Update streamlit_app.py

streamlit_app.py

@@ -1,118 +1,3 @@
-# import streamlit as st
-# import requests
-# import json
-# import pandas as pd
-
-# st.set_page_config(page_title="QueryMate: Text to SQL & CSV")
-
-# st.markdown("# QueryMate: Text to SQL & CSV 💬🗄️")
-# st.markdown('''Welcome to QueryMate, your friendly assistant for converting natural language queries into SQL statements and CSV outputs!
-#                Let's get started with your data queries!''')
-
-# # Load chat history
-# def load_chat_history():
-#     try:
-#         with open('chat_history.json', 'r') as f:
-#             return json.load(f)
-#     except FileNotFoundError:
-#         return []
-
-# def save_chat_history(history):
-#     with open('chat_history.json', 'w') as f:
-#         json.dump(history, f)
-
-# chat_history = load_chat_history()
-
-# # Data source selection
-# data_source = st.radio("Select Data Source:", ('SQL Database', 'Employee CSV'))
-
-# # Predefined queries
-# predefined_queries = {
-#     'SQL Database': [
-#         'Print all students',
-#         'Count total number of students',
-#         'List students in Data Science class'
-#     ],
-#     'Employee CSV': [
-#         'Print employees having the department id equal to 100',
-#         'Count total number of employees',
-#         'List Top 5 employees according to salary in descending order'
-#     ]
-# }
-
-# st.markdown(f"### Predefined Queries for {data_source}")
-
-# # Create buttons for predefined queries
-# for query in predefined_queries[data_source]:
-#     if st.button(query):
-#         st.session_state.predefined_query = query
-
-# st.markdown("### Enter Your Question")
-# question = st.text_input("Input: ", key="input", value=st.session_state.get('predefined_query', ''))
-
-# # Submit button
-# submit = st.button("Submit")
-
-# if submit:
-#     # Send request to FastAPI backend
-#     response = requests.post("http://localhost:8000/query", 
-#                              json={"question": question, "data_source": data_source})
-#     if response.status_code == 200:
-#         data = response.json()
-#         st.markdown(f"## Generated {'SQL' if data_source == 'SQL Database' else 'Pandas'} Query")
-#         st.code(data['query'])
-        
-#         st.markdown("## Query Results")
-#         result = data['result']
-        
-#         if isinstance(result, list) and len(result) > 0:
-#             if isinstance(result[0], dict):
-#                 # For CSV queries that return a list of dictionaries
-#                 df = pd.DataFrame(result)
-#                 st.dataframe(df)
-#             elif isinstance(result[0], list):
-#                 # For SQL queries that return a list of lists
-#                 df = pd.DataFrame(result)
-#                 st.dataframe(df)
-#             else:
-#                 # For single column results
-#                 st.dataframe(pd.DataFrame(result, columns=['Result']))
-#         elif isinstance(result, dict):
-#             # For single row results
-#             st.table(result)
-#         else:
-#             # For scalar results or empty results
-#             st.write(result)
-
-#         if data_source == 'Employee CSV':
-#             st.markdown("## Available CSV Columns")
-#             st.write(data['columns'])
-
-#         # Update chat history
-#         chat_history.append(f"👨‍💻({data_source}): {question}")
-#         chat_history.append(f"🤖: {data['query']}")
-#         save_chat_history(chat_history)
-#     else:
-#         st.error(f"Error processing your request: {response.text}")
-
-#     # Clear the predefined query from session state
-#     st.session_state.pop('predefined_query', None)
-
-# # Display chat history
-# st.markdown("## Chat History")
-# for message in chat_history:
-#     st.text(message)
-
-# # Option to clear chat history
-# if st.button("Clear Chat History"):
-#     chat_history.clear()
-#     save_chat_history(chat_history)
-#     st.success("Chat history cleared!")
-
-
-
-
-
 import streamlit as st
 import requests
 import pandas as pd