Chroma().similarity_search_with_score(query=t, k=2) with asyncio.create_task() and an error

[lishaozheng]

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Example Code

product_result.append(asyncio.create_task(product_docsearchs.similarity_search_with_score(query=t, k=2)))

error:
[error]get_vectordb_docs：a coroutine was expected, got [(Document(metadata={'source': 'Chatgpt/data/_2282520061259682545424211/product0/_2282520061259682545424211/product.txt'}, page_content='XXXXXXXXXXXXXXXXXXXXXX'), 0.8398316502571106), (Document(metadata={'source': 'Chatgpt/data/_2282520061259682545424211/product0/_2282520061259682545424211/product.txt'}, page_content='XXXXXXXXXXXXXXXXXXXXXX'), 1.0837570428848267)]
2024-11-20 16:31:08,918 - ERROR - Traceback (most recent call last):
  File "G:\LiProbject\project\loading_server\AIX_Chatgpt\Chatgpt\Gpt_module\chatgpt_module.py", line 538, in get_vectordb_docs
    asyncio.create_task(
  File "I:\ProgramData\anaconda3\envs\ivreal_agi\lib\asyncio\tasks.py", line 337, in create_task
    task = loop.create_task(coro)
  File "I:\ProgramData\anaconda3\envs\ivreal_agi\lib\asyncio\base_events.py", line 433, in create_task
    task = tasks.Task(coro, loop=self, name=name)
TypeError: a coroutine was expected, got [(Document(metadata={'source': 'Chatgpt/data/_2282520061259682545424211/product0/_2282520061259682545424211/product.txt'}, page_content='XXXXXXXXXXXXXXXXXX'), 0.8398316502571106), (Document(metadata={'source': 'Chatgpt/data/_2282520061259682545424211/product0/_2282520061259682545424211/product.txt'}, page_content='XXXXXXXXXXXXXXXXXXXXXXXXXXX'), 1.0837570428848267)]

Description

In FaskAPI, concurrency is handled with asyncio.create_task(). For example, openai has a from openai import AsyncOpenAI, Support await self.openai.chat.com pletions. Create, and then the Chroma vector database, how to use this asyncio similarity_search_with_score. Create_task ()

System Info

langchian-0.2.15

[lishaozheng]