Added use of PersonaConverter

app.py

@@ -2,12 +2,12 @@ import gradio as gr
 from neon_llm_chatgpt.chatgpt import ChatGPT
 from neon_llm_palm2.palm2 import Palm2
 from neon_llm_claude.claude import Claude
-from utils import convert_history
+from utils import convert_history, PersonaConverter
 import os
 
 
 
-role = "You are trying to give a short answer in less than 40 words."
+role = ""
 
 
 key = os.environ['OPENAI_API_KEY']
@@ -52,10 +52,16 @@ model_choices = {
 }
 model_choices_list = list(model_choices.keys())
 
-def ask(message, history, persona, model_name):
+
+personaConverter = PersonaConverter()
+preset_choices_list = list(personaConverter.personas.keys())
+
+def ask(message, history, persona, model_name, preset, imaginary, short):
     chat_history = convert_history(history)
     model = model_choices[model_name]
-    responce = model.ask(message, chat_history, persona = {"description": persona})
+    persona_description = personaConverter(name = preset, description = persona,
+                                imaginary = imaginary, short = short)
+    responce = model.ask(message, chat_history, persona = {"description": persona_description})
 
     return responce
 
@@ -63,7 +69,10 @@ def ask(message, history, persona, model_name):
 demo = gr.ChatInterface(ask, 
     additional_inputs=[
         gr.Textbox(role, label="Persona"), 
-        gr.Dropdown(choices=model_choices_list, value=model_choices_list[0], label="Model")
+        gr.Dropdown(choices=model_choices_list, value=model_choices_list[0], label="Model"),
+        gr.Dropdown(choices=preset_choices_list, value=preset_choices_list[0], label="Preset"),
+        gr.Checkbox(value=False, label="Imaginary"),
+        gr.Checkbox(value=True, label="Short response"),
     ]
 )