Create app.py

app.py

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+import gradio as gr
+
+
+
+# 读取图片
+import base64
+# Function to encode the image
+def encode_image(image_path):
+  with open(image_path, "rb") as image_file:
+    return base64.b64encode(image_file.read()).decode('utf-8')
+
+import requests
+import os
+
+openai_api_key = os.environ.get('openai_api_key')
+
+def ask_image(image,text,api_token=openai_api_key):
+  base64_image = encode_image(image)
+  messages=[
+      {
+        "role": "user",
+        "content": [
+          {"type": "text", "text": text},
+          {
+            "type": "image_url",
+            "image_url": {
+                "url":f"data:image/jpeg;base64,{base64_image}"
+  #               "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg",
+            },
+          },
+        ],
+      }
+    ]
+
+  # 请求头部信息
+  headers = {
+      'Authorization': f'Bearer {api_token}'
+  }
+
+  # 请求体信息
+  data = {
+      'model': 'gpt-4o',  # 可以根据需要更换其他模型
+      'messages': messages,
+      'temperature': 0.7  # 可以根据需要调整
+  }
+
+
+  # 设定最大重试次数
+  max_retry = 3
+
+  for i in range(max_retry):
+      try:
+          # 发送请求
+          response = requests.post('https://burn.hair/v1/chat/completions', headers=headers, json=data)
+
+          # 解析响应内容
+          response_data = response.json()
+          response_content = response_data['choices'][0]['message']['content']
+          usage = response_data['usage']
+
+          return response_content
+
+      except Exception as e:
+          # 如果已经达到最大重试次数，那么返回空值
+          if i == max_retry - 1:
+              print(f'重试次数已达上限，仍未能成功获取数据，错误信息：{e}')
+              response_content = ''
+              usage = {}
+              return response_content
+          else:
+              # 如果未达到最大重试次数，打印错误信息，并继续下一次循环
+              print(f'第{i+1}次请求失败，错误信息：{e}，准备进行第{i+2}次尝试')
+
+
+# gradio demo
+
+title = "Ask Image"
+description = "Ask anything about your Image"
+
+demo = gr.Interface(
+    fn=ask_image,
+    inputs=[gr.Image(label='',type='filepath'), gr.Text(label="Question")],
+    outputs=[gr.Textbox(label="Answer",lines=3)],
+    title = title,
+    description = description
+)
+demo.queue(max_size = 20)
+
+demo.launch(share = True)