Add model selection

app.py

@@ -9,7 +9,15 @@ API_URL = "https://api.openai.com/v1/chat/completions" #os.getenv("API_URL") + "
 #Testing with my Open AI Key 
 OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") 
 
-def predict(inputs, top_p, temperature, openai_api_key, chat_counter, chatbot=[], history=[]):  #repetition_penalty, top_k
+MODELS = [
+    'gpt-4o',
+    'gpt-4o-mini',
+    'gpt-4-turbo',
+    'gpt-4',
+    'gpt-3.5-turbo',
+]
+
+def predict(model_name, inputs, top_p, temperature, openai_api_key, chat_counter, chatbot=[], history=[]):  #repetition_penalty, top_k
 
     payload = {
     "model": "gpt-3.5-turbo",
@@ -45,7 +53,7 @@ def predict(inputs, top_p, temperature, openai_api_key, chat_counter, chatbot=[]
         messages.append(temp3)
         #messages
         payload = {
-        "model": "gpt-3.5-turbo",
+        "model": model_name,
         "messages": messages, #[{"role": "user", "content": f"{inputs}"}],
         "temperature" : temperature, #1.0,
         "top_p": top_p, #1.0,
@@ -92,7 +100,7 @@ def predict(inputs, top_p, temperature, openai_api_key, chat_counter, chatbot=[]
 def reset_textbox():
     return gr.update(value='')
 
-title = """<h1 align="center">Lisa Chatbot</h1>"""
+title = """<h1 align="center">GPT-4 via API</h1>"""
 description = """Language models can be conditioned to act like dialogue agents through a conversational prompt that typically takes the form:
 ```
 User: <utterance>
@@ -109,6 +117,7 @@ with gr.Blocks(css = """#col_container {width: 1000px; margin-left: auto; margin
     gr.HTML(title)
     with gr.Column(elem_id = "col_container"):
         openai_api_key = gr.Textbox(type='password', label="Enter your OpenAI API key here", value=OPENAI_API_KEY)
+        model_name = gr.Dropdown(choices=MODELS, value=MODELS[0], allow_custom_value=True)
         chatbot = gr.Chatbot(elem_id='chatbot') #c
         inputs = gr.Textbox(placeholder= "Type here!", label= "Type an input and press Enter") #t
         state = gr.State([]) #s
@@ -122,8 +131,8 @@ with gr.Blocks(css = """#col_container {width: 1000px; margin-left: auto; margin
             #repetition_penalty = gr.Slider( minimum=0.1, maximum=3.0, value=1.03, step=0.01, interactive=True, label="Repetition Penalty", )
             chat_counter = gr.Number(value=0, visible=False, precision=0)
     
-    inputs.submit( predict, [inputs, top_p, temperature, openai_api_key, chat_counter, chatbot, state], [chatbot, state, chat_counter],)
-    b1.click( predict, [inputs, top_p, temperature, openai_api_key, chat_counter, chatbot, state], [chatbot, state, chat_counter],)
+    inputs.submit( predict, [model_name, inputs, top_p, temperature, openai_api_key, chat_counter, chatbot, state], [chatbot, state, chat_counter],)
+    b1.click( predict, [model_name, inputs, top_p, temperature, openai_api_key, chat_counter, chatbot, state], [chatbot, state, chat_counter],)
     b1.click(reset_textbox, [], [inputs])
     inputs.submit(reset_textbox, [], [inputs])