generated from dellevin/template
41 lines
1.1 KiB
Python
41 lines
1.1 KiB
Python
import extract_doc_tag as ex_doc_tag
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# --- 方式一：指定文件路径 ---
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file_path = 'test.txt'
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try:
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with open(file_path, 'r', encoding='utf-8') as file:
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my_article_content = file.read()
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except FileNotFoundError:
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print(f"错误：找不到文件 '{file_path}'")
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exit(1)
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except Exception as e:
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print(f"读取文件时发生错误: {e}")
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exit(1)
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model = "qwen3:1.7b"
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# model = "qwen3:0.6b"
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# OLLAMA_BASE_URL = "http://127.0.0.1:11434/api/generate"
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OLLAMA_BASE_URL = "http://152.136.153.72:27009/api/generate"
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extracted_tags = ex_doc_tag.extract_tags_with_ollama_from_content(
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OLLAMA_BASE_URL,
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model,
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my_article_content,
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max_tags=5,
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min_length=2,
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max_length=10
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)
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if extracted_tags['code'] == 0:
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print('思考过程：')
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print(extracted_tags['data']['think'])
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print('=' * 60)
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print('文章内容长度', len(my_article_content))
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# print(f"Ollama 模型：{model}")
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print('=' * 60)
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print('文章标签：', extracted_tags['data']['tags'])
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print('=' * 60)
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print(f"总耗时: {extracted_tags['data']['consume']:.2f} 秒")
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else:
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print(extracted_tags)
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