Closed angelo-smartsheet closed 7 months ago
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Thank you for your suggestion, angelo-smartsheet. The idea of using a graph database like Neo4j instead of a vector database like Pinecone is indeed an interesting one. Graph databases can provide certain advantages in terms of data relationships and querying capabilities.
However, the current implementation of the gpt4-pdf-chatbot-langchain uses Pinecone, a vector database, which is particularly suited for machine learning applications. This is evident from the import statement import { PineconeStore } from 'langchain/vectorstores/pinecone';
and the usage of PineconeStore.fromExistingIndex
to create a vector store in the pages/api/chat.ts file.
Switching to a graph database would require significant changes to the codebase and the way data is stored and retrieved. It would also require a thorough evaluation to ensure that the performance and other benefits of a graph database outweigh the costs of such a transition.
While I can't make this change, I recommend creating a detailed proposal outlining the benefits and potential implementation strategy for this enhancement. This would provide a solid basis for the repository maintainers to consider this enhancement.
Please let me know if you need any further clarification or assistance.
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Some research out there says that a graph database can give more performance instead of a vector database. Would be cool if such a feature existed!
https://tomoro.ai/insights/graph-databases-as-rag-backends