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version. 0.15.0.full
we configured the embeddig model with uid:jina-embeddings-v3
why ragflow send the request to model:jina-embeddings-v3-1-0
This issue is not always happened, when we import one pdf in which there is one large table occupaning more than one pages, it might happen.
logs:
2025-02-14 15:02:50,784 INFO 21 set_progress(0bb1afeaea9f11efbed00242ac150003), progress: -1, progress_msg: Page(145~157): [ERROR]Generate embedding error:Error code: 400 - {'detail': '[address=0.0.0.0:54878, pid=140] Model not found, uid: jina-embeddings-v3-1-0'}
2025-02-14 15:02:50,797 ERROR 21 Generate embedding error:Error code: 400 - {'detail': '[address=0.0.0.0:54878, pid=140] Model not found, uid: jina-embeddings-v3-1-0'}
Traceback (most recent call last):
File "/ragflow/rag/svr/task_executor.py", line 461, in do_handle_task
token_count, vector_size = embedding(chunks, embedding_model, task_parser_config, progress_callback)
File "/ragflow/rag/svr/task_executor.py", line 319, in embedding
vts, c = mdl.encode(tts[i: i + batch_size])
File "<@beartype(api.db.services.llm_service.LLMBundle.encode) at 0x7f6f17462680>", line 31, in encode
File "/ragflow/api/db/services/llm_service.py", line 236, in encode
embeddings, used_tokens = self.mdl.encode(texts)
File "<@beartype(rag.llm.embedding_model.XinferenceEmbed.encode) at 0x7f6f1767d2d0>", line 31, in encode
File "/ragflow/rag/llm/embedding_model.py", line 297, in encode
res = self.client.embeddings.create(input=texts[i:i + batch_size], model=self.model_name)
File "/ragflow/.venv/lib/python3.10/site-packages/openai/resources/embeddings.py", line 125, in create
return self._post(
File "/ragflow/.venv/lib/python3.10/site-packages/openai/_base_client.py", line 1260, in post
return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))
File "/ragflow/.venv/lib/python3.10/site-packages/openai/_base_client.py", line 937, in request
return self._request(
File "/ragflow/.venv/lib/python3.10/site-packages/openai/_base_client.py", line 1041, in _request
raise self._make_status_error_from_response(err.response) from None
openai.BadRequestError: Error code: 400 - {'detail': '[address=0.0.0.0:54878, pid=140] Model not found, uid: jina-embeddings-v3-1-0'}
2025-02-14 15:02:50,799 INFO 21 set_progress(0bb1afeaea9f11efbed00242ac150003), progress: -1, progress_msg: [ERROR]handle_task got exception, please check log
2025-02-14 15:02:50,802 ERROR 21 handle_task got exception for task {"id": "0bb1afeaea9f11efbed00242ac150003", "doc_id": "0830dcecea9f11ef86a60242ac150003", "from_page": 144, "to_page": 156, "retry_count": 0, "kb_id": "b8d7a210e9af11ef81ae0242ac150003", "parser_id": "naive", "parser_config": {"auto_keywords": 0, "auto_questions": 0, "raptor": {"use_raptor": false}, "chunk_token_num": 128, "delimiter": "\n!?;\u3002\uff1b\uff01\uff1f", "layout_recognize": true, "html4excel": false}, "name": "29510-gf0_clean.pdf", "type": "pdf", "location": "29510-gf0_clean.pdf", "size": 2964556, "tenant_id": "8844566eb8f111ef82890242ac150006", "language": "English", "embd_id": "jina-embeddings-v3@Xinference", "pagerank": 0, "img2txt_id": "qwen-vl-max@Tongyi-Qianwen", "asr_id": "paraformer-realtime-8k-v1@Tongyi-Qianwen", "llm_id": "qwen2.5-instruct@Xinference", "update_time": 173[515428883}](mailto:515428883%7d%0dTraceback%20(most%20)
[Traceback (most ](mailto:515428883%7d%0dTraceback%20(most%20)ecent call last):
File "/ragflow/rag/svr/task_executor.py", line 511, in handle_task
do_handle_task(task)
File "/ragflow/rag/svr/task_executor.py", line 461, in do_handle_task
token_count, vector_size = embedding(chunks, embedding_model, task_parser_config, progress_callback)
File "/ragflow/rag/svr/task_executor.py", line 319, in embedding
vts, c = mdl.encode(tts[i: i + batch_size])
File "<@beartype(api.db.services.llm_service.LLMBundle.encode) at 0x7f6f17462680>", line 31, in encode
File "/ragflow/api/db/services/llm_service.py", line 236, in encode
embeddings, used_tokens = self.mdl.encode(texts)
File "<@beartype(rag.llm.embedding_model.XinferenceEmbed.encode) at 0x7f6f1767d2d0>", line 31, in encode
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