Initial.

app.py

@@ -0,0 +1,50 @@
+import os
+import openai
+import gradio as gr
+
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+start_sequence = "\nCoach:"
+restart_sequence = "\nMe:"
+
+prompt = "The following is a conversation with an instructor. The instructor is an expert in opportunity cost. You will act as the instructor, I will be the student."
+
+def completion_create(prompt):
+    
+    response = openai.Completion.create(
+        model = "text-davinci-003",
+        prompt=prompt,
+        temperature=0.9,
+        max_tokens=150,
+        top_p=1,
+        frequency_penalty=0,
+        presence_penalty=0.6,
+        stop=[" Coach:", " Me:"])
+    print("Raw response: ")
+    print(response)
+    return response.choices[0].text
+
+def chat_clone(input, history):
+    history = history or []
+    s = list(sum(history, ()))
+    print(s)
+    s.append(input)
+    inp = ' '.join(s)
+    output = completion_create(inp)
+    if (len(output) < 5): print("ERROR, short output")
+    print(output)
+    history.append((input, output))
+    return history, history
+
+block = gr.Blocks(css="main.css", title="Coaching Demo")
+
+with block:
+    gr.Markdown("""<h1><center>Coaching Demo</center></h1>""")
+    chatbot = gr.Chatbot()
+    input = gr.Textbox(placeholder=None,value="")
+    state = gr.State()
+    input.submit(chat_clone, inputs=[input, state], outputs=[chatbot, state])
+    submit = gr.Button("Ask")
+    submit.click(chat_clone, inputs=[input, state], outputs=[chatbot, state])
+    
+block.launch(share=False,debug=True)

requirements.txt

@@ -0,0 +1,2 @@
+gradio
+openai