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api.py

@@ -1,17 +1,49 @@
-import time
+from openai import OpenAI
+import os
+
+client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])
 
 def generate_scenario(gender):
-    time.sleep(1)
-    return f"I see a {gender} in a coffee shop."
+    PROMPT = f"""Create a scenario where you're see a {gender} you're interested in. You haven't yet approached them yet but are interested. Keep it brief, around 20 words. For example: 'There's a cute {gender} in my boxing class. I approach her after a class.' or 'I see two {gender}s having coffee at the table next to mine.'."""
+    return llm(PROMPT)
+
+def suggest_next_line(scenario, history):
+    PROMPT = f"""This is my scenario: {scenario} \n\n"""
+    if len(history) == 0:
+        PROMPT += "Suggest a line with which I can introduce myself or strike up a conversation."
+    else:
+        PROMPT += f"""This is the conversation so far: \n\n{format_history(history)} \n\nSuggest my next response. Provide the response and nothing else."""
+    return llm(PROMPT)
+
+def generate_response(scenario, history, personality, interested):
+    PROMPT = f"""This is my scenario: {scenario}. Roleplay the conversation with me. Provide the response and nothing else. You're personality is {personality}. You are {'interested' if interested else 'not interested'} in me. 
+    
+    The conversation so far: \n\n{format_history(history)}
+                                  
+    Only provide the response and nothing else.
+    """
+    return llm(PROMPT)
 
-def suggest_next_line(history):
-    time.sleep(1)
-    return "So.. what do you do for fun?"
+def transcribe_audio(audio_path):
+    with open(audio_path, "rb") as audio_file:
+        transcript = client.audio.transcriptions.create(
+            model="whisper-1", 
+            file=audio_file
+        )
+    return transcript.text
 
-def generate_response(history):
-    time.sleep(1)
-    return "Nice to meet you"
+def llm(prompt):
+    response = client.completions.create(
+        model="gpt-3.5-turbo-instruct",
+        prompt=prompt,
+        temperature=0.9,
+        max_tokens=100,
+        top_p=1,
+        frequency_penalty=0.0,
+        presence_penalty=0.6,
+    )
+    return response.choices[0].text.strip()
+    
 
-def transcribe_audio(audio):
-    time.sleep(1)
-    return "I like your face"
+def format_history(history):
+    return "\n\n".join([f"Me: {line[0]} \nThem: {line[1] if line[1] else ''}" for line in history])

requirements.txt

@@ -0,0 +1 @@
+openai

run.py

@@ -1,5 +1,6 @@
 import api
 import gradio as gr
+import random
 
 with gr.Blocks() as demo:
     with gr.Column() as setup_col:
@@ -15,7 +16,7 @@ with gr.Blocks() as demo:
 
     with gr.Column(visible=False) as convo_col:
         chat = gr.Chatbot()
-        recording = gr.Audio(label="Your Line", sources="microphone")
+        recording = gr.Audio(label="Your Line", sources="microphone", type="filepath")
         with gr.Group():
             with gr.Row():
                 help_btn = gr.Button("Help Me", scale=0)
@@ -29,6 +30,8 @@ with gr.Blocks() as demo:
         } 
     
     scenario = gr.State()
+    personality = gr.State(lambda: random.choice(["shy", "confident", "awkward", "charming", "rude"]))
+    interested = gr.State(lambda: random.choice([True, False]))
     SCENARIO_LINE = "The scenario is: **{}** \n\n Record your opening line below!"
 
     def start_chat(scenario):
@@ -44,16 +47,16 @@ with gr.Blocks() as demo:
         chat.append([user_message, None])
         return chat
     
-    def respond(chat):
-        response = api.generate_response(chat[1:])
+    def respond(scenario, chat, personality, interested):
+        response = api.generate_response(scenario, chat[1:], personality, interested)
         chat[-1][1] = response
         return chat
 
 
     recording.stop_recording(transcribe, inputs=[recording, chat], outputs=[chat]
-    ).then(respond, inputs=[chat], outputs=[chat]
+    ).then(respond, inputs=[scenario, chat, personality, interested], outputs=[chat]
     ).then(lambda: None, outputs=[recording])
 
-    help_btn.click(lambda chat: api.suggest_next_line(chat[1:]), inputs=[chat], outputs=[suggestion])
+    help_btn.click(lambda scenario, chat: api.suggest_next_line(scenario, chat[1:]), inputs=[scenario, chat], outputs=[suggestion])
     
 demo.launch()