setback

app.py

@@ -2,11 +2,6 @@ import chainlit as cl
 import pandas as pd
 import time
 from typing import Dict, Any
-import os
-import json
-from datetime import datetime
-import hashlib
-import uuid
 
 from agents.table_selection import table_selection_agent
 from agents.data_retrieval import sample_data_retrieval_agent
@@ -16,167 +11,42 @@ from agents.execution import execution_agent
 from utils.bigquery_utils import init_bigquery_connection
 from utils.feedback_utils import save_feedback_to_bigquery
 
-# File to store chat history
-HISTORY_DIR = "chat_history"
-os.makedirs(HISTORY_DIR, exist_ok=True)
-
-# Function to get or create a user ID
-def get_user_id():
-    # Check if user already has an ID
-    user_id = cl.user_session.get("user_id")
-    
-    if not user_id:
-        # Generate a new user ID if none exists
-        # In a real app, you might use authentication or cookies
-        user_id = str(uuid.uuid4())
-        cl.user_session.set("user_id", user_id)
-        
-        # Create a user directory for this user
-        user_dir = os.path.join(HISTORY_DIR, user_id)
-        os.makedirs(user_dir, exist_ok=True)
-    
-    return user_id
-
-# Function to save chat history
-def save_chat_history(user_id, conversation_id, user_message, assistant_response):
-    user_dir = os.path.join(HISTORY_DIR, user_id)
-    os.makedirs(user_dir, exist_ok=True)
-    
-    history_file = os.path.join(user_dir, f"{conversation_id}.json")
-    
-    # Load existing history if it exists
-    if os.path.exists(history_file):
-        with open(history_file, 'r') as f:
-            history = json.load(f)
-    else:
-        history = {
-            "conversation_id": conversation_id,
-            "created_at": datetime.now().isoformat(),
-            "messages": []
-        }
-    
-    # Add new messages
-    timestamp = datetime.now().isoformat()
-    history["messages"].append({
-        "timestamp": timestamp,
-        "user": user_message,
-        "assistant": assistant_response
-    })
-    
-    # Save updated history
-    with open(history_file, 'w') as f:
-        json.dump(history, f, indent=2)
-
-# Function to load chat history for a user
-def load_chat_history(user_id, conversation_id=None):
-    user_dir = os.path.join(HISTORY_DIR, user_id)
-    
-    if not os.path.exists(user_dir):
-        return []
-    
-    if conversation_id:
-        # Load specific conversation
-        history_file = os.path.join(user_dir, f"{conversation_id}.json")
-        if os.path.exists(history_file):
-            with open(history_file, 'r') as f:
-                return json.load(f)
-        return None
-    else:
-        # Load all conversations (just metadata)
-        conversations = []
-        for filename in os.listdir(user_dir):
-            if filename.endswith('.json'):
-                with open(os.path.join(user_dir, filename), 'r') as f:
-                    data = json.load(f)
-                    conversations.append({
-                        "conversation_id": data["conversation_id"],
-                        "created_at": data["created_at"],
-                        "message_count": len(data["messages"])
-                    })
-        return sorted(conversations, key=lambda x: x["created_at"], reverse=True)
-
 @cl.on_chat_start
-async def start():
-    # Get or create user ID
-    user_id = get_user_id()
-    
-    # Create a new conversation ID for this session
-    conversation_id = str(uuid.uuid4())
-    cl.user_session.set("conversation_id", conversation_id)
+async def on_chat_start():
+    """Initialize the chat session."""
+    # Initialize BigQuery client
+    client = init_bigquery_connection()
     
-    # Load previous conversations for this user
-    conversations = load_chat_history(user_id)
+    # Store the client in the user session
+    cl.user_session.set("client", client)
     
-    if conversations:
-        # Display a welcome back message
-        await cl.Message(
-            content=f"Welcome back! You have {len(conversations)} previous conversations.",
-        ).send()
-        
-        # Create a dropdown to select previous conversations
-        options = [{"value": conv["conversation_id"], "label": f"Conversation from {conv['created_at'][:10]} ({conv['message_count']} messages)"} for conv in conversations]
-        options.insert(0, {"value": "new", "label": "Start a new conversation"})
-        
-        res = await cl.AskUserMessage(
-            content="Would you like to continue a previous conversation or start a new one?",
-            timeout=30,
-            select={"options": options, "value": "new"}
-        ).send()
-        
-        if res and res.get("value") != "new":
-            # User selected a previous conversation
-            selected_conv_id = res.get("value")
-            cl.user_session.set("conversation_id", selected_conv_id)
-            
-            # Load the selected conversation
-            conversation = load_chat_history(user_id, selected_conv_id)
-            if conversation:
-                # Display previous messages
-                await cl.Message(content="Loading your previous conversation...").send()
-                for msg in conversation["messages"]:
-                    await cl.Message(content=msg["user"], author="You").send()
-                    await cl.Message(content=msg["assistant"]).send()
-    else:
-        # First time user
-        await cl.Message(
-            content="Welcome to the E-commerce Analytics Assistant! How can I help you today?",
-        ).send()
-    
-    # Add option to clear history
-    await cl.Action(name="clear_history", label="Clear Chat History", description="Erase all previous conversation history").send()
-
-@cl.on_message
-async def on_message(message: cl.Message):
-    # Get user and conversation IDs
-    user_id = cl.user_session.get("user_id")
-    conversation_id = cl.user_session.get("conversation_id")
-    
-    # Process the message and generate a response
-    # Replace this with your actual processing logic
-    response = f"You said: {message.content}"
-    
-    # Send the response
-    await cl.Message(content=response).send()
+    # Send a welcome message
+    await cl.Message(
+        content="👋 Welcome to the Natural Language to SQL Query Assistant! Ask me any question about your e-commerce data.",
+        author="SQL Assistant"
+    ).send()
     
-    # Save to chat history
-    save_chat_history(user_id, conversation_id, message.content, response)
-
-@cl.action_callback("clear_history")
-async def clear_history_callback(action):
-    user_id = cl.user_session.get("user_id")
-    conversation_id = cl.user_session.get("conversation_id")
+    # Add some example questions without using actions
+    await cl.Message(
+        content="Here are some example questions you can ask:",
+        author="SQL Assistant"
+    ).send()
     
-    # Clear specific conversation or all conversations
-    user_dir = os.path.join(HISTORY_DIR, user_id)
-    history_file = os.path.join(user_dir, f"{conversation_id}.json")
+    examples = [
+        "What are the top 5 products by revenue?",
+        "How many orders were placed in the last month?",
+        "Which customers spent the most in 2023?",
+        "What is the average order value by product category?"
+    ]
     
-    if os.path.exists(history_file):
-        os.remove(history_file)
-        await cl.Message(content="Your current conversation history has been cleared.").send()
+    # Display all examples in a single message
+    examples_text = "\n\n".join([f"• {example}" for example in examples])
+    examples_text += "\n\n(You can copy and paste any of these examples to try them out)"
     
-    # Create a new conversation ID
-    new_conversation_id = str(uuid.uuid4())
-    cl.user_session.set("conversation_id", new_conversation_id)
+    await cl.Message(
+        content=examples_text,
+        author="SQL Assistant"
+    ).send()
 
 @cl.on_message
 async def on_message(message: cl.Message):