id = match.metadata["id"]KeyError: 'id'I am getting the above error when i call query on

Please stand by @zzzz7902 as I search the knowledge base. We are experiencing especially high traffic right now and might take longer than usual. :wave:

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Hmm, I don't know enough to give you a confident answer yet. However, you can refer to the LlamaIndex documentation and examples for more information on how to use Pinecone with LlamaIndex:

• Pinecone Reader Example (https://gpt-index.readthedocs.io/en/latest/examples/data_connectors/PineconeDemo.html)
• Pinecone Vector Store (https://gpt-index.readthedocs.io/en/latest/reference/storage/vector_store.html)
• City Analysis Example (https://gpt-index.readthedocs.io/en/latest/examples/composable_indices/city_analysis/PineconeDemo-CityAnalysis.html)

These resources might help you understand how to properly use Pinecone with LlamaIndex and avoid the KeyError you're encountering.
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Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
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@kapa.ai what purpose does id = match.metadata["id"] have in query()?

Let me check the knowledge base for you. One moment! :books:

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I'm sorry, but I cannot find any reference to id = match.metadata["id"] in the provided information extracts. As an AI, I can only provide information based on the given extracts. If you have any other questions related to LlamaIndex, feel free to ask, and I'll do my best to help you based on the available information.
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Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
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@kapa.ai in function query() in vector_store/pinecone.py, for match in response.matches:
text = match.metadata[self._text_key]
id = match.id
in what cases will match.id not be there?

Let me check the knowledge base for you. One moment! :books:

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Based on the information extracts provided, there is no direct reference to the query() function in vector_store/pinecone.py. However, there is a reference to the query() function in the Vector Store documentation (https://gpt-index.readthedocs.io/en/latest/reference/storage/vector_store.html):



In general, the query() function is used to find the top k most similar nodes in the vector store. However, without the specific implementation details of the query() function in vector_store/pinecone.py, I cannot provide information on when match.id might not be present.

If you have any other questions related to LlamaIndex, feel free to ask, and I'll do my best to help you based on the available information.
----------------------
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
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@kapa.ai the implementation of query of class PineconeVectorStore(VectorStore):

Let me check the knowledge base for you. One moment! :books:

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I apologize for the confusion earlier. Based on the provided information extracts, there is no direct reference to the implementation of the query() function for the PineconeVectorStore class. As an AI, I can only provide information based on the given extracts.

However, you can refer to the LlamaIndex documentation and examples for more information on how to use Pinecone with LlamaIndex:

• Pinecone Reader Example (https://gpt-index.readthedocs.io/en/latest/examples/data_connectors/PineconeDemo.html)
• Pinecone Vector Store (https://gpt-index.readthedocs.io/en/latest/reference/storage/vector_store.html)
• City Analysis Example (https://gpt-index.readthedocs.io/en/latest/examples/composable_indices/city_analysis/PineconeDemo-CityAnalysis.html)

These resources might help you understand how to properly use Pinecone with LlamaIndex. If you have any other questions related to LlamaIndex, feel free to ask, and I'll do my best to help you based on the available information.
----------------------
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
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this is fixed by updating llamaindex