Update app.py

app.py

@@ -144,47 +144,6 @@ Know how your message sounds and how to improve the tone of the message with Emo
 <div style='color: green;'>Developed by Hashir Ehtisham</div>
 """
 
-# Forum data
-posts = []
-comments = {}
-users = []
-
-def register_user(username):
-    if username not in users:
-        users.append(username)
-        return f"User '{username}' registered successfully."
-    return f"User '{username}' already registered."
-
-def submit_post(username, content, is_anonymous):
-    post_id = len(posts) + 1
-    posts.append({
-        'id': post_id,
-        'username': username,
-        'content': content,
-        'is_anonymous': is_anonymous
-    })
-    comments[post_id] = []
-    return "Post submitted successfully."
-
-def get_posts():
-    return pd.DataFrame(posts)
-
-def submit_comment(post_id, username, comment):
-    if post_id in comments:
-        comments[post_id].append({'username': username, 'comment': comment})
-        return "Comment added successfully."
-    return "Post not found."
-
-def get_comments(post_id):
-    return pd.DataFrame(comments.get(post_id, []))
-
-def view_user_posts(username):
-    user_posts = [post for post in posts if post['username'] == username]
-    return pd.DataFrame(user_posts)
-
-def view_post_comments(post_id):
-    return pd.DataFrame(comments.get(post_id, []))
-
 # Define the Gradio Blocks interface
 with gr.Blocks(css=css) as demo:
     with gr.Tab("Emotional Support Chatbot"):
@@ -219,79 +178,57 @@ with gr.Blocks(css=css) as demo:
         gr.Markdown("# Motivational Quotes")
         gr.Markdown(motivational_tagline)
         
-        # Define a dummy response function for motivational quotes
-        def motivational_response(message):
-            return "Here’s a motivational quote for you!"
-
-        motivational_message = gr.Textbox(label="Your message")
-        motivational_output = gr.Textbox(label="Motivational Quote", interactive=False)
-        motivational_button = gr.Button("Get Quote")
+        system_message_motivational = gr.Textbox(value="You are a friendly Motivational Quotes Chatbot.", visible=False)
+        chatbot_motivational = gr.Chatbot()
+        msg_motivational = gr.Textbox(label="Your message")
+        clear_motivational = gr.Button("Clear")
+        
+        with gr.Accordion("Additional Inputs", open=False):
+            max_tokens_motivational = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens")
+            temperature_motivational = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature")
+            top_p_motivational = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)")
 
-        motivational_button.click(motivational_response, motivational_message, motivational_output)
+        def respond_wrapper_motivational(message, chat_history, system_message_val, max_tokens_val, temperature_val, top_p_val):
+            chat_history, _ = send_message(
+                message=message,
+                history=chat_history,
+                system_message=system_message_val,
+                max_tokens=max_tokens_val,
+                temperature=temperature_val,
+                top_p=top_p_val,
+            )
+            return gr.update(value=""), chat_history
 
+        msg_motivational.submit(respond_wrapper_motivational, [msg_motivational, chatbot_motivational, system_message_motivational, max_tokens_motivational, temperature_motivational, top_p_motivational], [msg_motivational, chatbot_motivational])
+        clear_motivational.click(lambda: None, None, chatbot_motivational, queue=False)
+    
     with gr.Tab("Emotions Detector"):
         gr.Markdown("# Emotions Detector")
         gr.Markdown(emotions_detector_tagline)
         
-        # Define a dummy function for emotions detection
-        def emotions_detector(message):
-            return "Your message sounds positive!"
-
-        emotions_message = gr.Textbox(label="Your message")
-        emotions_output = gr.Textbox(label="Emotions Analysis", interactive=False)
-        emotions_button = gr.Button("Analyze")
-
-        emotions_button.click(emotions_detector, emotions_message, emotions_output)
-
-    with gr.Tab("Forum"):
-        gr.Markdown("# Community Support Forum")
-        gr.Markdown("Connect with others, share your stories, and seek advice.")
-
-        with gr.Row():
-            username_input = gr.Textbox(label="Username")
-            register_button = gr.Button("Register")
+        system_message_emotions = gr.Textbox(value="You are an Emotions Detector Chatbot. Analyze the tone of the message (happy, sad, funny, excited, regret, depressed, joy, surprise, fear, anger) and provide suggestions to improve the message.", visible=False)
+        chatbot_emotions = gr.Chatbot()
+        msg_emotions = gr.Textbox(label="Your message")
+        clear_emotions = gr.Button("Clear")
         
-        with gr.Row():
-            post_content = gr.Textbox(label="Post Content")
-            is_anonymous = gr.Checkbox(label="Post Anonymously")
-            submit_post_button = gr.Button("Submit Post")
-
-        with gr.Row():
-            view_posts_button = gr.Button("View All Posts")
-            view_user_posts_button = gr.Button("View User Posts")
-
-        with gr.Row():
-            post_id_input = gr.Textbox(label="Post ID")
-            comment_content = gr.Textbox(label="Comment Content")
-            submit_comment_button = gr.Button("Submit Comment")
-
-        with gr.Row():
-            view_comments_button = gr.Button("View Post Comments")
-
-        def register_user_wrapper(username):
-            return register_user(username)
-
-        def submit_post_wrapper(username, content, is_anonymous):
-            return submit_post(username, content, is_anonymous)
-
-        def get_all_posts():
-            return get_posts()
-
-        def get_user_posts(username):
-            return view_user_posts(username)
-
-        def submit_comment_wrapper(post_id, username, comment):
-            return submit_comment(post_id, username, comment)
+        with gr.Accordion("Additional Inputs", open=False):
+            max_tokens_emotions = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens")
+            temperature_emotions = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature")
+            top_p_emotions = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)")
 
-        def get_post_comments(post_id):
-            return view_post_comments(post_id)
+        def respond_wrapper_emotions(message, chat_history, system_message_val, max_tokens_val, temperature_val, top_p_val):
+            chat_history, _ = send_message(
+                message=message,
+                history=chat_history,
+                system_message=system_message_val,
+                max_tokens=max_tokens_val,
+                temperature=temperature_val,
+                top_p=top_p_val,
+            )
+            return gr.update(value=""), chat_history
 
-        register_button.click(register_user_wrapper, username_input, "Registration Status")
-        submit_post_button.click(submit_post_wrapper, [username_input, post_content, is_anonymous], "Post Status")
-        view_posts_button.click(get_all_posts, None, "All Posts")
-        view_user_posts_button.click(get_user_posts, username_input, "User Posts")
-        submit_comment_button.click(submit_comment_wrapper, [post_id_input, username_input, comment_content], "Comment Status")
-        view_comments_button.click(get_post_comments, post_id_input, "Post Comments")
+        msg_emotions.submit(respond_wrapper_emotions, [msg_emotions, chatbot_emotions, system_message_emotions, max_tokens_emotions, temperature_emotions, top_p_emotions], [msg_emotions, chatbot_emotions])
+        clear_emotions.click(lambda: None, None, chatbot_emotions, queue=False)
 
 if __name__ == "__main__":
     demo.launch()