Update app.py

app.py

@@ -1,41 +1,41 @@
-import streamlit as st
-import requests  # Standard library for sending API requests
-
-st.set_page_config(page_title="Medical AI Assistant", layout="centered")
-st.title("⚕️ General Medicine Chatbot")
-
-# This is the address of your FastAPI "Brain"
-API_URL = "http://127.0.0.1:8000/ask"
-
-# Initialize chat history
-if "messages" not in st.session_state:
-    st.session_state.messages = []
-
-# Display previous messages
-for message in st.session_state.messages:
-    with st.chat_message(message["role"]):
-        st.markdown(message["content"])
-
-if prompt := st.chat_input("Ask a medical question..."):
-    # 1. Display user message
-    st.chat_message("user").markdown(prompt)
-    st.session_state.messages.append({"role": "user", "content": prompt})
-
-    # 2. Call the API
-    with st.chat_message("assistant"):
-        with st.spinner("Thinking..."):
-            try:
-                # We send the query to your FastAPI server
-                # Note: 'query' must match the Pydantic model in main.py
-                payload = {"query": prompt}
-                response = requests.post(API_URL, json=payload)
-                
-                if response.status_code == 200:
-                    answer = response.json().get("answer", "No answer found.")
-                    st.markdown(answer)
-                    st.session_state.messages.append({"role": "assistant", "content": answer})
-                else:
-                    st.error(f"API Error {response.status_code}: {response.text}")
-            
-            except Exception as e:
+import streamlit as st
+import requests  # Standard library for sending API requests
+
+st.set_page_config(page_title="Medical AI Assistant", layout="centered")
+st.title("⚕️ General Medicine Chatbot")
+
+# This is the address of your FastAPI "Brain"
+API_URL = "http://0.0.0.0:8000/ask"
+
+# Initialize chat history
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+# Display previous messages
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+if prompt := st.chat_input("Ask a medical question..."):
+    # 1. Display user message
+    st.chat_message("user").markdown(prompt)
+    st.session_state.messages.append({"role": "user", "content": prompt})
+
+    # 2. Call the API
+    with st.chat_message("assistant"):
+        with st.spinner("Thinking..."):
+            try:
+                # We send the query to your FastAPI server
+                # Note: 'query' must match the Pydantic model in main.py
+                payload = {"query": prompt}
+                response = requests.post(API_URL, json=payload)
+                
+                if response.status_code == 200:
+                    answer = response.json().get("answer", "No answer found.")
+                    st.markdown(answer)
+                    st.session_state.messages.append({"role": "assistant", "content": answer})
+                else:
+                    st.error(f"API Error {response.status_code}: {response.text}")
+            
+            except Exception as e:
                 st.error(f"Could not connect to the API. Is Uvicorn running? Error: {e}")