREDENTIALS)
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google.auth.exceptions.DefaultCredentialsError: Your default credentials were not found. To set up Application Default Credentials, see
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https://cloud.google.com/docs/authentication/external/set-up-adc for more information.
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```
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happens if you forgot to prefix your gemini model with `gemini/`.
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### Error during cost calculation
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```
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Exception: This model isn't mapped yet. model=together_ai/qwen/qwen3-coder-480b-a35b-instruct-fp8, custom_llm_provider=together_ai.
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Add it here - https://github.com/BerriAI/litellm/blob/main/model_prices_and_context_window.json.
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```
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`litellm` doesn't know about the cost of your model.
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Take a look at the model registry section of the [local models](local_models.md) guide to add it.
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Another common mistake is to not include any or the correct provider in the model name (e.g., `gemini-2.0-flash` instead of `gemini/gemini-2.0-flash`).
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## Temperature not supported
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Some models (like `o1`, `o3`, `GPT-5` etc.) do not support temperature. The default config no longer specifies a temperature value, so this should work out of the box now.
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## Portkey
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### Error during cost calculation
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We use `litellm` to calculate costs for Portkey models because Portkey doesn't seem to provide per-request cost information without
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very inconvenient APIs.
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This can lead to errors likethis:
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```
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  File "/opt/miniconda3/envs/clash/lib/python3.10/site-packages/minisweagent/models/portkey_model.py", line 85, in query
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    cost = litellm.cost_calculator.completion_cost(response)
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  File "/opt/miniconda3/envs/clash/lib/python3.10/site-packages/litellm/cost_calculator.py", line 973, in completion_cost
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    raise e
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  File "/opt/miniconda3/envs/clash/lib/python3.10/site-packages/litellm/cost_calculator.py", line 966, in completion_cost
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    raise e
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  File "/opt/miniconda3/envs/clash/lib/python3.10/site-packages/litellm/cost_calculator.py", line 928, in completion_cost
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    ) = cost_per_token(
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  File "/opt/miniconda3/envs/clash/lib/python3.10/site-packages/litellm/cost_calculator.py", line 218, in cost_per_token
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    _, custom_llm_provider, _, _ = litellm.get_llm_provider(model=model)
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  File "/opt/miniconda3/envs/clash/lib/python3.10/site-packages/litellm/litellm_core_utils/get_llm_provider_logic.py", line 395, in get_llm_provider
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    raise e
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  File "/opt/miniconda3/envs/clash/lib/python3.10/site-packages/litellm/litellm_core_utils/get_llm_provider_logic.py", line 372, in get_llm_provider
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    raise litellm.exceptions.BadRequestError(  # type: ignore
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litellm.exceptions.BadRequestError: litellm.BadRequestError: LLM Provider NOT provided. Pass in the LLM provider you are trying to call. You passed model=grok-code-fast-1
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 Pass model as E.g. For 'Huggingface' inference endpoints pass in `completion(model='huggingface/starcoder',..)` Learn more: https://docs.litellm.ai/docs/providers
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```
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In this case, the issue is simply that the portkey model name doesn't match the litellm model name (and very specifically here
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doesn't include the provider).
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To fix this, you can manually set the litellm model name to the portkey model name with the `litellm_model_name_override` key.
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For example:
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```yaml
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model:
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  model_name: "grok-code-fast-1"  # the portkey model name
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  model_class: "portkey"  # make sure to use the portkey model class
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  litellm_model_name_override: "xai/grok-code-fast-1"  # the litellm model name for cost information
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  ...
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```
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