Update app.py

app.py

@@ -4,149 +4,147 @@ import streamlit as st
 import logging
 from datetime import datetime
 from urllib.parse import urlparse, parse_qs
-import pandas as pd # Added as a common dependency, although not strictly required by the core chat logic
-
-# --- HUGGING FACE SECRETS ADJUSTMENT ---
-# In Hugging Face, secrets are generally managed via the repository settings 
-# and accessed within the app using st.secrets.
-# We'll use st.secrets.get() for deployment-friendly API key retrieval.
 
 # Set browser tab title
-st.set_page_config(page_title="Learn AI with Rajamanickam.com")
+st.set_page_config(page_title="Wellness Bot")
 
-# start of admin side
+#start of admin side
 # Check if "admin" query parameter is present and valid
 query_params = st.query_params
 is_admin = query_params.get("admin") == "1234"
 
 # If admin, show download button
 if is_admin:
-    if os.path.exists("usage_log.txt"):
-        with open("usage_log.txt", "rb") as f:
+    if os.path.exists("usage_log_wellness.txt"):
+        with open("usage_log_wellness.txt", "rb") as f:
             st.download_button(
                 label="⬇️ Download Usage Log",
                 data=f,
-                file_name="usage_log.txt",
+                file_name="usage_log_wellness.txt",
                 mime="text/plain"
             )
     else:
         st.warning("⚠️ Log file not found.")
-# end of admin side
-
-# Setup lightweight logger
-logging.basicConfig(filename="usage_log.txt", level=logging.INFO, format="%(asctime)s - %(message)s")
-
-# --- API KEY SETUP ---
-# CRITICAL CHANGE FOR DEPLOYMENT: Use st.secrets instead of os.environ
-api_key = st.secrets.get("GEMINI_API_KEY") 
-
-if not api_key:
-    st.error("GEMINI_API_KEY not found. Please set it in Streamlit Secrets or environment variables.")
-else:
-    # Set up API key and model
-    genai.configure(api_key=api_key)
-    model = genai.GenerativeModel('gemini-1.5-flash-8b')
-
-    # Define system prompt
-    system_prompt = """You are a friendly and knowledgeable AI tutor.
-    Your goal is to help users understand AI concepts in a simple and engaging way.
-    Keep responses short, clear, and conversational.
-    Avoid technical jargon unless necessary, and do not generate long essays.
-    It is your responsibility to bring the discussion back to AI topics, even if the user starts another topic.
-    Improve the quality of your response based on the responses of the user and make sure that you change your way of chatting based on the knowledge level of the user. You should give an amazing AI learning experience to the user.
-    If the user expresses interest in personal AI guidance, consultancy, or development support, encourage them to contact rajamanickam.a@gmail.com for one-on-one coaching, AI consulting, or affordable AI development services.
-    Based on the conversation, suggest suitable learning products from the list below when relevant.
-    Here is your product list:- Course - AI for Beginners - https://www.rajamanickam.com/l/LearnAI?layout=profile- Ebook - AI Insights into the Bible - https://www.rajamanickam.com/l/vgizdq?layout=profile- Ebook - Retrieval-Augmented Generation (RAG) - https://www.rajamanickam.com/l/RAG?layout=profile- Ebook - Mastering Snowflake - https://www.rajamanickam.com/l/snowflake?layout=profile- Ebook - Mastering SQL - https://www.rajamanickam.com/l/sql?layout=profile- Ebook - Unlocking AI - https://www.rajamanickam.com/l/aibook?layout=profile- Ebook - Python for AI Developers - https://www.rajamanickam.com/l/python?layout=profile- Ebook - Earn Money Selling AI Courses - https://www.rajamanickam.com/l/sellai?layout=profile- Ebook - AI for Entrepreneurs - https://www.rajamanickam.com/l/aibusiness?layout=profile- Ebook - Unlocking Google Gemini - https://www.rajamanickam.com/l/djxlz?layout=profile- Ebook - Mastering the Art of Talking to AI - https://www.rajamanickam.com/l/uzvhj?layout=profile- Playlist - YouTube playlist to learn AI - https://www.youtube.com/playlist?list=PLK2ccNIJVPpD-9MMKHC2QEtiZIea2cgLh- Quiz - AI Quiz to test your AI knowledge - https://qualitypointtech.com/quiz/index.php"""
-
-    # Define product catalog
-    product_catalog = {
-        "aibeginners": {"name": "AI for Beginners Course", "url": "https://www.rajamanickam.com/l/LearnAI?layout=profile", "tags": ["ai", "learning", "career"]},
-        "bible": {"name": "AI Insights into the Bible", "url": "https://www.rajamanickam.com/l/vgizdq?layout=profile", "tags": ["bible", "faith", "ai"]},
-        "rag": {"name": "Retrieval-Augmented Generation (RAG)", "url": "https://www.rajamanickam.com/l/RAG?layout=profile", "tags": ["rag", "retrieval", "generation"]},
-        "snowflake": {"name": "Mastering Snowflake", "url": "https://www.rajamanickam.com/l/snowflake?layout=profile", "tags": ["snowflake", "data", "cloud"]},
-        "sql": {"name": "Mastering SQL", "url": "https://www.rajamanickam.com/l/sql?layout=profile", "tags": ["sql", "database"]},
-        "unlockai": {"name": "Unlocking AI", "url": "https://www.rajamanickam.com/l/aibook?layout=profile", "tags": ["ai", "intro"]},
-        "python": {"name": "Python for AI Developers", "url": "https://www.rajamanickam.com/l/python?layout=profile", "tags": ["python", "code"]},
-        "sellai": {"name": "Earn Money Selling AI Courses", "url": "https://www.rajamanickam.com/l/sellai?layout=profile", "tags": ["money", "courses"]},
-        "aibusiness": {"name": "AI for Entrepreneurs", "url": "https://www.rajamanickam.com/l/aibusiness?layout=profile", "tags": ["business", "startup"]},
-        "gemini": {"name": "Unlocking Google Gemini", "url": "https://www.rajamanickam.com/l/djxlz?layout=profile", "tags": ["gemini", "google"]},
-        "prompts": {"name": "Mastering the Art of Talking to AI", "url": "https://www.rajamanickam.com/l/uzvhj?layout=profile", "tags": ["prompt", "talking", "engineering"]},
-        "playlist": {"name": "YouTube playlist to learn AI", "url": "https://www.youtube.com/playlist?list=PLK2ccNIJVPpD-9MMKHC2QEtiZIea2cgLh", "tags": ["youtube", "playlist", "tutorial"]},
-        "quiz": {"name": "AI Quiz to test your AI knowledge", "url": "https://qualitypointtech.com/quiz/index.php", "tags": ["quiz", "test", "assessment"]}}
-
-    # Function to detect relevant product suggestions
-    def detect_relevant_products(chat_history):
-        suggestions = []
-        history_text = " ".join([msg["content"].lower() for msg in chat_history])
-        for key, product in product_catalog.items():
-            if any(tag in history_text for tag in product["tags"]):
-                if key not in st.session_state.suggested_products:
-                    suggestions.append(product)
-                    st.session_state.suggested_products.add(key)
-        return suggestions
-
-    # Initialize session state
-    if "messages" not in st.session_state:
-        st.session_state.messages = [
-            {"role": "assistant", "content": "👋 Welcome! I'm your AI learning assistant. What AI topic would you like to explore today?"}
-        ]
-    if "suggested_products" not in st.session_state:
-        st.session_state.suggested_products = set()
-
-    # Streamlit UI
-    st.markdown("**🎓 [AI Quiz](https://qualitypointtech.com/quiz/index.php) | Use discount code `QPT` for AI course at [Rajamanickam.Com](https://www.rajamanickam.com/l/LearnAI?layout=profile)**")
-    st.title("Learn AI Chatbot 💬")
-
-    # Display chat history
-    for message in st.session_state.messages:
-        with st.chat_message(message["role"]):
-            st.markdown(message["content"])
-
-    # Chat input and assistant's response
-    if prompt := st.chat_input("Ask your question about AI related topics..."):
+#end of admin side
         
-        # Input length control
-        if len(prompt) > 500:
-            warning_msg = "⚠️ Please keep your question brief (under 500 characters) for better results."
-            st.session_state.messages.append({"role": "assistant", "content": warning_msg})
-            with st.chat_message("assistant"):
-                st.markdown(warning_msg)
-        else:
-            # Log user input
-            logging.info(f"User: {prompt}")
-            st.session_state.messages.append({"role": "user", "content": prompt})
-            with st.chat_message("user"):
-                st.markdown(prompt)
-
-            with st.chat_message("assistant"):
-                message_placeholder = st.empty()
-                full_response = ""
-                try:
-                    past_convo = "\n".join([msg["content"] for msg in st.session_state.messages])
-                    full_prompt = f"{system_prompt}\n{past_convo}\nUser: {prompt}\nAssistant:"
-                    
-                    # Ensure model is defined before calling generate_content
-                    if 'model' in locals(): 
-                        for chunk in model.generate_content(full_prompt, stream=True):
-                            full_response += (chunk.text or "")
-                            message_placeholder.markdown(full_response + "▌")
-                        message_placeholder.markdown(full_response)
-                    else:
-                        full_response = "AI model could not be initialized due to missing API key."
-                        message_placeholder.markdown(full_response)
-
-                except Exception as e:
-                    full_response = f"An error occurred: {e}"
-                    message_placeholder.markdown(full_response)
-
-                st.session_state.messages.append({"role": "assistant", "content": full_response})
-                logging.info(f"Bot: {full_response[:150]}...")  # Log first 150 chars
-
-            # Product suggestions
-            user_message_count = sum(1 for msg in st.session_state.messages if msg["role"] == "user")
-            if user_message_count > 2 and user_message_count % 3 == 0:
-                relevant_products = detect_relevant_products(st.session_state.messages)
-                if relevant_products:
-                    st.markdown("#### Recommended for You:")
-                    for product in relevant_products:
-                        st.markdown(f"- 📘 [{product['name']}]({product['url']})")
+# Setup lightweight logger
+logging.basicConfig(filename="usage_log_wellness.txt", level=logging.INFO, format="%(asctime)s - %(message)s")
+
+# Set up API key and model
+api_key = os.environ.get("GEMINI_API_KEY")
+genai.configure(api_key=api_key)
+model = genai.GenerativeModel('gemini-1.5-flash-8b')
+
+# Define system prompt
+system_prompt = """
+You are a friendly and knowledgeable wellness and fitness guide.
+Your goal is to help users improve their health, lifestyle, and overall well-being.
+Provide practical wellness and fitness tips. Based on the conversation, suggest suitable products from the list below (if appropriate).
+Here is your product list:
+- Dream Big, Move Forward Inch By Inch - ebook link https://www.rajamanickam.com/l/dykgcx?layout=profile
+- Best Motivational Quotes - ebook link https://www.rajamanickam.com/l/quotes?layout=profile
+- Course - AI for Beginners - course sales link https://www.rajamanickam.com/l/LearnAI?layout=profile
+- Ebook - AI Insights into the Bible - ebook link https://www.rajamanickam.com/l/vgizdq?layout=profile
+Use natural conversation, and only suggest the product seamlessly without visible promotion.
+"""
+
+# Define product catalog
+product_catalog = {
+    "motivation": {
+        "name": "Dream Big, Move Forward Inch By Inch",
+        "url": "https://www.rajamanickam.com/l/dykgcx?layout=profile",
+        "tags": ["motivation", "confidence", "goals"]
+    },
+    "ai": {
+        "name": "AI for Beginners Course",
+        "url": "https://www.rajamanickam.com/l/LearnAI?layout=profile",
+        "tags": ["ai", "learning", "career"]
+    },
+    "quotes": {
+        "name": "Best Motivational Quotes",
+        "url": "https://www.rajamanickam.com/l/quotes?layout=profile",
+        "tags": ["quotes", "inspiration"]
+    },
+    "bible": {
+        "name": "AI Insights into the Bible",
+        "url": "https://www.rajamanickam.com/l/vgizdq?layout=profile",
+        "tags": ["bible", "faith", "ai"]
+    }
+}
+
+
+# Function to detect relevant product suggestions
+def detect_relevant_products(chat_history):
+    suggestions = []
+    history_text = " ".join([msg["content"].lower() for msg in chat_history])
+    for key, product in product_catalog.items():
+        if any(tag in history_text for tag in product["tags"]):
+            if key not in st.session_state.suggested_products:
+                suggestions.append(product)
+                st.session_state.suggested_products.add(key)
+    return suggestions
+
+# Initialize session state
+if "messages" not in st.session_state:
+    st.session_state.messages = [
+        {"role": "assistant", "content": "👋 Welcome! I'm your wellness assistant. What Wellness topic would you like to explore today?"}
+    ]
+if "suggested_products" not in st.session_state:
+    st.session_state.suggested_products = set()
+
+
+# Streamlit UI
+st.markdown("[Dream Big](https://www.rajamanickam.com/l/dykgcx?layout=profile) | Use discount code `QPT` for AI course at [Rajamanickam.Com](https://www.rajamanickam.com/l/LearnAI?layout=profile)")
+
+st.title("Wellness Chatbot 💬")
+
+# Display chat history
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+# Chat input and assistant's response
+if prompt := st.chat_input("Ask your question about wellness topics..."):
+    
+
+    # Input length control
+    if len(prompt) > 500:
+        warning_msg = "⚠️ Please keep your question brief (under 500 characters) for better results."
+        st.session_state.messages.append({"role": "assistant", "content": warning_msg})
+        with st.chat_message("assistant"):
+            st.markdown(warning_msg)
+    else:
+        # Log user input
+        logging.info(f"User: {prompt}")
+
+        st.session_state.messages.append({"role": "user", "content": prompt})
+        with st.chat_message("user"):
+            st.markdown(prompt)
+
+        with st.chat_message("assistant"):
+            message_placeholder = st.empty()
+            full_response = ""
+            try:
+                past_convo = "\n".join([msg["content"] for msg in st.session_state.messages])
+                full_prompt = f"{system_prompt}\n{past_convo}\nUser: {prompt}\nAssistant:"
+
+                for chunk in model.generate_content(full_prompt, stream=True):
+                    full_response += (chunk.text or "")
+                    message_placeholder.markdown(full_response + "▌")
+                message_placeholder.markdown(full_response)
+            except Exception as e:
+                full_response = f"An error occurred: {e}"
+                message_placeholder.markdown(full_response)
+
+            st.session_state.messages.append({"role": "assistant", "content": full_response})
+            logging.info(f"Bot: {full_response[:150]}...")  # Log first 150 chars
+
+        # Product suggestions
+        user_message_count = sum(1 for msg in st.session_state.messages if msg["role"] == "user")
+
+        if user_message_count > 1 and user_message_count % 3 == 0: 
+            relevant_products = detect_relevant_products(st.session_state.messages)
+            if relevant_products:
+                st.markdown("#### Recommended for You:")
+                for product in relevant_products:
+                    st.markdown(f"- 📘 [{product['name']}]({product['url']})")