Update app.py

app.py

@@ -5,10 +5,15 @@ 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 firebase_admin
+from firebase_admin import db, credentials
+import datetime
+import uuid
 # Load environment variables
 load_dotenv()
-
+# authenticate to firebase
+cred = credentials.Certificate("redfernstech-fd8fe-firebase-adminsdk-g9vcn-0537b4efd6.json")
+firebase_admin.initialize_app(cred, {"databaseURL": "https://redfernstech-fd8fe-default-rtdb.firebaseio.com/"})
 # Configure the Llama index settings
 Settings.llm = HuggingFaceInferenceAPI(
     model_name="meta-llama/Meta-Llama-3-8B-Instruct",
@@ -98,6 +103,35 @@ def predict(message, history):
     response = handle_query(message)
     response_with_logo = f'<div class="response-with-logo">{logo_html}<div class="response-text">{response}</div></div>'
     return response_with_logo
+def save_chat_message(session_id, message_data):
+    ref = db.reference(f'/chat_history/{session_id}')  # Use the session ID to save chat data
+    ref.push().set(message_data)
+
+# Define your Gradio chat interface function (replace with your actual logic)
+def chat_interface(message, history):
+    try:
+        # Generate a unique session ID for this chat session
+        session_id = str(uuid.uuid4())
+
+        # Process the user message and generate a response (your chatbot logic)
+        response = handle_query(message)
+
+        # Capture the message data
+        message_data = {
+            "sender": "user",
+            "message": message,
+            "response": response,
+            "timestamp": datetime.datetime.now().isoformat()  # Use a library like datetime
+        }
+
+        # Call the save function to store in Firebase with the generated session ID
+        save_chat_message(session_id, message_data)
+
+        # Return the bot response
+        return response
+    except Exception as e:
+        return str(e)
+
 # Custom CSS for styling
 css = '''
   .circle-logo {
@@ -109,13 +143,11 @@ css = '''
   margin-right: 10px;
   vertical-align: middle;
 }
-
 .circle-logo img {
   width: 100%;
   height: 100%;
   object-fit: cover;
 }
-
 .response-with-logo {
   display: flex;
   align-items: center;
@@ -127,7 +159,7 @@ footer {
   }
 label.svelte-1b6s6s {display: none}
 '''
-gr.ChatInterface(predict,
+gr.ChatInterface(chat_interface,
                  css=css,
                  description="FernAI",
                  clear_btn=None, undo_btn=None, retry_btn=None,