1200字范文 > NLP实战一利用OpenAI Codex实现中文转python代码

NLP实战一利用OpenAI Codex实现中文转python代码

时间：2023-04-15 13:07:42

OpenAI Codex 是 GPT-3 的后代；它的训练数据包含自然语言和来自公开来源的数十亿行源代码，包括公共 GitHub 存储库中的代码。OpenAI Codex 最擅长 Python，但它也精通十多种语言，包括 JavaScript、Go、Perl、PHP、Ruby、Swift 和 TypeScript，甚至是 Shell。它有 14KB 的 Python 代码内存，而 GPT-3 只有 4KB——因此它在执行任何任务时可以考虑超过 3 倍的上下文信息。

GPT-3 的主要技能是生成自然语言以响应自然语言提示，这意味着它影响世界的唯一方式是通过读者的思想。OpenAI Codex 具有对 GPT-3 的大部分自然语言理解，但它会生成工作代码——这意味着您可以使用 API 向任何软件发出英语命令。OpenAI Codex 使计算机能够更好地理解人们的意图，这可以使每个人都能用计算机做更多的事情。

一旦程序员知道要构建什么，编写代码的行为就可以被认为是 (1) 将问题分解为更简单的问题，以及 (2) 将这些简单问题映射到已经存在的代码（库、API 或函数）存在。后一项活动可能是编程中最不有趣的部分（也是进入门槛最高的部分），也是 OpenAI Codex 最擅长的地方。OpenAI Codex 是一种通用编程模型，这意味着它基本上可以应用于任何编程任务（尽管结果可能会有所不同）。我们已经成功地将它用于编译、解释代码和重构代码。但我们知道，我们只触及了可以做的事情的皮毛。

先调用有道翻译的API接口，将汉语翻译为英语，再用GTP3的codex生成代码

import requestsfrom hashlib import md5import timeimport random#请求地址url = "/translate_o?smartresult=dict&smartresult=rule"appVersion = "5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/84.0.4147.125 Safari/537.36"headers = {"Accept": "application/json, text/javascript, */*; q=0.01","Accept-Encoding": "gzip, deflate","Accept-Language": "zh-CN,zh;q=0.9","Connection": "keep-alive","Content-Length": "244","Content-Type": "application/x-www-form-urlencoded; charset=UTF-8","Cookie": "OUTFOX_SEARCH_USER_ID=-1506602845@10.169.0.82; JSESSIONID=aaaUggpd8kfhja1AIJYpx; OUTFOX_SEARCH_USER_ID_NCOO=108436537.92676207; ___rl__test__cookies=1597502296408","Host": "","Origin": "","Referer": "/","user-agent": appVersion,"X-Requested-With": "XMLHttpRequest",}#模拟jsdef r(e):# bvt = md5(appVersion.encode()).hexdigest()# ltsr = str(int(time.time() * 1000))# ii = r + str(random.randint(0,9))return {"ts": r,"bv": t,"salt": i,"sign": md5(("fanyideskweb" + e + i + "]BjuETDhU)zqSxf-=B#7m").encode()).hexdigest()}def fanyi(word):data = r(word)params = {"i": word,"from": "UTO","to": "AUTO","smartresult": "dict","client": "fanyideskweb","salt": data["salt"],"sign": data["sign"],"lts": data["ts"],"bv": data["bv"],"doctype": "json","version": "2.1","keyfrom": "fanyi.web","action": "FY_BY_REALTlME",}response = requests.post(url=url,headers=headers,data=params)return response.json()text="""计算一组点之间的平均距离"""result = fanyi(text)r_data = result["translateResult"]for data in r_data:print(data[0]["tgt"])print(data[0]["src"])

import osimport openaiimport jsonopenai.api_key_path = "C:\ProgramData\Anaconda3\Lib\site-packages\openai\openaikey.txt"# openai.api_key = os.getenv("OPENAI_API_KEY")response = pletion.create(model="text-davinci-002",prompt="# Python 3\n# "+data[0]["tgt"],#"Generates an arithmetic sequence of 1-100 in the list",temperature=0.7,max_tokens=256,top_p=1,frequency_penalty=0,presence_penalty=0)print(json.loads(str(response))['choices'][0]['text'])

生成的结果

# in (x,y) coordinate space#def average(points):sumx = 0sumy = 0for i in range(len(points)):sumx = sumx + points[i][0]sumy = sumy + points[i][1]return sumx / len(points), sumy / len(points)## Python 3# Calculate the Euclidean distance between two points# in (x,y) coordinate space#def euclideanDistance(point1, point2):sum = 0for i in range(len(point1)):sum = sum + math.pow(point1[i] - point2[i], 2)return math.sqrt(sum)## Python 3# Calculate the average distance between a set of points# in (x,y) coordinate space#def averageDistance(points):sum = 0for i in range(len(points)):for j in range(i + 1, len(points)):

实现的方法

拿到OPENAI的key

解决 OpenAI’s API is not available in your country.（不支持中国）

/overview购买了OPENAI账号

import osimport openaiopenai.api_key_path = "C:\ProgramData\Anaconda3\Lib\site-packages\openai\openaikey.txt"# openai.api_key = os.getenv("") response = pletion.create(model="text-davinci-002",prompt="Convert this text to a programmatic command:\n\nExample: Ask Constance if we need some bread\nOutput: send-msg `find constance` Do we need some bread?\n\nContact the ski store and figure out if I can get my skis fixed before I leave on Thursday",temperature=0,max_tokens=100,top_p=1.0,frequency_penalty=0.2,presence_penalty=0.0,stop=["\n"])response