Update app.py

app.py

@@ -1,16 +1,17 @@
+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
 
-# 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"]
+# 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
 
+# 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."
 messages = [{"role": "system", "content": system_message}]
 messages.append({
@@ -25,6 +26,7 @@ try:
 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):
     try:
         with open(filename, 'r', encoding='utf-8') as file:
@@ -35,8 +37,10 @@ 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):
     try:
         lower_query = user_query.lower()
@@ -49,43 +53,32 @@ def find_relevant_segment(user_query, segments):
         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):
     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})
 
-        # Encode the input and generate a response
-        input_ids = tokenizer.encode(user_message, return_tensors='pt')
-
-        # Create the attention mask (1 for real tokens, 0 for padding tokens)
-        attention_mask = torch.ones(input_ids.shape, dtype=torch.long)  # Create a tensor of ones
-
-        # Generate the response using the model
-        output = model.generate(
-            input_ids,
-            attention_mask=attention_mask,
-            max_length=150,
-            num_return_sequences=1,
-            pad_token_id=tokenizer.eos_token_id  # Set pad_token_id to eos_token_id
+        # Use OpenAI's API to generate a response
+        response = openai.ChatCompletion.create(
+            model="gpt-4",
+            messages=messages,
+            max_tokens=150,
+            temperature=0.7,
         )
 
-        output_text = tokenizer.decode(output[0], skip_special_tokens=True)
+        # Extract and return the response from gpt-4
+        assistant_reply = response['choices'][0]['message']['content']
+        messages.append({"role": "assistant", "content": assistant_reply})
 
-        # Append assistant's message to messages list for context
-        messages.append({"role": "user", "content": user_message})
-        
-        response = openai.ChatCompletion.create(
-            model="gpt-4o",
-            messages=messages,
-            max_tokens=4000,
-            temperature=0.5,
-        return output_text
+        return assistant_reply
 
     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):
     if question == "":
         return "Welcome to CalmConnect! Ask me anything about destressing strategies or student opportunities. Feel free to talk to our online therapist!"
@@ -95,7 +88,7 @@ def query_model(question):
     response = generate_response(question, relevant_segment)
     return response
 
-# Define the HTML iframe content
+# 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>
 '''
@@ -104,16 +97,11 @@ 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>
 '''
 
-
-# Define the welcome message and specific topics the chatbot can provide information about
+# Markdown content for welcome and topics sections
 welcome_message = """
 <span style="color:#718355; font-size:24px; font-weight:bold;"> 🪷 Welcome to CalmConnect! 🪷</span>
 """
 
-"""
-## Your AI-driven assistant for destressing and extracurricular opportunity queries. Created by Olivia W, Alice T, and Cindy W of the 2024 Kode With Klossy CITY Camp. 
-"""
-
 topics = """
 ### If you are interested in the following below, click on our Student Opportunities Database!
 - Engineering
@@ -123,7 +111,7 @@ topics = """
 - Law / Political Science / Debate
 - The Arts
 - Business / Leadership
-- Pyschology
+- Psychology
 - Medicine / Biology
 - Literature / Writing
 - College Prep
@@ -132,7 +120,7 @@ topics = """
 - Study Abroad
 """
 
-topics2= """
+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.)
@@ -145,14 +133,14 @@ topics2= """
 - Support Resources
 """
 
-# Create a Gradio HTML component
+# Function to display the embedded HTML content
 def display_iframe():
     return iframe
 
 def display_iframe2():
     return iframe2
 
-
+# Setup Gradio interface with customized theme
 theme = gr.themes.Default(
     primary_hue="neutral",
     secondary_hue="neutral",
@@ -169,39 +157,33 @@ theme = gr.themes.Default(
     button_primary_background_fill="#f8f1ea",
     button_primary_background_fill_dark="#f8f1ea"
 )
-    
-# Setup the Gradio Blocks interface with custom layout components
+
+# Create Gradio interface layout
 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 the formatted welcome message
-    
+    gr.Markdown(welcome_message)  # Display welcome message
+
     with gr.Row():
         with gr.Column():
-            gr.Markdown(topics)  # Show the topics on the left side
-            gr.HTML(iframe)  # Embed the iframe on the left side
-            gr.HTML(iframe2)  # Embed the iframe on the right side
-        
+            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 the topics on the left side
+            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)
+                    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)
-    
-    with gr.Row():
-        big_block = gr.HTML("### <button><a href='https://www.headspace.com/teens'>FREE: HEADSPACE FOR TEENS </a></button>")
-        big_block2 = gr.HTML("<button><a href='https://calmconnect-flower.replit.app/'>PLAY FLOWER GAME</a></button>")
-        big_block3 = gr.HTML("<button><a href='https://www.nyc.gov/site/doh/health/health-topics/teenspace.page'>NYC: TEENSPACE (free services)</a></button>")
-        big_block4 =gr.HTML("<button><a href='https://www.teenlife.com/blog/mental-health-resources-for-teens/'>TEEN MENTAL HEALTH RESOURCES (free services)</a></button>")
-
-
-demo.launch()
-
-
-
 
+    # 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>")
 
-# Launch the Gradio app to allow user interaction
-demo.launch(share=True)
+# Launch the Gradio app
+demo.launch(share=True)