chatterbot使用java调用例子 https://github.com/gunthercox/ChatterBot MySQL支持请确认chatterbot/ext/sqlalchemy_app/models.py中的UnicodeString改为UnicodeString(512) https://github.com/gunthercox/ChatterBot/pull/1200

bot.py

# -*- coding: utf-8 -*-
import sys

from chatterbot import ChatBot
from chatterbot.comparisons import sentiment_comparison
from chatterbot.trainers import ChatterBotCorpusTrainer

bot = ChatBot(
    "sf",
    storage_adapter="chatterbot.storage.SQLStorageAdapter",
    database_uri="mysql+pymysql://root:root@localhost/test?charset=utf8mb4",
    # database="D:/workspace/chatterbot-api/src/main/resources/py/sf.sqlite3",
    read_only=True,
    # statement_comparison_function=sentiment_comparison,
    logic_adapters=[
      {
        'import_path': 'chatterbot.logic.SpecificResponseAdapter',
        'input_text': 'sfpp',
        'output_text': '您好，请访问: http://sfpp.sf-express.com'
      },
      {
        'import_path': 'chatterbot.logic.LowConfidenceAdapter',
        'threshold': 0.25,
        'default_response': '您好，我现在还不知道怎么回答您的问题！请访问SFPP--搜索您的问题--也许能得到答案，3Q。'
      },
      {
        'import_path': 'chatterbot.logic.BestMatch'
      }
    ]
)

bot.set_trainer(ChatterBotCorpusTrainer)
bot.train([
  "chatterbot.corpus.chinese"
])


def get_bot(arg):
  response = bot.get_response(arg, conversation_id=10)

  print(response)


if __name__ == '__main__':
  get_bot(sys.argv[1])

ChatterbotService.java

package com.xxxx.chatterbot.chatterbotapi.service;

import java.io.ByteArrayOutputStream;
import java.io.IOException;
import lombok.extern.slf4j.Slf4j;
import org.apache.commons.exec.CommandLine;
import org.apache.commons.exec.DefaultExecutor;
import org.apache.commons.exec.ExecuteStreamHandler;
import org.apache.commons.exec.ExecuteWatchdog;
import org.apache.commons.exec.Executor;
import org.apache.commons.exec.PumpStreamHandler;
import org.apache.commons.lang3.SystemUtils;
import org.springframework.beans.factory.InitializingBean;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.stereotype.Service;

/**
 * @author YANGLiiN 2018-02-01 16:46
 */

@Slf4j
@Service
public class ChatterbotService implements InitializingBean {

  @Value("${python.command.path:/home/sfapp/}")
  private String pythonCommandPath;

  private static final String CHARSET = SystemUtils.IS_OS_WINDOWS ? "GBK" : "UTF-8";

  public String bot(String question) {
    String resp = execCommand(
        "python " + pythonCommandPath + "chatterbot.py " + question);

    return resp;
  }


  @Override
  public void afterPropertiesSet() throws Exception {
    execCommand("python " + pythonCommandPath + "train.py");
  }


  private final String execCommand(String commandLine) {
    log.info("要执行的命令是：{}", commandLine);
    String resp = null;
    Executor executor = new DefaultExecutor();

    //接收正常结果流
    ByteArrayOutputStream outputStream = new ByteArrayOutputStream();
    //接收异常结果流
    ByteArrayOutputStream errorStream = new ByteArrayOutputStream();
    ExecuteStreamHandler streamHandler = new PumpStreamHandler(outputStream, errorStream);
    executor.setStreamHandler(streamHandler);

    // 设置脚本执行超时时间
    ExecuteWatchdog watchdog = new ExecuteWatchdog(60 * 1000);
    executor.setWatchdog(watchdog);

    CommandLine cl = CommandLine.parse(commandLine);
    try {
      executor.execute(cl);
      resp = outputStream.toString(CHARSET);
    } catch (IOException e) {
      e.printStackTrace();
    }

    return resp;
  }
}

dgk.py

from datetime import datetime

from chatterbot import ChatBot
from chatterbot.trainers import ListTrainer

# 初始化聊天机器人
momo = ChatBot(
    'Momo',
    storage_adapter="chatterbot.storage.SQLStorageAdapter",
    database_uri="mysql+pymysql://root:root@localhost/test?charset=utf8mb4",
    read_only=False
)


# 读取.conv 数据文件，因为我服务器配置较低，所以选择了一个内容较少的文件
# 这个函数是一个生成器
def read_conv(filename='D:/opensource/dgk_lost_conv/results/prisonb.conv'):
  with open(filename, mode='rt', encoding='utf-8') as f:
    conv = []
    # 逐行读取
    for line in f:
      _line = line.replace('\n', '').replace('/', '').strip()  # 预处理字符串 去掉首位空格
      if _line.startswith('E'):  # 如果是分隔符 表示对话结束 返回对话列表
        yield conv
        conv = []  # 重置对话列表
      elif _line.startswith('M'):  # 不是分隔符则将内容加入对话列表
        # c = _line.split()[-1]  # 其实这里如果对话中包含空格 对话数据会不完整，应该只去掉M和开头的空格
        c = _line.replace('M ',
                          '').strip()
        conv.append(c)


def train_momo():
  for conv in read_conv():
    print(conv)
    momo.set_trainer(ListTrainer)  # 指定训练方式
    momo.train(conv)  # 训练数据


def test_momo(question=None):
  print(momo.get_response(question, 7))


if __name__ == '__main__':
  # train_momo()
  print(datetime.now())
  test_momo('到底发生什么了')
  print(datetime.now())

flask_api.py

import logging

from chatterbot import ChatBot
from chatterbot.trainers import ListTrainer
from flask import Flask, request, jsonify

logging.basicConfig(level=logging.INFO, filename='mybot.log',
                    format='%(asctime)s %(filename)s[line:%(lineno)d] %(levelname)s %(message)s')

app = Flask(__name__)
app.config['JSON_AS_ASCII'] = False

tbot = ChatBot(
    "sfbot",
    storage_adapter="chatterbot.storage.SQLStorageAdapter",
    database_uri="mysql+pymysql://appmgr:[email protected]:3306/bot?charset=utf8mb4",
    logic_adapters=["chatterbot.logic.BestMatch"],
    read_only=False
)

cbot = ChatBot(
    "sfbot",
    storage_adapter="chatterbot.storage.SQLStorageAdapter",
    database_uri="mysql+pymysql://appmgr:[email protected]:3306/bot?charset=utf8mb4",
    read_only=True,
    # statement_comparison_function=sentiment_comparison,
    logic_adapters=[
        {
            'import_path': 'chatterbot.logic.BestMatch'
        },
        {
            'import_path': 'chatterbot.logic.SpecificResponseAdapter',
            'input_text': 'sfpp',
            'output_text': '您好，请访问: http://sfpp.sf-express.com'
        },
        {
            'import_path': 'chatterbot.logic.LowConfidenceAdapter',
            'threshold': 0.25,
            'default_response': '您好，我现在还不知道怎么回答您的问题！请访问SFPP--搜索您的问题--也许能得到答案，3Q。'
        }
    ]
)

error_format_msg = '训练数据为空或格式不正确，请按照"Q: 问题A: 答案"这种格式，注意Q: A: 后边各一个英文空格'


@app.route('/chat', methods=['GET', 'POST'])
def chat_bot():
    question = request.args.get('question', '')
    user_id = request.args.get('user_id', '1')

    try:
        resp = cbot.get_response(question, user_id)
        return jsonify(code=1, data=resp.text)
    except Exception:
        logging.exception('获取回复报错了,请求参数question[%s] user_id[%s]', question, user_id)
        return jsonify(code=-1, data='error')


@app.route('/train', methods=['POST'])
def train_bot():
    lines = []
    ss = request.form.get('data')

    if ss:
        data = ss.split('Q: ')
        if data:
            for d in data:
                idx_a = d.find('A: ')

                if idx_a > -1:
                    q = d[:idx_a]
                    a = d[idx_a + 2:]

                    lines.append(q.strip())
                    lines.append(a.strip())

        else:
            return jsonify(code=2, data=error_format_msg)

    else:
        return jsonify(code=2, data=error_format_msg)

    try:
        if lines:
            tbot.set_trainer(ListTrainer)
            tbot.train(lines)
        return jsonify(code=1, data='success')
    except Exception:
        logging.exception('训练数据时报错了')
        return jsonify(code=-1, data='error')


if __name__ == '__main__':
    app.run(host='0.0.0.0', port=5000)

pom.xml

    <dependency>
      <groupId>org.apache.commons</groupId>
      <artifactId>commons-exec</artifactId>
      <version>1.3</version>
    </dependency>
    <dependency>
      <groupId>org.apache.commons</groupId>
      <artifactId>commons-lang3</artifactId>
      <version>3.7</version>
    </dependency>

train.py

# -*- coding: utf-8 -*-
from chatterbot import ChatBot
from chatterbot.trainers import ChatterBotCorpusTrainer

bot = ChatBot(
    "sf",
    storage_adapter="chatterbot.storage.SQLStorageAdapter",
    database_uri="mysql+pymysql://root:root@localhost/test?charset=utf8mb4"
    # database="D:/workspace/chatterbot-api/src/main/resources/py/sf.sqlite3"

)

bot.set_trainer(ChatterBotCorpusTrainer)

bot.train([
  "chatterbot.corpus.chinese"
])

if __name__ == '__main__':
  print(bot.get_response('disconf'))