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psycopg2.errors.UndefinedTable: relation "embedding_vector_index_0799a0c6_ca9a_418e_9e33_900236a74af4_nod" does not exist #3750

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opened 2026-02-21 18:01:34 -05:00 by yindo · 0 comments
yindo commented 2026-02-21 18:01:34 -05:00
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Originally created by @wencan on GitHub (May 27, 2024).

Self Checks

  • This is only for bug report, if you would like to ask a question, please head to Discussions.
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Dify version

0.6.8

Cloud or Self Hosted

Self Hosted (Docker), Self Hosted (Source)

Steps to reproduce

  1. docker compose 在本地运行dify。vector数据库选pgvector。
  2. 知识库上传一个txt文件，可以用下面附件中的。自定义分割，分割标记为\n\n。embedding和rerank我选择了bce的，都是运行在xinference上。高精度-混合搜索。这时topk保持默认的3。
  3. 在chatbot中添加知识库。最重要一步来了，chatbot页面，修改知识库，topk改为1。
  4. 回到知识库，测试页面。随便输点什么，点测试，右边会闪下，下面recents会新增一条，还有日志：
pgvector-1    | 2024-05-27 16:02:11.622 UTC [15031] ERROR:  relation "embedding_vector_index_19b3d0de_5efd_46d0_a74e_9f19b6bd951b_nod" does not exist at character 17053
pgvector-1    | 2024-05-27 16:02:11.622 UTC [15031] STATEMENT:  SELECT meta, text, embedding <=> '[0.01672604118639007, 0.014439345314756559, 0.01530501150914625, 0.02549769352839403, -0.06947399664927052, -0.030314819839635448, 0.00847174039641705, -0.0252105649164462, 0.09150560185832687, 0.06796652067946418, 0.003746830852401398, 0.0225697420182749, 0.11625115555135326, -0.008024675758981872, -0.011151345429179537, 0.04210279502807976, -0.013978434704626334, -0.024566402620209773, 0.023689674176296187, 0.04349188872296763, -0.006467775897202232, 0.04668087132388973, 0.031365521202858924, 0.01361495440548638, 0.04893135644255653, -0.007923617015246603, -0.005683782035865083, 0.04474582143545914, 0.01860995960290949, -0.00036008280528926687, -0.03489530453561959, -0.01380581779098295, 0.02980687837088363, 0.015871826534359854, -0.01881160584115801, 0.041841827267211765, 0.009256710283810862, -0.004263120231037658, 0.0024838147180232997, -0.031582947770786934, -0.02212635610500367, 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-0.04661148406689963, -0.000872647970474645, -0.04591032855447662, -0.001210926913615757, 0.013546456561553642, 0.06921698887198356, 0.031781181643127425, 0.0183652117559755, -0.01378934362598647]' AS distance FROM embedding_Vector_index_19b3d0de_5efd_46d0_a74e_9f19b6bd951b_Node ORDER BY distance LIMIT 1
api-1         | Exception in thread Thread-45 (embedding_search):
api-1         | Traceback (most recent call last):
api-1         |   File "/usr/local/lib/python3.10/threading.py", line 1016, in _bootstrap_inner
api-1         |     self.run()
api-1         |   File "/usr/local/lib/python3.10/threading.py", line 953, in run
api-1         |     self._target(*self._args, **self._kwargs)
api-1         |   File "/app/api/core/rag/datasource/retrieval_service.py", line 121, in embedding_search
api-1         |     documents = vector.search_by_vector(
api-1         |   File "/app/api/core/rag/datasource/vdb/vector_factory.py", line 226, in search_by_vector
api-1         |     return self._vector_processor.search_by_vector(query_vector, **kwargs)
api-1         |   File "/app/api/core/rag/datasource/vdb/pgvector/pgvector.py", line 135, in search_by_vector
api-1         |     cur.execute(
api-1         | psycopg2.errors.UndefinedTable: relation "embedding_vector_index_19b3d0de_5efd_46d0_a74e_9f19b6bd951b_nod" does not exist
api-1         | LINE 1: ...17559755, -0.01378934362598647]' AS distance FROM embedding_...
api-1         |                                                              ^
api-1         |

fh21_ask_test.txt

✔️ Expected Behavior

期望正常检索知识库

❌ Actual Behavior

异常了

Originally created by @wencan on GitHub (May 27, 2024). ### Self Checks - [X] This is only for bug report, if you would like to ask a question, please head to [Discussions](https://github.com/langgenius/dify/discussions/categories/general). - [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] Please do not modify this template :) and fill in all the required fields. ### Dify version 0.6.8 ### Cloud or Self Hosted Self Hosted (Docker), Self Hosted (Source) ### Steps to reproduce 1. docker compose 在本地运行dify。vector数据库选pgvector。 2. 知识库上传一个txt文件，可以用下面附件中的。自定义分割，分割标记为\n\n。embedding和rerank我选择了bce的，都是运行在xinference上。高精度-混合搜索。这时topk保持默认的3。 3. 在chatbot中添加知识库。最重要一步来了，chatbot页面，修改知识库，topk改为1。 4. 回到知识库，测试页面。随便输点什么，点测试，右边会闪下，下面recents会新增一条，还有日志： ``` pgvector-1 | 2024-05-27 16:02:11.622 UTC [15031] ERROR: relation "embedding_vector_index_19b3d0de_5efd_46d0_a74e_9f19b6bd951b_nod" does not exist at character 17053 pgvector-1 | 2024-05-27 16:02:11.622 UTC [15031] STATEMENT: SELECT meta, text, embedding <=> '[0.01672604118639007, 0.014439345314756559, 0.01530501150914625, 0.02549769352839403, -0.06947399664927052, -0.030314819839635448, 0.00847174039641705, -0.0252105649164462, 0.09150560185832687, 0.06796652067946418, 0.003746830852401398, 0.0225697420182749, 0.11625115555135326, -0.008024675758981872, -0.011151345429179537, 0.04210279502807976, -0.013978434704626334, -0.024566402620209773, 0.023689674176296187, 0.04349188872296763, -0.006467775897202232, 0.04668087132388973, 0.031365521202858924, 0.01361495440548638, 0.04893135644255653, -0.007923617015246603, -0.005683782035865083, 0.04474582143545914, 0.01860995960290949, -0.00036008280528926687, -0.03489530453561959, -0.01380581779098295, 0.02980687837088363, 0.015871826534359854, -0.01881160584115801, 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-0.017679315032591, -0.030266040888544052, -0.031529646317280315, -0.03509819874611614, -0.017571978243390116, -0.029197266279465988, 0.006636753667891024, -0.04661148406689963, -0.000872647970474645, -0.04591032855447662, -0.001210926913615757, 0.013546456561553642, 0.06921698887198356, 0.031781181643127425, 0.0183652117559755, -0.01378934362598647]' AS distance FROM embedding_Vector_index_19b3d0de_5efd_46d0_a74e_9f19b6bd951b_Node ORDER BY distance LIMIT 1 api-1 | Exception in thread Thread-45 (embedding_search): api-1 | Traceback (most recent call last): api-1 | File "/usr/local/lib/python3.10/threading.py", line 1016, in _bootstrap_inner api-1 | self.run() api-1 | File "/usr/local/lib/python3.10/threading.py", line 953, in run api-1 | self._target(*self._args, **self._kwargs) api-1 | File "/app/api/core/rag/datasource/retrieval_service.py", line 121, in embedding_search api-1 | documents = vector.search_by_vector( api-1 | File "/app/api/core/rag/datasource/vdb/vector_factory.py", line 226, in search_by_vector api-1 | return self._vector_processor.search_by_vector(query_vector, **kwargs) api-1 | File "/app/api/core/rag/datasource/vdb/pgvector/pgvector.py", line 135, in search_by_vector api-1 | cur.execute( api-1 | psycopg2.errors.UndefinedTable: relation "embedding_vector_index_19b3d0de_5efd_46d0_a74e_9f19b6bd951b_nod" does not exist api-1 | LINE 1: ...17559755, -0.01378934362598647]' AS distance FROM embedding_... api-1 | ^ api-1 | ``` [fh21_ask_test.txt](https://github.com/langgenius/dify/files/15458028/fh21_ask_test.txt) ### ✔️ Expected Behavior 期望正常检索知识库 ### ❌ Actual Behavior 异常了
yindo added the 🐞 bug label 2026-02-21 18:01:34 -05:00
yindo closed this issue 2026-02-21 18:01:34 -05:00
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Reference: langgenius/dify#3750
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