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()