玩转DFRobot ESP32-P4开发板，用Micropython仿制小智
本帖最后由 PY学习笔记 于 2025-8-25 17:07 编辑近期，DFRobot 推出了全新开发板 FireBeetle 2 ESP32-P4。这块开发板搭载了 ESP32-P4 主控，虽未集成 Wi-Fi 与蓝牙，但凭借强劲性能，依然令人眼前一亮。很荣幸能抢先体验这块开发板！1.开发板介绍FireBeetle 2 ESP32-P4有很多种外设:
[*]Type-C USB CDC：Type-C USB烧录、调试接口
[*]IO3/LED：板载LED引脚
[*]Power LED：主板电源指示灯
[*]RST：复位按键
[*]IO35/BOOT：IO引脚/BOOT按键
[*]MIC: MEMS PDM麦克风
[*]HIGH-SPEED USB OTG 2.0: Type-C高速USB OTG 2.0
[*]ESP32-P4：ESP32-P4芯片
[*]MIPI-DSI: 两通道MIPI-DSI屏幕（兼容树莓派4B DSI屏幕线序）
[*]MIPI-CSI: 两通道MIPI-DSI屏幕（兼容树莓派4B CSI摄像头线序）
[*]TF Card: TF卡插槽
[*]16MB FLASH: 16MB Flash存储
[*]ESP32-C6：ESP32-C6-MINI-1模组，通过SDIO与ESP32-P4连接，用于扩展WiFi、蓝牙
2.实现原理由于MicroPython不支持离线语音识别与合成，所以采用在线语音识别和在线语音合成，AI也是采用在线的方式，在线语音识别和AI大模型均使用siliconflow的免费模型，而在线语音合成使用了百度的语音合成（实名认证后免费5万次），再结合ST7789屏幕（使用MIPI屏幕会出问题），MAX9835功放模块，以及板载的PDM麦克风即可实现。3.代码实现参考代码如下：# 录音+语音识别+AI对话+语音合成的完整闭环
import network, urequests, ujson, gc, time, st7789_spi, baidu_tts
from easydisplay import EasyDisplay
from machine import Pin, I2S, SPI
# ---------- 全局配置 ----------
WIFI_SSID = "SSID"
WIFI_PASS = "PWD"
API_KEY = "API-KEY"
TTS_API_KEY = "API-KEY"
TTS_SEC_KEY = "SEC-KEY"
ASR_URL = "https://api.siliconflow.cn/v1/audio/transcriptions"
CHAT_URL= "https://api.siliconflow.cn/v1/chat/completions"
ASR_MODEL = "FunAudioLLM/SenseVoiceSmall"
LLM_MODEL = "Qwen/Qwen3-8B"
# I2S 引脚
SCK_PIN = 12
SD_PIN= 9
boot = Pin(35, Pin.IN, Pin.PULL_UP) # BOOT 键，按下为 0
led = Pin(3,Pin.OUT)
spi = SPI(2, baudrate=20000000, polarity=0, phase=0, sck=Pin(28), mosi=Pin(29))
dp = st7789_spi.ST7789(width=240, height=280, spi=spi, cs=20, dc=4, res=30, rotate=1,invert=False, rgb=False)
ed = EasyDisplay(dp, "RGB565", font="/text_lite_16px_2312.v3.bmf", show=True, color=0xFFFF, clear=True,auto_wrap=True)
# ---------- 联网 ----------
def connect_wifi():
sta = network.WLAN(network.STA_IF)
sta.active(True)
sta.connect(WIFI_SSID, WIFI_PASS)
while not sta.isconnected():
time.sleep(0.5)
print("Wi-Fi OK:", sta.ifconfig())
return sta
def record_audio(sr=8000):
# 等待按下
print("长按 BOOT 开始录音...")
while boot.value() == 1:
time.sleep_ms(10)
# 开始录音
pcm = bytearray()
audio = I2S(0,
sck=Pin(SCK_PIN),
sd=Pin(SD_PIN),
mode=I2S.PDM_RX,
bits=16,
format=I2S.MONO,
rate=sr * 4,
ibuf=10240)
# 边录边检查按键
chunk = bytearray(1024)
print("录音中，松开 BOOT 结束...")
while boot.value() == 0: # 0 表示仍按着
n = audio.readinto(chunk)
pcm.extend(chunk[:n])
audio.deinit()
return pcm, sr
# ---------- 构造 WAV ----------
def wav_header(data_len, sample_rate):
hdr = bytearray(44)
hdr = b'RIFF'
hdr = (data_len + 36).to_bytes(4, 'little')
hdr= b'WAVE'
hdr = b'fmt '
hdr = (16).to_bytes(4, 'little')
hdr = (1).to_bytes(2, 'little') # PCM
hdr = (1).to_bytes(2, 'little') # mono
hdr = sample_rate.to_bytes(4, 'little')
hdr = (sample_rate * 2).to_bytes(4, 'little')
hdr = (2).to_bytes(2, 'little') # block align
hdr = (16).to_bytes(2, 'little') # bits per sample
hdr = b'data'
hdr = data_len.to_bytes(4, 'little')
return hdr
# ---------- 语音识别 ----------
def speech_to_text(pcm, sr):
wav = wav_header(len(pcm), sr) + pcm
boundary = "----VoiceBoundary"
body= b"--" + boundary.encode() + b"\r\n"
body += b'Content-Disposition: form-data; name="file"; filename="mic.wav"\r\n'
body += b"Content-Type: audio/wav\r\n\r\n"
body += wav
body += b"\r\n--" + boundary.encode() + b"\r\n"
body += b'Content-Disposition: form-data; name="model"\r\n\r\n'
body += ASR_MODEL.encode()
body += b"\r\n--" + boundary.encode() + b"--\r\n"
headers = {
"Authorization": "Bearer " + API_KEY,
"Content-Type": "multipart/form-data; boundary=" + boundary
}
print("识别中…")
res = urequests.post(ASR_URL, data=body, headers=headers)
text = res.json().get("text", "").strip()
res.close()
gc.collect()
return text
# ---------- 对话 ----------
def chat_with_ai(text):
headers = {
"Authorization": "Bearer " + API_KEY,
"Content-Type": "application/json"
}
payload = {
"model": LLM_MODEL,
"messages": [
{"role": "system", "content": "你是我的AI助手小智，你必须用中文回答且不超过100字还不允许使用MD进行回答"},
{"role": "user", "content": text}
],
"enable_thinking":False,
}
print("AI思考中…")
start = time.time()
res = urequests.post(CHAT_URL, data=ujson.dumps(payload).encode(), headers=headers)
delta = time.time() - start
if res.status_code == 200:
reply = res.json()['choices']['message']['content'].replace("\n", "")
print(f"({delta:.1f}s) AI:", reply)
ed.text(f"({delta:.1f}s) AI:"+reply, 0, 50)
baidu_tts.run(
access=TTS_API_KEY,
secret=TTS_SEC_KEY,
text=reply,
)
else:
print("Error:", res.status_code, res.text)
reply = ""
res.close()
gc.collect()
return reply
# ---------- 主循环 ----------
def main():
connect_wifi()
while True:
pcm, sr = record_audio()
text = speech_to_text(pcm, sr)
if not text:
print("没听清，请再说一遍")
baidu_tts.run(
access=TTS_API_KEY,
secret=TTS_SEC_KEY,
text="没听清，请再说一遍",
out_path='welcome.wav'
)
continue
elif "开灯" in text:
print("你:", text)
led.on()
print("AI:LED灯已开启")
ed.text("AI:LED灯已开启", 0, 50)
baidu_tts.run(
access=TTS_API_KEY,
secret=TTS_SEC_KEY,
text="LED灯已开启",
)
elif "关灯" in text:
print("你:", text)
led.off()
print("AI:LED灯已关闭")
ed.text("AI:LED灯已关闭", 0, 50)
baidu_tts.run(
access=TTS_API_KEY,
secret=TTS_SEC_KEY,
text="LED灯已关闭",
)
else:
print("你:", text)
chat_with_ai(text)
if __name__ == "__main__":
main()
4.效果
https://www.bilibili.com/video/BV1SyeRz6E5D/
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