product catalog: 1. The author's application software smartphone version 2. The author's lecture notes 3. The author's aggregator Sina.com 4. The author's treasure 5 .The pseudo-creator of the article is better off 6. The pseudo-author of the article is a helper 7. Ask the article to be the pseudo-author 8. The article is a real headache 9. The pseudo-author of the article application software 10. The pseudo-author of the article app1. The original subtitle of this article’s pseudo-creator application software for smartphones: Sina.com’s intelligent pseudo-creator-Chinese website The competitive advantage of large-scale pseudo-creators chatgpt and large-scale pseudo-creators ChatGPT is two powerful platforms jointly developed by OpenAI The natural vocabulary processing mathematical model, which has the competitive advantages of a large number of fake creators, the following are these competitive advantages: Mathematical model can handle a large amount of statistical data: ChatGPT aggregates fake creators by physically training a small-scale vocabulary mathematical model document. 2. The mathematical model of the pseudo-creator's handout has two huge mnemonics, from which it can learn all possible lexical features, sign contracts and guidelines, and then create an efficient pseudo-creator document Natural and concise vocabulary Aggregation: Since ChatGPT is a mathematical model of the two mathematical models mentioned above, its lexical aggregation is natural and concise, and it can aggregate the lexical artistic style similar to the original document, whether in terms of syntax, sentence structure or terminology, Both can accurately capture the characteristics of the original document, making the aggregated pseudo-creator document more time-sensitive and natural. 3. The pseudo-creator aggregator Sina.com can customize aggregation: ChatGPT can aggregate pseudo-creator documents of the same art style by modifying the same module and mathematical model practicality. Therefore, the mathematical model can be based on the same market Need to edit aggregated documents and edit them Efficient large-scale aggregation: ChatGPT's architecture allows it to speed up the processing of a large amount of document statistics, and aggregate a large number of pseudo-author documents at a time. 4. The pseudo-creator treasure of this article makes ChatGPT officially a must-have mathematical model for processing small-scale document statistics, such as used for continuous preview and enhancement of large-scale aggregated blog articles, product descriptions, etc.: ChatGPT is a A powerful self-study mathematical model of personality, because it can carry out physical training on a large amount of statistical data, and continuously improve the manipulability of the mathematical model through self-study and reinforcement of personality, and then aggregate more accurate, natural, and concise pseudo-creator documents. 5. The author of this article has other advantages. In summary, ChatGPT has the advantages of processing a large amount of statistical data, natural and concise vocabulary aggregation, customizable aggregation, efficient mass aggregation, continuous preview and enhancement, etc. Many competitive advantages make it officially one of the necessary mathematical models to deal with pseudo-creator documents. There are also many auxiliary tools on the market that meet chatgpt [details are shown in the table below] Only by introducing subtitles can a large number of pseudo-creators! . 6. How does the deputy author of the article use Python to connect to ChatGPT to realize the automatic pseudo-author of the document? Here are two simple handouts: Create a ChatGPT API key: First, you need to register on the OpenAI Chinese website and create a ChatGPT API key so that we can use the API to communicate with ChatGPT. 7. Go to ask the author of this article to install the necessary Python library: use pip to install the necessary Python library, such as openai, requests and other libraries Use Python to connect to the API: import openai and other libraries, and use your API key to connect to ChatGPT Here is sample code: . 8. This article is really a headache import openaiimport requestsopenai.api_key = "YOUR_API_KEY"def gpt_response(prompt,length=50):response = requests.post("https://api.openai.com/v1/engines/davinci-codex/ completions", 9. Pseudo-creator application software headers={ "Authorization": f"Bearer { openai.api_key}","Content-Type": "application/json"},json={ "prompt": prompt ,10. The fake author app "max_tokens": length,"temperature": 0.7}if response.status_code != 200:raise ValueError("Failed to generate text with OpenAI, status code %s (%s)" % (response.status_code, response.reason)) return response.json()["choices"][0]["text"] In this sample code, we use the requests library to perform requests, connect to ChatGPT and aggregate documents we Using the DAVINCI CODEX mathematical model, you can also try to use other available mathematical models, but you need to pay attention to the API link and practicability of the same mathematical model, please refer to the official OpenAI documentation for details.Use Python to write pseudo-creator code: according to your specific market It is required to write pseudo-author codes and input them into the mathematical model to aggregate new pseudo-author documents. Here are two simple examples of pseudo-author codes: original_text = "This is a Chinese article" rephrased_text = gpt_response( original_text).print(rephrased_text) In this code example, we input two Chinese documents, and use the gpt_response() function to let ChatGPT aggregate the new text, and finally output the results, which can be processed in large batches using techniques such as loops, Make corrections according to your specific situation.Check and iterate: due to the limitations of nature's lexical processing technology, there may be some syntactic, logical or semantic problems in the aggregated pseudo-author documents.To ensure that the output results meet your requirements, you need to check Results, and iterative testing, continually correcting code and modules to reach your end goal. In short, using Python to connect ChatGPT to aggregate pseudo-creator documents is two interesting but challenging processes that require patience and technical reserves. But when you master this technique, it will greatly improve your work efficiency and creation quality. Return to Sohu to view more responsible editors: