在飞腾E2000Q开发板上，基于RT-Thread操作系统，实现DeepSeek语音交互

目录

一 ，简介

二 ，流程与结果分享

   1. Phytium E2000q demo开发板连接

   2. RT-Thread Kconfig 配置选择

（1）驱动

（2）软件包

 3. 主要代码

（1）录音功能，将录音结果保存为PCM文件

（2）使用百度AI进行语音识别

（3）将识别内容上传至DeepSeek，并显示返回打印

 4. 结果展示

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一 ，简介

DeepSeek是由深度求索团队开发的大语言模型，本实验将基于DeepSeek-R1模型。结合百度AI语音识别，在嵌入式设备上实现实时聊天功能。

1. 使用Rt-Thread的Phytium E2000Q demo开发板
2. 插入SD卡，挂载RT-Thread DFS-V2 elm FatFs文件系统
3. 安装Rt-Thread支持的webclient，mbedtls，cJSON，llm-chat软件包
4. 使用Audio组件，实现实时录音功能，将录音内容以PCM格式存入文件系统
5. 使用webclient将PCM文件上传到百度语音识别AI服务端，识别后返回Json
6. 将识别内容通过Webclient + mbedtls 上传至Deep-Seek服务端，使用llm-chat + cJson分析返回内容，在输出界面上实时打印返回内容。

二 ，流程与结果分享

   1. Phytium E2000q demo开发板连接

按照官方指南，搭载RT-Thread运行环境

   2. RT-Thread Kconfig 配置选择

（1）驱动

E2000Q demo自带的ES8336驱动需要I2C支持，I2C设备也需要勾选

勾选I2S设备，并按下图配置采样率和采样位数

（2）软件包

WebClient，并支持MbedTLS

cJSON支持，用于分析返回json

llm 用于创建与DeepSeek的连接，若无配置选项，可下载后放置于bsp\phytium\aarch64\packages下，开源仓库：https://github.com/Rbb666/llm_chat

 3. 主要代码

（1）录音功能，将录音结果保存为PCM文件

/* pcm_record.c */
#include <rtthread.h>
#include <rtdevice.h>
#include <dfs_posix.h>#define RECORD_TIME_MS      5000
#define RT_I2S_SAMPLERATE   8000
#define RECORD_CHANNEL      2
#define RECORD_CHUNK_SZ     ((RT_I2S_SAMPLERATE * RECORD_CHANNEL * 2) * 20 / 1000)#define SOUND_DEVICE_NAME    "I2S0"      /* Audio 设备名称 */
static rt_device_t mic_dev;              /* Audio 设备句柄 */int pcm_record()
{int fd = -1;uint8_t *buffer = NULL;int length, total_length = 0;fd = open("file.pcm", O_WRONLY | O_CREAT);if (fd < 0){rt_kprintf("open file for recording failed!\n");return -1;}buffer = rt_malloc(RECORD_CHUNK_SZ);if (buffer == RT_NULL)goto __exit;mic_dev = rt_device_find(SOUND_DEVICE_NAME);if (mic_dev == RT_NULL)goto __exit;rt_device_open(mic_dev, RT_DEVICE_OFLAG_RDONLY);while (1){length = rt_device_read(mic_dev, 0, buffer, RECORD_CHUNK_SZ);if (length){write(fd, buffer, length);total_length += length;}if ((total_length / RECORD_CHUNK_SZ) >  (RECORD_TIME_MS / 20))break;}close(fd);rt_device_close(mic_dev);__exit:if (fd >= 0)close(fd);if (buffer)rt_free(buffer);return 0;
}
MSH_CMD_EXPORT(pcm_record, record voice to a pcm file);  // 修改命令描述

（2）使用百度AI进行语音识别

使用百度语音之前，需要在百度AI官网上获取token，请按照官方教程获取百度AI开放平台-全球领先的人工智能服务平台

        以短语音识别模型为例，其中get_llm_answer(item->valuestring)函数用于获取自然语言模型的输出结果并打印。

#include <rtthread.h>
#include <sys/socket.h> 
#include <webclient.h>  
#include <dfs_posix.h>  
#include <cJSON.h>      /* 使用外设需要的头文件 */
#include <rtdevice.h>
#include <board.h>#define RES_BUFFER_SIZE     4096        //数据接收数组大小
#define HEADER_BUFFER_SIZE      2048    //最大支持的头部长度/* URL 请在**处自己填写主要参数cuid, token */
#define POST_FILE_URL  "http://vop.baidu.com/server_api?dev_pid=1537&cuid=**&token=**"
/*采样率与文件格式选择如下*/
char *form_data = "audio/pcm;rate=16000";
void baidu_voice_recignition()
{    char *filename = NULL;unsigned char *buffer = RT_NULL;int content_length = -1, bytes_read = 0;int content_pos = 0;int ret = 0;/* 获取pcm音频文件名 */filename = "file.pcm";/* 以只读方式打开音频文件 */int fd = open(filename, O_RDONLY, 0);if(fd < 0){rt_kprintf("open %d fail!\r\n", filename);goto __exit;}/* 获取pcm音频文件大小 */size_t length = lseek(fd, 0, SEEK_END);lseek(fd, 0, SEEK_SET);/* 创建响应数据接收数据 */buffer = (unsigned char *) web_malloc(RES_BUFFER_SIZE);if(buffer == RT_NULL){rt_kprintf("no memory for receive response buffer.\n");ret = -RT_ENOMEM;goto __exit;}/* 创建会话 */struct webclient_session *session = webclient_session_create(HEADER_BUFFER_SIZE);if(session == RT_NULL){ret = -RT_ENOMEM;goto __exit;}/* 拼接头部数据 */webclient_header_fields_add(session, "Content-Length: %d\r\n", length);webclient_header_fields_add(session, "Content-Type: %s\r\n", form_data);/* 发送POST请求 */int rc = webclient_post(session, POST_FILE_URL, NULL, 100);if(rc < 0){rt_kprintf("webclient post data error!\n");goto __exit;}else if (rc == 0){rt_kprintf("webclient connected !\n");}else{rt_kprintf("rc code: %d!\n", rc);}while(1){rt_memset(buffer, 0, RES_BUFFER_SIZE);length = read(fd, buffer, RES_BUFFER_SIZE);if(length <= 0){break;}ret = webclient_write(session, buffer, length);if(ret < 0){rt_kprintf("webclient write error!\r\n");break;}   rt_thread_mdelay(100);}close(fd);rt_kprintf("Please wait ... \r\n");if(webclient_handle_response(session) != 200){rt_kprintf("get handle resposne error!");goto __exit;}   /* 获取接收的响应数据长度 */content_length = webclient_content_length_get(session);rt_thread_delay(100);do{bytes_read = webclient_read(session, buffer, 1024);if (bytes_read <= 0){break;}for(int index = 0; index < bytes_read; index++){rt_kprintf("%c", buffer[index]);}content_pos += bytes_read;}while(content_pos < content_length);   /* 解析json数据 */bd_data_parse(buffer);__exit:if(fd >= 0)close(fd);if(session != NULL)webclient_close(session);if(buffer != NULL)web_free(buffer);return;
}/*JSON数据分析*/
void bd_data_parse(uint8_t *data)
{cJSON *root = RT_NULL, *object = RT_NULL, *item =RT_NULL;root = cJSON_Parse((const char *)data);if (!root){rt_kprintf("No memory for cJSON root!\n");return;}object = cJSON_GetObjectItem(root, "result");item = object->child;rt_kprintf("\nQuestion :%s \r\n", item->valuestring);/*获取自然语言模型输出结果并打印*/get_llm_answer(item->valuestring);if (root != RT_NULL)cJSON_Delete(root);
}/*导出指令，便于阶段性测试*/
MSH_CMD_EXPORT(baidu_voice_recignition, webclient post file);

（3）将识别内容上传至DeepSeek，并显示返回打印

        可以按照DeepSeek官方教程注册API_Key，但当前使用DeepSeekAPI可能会出现服务器崩溃，网络异常问题。因此建议使用火山引擎的DeepSeek模型。

创建API_Key

        创建API_Key后，在在线推理栏中接入Deep-Seek模型，一般新创建的账号会提供免费的使用次数。

        以上步骤Ok后，修改"llm_chat/ports/chat/port/chat_port.c"文件中的LLM_API_KEY ,LLM_API_URL, LLM_MODEL_NAME.

/** Copyright (c) 2006-2025, RT-Thread Development Team** SPDX-License-Identifier: MIT** Change Logs:* Date           Author       Notes* 2025/02/01     Rbb666       Add license info* 2025/02/03     Rbb666       Unified Adaptive Interface* 2025/02/06     Rbb666       Add http stream support*/
#include "llm.h"
#include "webclient.h"
#include <cJSON.h>#define LLM_API_KEY ""
#define LLM_API_URL ""#define LLM_MODEL_NAME ""
#define WEB_SOCKET_BUF_SIZE 80960static char authHeader[128] = {0};
static char responseBuffer[WEB_SOCKET_BUF_SIZE] = {0};
static char contentBuffer[WEB_SOCKET_BUF_SIZE] = {0};char *get_llm_answer(const char *inputText)
{struct webclient_session *webSession = NULL;char *allContent = NULL;int bytesRead, responseStatus;cJSON *responseRoot = NULL;// Create web sessionwebSession = webclient_session_create(WEB_SOCKET_BUF_SIZE);if (webSession == NULL){rt_kprintf("Failed to create webclient session.\n");goto cleanup;}// Create JSON payloadcJSON *requestRoot = cJSON_CreateObject();cJSON *model = cJSON_CreateString(LLM_MODEL_NAME);cJSON *messages = cJSON_CreateArray();cJSON *systemMessage = cJSON_CreateObject();cJSON *userMessage = cJSON_CreateObject();cJSON_AddItemToObject(requestRoot, "model", model);cJSON_AddItemToObject(requestRoot, "messages", messages);
// #ifdef PKG_LLMCHAT_STREAMcJSON_AddBoolToObject(requestRoot, "stream", RT_TRUE);
// #else// cJSON_AddBoolToObject(requestRoot, "stream", RT_FALSE);
// #endifcJSON_AddItemToArray(messages, systemMessage);cJSON_AddItemToArray(messages, userMessage);cJSON_AddStringToObject(systemMessage, "role", "system");cJSON_AddStringToObject(systemMessage, "content", "");cJSON_AddStringToObject(userMessage, "role", "user");cJSON_AddStringToObject(userMessage, "content", inputText);char *payload = cJSON_PrintUnformatted(requestRoot);if (payload == NULL){rt_kprintf("Failed to create JSON payload.\n");goto cleanup;}// Prepare authorization headerrt_snprintf(authHeader, sizeof(authHeader), "Authorization: Bearer %s\r\n", LLM_API_KEY);// Add headerswebclient_header_fields_add(webSession, "Content-Type: application/json\r\n");webclient_header_fields_add(webSession, authHeader);webclient_header_fields_add(webSession, "Content-Length: %d\r\n", rt_strlen(payload));// LLM_DBG("HTTP Header: %s\n", webSession->header->buffer);// LLM_DBG("HTTP Payload: %s\n", payload);// Send POST requestresponseStatus = webclient_post(webSession, LLM_API_URL, payload, rt_strlen(payload));if (responseStatus != 200){rt_kprintf("Webclient POST request failed, response status: %d\n", responseStatus);goto cleanup;}// Read and process responsewhile ((bytesRead = webclient_read(webSession, responseBuffer, WEB_SOCKET_BUF_SIZE)) > 0){// printf("bytesRead == %d\n", bytesRead);int inContent = 0;for (int i = 0; i < bytesRead; i++){if (inContent){if (responseBuffer[i] == '"'){inContent = 0;// Append content to allContentchar *oldAllContent = allContent;size_t oldLen = oldAllContent ? rt_strlen(oldAllContent) : 0;size_t newLen = rt_strlen(contentBuffer);size_t totalLen = oldLen + newLen + 1;char *newAllContent = (char *)web_malloc(totalLen);if (newAllContent){newAllContent[0] = '\0';if (oldAllContent){rt_strcpy(newAllContent, oldAllContent);}strcat(newAllContent, contentBuffer);allContent = newAllContent;for (int i = 0; contentBuffer[i] != '\0'; i++) {// 当遇到 \n 时，替换为换行符if (contentBuffer[i] == '\\' && contentBuffer[i + 1] == 'n') {rt_kprintf("\r\n");  // 输出真正的换行符i++;  // 跳过下一个字符 'n'} else {rt_kprintf("%c", contentBuffer[i]);}}rt_free(oldAllContent);}else{rt_kprintf("Memory allocation failed, content truncated!\n");}contentBuffer[0] = '\0'; // Reset content buffer}else{strncat(contentBuffer, &responseBuffer[i], 1);}}else if (responseBuffer[i] == '"' && i > 8 &&rt_strncmp(&responseBuffer[i - 10], "\"content\":\"", 10) == 0){inContent = 1;}}}rt_kprintf("\n");cleanup:// Cleanup resourcesif (webSession)webclient_close(webSession);if (requestRoot)cJSON_Delete(requestRoot);if (responseRoot)cJSON_Delete(responseRoot);if (payload)cJSON_free(payload);return allContent;
}

将之前的代码创建线程进行串联，请在合适位置执行voice_recignition（）初始化线程

#include <rtthread.h>
#include <rtdevice.h>
#include <board.h>
#include <dfs_posix.h>
#include <string.h>/* 函数声明 */    
extern int pcm_record();
extern void baidu_voice_recignition();/* 线程参数 */
#define THREAD_PRIORITY          25      //优先级
#define THREAD_STACK_SIZE        40096    //线程栈大小
#define THREAD_TIMESLICE         10      //时间片/* 线程句柄 */
static rt_thread_t tid1 = RT_NULL;
static rt_thread_t tid2 = RT_NULL;/* 指向信号量的指针 */
static rt_sem_t start_record_sem = RT_NULL;
static rt_sem_t voice_recignition_sem = RT_NULL;/* 录音线程入口函数 */
static void record_entry(void *parameter)
{static rt_err_t result;while(1){result = rt_sem_take(start_record_sem, RT_WAITING_FOREVER);if (result != RT_EOK){rt_kprintf("take a dynamic semaphore, failed.\n");rt_sem_delete(start_record_sem);return;}else{rt_kprintf("take a dynamic semaphore, successfully.creat pcm file\n");pcm_record();         //获取到信号量，开始录音，生成pcm文件rt_sem_release(voice_recignition_sem);  }rt_thread_mdelay(100);}        
}/* 语音识别线程入口函数 */
static void voice_recignition_entry(void *parameter)
{while (1){if (rt_sem_take(voice_recignition_sem, RT_WAITING_FOREVER) == RT_EOK){baidu_voice_recignition();       //收到邮件，进行语音识别rt_thread_mdelay(100);}}
}/* start_record 函数 */
static void start_record(void *parameter)
{rt_kprintf("release a start_record_sem semaphore.\n");rt_sem_release(start_record_sem);        
}MSH_CMD_EXPORT(start_record, record voice to a pcm file and uplode to deepseek);int voice_recignition(void)
{start_record_sem = rt_sem_create("start_record_sem", 0, RT_IPC_FLAG_FIFO);if (start_record_sem == RT_NULL){rt_kprintf("create dynamic semaphore failed.\n");return -1;}voice_recignition_sem = rt_sem_create("voice_recignition_sem", 0, RT_IPC_FLAG_FIFO);if (voice_recignition_sem == RT_NULL){rt_kprintf("create dynamic semaphore failed.\n");return -1;}/* 创建线程 */    tid1 = rt_thread_create("thread1",record_entry, RT_NULL,THREAD_STACK_SIZE,THREAD_PRIORITY, THREAD_TIMESLICE);if (tid1 != RT_NULL)rt_thread_startup(tid1);tid2 = rt_thread_create("thread2",voice_recignition_entry, RT_NULL,THREAD_STACK_SIZE,THREAD_PRIORITY, THREAD_TIMESLICE);if (tid2 != RT_NULL)rt_thread_startup(tid2);return 0;
}

 4. 结果展示

以下是语音交谈的结果

以下是直接键入汉字的交流结果

参考文章：

软件包应用分享|基于RT-Thread的百度语音识别（一）_wx60dac676d6910的技术博客_51CTO博客

Deepseek上单片机？RT-Thread上跑通大语言模型-电子发烧友网