Update app.py

app.py

@@ -1,33 +1,35 @@
-import os
-import openai
 import gradio as gr
 from sentence_transformers import SentenceTransformer, util
+import openai  
+import os
 
-# Set up environment and variables
 os.environ["TOKENIZERS_PARALLELISM"] = "false"
-openai.api_key = os.environ.get("OPENAI_API_KEY")  # Make sure your API key is set in the environment
 
-# File and model configurations
-filename = "output_topic_details.txt"  # File containing details for specific topics
-retrieval_model_name = 'output/sentence-transformer-finetuned/'  # Path to the fine-tuned model
+# Initialize paths and model identifiers for easy configuration and maintenance
+filename = "output_topic_details.txt"  # Path to the file storing destress-specific details
+retrieval_model_name = 'output/sentence-transformer-finetuned/'
+
+# openai.api_key = os.environ["OPENAI_API_KEY"]
 
-# Define initial system message for the chatbot
-system_message = "You are a comfort chatbot specialized in providing information on therapy, destressing activities, and student opportunities."
+system_message = "You are a comfort chatbot specialized in providing information on destressing activities."
+# Initial system message to set the behavior of the assistant
 messages = [{"role": "system", "content": system_message}]
 messages.append({
-    "role": "system",
-    "content": "Do not use Markdown Format. Do not include hashtags or asterisks"
+	"role": "system",
+	"content": "Do not use Markdown Format. Do not include hashtags or asterisks"
 })
 
-# Load the retrieval model
+# Attempt to load the necessary models and provide feedback on success or failure
 try:
     retrieval_model = SentenceTransformer(retrieval_model_name)
     print("Models loaded successfully.")
 except Exception as e:
     print(f"Failed to load models: {e}")
 
-# Function to load and preprocess the text file
 def load_and_preprocess_text(filename):
+    """
+    Load and preprocess text from a file, removing empty lines and stripping whitespace.
+    """
     try:
         with open(filename, 'r', encoding='utf-8') as file:
             segments = [line.strip() for line in file if line.strip()]
@@ -37,110 +39,80 @@ def load_and_preprocess_text(filename):
         print(f"Failed to load or preprocess text: {e}")
         return []
 
-# Load the segments from the text file
 segments = load_and_preprocess_text(filename)
 
-# Function to find the most relevant segment from the file
 def find_relevant_segment(user_query, segments):
+    """
+    Find the most relevant text segment for a user's query using cosine similarity among sentence embeddings.
+    This version finds the best match based on the content of the query.
+    """
     try:
+        # Lowercase the query for better matching
         lower_query = user_query.lower()
+        
+        # Encode the query and the segments
         query_embedding = retrieval_model.encode(lower_query)
         segment_embeddings = retrieval_model.encode(segments)
+        
+        # Compute cosine similarities between the query and the segments
         similarities = util.pytorch_cos_sim(query_embedding, segment_embeddings)[0]
+        
+        # Find the index of the most similar segment
         best_idx = similarities.argmax()
+        
+        # Return the most relevant segment
         return segments[best_idx]
     except Exception as e:
         print(f"Error in finding relevant segment: {e}")
         return ""
 
-# Function to generate a response using OpenAI's gpt-4
 def generate_response(user_query, relevant_segment):
+    """
+    Generate a response emphasizing the bot's capability in providing therapy, destressing activites, and student opportunities information.
+    """
     try:
-        # Construct the user message with relevant information
         user_message = f"Here's the information on your request: {relevant_segment}"
-        messages.append({"role": "user", "content": user_message})
 
-        # Use OpenAI's API to generate a response
+        # Append user's message to messages list
+        messages.append({"role": "user", "content": user_message})
+        
         response = openai.ChatCompletion.create(
-            model="gpt-4o",
+            model="gpt-4",
             messages=messages,
-            max_tokens=150,
-            temperature=0.7,
+            max_tokens=4000,
+            temperature=0.5,
+            top_p=1,
+            frequency_penalty=0.5,
+            presence_penalty=0.5,
         )
-
-        # Extract and return the response from gpt-4
-        assistant_reply = response['choices'][0]['message']['content']
-        messages.append({"role": "assistant", "content": assistant_reply})
-
-        return assistant_reply
-
+        
+        # Extract the response text
+        output_text = response['choices'][0]['message']['content'].strip()
+        
+        # Append assistant's message to messages list for context
+        messages.append({"role": "assistant", "content": output_text})
+        
+        return output_text
+        
     except Exception as e:
         print(f"Error in generating response: {e}")
         return f"Error in generating response: {e}"
 
-# Function to process user queries
 def query_model(question):
+    """
+    Process a question, find relevant information, and generate a response.
+    """
     if question == "":
-        return "Welcome to CalmConnect! Ask me anything about destressing strategies or student opportunities. Feel free to talk to our online therapist!"
+        return "Welcome to CalmConnect's CalmBot! Ask me anything about destressing strategies and we'll provide you ways to unlock your inner calm!"
     relevant_segment = find_relevant_segment(question, segments)
     if not relevant_segment:
         return "Could not find specific information. Please refine your question or head to our resources page."
     response = generate_response(question, relevant_segment)
     return response
 
-# HTML content for embedded resources
-iframe = '''
-<iframe style="border-radius:12px" src="https://docs.google.com/spreadsheets/d/e/2PACX-1vRroWVBXq1Fa0x7SvRTzSBMHFIp59VtVEWCxeg8kWJU4ll1_o4yzBnt4ArT88s7g4TQrMKEXZUQAeHF/pubhtml?widget=true&amp;headers=false" width="100%" height="352" frameBorder="0" allowfullscreen="true" allow="autoplay; clipboard-write; encrypted-media; fullscreen; picture-in-picture" loading="lazy"></iframe>
-'''
-
-iframe2 = '''
-<iframe style="border-radius:12px" src="https://open.spotify.com/embed/playlist/6wwxTePuIKYMqt6RCytB7X?utm_source=generator" width="100%" height="300" frameBorder="0" allowfullscreen="" allow="autoplay; clipboard-write; encrypted-media; fullscreen; picture-in-picture" loading="lazy"></iframe>
-'''
-
-# Markdown content for welcome and topics sections
-welcome_message = """
-<span style="color:#718355; font-size:24px; font-weight:bold;"> 🪷 Welcome to CalmConnect! 🪷</span>
-"""
-
-topics = """
-### If you are interested in the following below, click on our Student Opportunities Database!
-- Engineering
-- Technology / Computer Science
-- Research : STEM
-- Finance
-- Law / Political Science / Debate
-- The Arts
-- Business / Leadership
-- Psychology
-- Medicine / Biology
-- Literature / Writing
-- College Prep
-- Advocacy: Non-Profit, Environment or Identity 
-- Volunteering 
-- Study Abroad
-"""
-
-topics2 = """
-### Feel Free to ask CalmBot (Our Therapist Bot) anything from the topics below!
-- Arts and Crafts (When asking for arts and crafts ideas, state whether you have 15 min, 30 min, 45 min, 1 hour, 1 hour and a half, 2 hours, 2 hours and a half, 3 hours or greater)
-- Destressing strategies (Breathing Exercises, stretches, etc.)
-- Mental Health
-- Identity (Sexual, Gender, etc.)
-- Bullying
-- Racism
-- Relationships (Family, Friends, etc.)
-- Abuse (Emotional, Physical, Sexual, Mental, etc.)
-- Support Resources
-"""
-
-# Function to display the embedded HTML content
-def display_iframe():
-    return iframe
-
-def display_iframe2():
-    return iframe2
-
-# Setup Gradio interface with customized theme
+welcome_message = ""
+topics = ""
+
 theme = gr.themes.Default(
     primary_hue="neutral",
     secondary_hue="neutral",
@@ -157,33 +129,32 @@ theme = gr.themes.Default(
     button_primary_background_fill="#f8f1ea",
     button_primary_background_fill_dark="#f8f1ea"
 )
-
-# Create Gradio interface layout
+    
+# Setup the Gradio Blocks interface with custom layout components
 with gr.Blocks(theme=theme) as demo:
-    gr.Image("CalmConnect.jpg", show_label=False, show_share_button=False, show_download_button=False)
-    gr.Markdown(welcome_message)  # Display welcome message
 
+    gr.Markdown(welcome_message)  # Display the formatted welcome message
+    
     with gr.Row():
-        with gr.Column():
-            gr.Markdown(topics)  # Show topics on the left
-            gr.HTML(iframe)  # Embed iframe content
-            gr.HTML(iframe2)  # Embed additional iframe content
-
-        with gr.Column():
-            gr.Markdown(topics2)  # Show therapy topics on the right
-            with gr.Row():
-                with gr.Column():
-                    question = gr.Textbox(label="You", placeholder="What do you want to talk to CalmBot about?")
-                    answer = gr.Textbox(label="CalmBot's Response :D", placeholder="CalmBot will respond here...", interactive=False, lines=20)
-                    submit_button = gr.Button("Submit")
-                    submit_button.click(fn=query_model, inputs=question, outputs=answer)
-
-    # Add additional HTML buttons for resources
-    with gr.Row():
-        gr.HTML("### <button><a href='https://www.headspace.com/teens'>FREE: HEADSPACE FOR TEENS </a></button>")
-        gr.HTML("<button><a href='https://calmconnect-flower.replit.app/'>PLAY FLOWER GAME</a></button>")
-        gr.HTML("<button><a href='https://www.nyc.gov/site/doh/health/health-topics/teenspace.page'>NYC: TEENSPACE (free services)</a></button>")
-        gr.HTML("<button><a href='https://www.teenlife.com/blog/mental-health-resources-for-teens/'>TEEN MENTAL HEALTH RESOURCES (free services)</a></button>")
+        with gr.Column(scale=0.8):
+            gr.Markdown(topics)
+          
+        
+           # Show the topics on the left side
+        with gr.Row():
+            with gr.Column():
+                question = gr.Textbox(label="You", placeholder="What do you want to talk to CalmBot about?")
+                answer = gr.Textbox(label="CalmBot's Response :D", placeholder="CalmBot will respond here..", interactive=False, lines=20)
+                submit_button = gr.Button("Submit")
+                submit_button.click(fn=query_model, inputs=question, outputs=answer)
+        
+
+
+demo.launch()
+
+
+
+
 
-# Launch the Gradio app
+# Launch the Gradio app to allow user interaction
 demo.launch(share=True)