Update app.py

app.py

@@ -1,33 +1,29 @@
 import os
 import io
 import base64
-from typing import Optional
+from typing import List, Dict, Any
 
-import httpx
 import gradio as gr
 from PIL import Image
+import httpx
 from fastapi import FastAPI
 
-# --------- 基本配置 ---------
+# ================== 配置 ==================
 STEPFUN_ENDPOINT = os.getenv("STEPFUN_ENDPOINT", "https://api.stepfun.com/v1")
 MODEL_NAME = os.getenv("MODEL_NAME", "step-3")
-TITLE = "StepFun · step-3 图片问答 Demo"
-DESC = "上传一张图片，问一个问题；后台通过 StepFun OpenAI 兼容接口完成图文对话。"
-FOOTER = "提示：在 HF Spaces 的 Settings -> Variables 里设置 OPENAI_API_KEY 或 STEPFUN_KEY"
-# ---------------------------
+# =========================================
 
 
-def _get_api_key() -> Optional[str]:
+def _get_api_key() -> str | None:
     """
-    从环境变量里取 API Key。
-    优先 OPENAI_API_KEY（OpenAI 兼容接口的常用名），否则退回 STEPFUN_KEY。
+    优先读 OPENAI_API_KEY（兼容 OpenAI SDK 约定），其次读 STEPFUN_KEY
     """
     return os.getenv("OPENAI_API_KEY") or os.getenv("STEPFUN_KEY")
 
 
 def _pil_to_data_url(img: Image.Image, fmt: str = "PNG") -> str:
     """
-    PIL.Image -> data:image/...;base64,... （OpenAI兼容的 image_url 需要）
+    PIL.Image -> data:image/...;base64,xxxxx
     """
     buf = io.BytesIO()
     img.save(buf, format=fmt)
@@ -36,19 +32,19 @@ def _pil_to_data_url(img: Image.Image, fmt: str = "PNG") -> str:
     return f"data:{mime};base64,{b64}"
 
 
-def _post_chat(messages: list, temperature: float = 0.7) -> str:
+def _post_chat(messages: List[Dict[str, Any]], temperature: float = 0.7) -> str:
     """
-    直接用 httpx 调用 StepFun 的 /chat/completions 接口，返回文本。
+    直连 StepFun 的 OpenAI 兼容接口：/chat/completions
     """
     key = _get_api_key()
     if not key:
-        raise RuntimeError(
+        return (
             "API Key 未设置。\n"
-            "请在本地环境变量或 HF Spaces -> Settings -> Variables 里设置：\n"
-            "OPENAI_API_KEY 或 STEPFUN_KEY（值为 StepFun API Key）。"
+            "请在 Space 的 Settings → Variables and secrets 中添加：\n"
+            "OPENAI_API_KEY=<你的 StepFun API Key>（或设置 STEPFUN_KEY 也可）"
         )
 
-    url = f"{STEPFUN_ENDPOINT.rstrip('/')}/chat/completions"
+    url = f"{STEPFUN_ENDPOINT}/chat/completions"
     headers = {
         "Authorization": f"Bearer {key}",
         "Content-Type": "application/json",
@@ -59,25 +55,27 @@ def _post_chat(messages: list, temperature: float = 0.7) -> str:
         "temperature": temperature,
     }
 
-    # 简单超时与错误抛出
-    resp = httpx.post(url, headers=headers, json=payload, timeout=60)
-    resp.raise_for_status()
-    data = resp.json()
-    return data["choices"][0]["message"]["content"]
+    try:
+        resp = httpx.post(url, headers=headers, json=payload, timeout=60)
+        resp.raise_for_status()
+        data = resp.json()
+        return data["choices"][0]["message"]["content"]
+    except httpx.HTTPError as e:
+        return f"调用失败（HTTP）：{e}"
+    except Exception as e:
+        return f"调用失败：{e}"
 
 
-def chat_with_step3(image: Optional[Image.Image], question: Optional[str]) -> str:
+def chat_fn(image: Image.Image, question: str) -> str:
     """
-    Gradio 回调函数：输入图片和问题，返回模型回答。
+    Gradio 回调：上传图片 + 文本问题 → 模型答案
     """
     if image is None:
         return "请先上传图片。"
 
-    q = (question or "").strip()
-    if not q:
-        q = "请描述这张图片的内容，并指出可能的菜品名称与做法要点。"
-
+    q = question.strip() or "请描述这张图片。"
     data_url = _pil_to_data_url(image, fmt="PNG")
+
     messages = [
         {
             "role": "user",
@@ -87,49 +85,28 @@ def chat_with_step3(image: Optional[Image.Image], question: Optional[str]) -> st
             ],
         }
     ]
-
-    try:
-        return _post_chat(messages)
-    except httpx.HTTPStatusError as e:
-        # 返回后端具体错误信息，便于排障
-        try:
-            detail = e.response.json()
-        except Exception:
-            detail = e.response.text
-        return f"后端返回错误：HTTP {e.response.status_code}\n{detail}"
-    except Exception as e:
-        return f"调用失败：{repr(e)}"
+    return _post_chat(messages)
 
 
-# --------- 构建 Gradio 界面 ---------
-with gr.Blocks(title=TITLE, analytics_enabled=False) as demo:
-    gr.Markdown(f"## {TITLE}")
-    gr.Markdown(DESC)
-
+with gr.Blocks(title="Step-3 · 图片问答") as demo:
+    gr.Markdown("## Step-3 图片问答\n上传一张图，随便问。")
     with gr.Row():
+        img = gr.Image(type="pil", label="上传图片")
         with gr.Column():
-            img_in = gr.Image(type="pil", label="上传图片")
-            txt_in = gr.Textbox(
-                label="问题（可留空）",
-                placeholder="例如：这���什么菜？做法是怎样的？",
-            )
+            q = gr.Textbox(label="问题", placeholder="比如：这是什么菜？怎么做？")
             btn = gr.Button("提交")
-        with gr.Column():
-            out = gr.Textbox(label="回答", lines=12)
-
-    btn.click(fn=chat_with_step3, inputs=[img_in, txt_in], outputs=out)
-
-    gr.Markdown(f"<small>{FOOTER}</small>")
-
-# 让 HF Spaces 识别到 FastAPI/ASGI 应用
-app = FastAPI()
-# 不使用自定义路径参数，直接挂载到根路径
-app = gr.mount_gradio_app(app, demo, path="/")
+    out = gr.Textbox(label="答案", lines=8)
 
+    btn.click(fn=chat_fn, inputs=[img, q], outputs=[out])
+    # 也支持回车触发
+    q.submit(fn=chat_fn, inputs=[img, q], outputs=[out])
 
-# --------- 本地调试专用（Spaces 环境不会执行）---------
-if __name__ == "__main__" and os.environ.get("SPACE_BUILD") is None:
-    import uvicorn
+# ---- FastAPI + 挂载 Gradio（给 HF Spaces 用）----
+_fastapi = FastAPI()
+app = gr.mount_gradio_app(_fastapi, demo, path="/")
 
-    port = int(os.getenv("PORT", "7860"))
-    uvicorn.run(app, host="0.0.0.0", port=port)
+# ---- 本地调试：只有在非 HF Spaces 才会启动 ----
+if __name__ == "__main__" and os.environ.get("SYSTEM") != "spaces":
+    # 本地跑：python app.py
+    # 不要在 HF Spaces 起 uvicorn，否则会端口冲突
+    demo.queue(max_size=32).launch(server_name="0.0.0.0", server_port=int(os.getenv("PORT", "7860")))