update space

app.py

@@ -11,11 +11,16 @@ from werkzeug.security import generate_password_hash, check_password_hash
 from utils import PoultryFarmBot, llama3_response
 from chatbot_interface import build_chatbot_interface  # Importing chatbot interface function
 from transformers import AutoModelForCausalLM, AutoTokenizer
+from flask import Flask, render_template, request, redirect, url_for, session
 
 # Setup logging for better monitoring
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
 logger = logging.getLogger(__name__)
 
+# Flask app setup
+app = Flask(__name__)
+app.secret_key = os.environ.get("SECRET_KEY", "default_secret_key")
+
 # MongoDB Setup for logging and audit
 MONGO_URI = os.environ.get("MONGO_URI")
 if not MONGO_URI:
@@ -106,77 +111,36 @@ def authenticate_user(username, password):
     else:
         return False, None
 
-# Gradio authentication interface
-def build_auth_interface():
-    """
-    Build the authentication interface for the chatbot.
-
-    Returns:
-        gr.Blocks: Gradio Blocks object representing the authentication interface.
-    """
-    try:
-        logger.info("Building Gradio authentication interface.")
-        with gr.Blocks(theme=gr.themes.Base()) as auth_interface:
-            gr.Markdown("# 🐔 Poultry Management Chatbot - Authentication")
-            gr.Markdown("Please enter your credentials to access the poultry management chatbot.")
-
-            username = gr.Textbox(
-                label="Username",
-                placeholder="Enter your username",
-                lines=1,
-                elem_id="username-input",
-            )
-            password = gr.Textbox(
-                label="Password",
-                placeholder="Enter your password",
-                type="password",
-                lines=1,
-                elem_id="password-input",
-            )
-            auth_button = gr.Button(
-                "Login",
-                variant="primary",
-                elem_id="login-button"
-            )
-            output_box = gr.Textbox(
-                label="Authentication Status",
-                placeholder="Status will appear here...",
-                interactive=False,
-                lines=3,
-                elem_id="auth-output",
-            )
-
-            # Function to authenticate user and navigate to chatbot if successful
-            def handle_login(username, password):
-                success, user = authenticate_user(username, password)
-                if success:
-                    logger.info("Authentication successful. Redirecting to chatbot.")
-                    return "Authentication successful. Redirecting to chatbot...", user
-                else:
-                    logger.warning("Authentication failed. Incorrect username or password.")
-                    return "Authentication failed. Please check your username and password.", None
-
-            auth_button.click(fn=handle_login, inputs=[username, password], outputs=[output_box])
-        logger.info("Authentication interface built successfully.")
-        return auth_interface
-    except Exception as e:
-        logger.error(f"Error building authentication interface: {e}")
-        raise RuntimeError("Could not build the authentication interface. Please check the configuration.")
-
-# Launch the Gradio interface
+# Flask routes for AdminLTE authentication
+@app.route('/', methods=['GET', 'POST'])
+def login():
+    if request.method == 'POST':
+        username = request.form['username']
+        password = request.form['password']
+        success, user = authenticate_user(username, password)
+        if success:
+            logger.info("Authentication successful for user: %s", username)
+            session['username'] = username
+            return redirect(url_for('chatbot'))
+        else:
+            logger.warning("Authentication failed for user: %s", username)
+            return render_template('login.html', error="Invalid username or password.")
+    return render_template('login.html')
+
+@app.route('/chatbot')
+def chatbot():
+    if 'username' not in session:
+        return redirect(url_for('login'))
+    username = session['username']
+    logger.info("Launching Gradio chatbot interface for user: %s", username)
+    chatbot_interface = build_chatbot_interface({'username': username})
+    return chatbot_interface.launch(inline=True, share=True)
+
+# Launch the Flask application
 if __name__ == "__main__":
     try:
-        logger.info("Launching Gradio authentication interface.")
-        auth_interface = build_auth_interface()
-
-        def launch_chatbot(auth_output, user):
-            if "successful" in auth_output.lower() and user is not None:
-                logger.info("Launching Gradio chatbot interface.")
-                chatbot_interface = build_chatbot_interface(user)
-                chatbot_interface.queue().launch(debug=True, share=True)
-
-        # Launch the authentication interface with callback to chatbot on success
-        auth_interface.queue().launch(debug=True, share=True, success=launch_chatbot)
+        logger.info("Launching Flask server for AdminLTE authentication.")
+        app.run(host='0.0.0.0', port=5000, debug=True)
     except Exception as e:
-        logger.error(f"Failed to launch Gradio interface: {e}")
-        raise RuntimeError("Could not launch the Gradio interface. Please check the application setup.")
+        logger.error(f"Failed to launch Flask server: {e}")
+        raise RuntimeError("Could not launch the Flask server. Please check the application setup.")

utils.py

@@ -72,7 +72,7 @@ def llama3_response(user_input, tokenizer, model):
         logger.error(f"Error generating response: {str(e)}")
         return f"Error generating response: {str(e)}"
 
-def chatbot_response(image, text, username, password):
+def chatbot_response(image, text, username, password, bot, tokenizer, model):
     """
     Handle user input and generate appropriate responses.
 
@@ -81,6 +81,9 @@ def chatbot_response(image, text, username, password):
         text (str): Text input for general queries.
         username (str): Username for authentication.
         password (str): Password for authentication.
+        bot (PoultryFarmBot): Instance of PoultryFarmBot for handling disease detection.
+        tokenizer (AutoTokenizer): Tokenizer for generating responses.
+        model (AutoModelForCausalLM): Pre-trained language model for generating responses.
 
     Returns:
         str: Response generated by the chatbot.