update space

app.py

@@ -20,6 +20,35 @@ dotenv.load_dotenv()
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
 logger = logging.getLogger(__name__)
 
+# MongoDB Setup for logging and audit
+MONGO_URI = os.getenv("MONGO_URI")
+logger.info("Connecting to MongoDB.")
+client = MongoClient(MONGO_URI)
+db = client.poultry_farm  # Connect to the 'poultry_farm' database
+enquiries_collection = db.enquiries  # Collection to store farmer enquiries
+users_collection = db.users  # Collection to store user credentials
+logs_collection = db.logs  # Collection to store application logs
+
+def log_to_db(level, message):
+    log_entry = {
+        "level": level,
+        "message": message,
+        "timestamp": datetime.utcnow()
+    }
+    logs_collection.insert_one(log_entry)
+
+# Override logger methods to also log to MongoDB
+class MongoHandler(logging.Handler):
+    def emit(self, record):
+        log_entry = self.format(record)
+        log_to_db(record.levelname, log_entry)
+
+mongo_handler = MongoHandler()
+mongo_handler.setLevel(logging.INFO)
+formatter = logging.Formatter('%(asctime)s - %(levelname)s - %(message)s')
+mongo_handler.setFormatter(formatter)
+logger.addHandler(mongo_handler)
+
 # Hugging Face token setup
 tok = os.getenv('HF_TOKEN')
 if tok:
@@ -29,14 +58,6 @@ if tok:
 else:
     logger.warning("Hugging Face token not found in environment variables.")
 
-# MongoDB Setup
-MONGO_URI = os.getenv("MONGO_URI")
-logger.info("Connecting to MongoDB.")
-client = MongoClient(MONGO_URI)
-db = client.poultry_farm  # Connect to the 'poultry_farm' database
-enquiries_collection = db.enquiries  # Collection to store farmer enquiries
-users_collection = db.users  # Collection to store user credentials
-
 # GPU Setup for TensorFlow
 logger.info("TensorFlow version: %s", tf.__version__)
 logger.info("Eager execution: %s", tf.executing_eagerly())
@@ -348,65 +369,6 @@ def build_gradio_interface():
         gr.Blocks: Gradio Blocks object representing the chatbot interface.
     """
     logger.info("Building Gradio interface.")
-    with gr.Blocks(theme=gr.themes.Soft(primary_hue="green", neutral_hue="slate")) as chatbot_interface:
+    with gr.Blocks(theme=gr.themes.Base()):
         gr.Markdown("# 🐔 Poultry Management Chatbot")
-        gr.Markdown("This chatbot helps you manage your poultry. Upload an image for disease detection or just ask questions!")
-
-        with gr.Row():
-            with gr.Column(scale=1):
-                fecal_image = gr.Image(
-                    label="Upload Image of Poultry Feces (Optional)",
-                    type="numpy",
-                    elem_id="image-upload",
-                    show_label=True,
-                )
-            with gr.Column(scale=2):
-                user_input = gr.Textbox(
-                    label="Ask a question",
-                    placeholder="Ask about poultry management...",
-                    lines=3,
-                    elem_id="user-input",
-                )
-                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",
-                )
-
-        output_box = gr.Textbox(
-            label="Response",
-            placeholder="Response will appear here...",
-            interactive=False,
-            lines=10,
-            elem_id="output-box",
-        )
-
-        submit_button = gr.Button(
-            "Submit",
-            variant="primary",
-            elem_id="submit-button"
-        )
-        # Connect the submit button to the chatbot response function
-        submit_button.click(
-            fn=chatbot_response,
-            inputs=[fecal_image, user_input, username, password],
-            outputs=[output_box]
-        )
-    logger.info("Gradio interface built successfully.")
-    return chatbot_interface
-
-# Launch the Gradio interface
-if __name__ == "__main__":
-    logger.info("Launching Gradio interface.")
-    interface = build_gradio_interface()
-    # Launch the interface with queuing enabled for concurrent requests
-    interface.queue().launch(debug=True, share=True)
-    logger.info("Gradio interface launched.")
+        gr.Markdown("Welcome! This chatbot helps you manage your poultry with ease. You