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e36130a 0221616 e36130a 0221616 e36130a 0221616 61849d0 0221616 61849d0 0221616 c554bff 0221616 e36130a 0221616 e36130a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 | import gradio as gr
from huggingface_hub import InferenceClient
import requests
"""
For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
"""
TRAY_API_URL = "https://1591a0e5-d083-483b-a8b8-21fc282cdb21-api.trayapp.io/getResponse"
def respond_chatgpt(message, history, system_message, max_tokens, temperature, top_p):
messages = [{"role": "system", "content": system_message}]
# Prepare the conversation history for the model
for user, assistant in history:
if user:
messages.append({"role": "user", "content": user})
if assistant:
messages.append({"role": "assistant", "content": assistant})
messages.append({"role": "user", "content": message})
# Call the Hugging Face model
response = ""
# Tray.io API call
try:
tray_response = requests.get(TRAY_API_URL, params={"query": message})
# Process Tray.io API response
if tray_response.status_code == 200:
tray_data = tray_response.json()
tray_message = tray_data.get("message", "The agent did not return a response.")
response += f"\n\nTAnswer: {tray_message}"
else:
response += "\n\nError: Failed to retrieve response from Tray.io."
except requests.RequestException as e:
response += f"\n\nError calling Tray.io API: {e}"
yield response
"""
For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
"""
demo = gr.ChatInterface(
respond_chatgpt,
additional_inputs=[
gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
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)",
),
],
)
if __name__ == "__main__":
demo.launch()
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