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89 lines
2.7 KiB
Python
89 lines
2.7 KiB
Python
import requests
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from bs4 import BeautifulSoup
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import openai
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from openai import OpenAI
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import wikipediaapi
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import os
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import time
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self_api_key = os.environ.get('OPENAI_API_KEY')
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BASE_URL = os.environ.get('BASE_URL')
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if BASE_URL:
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client = openai.OpenAI(
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api_key=self_api_key,
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base_url=BASE_URL,
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)
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else:
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client = openai.OpenAI(
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api_key=self_api_key
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)
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def get_baidu_baike_content(keyword):
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# design api by the baidubaike
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url = f'https://baike.baidu.com/item/{keyword}'
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# post request
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response = requests.get(url)
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# Beautiful Soup part for the html content
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soup = BeautifulSoup(response.content, 'html.parser')
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# find the main content in the page
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# main_content = soup.find('div', class_='lemma-summary')
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main_content = soup.contents[-1].contents[0].contents[4].attrs['content']
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# find the target content
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# content_text = main_content.get_text().strip()
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return main_content
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def get_wiki_content(keyword):
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# Wikipedia API ready
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wiki_wiki = wikipediaapi.Wikipedia('MyProjectName (merlin@example.com)', 'en')
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#the topic content which you want to spider
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search_topic = keyword
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# get the page content
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page_py = wiki_wiki.page(search_topic)
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# check the existence of the content in the page
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if page_py.exists():
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print("Page - Title:", page_py.title)
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print("Page - Summary:", page_py.summary)
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else:
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print("Page not found.")
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return page_py.summary
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def modal_trans(task_dsp):
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try:
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task_in ="'" + task_dsp + \
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"'Just give me the most important keyword about this sentence without explaining it and your answer should be only one keyword."
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messages = [{"role": "user", "content": task_in}]
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response = client.chat.completions.create(messages=messages,
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model="gpt-3.5-turbo-16k",
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temperature=0.2,
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top_p=1.0,
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n=1,
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stream=False,
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frequency_penalty=0.0,
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presence_penalty=0.0,
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logit_bias={})
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response_text = response.choices[0].message.content
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spider_content = get_wiki_content(response_text)
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# time.sleep(1)
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task_in = "'" + spider_content + \
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"',Summarize this paragraph and return the key information."
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messages = [{"role": "user", "content": task_in}]
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response = client.chat.completions.create(messages=messages,
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model="gpt-3.5-turbo-16k",
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temperature=0.2,
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top_p=1.0,
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n=1,
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stream=False,
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frequency_penalty=0.0,
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presence_penalty=0.0,
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logit_bias={})
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result = response.choices[0].message.content
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print("web spider content:", result)
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except:
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result = ''
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print("the content is none")
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return result |