Update app.py

app.py

@@ -1,6 +1,7 @@
 import os
 import streamlit as st
 from groq import Groq
+from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
 
 # Set up the Groq API Key
 GROQ_API_KEY = "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"
@@ -9,49 +10,22 @@ os.environ["GROQ_API_KEY"] = GROQ_API_KEY
 # Initialize the Groq client
 client = Groq(api_key=GROQ_API_KEY)
 
+# Initialize Hugging Face DeepSeek R1 model
+pipe = pipeline("text-generation", model="deepseek-ai/DeepSeek-R1", trust_remote_code=True)
+
+def generate_response_hf(user_message):
+    response = pipe(user_message, max_length=200, do_sample=True)
+    return response[0]['generated_text']
+
 # Streamlit user interface setup
 st.set_page_config(page_title="AI Study Assistant", page_icon="🤖", layout="wide")
 st.title("📚 Subject-specific AI Chatbot")
 st.write("Hello! I'm your AI Study Assistant. You can ask me any questions related to your subjects, and I'll try to help.")
 
-# Add sidebar with styling options
+# Add sidebar with settings
 st.sidebar.header("⚙️ Settings")
 st.sidebar.write("Customize your chatbot experience!")
-chat_theme = st.sidebar.radio("Choose a theme:", ["Light", "Dark", "Blue", "Green"])
-
-# Apply theme
-if chat_theme == "Dark":
-    st.markdown("""
-        <style>
-            body {background-color: #1e1e1e; color: white;}
-            .stButton>button {background-color: #4CAF50; color: white;}
-            .chat-bubble {background-color: #2c2c2c; border-radius: 10px; padding: 10px;}
-        </style>
-    """, unsafe_allow_html=True)
-elif chat_theme == "Blue":
-    st.markdown("""
-        <style>
-            body {background-color: #e3f2fd; color: black;}
-            .stButton>button {background-color: #2196F3; color: white;}
-            .chat-bubble {background-color: #bbdefb; border-radius: 10px; padding: 10px;}
-        </style>
-    """, unsafe_allow_html=True)
-elif chat_theme == "Green":
-    st.markdown("""
-        <style>
-            body {background-color: #e8f5e9; color: black;}
-            .stButton>button {background-color: #4CAF50; color: white;}
-            .chat-bubble {background-color: #c8e6c9; border-radius: 10px; padding: 10px;}
-        </style>
-    """, unsafe_allow_html=True)
-else:
-    st.markdown("""
-        <style>
-            body {background-color: #ffffff; color: black;}
-            .stButton>button {background-color: #008CBA; color: white;}
-            .chat-bubble {background-color: #f1f1f1; border-radius: 10px; padding: 10px;}
-        </style>
-    """, unsafe_allow_html=True)
+chat_model = st.sidebar.radio("Choose AI Model:", ["Groq API", "DeepSeek R1 (Hugging Face)"])
 
 # Initialize session state for maintaining conversation
 if 'conversation_history' not in st.session_state:
@@ -60,42 +34,29 @@ if 'conversation_history' not in st.session_state:
 # Define a list of subjects for which the chatbot will answer
 subjects = ["Chemistry", "Computer", "English", "Islamiat", "Mathematics", "Physics", "Urdu"]
 
-# Function to generate chatbot response based on subject-specific user input
 def generate_chatbot_response(user_message):
-    # Check if the user's question is related to any subject
-    related_subject = None
-    for subject in subjects:
-        if subject.lower() in user_message.lower():
-            related_subject = subject
-            break
+    related_subject = next((subject for subject in subjects if subject.lower() in user_message.lower()), None)
     
-    # Custom response for "who created you" type of questions
     if "kisne banaya" in user_message.lower() or "who created you" in user_message.lower():
-        return "I Created by Abdul Basit 😊"
+        return "I was created by Abdul Basit 😊"
 
-    if related_subject:
-        prompt = f"You are a helpful AI chatbot for studying {related_subject}. The user is asking: {user_message}. Provide a detailed, helpful response related to {related_subject}."
+    prompt = f"You are a helpful AI chatbot for studying {related_subject if related_subject else 'general knowledge'}. The user is asking: {user_message}. Provide a detailed, helpful response."
+    
+    if chat_model == "Groq API":
+        chat_completion = client.chat.completions.create(
+            messages=[{"role": "user", "content": prompt}],
+            model="deepseek-chat"
+        )
+        return chat_completion.choices[0].message.content
     else:
-        prompt = f"You are a helpful AI chatbot. The user is asking: {user_message}. If the question is not related to any of the specified subjects (Chemistry, Computer, English, Islamiat, Mathematics, Physics, Urdu), politely let them know."
+        return generate_response_hf(prompt)
 
-    # Generate response using Groq API
-    chat_completion = client.chat.completions.create(
-        messages=[{"role": "user", "content": prompt}],
-        model="llama3-8b-8192",  # You can replace with the appropriate model name
-    )
-
-    response = chat_completion.choices[0].message.content
-    return response
-
-# User input for conversation (now placed at the bottom)
+# User input for conversation
 st.markdown("### 💬 Chat with me")
 user_input = st.chat_input("Ask me a subject-related question:")
 
-# Handle user input and display conversation
 if user_input:
     chatbot_response = generate_chatbot_response(user_input)
-
-    # Save the conversation history
     st.session_state.conversation_history.append(("User: " + user_input, "Chatbot: " + chatbot_response))
 
 # Display chat history