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chatbot/conversation.py

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+import uuid
+from langchain_community.chat_message_histories import SQLChatMessageHistory
+from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+from langchain_core.runnables.history import RunnableWithMessageHistory
+from langchain_google_genai import GoogleGenerativeAI  # Update based on your model
+from langchain_core.output_parsers  import StrOutputParser
+from config import DB_PATH  # Import database path
+import config
+
+# Generate a unique session ID
+def generate_session_id():
+    return str(uuid.uuid4())
+
+# Fetch session message history from the database
+def get_session_message_history_from_db(session_id):
+    chat_message_history = SQLChatMessageHistory(session_id=session_id, connection=f"sqlite:///{DB_PATH}")
+    return chat_message_history
+
+# Define a chat template
+chat_template = ChatPromptTemplate(
+    messages=[
+        ("system", """You are a helpful AI assistant. Provide clear, concise, and accurate responses. 
+                    Maintain a friendly and professional tone.  
+                    For technical queries, give step-by-step explanations and examples.  
+                    If a question is unclear, ask for clarification.  
+                    Keep responses engaging and contextually relevant.  
+                    If unsure, admit it rather than guessing."""), 
+        MessagesPlaceholder(variable_name="history"), 
+        ("human", "{human_input}")
+    ]
+)
+
+# Define the AI model (Update based on your API key and provider)
+model = GoogleGenerativeAI(model="gemini-1.5-pro", google_api_key=config.GOOGLE_API_KEY)
+
+
+# Define output parser
+output_parser = StrOutputParser()
+
+# Create the conversation chain
+chain = chat_template | model | output_parser
+
+# Use RunnableWithMessageHistory to manage chat history
+conversation_chain = RunnableWithMessageHistory(
+    chain, 
+    get_session_message_history_from_db,
+    input_messages_key="human_input", 
+    history_messages_key="history"
+)
+
+# Function to interact with the chatbot
+def chat_bot(prompt, session_id=None):
+    if session_id is None:
+        session_id = generate_session_id()  # Generate a new session ID if not provided
+
+    config = {"configurable": {"session_id": session_id}}
+    input_prompt = {"human_input": prompt}
+
+    response = conversation_chain.invoke(input_prompt, config=config)
+
+    return response, session_id  # Return both response and session ID

chatbot/database.py

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+import sqlite3
+from config import DB_PATH # Import database path from config.py
+
+def create_table():
+    """Creates the chat history table if it doesn't exist."""
+    conn = sqlite3.connect(DB_PATH)
+    cursor = conn.cursor()
+    cursor.execute("""
+        CREATE TABLE IF NOT EXISTS chat_history (
+            id INTEGER PRIMARY KEY AUTOINCREMENT,
+            session_id TEXT,
+            user_message TEXT,
+            bot_response TEXT,
+            timestamp DATETIME DEFAULT CURRENT_TIMESTAMP
+        )
+    """)
+    conn.commit()
+    conn.close()
+
+def get_chat_history(session_id):
+    """Fetches chat history for a given session."""
+    conn = sqlite3.connect(DB_PATH)
+    cursor = conn.cursor()
+    cursor.execute("SELECT user_message, bot_response FROM chat_history WHERE session_id=? ORDER BY timestamp", 
+                   (session_id,))
+    history = cursor.fetchall()
+    conn.close()
+    return history
+
+def save_chat(session_id, user_message, bot_response):
+    """Stores a chat message in the database."""
+    conn = sqlite3.connect(DB_PATH)
+    cursor = conn.cursor()
+    cursor.execute("INSERT INTO chat_history (session_id, user_message, bot_response) VALUES (?, ?, ?)", 
+                   (session_id, user_message, bot_response))
+    conn.commit()
+    conn.close()
+
+# Initialize the database
+create_table()