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mistral-ai
#10144
model_selection_error
The model name provided is invalid. Please ensure the model name is correct and try again.
This error has been identified and solved.
Reason
The " Invalid model name" error in the mistral-ai API, or any similar API like OpenAI, can be triggered by several reasons:
Incorrect Model Name
The model name specified in the request does not match any of the permitted or available models. This could be due to a typo, an outdated model name, or the model not being supported by the API.
Invalid Configuration
The request may contain invalid syntax or configuration, such as incorrect headers, missing required properties (e.g., Content-Type
or Authorization
headers), or incorrect data types for the parameters.
Rate Limiting or Throttling
Although less likely for an invalid model name, rate limiting or throttling issues can sometimes manifest as a 400 error if the request is malformed or not properly handled within the rate limits.
Environmental or Variable Issues
The error could also arise if environment variables or other configuration values are not correctly set or are of the wrong type (e.g., text instead of numeric).
Network or Middleware Issues
Problems with network traffic or middleware configurations (such as Axios setup) can also lead to a 400 error, although this is more general and not specific to the model name.
Solution
To resolve the "Invalid model name" error in the mistral-ai API, here are some key steps to follow:
Ensure that the model name you are using is correct and matches one of the available models supported by the API. Here are some concise actions to take:
Verify the Model Name: Double-check the model name against the API documentation to ensure it is accurate and supported.
Check API Keys and Headers: Make sure your API keys and headers, such as
Authorization
andContent-Type
, are correctly set.Review Request Syntax: Ensure the request syntax is valid and all required properties are included.
Inspect Network Traffic: Use tools to inspect network traffic for any anomalies or issues.
Check Environment Variables: Verify that all environment variables and configuration values are correctly set and of the correct type.
Rate Limiting: Ensure your requests are within the rate limits set by the API to avoid throttling issues.
Suggested Links
https://cheatsheet.md/chatgpt-cheatsheet/openai-api-error-axioserror-request-failed-status-code-400
https://community.make.com/t/400-invalid-model-llama-3-8b-instruct-how-is-that-possible-if-it-is-actually-permitted/53562
https://community.openai.com/t/request-failed-with-status-code-400/39242
https://community.openai.com/t/content-is-required-property-error-400/486260
https://discuss.huggingface.co/t/400-client-error-in-inference-api-for-sentence-similarity-task/34784
https://learn.microsoft.com/en-us/answers/questions/2117664/my-mistral-large-2407-serverless-deployment-api-is
https://community.crewai.com/t/crewai-on-mistral-api-error/1559
https://github.com/langchain-ai/langchain/issues/16869
https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2/discussions/98