fix: cannot login with default password
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@@ -30,6 +30,27 @@ class AIAnalysisRequest(BaseModel):
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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(...)):
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ext = os.path.splitext(file.filename)[1]
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@@ -172,3 +193,116 @@ async def export_audio(req: ExportRequest):
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"task_id": task.id,
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"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):
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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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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 = None
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if req.file_id:
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upload_path = os.path.join(settings.UPLOADS_DIR, req.file_id)
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processed_path = os.path.join(settings.PROCESSED_DIR, req.file_id)
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if os.path.exists(processed_path):
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file_path = processed_path
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elif os.path.exists(upload_path):
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file_path = upload_path
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if file_path and os.path.exists(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):
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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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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"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 = None
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if req.file_id:
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upload_path = os.path.join(settings.UPLOADS_DIR, req.file_id)
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processed_path = os.path.join(settings.PROCESSED_DIR, req.file_id)
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if os.path.exists(processed_path):
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file_path = processed_path
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elif os.path.exists(upload_path):
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file_path = upload_path
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if file_path and os.path.exists(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):
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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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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"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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