[Bug]: Model Not Found, Uid: Qwen2.5-instruct-0'

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Bug Report: Model not found, uid: qwen2.5-instruct-0'

In this article, we will be discussing a bug that occurs when importing a large text document with graphrag and Xinference model. The error message "Model not found, uid: qwen2.5-instruct-0'" is displayed, indicating that the model is not found. This issue is crucial to resolve as it affects the functionality of the application and causes inconvenience to the users.

Before submitting this report, we have performed the necessary self checks to ensure that the issue is not already reported and that the report is submitted in the correct language.

The latest commit ID of the RAGFlow workspace code is not provided.

The RAGFlow image version being used is v0.17.0 slim.

The following environment information is provided:

RagFlow: Docker Version
Xinference: v1.3.0.post2

When importing a large text document with graphrag and Xinference model, the following error message is displayed:

"Model not found, uid: qwen2.5-instruct-0'"

The expected behavior is that there should be no response or error message when importing the large text document with graphrag and Xinference model.

The steps to reproduce the issue are as follows:

Import a large text document with graphrag and Xinference.

No additional information is provided.

In conclusion, the bug "Model not found, uid: qwen2.5-instruct-0'" occurs when importing a large text document with graphrag and Xinference model. The error message is displayed, indicating that the model is not found. This issue is crucial to resolve as it affects the functionality of the application and causes inconvenience to the users. We have performed the necessary self checks and have provided the required information to help resolve this issue.

Based on the information provided, the following recommendations can be made:

  • Update RAGFlow Image Version: Update the RAGFlow image version to the latest version to resolve any potential issues.
  • Check Model Configuration: Check the model configuration to ensure that it is correct and that the model is properly loaded.
  • Optimize Import Process: Optimize the import process to handle large text documents efficiently and prevent errors.

By following these recommendations, the issue can be resolved, and the application can function smoothly without any errors.

In the future, it would be beneficial to:

  • Implement Error Handling: Implement error handling mechanisms to catch and handle errors that occur during the import process.
  • Provide User Feedback: Provide user feedback to inform users of any errors that occur during the import process.
  • Optimize Application Performance: Optimize the application performance to handle large text documents efficiently and prevent errors.

By implementing these features, the application can provide a better user experience and prevent errors from occurring.
Q&A: Model not found, uid: qwen2.5-instruct-0' Bug

In our previous article, we discussed the bug "Model not found, uid: qwen2.5-instruct-0'" that occurs when importing a large text document with graphrag and Xinference model. In this article, we will provide a Q&A section to address any questions or concerns that users may have regarding this issue.

A: The cause of the "Model not found, uid: qwen2.5-instruct-0'" error is not explicitly stated in the provided information. However, based on the error message, it is likely that the model is not found or is not properly loaded.

A: To resolve the "Model not found, uid: qwen2.5-instruct-0'" error, you can try the following:

  • Update RAGFlow Image Version: Update the RAGFlow image version to the latest version to resolve any potential issues.
  • Check Model Configuration: Check the model configuration to ensure that it is correct and that the model is properly loaded.
  • Optimize Import Process: Optimize the import process to handle large text documents efficiently and prevent errors.

A: The recommended steps to reproduce the issue are as follows:

Import a large text document with graphrag and Xinference.

A: The system requirements for RAGFlow are not explicitly stated in the provided information. However, based on the environment information provided, it is likely that the system requirements are as follows:

  • RagFlow: Docker Version: The RagFlow Docker version is v1.3.0.post2.
  • Xinference: v1.3.0.post2: The Xinference version is v1.3.0.post2.

A: To provide feedback or report issues with RAGFlow, you can follow these steps:

  • Search for Existing Issues: Search for existing issues, including closed ones, on the GitHub repository of RagFlow.
  • Submit a New Issue: If the issue is not already reported, submit a new issue on the GitHub repository of RagFlow.
  • Follow the Language Policy: Follow the language policy stated in https://github.com/infiniflow/ragflow/issues/5910.

A: The future plans for RAGFlow are not explicitly stated in the provided information. However, based on the recommendations provided, it is likely that the future plans include:

  • Implement Error Handling: Implement error handling mechanisms to catch and handle errors that occur during the import process.
  • Provide User Feedback: Provide user feedback to inform users of any errors that occur during the import process.
  • Optimize Application Performance: Optimize the application performance to handle large text documents efficiently and prevent errors.

By following these future plans, RAGFlow can provide a better user experience and prevent errors from occurring.