import os # ---- Space mode gating (place above any JAX import!) ---- SPACE_MODE = os.getenv("SPACE_MODE") if SPACE_MODE is None: try: import jax SPACE_MODE = "serve" if any(getattr(d, "platform", "") in ("gpu","cuda","rocm") for d in jax.devices()) else "template" except Exception: SPACE_MODE = "template" if SPACE_MODE != "serve": # In template mode, force JAX to CPU so it won't try to load CUDA plugins os.environ.setdefault("JAX_PLATFORMS", "cpu") else: # Only set GPU-friendly XLA flags when we actually intend to serve on GPU os.environ.setdefault( "XLA_FLAGS", " ".join([ "--xla_gpu_enable_triton_gemm=true", "--xla_gpu_enable_latency_hiding_scheduler=true", "--xla_gpu_autotune_level=2", ]) ) # Optional: persist JAX compile cache across restarts (reduces warmup time) os.environ.setdefault("JAX_CACHE_DIR", "/home/appuser/.cache/jax") import jax # ✅ Valid choices include: "default", "high", "highest", "tensorfloat32", "float32", etc. # TF32 is the sweet spot on Ampere/Ada GPUs for ~1.1–1.3× matmul speedups. try: jax.config.update("jax_default_matmul_precision", "tensorfloat32") except Exception: jax.config.update("jax_default_matmul_precision", "high") # older alias # Initialize the on-disk compilation cache (best-effort) try: from jax.experimental.compilation_cache import compilation_cache as cc cc.initialize_cache(os.environ["JAX_CACHE_DIR"]) except Exception: pass # -------------------------------------------------------------------- from magenta_rt import system, audio as au import numpy as np from fastapi import FastAPI, UploadFile, File, Form, Body, HTTPException, Response, Request, WebSocket, WebSocketDisconnect, Query from fastapi.responses import JSONResponse, FileResponse, HTMLResponse import tempfile, io, base64, math, threading from fastapi.middleware.cors import CORSMiddleware from contextlib import contextmanager import soundfile as sf from math import gcd from scipy.signal import resample_poly from utils import ( match_loudness_to_reference, stitch_generated, hard_trim_seconds, apply_micro_fades, make_bar_aligned_context, take_bar_aligned_tail, resample_and_snap, wav_bytes_base64 ) from jam_worker import JamWorker, JamParams, JamChunk from one_shot_generation import generate_loop_continuation_with_mrt, generate_style_only_with_mrt import uuid, threading import logging import gradio as gr from typing import Optional, Union, Literal import json, asyncio, base64 import time from starlette.websockets import WebSocketState try: from uvicorn.protocols.utils import ClientDisconnected # uvicorn >= 0.20 except Exception: class ClientDisconnected(Exception): # fallback pass import re, tarfile from pathlib import Path from huggingface_hub import snapshot_download, HfApi from pydantic import BaseModel from model_management import CheckpointManager, AssetManager, ModelSelector, ModelSelect def _gpu_probe() -> dict: """ Returns: { "ok": bool, "backend": str | None, # "gpu" | "cpu" | "tpu" | None "has_gpu": bool, "devices": list[str], # e.g. ["gpu:0", "gpu:1"] "error": str | None, } """ try: import jax try: backend = jax.default_backend() # "gpu", "cpu", "tpu" except Exception: from jax.lib import xla_bridge backend = getattr(xla_bridge.get_backend(), "platform", None) try: devices = jax.devices() has_gpu = any(getattr(d, "platform", "") in ("gpu", "cuda", "rocm") for d in devices) dev_list = [f"{getattr(d, 'platform', '?')}:{getattr(d, 'id', '?')}" for d in devices] return {"ok": True, "backend": backend, "has_gpu": has_gpu, "devices": dev_list, "error": None} except Exception as e: return {"ok": False, "backend": backend, "has_gpu": False, "devices": [], "error": f"jax.devices failed: {e}"} except Exception as e: return {"ok": False, "backend": None, "has_gpu": False, "devices": [], "error": f"jax import failed: {e}"} # ---- Finetune assets (mean & centroids) -------------------------------------- # _FINETUNE_REPO_DEFAULT = os.getenv("MRT_ASSETS_REPO", "thepatch/magenta-ft") _ASSETS_REPO_ID: str | None = None _MEAN_EMBED: np.ndarray | None = None # shape (D,) dtype float32 _CENTROIDS: np.ndarray | None = None # shape (K, D) dtype float32 # _STEP_RE = re.compile(r"(?:^|/)checkpoint_(\d+)(?:/|\.tar\.gz|\.tgz)?$") # Create instances (these don't modify globals) asset_manager = AssetManager() model_selector = ModelSelector(CheckpointManager(), asset_manager) def _sync_assets_globals_from_manager(): # Keeps /model/config in sync with what the asset manager has global _MEAN_EMBED, _CENTROIDS, _ASSETS_REPO_ID _MEAN_EMBED = asset_manager.mean_embed _CENTROIDS = asset_manager.centroids _ASSETS_REPO_ID = asset_manager.assets_repo_id def _any_jam_running() -> bool: with jam_lock: return any(w.is_alive() for w in jam_registry.values()) def _stop_all_jams(timeout: float = 5.0): with jam_lock: for sid, w in list(jam_registry.items()): if w.is_alive(): w.stop() w.join(timeout=timeout) jam_registry.pop(sid, None) async def send_json_safe(ws: WebSocket, obj) -> bool: """Try to send. Returns False if the socket is (or becomes) closed.""" if ws.client_state == WebSocketState.DISCONNECTED or ws.application_state == WebSocketState.DISCONNECTED: return False try: await ws.send_text(json.dumps(obj)) return True except (WebSocketDisconnect, ClientDisconnected, RuntimeError): return False except Exception: return False # --- Patch T5X mesh helpers for GPUs on JAX >= 0.7 (coords present, no core_on_chip) --- def _patch_t5x_for_gpu_coords(): try: import jax from t5x import partitioning as _t5x_part old_bounds = getattr(_t5x_part, "bounds_from_last_device", None) old_getcoords = getattr(_t5x_part, "get_coords", None) def _bounds_from_last_device_gpu_safe(last_device): # TPU: coords + core_on_chip core = getattr(last_device, "core_on_chip", None) coords = getattr(last_device, "coords", None) if coords is not None and core is not None: x, y, z = coords return x + 1, y + 1, z + 1, core + 1 # Non-TPU (or GPU lacking core_on_chip): hosts x local_devices return jax.host_count(), jax.local_device_count() def _get_coords_gpu_safe(device): core = getattr(device, "core_on_chip", None) coords = getattr(device, "coords", None) if coords is not None and core is not None: return (*coords, core) # Fallback that works on CPU/GPU return (device.process_index, device.id % jax.local_device_count()) _t5x_part.bounds_from_last_device = _bounds_from_last_device_gpu_safe _t5x_part.get_coords = _get_coords_gpu_safe import logging; logging.info("Patched t5x.partitioning for GPU coords without core_on_chip.") except Exception as e: import logging; logging.exception("t5x GPU-coords patch failed: %s", e) # Call the patch immediately at import time (before MagentaRT init) _patch_t5x_for_gpu_coords() jam_registry: dict[str, JamWorker] = {} jam_lock = threading.Lock() @contextmanager def mrt_overrides(mrt, **kwargs): """Temporarily set attributes on MRT if they exist; restore after.""" old = {} try: for k, v in kwargs.items(): if hasattr(mrt, k): old[k] = getattr(mrt, k) setattr(mrt, k, v) yield finally: for k, v in old.items(): setattr(mrt, k, v) # loudness utils try: import pyloudnorm as pyln _HAS_LOUDNORM = True except Exception: _HAS_LOUDNORM = False # def _combine_styles(mrt, styles_str: str = "", weights_str: str = ""): # extra = [s.strip() for s in (styles_str or "").split(",") if s.strip()] # if not extra: # return mrt.embed_style("warmup") # sw = [float(x) for x in (weights_str or "").split(",") if x.strip()] # embeds, weights = [], [] # for i, s in enumerate(extra): # embeds.append(mrt.embed_style(s)) # weights.append(sw[i] if i < len(sw) else 1.0) # wsum = sum(weights) or 1.0 # weights = [w/wsum for w in weights] # import numpy as np # return np.sum([w*e for w, e in zip(weights, embeds)], axis=0).astype(np.float32) def build_style_vector( mrt, *, text_styles: list[str] | None = None, text_weights: list[float] | None = None, loop_embed: np.ndarray | None = None, loop_weight: float | None = None, mean_weight: float | None = None, centroid_weights: list[float] | None = None, ) -> np.ndarray: """ Returns a single style embedding combining: - loop embedding (optional) - one or more text style embeddings (optional) - mean finetune embedding (optional) - centroid embeddings (optional) All weights are normalized so they sum to 1 if > 0. """ comps: list[np.ndarray] = [] weights: list[float] = [] # loop component if loop_embed is not None and (loop_weight or 0) > 0: comps.append(loop_embed.astype(np.float32, copy=False)) weights.append(float(loop_weight)) # text components if text_styles: for i, s in enumerate(text_styles): s = s.strip() if not s: continue w = 1.0 if text_weights and i < len(text_weights): try: w = float(text_weights[i]) except: w = 1.0 if w <= 0: continue e = mrt.embed_style(s) comps.append(e.astype(np.float32, copy=False)) weights.append(w) # mean finetune if mean_weight and (_MEAN_EMBED is not None) and mean_weight > 0: comps.append(_MEAN_EMBED) weights.append(float(mean_weight)) # centroid components if centroid_weights and _CENTROIDS is not None: K = _CENTROIDS.shape[0] for k, w in enumerate(centroid_weights[:K]): try: w = float(w) except: w = 0.0 if w <= 0: continue comps.append(_CENTROIDS[k]) weights.append(w) if not comps: # fallback: neutral style if nothing provided return mrt.embed_style("") wsum = sum(weights) if wsum <= 0: return mrt.embed_style("") weights = [w/wsum for w in weights] # weighted sum out = np.zeros_like(comps[0], dtype=np.float32) for w, e in zip(weights, comps): out += w * e.astype(np.float32, copy=False) return out # ---------------------------- # FastAPI app with lazy, thread-safe model init # ---------------------------- app = FastAPI() app.add_middleware( CORSMiddleware, allow_origins=["*"], # or lock to your domain(s) allow_credentials=True, allow_methods=["*"], allow_headers=["*"], ) _MRT = None _MRT_LOCK = threading.Lock() def get_mrt(): global _MRT if _MRT is None: with _MRT_LOCK: if _MRT is None: ckpt_dir = CheckpointManager.resolve_checkpoint_dir() # uses MRT_CKPT_REPO/STEP if present _MRT = system.MagentaRT( tag=os.getenv("MRT_SIZE", "large"), guidance_weight=5.0, device="gpu", checkpoint_dir=ckpt_dir, lazy=False ) # If no assets loaded yet, and a repo is configured, load them now. if asset_manager.mean_embed is None and asset_manager.centroids is None: repo = os.getenv("MRT_ASSETS_REPO") or os.getenv("MRT_CKPT_REPO") if repo: asset_manager.load_finetune_assets_from_hf(repo, None) _sync_assets_globals_from_manager() return _MRT _WARMED = False _WARMUP_LOCK = threading.Lock() def _mrt_warmup(): """ Build a minimal, bar-aligned silent context and run one 2s generate_chunk to trigger XLA JIT & autotune so first real request is fast. """ global _WARMED with _WARMUP_LOCK: if _WARMED: return try: mrt = get_mrt() # --- derive timing from model config --- codec_fps = float(mrt.codec.frame_rate) ctx_seconds = float(mrt.config.context_length_frames) / codec_fps sr = int(mrt.sample_rate) # We'll align to 120 BPM, 4/4, and generate one ~2s chunk bpm = 120.0 beats_per_bar = 4 # --- build a silent, stereo context of ctx_seconds --- samples = int(max(1, round(ctx_seconds * sr))) silent = np.zeros((samples, 2), dtype=np.float32) with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp: sf.write(tmp.name, silent, sr, subtype="PCM_16") tmp_path = tmp.name try: # Load as Waveform and take a tail of exactly ctx_seconds loop = au.Waveform.from_file(tmp_path).resample(sr).as_stereo() seconds_per_bar = beats_per_bar * (60.0 / bpm) ctx_tail = take_bar_aligned_tail(loop, bpm, beats_per_bar, ctx_seconds) # Tokens for context window tokens_full = mrt.codec.encode(ctx_tail).astype(np.int32) tokens = tokens_full[:, :mrt.config.decoder_codec_rvq_depth] context_tokens = make_bar_aligned_context( tokens, bpm=bpm, fps=float(mrt.codec.frame_rate), ctx_frames=mrt.config.context_length_frames, beats_per_bar=beats_per_bar, ) # Init state and a basic style vector (text token is fine) state = mrt.init_state() state.context_tokens = context_tokens style_vec = mrt.embed_style("warmup") # --- one throwaway chunk (~2s) --- _wav, _state = mrt.generate_chunk(state=state, style=style_vec) logging.info("MagentaRT warmup complete.") finally: try: os.unlink(tmp_path) except Exception: pass _WARMED = True except Exception as e: # Never crash on warmup errors; log and continue serving logging.exception("MagentaRT warmup failed (continuing without warmup): %s", e) # ---------------------------- # startup and model selection # ---------------------------- @app.on_event("startup") def _boot(): # 1) Load finetune assets up front (only if envs are present) repo = os.getenv("MRT_ASSETS_REPO") or os.getenv("MRT_CKPT_REPO") if repo: ok, msg = asset_manager.load_finetune_assets_from_hf(repo, None) _sync_assets_globals_from_manager() # keep /model/config in sync logging.info("Startup asset load from %s: %s", repo, "ok" if ok else msg) else: logging.info("Startup asset load: no repo env set; skipping.") # 2) Start warmup in the background (unchanged behavior) if os.getenv("MRT_WARMUP", "1") != "0": threading.Thread(target=_mrt_warmup, name="mrt-warmup", daemon=True).start() @app.get("/model/status") def model_status(): mrt = get_mrt() return { "tag": getattr(mrt, "_tag", "unknown"), "using_checkpoint_dir": True, "codec_frame_rate": float(mrt.codec.frame_rate), "decoder_rvq_depth": int(mrt.config.decoder_codec_rvq_depth), "context_seconds": float(mrt.config.context_length), "chunk_seconds": float(mrt.config.chunk_length), "crossfade_seconds": float(mrt.config.crossfade_length), "selected_step": os.getenv("MRT_CKPT_STEP"), "repo": os.getenv("MRT_CKPT_REPO"), } @app.post("/model/swap") def model_swap(step: int = Form(...)): # stop any active jam if you want to be strict (not shown) os.environ["MRT_CKPT_STEP"] = str(step) global _MRT with _MRT_LOCK: _MRT = None # force re-create on next get_mrt() # optionally pre-warm here by calling get_mrt() return {"reloaded": True, "step": step} @app.post("/model/assets/load") def model_assets_load(repo_id: str = Form(None)): global _MEAN_EMBED, _CENTROIDS, _ASSETS_REPO_ID ok, msg = asset_manager.load_finetune_assets_from_hf(repo_id, get_mrt()) # Sync globals after loading _MEAN_EMBED = asset_manager.mean_embed _CENTROIDS = asset_manager.centroids _ASSETS_REPO_ID = asset_manager.assets_repo_id return {"ok": ok, "message": msg, "repo_id": _ASSETS_REPO_ID, "mean": _MEAN_EMBED is not None, "centroids": None if _CENTROIDS is None else int(_CENTROIDS.shape[0])} @app.get("/model/assets/status") def model_assets_status(): d = None try: d = int(get_mrt().style_model.config.embedding_dim) except Exception: pass return { "repo_id": _ASSETS_REPO_ID, "mean_loaded": _MEAN_EMBED is not None, "centroids_loaded": False if _CENTROIDS is None else True, "centroid_count": None if _CENTROIDS is None else int(_CENTROIDS.shape[0]), "embedding_dim": d, } @app.get("/model/config") def model_config(): """ Lightweight config snapshot: - never calls get_mrt() (no model build / no downloads) - never calls snapshot_download() - reports whether a model instance is currently loaded in memory - best-effort local checkpoint presence (no network) """ # Read-only snapshot of in-memory model presence with _MRT_LOCK: loaded = (_MRT is not None) size = os.getenv("MRT_SIZE", "large") repo = os.getenv("MRT_CKPT_REPO") rev = os.getenv("MRT_CKPT_REV", "main") step = os.getenv("MRT_CKPT_STEP") assets = os.getenv("MRT_ASSETS_REPO") # Use CheckpointManager for local cache probe (no network) local_ckpt = None if step: try: from pathlib import Path import re step_escaped = re.escape(str(step)) candidates = [] for root in ("/home/appuser/.cache/mrt_ckpt/extracted", "/home/appuser/.cache/mrt_ckpt/repo"): p = Path(root) if not p.exists(): continue # Look for exact "checkpoint_" directories anywhere under these roots for d in p.rglob(f"checkpoint_{step}"): if d.is_dir(): candidates.append(str(d)) local_ckpt = candidates[0] if candidates else None except Exception: local_ckpt = None return { "size": size, "repo": repo, "revision": rev, "selected_step": step, "assets_repo": assets, # in-memory + local cache hints (no network, no model build) "loaded": loaded, "active_jam": _any_jam_running(), "local_checkpoint_dir": local_ckpt, # None if not found locally # steering assets currently resident in memory "mean_loaded": (_MEAN_EMBED is not None), "centroids_loaded": (_CENTROIDS is not None), "centroid_count": (None if _CENTROIDS is None else int(_CENTROIDS.shape[0])), "warmup_done": bool(_WARMED), } @app.get("/model/checkpoints") def model_checkpoints(repo_id: str, revision: str = "main"): steps = CheckpointManager.list_ckpt_steps(repo_id, revision) return {"repo": repo_id, "revision": revision, "steps": steps, "latest": (steps[-1] if steps else None)} @app.post("/model/select") def model_select(req: ModelSelect): """ Swap model/checkpoint/assets. If req.prewarm is True, run the full bar-aligned warmup (_mrt_warmup) synchronously so we only report warmed once the new model is actually ready. """ global _MRT, _MEAN_EMBED, _CENTROIDS, _ASSETS_REPO_ID, _WARMED # 1) Validate the request (no side-effects) success, validation_result = model_selector.validate_selection(req) if not success: if "error" in validation_result: raise HTTPException(status_code=400, detail=validation_result["error"]) return {"ok": False, **validation_result} # Augment response surface validation_result["active_jam"] = _any_jam_running() # Dry-run path if req.dry_run: return {"ok": True, "dry_run": True, **validation_result} if isinstance(req.step, str) and req.step.lower() == "none": # user asked for stock base # Clear any resident finetune assets so /model/config reflects "no assets" asset_manager.mean_embed = None asset_manager.centroids = None asset_manager.assets_repo_id = None # keep module-level mirrors in sync _MEAN_EMBED = None _CENTROIDS = None _ASSETS_REPO_ID = None # 2) Handle jam policy if _any_jam_running(): if req.stop_active: _stop_all_jams() else: raise HTTPException(status_code=409, detail="A jam is running; retry with stop_active=true") # 3) Compute environment changes (no mutation yet) env_changes = model_selector.prepare_env_changes(req, validation_result) # Keep current env for rollback old_env = { "MRT_SIZE": os.getenv("MRT_SIZE"), "MRT_CKPT_REPO": os.getenv("MRT_CKPT_REPO"), "MRT_CKPT_REV": os.getenv("MRT_CKPT_REV"), "MRT_CKPT_STEP": os.getenv("MRT_CKPT_STEP"), "MRT_ASSETS_REPO": os.getenv("MRT_ASSETS_REPO"), } try: # 4) Apply env atomically for key, value in env_changes.items(): if value is None: os.environ.pop(key, None) else: os.environ[key] = str(value) # 5) Force rebuild of the model and reset warmup state with _MRT_LOCK: _MRT = None with _WARMUP_LOCK: _WARMED = False # ← critical: don't leak previous model's warmed state # 6) Load finetune assets if requested (mean/centroids) if req.sync_assets and validation_result.get("assets_repo"): ok, msg = asset_manager.load_finetune_assets_from_hf( validation_result["assets_repo"], None # don't implicitly instantiate model here; we'll do it below ) if ok: _MEAN_EMBED = asset_manager.mean_embed _CENTROIDS = asset_manager.centroids _ASSETS_REPO_ID = asset_manager.assets_repo_id else: logging.warning("Asset sync skipped/failed: %s", msg) # 7) Prewarm behavior: # - If prewarm=True, run the *real* bar-aligned warmup synchronously. # - This will instantiate the new MRT and set _WARMED=True on success. if req.prewarm: _mrt_warmup() # builds MRT internally via get_mrt(), runs generate_chunk, sets _WARMED # Optional: if you want to always ensure MRT exists (even without prewarm), uncomment: # else: # _ = get_mrt() return { "ok": True, **validation_result, "warmup_done": bool(_WARMED), } except Exception as e: # 8) Roll back env on failure for k, v in old_env.items(): if v is None: os.environ.pop(k, None) else: os.environ[k] = v # Also reset model pointer & warmed flag to a safe state with _MRT_LOCK: _MRT = None with _WARMUP_LOCK: _WARMED = False logging.exception("Model select failed: %s", e) raise HTTPException(status_code=500, detail=f"Model select failed: {e}") # ---------------------------- # one-shot generation # ---------------------------- @app.post("/generate") def generate( loop_audio: UploadFile = File(...), bpm: float = Form(...), bars: int = Form(8), beats_per_bar: int = Form(4), styles: str = Form("acid house"), style_weights: str = Form(""), loop_weight: float = Form(1.0), loudness_mode: str = Form("auto"), loudness_headroom_db: float = Form(1.0), guidance_weight: float = Form(5.0), temperature: float = Form(1.1), topk: int = Form(40), target_sample_rate: int | None = Form(None), intro_bars_to_drop: int = Form(0), # <— NEW ): # Read file data = loop_audio.file.read() if not data: return {"error": "Empty file"} with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp: tmp.write(data) tmp_path = tmp.name # Parse styles + weights extra_styles = [s for s in (styles.split(",") if styles else []) if s.strip()] weights = [float(x) for x in style_weights.split(",")] if style_weights else None mrt = get_mrt() # warm once, in this worker thread # Temporarily override MRT inference knobs for this request with mrt_overrides(mrt, guidance_weight=guidance_weight, temperature=temperature, topk=topk): wav, loud_stats = generate_loop_continuation_with_mrt( mrt, input_wav_path=tmp_path, bpm=bpm, extra_styles=extra_styles, style_weights=weights, bars=bars, beats_per_bar=beats_per_bar, loop_weight=loop_weight, loudness_mode=loudness_mode, loudness_headroom_db=loudness_headroom_db, intro_bars_to_drop=intro_bars_to_drop, # <— pass through ) # 1) Figure out the desired SR inp_info = sf.info(tmp_path) input_sr = int(inp_info.samplerate) target_sr = int(target_sample_rate or input_sr) # 2) Convert to target SR + snap to exact bars cur_sr = int(mrt.sample_rate) x = wav.samples if wav.samples.ndim == 2 else wav.samples[:, None] seconds_per_bar = (60.0 / float(bpm)) * int(beats_per_bar) expected_secs = float(bars) * seconds_per_bar x = resample_and_snap(x, cur_sr=cur_sr, target_sr=target_sr, seconds=expected_secs) # 3) Encode WAV once (no extra write) audio_b64, total_samples, channels = wav_bytes_base64(x, target_sr) loop_duration_seconds = total_samples / float(target_sr) # 4) Metadata metadata = { "bpm": int(round(bpm)), "bars": int(bars), "beats_per_bar": int(beats_per_bar), "styles": extra_styles, "style_weights": weights, "loop_weight": loop_weight, "loudness": loud_stats, "sample_rate": int(target_sr), "channels": int(channels), "crossfade_seconds": mrt.config.crossfade_length, "total_samples": int(total_samples), "seconds_per_bar": seconds_per_bar, "loop_duration_seconds": loop_duration_seconds, "guidance_weight": guidance_weight, "temperature": temperature, "topk": topk, } return {"audio_base64": audio_b64, "metadata": metadata} # new endpoint to return a bar-aligned chunk without the need for combined audio @app.post("/generate_style") def generate_style( bpm: float = Form(...), bars: int = Form(8), beats_per_bar: int = Form(4), styles: str = Form("warmup"), style_weights: str = Form(""), guidance_weight: float = Form(1.1), temperature: float = Form(1.1), topk: int = Form(40), target_sample_rate: int | None = Form(None), intro_bars_to_drop: int = Form(0), ): """ Style-only, bar-aligned generation (no input audio). Seeds with 10s of silent context; outputs exactly `bars` at the requested BPM. """ mrt = get_mrt() # Override sampling knobs just for this request with mrt_overrides(mrt, guidance_weight=guidance_weight, temperature=temperature, topk=topk): wav, _ = generate_style_only_with_mrt( mrt, bpm=bpm, bars=bars, beats_per_bar=beats_per_bar, styles=styles, style_weights=style_weights, intro_bars_to_drop=intro_bars_to_drop, ) # Determine target SR (defaults to model SR = 48k) cur_sr = int(mrt.sample_rate) target_sr = int(target_sample_rate or cur_sr) x = wav.samples if wav.samples.ndim == 2 else wav.samples[:, None] seconds_per_bar = (60.0 / float(bpm)) * int(beats_per_bar) expected_secs = float(bars) * seconds_per_bar # Snap exactly to musical length at the requested sample rate x = resample_and_snap(x, cur_sr=cur_sr, target_sr=target_sr, seconds=expected_secs) audio_b64, total_samples, channels = wav_bytes_base64(x, target_sr) metadata = { "bpm": int(round(bpm)), "bars": int(bars), "beats_per_bar": int(beats_per_bar), "styles": [s.strip() for s in (styles.split(",") if styles else []) if s.strip()], "style_weights": [float(y) for y in style_weights.split(",")] if style_weights else None, "sample_rate": int(target_sr), "channels": int(channels), "crossfade_seconds": mrt.config.crossfade_length, "seconds_per_bar": seconds_per_bar, "loop_duration_seconds": total_samples / float(target_sr), "guidance_weight": guidance_weight, "temperature": temperature, "topk": topk, } return {"audio_base64": audio_b64, "metadata": metadata} # ---------------------------- # the 'keep jamming' button # ---------------------------- @app.post("/jam/start") def jam_start( loop_audio: UploadFile = File(...), bpm: float = Form(...), bars_per_chunk: int = Form(4), beats_per_bar: int = Form(4), styles: str = Form(""), style_weights: str = Form(""), loop_weight: float = Form(1.0), # NEW steering params: mean: float = Form(0.0), centroid_weights: str = Form(""), loudness_mode: str = Form("auto"), loudness_headroom_db: float = Form(1.0), guidance_weight: float = Form(1.1), temperature: float = Form(1.1), topk: int = Form(40), target_sample_rate: int | None = Form(None), ): asset_manager.ensure_assets_loaded(get_mrt()) # enforce single active jam per GPU with jam_lock: for sid, w in list(jam_registry.items()): if w.is_alive(): raise HTTPException(status_code=429, detail="A jam is already running. Try again later.") # read input + prep context/style (reuse your existing code) data = loop_audio.file.read() if not data: raise HTTPException(status_code=400, detail="Empty file") with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp: tmp.write(data); tmp_path = tmp.name mrt = get_mrt() loop = au.Waveform.from_file(tmp_path).resample(mrt.sample_rate).as_stereo() # build tail context + style vec (tail-biased) codec_fps = float(mrt.codec.frame_rate) ctx_seconds = float(mrt.config.context_length_frames) / codec_fps loop_tail = take_bar_aligned_tail(loop, bpm, beats_per_bar, ctx_seconds) # Parse client style fields (preserves your semantics) text_list = [s.strip() for s in (styles.split(",") if styles else []) if s.strip()] try: tw = [float(x) for x in style_weights.split(",")] if style_weights else [] except ValueError: tw = [] try: cw = [float(x) for x in centroid_weights.split(",")] if centroid_weights else [] except ValueError: cw = [] # Compute loop-tail embed once (same as before) loop_tail_embed = mrt.embed_style(loop_tail) # Build final style vector: # - identical to your previous mix when mean==0 and cw is empty # - otherwise includes mean and centroid components (weights auto-normalized) style_vec = build_style_vector( mrt, text_styles=text_list, text_weights=tw, loop_embed=loop_tail_embed, loop_weight=float(loop_weight), mean_weight=float(mean), centroid_weights=cw, ).astype(np.float32, copy=False) # target SR (default input SR) inp_info = sf.info(tmp_path) input_sr = int(inp_info.samplerate) target_sr = int(target_sample_rate or input_sr) params = JamParams( bpm=bpm, beats_per_bar=beats_per_bar, bars_per_chunk=bars_per_chunk, target_sr=target_sr, loudness_mode=loudness_mode, headroom_db=loudness_headroom_db, style_vec=style_vec, ref_loop=loop_tail, # For loudness matching combined_loop=loop, # NEW: Full loop for context setup guidance_weight=guidance_weight, temperature=temperature, topk=topk ) worker = JamWorker(mrt, params) sid = str(uuid.uuid4()) with jam_lock: jam_registry[sid] = worker worker.start() return {"session_id": sid} @app.get("/jam/next") def jam_next(session_id: str): """ Get the next sequential chunk in the jam session. This ensures chunks are delivered in order without gaps. """ with jam_lock: worker = jam_registry.get(session_id) if worker is None or not worker.is_alive(): raise HTTPException(status_code=404, detail="Session not found") # Get the next sequential chunk (this blocks until ready) chunk = worker.get_next_chunk() if chunk is None: raise HTTPException(status_code=408, detail="Chunk not ready within timeout") return { "chunk": { "index": chunk.index, "audio_base64": chunk.audio_base64, "metadata": chunk.metadata } } @app.post("/jam/consume") def jam_consume(session_id: str = Form(...), chunk_index: int = Form(...)): """ Mark a chunk as consumed by the frontend. This helps the worker manage its buffer and generation flow. """ with jam_lock: worker = jam_registry.get(session_id) if worker is None or not worker.is_alive(): raise HTTPException(status_code=404, detail="Session not found") worker.mark_chunk_consumed(chunk_index) return {"consumed": chunk_index} @app.post("/jam/stop") def jam_stop(session_id: str = Body(..., embed=True)): with jam_lock: worker = jam_registry.get(session_id) if worker is None: raise HTTPException(status_code=404, detail="Session not found") worker.stop() worker.join(timeout=5.0) if worker.is_alive(): # It’s daemon=True, so it won’t block process exit, but report it print(f"⚠️ JamWorker {session_id} did not stop within timeout") with jam_lock: jam_registry.pop(session_id, None) return {"stopped": True} @app.post("/jam/update") def jam_update( session_id: str = Form(...), # knobs guidance_weight: Optional[float] = Form(None), temperature: Optional[float] = Form(None), topk: Optional[int] = Form(None), # styles styles: str = Form(""), style_weights: str = Form(""), loop_weight: Optional[float] = Form(None), use_current_mix_as_style: bool = Form(False), # NEW steering mean: Optional[float] = Form(None), centroid_weights: str = Form(""), ): asset_manager.ensure_assets_loaded(get_mrt()) with jam_lock: worker = jam_registry.get(session_id) if worker is None or not worker.is_alive(): raise HTTPException(status_code=404, detail="Session not found") # 1) fast knob updates if any(v is not None for v in (guidance_weight, temperature, topk)): worker.update_knobs( guidance_weight=guidance_weight, temperature=temperature, topk=topk ) # 2) rebuild style only if asked wants_style_update = ( use_current_mix_as_style or (styles.strip() != "") or (mean is not None) or (centroid_weights.strip() != "") ) if not wants_style_update: return {"ok": True} # --- parse inputs (robust) --- text_list = [s.strip() for s in (styles.split(",") if styles else []) if s.strip()] try: tw = [float(x) for x in style_weights.split(",")] if style_weights else [] except ValueError: tw = [] try: cw = [float(x) for x in centroid_weights.split(",")] if centroid_weights else [] except ValueError: cw = [] # Clamp centroid weights to available centroids (if loaded) max_c = 0 if _CENTROIDS is None else int(_CENTROIDS.shape[0]) if max_c and len(cw) > max_c: cw = cw[:max_c] # Snapshot minimal state under lock with worker._lock: combined_loop = worker.params.combined_loop if use_current_mix_as_style else None lw = None if use_current_mix_as_style: lw = 1.0 if (loop_weight is None) else float(loop_weight) mrt = worker.mrt # Heavy work OUTSIDE the lock loop_embed = None if combined_loop is not None: loop_embed = mrt.embed_style(combined_loop) style_vec = build_style_vector( mrt, text_styles=text_list, text_weights=tw, loop_embed=loop_embed, # None => ignored by builder loop_weight=lw, # None => ignored by builder mean_weight=(None if mean is None else float(mean)), centroid_weights=cw, # [] => ignored by builder ).astype(np.float32, copy=False) # Swap atomically with worker._lock: worker.params.style_vec = style_vec return {"ok": True} @app.post("/jam/reseed") def jam_reseed(session_id: str = Form(...), loop_audio: UploadFile = File(None)): with jam_lock: worker = jam_registry.get(session_id) if worker is None or not worker.is_alive(): raise HTTPException(status_code=404, detail="Session not found") # Option 1: use uploaded new “combined” bounce from the app if loop_audio is not None: data = loop_audio.file.read() if not data: raise HTTPException(status_code=400, detail="Empty file") with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp: tmp.write(data); path = tmp.name wav = au.Waveform.from_file(path).resample(worker.mrt.sample_rate).as_stereo() else: # Option 2: reseed from what we’ve been streaming (the model side) # (Usually better to reseed from the Swift-side “combined” mix you trust.) s = getattr(worker, "_stream", None) if s is None or s.shape[0] == 0: raise HTTPException(status_code=400, detail="No internal stream to reseed from") wav = au.Waveform(s.astype(np.float32, copy=False), int(worker.mrt.sample_rate)).as_stereo() worker.reseed_from_waveform(wav) return {"ok": True} @app.post("/jam/reseed_splice") def jam_reseed_splice( session_id: str = Form(...), anchor_bars: float = Form(2.0), # how much of the original to re-inject combined_audio: UploadFile = File(None), # preferred: Swift supplies the current combined mix ): worker = jam_registry.get(session_id) if worker is None or not worker.is_alive(): raise HTTPException(status_code=404, detail="Session not found") # Build a waveform to reseed from wav = None if combined_audio is not None: data = combined_audio.file.read() if not data: raise HTTPException(status_code=400, detail="Empty combined_audio") with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp: tmp.write(data) path = tmp.name wav = au.Waveform.from_file(path).resample(worker.mrt.sample_rate).as_stereo() else: # Fallback: reseed from the model’s internal stream (less ideal than the Swift-side bounce) s = getattr(worker, "_stream", None) if s is None or s.shape[0] == 0: raise HTTPException(status_code=400, detail="No audio available to reseed from") wav = au.Waveform(s.astype(np.float32, copy=False), int(worker.mrt.sample_rate)).as_stereo() # Perform the splice reseed worker.reseed_splice(wav, anchor_bars=float(anchor_bars)) return {"ok": True, "anchor_bars": float(anchor_bars)} @app.get("/jam/status") def jam_status(session_id: str): with jam_lock: worker = jam_registry.get(session_id) if worker is None: raise HTTPException(status_code=404, detail="Session not found") running = worker.is_alive() # Snapshot safely with worker._lock: last_generated = int(worker.idx) last_delivered = int(worker._last_delivered_index) queued = len(worker.outbox) buffer_ahead = last_generated - last_delivered p = worker.params spb = p.beats_per_bar * (60.0 / p.bpm) chunk_secs = p.bars_per_chunk * spb return { "running": running, "last_generated_index": last_generated, # Last chunk that finished generating "last_delivered_index": last_delivered, # Last chunk sent to frontend "buffer_ahead": buffer_ahead, # How many chunks ahead we are "queued_chunks": queued, # Total chunks in outbox "bpm": p.bpm, "beats_per_bar": p.beats_per_bar, "bars_per_chunk": p.bars_per_chunk, "seconds_per_bar": spb, "chunk_duration_seconds": chunk_secs, "target_sample_rate": p.target_sr, "last_chunk_started_at": worker.last_chunk_started_at, "last_chunk_completed_at": worker.last_chunk_completed_at, } @app.get("/health") def health(): # 1) Template mode → not ready (encourage duplication on GPU) if SPACE_MODE != "serve": return JSONResponse( status_code=503, content={ "ok": False, "status": "template_mode", "message": "This Space is a GPU template. Duplicate it and select an L40s/A100-class runtime to use the API.", "mode": SPACE_MODE, }, ) # 2) Runtime hardware probe probe = _gpu_probe() if not probe["ok"] or not probe["has_gpu"] or probe.get("backend") != "gpu": return JSONResponse( status_code=503, content={ "ok": False, "status": "gpu_unavailable", "message": "GPU is not visible to JAX. Select a GPU runtime (e.g., L40s) to serve.", "probe": probe, "mode": SPACE_MODE, }, ) # 3) Ready; include operational hints warmed = bool(_WARMED) with jam_lock: active_jams = sum(1 for w in jam_registry.values() if w.is_alive()) return { "ok": True, "status": "ready" if warmed else "initializing", "mode": SPACE_MODE, "warmed": warmed, "active_jams": active_jams, "probe": probe, } @app.middleware("http") async def log_requests(request: Request, call_next): rid = request.headers.get("X-Request-ID", "-") print(f"📥 {request.method} {request.url.path}?{request.url.query} [rid={rid}]") try: response = await call_next(request) except Exception as e: print(f"💥 exception for {request.url.path} [rid={rid}]: {e}") raise print(f"📤 {response.status_code} {request.url.path} [rid={rid}]") return response # ---------------------------- # websockets route # ---------------------------- @app.websocket("/ws/jam") async def ws_jam(websocket: WebSocket): await websocket.accept() sid = None worker = None binary_audio = False mode = "rt" # or "bar" # NEW: capture ws in closure async def send_json(obj): return await send_json_safe(websocket, obj) try: while True: raw = await websocket.receive_text() msg = json.loads(raw) mtype = msg.get("type") # --- START --- if mtype == "start": binary_audio = bool(msg.get("binary_audio", False)) mode = msg.get("mode", "rt") params = msg.get("params", {}) or {} sid = msg.get("session_id") # attach or create if sid: with jam_lock: worker = jam_registry.get(sid) if worker is None or not worker.is_alive(): await send_json({"type":"error","error":"Session not found"}) continue else: # optionally accept base64 loop and start a new worker (bar-mode) if mode == "bar": loop_b64 = msg.get("loop_audio_b64") if not loop_b64: await send_json({"type":"error","error":"loop_audio_b64 required for mode=bar when no session_id"}) continue loop_bytes = base64.b64decode(loop_b64) # mimic /jam/start with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp: tmp.write(loop_bytes); tmp_path = tmp.name # build JamParams similar to /jam/start mrt = get_mrt() model_sr = int(mrt.sample_rate) # typically 48000 # Defaults for WS: raw loudness @ model SR, unless overridden by client: target_sr = int(params.get("target_sr", model_sr)) loudness_mode = params.get("loudness_mode", "none") headroom_db = float(params.get("headroom_db", 1.0)) loop = au.Waveform.from_file(tmp_path).resample(mrt.sample_rate).as_stereo() codec_fps = float(mrt.codec.frame_rate) ctx_seconds = float(mrt.config.context_length_frames) / codec_fps bpm = float(params.get("bpm", 120.0)) bpb = int(params.get("beats_per_bar", 4)) loop_tail = take_bar_aligned_tail(loop, bpm, bpb, ctx_seconds) # style vector (loop + extra styles) embeds, weights = [mrt.embed_style(loop_tail)], [float(params.get("loop_weight", 1.0))] extra = [s for s in (params.get("styles","").split(",")) if s.strip()] sw = [float(x) for x in params.get("style_weights","").split(",") if x.strip()] for i, s in enumerate(extra): embeds.append(mrt.embed_style(s.strip())) weights.append(sw[i] if i < len(sw) else 1.0) wsum = sum(weights) or 1.0 weights = [w/wsum for w in weights] style_vec = np.sum([w*e for w, e in zip(weights, embeds)], axis=0).astype(np.float32) # target SR fallback: input SR inp_info = sf.info(tmp_path) target_sr = int(params.get("target_sr", int(inp_info.samplerate))) # Build JamParams for WS bar-mode jp = JamParams( bpm=bpm, beats_per_bar=bpb, bars_per_chunk=int(params.get("bars_per_chunk", 8)), target_sr=target_sr, loudness_mode=loudness_mode, headroom_db=headroom_db, style_vec=style_vec, ref_loop=None if loudness_mode == "none" else loop_tail, # disable match by default combined_loop=loop, guidance_weight=float(params.get("guidance_weight", 1.1)), temperature=float(params.get("temperature", 1.1)), topk=int(params.get("topk", 40)), ) worker = JamWorker(get_mrt(), jp) sid = str(uuid.uuid4()) with jam_lock: # single active jam per GPU, mirroring /jam/start for _sid, w in list(jam_registry.items()): if w.is_alive(): await send_json({"type":"error","error":"A jam is already running"}) worker = None; sid = None break if worker is not None: jam_registry[sid] = worker worker.start() else: # mode == "rt" (Colab-style, no loop context) mrt = get_mrt() state = mrt.init_state() # Build silent context (10s) tokens codec_fps = float(mrt.codec.frame_rate) ctx_seconds = float(mrt.config.context_length_frames) / codec_fps sr = int(mrt.sample_rate) samples = int(max(1, round(ctx_seconds * sr))) silent = au.Waveform(np.zeros((samples, 2), np.float32), sr) tokens = mrt.codec.encode(silent).astype(np.int32)[:, :mrt.config.decoder_codec_rvq_depth] state.context_tokens = tokens # Parse params (including steering) asset_manager.ensure_assets_loaded(get_mrt()) styles_str = params.get("styles", "warmup") or "" style_weights_str = params.get("style_weights", "") or "" mean_w = float(params.get("mean", 0.0) or 0.0) cw_str = str(params.get("centroid_weights", "") or "") text_list = [s.strip() for s in styles_str.split(",") if s.strip()] try: text_w = [float(x) for x in style_weights_str.split(",")] if style_weights_str else [] except ValueError: text_w = [] try: cw = [float(x) for x in cw_str.split(",") if x.strip() != ""] except ValueError: cw = [] # Clamp centroid weights to available centroids if _CENTROIDS is not None and len(cw) > int(_CENTROIDS.shape[0]): cw = cw[: int(_CENTROIDS.shape[0])] # Build initial style vector (no loop_embed in rt mode) style_vec = build_style_vector( mrt, text_styles=text_list, text_weights=text_w, loop_embed=None, loop_weight=None, mean_weight=mean_w, centroid_weights=cw, ) # Stash rt session fields websocket._mrt = mrt websocket._state = state websocket._style_cur = style_vec websocket._style_tgt = style_vec websocket._style_ramp_s = float(params.get("style_ramp_seconds", 0.0)) websocket._rt_mean = mean_w websocket._rt_centroid_weights = cw websocket._rt_running = True websocket._rt_sr = sr websocket._rt_topk = int(params.get("topk", 40)) websocket._rt_temp = float(params.get("temperature", 1.1)) websocket._rt_guid = float(params.get("guidance_weight", 1.1)) websocket._pace = params.get("pace", "asap") # "realtime" | "asap" # (Optional) report whether steering assets were loaded assets_ok = (_MEAN_EMBED is not None) or (_CENTROIDS is not None) await send_json({"type": "started", "mode": "rt", "steering_assets": "loaded" if assets_ok else "none"}) # kick off the ~2s streaming loop async def _rt_loop(): try: mrt = websocket._mrt chunk_secs = (mrt.config.chunk_length_frames * mrt.config.frame_length_samples) / float(mrt.sample_rate) target_next = time.perf_counter() while websocket._rt_running: mrt.guidance_weight = websocket._rt_guid mrt.temperature = websocket._rt_temp mrt.topk = websocket._rt_topk # ramp style ramp = float(getattr(websocket, "_style_ramp_s", 0.0) or 0.0) if ramp <= 0.0: websocket._style_cur = websocket._style_tgt else: step = min(1.0, chunk_secs / ramp) websocket._style_cur = websocket._style_cur + step * (websocket._style_tgt - websocket._style_cur) wav, new_state = mrt.generate_chunk(state=websocket._state, style=websocket._style_cur) websocket._state = new_state x = wav.samples.astype(np.float32, copy=False) buf = io.BytesIO() sf.write(buf, x, mrt.sample_rate, subtype="FLOAT", format="WAV") ok = True if binary_audio: try: await websocket.send_bytes(buf.getvalue()) ok = await send_json({"type": "chunk_meta", "metadata": {"sample_rate": mrt.sample_rate}}) except Exception: ok = False else: b64 = base64.b64encode(buf.getvalue()).decode("utf-8") ok = await send_json({"type": "chunk", "audio_base64": b64, "metadata": {"sample_rate": mrt.sample_rate}}) if not ok: break if getattr(websocket, "_pace", "asap") == "realtime": t1 = time.perf_counter() target_next += chunk_secs sleep_s = max(0.0, target_next - t1 - 0.02) if sleep_s > 0: await asyncio.sleep(sleep_s) except asyncio.CancelledError: pass except Exception: pass websocket._rt_task = asyncio.create_task(_rt_loop()) continue # skip the “bar-mode started” message below await send_json({"type":"started","session_id": sid, "mode": mode}) # if we’re in bar-mode, begin pushing chunks as they arrive if mode == "bar" and worker is not None: async def _pump(): while True: if not worker.is_alive(): break chunk = worker.get_next_chunk(timeout=60.0) if chunk is None: continue if binary_audio: await websocket.send_bytes(base64.b64decode(chunk.audio_base64)) await send_json({"type":"chunk_meta","index":chunk.index,"metadata":chunk.metadata}) else: await send_json({"type":"chunk","index":chunk.index, "audio_base64":chunk.audio_base64,"metadata":chunk.metadata}) asyncio.create_task(_pump()) # --- UPDATES (bar or rt) --- elif mtype == "update": if mode == "bar": if not sid: await send_json({"type":"error","error":"No session_id yet"}); return # fan values straight into your existing HTTP handler: res = jam_update( session_id=sid, guidance_weight=msg.get("guidance_weight"), temperature=msg.get("temperature"), topk=msg.get("topk"), styles=msg.get("styles",""), style_weights=msg.get("style_weights",""), loop_weight=msg.get("loop_weight"), use_current_mix_as_style=bool(msg.get("use_current_mix_as_style", False)), ) await send_json({"type":"status", **res}) # {"ok": True} else: # rt-mode: there’s no JamWorker; update the local knobs/state websocket._rt_temp = float(msg.get("temperature", websocket._rt_temp)) websocket._rt_topk = int(msg.get("topk", websocket._rt_topk)) websocket._rt_guid = float(msg.get("guidance_weight", websocket._rt_guid)) # NEW steering fields if "mean" in msg and msg["mean"] is not None: try: websocket._rt_mean = float(msg["mean"]) except: websocket._rt_mean = 0.0 if "centroid_weights" in msg: cw = [w.strip() for w in str(msg["centroid_weights"]).split(",") if w.strip() != ""] try: websocket._rt_centroid_weights = [float(x) for x in cw] except: websocket._rt_centroid_weights = [] # styles / text weights (optional, comma-separated) styles_str = msg.get("styles", None) style_weights_str = msg.get("style_weights", "") text_list = [s for s in (styles_str.split(",") if styles_str else []) if s.strip()] text_w = [float(x) for x in style_weights_str.split(",")] if style_weights_str else [] asset_manager.ensure_assets_loaded(get_mrt()) websocket._style_tgt = build_style_vector( websocket._mrt, text_styles=text_list, text_weights=text_w, loop_embed=None, loop_weight=None, mean_weight=float(websocket._rt_mean), centroid_weights=websocket._rt_centroid_weights, ) # optionally allow live changes to ramp: if "style_ramp_seconds" in msg: try: websocket._style_ramp_s = float(msg["style_ramp_seconds"]) except: pass await send_json({"type":"status","updated":"rt-knobs+style"}) elif mtype == "consume" and mode == "bar": with jam_lock: worker = jam_registry.get(msg.get("session_id")) if worker is not None: worker.mark_chunk_consumed(int(msg.get("chunk_index", -1))) elif mtype == "reseed" and mode == "bar": with jam_lock: worker = jam_registry.get(msg.get("session_id")) if worker is None or not worker.is_alive(): await send_json({"type":"error","error":"Session not found"}); continue loop_b64 = msg.get("loop_audio_b64") if not loop_b64: await send_json({"type":"error","error":"loop_audio_b64 required"}); continue loop_bytes = base64.b64decode(loop_b64) with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp: tmp.write(loop_bytes); path = tmp.name wav = au.Waveform.from_file(path).resample(worker.mrt.sample_rate).as_stereo() worker.reseed_from_waveform(wav) await send_json({"type":"status","reseeded":True}) elif mtype == "reseed_splice" and mode == "bar": with jam_lock: worker = jam_registry.get(msg.get("session_id")) if worker is None or not worker.is_alive(): await send_json({"type":"error","error":"Session not found"}); continue anchor = float(msg.get("anchor_bars", 2.0)) b64 = msg.get("combined_audio_b64") if b64: data = base64.b64decode(b64) with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp: tmp.write(data); path = tmp.name wav = au.Waveform.from_file(path).resample(worker.mrt.sample_rate).as_stereo() worker.reseed_splice(wav, anchor_bars=anchor) else: # fallback: model-side stream splice worker.reseed_splice(worker.params.combined_loop, anchor_bars=anchor) await send_json({"type":"status","splice":anchor}) elif mtype == "stop": if mode == "rt": websocket._rt_running = False task = getattr(websocket, "_rt_task", None) if task is not None: task.cancel() try: await task except asyncio.CancelledError: pass await send_json({"type":"stopped"}) break # <- add this if you want to end the socket after stop elif mtype == "ping": await send_json({"type":"pong"}) else: await send_json({"type":"error","error":f"Unknown type {mtype}"}) except WebSocketDisconnect: # best-effort cleanup for bar-mode sessions started within this socket (optional) pass except Exception as e: try: await send_json({"type":"error","error":str(e)}) except Exception: pass finally: try: if websocket.client_state != WebSocketState.DISCONNECTED: await websocket.close() except Exception: pass @app.get("/ping") def ping(): return {"ok": True} @app.get("/", response_class=Response) def read_root(): """Root endpoint that explains what this API does""" try: html_file = Path(__file__).parent / "documentation.html" html_content = html_file.read_text(encoding='utf-8') except FileNotFoundError: # Fallback if file is missing html_content = """

MagentaRT Research API

Documentation file not found. Please check documentation.html

""" return Response(content=html_content, media_type="text/html") @app.get("/lil_demo_540p.mp4") def demo_video(): return FileResponse(Path(__file__).parent / "lil_demo_540p.mp4", media_type="video/mp4") @app.get("/tester", response_class=HTMLResponse) def tester(): html_path = Path(__file__).parent / "magentaRT_rt_tester.html" return HTMLResponse( html_path.read_text(encoding="utf-8"), headers={"Cache-Control": "no-store"} # avoid sticky caches while iterating )