简单人工智能---基于百度接口和图灵机器人
基础准备工作
百度api接口准备:
接下来就是创建应用
选择需要的,然后生成api接口
图灵机器人准备:
创建一个机器人
进行机器人的设置
写后台代码
from flask import Flask,render_template,jsonify,request,send_file from uuid import uuid4 from others import audio2text ,text2audio,my_nlp app = Flask(__name__) @app.route("/") def index(): return render_template("WebToy.html") @app.route("/upload",methods=["post"]) def upload(): fi = request.files.get("reco") fi_name = f"{uuid4()}.wav" fi.save(fi_name) text = audio2text(fi_name) new_text = my_nlp(text) filename = text2audio(new_text) ret = { "filename":filename, "content":new_text, "code":0 } return jsonify(ret) @app.route("/get_file/<name>") def get_file(name): return send_file(name) if __name__ == '__main__': app.run("0.0.0.0",9527)
import os import requests from aip import AipSpeech from aip import AipNlp from uuid import uuid4 """ 你的 APPID AK SK """ APP_ID = '15842542' API_KEY = 'AMphU5SfVThjqH6Ii7BFnacm' SECRET_KEY = 'aHiCNZ3psw1cOiW62p0nQMvaG4DhLrjS' client = AipSpeech(APP_ID, API_KEY, SECRET_KEY) nlp_client = AipNlp(APP_ID, API_KEY, SECRET_KEY) # 读取文件 def get_file_content(filepath): os.system(f"ffmpeg -y -i {filepath} -acodec pcm_s16le -f s16le -ac 1 -ar 16000 {filepath}.pcm") with open(f"{filepath}.pcm", "rb") as f: return f.read() # 识别本地文件 def audio2text(filepath): res = client.asr(get_file_content(filepath), 'pcm', 16000, { "dev_pid": 1536, }) text = res.get("result")[0] return text # 智能问答 def to_ling(text, uid): data = { "perception": { "inputText": { "text": "附近的酒店" } }, "userInfo": { "apiKey": "6d84dea150a34a3db748a9728fa93fec", "userId": "1" } } data["perception"]["inputText"]["text"] = text data["userInfo"]["userId"] = uid res = requests.post("http://openapi.tuling123.com/openapi/api/v2",json=data) res_json = res.json() text = res_json.get("results")[0].get('values').get("text") return text def my_nlp(text): if nlp_client.simnet(text, "你叫什么名字").get("score") >= 0.75: A = "我叫车干儿" return A if nlp_client.simnet(text, "你吃饭了没有").get("score") >= 0.75: A = "现在才几点,我还没有吃饭了" return A A = to_ling(text,2) return A # 语音合成 def text2audio(text): result = client.synthesis(text, "zh", 1, { "vol": 6, "per": 4, "spd": 4, "pit": 7, }) filename = f"{uuid4()}.mp3" if not isinstance(result, dict): with open(filename, "wb") as f1: f1.write(result) return filename
#前端代码 <!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <title>我是玩具</title> </head> <body> <p> <audio id="player" controls autoplay></audio> </p> <button onclick="start_reco()">录音</button> <button onclick="stop_reco()">发送录音</button> <div id="mes"> </div> </body> <script type="text/javascript" src="/static/Recorder.js"></script> <script type="text/javascript" src="/static/jquery-3.3.1.min.js"></script> <script type="text/javascript"> var serv = "http://192.168.11.54:9527"; var reco = null; var audio_context = new AudioContext();//音频内容对象 navigator.getUserMedia = (navigator.getUserMedia || navigator.webkitGetUserMedia || navigator.mozGetUserMedia || navigator.msGetUserMedia); navigator.getUserMedia({audio: true}, create_stream, function (err) { console.log(err) }); function create_stream(user_media) { var stream_input = audio_context.createMediaStreamSource(user_media); reco = new Recorder(stream_input); } function start_reco() { reco.record(); } function stop_reco() { reco.stop(); reco.exportWAV(function (wav_file) { console.log(wav_file); var formdata = new FormData(); // form 表单 {key:value} formdata.append("reco", wav_file); // form input type="file" $.ajax({ url: serv + "/upload", type: 'post', processData: false, contentType: false, data: formdata, dataType: 'json', success: function (data) { if(data.code == 0) { document.getElementById("player").src="http://192.168.11.54:9527/get_file/"+ data.filename; document.getElementById("mes").innerText=data.content; } } }) }); reco.clear(); } </script> </html>
注意事项:
录音的时候,文件需要进行一个转码,需要安装ffmpeg
安装:pip install ffmpeg
添加环境变量:
添加环境变量即可!!!