Update app.py

app.py

@@ -5,6 +5,7 @@ import uuid
 
 import pandas as pd
 from datetime import datetime
+import sqlite3
 
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
 from langchain_community.utilities.sql_database import SQLDatabase
@@ -290,20 +291,24 @@ Here’s a comprehensive system prompt for your e-commerce chatbot with clear in
 You are an intelligent e-commerce chatbot designed to assist users with post-order queries. Gather necessary information from the user to help them with their query.
 Use the following workflow to solve user queries. do not provide sql inputs to the sql tool - you only need to ask in natural language what information you need.
   - If at any point you cannot determine the next steps - defer to human. you do not have clearance to go beyond the scope the following flow.
+
+Following is the information about the customer from the last 2 weeks: 
+{df}
+If this information is not enough, fetch necessary information usign the sql_tool.
+
 ### **Workflow:**
 #### 1. **Cancel Order**
 - Get necessary details and why customer wants to cancel.
 - Retrieve cancellation fee, validity period, and amount for the product with `sql_tool`.
 - Check If the cancellation meets the criteria - proceed to "Get Refund" flow.
 #### 2. **Check Cancellation Fee**
-- Check the cancellation fee using `sql_tool`.
+- Return the Cancellation Fee
 #### 3. **Check Refund Policy**
-- Provide the refund policy details using `sql_tool`.
+- Provide the refund policy details.
 #### 4. **Get Invoice**
-- Retrieve necessary details using `sql_tool`.
+- Retrieve necessary details.
 - Provide the invoice information to the customer.
 #### 5. **Get Refund**
-- Retrieve necessary details using `sql_tool`.
 - Retrieve cancellation fee, validity period, and amount for the product with `sql_tool`.
 - Check If the cancellation meets the criteria: i.e,
   if the order is within the validity period by checking days since purchase - use the days_since tool to calculate the number of days since delivery
@@ -311,15 +316,15 @@ Use the following workflow to solve user queries. do not provide sql inputs to t
   if the customer is okay with the cancellation fee - do not proceed to cancel if the customer is not okay with the cancellation fee
   - Call `cancel_order`.
   - Process a refund using `process_refund` (output as JSON). refund amount should be product price - cancellation fee.
-  if it doesn't meet the criteria you do not have the clearance to process refund. defer to human.
+  if it doesn't meet the criteria you do not have the clearance to process refund. defer to human. 
+  Also, provide necessary information to the customer on why you took that decision. It is important to let the customer know why something is done.
 - If at any point you cannot determine the next steps - defer to human.
 #### 6. **Track Order/Track Refund**
-- Get necessary information from user
-- Retrieve the order or refund status using `sql_tool`.
-- Provide the information to the customer.
+- Return the order or refund status.
 #### 7. **Change Shipping Address**
-- Retrieve necessary details using `sql_tool`.
+- Retrieve necessary details.
 - Update the shipping address with `change_address`.
+
 MANDATORY STEP:
 After helping the customer with their concern,
 - Ask if the customer needs help with anything else. If they ask for anything from the above list help them.
@@ -330,6 +335,7 @@ Once the customer confirms they do not need any further assistance:
    - The category of the query (e.g., cancellation, refund, tracking, etc.).
    - The feedback received.
    - the rating given
+   
 ---
 ### **Handling Out-of-Scope Queries:**
 If the user's query, at any point is not covered by the workflows above:
@@ -338,6 +344,7 @@ If the user's query, at any point is not covered by the workflows above:
 - End the conversation.
 ---
 ### **Important Notes for the Model:**
+- Be empathetic to the customer but loyal to the instructions provided to you. Try to deescalate a situation before 
 - Always aim to minimize the number of questions asked by retrieving as much information as possible from the database using `sql_tool` - retrieve customer information using any details provided and use it throughout the conversation.
 - Follow the exact workflows for each query category.
 - Ensure smooth transitions between steps, asking the customer if they need further assistance after resolving their issue.
@@ -369,17 +376,70 @@ agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
 
 #================================LOGIN=========================================#
 
-# Function to check login credentials
 def check_login(email, phone):
-    query = f'''
-    SELECT COUNT(*) as count 
-    FROM customers 
-    WHERE email = "{email}" AND phone_number = "{phone}"
-    '''
-    result = sql_tool(query)
-    return int(result.strip()) > 0  # Assuming result is returned as a single integer-like string
-
+    try:
+        # Connect to the SQLite database
+        connection = sqlite3.connect("2911.db")  # Replace with your .db file path
+        cursor = connection.cursor()
+
+        # Query to count matching customers
+        query = """
+        SELECT COUNT(*)
+        FROM customers
+        WHERE email = ? AND phone = ?;
+        """
+        cursor.execute(query, (email, phone))
+        result = cursor.fetchone()
+ 
+        # Extract the count and return
+        customer_count = result[0] if result else 0
+
+        query = """
+        SELECT
+            c.customer_id,
+            c.first_name || ' ' || c.last_name AS customer_name,
+            c.email,
+            c.phone,
+            c.address AS customer_address,
+            o.order_id,
+            o.order_date,
+            o.status AS order_status,
+            o.price AS order_price,
+            p.name AS product_name,
+            p.price AS product_price,
+            i.invoice_date,
+            i.amount AS invoice_amount,
+            i.invoice_url,
+            s.delivery_date,
+            s.shipping_status,
+            s.shipping_address,
+            r.refund_amount,
+            r.refund_status
+        FROM Customers c
+        LEFT JOIN Orders o ON c.customer_id = o.customer_id
+        LEFT JOIN Products p ON o.product_id = p.product_id
+        LEFT JOIN Invoices i ON o.order_id = i.order_id
+        LEFT JOIN Shipping s ON o.order_id = s.order_id
+        LEFT JOIN Refund r ON o.order_id = r.order_id
+        WHERE o.order_date >= datetime('now', '-14 days')
+        ORDER BY o.order_date DESC;
+        """
+        global df
+        # Execute the query and fetch data into a DataFrame
+        df = pd.read_sql_query(query, connection)
+        st.write(df)
+        
+        return customer_count > 0  # True if at least 1 customer matches
 
+    except Exception as e:
+        print(f"Error: {e}")
+        return False
+
+    finally:
+        # Close the connection
+        if connection:
+            cursor.close()
+            connection.close()
 
 # Function to process user input and generate a chatbot response
 def chat_with_agent():