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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() |