Error in Java Multi-modal Tongyi

yanghangxl commented 1 month ago

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Dify version

0.6.9

Cloud or Self Hosted

Self Hosted (Docker)

Steps to reproduce

After uploading an image to dify using Java and obtaining the image ID, I passed the image ID through the calling process to the Tongyi multi-modal model, but encountered an error: [tongyi] Error: list index out of range.

✔️ Expected Behavior

No response

❌ Actual Behavior

No response

dosubot[bot] commented 1 month ago

@yanghangxl Hello there! I'm here to help you with any bugs, questions, or contributions you have regarding Dify. If you need assistance, feel free to ask.

I found a similar unsolved discussion and a closed issue that might be relevant to your problem:

I can't upload the image on dify workflow via api (Unsolved) ^[1].
无法使用Xinference中的视觉模型，无法传入图片，files: [] (Closed) ^[2].

The 'list index out of range' error in the context of the Tongyi multi-modal model can occur due to several reasons:

Accessing an Empty List: If the list you're trying to access is empty, it will result in this error. Ensure that the list contains elements before accessing them.
Incorrect Range Calculation: Ensure that the range for iterating over inputs is correctly calculated to avoid accessing non-existent indices.
Response Handling: Ensure that the response from the embed_documents method contains the expected data structure before accessing its elements.

Here is an example of how to handle the response correctly:

if response.output and "embeddings" in response.output and response.output["embeddings"]:
    data = response.output["embeddings"][0]
    if "embedding" in data:
        embeddings.append(data["embedding"])
    else:
        raise ValueError("Embedding data is missing in the response.")
else:
    raise ValueError("Response output is missing or does not contain embeddings.")

Additionally, ensure that the image ID is correctly formatted as a URL when passed to the Tongyi multi-modal model. If the image data is in base64 format, it should be converted to a file, and the file path should be used as the image URL ^[3].

For debugging and resolving errors related to image processing, follow these steps:

Check the Error Code: Identify the specific error code returned by the API.
Verify Request Format: Ensure the request is correctly formatted.
Check File Type and Size: Ensure the file type and size are within the supported limits.
Validate API Key and Permissions: Ensure the API-Key is valid and has the necessary permissions.
Review Server Logs: Check server logs for more detailed error messages.
Test with Different Files: Try uploading different files to determine if the issue is specific to certain files.
Check S3 Configuration: If using S3 for storage, ensure the S3 service is properly configured and accessible ^[4].

By following these steps, you should be able to identify and resolve the issue.

To continue talking to Dosu, mention @dosu.

crazywoola commented 1 month ago

Please upgrade to the latest version to see if this persists.

langgenius / dify