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
@@ -46,16 +48,14 @@ def predict(message, history, selected_agent):
     return non_cited_output
 
 # Define the Gradio interface
-def app_interface():
-    dropdown = gr.Dropdown(choices=list(extractor_agents.keys()), value="Solution Specifier A", label="Choose Extractor Agent")
-    chat = gr.ChatInterface(
-        fn=lambda message, history, selected_agent: predict(message, history, selected_agent),
-        inputs=[dropdown],
-        title="Solution Specifier Chat",
-        description="Test with different solution specifiers"
-    )
-    return chat
+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"
+)
 
 # Launch the app
-chat_interface = app_interface()
 chat_interface.launch(share=True)