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app.py

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+import os
+import datetime
+
+import google.generativeai as genai
+import streamlit as st 
+
+from dotenv import load_dotenv
+from typing import Any, Dict, List 
+
+from db_ops import get_recent_conversations, init_db, store_conversation_summary, store_message 
+
+# Loading environment variables from .env file 
+load_dotenv()
+
+# Configure Gemini API 
+gemini_api_key = os.getenv("GEMINI_API_KEY")
+genai.configure(api_key=gemini_api_key)
+
+# Intialize the gemini Model 
+model = genai.GenerativeModel("gemini-2.0-flash")
+
+
+def chat_with_gemini(prompt:str, chat_history:List[Dict[str, str]]) -> str:
+    try:
+        # Format the message for Gemini 
+        messages = []
+        for msg in chat_history:
+            if msg["role"] == "user":
+                messages.append({"role": "user", "parts": msg["content"]})
+            else:
+                messages.append({"role": "model", "parts": [msg["content"]]})
+
+        # Add current prompt 
+        messages.append({"role": "user", "parts": [prompt]}) 
+
+        # Generate the response from Gemini 
+        chat = model.start_chat(history=messages[:-1])
+        response = chat.send_message(prompt)
+        return response.text 
+    except Exception as e:
+        return f"Error communicating with GEMINI API: {str(e)}" 
+    
+
+def summarize_conversations(conversations:List[Dict[str, Any]])->str:
+    if not conversations:
+        return "No recent conversations to summarize."
+    
+    # Format conversations for the model
+    conversation_texts = []
+    for idx, conv in enumerate(conversations, 1):
+        conv_text = f"Conversation {idx} ({conv['timestamp']}):\n"
+        for msg in conv["messages"]:
+            conv_text += f"{msg['role'].upper()}: {msg['content']}\n"
+        conversation_texts.append(conv_text)
+
+    prompt = f"""
+    Please provide a concise summary of the following recent conversations:
+
+    {"\n\n".join(conversation_texts)}
+
+    Focus on key topics discussed, questions asked, and information provided.
+    Highlight any recurring themes or import points.
+    """
+
+    response = model.generate_content(prompt.strip())
+    return response.text
+
+
+# Streamlit UI 
+def main():
+    st.set_page_config(page_title="Gemini-Chatbot", page_icon="🤖")
+    st.title("🤖 Gemini AI Chatbot")
+
+    # Intialize the database 
+    init_db()
+
+    # Intialize session state for chat history and session ID
+    if "session_id" not in st.session_state:
+        st.session_state.session_id = datetime.datetime.now().strftime("%Y%m%d%H%M%S")
+
+    if "chat_history" not in st.session_state:
+        st.session_state.chat_history = []
+
+    # Chat input area 
+    with st.container():
+        user_input = st.chat_input("Type your message here...") 
+
+        if user_input:
+            # Add user message to chat history
+            st.session_state.chat_history.append({"role": "user", "content": user_input})
+            store_message(st.session_state.session_id, "user", user_input)
+
+            # Get response from Gemini AI
+            with st.spinner("Thinking..."):
+                response = chat_with_gemini(user_input, st.session_state.chat_history)
+
+            # Add assistant message to chat history
+            st.session_state.chat_history.append({"role": "assistant", "content": response})
+            store_message(st.session_state.session_id, "assistant", response)
+
+    # Display the chat history 
+    for message in st.session_state.chat_history:
+        with st.chat_message(message["role"]):
+            st.write(message["content"])
+
+    # Sidebar for recent conversations
+    with st.sidebar:
+        st.title("Conversation Recall")
+
+        if st.button("🌸 Summarize Recent conversations"):
+            with st.spinner("Generating summary..."):
+                # Get recent conversations 
+                recent_convs = get_recent_conversations(st.session_state.session_id, limit=5)
+
+                # Generate summary 
+                summary = summarize_conversations(recent_convs)
+
+                # Store summary for recent conversations 
+                if recent_convs:
+                    store_conversation_summary(st.session_state.session_id, recent_convs[0]["id"], summary)
+
+                # Display summary
+                st.subheader("Summary of Recent Conversations")
+                st.write(summary)
+
+        # Clear chat button 
+        if st.button("🗑️ Clear Chat"):
+            st.session_state.chat_history = []
+            st.session_state.session_id = datetime.datetime.now().strftime("%Y%m%d%H%M%S")
+            st.success("Chat history cleared!")
+            st.rerun()
+
+if __name__ == "__main__":
+    main()

db_ops.py

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+import sqlite3
+
+from typing import Any, Dict, List
+
+# Database Design 
+def init_db():
+    """Initialize SQLite database with required tables"""
+    conn = sqlite3.connect("chatbot.db")
+    c = conn.cursor()
+
+    # Create conversations table 
+    c.execute("""
+CREATE TABLE IF NOT EXISTS conversations (
+    id INTEGER PRIMARY KEY AUTOINCREMENT,
+    session_id TEXT NOT NULL,  
+    timestamp DATETIME DEFAULT CURRENT_TIMESTAMP,
+    summary TEXT        
+)
+""")
+    
+    # Create messages table 
+    c.execute("""
+CREATE TABLE IF NOT EXISTS messages (
+    id INTEGER PRIMARY KEY AUTOINCREMENT, 
+    conversation_id INTEGER,
+    role TEXT NOT NULL, 
+    content TEXT NOT NULL, 
+    timestamp DATETIME DEFAULT CURRENT_TIMESTAMP, 
+    FOREIGN KEY (conversation_id) REFERENCES conversations (id)                        
+)
+""")
+    
+    conn.commit()
+    conn.close()
+
+# Adding Conversations
+def store_message(session_id:str, role:str, content:str)->None:
+    """Store a message in the database"""
+    conn = sqlite3.connect("chatbot.db")
+    c = conn.cursor()
+
+    # Get current conversation id or create new one 
+    c.execute("SELECT id FROM conversations WHERE session_id=? ORDER BY timestamp DESC LIMIT 1",
+               (session_id,))
+    result = c.fetchone()
+
+    if result is None:
+        # Create a new conversation 
+        c.execute("INSERT INTO conversations (session_id) VALUES (?)", (session_id,))
+        conversation_id = c.lastrowid
+    else:
+        conversation_id = result[0] 
+
+    # Store message 
+    c.execute("INSERT INTO messages (conversation_id, role, content) VALUES (?, ?, ?)", 
+              (conversation_id, role, content))
+    
+    conn.commit()
+    conn.close()
+
+# Retrieve Conversations
+def get_recent_conversations(session_id:str, limit:int=5)->List[Dict[str, Any]]:
+    """Retrieve the most recent conversation for a session"""
+    conn = sqlite3.connect("chatbot.db")
+    conn.row_factory = sqlite3.Row
+    c = conn.cursor()
+
+    # Get recent conversation ID 
+    c.execute('''
+SELECT id, timestamp FROM conversations 
+WHERE session_id = ?
+ORDER BY timestamp DESC 
+LIMIT ?
+''', (session_id, limit))
+    
+    conversations = []
+
+    for conv_row in c.fetchall():
+        conv_id = conv_row["id"]
+
+        # Get messages for this conversations 
+        c.execute('''
+SELECT role, content FROM messages 
+WHERE conversation_id = ? 
+ORDER BY timestamp ASC
+''', (conv_id,)) 
+        
+        messages = []
+        for msg in c.fetchall():
+            messages.append({"role": msg["role"], "content": msg["content"]})
+
+        conversations.append({
+            "id": conv_id, 
+            "timestamp": conv_row["timestamp"], 
+            "messages":messages
+        })
+
+    conn.close()
+    return conversations 
+
+# Storing Conversations 
+def store_conversation_summary(session_id:str, conv_id:int, summary:str)->None:
+    """Store a generated summary for a conversation"""
+    conn = sqlite3.connect("chatbot.db")
+    c = conn.cursor()
+
+    # Update the summary for the conversation 
+    c.execute('''UPDATE conversations SET summary = ? WHERE id = ?''', (summary, conv_id))
+    conn.commit()
+    conn.close()

requirements.txt

@@ -1,3 +1,60 @@
-altair
-pandas
-streamlit
+altair==5.5.0
+annotated-types==0.7.0
+attrs==25.3.0
+blinker==1.9.0
+cachetools==5.5.2
+certifi==2025.1.31
+charset-normalizer==3.4.1
+click==8.1.8
+colorama==0.4.6
+gitdb==4.0.12
+GitPython==3.1.44
+google-ai-generativelanguage==0.6.15
+google-api-core==2.24.2
+google-api-python-client==2.167.0
+google-auth==2.39.0
+google-auth-httplib2==0.2.0
+google-generativeai==0.8.5
+googleapis-common-protos==1.70.0
+grpcio==1.71.0
+grpcio-status==1.71.0
+httplib2==0.22.0
+idna==3.10
+Jinja2==3.1.6
+jsonschema==4.23.0
+jsonschema-specifications==2025.4.1
+MarkupSafe==3.0.2
+narwhals==1.36.0
+numpy==2.2.5
+packaging==24.2
+pandas==2.2.3
+pillow==11.2.1
+proto-plus==1.26.1
+protobuf==5.29.4
+pyarrow==19.0.1
+pyasn1==0.6.1
+pyasn1_modules==0.4.2
+pydantic==2.11.3
+pydantic_core==2.33.1
+pydeck==0.9.1
+pyparsing==3.2.3
+python-dateutil==2.9.0.post0
+python-dotenv==1.1.0
+pytz==2025.2
+referencing==0.36.2
+requests==2.32.3
+rpds-py==0.24.0
+rsa==4.9.1
+six==1.17.0
+smmap==5.0.2
+streamlit==1.44.1
+tenacity==9.1.2
+toml==0.10.2
+tornado==6.4.2
+tqdm==4.67.1
+typing-inspection==0.4.0
+typing_extensions==4.13.2
+tzdata==2025.2
+uritemplate==4.1.1
+urllib3==2.4.0
+watchdog==6.0.0