Spaces:
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Build error
Zenith Wang
commited on
Commit
·
96f986b
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Parent(s):
1003bfe
完全重写应用:使用更稳定的Gradio 3.50.2版本和简化的代码结构
Browse files- app.py +219 -157
- requirements.txt +3 -3
app.py
CHANGED
@@ -1,178 +1,240 @@
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import os
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import io
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import base64
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from typing import List, Tuple, Optional
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import gradio as gr
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from PIL import Image
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from openai import OpenAI
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BASE_URL = "https://api.stepfun.com/v1"
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DEFAULT_MODEL = "step-3" #
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DEFAULT_DETAIL = "high" # high | low | auto
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def _get_api_key() -> Optional[str]:
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# 优先读环境变量(在 HF Spaces 的 Settings -> Variables and secrets 中配置)
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return os.environ.get("STEPFUN_API_KEY")
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def
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buffer = io.BytesIO()
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return f"data:image/jpeg;base64,{
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messages.append({
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"role": "
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"content":
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})
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})
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})
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# 保底,避免空消息
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content.append({"type": "text", "text": ""})
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messages.append({"role": "user", "content": content})
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return messages
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def stream_response(
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user_text: str,
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image: Optional[Image.Image],
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model: str,
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detail: str,
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system_prompt: str,
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chat_history: List[Tuple[str, str]],
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):
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api_key = _get_api_key()
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if not api_key:
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error_text = "未检测到 STEPFUN_API_KEY,请在 Space 的 Settings -> Variables and secrets 中配置后重试。"
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# 将错误作为助手消息显示
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display_user = (user_text or "") + ("\n[已附带图片]" if image is not None else "")
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new_history = chat_history + [(display_user, error_text)]
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yield new_history, ""
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return
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client = OpenAI(api_key=api_key, base_url=BASE_URL)
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# 将用户消息先追加到对话框
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display_user = (user_text or "") + ("\n[已附带图片]" if image is not None else "")
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chat_history = chat_history + [(display_user, "")] # 预先占位一条助手回复
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yield chat_history, ""
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try:
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messages = build_messages(chat_history[:-1], user_text=user_text, image=image, system_prompt=system_prompt, detail=detail)
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stream = client.chat.completions.create(
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model=model or DEFAULT_MODEL,
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messages=messages,
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stream=True
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)
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yield chat_history, ""
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except Exception as e:
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yield
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)
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)
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label="系统提示(可选)",
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placeholder="例如:你是一个美食专家,回答要简洁。",
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lines=2,
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)
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chatbot = gr.Chatbot(height=420, show_label=False, type="tuples")
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with gr.Row():
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image = gr.Image(label="上传图片(可选)", type="pil")
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user_text = gr.Textbox(label="你的问题", placeholder="描述你的问题……", lines=4)
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with gr.Row():
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submit = gr.Button("发送", variant="primary")
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clear = gr.Button("清空对话")
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# 清空
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def _clear_chat():
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return [], None, ""
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clear.click(_clear_chat, outputs=[chatbot, image, user_text])
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# 发送并流式生成
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submit.click(
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fn=stream_response,
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inputs=[user_text, image, model, detail, system_prompt, chatbot],
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outputs=[chatbot, user_text],
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)
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if __name__ == "__main__":
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import os
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import io
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import base64
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import gradio as gr
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from PIL import Image
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from openai import OpenAI
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# 配置
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BASE_URL = "https://api.stepfun.com/v1"
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DEFAULT_MODEL = "step-3" # 可选: step-3, step-r1-v-mini
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def get_api_key():
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"""获取API密钥"""
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api_key = os.environ.get("STEPFUN_API_KEY")
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if not api_key:
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raise ValueError("请设置环境变量 STEPFUN_API_KEY")
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return api_key
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def image_to_base64(image):
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"""将PIL图像转换为base64编码"""
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if image is None:
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return None
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# 转换为RGB格式
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if image.mode != 'RGB':
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image = image.convert('RGB')
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# 保存到字节流
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buffer = io.BytesIO()
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image.save(buffer, format='JPEG', quality=85)
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# 编码为base64
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img_str = base64.b64encode(buffer.getvalue()).decode('utf-8')
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return f"data:image/jpeg;base64,{img_str}"
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def chat_with_stepfun(message, image, history, model, system_prompt):
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"""
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处理聊天请求
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Args:
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message: 用户输入的文本
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image: 用户上传的图片 (PIL Image)
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history: 聊天历史
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model: 选择的模型
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system_prompt: 系统提示词
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Returns:
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更新后的聊天历史
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"""
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try:
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# 获取API密钥
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api_key = get_api_key()
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client = OpenAI(api_key=api_key, base_url=BASE_URL)
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# 构建消息列表
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messages = []
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# 添加系统提示
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if system_prompt and system_prompt.strip():
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messages.append({
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"role": "system",
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"content": system_prompt
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})
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# 添加历史对话
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for user_msg, assistant_msg in history:
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if user_msg:
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messages.append({
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"role": "user",
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"content": user_msg
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})
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if assistant_msg:
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messages.append({
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"role": "assistant",
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"content": assistant_msg
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})
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# 构建当前用户消息
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current_content = []
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# 添加图片
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if image is not None:
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img_base64 = image_to_base64(image)
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current_content.append({
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"type": "image_url",
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"image_url": {
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"url": img_base64,
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"detail": "high"
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}
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})
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# 添加文本
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if message and message.strip():
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current_content.append({
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"type": "text",
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"text": message
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})
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# 如果没有任何内容,返回
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if not current_content:
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return history
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# 添加当前消息
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messages.append({
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"role": "user",
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"content": current_content
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})
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# 调用API
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response = client.chat.completions.create(
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model=model,
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messages=messages,
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stream=True
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)
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# 处理流式响应
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full_response = ""
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for chunk in response:
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if chunk.choices[0].delta.content:
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full_response += chunk.choices[0].delta.content
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# 实时更新界面
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yield history + [(message, full_response)]
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# 返回最终结果
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yield history + [(message, full_response)]
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except Exception as e:
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error_msg = f"错误: {str(e)}"
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yield history + [(message, error_msg)]
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def clear_chat():
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"""清空聊天记录"""
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return None, None, []
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# 创建Gradio界面
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def create_interface():
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with gr.Blocks(title="StepFun 多模态对话") as demo:
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gr.Markdown("""
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# 🚀 StepFun Step-3 多模态对话
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支持图片理解和文本对话,使用StepFun API。
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**使用说明:**
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1. 在环境变量中设置 `STEPFUN_API_KEY`
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2. 可选择上传图片进行视觉理解
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3. 输入文本进行对话
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""")
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with gr.Row():
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with gr.Column(scale=3):
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# 聊天界面
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chatbot = gr.Chatbot(
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height=500,
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bubble_full_width=False,
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avatar_images=(None, None)
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)
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with gr.Row():
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with gr.Column(scale=3):
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msg = gr.Textbox(
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label="输入消息",
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placeholder="输入你的问题...",
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lines=2
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)
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with gr.Column(scale=1):
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img = gr.Image(
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label="上传图片(可选)",
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type="pil"
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)
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with gr.Row():
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submit = gr.Button("发送", variant="primary")
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clear = gr.Button("清空对话")
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with gr.Column(scale=1):
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# 设置面板
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model = gr.Dropdown(
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label="选择模型",
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choices=["step-3", "step-r1-v-mini"],
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value="step-3"
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)
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system_prompt = gr.Textbox(
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label="系统提示(可选)",
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placeholder="设置AI的角色或行为...",
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lines=3
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)
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gr.Markdown("""
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### 说明
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- **step-3**: 标准多模态模型
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- **step-r1-v-mini**: 轻量级版本
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### 提示
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- 支持中英文对话
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- 图片支持JPG/PNG格式
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- 可以询问图片内容
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""")
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# 事件绑定
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submit.click(
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fn=chat_with_stepfun,
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inputs=[msg, img, chatbot, model, system_prompt],
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outputs=[chatbot],
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queue=True
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).then(
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lambda: (None, None),
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outputs=[msg, img]
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)
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msg.submit(
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fn=chat_with_stepfun,
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inputs=[msg, img, chatbot, model, system_prompt],
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outputs=[chatbot],
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queue=True
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).then(
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lambda: (None, None),
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outputs=[msg, img]
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)
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clear.click(
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fn=clear_chat,
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outputs=[msg, img, chatbot]
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)
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return demo
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# 主程序
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|
|
|
|
|
|
|
|
|
|
|
229 |
if __name__ == "__main__":
|
230 |
+
demo = create_interface()
|
231 |
+
|
232 |
+
# 获取端口
|
233 |
+
port = int(os.environ.get("PORT", 7860))
|
234 |
+
|
235 |
+
# 启动应用
|
236 |
+
demo.launch(
|
237 |
+
server_name="0.0.0.0",
|
238 |
+
server_port=port,
|
239 |
+
share=False
|
240 |
+
)
|
requirements.txt
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
-
|
2 |
-
|
3 |
-
|
|
|
1 |
+
gradio==3.50.2
|
2 |
+
openai>=1.0.0
|
3 |
+
Pillow>=9.0.0
|