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README.md

@@ -160,51 +160,6 @@ curl http://localhost:8000/v1/chat/completions \
 pip install gradio
 ```
 
-1.1 基于gradio的llava对话
-
-```python
-#gradio_openai_vlm_webserver.py
-import argparse
-import gradio as gr
-from openai import OpenAI
-
-parser = argparse.ArgumentParser(description='LLaVA Chatbot Interface')
-parser.add_argument('--model-url', type=str, default='http://localhost:8000/v1', help='Model URL')
-parser.add_argument('-m', '--model', type=str, required=True, help='Model path')
-parser.add_argument("--host", type=str, default=None)
-parser.add_argument("--port", type=int, default=8001)
-
-args = parser.parse_args()
-
-openai_api_key = "EMPTY"
-openai_api_base = args.model_url
-
-client = OpenAI(api_key=openai_api_key, base_url=openai_api_base)
-
-def predict(message, history, image):
-    history_openai_format = []
-    user_message = message
-    if image:
-        user_message += f" [local file]({image})"
-    history_openai_format.append({"role": "user", "content": user_message})
-    try:
-        chat_response = client.chat.completions.create(
-            model=args.model,
-            messages=history_openai_format
-        )
-        return chat_response.choices[0].message.content
-    except Exception as e:
-        return f"An error occurred: {str(e)}"
-gr.ChatInterface(
-    predict,
-    additional_inputs=[
-        gr.Image(label="Upload Image", type="filepath",scale=1, width="50%")
-    ],
-    title="LLaVA Chatbot",
-    description="Chat with the LLaVA model and upload images for visual understanding."
-).queue().launch(server_name=args.host, server_port=args.port, share=True)
-```
-
 2.安装必要文件
 
     2.1 启动gradio服务，根据提示操作

gradio_openai_vlm_webserver.py

+#gradio_openai_vlm_webserver.py
+import argparse
+import gradio as gr
+from openai import OpenAI
+
+parser = argparse.ArgumentParser(description='LLaVA Chatbot Interface')
+parser.add_argument('--model-url', type=str, default='http://localhost:8000/v1', help='Model URL')
+parser.add_argument('-m', '--model', type=str, required=True, help='Model path')
+parser.add_argument("--host", type=str, default=None)
+parser.add_argument("--port", type=int, default=8001)
+
+args = parser.parse_args()
+
+openai_api_key = "EMPTY"
+openai_api_base = args.model_url
+
+client = OpenAI(api_key=openai_api_key, base_url=openai_api_base)
+
+def predict(message, history, image):
+    history_openai_format = []
+    user_message = message
+    if image:
+        user_message += f" [local file]({image})"
+    history_openai_format.append({"role": "user", "content": user_message})
+    try:
+        chat_response = client.chat.completions.create(
+            model=args.model,
+            messages=history_openai_format
+        )
+        return chat_response.choices[0].message.content
+    except Exception as e:
+        return f"An error occurred: {str(e)}"
+gr.ChatInterface(
+    predict,
+    additional_inputs=[
+        gr.Image(label="Upload Image", type="filepath",scale=1, width="50%")
+    ],
+    title="LLaVA Chatbot",
+    description="Chat with the LLaVA model and upload images for visual understanding."
+).queue().launch(server_name=args.host, server_port=args.port, share=True)