Update app.py

app.py

@@ -1,47 +1,34 @@
-import os
+import gradio as gr
 import requests
-from flask import Flask, render_template, request, jsonify
 
-# 配置 Flask
-app = Flask(__name__)
-UPLOAD_FOLDER = "static/uploads"
-app.config["UPLOAD_FOLDER"] = UPLOAD_FOLDER
-
-# 你的推理服务器地址
-SERVER_URL = "http://127.0.0.1:5000/infer"  # 如果你的服务器在远程，改为公网 IP 或 ngrok 地址
-
-# 确保上传目录存在
-if not os.path.exists(UPLOAD_FOLDER):
-    os.makedirs(UPLOAD_FOLDER)
-
-@app.route("/", methods=["GET", "POST"])
-def index():
-    if request.method == "POST":
-        # 获取上传的图片和文本
-        image = request.files["image"]
-        text = request.form["text"]
-        conv_mode = request.form.get("conv_mode", "vicuna_v1")
-
-        if image:
-            image_path = os.path.join(app.config["UPLOAD_FOLDER"], image.filename)
-            image.save(image_path)  # 保存图片
-
-            # 发送请求到推理服务器
-            payload = {
-                "image_path": image_path,
-                "text": text,
-                "conv_mode": conv_mode
-            }
-            response = requests.post(SERVER_URL, json=payload)
-
-            if response.status_code == 200:
-                result = response.json()["response"]
-            else:
-                result = "Error: Server did not respond correctly."
-
-            return render_template("index.html", image_url=image_path, text=text, result=result)
-
-    return render_template("index.html", image_url=None, text="", result="")
-
-if __name__ == "__main__":
-    app.run(host="0.0.0.0", port=8080, debug=True)
+# 你的 ngrok 地址（确保它正确）
+API_URL = "https://8725-169-233-7-2.ngrok-free.app/predict/"
+
+def chat(image, text):
+    """调用本地 LLaVA 服务器的 API"""
+    if image is None:
+        return "请上传图片"
+    
+    # 保存图片为临时文件
+    image.save("temp.jpg")
+
+    files = {"image": open("temp.jpg", "rb")}
+    data = {"text": text}
+
+    try:
+        response = requests.post(API_URL, files=files, data=data)
+        return response.json().get("response", "错误：无法解析响应")
+    except Exception as e:
+        return f"请求失败: {str(e)}"
+
+# 创建 Gradio 界面
+iface = gr.Interface(
+    fn=chat,
+    inputs=[gr.Image(type="pil"), gr.Textbox(lines=2, placeholder="输入你的问题")],
+    outputs=gr.Textbox(),
+    title="LLaVA Visual Chatbot",
+    description="上传图片并输入问题，LLaVA 将回答你的问题。",
+)
+
+# 启动 Gradio
+iface.launch(server_name="0.0.0.0", server_port=7860)