Fixed

app.py

@@ -1,114 +0,0 @@
-import streamlit as st
-import requests
-import uuid
-import time
-
-# --- CONFIGURATION ---
-API_URL = "http://localhost:8000" # Your FastAPI server URL
-
-st.set_page_config(page_title="Text@SQL Agent", page_icon="🤖", layout="centered")
-
-# --- SESSION STATE INITIALIZATION ---
-# This ensures variables survive when Streamlit re-renders the page
-if "thread_id" not in st.session_state:
-    st.session_state.thread_id = str(uuid.uuid4()) # Unique session ID for LangGraph memory
-if "user_id" not in st.session_state:
-    st.session_state.user_id = "tenant_" + str(uuid.uuid4())[:8]
-if "is_db_connected" not in st.session_state:
-    st.session_state.is_db_connected = False
-if "connection_url" not in st.session_state:
-    st.session_state.connection_url = ""
-if "chat_history" not in st.session_state:
-    st.session_state.chat_history = []
-
-# --- SIDEBAR: DATABASE CONNECTION ---
-with st.sidebar:
-    st.header("⚙️ Database Setup")
-    
-    # If already connected, disable the input to enforce ONE database connection
-    db_input = st.text_input(
-        "Enter Database URL:",
-        disabled=st.session_state.is_db_connected
-    )
-    
-    if not st.session_state.is_db_connected:
-        if st.button("Connect & Initialize", type="primary", use_container_width=True):
-            if not db_input:
-                st.error("Please enter a valid URL.")
-            else:
-                with st.spinner("Building embeddings and initializing agent..."):
-                    try:
-                        # 1. Hit your FastAPI upload endpoint
-                        payload = {"connection_url": db_input, "user_id": st.session_state.user_id}
-                        response = requests.post(f"{API_URL}/upload_url", json=payload)
-                        
-                        if response.status_code == 200:
-                            # 2. Lock the connection and unlock the chat
-                            st.session_state.is_db_connected = True
-                            st.session_state.connection_url = db_input
-                            
-                            # Because your FastAPI upload uses BackgroundTasks, it returns instantly. 
-                            # We add a 2-second UI buffer here so the Qdrant embeddings have time to finish 
-                            # before the user fires off their first chat question.
-                            time.sleep(15) 
-                            
-                            st.success("Database connected securely!")
-                            st.rerun() # Refresh UI to unlock the chat window
-                        else:
-                            st.error(f"Failed to connect: {response.text}")
-                    except requests.exceptions.ConnectionError:
-                        st.error("🚨 Cannot connect to backend. Is FastAPI running?")
-    else:
-        st.success("✅ Connected to Database")
-        st.caption(f"URL: {st.session_state.connection_url}")
-        
-        # Add a reset button just in case they want to start completely over
-        if st.button("Disconnect & Reset", use_container_width=True):
-            st.session_state.clear()
-            st.rerun()
-
-# --- MAIN CHAT INTERFACE ---
-st.title("🗣️ Text2SQL Agent")
-
-# The Lock: Do not render the chat if DB is not connected
-if not st.session_state.is_db_connected:
-    st.info("👈 Please connect your database in the sidebar to begin analyzing data.")
-else:
-    # 1. Display previous chat messages from session state
-    for msg in st.session_state.chat_history:
-        with st.chat_message(msg["role"]):
-            st.markdown(msg["content"])
-
-    # 2. The Chat Input box
-    if user_query := st.chat_input("Ask a question about your data..."):
-        
-        # Immediately display the user's question in the UI
-        st.session_state.chat_history.append({"role": "user", "content": user_query})
-        with st.chat_message("user"):
-            st.markdown(user_query)
-
-        # 3. Call the LangGraph Backend
-        with st.chat_message("assistant"):
-            with st.spinner("Analyzing schema and generating SQL..."):
-                try:
-                    payload = {
-                        "message": user_query,
-                        "thread_id": st.session_state.thread_id,
-                        "user_id": st.session_state.user_id,
-                        "connection_url": st.session_state.connection_url
-                    }
-                    
-                    response = requests.post(f"{API_URL}/chat", json=payload)
-                    
-                    if response.status_code == 200:
-                        # Extract the final_result from your FastAPI JSON response
-                        answer = response.json().get("response", "No response found.")
-                        st.markdown(answer)
-                        
-                        # Save the assistant's answer to the UI history
-                        st.session_state.chat_history.append({"role": "assistant", "content": answer})
-                    else:
-                        st.error(f"Agent Error: {response.text}")
-                        
-                except requests.exceptions.ConnectionError:
-                    st.error("🚨 Connection dropped. Ensure FastAPI is running.")