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Currently, using Qianwen as a knowledge base for data embedding is very slow #4492

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opened 2026-02-21 18:06:46 -05:00 by yindo · 1 comment
yindo commented 2026-02-21 18:06:46 -05:00
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Originally created by @baiyi-os on GitHub (Jul 8, 2024).

Self Checks

  • I have searched for existing issues search for existing issues, including closed ones.
  • I confirm that I am using English to submit this report (我已阅读并同意 Language Policy).
  • 请务必使用英文提交 Issue，否则会被关闭。谢谢！:）
  • Please do not modify this template :) and fill in all the required fields.

1. Is this request related to a challenge you're experiencing? Tell me about your story.

My EMBEDDING model uses qwen2:72b
Uploading txt documents to the knowledge base, currently embedding processing is slow

2. Additional context or comments

我的EMBEDDING模型使用qwen2:72b
上传txt文档到知识库，目前嵌入处理很慢

3. Can you help us with this feature?

  • I am interested in contributing to this feature.
Originally created by @baiyi-os on GitHub (Jul 8, 2024). ### Self Checks - [X] I have searched for existing issues [search for existing issues](https://github.com/langgenius/dify/issues), including closed ones. - [X] I confirm that I am using English to submit this report (我已阅读并同意 [Language Policy](https://github.com/langgenius/dify/issues/1542)). - [X] 请务必使用英文提交 Issue，否则会被关闭。谢谢！:） - [X] Please do not modify this template :) and fill in all the required fields. ### 1. Is this request related to a challenge you're experiencing? Tell me about your story. My EMBEDDING model uses qwen2:72b Uploading txt documents to the knowledge base, currently embedding processing is slow ### 2. Additional context or comments 我的EMBEDDING模型使用qwen2:72b 上传txt文档到知识库，目前嵌入处理很慢 ### 3. Can you help us with this feature? - [ ] I am interested in contributing to this feature.
yindo closed this issue 2026-02-21 18:06:46 -05:00
yindo commented 2026-02-21 18:06:46 -05:00
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@crazywoola commented on GitHub (Jul 8, 2024):

We send documents to embedding model to process, so the speeds highly depends on the model itself and deploy method.

@crazywoola commented on GitHub (Jul 8, 2024): We send documents to embedding model to process, so the speeds highly depends on the model itself and deploy method.
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Reference: langgenius/dify#4492
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