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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 !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) as demo: | |
chatbot = gr.ChatInterface(chat_response) | |
demo.launch(share=True) |