Feat/sensor

app/controller/RecordController.py

@@ -1,16 +1,23 @@
 import os
+import subprocess
+import time
 from typing import List
 
 import requests
-from boto3 import client
+
 from fastapi import APIRouter, Request, UploadFile, File, Form
+from boto3 import client
+from pydub import AudioSegment
+from pydub.playback import play
+
+from app import s3Service
+from app.dto.BasicTTSRequestDto import BasicTTSRequestDto
+from app.dto.FirstTTSRequestDto import FirstTTSRequestDto
+from app.dto.ExtraTTSRequestDto import ExtraTTSRequestDto
 
-from app.dto.ScheduleSpeakRequestDto import ScheduleSpeakRequestDto
-from app.dto.ScheduleTTSRequestDto import ScheduleTTSRequestDto
-from app.service.elevenLabs import text_to_speech_file_save_AWS
-from app.service.gpt import ChatgptAPI
-from app.service.s3Service import download_from_s3
-from app.utils import play_file
+
+from app.elevenLabs import add_voice, text_to_speech_file_save_AWS, get_voice, delete_all_voice, text_to_speech_file
+from app.s3Service import download_from_s3_links, download_from_s3
 
 router = APIRouter(
     prefix="/api/fastapi",
@@ -30,18 +37,6 @@
 )
 
 
-async def save_local_file(file: UploadFile) -> str:
-    """하나의 파일을 로컬에 저장하고 경로를 반환합니다."""
-    audio_dir = "./audio"
-    if not os.path.exists(audio_dir):
-        os.makedirs(audio_dir)
-
-    local_file_path = os.path.join(audio_dir, file.filename)
-    with open(local_file_path, "wb") as f:
-        f.write(await file.read())
-    return local_file_path
-
-
 async def save_local_files(files: List[UploadFile]) -> list:
     """업로드된 파일을 로컬에 저장하고 파일 경로를 반환합니다."""
     audio_dir = "./audio"
@@ -56,76 +51,82 @@ async def save_local_files(files: List[UploadFile]) -> list:
     return local_file_path_list
 
 
-# 첫 로그인 시 목소리 녹음 api
+# 첫 로그인 시 1분 목소리 녹음 api
 @router.post("/voices")
-async def getVoice(request: Request, user_id: int = Form(...), file: UploadFile = File(...)):
-    token = request.headers.get("Authorization").split(" ")[1]
-    local_file_path = await save_local_file(file)
-    name = str(user_id)
-    # voice_id = add_voice(name=name, local_file_paths=[local_file_path])
-    print(name)
+async def getVoice(request: Request, files: List[UploadFile] = File(...)):
+    # token = request.headers.get("Authorization").split(" ")[1]
+    local_file_path_list = await save_local_files(files)
+    name = 'yjg'
+    voice_id = add_voice(name=name, local_file_paths=local_file_path_list)
+    print(voice_id)
     # voice_url = s3Service.upload_to_s3(local_file_path)
-    os.remove(local_file_path)
+    # os.remove(local_file_path)
 
-    send_user_voice_id_to_spring(token=token, voice_id=yjg_voice_id)
+    # send_user_voice_file_to_spring(token=token, voice_url=voice_url)
 
-
-@router.post("/schedules")
-async def schedule_tts(request: Request, schedules: ScheduleTTSRequestDto):
+@router.post("/save/basic-tts")
+async def save_S3_basic_tts(request: Request, firstTTSRequestDtoList: FirstTTSRequestDto):
     # token = request.headers.get("Authorization").split(" ")[1]
-    voice_id = schedules.voice_id
-
-    prompt = ChatgptAPI(schedules.schedule_text, schedules.alias)
-
-    # schedule_dict: {"저녁": "엄마~ 저녁 잘 챙겨 먹었어?", "운동": "오늘 운동했어? 건강 챙겨~!"}
-    schedule_dict = prompt.get_schedule_json()
+    # text가 어떤형식으로 올지 몰라서 일단 그대로 내보낸다고 가정 (변환시 지피티 사용)
 
     # TTS 처리 (MP3 파일 생성 후 s3 저장)
     response = {
-        schedules.schedule_id[i]: {
-            "keyword": schedules.schedule_text[i],  # 키워드 직접 저장
-            "text": schedule_dict.get(schedules.schedule_text[i], ""),  # 문장은 GPT 결과에서 매핑
-            "url": text_to_speech_file_save_AWS(
-                schedule_dict.get(schedules.schedule_text[i], ""),
-                yjg_voice_id
-            )
-        }
-        for i in range(len(schedules.schedule_id))
+        firstTTSRequestDtoList.basic_schedule_id[i]: text_to_speech_file_save_AWS(firstTTSRequestDtoList.basic_schedule_text[i],
+                                                                       yjg_voice_id)
+        for i in range(len(firstTTSRequestDtoList.basic_schedule_id))
     }
+
     return response
 
 
-@router.post("/schedules-speak")
-async def speak_schedule(request: Request, scheduleSpeakRequestDto: ScheduleSpeakRequestDto):
+@router.post("/basic-tts")
+async def speak_schedule_tts(request: Request, basicTTSRequestDto: BasicTTSRequestDto):
     # token = request.headers.get("Authorization").split(" ")[1]
-    local_file_path = download_from_s3(scheduleSpeakRequestDto.schedule_voice_Url)
+    local_file_path = download_from_s3(basicTTSRequestDto.schedule_voice_Url)
     print(f"Downloaded file path: {local_file_path}")
 
-    # target_time에 맞춰서 TTS 파일 재생
-    play_file.play_at_target_time(scheduleSpeakRequestDto.target_time, local_file_path)
+    # 블루투스 헤드셋 또는 기본 스피커로 출력
+    os.system("pactl list sinks | grep 'bluez_sink'")  # 블루투스 출력 장치 확인
+    os.system("pactl set-default-sink `pactl list sinks short | grep bluez_sink | awk '{print $2}'`")  # 기본 출력 변경
 
-    return {"message": "TTS completed and played on speaker"}
+    # 로컬 파일을 직접 재생
+    subprocess.run(["mpg321", local_file_path])
 
+    return {"message": "TTS completed and played on Bluetooth headset or speaker"}
 
-def send_user_voice_file_to_spring(token: str, voice_url: str):
-    headers = {
-        "Authorization": f"Bearer {token}"
-    }
-    data = {
-        "voiceUrl": voice_url
-    }
-    requests.post("http://localhost:8080/api/spring/records/voices", headers=headers, json=data)
-    # requests.post("https://peachmentor.com/api/spring/records/voices", headers=headers, json=data)
 
+@router.post("/extra-tts")
+async def speak_schedule_tts(request: Rlocalhostquest, extraTTSRequestDto: ExtraTTSRequestDto):
+    # token = request.headers.get("Authorization").split(" ")[1]
+    schedule_text = extraTTSRequestDto.schedule_text
+
+    #진짜 실제로 쓸 코드
+    local_file_path = text_to_speech_file(schedule_text, yjg_voice_id)
+
+    # 테스트하면서 AWS에 올려놓으려고 남긴 코드
+    url = text_to_speech_file_save_AWS(schedule_text, yjg_voice_id)
+    local_file_path = download_from_s3(url)
+
+    # local_file_path = os.getcwd()+"/test_audio/test8.mp3" # test
+    # 블루투스 헤드셋 또는 기본 스피커로 출력
+    os.system("pactl list sinks | grep 'bluez_sink'")  # 블루투스 출력 장치 확인
+    os.system("pactl set-default-sink `pactl list sinks short | grep bluez_sink | awk '{print $2}'`")  # 기본 출력 변경
 
-def send_user_voice_id_to_spring(token: str, voice_id: str):
+    # 로컬 파일을 직접 재생
+    subprocess.run(["/usr/bin/mpg321", local_file_path])
+    # subprocess.run(["ffplay", "-nodisp", "-autoexit", local_file_path],
+    #                stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL) # 윈도우용
+    return {"message": "TTS completed and played on Bluetooth headset or speaker"}
+
+
+def send_user_voice_file_to_spring(token: str, voice_url: str):
     headers = {
         "Authorization": f"Bearer {token}"
     }
     data = {
-        "voiceId": voice_id
+        "voiceUrl": voice_url
     }
-    requests.post("http://localhost:8080/api/spring/records/voices", headers=headers, json=data)
+    requests.post("http://springboot:8080/api/spring/records/voices", headers=headers, json=data)
     # requests.post("https://peachmentor.com/api/spring/records/voices", headers=headers, json=data)
 
 
@@ -137,15 +138,15 @@ def send_user_speech_file_to_spring(token: str, before_audio_link: str, answerId
         "beforeAudioLink": before_audio_link,
         "answerId": answerId
     }
-    requests.post("http://localhost:8080/api/spring/records/speeches", headers=headers, json=data)
+    requests.post("http://springboot:8080/api/spring/records/speeches", headers=headers, json=data)
     # requests.post("https://peachmentor.com/api/spring/records/speeches", headers=headers, json=data)
 
 
 def receive_self_feedback(token: str) -> str:
     headers = {
         "Authorization": f"Bearer {token}"
     }
-    response = requests.get("http://localhost:8080/api/spring/self-feedbacks/latest-feedbacks", headers=headers)
+    response = requests.get("http://springboot:8080/api/spring/self-feedbacks/latest-feedbacks", headers=headers)
     # response = requests.get("https://peachmentor.com/api/spring/self-feedbacks/latest-feedbacks", headers=headers)
 
     feedback_data = response.json().get('result', {})
@@ -165,7 +166,7 @@ def send_statistics_to_spring(token: str, gantourCount: int, silentTime: float,
         "silentTime": silentTime,
         "answerId": answerId
     }
-    requests.post("http://localhost:8080/api/spring/statistics", headers=headers, json=data)
+    requests.post("http://springboot:8080/api/spring/statistics", headers=headers, json=data)
     # requests.post("https://peachmentor.com/api/spring/statistics", headers=headers, json=data)
 
 # # 질문 답변에 대한 insight 제공 api
@@ -232,4 +233,4 @@ def send_statistics_to_spring(token: str, gantourCount: int, silentTime: float,
 #     analysis_gpt = AnalysisAssistant(questions=analysisRequestDto.questions, beforeScripts=analysisRequestDto.beforeScripts)
 #     analysis = analysis_gpt.get_analysis()
 #
-#     return {"analysisText": analysis}  # 데이터를 JSON 객체로 감쌈
+#     return {"analysisText": analysis}  # 데이터를 JSON 객체로 감쌈

main.py

@@ -1,11 +1,71 @@
+import RPi.GPIO as GPIO
 import time
+from datetime import datetime
 
-import uvicorn
+# ───────────────────────────────
+# PIR 센서 관련
+# ───────────────────────────────
+PIR_PIN = 17  # GPIO17
 
+def detect_motion():
+    GPIO.setmode(GPIO.BCM)
+    GPIO.setup(PIR_PIN, GPIO.IN)
+
+    print("PIR 센서 디버깅 시작 (Ctrl+C 종료)")
+    prev_state = None
+
+    try:
+        while True:
+            signal = GPIO.input(PIR_PIN)
+
+            if signal != prev_state:
+                timestamp = datetime.now().strftime("%H:%M:%S")
+                state_str = "감지됨 (HIGH)" if signal else " 없음 (LOW)"
+                print(f"[{timestamp}] 상태 변경 ▶ {state_str}")
+                prev_state = signal
+
+            time.sleep(0.1)
+    except KeyboardInterrupt:
+        print("⛔ 종료 중...")
+        GPIO.cleanup()
+
+
+# ───────────────────────────────
+# DHT11 센서 관련 (5회 재시도 버전)
+# ───────────────────────────────
+import adafruit_dht
+import board
+
+def read_dht11():
+    print("🌡️ DHT11 센서 측정 시작...")
+    dhtDevice = adafruit_dht.DHT11(board.D4)  # GPIO4 (멀티보드 IO4)
+
+    for i in range(5):  # 최대 5번 재시도
+        try:
+            print(f"📡 시도 {i + 1} ...")
+            temperature = dhtDevice.temperature
+            humidity = dhtDevice.humidity
+
+            if temperature is not None and humidity is not None:
+                print(f"✅ 온도: {temperature}°C")
+                print(f"✅ 습도: {humidity}%")
+                break
+            else:
+                print("⚠️ 센서로부터 데이터를 읽을 수 없습니다.")
+        except RuntimeError as error:
+            print(f"⚠️ 에러 발생: {error.args[0]}")
+        except Exception as error:
+            print(f"❌ 심각한 오류: {error}")
+            break
+        time.sleep(2)  # 재시도 간 간격
+
+    # 종료 함수는 비활성화 (라이브러리 오류 방지)
+    # dhtDevice.exit()
+
+
+# ───────────────────────────────
+# 메인 함수
+# ───────────────────────────────
 if __name__ == "__main__":
-    uvicorn.run(
-        app="app.main:app",
-        host="localhost",
-        # host="0.0.0.0",
-        port=8000,
-    )
+    # detect_motion()  # PIR 센서 테스트 시 주석 해제
+    read_dht11()        # 현재는 DHT11만 테스트