esp-ai/src/functions/llm/dashscope/index.js

Provide a complete set of AI dialogue solutions for your development board, including but not limited to the IAT+LLM+TTS integration solution for the ESP32 series development board. | 为你的开发板提供全套的AI对话方案，包括但不限于 `ESP32` 系列开发板的 `IAT+LLM+TTS` 集成方案。

/**
 * Copyright (c) 2024 小明IO
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 *
 * Commercial use of this software requires prior written authorization from the Licensor.
 * 请注意：将 ESP-AI 代码用于商业用途需要事先获得许可方的授权。
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 * 
 * @author 小明IO   
 * @email  1746809408@qq.com
 * @github https://github.com/wangzongming/esp-ai
 * @websit https://espai.fun
 */

const https = require('https'); 

/**
 * 大语言模型插件
 * @param {String}      device_id           设备id 
 * @param {Number}      devLog              日志输出等级，为0时不应该输出任何日志   
 * @param {Object}      llm_config          用户配置的 apikey 等信息   
 * @param {String}      iat_server          用户配置的 iat 服务 
 * @param {String}      llm_server          用户配置的 llm 服务 
 * @param {String}      tts_server          用户配置的 tts 服务 
 * @param {String}      text                对话文本
 * @param {Function}    connectServerBeforeCb 连接 LLM 服务逻辑开始前需要调用这个方法告诉框架：eg: connectServerBeforeCb()
 * @param {Function}    connectServerCb     连接 LLM 服务后需要调用这个方法告诉框架：eg: connectServerCb(true)
 * @param {Function}    cb                  LLM 服务返回音频数据时调用，eg: cb({  count_text, text, texts })
 * @param {Function}    llmServerErrorCb    与 LLM 服务之间发生错误时调用，并且传入错误说明，eg: llmServerErrorCb("意外错误")
 * @param {Function}    llm_params_set      用户配置的设置 LLM 参数的函数
 * @param {Function}    logWSServer         将 ws 服务回传给框架，如果不是ws服务可以这么写: logWSServer({ close: ()=> {  中断逻辑... } })
 * @param {{role, content}[]}  llm_init_messages   用户配置的初始化时的对话数据
 * @param {{role, content}[]}  llm_historys llm 历史对话数据
 * @param {Function}    log                 为保证日志输出的一致性，请使用 log 对象进行日志输出，eg: log.error("错误信息")、log.info("普通信息")、log.llm_info("llm 专属信息")
 *  
*/
function LLM_FN({ devLog, is_pre_connect, log, llm_config, text, llmServerErrorCb, llm_init_messages = [], llm_historys = [], cb, llm_params_set, logWSServer, connectServerBeforeCb, connectServerCb }) {
    try {
        const { apiKey, llm, ...other_config } = llm_config;
        if (!apiKey) return log.error(`请配给 LLM 配置 apiKey 参数。`)
        if (!llm) return log.error(`请配给 LLM 配置 llm 参数。`)

        const url = 'https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation';
        const headers = {
            'Content-Type': 'application/json',
            'Authorization': 'Bearer ' + apiKey,
            'X-DashScope-SSE': 'enable'
        };

        // 预先连接函数
        async function preConnect() { 
            // 阿里没有太大作用...
        }
        if (is_pre_connect) {
            preConnect()
            return;
        }


        // 如果关闭后 message 还没有被关闭，需要定义一个标志控制
        let shouldClose = false;
        // 这个对象是固定写法，每个 TTS 都必须按这个结构定义
        const texts = {
            all_text: "",
            count_text: "",
            index: 0,
        } 

        connectServerBeforeCb();
        const r_params = {
            ...other_config,
            "model": llm,
            "input": {
                "messages": [
                    ...llm_init_messages,
                    ...llm_historys,
                    {
                        "role": "user", "content": text
                    },
                ]
            },
            "parameters": {
                "incremental_output": true,
                "result_format": "message"
            }
        };
        const body = JSON.stringify(llm_params_set ? llm_params_set({ ...r_params }) : r_params);
        const options = {
            method: 'POST',
            headers: headers
        }; 
        const req = https.request(url, options, (res) => {
            let httpResponse = '';
            if (res.statusCode !== 200) {
                connectServerCb(false);
                llmServerErrorCb("积灵 LLM 报错: " + res.statusCode + ", statusMessage:" + res.statusMessage)
            } else {
                connectServerCb(true);
            }

            res.on('data', (chunk) => {
                try {
                    const chunk_obj = JSON.parse(chunk.toString());
                    if (chunk_obj.code) {
                        llmServerErrorCb("积灵 LLM 报错: " + chunk.toString())
                    }
                } catch (err) { }
                if (shouldClose) return;
                httpResponse += chunk.toString();
                const text_pattern = /"content":"(.*?)","role"/g;
                let match;
                while (match = text_pattern.exec(chunk)) {
                    const chunk_text = match[1];
                    if (chunk_text) {
                        // console.log('LLM 输出 ：', chunk_text);
                        devLog === 2 && log.llm_info('LLM 输出 ：', chunk_text);
                        texts["count_text"] += chunk_text;
                        cb({ text, texts, chunk_text: chunk_text })
                    }
                }
            });

            res.on('end', () => {
                if (shouldClose) return;
                cb({
                    text,
                    is_over: true,
                    texts,
                    shouldClose
                })

                connectServerCb(false);
                devLog && log.llm_info("LLM 结果： " + texts["count_text"])
                devLog && log.llm_info('LLM connect close!\n')
            });
        });

        req.on('error', (err) => {
            connectServerCb(false);
            llmServerErrorCb("llm connect err: " + err)
        });

        logWSServer({
            close: () => {
                connectServerCb(false);
                shouldClose = true;
                req.abort()
            }
        })
 
        // 写入请求体
        req.write(body);
        req.end();
    } catch (err) {
        connectServerCb(false);
        console.log(err);
        log.error("积灵 LLM 插件错误：", err)
    }



}

module.exports = LLM_FN;