How can I remove unwanted metadata from chatbot replies stored in Pinecone?

Below is an overview of why you’re seeing this metadata (and how to address it):

What’s Happening

When you enabled the vector store extension for writing session messages, the node that writes into Pinecone started adding extra information (the metadata) along with the chat message content. This metadata is useful when you need additional context for retrieval (for example, indicating the data source or text location). When the vector store extension is disabled, the metadata isn’t written, so it disappears from your downstream payload.

What You Can Do

1. Review Your Insertion Configuration:
   Check how you’re structuring the data before inserting it into the vector store. If you’re using a function or directly writing JSON, you might be unintentionally including metadata. For example, if your code or node configuration inserts a document like this:

   JAVASCRIPTCopied
   {
     metadata: {
       source: 'blob',
       blobType: 'application/json',
       loc: { lines: { from: 1, to: 1 } }
     },
     pageContent: 'Hello! How can I assist you today?'
   }

   and you don’t need those extra fields, consider removing or adjusting them before insertion.

2. Filter Metadata Downstream:
   If you need the metadata for other purposes (like filtering or debugging) but don’t want it shown in your chat responses, you can add a transformation node (such as a Function node) in your workflow to remove or ignore the metadata field. For example:

   JAVASCRIPTCopied
   // Function node to strip out metadata
   return items.map(item => {
     return {
       json: {
         pageContent: item.json.pageContent
         // add any other fields you need to keep
       }
     };
   });

3. Use a Different Field for Context (if needed):
   If you’re using metadata to store session-specific details, consider using a more specific key or namespace for that data. That way, you can structure your downstream nodes to extract the clean chat content (e.g., from pageContent) without mixing it with technical metadata details.

Final Thoughts

The appearance of metadata is a side effect of the vector store insertion—that extension is designed to store additional context to help with subsequent retrieval. If this information isn’t useful for your chat responses, strip it out before you pass the data to the chat model or render it in your UI.

By adjusting either the data you write to Pinecone or filtering it out later in your workflow, you can ensure that your chatbot responses appear clean and focused on the dialogue content.