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Hey @takatea! 👋 I'm here to help you with bug fixes, answer questions, and support your contributions. Let's squash those bugs together!
I found a similar closed issue regarding the model list not being synchronized in the Docker version of Dify. The suggested solution includes several areas to investigate:
Model Configuration: Ensure that the models you expect to see are properly configured in the codebase. Check if the models are included in relevant lists such as LLM_BASE_MODELS in the file api/core/model_runtime/model_providers/azure_openai/_constant.py.
Environment Variables: Verify the environment variables related to model providers in your setup. Specifically, check the POSITION_PROVIDER_PINS, POSITION_PROVIDER_INCLUDES, and POSITION_PROVIDER_EXCLUDES settings in your .env file to ensure they are not excluding the models you want to see.
ML Frameworks: Make sure that the necessary ML frameworks (e.g., PyTorch, TensorFlow, Flax) are installed and properly configured in your environment.
Configuration: Ensure that your configuration allows access to local models or external services, which might involve setting the correct network configurations or environment variables.
These steps might help in resolving the issue with the "gemini-2.0-flash-001" model not being visible in the model list [1].
Self Checks
Dify version
0.15.3
Cloud or Self Hosted
Cloud
Steps to reproduce
Additional Notes
Version:
Note:
"gemini-2.0-pro-exp-02-05" model, which was added in the same PR (#13247), is visible in the list.
✔️ Expected Behavior
"gemini-2.0-flash-001" model should be listed in the Gemini model list
❌ Actual Behavior
"gemini-2.0-flash-001" model is not visible in the model list despite being defined in the Gemini model list
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