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import gradio as gr
import os
import requests
CHAT_URL = os.getenv("CHAT_URL")
PROJECT_ID = os.getenv("PROJECT_ID")
def respond(
message,
history: list[dict[str, str]],
system_message,
token,
# max_tokens,
# temperature,
# top_p,
# hf_token: gr.OAuthToken,
):
req = requests.post(
CHAT_URL,
json={
"project_id": PROJECT_ID,
"session_id":system_message,
"user_input":message,
# "output_variables": ["results", "category_list"]
},
headers={"Authorization" : f"Bearer {token}"}
)
print("[REQ CONTENT]", req.content)
out = req.json()["data"]["results"]
print("[OUT]",out)
return out.encode('utf-8').decode('unicode_escape')
"""
For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
"""
chatbot = gr.ChatInterface(
respond,
type="messages",
additional_inputs=[
gr.Textbox(value="<<TEST_123>>", label="session_id"),
gr.Textbox(value="[TOKEN]", label="token"),
# gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
# gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
# gr.Slider(
# minimum=0.1,
# maximum=1.0,
# value=0.95,
# step=0.05,
# label="Top-p (nucleus sampling)",
# ),
],
)
with gr.Blocks() as demo:
chatbot.render()
title = gr.HTML("<h3>Use #ai to ask the ai</h3>")
if __name__ == "__main__":
demo.launch()
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