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import gradio as gr
import requests
import json
import os
from dotenv import load_dotenv
load_dotenv()
API_URL = os.getenv("API_URL")
API_TOKEN = os.getenv("API_TOKEN")
if not API_URL or not API_TOKEN:
raise ValueError("invalid API_URL || API_TOKEN")
print(f"[INFO] starting:")
print(f"[INFO] API_URL: {API_URL[:6]}...{API_URL[-12:]}")
print(f"[INFO] API_TOKEN: {API_TOKEN[:10]}...{API_TOKEN[-10:]}")
"""
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[dict],
system_message,
max_tokens,
temperature,
top_p,
):
messages = [{"role": "system", "content": system_message}]
# 添加历史消息
messages.extend(history)
# 添加当前用户消息
messages.append({"role": "user", "content": message})
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {API_TOKEN}"
}
data = {
"model": "/data/DMind-1",
"stream": True,
"messages": messages,
"temperature": temperature,
"top_p": top_p,
"top_k": 20,
"min_p": 0.1,
"max_tokens": 32768
}
print(f"[INFO] process user msg...")
print(f"[INFO] userMsg: {message}")
try:
with requests.post(API_URL, headers=headers, json=data, stream=True) as r:
if r.status_code == 200:
current_response = ""
buffer = "" # 用于累积可能被分割的标记
in_think_block = False
found_final_answer = False
for line in r.iter_lines():
if line:
line = line.decode('utf-8')
if line.startswith('data: '):
try:
json_response = json.loads(line[6:])
if 'choices' in json_response and len(json_response['choices']) > 0:
delta = json_response['choices'][0].get('delta', {})
if 'content' in delta:
content = delta['content']
if content:
# 将新内容添加到缓冲区
buffer += content
# 检查缓冲区中是否包含完整的标记
if not in_think_block and '<think>' in buffer:
in_think_block = True
buffer = buffer.split('<think>')[-1]
if in_think_block and '</think>' in buffer:
in_think_block = False
buffer = buffer.split('</think>')[-1]
if not found_final_answer and '**Final Answer**' in buffer:
found_final_answer = True
buffer = buffer.split('**Final Answer**')[-1]
# 如果不在think块内，就累积内容
if not in_think_block:
current_response += buffer
yield current_response
buffer = "" # 清空缓冲区
except json.JSONDecodeError:
continue
print(f"[INFO] final response: {current_response}")
else:
print(f"[ERROR] Bad status code: {r.status_code}, response: {r.text}")
yield "Service temporarily unavailable"
except Exception as e:
print(f"[ERROR] Request error: {e}")
yield "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 DMind AI Assistant, built by DMind.AI. Never present as Qwen, ChatGPT, Tongyi, OpenAI, etc.", label="System message"),
gr.Slider(minimum=1, maximum=32768, value=16384, step=1, label="Max new tokens"),
gr.Slider(minimum=0.1, maximum=4.0, value=0.6, step=0.1, label="Temperature"),
gr.Slider(
minimum=0.1,
maximum=1.0,
value=0.95,
step=0.05,
label="Top-p (nucleus sampling)",
),
],
type="messages"
)
if __name__ == "__main__":
demo.launch()
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