ERROR Error executing verb "text_embed" in create_final_entities: list index out of range

[Ikaros-521]

17:20:01,456 openai._base_client DEBUG HTTP Request: POST http://127.0.0.1:3000/v1/embeddings "200 OK"
17:20:01,461 graphrag.llm.base.rate_limiting_llm INFO perf - llm.embedding "Process" with 0 retries took 1.562000000005355. input_tokens=176, output_tokens=0
17:20:01,463 datashaper.workflow.workflow ERROR Error executing verb "text_embed" in create_final_entities: list index out of range
Traceback (most recent call last):
  File "f:\GraphRAG-Ollama-UI\Miniconda3\lib\site-packages\datashaper\workflow\workflow.py", line 415, in _execute_verb
    result = await result
  File "F:\GraphRAG-Ollama-UI\graphrag\index\verbs\text\embed\text_embed.py", line 105, in text_embed
    return await _text_embed_in_memory(
  File "F:\GraphRAG-Ollama-UI\graphrag\index\verbs\text\embed\text_embed.py", line 130, in _text_embed_in_memory
    result = await strategy_exec(texts, callbacks, cache, strategy_args)
  File "F:\GraphRAG-Ollama-UI\graphrag\index\verbs\text\embed\strategies\openai.py", line 63, in run
    embeddings = _reconstitute_embeddings(embeddings, input_sizes)
  File "F:\GraphRAG-Ollama-UI\graphrag\index\verbs\text\embed\strategies\openai.py", line 172, in _reconstitute_embeddings
    embedding = raw_embeddings[cursor]
IndexError: list index out of range
17:20:01,464 graphrag.index.reporting.file_workflow_callbacks INFO Error executing verb "text_embed" in create_final_entities: list index out of range details=None
17:20:01,464 graphrag.index.run ERROR error running workflow create_final_entities
Traceback (most recent call last):
  File "F:\GraphRAG-Ollama-UI\graphrag\index\run.py", line 323, in run_pipeline
    result = await workflow.run(context, callbacks)
  File "f:\GraphRAG-Ollama-UI\Miniconda3\lib\site-packages\datashaper\workflow\workflow.py", line 369, in run
    timing = await self._execute_verb(node, context, callbacks)
  File "f:\GraphRAG-Ollama-UI\Miniconda3\lib\site-packages\datashaper\workflow\workflow.py", line 415, in _execute_verb
    result = await result
  File "F:\GraphRAG-Ollama-UI\graphrag\index\verbs\text\embed\text_embed.py", line 105, in text_embed
    return await _text_embed_in_memory(
  File "F:\GraphRAG-Ollama-UI\graphrag\index\verbs\text\embed\text_embed.py", line 130, in _text_embed_in_memory
    result = await strategy_exec(texts, callbacks, cache, strategy_args)
  File "F:\GraphRAG-Ollama-UI\graphrag\index\verbs\text\embed\strategies\openai.py", line 63, in run
    embeddings = _reconstitute_embeddings(embeddings, input_sizes)
  File "F:\GraphRAG-Ollama-UI\graphrag\index\verbs\text\embed\strategies\openai.py", line 172, in _reconstitute_embeddings
    embedding = raw_embeddings[cursor]
IndexError: list index out of range
17:20:01,464 graphrag.index.reporting.file_workflow_callbacks INFO Error running pipeline! details=None

[Ikaros-521]

更新同步最新版的源码后，暂时没有复现。 问题和 选用的llm embedding模型有关

[francis123455]

你好，请问logs.json记录的报错如下是什么问题： {"type": "error", "data": "Error executing verb \"text_embed\" in create_final_entities: list index out of range", "stack": "Traceback (most recent call last):\n File \"/home/ubuntu/anaconda3/envs/chatchat/lib/python3.10/site-packages/datashaper/workflow/workflow.py\", line 415, in _execute_verb\n result = await result\n File \"/home/ubuntu/GitProjects/graphrag-webui/graphrag/index/verbs/text/embed/text_embed.py\", line 105, in text_embed\n return await _text_embed_in_memory(\n File \"/home/ubuntu/GitProjects/graphrag-webui/graphrag/index/verbs/text/embed/text_embed.py\", line 130, in _text_embed_in_memory\n result = await strategy_exec(texts, callbacks, cache, strategy_args)\n File \"/home/ubuntu/GitProjects/graphrag-webui/graphrag/index/verbs/text/embed/strategies/openai.py\", line 62, in run\n embeddings = _reconstitute_embeddings(embeddings, input_sizes)\n File \"/home/ubuntu/GitProjects/graphrag-webui/graphrag/index/verbs/text/embed/strategies/openai.py\", line 171, in _reconstitute_embeddings\n embedding = raw_embeddings[cursor]\nIndexError: list index out of range\n", "source": "list index out of range", "details": null} {"type": "error", "data": "Error running pipeline!", "stack": "Traceback (most recent call last):\n File \"/home/ubuntu/GitProjects/graphrag-webui/graphrag/index/run.py\", line 320, in run_pipeline\n await inject_workflow_data_dependencies(workflow)\n File \"/home/ubuntu/GitProjects/graphrag-webui/graphrag/index/run.py\", line 256, in inject_workflow_data_dependencies\n table = await load_table_from_storage(f\"{id}.parquet\")\n File \"/home/ubuntu/GitProjects/graphrag-webui/graphrag/index/run.py\", line 242, in load_table_from_storage\n raise ValueError(msg)\nValueError: Could not find create_final_entities.parquet in storage!\n", "source": "Could not find create_final_entities.parquet in storage!", "details": null} 用的mistral和nomic-embed-text,之前使用利用graphrag包和ragtest目录在终端命令启动python -m graphrag.index --root ./ragtest是没问题的

[Ikaros-521]

Could not find create_final_entities.parquet in storage

Could not find create_final_entities.parquet in storage

有个配置需要 使能，才会生成这个parquet，具体哪个忘记了，可以看看官方文档

[francis123455]

        好的，谢谢，我再看看

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          Re: [Ikaros-521/GraphRAG-Ollama-UI] ERROR Error executing verb "text_embed" in create_final_entities: list index out of range (Issue #9)

Could not find create_final_entities.parquet in storage

Could not find create_final_entities.parquet in storage 有个配置需要 使能，才会生成这个parquet，具体哪个忘记了，可以看看官方文档

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[Ikaros-521]

好的，谢谢，我再看看 @. … ---- Replied Message ---- From @.> Date 8/20/2024 17:32 To @.> Cc @.> , @.> Subject Re: [Ikaros-521/GraphRAG-Ollama-UI] ERROR Error executing verb "text_embed" in create_final_entities: list index out of range (Issue #9) Could not find create_final_entities.parquet in storage Could not find create_final_entities.parquet in storage 有个配置需要 使能，才会生成这个parquet，具体哪个忘记了，可以看看官方文档 —Reply to this email directly, view it on GitHub, or unsubscribe.You are receiving this because you commented.Message ID: @.>

claim_extraction:
  enabled: true
  description: Any claims or facts that could be relevant to information discovery.
  max_gleanings: 0
  prompt: prompts/claim_extraction.txt
cluster_graph:
  max_cluster_size: 10
community_report:
  max_input_length: 8000
  max_length: 2000
  prompt: prompts/community_report.txt

前面这几个来着