Update app.py

app.py

@@ -5,6 +5,11 @@ from llama_index.core import StorageContext, load_index_from_storage, VectorStor
 from llama_index.llms.huggingface import HuggingFaceInferenceAPI
 from llama_index.embeddings.huggingface import HuggingFaceEmbedding
 from sentence_transformers import SentenceTransformer
+import csv
+import os
+
+PERSIST_DIR = "history"  # Replace with your actual directory path
+CSV_FILE = os.path.join(PERSIST_DIR, "chat_history.csv")
 
 # Load environment variables
 load_dotenv()
@@ -41,6 +46,9 @@ def data_ingestion_from_directory():
     index.storage_context.persist(persist_dir=PERSIST_DIR)
 
 def handle_query(query):
+    # Ensure the directory exists or create it
+    os.makedirs(PERSIST_DIR, exist_ok=True)
+
     chat_text_qa_msgs = [
         (
             "user",
@@ -60,7 +68,7 @@ def handle_query(query):
     storage_context = StorageContext.from_defaults(persist_dir=PERSIST_DIR)
     index = load_index_from_storage(storage_context)
 
-    # Use chat history to enhance response
+    # Use chat history to enhance response (assuming current_chat_history is defined)
     context_str = ""
     for past_query, response in reversed(current_chat_history):
         if past_query.strip():
@@ -79,6 +87,11 @@ def handle_query(query):
     # Update current chat history
     current_chat_history.append((query, response))
 
+    # Save chat history to CSV
+    with open(CSV_FILE, 'a', newline='', encoding='utf-8') as file:
+        csv_writer = csv.writer(file)
+        csv_writer.writerow([query, response])
+
     return response
 
 # Example usage: Process PDF ingestion from directory