Update app.py

app.py

@@ -12,7 +12,9 @@ import gradio as gr
 api_key = os.getenv('OPENAI_API_KEY')
 extractor_agents = {
     "Solution Specifier A": os.getenv('ASSISTANT_ID_SOLUTION_SPECIFIER_A'),
-    "Solution Specifier A1": os.getenv('ASSISTANT_ID_SOLUTION_SPECIFIER_A1'),
+    "Solution Specifier B": os.getenv('ASSISTANT_ID_SOLUTION_SPECIFIER_B'),
+    "Solution Specifier C": os.getenv('ASSISTANT_ID_SOLUTION_SPECIFIER_C'),
+    "Solution Specifier D": os.getenv('ASSISTANT_ID_SOLUTION_SPECIFIER_D'),
 }
 
 # Function to create a new extractor LLM instance
@@ -45,15 +47,25 @@ def predict(message, history, selected_agent):
     non_cited_output = remove_citation(output)
     return non_cited_output
 
-# Define the Gradio interface
-dropdown = gr.Dropdown(choices=list(extractor_agents.keys()), value="Solution Specifier A", label="Choose Extractor Agent")
-
-chat_interface = gr.ChatInterface(
-    fn=predict,
-    additional_inputs=[dropdown],
-    title="Solution Specifier Chat",
-    description="Test with different solution specifiers"
-)
+# Define the Gradio interface using Blocks for layout
+def app_interface():
+    with gr.Blocks() as demo:
+        with gr.Row():
+            dropdown = gr.Dropdown(
+                choices=list(extractor_agents.keys()),
+                value="Solution Specifier A",
+                label="Choose Extractor Agent",
+                interactive=True,
+            )
+        with gr.Row():
+            chat = gr.ChatInterface(
+                fn=predict,
+                additional_inputs=[dropdown],
+                title="Solution Specifier Chat",
+                description="Test with different solution specifiers"
+            )
+    return demo
 
 # Launch the app
+chat_interface = app_interface()
 chat_interface.launch(share=True)