AI indexing completed

main.py

@@ -4,16 +4,12 @@ sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
 from fastapi import FastAPI, HTTPException
 from fastapi.middleware.cors import CORSMiddleware
 from pydantic import BaseModel
-from utils import search, load_embedded_data
+from utils import  load_embedded_data, load_documents_from_directory, create_vector_store, save_embedded_data
+from search import search_and_summarize
 from data_ingest import load_data
 
 app = FastAPI()
 
-# Initialize global variables for FAISS index and vector store
-try:
-    vector_store = load_embedded_data()
-except Exception as e:
-    vector_store = None
 
 # Define allowed origins for CORS
 origins = [
@@ -37,19 +33,21 @@ class SearchRequest(BaseModel):
 
 @app.get("/load_documents")
 def load_documents(directory: str):
-    global vector_store
     
-    # Load documents using the utility function
-    vector_store = load_data(directory)
+    # loading the documents from the directory
+    documents, docs_id, num_pages = load_documents_from_directory(directory)
+    # embedding the documents
+    embed_db = create_vector_store(documents, docs_id, num_pages)
+    # saving the embedded data
+    status = save_embedded_data(embed_db)
     
     return {"status": "Documents loaded successfully"}
 
-@app.get("/search")
+@app.post("/search")
 def search(request: SearchRequest):
-    global vector_store
     
     # Perform search using the utility function
-    results = search(vector_store, request.query)
+    results = search_and_summarize(request.query)
     
     return {"results": results}