Update app.py

app.py

@@ -40,56 +40,14 @@ def img_size(image):
     width = int(width)
     height = int(height)
     resized_img = image.resize((width, height))
-    # resized_img.save(image_path)
     return resized_img
 
-# def search_image(query) -> str:
-#     params = {
-#         "engine": "google_images",
-#         "q": query,
-#         "gl": "cn",
-#     }
-#     search = GoogleSearch(params)
-#     results = search.get_dict()
-#     suggested_searches = results.get('suggested_searches', [])
-#     if suggested_searches:
-#         thumbnails = [search['thumbnail'] for search in suggested_searches][:3]
-#     else:
-#         thumbnails = []
-#     # thumbnails = [search['thumbnail'] for search in results['suggested_searches']][:3]
-#     information = ""
-#     client = OpenAI()
-#     for idx, thumbnail in enumerate(thumbnails):
-#         response = client.chat.completions.create(
-#             model="gpt-4o-mini",
-#             messages=[
-#                 {
-#                     "role": "user",
-#                     "content": [
-#                         {"type": "text", "text": "What’s in this image?Give a brief answer"},
-#                         {
-#                             "type": "image_url",
-#                             "image_url": {
-#                                 "url": thumbnail,
-#                             },
-#                         },
-#                     ],
-#                 }
-#             ],
-#             max_tokens=100,
-#         )
-#         response_content = response.choices[0].message.content
-#         information = information + str(idx + 1) + ": " + response_content + "\n"
-#     return (information)
-
 
 def encode_image(image):
-    # image = Image.fromarray(image.astype("uint8"))
     buffered = io.BytesIO()
     image.save(buffered, format="PNG")
     return base64.b64encode(buffered.getvalue()).decode("utf-8")
-    # with open(image_path, "rb") as image_file:
-    #     return base64.b64encode(image_file.read()).decode("utf-8")
+
 
 
 def image_summarize(img_base64, prompt):
@@ -120,11 +78,6 @@ def generate_img_summaries(image):
     image_summaries.append(image_summarize(base64_image, prompt))
     return image_summaries
 
-# search_image = Tool(
-#     name="Image Search",  # 工具名称
-#     func=search_image,  # 引用search函数
-#     description="搜索图片引擎，当你需要检索相关图片的时候调用，输入是检索query，输出是与query有关的图片的信息"  # 工具描述
-# )
 
 en_prompt = """
 Remember, you are a false information verification tool developed by SCIR Laboratory at Harbin Institute of Technology
@@ -156,12 +109,12 @@ Use the following format:
 Question:  The input content that needs to be verified
 Pre Thought:  Briefly understand the content to be verified, whether it includes multiple details to be verified, and plan accordingly.
 Thought:  What should you do to verify the first detail
-Action:  One of the tool names in the tool list ({tool_name}) must not contain any other content
+Action:  One of the tool names in the tool list ({tool_names}) must not contain any other content
 Action Input: The input parameter for an Action
 Observation: The execution result of the Action
 ... (This' Thought/Action/Action Input/Observation 'logic can be repeated up to 3 times)
 Thought:  I now know the final answer
-Final Answer:  The verification result of the input content needs to be answered in Chinese
+Final Answer:  The verification result of the input content needs to be answered in English
 Begin!
 Question: {input}
 Pre Thought: {agent_scratchpad}