sorta works.

new file:   .gitignore
	new file:   app.py
	new file:   requirements.txt
	new file:   templates/chat.html
	new file:   templates/index.html

app.py

@@ -0,0 +1,56 @@
+from flask import Flask, render_template, request
+from flask_socketio import SocketIO, emit, join_room
+
+import eventlet
+
+import openai
+
+import markdown
+
+app = Flask(__name__)
+app.config['SECRET_KEY'] = 'your_secret_key'
+socketio = SocketIO(app, async_mode='eventlet')
+
+@app.route('/')
+def index():
+    return render_template('index.html')
+
+@app.route('/chat/<room>')
+def chat(room):
+    return render_template('chat.html', room=room)
+
+@socketio.on('join')
+def on_join(data):
+    room = data['room']
+    join_room(room)
+    emit('message', f"{data['username']} has joined the room.", room=room)
+
+@socketio.on('message')
+def handle_message(data):
+    emit('message', f"{data['username']}: {data['message']}", room=data['room'])
+
+    openai.api_key = "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"
+
+    # Call the chat_gpt function without blocking using eventlet.spawn
+    eventlet.spawn(chat_gpt, data['username'], data['room'], data['message'])
+
+
+def chat_gpt(username, room, message):
+    # Send user's message to ChatGPT API
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages=[{"role": "user", "content": message}]
+    )
+
+    # Extract response from ChatGPT API
+    response_text = response['choices'][0]['message']['content']
+
+    # Convert response_text to Markdown
+    response_md = markdown.markdown(response_text, extensions=['fenced_code'])
+
+    # Emit the response to the room
+    socketio.emit('message', f"{username} (GPT-3.5): {response_md}", room=room)
+
+if __name__ == '__main__':
+    socketio.run(app, host='0.0.0.0', port=5000)
+