Use Python programming to realize the docking of Baidu's natural language processing interface to help you develop intelligent processing programs

Use Python programming to realize the docking of Baidu’s natural language processing interface to help you develop intelligent processing programs

With the continuous advancement of artificial intelligence, natural language processing (Natural Language Processing) Language Processing (NLP) has become an important tool to solve text processing problems. Baidu's natural language processing interface provides a series of powerful functions, such as keyword extraction, text classification, sentiment analysis, etc., which can help developers quickly build intelligent processing programs. This article will introduce how to use Python programming to implement the docking of Baidu's natural language processing interface, and provide code examples.

1. Preparation

First, we need to register an account on Baidu Cloud official website, create an application, and then obtain our own API Key and Secret Key. After that, we also need to install Python's requests library to send HTTP requests, and install Baidu AI SDK to facilitate calling Baidu natural language processing interface.

pip install requests
pip install baidu-aip

2. Text review example

In practical applications, text review is a common requirement. We can use the text review function of Baidu's natural language processing interface to determine whether a piece of text violates regulations. The following is a code example using the Baidu text review interface:

from urllib import request
from urllib.parse import urlencode

def text_moderation(text):
    url = 'https://aip.baidubce.com/rest/2.0/solution/v1/text_censor/v2/user_defined'
    params = {
        'access_token': 'YOUR_ACCESS_TOKEN'  # 替换成自己的API Key
    }
    headers = {
        'Content-Type': 'application/x-www-form-urlencoded'
    }
    data = urlencode({'text':text}).encode('utf-8')
    req = request.Request(url, data=data, headers=headers, method='POST')
    response = request.urlopen(req)
    result = response.read().decode('utf-8')
    return result

text = "这是一段测试文本"
result = text_moderation(text)
print(result)

In the code, we first construct the request URL and parameters, and set the Content-Type of the request header. We then use Python's urllib library to send the POST request and convert the returned result into a string. Finally, we print out the result, which is the judgment result of the text review.

3. Text classification example

Text classification is another common NLP task. We can use the text classification function of Baidu Natural Language Processing interface to classify a piece of text. The following is a code example using Baidu text classification interface:

from aip import AipNlp

def text_classification(text, model_type='BERT', top_k=2):
    """ 你的 APPID AK SK """
    APP_ID = 'YOUR_APPID'  # 替换成自己的APPID
    API_KEY = 'YOUR_API_KEY'  # 替换成自己的API Key
    SECRET_KEY = 'YOUR_SECRET_KEY'  # 替换成自己的Secret Key

    client = AipNlp(APP_ID, API_KEY, SECRET_KEY)

    result = client.keyword(text, max=top_k, model_type=model_type)
    items = result.get('items', [])
    for item in items:
        print(item['tag'], item['score'])
        
text = "这是一篇关于科技新闻的文章"
text_classification(text)

In the code, we first create an AipNlp client object and initialize it using the APPID, API Key and Secret Key we obtained previously. Then, we call the client.keyword method, pass in the text to be classified and related parameters, and obtain the returned result, which is the label and confidence of the text classification. Finally, we loop through the results and print out the labels and confidence.

Through the above code examples, we can quickly integrate Baidu's natural language processing interface into our Python program and add NLP technology to our intelligent processing program development. Of course, the above is just the tip of the iceberg of Baidu's natural language processing interface functions. You can also use other interface functions to complete more complex tasks according to your own needs.

Summary: This article introduces how to use Python programming to implement the docking of Baidu's natural language processing interface, and provides code examples. I hope this article can help readers better understand and use Baidu's natural language processing interface and implement intelligent text processing programs.

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