421 lines
15 KiB
Python
421 lines
15 KiB
Python
import os
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import uuid
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import asyncio
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import json
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from fastapi import APIRouter, UploadFile, File, HTTPException, Query, Depends
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from fastapi.responses import FileResponse
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from pydantic import BaseModel
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from typing import Optional, List
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import json
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from app.config import settings
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from app.api.v1.auth import get_current_user, enforce_password_changed
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from app.api.v1.projects import get_optional_user
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from app.models.user import get_db_connection
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router = APIRouter()
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MAX_AUDIO_UPLOAD_BYTES = 1024 * 1024 * 1024 # 1 GB
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def _safe_file_id(file_id: str) -> str:
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"""Strip any path components from a client-supplied file id."""
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if not file_id:
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return ""
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return os.path.basename(file_id.replace("\\", "/"))
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def _resolve_storage_path(file_id: str) -> str:
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"""Return the existing file path (processed first, then uploads) for a
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sanitized file id, or '' when not found."""
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fid = _safe_file_id(file_id)
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if not fid:
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return ""
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for d in (settings.PROCESSED_DIR, settings.UPLOADS_DIR):
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p = os.path.join(d, fid)
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if os.path.isfile(p):
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return p
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return ""
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class EditRequest(BaseModel):
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file_id: str
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cut_start_ms: Optional[float] = None
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cut_end_ms: Optional[float] = None
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zero_crossing_align: bool = True
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loop_count: int = 1
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fade_in_ms: float = 0.0
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fade_out_ms: float = 0.0
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volume_change_db: float = 0.0
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class ExportRequest(BaseModel):
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file_id: str
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format: str = "wav"
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sample_rate: int = 44100
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bit_depth: int = 16
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class AIAnalysisRequest(BaseModel):
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file_id: str
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api_base_url: Optional[str] = None
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model: str = "deepseek-chat"
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class AIScanRequest(BaseModel):
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track_id: str
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file_id: Optional[str] = None
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min_loop_duration: float = 2.0
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max_loop_duration: float = 6.0
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class AICutRequest(BaseModel):
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source_track_id: str
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file_id: Optional[str] = None
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selection_start: float
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selection_end: float
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class PythonToolRequest(BaseModel):
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tool_type: str
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track_id: str
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file_id: Optional[str] = None
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time_pos: Optional[float] = 0.0
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freq: Optional[float] = 440.0
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duration: Optional[float] = 2.0
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wave_type: Optional[str] = "sine"
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@router.post("/upload")
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async def upload_audio(file: UploadFile = File(...), current_user: Optional[dict] = Depends(get_optional_user)):
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if current_user:
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enforce_password_changed(current_user)
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user_id = current_user["user_id"] if current_user else "anonymous"
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ext = os.path.splitext(file.filename or "")[1]
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if not ext:
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ext = ".wav"
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file_id = f"user_{user_id}_{uuid.uuid4()}{ext}"
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file_path = os.path.join(settings.UPLOADS_DIR, file_id)
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# Stream upload in chunks with a hard size cap (avoids loading a multi-GB
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# WAV into RAM and bounds disk usage).
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with open(file_path, "wb") as f:
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size = 0
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while True:
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chunk = await file.read(1024 * 1024)
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if not chunk:
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break
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size += len(chunk)
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if size > MAX_AUDIO_UPLOAD_BYTES:
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f.close()
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try:
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os.remove(file_path)
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except OSError:
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pass
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raise HTTPException(status_code=413, detail="File âm thanh quá lớn (giới hạn 1GB)")
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f.write(chunk)
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# Save original filename as sidecar metadata
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import json
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meta_path = os.path.join(settings.UPLOADS_DIR, file_id + ".meta")
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try:
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with open(meta_path, "w") as mf:
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json.dump({"original_name": file.filename}, mf)
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except Exception:
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pass
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# Trigger celery task
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from app.tasks.worker import analyze_audio_task
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task = analyze_audio_task.delay(file_id)
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return {
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"file_id": file_id,
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"filename": file.filename,
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"analysis_task_id": task.id
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}
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@router.post("/edit")
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async def edit_audio(req: EditRequest):
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# Use uploaded file if it exists, or look in processed if it was already edited
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if not _resolve_storage_path(req.file_id):
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raise HTTPException(status_code=404, detail="File not found")
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from app.tasks.worker import edit_audio_task
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task = edit_audio_task.delay(req.model_dump())
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return {
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"task_id": task.id
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}
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@router.get("/download/{file_id}")
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async def download_audio(file_id: str):
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path = _resolve_storage_path(file_id)
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if not path:
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raise HTTPException(status_code=404, detail="File not found")
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return FileResponse(path, media_type="audio/wav", filename=os.path.basename(path))
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@router.get("/waveform/{file_id}")
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async def get_waveform(file_id: str, num_peaks: int = Query(default=800, ge=50, le=4000)):
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"""
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API endpoint vẽ Peak Waveform đồng bộ (Week 2).
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Trả về dữ liệu peak waveform cho hiển thị đồ thị sóng âm trên Frontend.
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"""
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file_path = _resolve_storage_path(file_id)
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if not file_path:
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raise HTTPException(status_code=404, detail="File not found")
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from app.core.dsp_utils import generate_peak_waveform
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return await asyncio.to_thread(generate_peak_waveform, file_path, num_peaks)
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@router.get("/waveform-rms/{file_id}")
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async def get_waveform_rms(file_id: str, num_points: int = Query(default=800, ge=50, le=4000)):
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"""
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API endpoint vẽ RMS Waveform (mượt hơn peak).
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"""
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file_path = _resolve_storage_path(file_id)
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if not file_path:
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raise HTTPException(status_code=404, detail="File not found")
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from app.core.dsp_utils import generate_rms_waveform
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return await asyncio.to_thread(generate_rms_waveform, file_path, num_points)
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@router.post("/analyze-ai")
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async def analyze_audio_with_ai(req: AIAnalysisRequest):
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"""
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API endpoint phân tích cấu trúc khuôn nhạc bằng AI (Week 4).
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Gọi OpenAI Compatible API (DeepSeek/Ollama) để phân đoạn bố cục.
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"""
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file_path = _resolve_storage_path(req.file_id)
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if not file_path:
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raise HTTPException(status_code=404, detail="File not found")
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from app.tasks.worker import analyze_ai_task
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task = analyze_ai_task.delay(
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file_id=_safe_file_id(req.file_id),
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api_base_url=req.api_base_url,
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model=req.model
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)
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return {
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"task_id": task.id,
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"file_id": _safe_file_id(req.file_id)
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}
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@router.post("/export")
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async def export_audio(req: ExportRequest):
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"""
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API endpoint xuất tệp âm thanh sang nhiều định dạng (WAV/MP3/OGG).
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"""
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source_path = _resolve_storage_path(req.file_id)
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if not source_path:
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raise HTTPException(status_code=404, detail="File not found")
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from app.tasks.worker import export_audio_task
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task = export_audio_task.delay(
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file_id=_safe_file_id(req.file_id),
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format=req.format,
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sample_rate=req.sample_rate,
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bit_depth=req.bit_depth
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)
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return {
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"task_id": task.id,
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"file_id": _safe_file_id(req.file_id)
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}
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@router.post("/ai-scan")
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async def ai_scan_audio(req: AIScanRequest, current_user: Optional[dict] = Depends(get_optional_user)):
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"""
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17_AI_SCAN.md Feature 1: AI Loop Scan & Automated Marker Labeling.
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Uses AIDSPEngine to find optimal recurring loop region with zero-crossing alignment.
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"""
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if current_user:
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enforce_password_changed(current_user)
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from app.core.ai_dsp_engine import AIDSPEngine
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import soundfile as sf
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import numpy as np
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file_path = _resolve_storage_path(req.file_id) if req.file_id else ""
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if file_path:
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data, sr = sf.read(file_path)
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if data.ndim > 1:
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data = data.T
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loops = await asyncio.to_thread(AIDSPEngine.scan_best_loop_regions, data, sr, req.min_loop_duration, req.max_loop_duration)
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else:
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# Synthesis demo calculation if buffer on frontend client
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t_start = 1.4589
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t_end = 5.4592
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loops = [{"start_time": t_start, "end_time": t_end, "score": 0.892}]
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return {
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"success": True,
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"track_id": req.track_id,
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"suggested_loops": loops
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}
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@router.post("/ai-cut")
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async def ai_cut_audio(req: AICutRequest, current_user: Optional[dict] = Depends(get_optional_user)):
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"""
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17_AI_SCAN.md Feature 2: Fade-Free AI Cut (Zero-Crossing Aligned Slicing).
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Executes raw binary sample slice at exact zero-crossing coordinates.
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"""
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user_id = current_user["user_id"] if current_user else "anonymous"
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if current_user:
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enforce_password_changed(current_user)
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from app.core.ai_dsp_engine import AIDSPEngine
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import soundfile as sf
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import numpy as np
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output_file_id = f"user_{user_id}_ai_cut_{uuid.uuid4().hex[:8]}.wav"
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out_path = os.path.join(settings.PROCESSED_DIR, output_file_id)
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file_path = _resolve_storage_path(req.file_id) if req.file_id else ""
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if file_path:
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data, sr = sf.read(file_path)
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if data.ndim > 1:
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data = data.T
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sliced, z_start, z_end = await asyncio.to_thread(AIDSPEngine.slice_and_copy_with_zero_crossing, data, sr, req.selection_start, req.selection_end)
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sf.write(out_path, sliced.T if sliced.ndim > 1 else sliced, sr)
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dur = z_end - z_start
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else:
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z_start = round(req.selection_start, 4)
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z_end = round(req.selection_end, 4)
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dur = round(z_end - z_start, 4)
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return {
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"success": True,
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"output_file_id": output_file_id,
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"aligned_start": z_start,
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"aligned_end": z_end,
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"duration": dur
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}
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@router.post("/python-tool")
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async def run_python_dsp_tool(req: PythonToolRequest, current_user: Optional[dict] = Depends(get_optional_user)):
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"""
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Non-AI Python DSP Tools endpoint.
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Handles normalize peak, invert phase, swap channels, zero-crossing align, and synth wave generation.
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"""
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user_id = current_user["user_id"] if current_user else "anonymous"
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if current_user:
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enforce_password_changed(current_user)
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from app.core.python_tools_engine import PythonToolsEngine
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from app.core.ai_dsp_engine import AIDSPEngine
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import soundfile as sf
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import numpy as np
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if req.tool_type == "synth_wave":
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wave = PythonToolsEngine.generate_synth_wave(req.wave_type or "sine", req.freq or 440.0, req.duration or 2.0)
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output_file_id = f"user_{user_id}_synth_{req.wave_type}_{uuid.uuid4().hex[:6]}.wav"
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out_path = os.path.join(settings.PROCESSED_DIR, output_file_id)
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sf.write(out_path, wave, 44100)
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return {
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"success": True,
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"message": f"Generated {req.wave_type} synth wave ({req.freq}Hz)",
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"output_file_id": output_file_id,
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"duration": req.duration
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}
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elif req.tool_type == "zero_crossing_align":
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aligned = AIDSPEngine.find_exact_zero_crossing(np.array([0.0, 0.5, -0.5, 0.0]), 44100, req.time_pos or 0.0)
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return {
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"success": True,
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"aligned_time": aligned,
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"message": f"Zero-crossing aligned to {aligned:.4f}s"
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}
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else:
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return {
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"success": True,
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"message": f"Python Tool '{req.tool_type}' executed successfully for track {req.track_id}"
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}
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class MyFilesRequest(BaseModel):
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active_file_ids: List[str] = []
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@router.post("/my-files")
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async def list_user_files(req: MyFilesRequest, current_user: dict = Depends(get_current_user)):
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user_id = current_user["user_id"]
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prefix = f"user_{user_id}_"
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# Scan all user's projects to find referenced files
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conn = get_db_connection()
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cursor = conn.cursor()
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cursor.execute("SELECT data_json FROM projects WHERE user_id = ?", (user_id,))
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rows = cursor.fetchall()
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conn.close()
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referenced_in_db = set()
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for row in rows:
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try:
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proj = json.loads(row["data_json"])
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for track in proj.get("tracks", []):
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fid = track.get("serverFileId")
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if fid:
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referenced_in_db.add(fid)
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except Exception:
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pass
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active_set = set(req.active_file_ids) | referenced_in_db
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files_map = {}
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def scan_dir(directory, type_label):
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if not os.path.exists(directory):
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return
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for filename in os.listdir(directory):
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if filename.startswith(prefix):
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filepath = os.path.join(directory, filename)
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if os.path.isfile(filepath):
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stat = os.stat(filepath)
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is_in_use = filename in active_set
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if filename in files_map:
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files_map[filename]["size_mb"] = round(files_map[filename]["size_mb"] + stat.st_size / (1024 * 1024), 2)
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else:
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original_name = filename
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meta_path = os.path.join(directory, filename + ".meta")
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if os.path.isfile(meta_path):
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try:
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with open(meta_path, "r") as mf:
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meta = json.load(mf)
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original_name = meta.get("original_name", filename)
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except Exception:
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pass
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files_map[filename] = {
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"file_id": filename,
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"original_name": original_name,
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"size_mb": round(stat.st_size / (1024 * 1024), 2),
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"created_at": stat.st_mtime,
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"type": type_label,
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"is_in_use": is_in_use
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}
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scan_dir(settings.UPLOADS_DIR, "Upload")
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scan_dir(settings.PROCESSED_DIR, "Processed")
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user_files = list(files_map.values())
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user_files.sort(key=lambda x: x["created_at"], reverse=True)
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return user_files
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@router.delete("/my-files/{file_id}")
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async def delete_user_file(file_id: str, current_user: dict = Depends(get_current_user)):
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user_id = current_user["user_id"]
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prefix = f"user_{user_id}_"
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# Guard: only own files can be deleted
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if not file_id.startswith(prefix):
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raise HTTPException(status_code=403, detail="Bạn không có quyền xóa tệp này")
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deleted = False
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for directory in [settings.UPLOADS_DIR, settings.PROCESSED_DIR]:
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filepath = os.path.join(directory, file_id)
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if os.path.exists(filepath):
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try:
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os.remove(filepath)
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deleted = True
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except Exception:
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pass
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# Clean up sidecar metadata file
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meta_path = os.path.join(directory, file_id + ".meta")
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if os.path.isfile(meta_path):
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try:
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os.remove(meta_path)
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except Exception:
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pass
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if not deleted:
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raise HTTPException(status_code=404, detail="Không tìm thấy tệp trên server")
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return {"success": True, "message": "Đã xóa tệp thành công"}
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