app.py

app.py

@@ -0,0 +1,84 @@
+import openai
+import requests
+import json
+import gradio as gr
+
+# 定义headers
+headers = {}
+
+def init_apis(openai_api_key, huggingface_api_key):
+    # 这个函数用于初始化OpenAI和Hugging Face API
+    openai.api_key = openai_api_key
+    headers["Authorization"] = f"Bearer {huggingface_api_key}"
+    print("APIs initialized successfully.")
+
+def query(url):
+    # 这个函数会向Hugging Face API发送图像URL，并获取图像中检测到的对象
+    API_URL = "https://api-inference.huggingface.co/models/facebook/detr-resnet-50"
+    response = requests.get(url)
+    response.raise_for_status()
+    data = response.content
+    api_response = requests.request("POST", API_URL, headers=headers, data=data)
+    return json.loads(api_response.content.decode("utf-8"))
+
+def process_query(openai_api_key, huggingface_api_key, user_query):
+    init_apis(openai_api_key, huggingface_api_key)
+
+    print("Processing the image object detection task...")
+    function_descriptions = [
+      {
+          "name": "目标检测模型",
+          "description": "Send an image URL to the Hugging Face API and get the detected objects in the image",
+          "parameters": {
+              "type": "object",
+              "properties": {
+                  "url": {
+                      "type": "string",
+                      "description": "The URL of the image to analyze",
+                  }
+              },
+              "required": ["url"],
+          },
+        }
+    ]
+
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo-0613",
+        messages=[{"role": "user", "content": user_query}],
+        functions=function_descriptions,
+        function_call="auto",
+    )
+
+    ai_response_message = response["choices"][0]["message"]
+    url = eval(ai_response_message['function_call']['arguments']).get("url")
+    function_response = query(url=url)
+
+    second_response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo-0613",
+        messages=[
+            {"role": "user", "content": user_query},
+            ai_response_message,
+            {
+                "role": "function",
+                "name": "query",
+                "content": json.dumps(function_response),
+            },
+        ],
+    )
+
+    return second_response['choices'][0]['message']['content']
+
+# Gradio界面
+iface = gr.Interface(
+    fn=process_query,
+    inputs=[
+        gr.inputs.Textbox(label="OpenAI Key", type="password"),
+        gr.inputs.Textbox(label="HuggingFace Key", type="password"),
+        gr.inputs.Textbox(label="Question")
+    ],
+    outputs="text",
+    title="Image Object Detection with Hugging Face and OpenAI",
+    description="Enter your OpenAI and Hugging Face API keys, and your question. The model will return the detected objects in the image.",
+)
+
+iface.launch()