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import gradio as gr
import requests
import json
import os
from dotenv import load_dotenv
# 加载.env文件中的环境变量
load_dotenv()
# 从环境变量中读取配置
API_URL = os.getenv("API_URL")
API_TOKEN = os.getenv("API_TOKEN")
# 验证必要的环境变量
if not API_URL or not API_TOKEN:
raise ValueError("请确保设置了环境变量 API_URL 和 API_TOKEN")
print(f"[INFO] starting:")
print(f"[INFO] API_URL: {API_URL[:6]}...{API_URL[-13:]}")
print(f"[INFO] API_TOKEN: {API_TOKEN[:10]}...{API_TOKEN[-10:]}") # 只显示token的前10位和后10位
"""
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
"""
def respond(
message,
history: list[tuple[str, str]],
system_message,
max_tokens,
temperature,
top_p,
):
messages = [{"role": "system", "content": system_message}]
for val in history:
if val[0]:
messages.append({"role": "user", "content": val[0]})
if val[1]:
messages.append({"role": "assistant", "content": val[1]})
messages.append({"role": "user", "content": message})
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {API_TOKEN}"
}
data = {
"model": "/data/DMind-1-mini",
"stream": False, # 改为非流式模式
"messages": messages,
"temperature": temperature,
"top_p": top_p,
"top_k": 20,
"min_p": 0.1
}
print(f"[INFO] process user msg...")
print(f"[INFO] sysMsg: {system_message}")
print(f"[INFO] userMsg: {message}")
print(f"[INFO] modelParam: temperature={temperature}, top_p={top_p}")
print(f"[INFO] reqData: {data}")
try:
with requests.post(API_URL, headers=headers, json=data) as r:
if r.status_code == 200:
json_response = r.json()
if 'choices' in json_response and len(json_response['choices']) > 0:
response = json_response['choices'][0].get('message', {}).get('content', '')
if response:
print(f"[INFO] API response content: {response}")
return response
else:
print("[ERROR] No content found in API response")
return "No content in the response"
else:
print("[ERROR] No choices found in API response")
return "No choices in the response"
else:
print(f"[ERROR] Unexpected status code: {r.status_code}")
return "Unexpected status code from API"
except Exception as e:
print(f"[ERROR] Request error: {e}")
return "Service error occurred"
"""
For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
"""
demo = gr.ChatInterface(
respond,
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=0.96,
step=0.05,
label="Top-p (nucleus sampling)",
),
],
)
if __name__ == "__main__":
demo.launch()
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