added Multithreading

app.py

@@ -5,18 +5,21 @@ from modules.validation import calculate_truthfulness_score
 from modules.knowledge_graph import search_kg
 from dotenv import load_dotenv
 import os
+from concurrent.futures import ThreadPoolExecutor
 
 # Load environment variables from .env file
 load_dotenv()
 
-
 # Constants
-KG_INDEX_PATH="KG/news_category_index.faiss"
-KG_DATASET_PATH="KG/News_Category_Dataset_v3.json"
+KG_INDEX_PATH = "KG/news_category_index.faiss"
+KG_DATASET_PATH = "KG/News_Category_Dataset_v3.json"
 SEARCH_API_KEY = os.getenv("SEARCH_API_KEY")
 SEARCH_BASE_URL = os.getenv("SEARCH_BASE_URL")
 SEARCH_MODEL = os.getenv("SEARCH_MODEL")
 
+# Initialize ThreadPoolExecutor
+executor = ThreadPoolExecutor(max_workers=2)
+
 # Function to process input and evaluate truthfulness
 def evaluate_news(news_input):
     # Display loading message
@@ -37,16 +40,13 @@ def evaluate_news(news_input):
         news_text = news_input
 
     try:
-        # Retrieve relevant info from FAISS knowledge graph
-        kg_content = search_kg(query=news_text, index_path=KG_INDEX_PATH, dataset_path=KG_DATASET_PATH)
+        # Run both search functions concurrently using ThreadPoolExecutor
+        future_kg = executor.submit(search_kg, news_text, KG_INDEX_PATH, KG_DATASET_PATH)
+        future_online = executor.submit(search_online, news_text, SEARCH_API_KEY, SEARCH_BASE_URL, SEARCH_MODEL)
 
-        # Search online for additional context
-        online_search_results = search_online(
-            query=news_text,
-            api_key=SEARCH_API_KEY,
-            base_url=SEARCH_BASE_URL,
-            model=SEARCH_MODEL
-        )
+        # Wait for the results of both tasks
+        kg_content = future_kg.result()
+        online_search_results = future_online.result()
 
         # Combine context from KG and online search
         context = online_search_results['message_content'] + '\n' + kg_content
@@ -98,4 +98,4 @@ with gr.Blocks() as demo:
     )
 
 # Launch Gradio App
-demo.launch()
+demo.launch()