Update app.py

app.py

@@ -1,36 +1,35 @@
-import streamlit as st
-import requests
+import gradio as gr
 
-# Streamlit app setup
-st.title("Healthcare AI Avatar Chatbot")
-st.markdown("""
-    This AI-powered avatar can assist with blindness treatment support and cosmetic surgery consultations. 
-    It can answer questions, guide patients, and collect necessary information securely.
-""")
+# Define a function for user interaction (if needed)
+def get_user_input(user_input):
+    # Here, you can process the input if necessary
+    return f"You said: {user_input}"
 
-# Avatar iframe embedded
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=get_user_input,
+    inputs="text",
+    outputs="text",
+    title="AI Avatar with D-ID",
+    description="Interact with your D-ID AI Avatar."
+)
+
+# Add HTML for D-ID AI Avatar
 avatar_html = """
-<script type="module"
+<div>
+    <script
+        type="module"
         src="https://agent.d-id.com/v1/index.js"
         data-name="did-agent"
         data-mode="fabio"
-        data-client-key="Z29vZ2xlLW9hdXRoMnwxMDE2MjgxNTc0MjI0MDkzMDQ0NzM6eUZROFMxSkRpV01NT2o0MThCQWFB"
+        data-client-key="Z29vZ2dlLW9hdXRoMnwxMDE2MjgxNTc0MjI0MDkzMDQ0NzM6eUZROFMxSkRpV01NT2o0MThCQWFB"
         data-agent-id="agt_RqZwS4UC"
         data-monitor="true">
-</script>
+    </script>
+</div>
 """
 
-st.components.v1.html(avatar_html, height=500)
-
-# Chatbot interaction
-st.markdown("### Ask me anything about blindness treatment or cosmetic surgery consultations!")
-user_input = st.text_input("Your question:")
-
-if user_input:
-    # Call the backend FastAPI chatbot API (to be created in step 2)
-    response = requests.post("http://localhost:8000/chat", json={"question": user_input})
-    bot_response = response.json().get("response")
+# Launch the Gradio interface with the HTML
+iface.launch(share=True, inline=True)
 
-    # Display chatbot response
-    st.markdown(f"**AI Avatar Response:** {bot_response}")