app.py

import gradio as gr
from random import randint
import os
from openai import OpenAI
import datetime

time = str(datetime.datetime.now())
print(time)

tok = os.getenv('deepseekapi')
client = OpenAI(api_key=tok, base_url="https://api.deepseek.com")
num = randint(0,1)
tok2 = os.getenv('HF_TOKEN')
huggingface_hub.login(tok2)

with gr.Blocks() as demo:
 chatbot = gr.Chatbot()
 msg = gr.Textbox()
 clear = gr.ClearButton([msg, chatbot])
 
 def telemetry(message, response):
 api = HfApi()
 api.upload_file(
 path_or_fileobj=("\nMessage:" + message + "\nResponse:" + response).encode('ascii') ,
 path_in_repo=("/"+time+"/Episode-"str(msgcounter)+".txt"),
 repo_id="BirdL/ChickenChatTelemetry",
 )
 
 def response(message, chat_history) 
 if num == 0:
 response = client.chat.completions.create(
 model="deepseek-chat",
 messages=[
 {"role": "system", "content": "You are a chicken and respond to answers only by clucking."},
 {"role": "user", "content": message},
 ],
 max_tokens=144,
 temperature=0.7,
 stream=False)
 else:
 response = client.chat.completions.create(
 model="deepseek-chat",
 messages=[
 {"role": "system", "content": "You are a chicken and respond to answers mostly by clucking."},
 {"role": "user", "content": message},
 ],
 max_tokens=144,
 temperature=0.7,
 stream=False) 
 telemetry(message, response)
 return response

 def telemetrybad(message):
 api = HfApi()
 api.upload_file(
 path_or_fileobj=("Bad").encode('ascii')
 path_in_repo=("/"+time+"/Rating-"str(msgcounter)+".txt"),
 repo_id="BirdL/ChickenChatTelemetry",
 )
 
 def telemetrygood(message):
 api = HfApi()
 api.upload_file(
 path_or_fileobj=("Good").encode('ascii')
 path_in_repo=("/"+time+"/Rating-"str(msgcounter)+".txt"),
 repo_id="BirdL/ChickenChatTelemetry",
 )
 

 msg.submit(response)
 goodchicken = gr.Button("Good Chicken!")
 goodchicken.click(fn=telemetrygood(message))
 badchicken = gr.Button("Bad Chicken!")
 badchicken.click(fn=telemetrybad(message))


if __name__ == "__main__":
 demo.launch()