Update app.py

app.py

@@ -1,48 +1,29 @@
 import gradio as gr
 import requests
-import base64
-from PIL import Image
-import io
 
-# **本地 GPU 服务器 API**
-LOCAL_SERVER_URL = "http://127.0.0.1:5000/infer"
-
-def image_to_base64(image):
-    """PIL Image -> Base64"""
-    buffer = io.BytesIO()
-    image.save(buffer, format="PNG")
-    return base64.b64encode(buffer.getvalue()).decode("utf-8")
-
-def llava_infer(image, text):
-    """把用户输入的图片+文本发送到本地服务器"""
-    if image is None or text.strip() == "":
-        return "请提供图片和文本输入"
-
-    image_base64 = image_to_base64(image)
-    payload = {"image": image_base64, "text": text}
-
-    try:
-        response = requests.post(LOCAL_SERVER_URL, json=payload)
-        response_data = response.json()
-        return response_data["response"]
-    except Exception as e:
-        return f"服务器错误: {e}"
-
-# **Gradio Web UI**
-with gr.Blocks(title="LLaVA Remote Web UI") as demo:
-    gr.Markdown("# 🌋 LLaVA Web Interface (Remote Inference)")
-    gr.Markdown("上传图片并输入文本，LLaVA 将在远程 GPU 服务器推理")
-
-    with gr.Row():
-        with gr.Column(scale=3):
-            image_input = gr.Image(type="pil", label="上传图片")
-            text_input = gr.Textbox(placeholder="输入文本...", label="输入文本")
-            submit_button = gr.Button("提交")
-
-        with gr.Column(scale=7):
-            chatbot_output = gr.Textbox(label="LLaVA 输出", interactive=False)
-
-    submit_button.click(fn=llava_infer, inputs=[image_input, text_input], outputs=chatbot_output)
-
-# **启动 Hugging Face Web UI**
-demo.launch(server_name="0.0.0.0", server_port=7860, share=True)
+API_URL = "http://169.233.7.2/infer"
+
+def process_image(image, text, conv_mode):
+    """调用本地 API 进行推理"""
+    if image is None:
+        return "Please upload an image."
+    
+    files = {"image": image}
+    data = {"text": text, "conv_mode": conv_mode}
+
+    response = requests.post(API_URL, files=files, json=data)
+    return response.json().get("response", "Error processing the image.")
+
+iface = gr.Interface(
+    fn=process_image,
+    inputs=[
+        gr.Image(type="file"), 
+        gr.Textbox(label="Prompt"), 
+        gr.Dropdown(choices=["vicuna_v1", "llama3"], label="Conversation Mode")
+    ],
+    outputs="text",
+    title="LLaVA Web Interface",
+    description="Upload an image and provide a prompt to interact with LLaVA."
+)
+
+iface.launch(server_name="0.0.0.0", server_port=7860)