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import gradio as gr
import os
from openai import OpenAI
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
openai_client = OpenAI(api_key=OPENAI_API_KEY)
DEEPSEEK_API_KEY = os.getenv("DEEPSEEK_API_KEY")
deepseek_client = OpenAI(api_key=DEEPSEEK_API_KEY, base_url="https://api.deepseek.com")
def generate_response(model_provider, prompt, temperature, top_p, max_tokens, repetition_penalty):
try:
# 根据选择使用不同的客户端和模型
if model_provider == "OpenAI":
client = openai_client
model_name = "gpt-3.5-turbo"
elif model_provider == "DeepSeek":
client = deepseek_client
model_name = "deepseek-chat" # 替换成你想用的 DeepSeek 模型名称
else:
return "❌ 无效的模型提供者选择"
response = client.chat.completions.create(
model=model_name,
messages=[{"role": "user", "content": prompt}],
temperature=temperature,
top_p=top_p,
max_tokens=int(max_tokens),
presence_penalty=repetition_penalty,
stream=False
)
return response.choices[0].message.content.strip()
except Exception as e:
return f"❌ API 调用出错：{str(e)}"
iface = gr.Interface(
fn=generate_response,
inputs=[
gr.Dropdown(choices=["DeepSeek", "OpenAI"], value="DeepSeek", label="Model Provider"),
gr.Textbox(label="Prompt", lines=6, placeholder="Ask something..."),
gr.Slider(minimum=0.1, maximum=1.5, value=0.7, step=0.1, label="Temperature"),
gr.Slider(minimum=0.1, maximum=1.0, value=0.9, step=0.05, label="Top-p"),
gr.Slider(minimum=32, maximum=2048, value=512, step=32, label="Max New Tokens"),
gr.Slider(minimum=1.0, maximum=2.0, value=1.1, step=0.1, label="Repetition Penalty")
],
outputs="text",
title="🧠 DeepSeek & OpenAI Chat with Parameter Tuning",
theme=gr.themes.Soft()
)
iface.launch()
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