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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; | |
footer{display:none !important} | |
""" | |
with gr.Blocks(css=css) as demo: | |
chatbot = gr.ChatInterface(chat_response) | |
demo.launch(share=True) |