Update app.py

app.py

@@ -6,12 +6,12 @@ import os
 os.environ["TOKENIZERS_PARALLELISM"] = "false"
 
 # Initialize paths and model identifiers for easy configuration and maintenance
-filename = "output_topic_details.txt"  # Path to the file storing chess-specific details
+filename = "output_topic_details.txt"  # Path to the file storing skincare-specific details
 retrieval_model_name = 'output/sentence-transformer-finetuned/'
 
 openai.api_key = os.environ["OPENAI_API_KEY"]
 
-system_message = "You are a chess chatbot specialized in providing information on chess rules, strategies, and terminology."
+system_message = "You are a skincare chatbot specialized in providing information on skincare dupes, ingredients , and effects."
 # Initial system message to set the behavior of the assistant
 messages = [{"role": "system", "content": system_message}]
 
@@ -45,17 +45,17 @@ def find_relevant_segment(user_query, segments):
     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:
@@ -64,14 +64,14 @@ def find_relevant_segment(user_query, segments):
 
 def generate_response(user_query, relevant_segment):
     """
-    Generate a response emphasizing the bot's capability in providing chess information.
+    Generate a response emphasizing the bot's capability in providing skincare information.
     """
     try:
-        user_message = f"Here's the information on chess: {relevant_segment}"
+        user_message = f"Here's the information on skincare: {relevant_segment}"
 
         # Append user's message to messages list
         messages.append({"role": "user", "content": user_message})
-        
+       
         response = openai.ChatCompletion.create(
             model="gpt-3.5-turbo",
             messages=messages,
@@ -81,15 +81,15 @@ def generate_response(user_query, relevant_segment):
             frequency_penalty=0,
             presence_penalty=0
         )
-        
+       
         # 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}"
@@ -99,31 +99,30 @@ def query_model(question):
     Process a question, find relevant information, and generate a response.
     """
     if question == "":
-        return "Welcome to ChessBot! Ask me anything about chess rules, strategies, and terminology."
+        return "Welcome to DupeBot! Ask me anything about skincare dupes and products for your skintype."
     relevant_segment = find_relevant_segment(question, segments)
     if not relevant_segment:
-        return "Could not find specific information. Please refine your question."
+        return "Could not find specific information. Please consult a dermatologist instead."
     response = generate_response(question, relevant_segment)
     return response
 
 # Define the welcome message and specific topics the chatbot can provide information about
 welcome_message = """
-# ♟️ Welcome to ChessBot!
+# 🌸🧴 Welcome to DupeBot! 🌸🧴
 
-## Your AI-driven assistant for all chess-related queries. Created by SCHOLAR1, SCHOLAR2, and SCHOLAR3 of the 2024 Kode With Klossy CITY Camp. 
+## DupeBot is your personal assistant for all skin-related queries. Created by SCHOLAR1, SCHOLAR2, and SCHOLAR3 of the 2024 Kode With Klossy CITY Camp.
 """
 
 topics = """
-### Feel Free to ask me anything from the topics below!
-- Chess piece movements
-- Special moves
-- Game phases
-- Common strategies
-- Chess terminology
-- Famous games
-- Chess tactics
+### Feel Free to Ask Me about Any of the Following Topics:
+- Skincare Dupes
+- Makeup dupes
+- Ideal Skincare Ingredients for Your Skin Type
+- Products Targeted Towards Your Specific Skin Issues
+- Uses for Various Ingredients
 """
 
+
 # Setup the Gradio Blocks interface with custom layout components
 with gr.Blocks(theme='JohnSmith9982/small_and_pretty') as demo:
     gr.Markdown(welcome_message)  # Display the formatted welcome message
@@ -133,10 +132,10 @@ with gr.Blocks(theme='JohnSmith9982/small_and_pretty') as demo:
     with gr.Row():
         with gr.Column():
             question = gr.Textbox(label="Your question", placeholder="What do you want to ask about?")
-            answer = gr.Textbox(label="ChessBot Response", placeholder="ChessBot will respond here...", interactive=False, lines=10)
+            answer = gr.Textbox(label="DupeBot Response", placeholder="DupeBot will respond here...", interactive=False, lines=10)
             submit_button = gr.Button("Submit")
             submit_button.click(fn=query_model, inputs=question, outputs=answer)
-    
+   
 
 # Launch the Gradio app to allow user interaction
 demo.launch(share=True)