Added codebase search and retrieval to Vectorstore

Summary indexing: Added functionality to embed and index file summaries from file_summaries.json in Pinecone
Vector search: Implemented semantic search to find the top 5 most relevant files for a query
Content retrieval: Added method to fetch full file content from file_content.json
API endpoints:
/getFileSummaries - Retrieves all file summaries
/getFileContent - Fetches file content by path
/getRawFileContent - Returns content as plain text to avoid JSON parsing errors
Error handling: Added comprehensive error handling and debugging throughout
Initialization: Implemented proper async initialization sequence with verification
Performance: Added streaming for large files to improve memory efficiency
Testing: Added automated test queries to validate functionality

1 files changed, 7 insertions, 1 deletions

diff --git a/src/client/views/nodes/chatbot/tools/RAGTool.ts b/src/client/views/nodes/chatbot/tools/RAGTool.ts
index 90b803d21..af44de520 100644
--- a/src/client/views/nodes/chatbot/tools/RAGTool.ts
+++ b/src/client/views/nodes/chatbot/tools/RAGTool.ts
@@ -12,6 +12,12 @@ const ragToolParams = [
         description: "A detailed prompt representing an ideal chunk to embed and compare against document vectors to retrieve the most relevant content for answering the user's query.",
         required: true,
     },
+    {
+        name: 'doc_ids',
+        type: 'string[]',
+        description: 'An optional array of document IDs to retrieve chunks from. If you want to retrieve chunks from all documents, leave this as an empty array: [] (DO NOT LEAVE THIS EMPTY).',
+        required: false,
+    },
 ] as const;
 
 type RAGToolParamsType = typeof ragToolParams;
@@ -69,7 +75,7 @@ export class RAGTool extends BaseTool<RAGToolParamsType> {
     }
 
     async execute(args: ParametersType<RAGToolParamsType>): Promise<Observation[]> {
-        const relevantChunks = await this.vectorstore.retrieve(args.hypothetical_document_chunk);
+        const relevantChunks = await this.vectorstore.retrieve(args.hypothetical_document_chunk, undefined, args.doc_ids ?? undefined);
         const formattedChunks = await this.getFormattedChunks(relevantChunks);
         return formattedChunks;
     }