import gradio as gr
from langchain.agents.openai_assistant import OpenAIAssistantRunnable
from openai import OpenAI
import os
#sk
apikey = os.getenv('openAI')  #key from client
agentkey = os.getenv('asstID')
os.environ["OPENAI_API_KEY"] = apikey

interpreter_assistant = OpenAIAssistantRunnable(assistant_id= agentkey) #, client = key
# output = interpreter_assistant.invoke({"content": "Hello?"})
# output[0].content[0].text.value

def chat_response(message, history):
  output = interpreter_assistant.invoke({"content": message})
  response = output[0].content[0].text.value
  return response
css = """
label[data-testid="block-label"] {
    display: none !important;
}
footer {
    display: none !important;
}
"""

js_func = """
function refresh() {
    const url = new URL(window.location);

    if (url.searchParams.get('__theme') !== 'dark') {
        url.searchParams.set('__theme', 'dark');
        window.location.href = url.href;
    }
}
"""
with gr.Blocks(css=css, js = js_func, theme="monochrome") as demo:
  chatbot = gr.ChatInterface(chat_response)

demo.launch(share=True)