remove recorder/upload samples

cli/run_generator_with_progress.py

@@ -0,0 +1,112 @@
+#!/usr/bin/env python3
+import argparse
+import queue
+import subprocess
+import sys
+import threading
+from pathlib import Path
+
+
+def _model_args(generator_args):
+    values = []
+    for idx, arg in enumerate(generator_args):
+        if arg == "--model" and idx + 1 < len(generator_args):
+            values.append(generator_args[idx + 1])
+    return values
+
+
+def _is_onnx_run(generator_args):
+    return any(str(value).endswith(".onnx") for value in _model_args(generator_args))
+
+
+def _format_line(line):
+    if line.startswith("DEBUG:piper.voice:"):
+        return None
+    for prefix in ("DEBUG:__main__:", "INFO:__main__:", "WARNING:__main__:", "ERROR:__main__:"):
+        if line.startswith(prefix):
+            return "   " + line[len(prefix):].strip()
+    return line
+
+
+def _reader(stdout, sink):
+    try:
+        for raw in stdout:
+            sink.put(raw.rstrip("\n"))
+    finally:
+        sink.put(None)
+
+
+def _progress_step(max_samples):
+    if max_samples <= 20:
+        return 1
+    if max_samples <= 100:
+        return 5
+    return 10
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--generator", required=True)
+    parser.add_argument("--output-dir", required=True)
+    parser.add_argument("--max-samples", required=True, type=int)
+    parser.add_argument("generator_args", nargs=argparse.REMAINDER)
+    args = parser.parse_args()
+
+    generator_args = list(args.generator_args)
+    if generator_args and generator_args[0] == "--":
+        generator_args = generator_args[1:]
+
+    cmd = [sys.executable, args.generator, *generator_args]
+    proc = subprocess.Popen(
+        cmd,
+        stdout=subprocess.PIPE,
+        stderr=subprocess.STDOUT,
+        text=True,
+        bufsize=1,
+    )
+    assert proc.stdout is not None
+
+    line_queue = queue.Queue()
+    reader = threading.Thread(target=_reader, args=(proc.stdout, line_queue), daemon=True)
+    reader.start()
+
+    output_dir = Path(args.output_dir)
+    use_sample_progress = _is_onnx_run(generator_args)
+    step = _progress_step(args.max_samples)
+    last_reported = 0
+    stream_done = False
+
+    while not stream_done or proc.poll() is None:
+        try:
+            line = line_queue.get(timeout=0.2)
+        except queue.Empty:
+            line = None
+
+        if line is None:
+            if not stream_done and not line_queue.empty():
+                continue
+            stream_done = proc.poll() is not None or stream_done
+        else:
+            formatted = _format_line(line)
+            if formatted:
+                print(formatted, flush=True)
+
+        if use_sample_progress:
+            current = len(list(output_dir.glob("*.wav")))
+            should_report = current > last_reported and (
+                current >= args.max_samples
+                or current - last_reported >= step
+            )
+            if should_report:
+                print(f"   Generated {current}/{args.max_samples} samples...", flush=True)
+                last_reported = current
+
+    rc = proc.wait()
+    final_count = len(list(output_dir.glob("*.wav"))) if use_sample_progress else 0
+    if use_sample_progress and final_count > last_reported:
+        print(f"   Generated {final_count}/{args.max_samples} samples...", flush=True)
+    return rc
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

cli/wake_word_sample_generator

@@ -138,11 +138,16 @@ export GRPC_VERBOSITY=ERROR
 echo "   Generating samples"
 rm -rf "${SAMPLES_DIR}" || :
 mkdir -p "${SAMPLES_DIR}" || :
-"${PSG}/generate_samples.py" "${WAKE_WORD}" \
+python "${PROGDIR}/run_generator_with_progress.py" \
+    --generator "${PSG}/generate_samples.py" \
+    --output-dir "${SAMPLES_DIR}" \
+    --max-samples ${SAMPLES} \
+    -- \
+    "${WAKE_WORD}" \
     "${MODEL_ARGS[@]}" \
     --max-samples ${SAMPLES} \
     --batch-size ${BATCH_SIZE} \
-    --output-dir "${SAMPLES_DIR}" 2>&1 | sed -r -e "s/(DEBUG|INFO):__main__:/      /g"
+    --output-dir "${SAMPLES_DIR}"
 
 generated_files=$(find "${SAMPLES_DIR}" -name '*.wav' | wc -l)
 if [ "${generated_files}" -ne "${SAMPLES}" ] ; then

dockerfile

@@ -10,7 +10,7 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
  && rm -rf /var/lib/apt/lists/* \
  && mkdir -p /data
 
-# Recorder port
+# Trainer UI port
 EXPOSE 8789
 
 # Script root
@@ -23,7 +23,7 @@ COPY --chown=root:root --chmod=0755 .bashrc /root/
 COPY --chown=root:root --chmod=0755 \
     train_wake_word \
     run_recorder.sh \
-    recorder_server.py \
+    trainer_server.py \
     requirements.txt \
     /root/mww-scripts/
 
@@ -33,8 +33,8 @@ COPY --chown=root:root cli/ /root/mww-scripts/cli/
 # Make all CLI scripts executable (avoids "Permission denied")
 RUN chmod -R a+x /root/mww-scripts/cli
 
-# Static UI for recorder
+# Static UI for trainer
 COPY --chown=root:root --chmod=0644 static/index.html /root/mww-scripts/static/index.html
 
-# recorder server
+# trainer server
 CMD ["/bin/bash", "-lc", "/root/mww-scripts/run_recorder.sh"]

run_recorder.sh

@@ -18,7 +18,7 @@ FASTAPI_VERSION="${REC_FASTAPI_VERSION:-0.115.6}"
 UVICORN_VERSION="${REC_UVICORN_VERSION:-0.30.6}"
 PY_MULTIPART_VERSION="${REC_PY_MULTIPART_VERSION:-0.0.9}"
 
-echo "microWakeWord Recorder (Docker)"
+echo "microWakeWord Trainer UI (Docker)"
 echo "-> ROOTDIR:  ${ROOTDIR}"
 echo "-> DATA_DIR: ${DATA_DIR}"
 echo "-> URL:      http://localhost:${PORT}/"
@@ -26,10 +26,10 @@ echo "-> URL:      http://localhost:${PORT}/"
 mkdir -p "${DATA_DIR}"
 
 # -----------------------------
-# Recorder venv (separate)
+# Trainer UI venv (separate)
 # -----------------------------
 if [[ ! -x "${PY}" ]]; then
-  echo "Creating recorder venv: ${VENV_DIR}"
+  echo "Creating trainer UI venv: ${VENV_DIR}"
   python3 -m venv "${VENV_DIR}"
 fi
 
@@ -37,7 +37,7 @@ fi
 source "${VENV_DIR}/bin/activate"
 
 if [[ ! -f "${PIN_FILE}" ]]; then
-  echo "Installing pinned recorder deps"
+  echo "Installing pinned trainer UI deps"
   ${PIP} install -U pip setuptools wheel
   ${PIP} install \
     "fastapi==${FASTAPI_VERSION}" \
@@ -45,20 +45,20 @@ if [[ ! -f "${PIN_FILE}" ]]; then
     "python-multipart==${PY_MULTIPART_VERSION}"
   touch "${PIN_FILE}"
 else
-  echo "Reusing existing recorder venv (no upgrades)"
+  echo "Reusing existing trainer UI venv (no upgrades)"
 fi
 
 # -----------------------------
-# Recorder server env
+# Trainer server env
 # -----------------------------
 export DATA_DIR="${DATA_DIR}"
 export STATIC_DIR="${ROOTDIR}/static"
 export PERSONAL_DIR="${DATA_DIR}/personal_samples"
 
-# IMPORTANT: leave training venv creation to /api/train inside recorder_server.py
+# IMPORTANT: leave training venv creation to /api/train inside trainer_server.py
 # but still set TRAIN_CMD so the server knows how to invoke training once ready
 export TRAIN_CMD="source '${DATA_DIR}/.venv/bin/activate' && train_wake_word --data-dir='${DATA_DIR}'"
 
 echo "Launching uvicorn on ${HOST}:${PORT}"
 cd "${ROOTDIR}"
-exec "${VENV_DIR}/bin/uvicorn" recorder_server:app --host "${HOST}" --port "${PORT}"
+exec "${VENV_DIR}/bin/uvicorn" trainer_server:app --host "${HOST}" --port "${PORT}"

trainer_server.py

@@ -1,13 +1,18 @@
-# recorder_server.py
+# trainer_server.py
+import io
 import os
 import re
 import json
 import shutil
 import subprocess
+import tempfile
 import threading
+import time
+import wave
 from datetime import datetime
 from pathlib import Path
 from typing import Dict, Any, List, Optional, Tuple
+from urllib.request import Request, urlopen
 
 from fastapi import FastAPI, UploadFile, File, Form
 from fastapi.responses import HTMLResponse, JSONResponse
@@ -26,6 +31,17 @@ PERSONAL_DIR = Path(os.environ.get("PERSONAL_DIR", str(DATA_DIR / "personal_samp
 
 # CLI folder inside repo
 CLI_DIR = Path(os.environ.get("CLI_DIR", str(ROOT_DIR / "cli"))).resolve()
+PIPER_ROOT = DATA_DIR / "tools" / "piper-sample-generator"
+PIPER_VOICES_DIR = PIPER_ROOT / "voices"
+PIPER_VOICES_INDEX_URL = os.environ.get(
+    "PIPER_VOICES_INDEX_URL",
+    "https://huggingface.co/rhasspy/piper-voices/raw/main/voices.json",
+)
+PIPER_VOICES_ROOT_URL = os.environ.get(
+    "PIPER_VOICES_ROOT_URL",
+    "https://huggingface.co/rhasspy/piper-voices/resolve/main",
+)
+PIPER_CATALOG_CACHE_TTL_SECONDS = int(os.environ.get("PIPER_CATALOG_CACHE_TTL_SECONDS", "900"))
 
 DATASET_CLEANUP_ARCHIVES = os.environ.get("REC_DATASET_CLEANUP_ARCHIVES", "false").lower() in ("1", "true", "yes", "y")
 DATASET_CLEANUP_INTERMEDIATE = os.environ.get("REC_DATASET_CLEANUP_INTERMEDIATE_FILES", "false").lower() in ("1", "true", "yes", "y")
@@ -39,13 +55,16 @@ DEFAULT_LANGUAGE = os.environ.get("MWW_LANGUAGE", "en")
 
 TAKES_PER_SPEAKER_DEFAULT = int(os.environ.get("REC_TAKES_PER_SPEAKER", "10"))
 SPEAKERS_TOTAL_DEFAULT = int(os.environ.get("REC_SPEAKERS_TOTAL", "1"))
+TARGET_SAMPLE_RATE = 16000
+TARGET_CHANNELS = 1
+TARGET_SAMPLE_WIDTH_BYTES = 2
 
 # Tail lines shown to UI
 TRAIN_LOG_TAIL_LINES = int(os.environ.get("REC_TRAIN_LOG_TAIL_LINES", "400"))
 # Safety cap for reads (bytes) to avoid giant file reads
 TRAIN_LOG_MAX_BYTES = int(os.environ.get("REC_TRAIN_LOG_MAX_BYTES", str(512 * 1024)))  # 512KB
 
-app = FastAPI(title="microWakeWord Personal Recorder")
+app = FastAPI(title="microWakeWord Personal Samples")
 
 STATIC_DIR.mkdir(parents=True, exist_ok=True)
 app.mount("/static", StaticFiles(directory=str(STATIC_DIR)), name="static")
@@ -84,6 +103,12 @@ STATE: Dict[str, Any] = {
 }
 
 STATE_LOCK = threading.Lock()
+SAMPLES_LOCK = threading.Lock()
+PIPER_CATALOG_LOCK = threading.Lock()
+PIPER_CATALOG_CACHE: Dict[str, Any] = {
+    "fetched_at": 0.0,
+    "entries": None,
+}
 
 
 def _reset_personal_samples_dir():
@@ -95,6 +120,362 @@ def _reset_personal_samples_dir():
             pass
 
 
+
+def _list_personal_samples() -> List[str]:
+    PERSONAL_DIR.mkdir(parents=True, exist_ok=True)
+    return sorted(p.name for p in PERSONAL_DIR.glob("*.wav"))
+
+
+def _sync_personal_samples_state() -> List[str]:
+    takes = _list_personal_samples()
+    with STATE_LOCK:
+        STATE["takes"] = takes
+        STATE["takes_received"] = len(takes)
+    return takes
+
+
+def _registered_language_family(language: Dict[str, Any]) -> str:
+    family = str(language.get("family") or "").strip().lower()
+    if family:
+        return family
+    code = str(language.get("code") or "").strip()
+    return code.split("_", 1)[0].lower() if code else ""
+
+
+def _register_language(
+    languages: Dict[str, Dict[str, Any]],
+    *,
+    family: str,
+    name: str,
+    region: str = "",
+    count: int = 1,
+):
+    if not family:
+        return
+    entry = languages.setdefault(
+        family,
+        {
+            "code": family,
+            "label": f"{name} ({family})",
+            "name": name,
+            "voice_count": 0,
+            "regions": [],
+        },
+    )
+    entry["voice_count"] += count
+    if region and region not in entry["regions"]:
+        entry["regions"].append(region)
+
+
+def _fetch_piper_catalog() -> Optional[Dict[str, Any]]:
+    req = Request(
+        PIPER_VOICES_INDEX_URL,
+        headers={"User-Agent": "microWakeWord-Trainer/1.0"},
+    )
+    with urlopen(req, timeout=15) as resp:
+        data = json.loads(resp.read().decode("utf-8"))
+    return data if isinstance(data, dict) else None
+
+
+def _load_piper_catalog() -> Optional[Dict[str, Any]]:
+    now = time.time()
+    with PIPER_CATALOG_LOCK:
+        cached = PIPER_CATALOG_CACHE.get("entries")
+        fetched_at = float(PIPER_CATALOG_CACHE.get("fetched_at") or 0.0)
+        if cached is not None and (now - fetched_at) < PIPER_CATALOG_CACHE_TTL_SECONDS:
+            return cached
+
+    try:
+        fresh = _fetch_piper_catalog()
+    except Exception:
+        fresh = None
+
+    with PIPER_CATALOG_LOCK:
+        if fresh is not None:
+            PIPER_CATALOG_CACHE["entries"] = fresh
+            PIPER_CATALOG_CACHE["fetched_at"] = now
+            return fresh
+        if PIPER_CATALOG_CACHE.get("entries") is None:
+            PIPER_CATALOG_CACHE["entries"] = {}
+        PIPER_CATALOG_CACHE["fetched_at"] = now
+        return PIPER_CATALOG_CACHE.get("entries")
+
+
+def _available_languages() -> List[Dict[str, Any]]:
+    languages: Dict[str, Dict[str, Any]] = {
+        "en": {
+            "code": "en",
+            "label": "English (en)",
+            "name": "English",
+            "voice_count": 1,
+            "regions": [],
+        }
+    }
+
+    if PIPER_VOICES_DIR.exists():
+        for meta_path in sorted(PIPER_VOICES_DIR.glob("*.onnx.json")):
+            try:
+                data = json.loads(meta_path.read_text(encoding="utf-8"))
+            except Exception:
+                continue
+
+            language = data.get("language") or {}
+            family = _registered_language_family(language)
+            if not family or family == "en":
+                continue
+
+            name = str(language.get("name_english") or language.get("name_native") or family.upper()).strip()
+            region = str(language.get("country_english") or language.get("region") or "").strip()
+            _register_language(languages, family=family, name=name, region=region, count=1)
+
+    catalog = _load_piper_catalog() or {}
+    for entry in catalog.values():
+        if not isinstance(entry, dict):
+            continue
+        language = entry.get("language") or {}
+        family = _registered_language_family(language)
+        if not family or family == "en":
+            continue
+        name = str(language.get("name_english") or language.get("name_native") or family.upper()).strip()
+        region = str(language.get("country_english") or language.get("region") or "").strip()
+        _register_language(languages, family=family, name=name, region=region, count=0)
+
+    ordered = [languages["en"]]
+    ordered.extend(
+        sorted(
+            (entry for code, entry in languages.items() if code != "en"),
+            key=lambda entry: (entry["name"].lower(), entry["code"]),
+        )
+    )
+    return ordered
+
+
+def _normalize_language(language: str | None) -> str:
+    requested = (language or DEFAULT_LANGUAGE).strip().lower() or DEFAULT_LANGUAGE
+    available_codes = {item["code"] for item in _available_languages()}
+    if requested in available_codes:
+        return requested
+    if DEFAULT_LANGUAGE in available_codes:
+        return DEFAULT_LANGUAGE
+    return "en"
+
+
+def _catalog_voice_files(language_family: str) -> List[Tuple[str, str]]:
+    if not language_family or language_family == "en":
+        return []
+
+    downloads: Dict[str, str] = {}
+    catalog = _load_piper_catalog() or {}
+    for entry in catalog.values():
+        if not isinstance(entry, dict):
+            continue
+        language = entry.get("language") or {}
+        family = _registered_language_family(language)
+        if family != language_family:
+            continue
+        files = entry.get("files") or {}
+        for rel_path in files.keys():
+            if not isinstance(rel_path, str):
+                continue
+            if not (rel_path.endswith(".onnx") or rel_path.endswith(".onnx.json")):
+                continue
+            downloads[Path(rel_path).name] = f"{PIPER_VOICES_ROOT_URL}/{rel_path}?download=true"
+
+    return sorted(downloads.items(), key=lambda item: item[0])
+
+
+def _download_to_path(url: str, dest_path: Path):
+    dest_path.parent.mkdir(parents=True, exist_ok=True)
+    tmp_path = dest_path.with_suffix(dest_path.suffix + ".tmp")
+    req = Request(url, headers={"User-Agent": "microWakeWord-Trainer/1.0"})
+    with urlopen(req, timeout=60) as resp, open(tmp_path, "wb") as out:
+        shutil.copyfileobj(resp, out)
+    tmp_path.replace(dest_path)
+
+
+def _ensure_non_english_language_voices(language_family: str, log) -> Dict[str, int]:
+    downloads = _catalog_voice_files(language_family)
+    local_voices = sorted(PIPER_VOICES_DIR.glob(f"{language_family}_*.onnx")) if PIPER_VOICES_DIR.exists() else []
+    if not downloads:
+        if local_voices:
+            log(f"===== Piper Voices ({language_family}) =====")
+            log(f"→ Using {len(local_voices)} installed voice(s) for language '{language_family}'")
+            return {
+                "downloaded_files": 0,
+                "existing_files": len(local_voices),
+                "voices": len(local_voices),
+            }
+        raise RuntimeError(
+            f"No Piper ONNX voices found for language '{language_family}' in the upstream catalog."
+        )
+
+    PIPER_VOICES_DIR.mkdir(parents=True, exist_ok=True)
+
+    downloaded_files = 0
+    existing_files = 0
+    voice_names = sorted(name for name, _ in downloads if name.endswith(".onnx"))
+
+    log(f"===== Piper Voices ({language_family}) =====")
+    log(f"→ Ensuring {len(voice_names)} voice(s) for language '{language_family}'")
+
+    for file_name, url in downloads:
+        dest_path = PIPER_VOICES_DIR / file_name
+        if dest_path.exists() and dest_path.stat().st_size > 0:
+            existing_files += 1
+            continue
+        log(f"→ Downloading {file_name}")
+        _download_to_path(url, dest_path)
+        downloaded_files += 1
+
+    log(
+        f"✓ Piper voices ready for '{language_family}' "
+        f"({downloaded_files} file(s) downloaded, {existing_files} already present)"
+    )
+    return {
+        "downloaded_files": downloaded_files,
+        "existing_files": existing_files,
+        "voices": len(voice_names),
+    }
+
+
+def _find_ffmpeg() -> Optional[str]:
+    candidates = [
+        shutil.which("ffmpeg"),
+        "/usr/bin/ffmpeg",
+        "/usr/local/bin/ffmpeg",
+        "/opt/homebrew/bin/ffmpeg",
+        "/opt/homebrew/opt/ffmpeg@7/bin/ffmpeg",
+        "/opt/homebrew/opt/ffmpeg/bin/ffmpeg",
+    ]
+    for candidate in candidates:
+        if candidate and Path(candidate).exists():
+            return candidate
+    return None
+
+
+def _inspect_wav_bytes(data: bytes) -> Optional[Dict[str, Any]]:
+    try:
+        with wave.open(io.BytesIO(data), "rb") as wf:
+            frames = wf.getnframes()
+            rate = wf.getframerate()
+            duration = (frames / rate) if rate else 0.0
+            return {
+                "container": "wav",
+                "sample_rate": rate,
+                "channels": wf.getnchannels(),
+                "sample_width_bits": wf.getsampwidth() * 8,
+                "compression": wf.getcomptype(),
+                "frames": frames,
+                "duration_s": round(duration, 3),
+            }
+    except Exception:
+        return None
+
+
+def _is_target_wav(info: Optional[Dict[str, Any]]) -> bool:
+    return bool(
+        info
+        and info.get("container") == "wav"
+        and info.get("sample_rate") == TARGET_SAMPLE_RATE
+        and info.get("channels") == TARGET_CHANNELS
+        and info.get("sample_width_bits") == TARGET_SAMPLE_WIDTH_BYTES * 8
+        and info.get("compression") == "NONE"
+        and info.get("frames", 0) > 0
+    )
+
+
+def _next_personal_sample_name(original_name: str) -> str:
+    current = _list_personal_samples()
+    next_index = 1
+    for name in current:
+        match = re.match(r"sample_(\d{4})", name)
+        if match:
+            next_index = max(next_index, int(match.group(1)) + 1)
+
+    stem = safe_name(Path(original_name or "sample").stem)
+    suffix = f"_{stem[:32]}" if stem and stem != "wakeword" else ""
+    return f"sample_{next_index:04d}{suffix}.wav"
+
+
+def _format_hint_from_filename(original_name: str) -> Dict[str, Any]:
+    suffix = (Path(original_name or "").suffix or "").lower().lstrip(".")
+    return {
+        "container": suffix or "unknown",
+        "sample_rate": None,
+        "channels": None,
+        "sample_width_bits": None,
+        "compression": None,
+        "frames": None,
+        "duration_s": None,
+    }
+
+
+def _normalize_audio_to_target_wav(data: bytes, original_name: str) -> bytes:
+    ffmpeg = _find_ffmpeg()
+    if not ffmpeg:
+        raise RuntimeError(
+            "ffmpeg is required to convert uploads that are not already 16 kHz mono 16-bit PCM WAV."
+        )
+
+    suffix = (Path(original_name or "").suffix or ".audio")
+    with tempfile.TemporaryDirectory(prefix="mww_upload_") as tmpdir:
+        src_path = Path(tmpdir) / f"source{suffix}"
+        dst_path = Path(tmpdir) / "normalized.wav"
+        src_path.write_bytes(data)
+
+        cmd = [
+            ffmpeg,
+            "-y",
+            "-i",
+            str(src_path),
+            "-vn",
+            "-ac",
+            str(TARGET_CHANNELS),
+            "-ar",
+            str(TARGET_SAMPLE_RATE),
+            "-c:a",
+            "pcm_s16le",
+            str(dst_path),
+        ]
+        proc = subprocess.run(cmd, capture_output=True, text=True)
+        if proc.returncode != 0 or not dst_path.exists():
+            err = (proc.stderr or proc.stdout or "ffmpeg conversion failed").strip()
+            raise RuntimeError(err.splitlines()[-1] if err else "ffmpeg conversion failed")
+
+        return dst_path.read_bytes()
+
+
+def _save_personal_sample(data: bytes, original_name: str, out_name: Optional[str] = None) -> Dict[str, Any]:
+    if not data:
+        raise ValueError("Empty or invalid audio file.")
+
+    original_info = _inspect_wav_bytes(data) or _format_hint_from_filename(original_name)
+    normalized = _is_target_wav(original_info)
+    final_bytes = data if normalized else _normalize_audio_to_target_wav(data, original_name)
+    final_info = _inspect_wav_bytes(final_bytes)
+
+    if not _is_target_wav(final_info):
+        raise ValueError("Uploaded audio could not be normalized to 16 kHz mono 16-bit PCM WAV.")
+
+    with SAMPLES_LOCK:
+        PERSONAL_DIR.mkdir(parents=True, exist_ok=True)
+        final_name = out_name or _next_personal_sample_name(original_name)
+        out_path = PERSONAL_DIR / final_name
+        out_path.write_bytes(final_bytes)
+
+    return {
+        "saved_as": final_name,
+        "converted": not normalized,
+        "original_name": original_name or final_name,
+        "detected_format": original_info,
+        "final_format": final_info,
+        "message": (
+            "Converted to 16 kHz mono 16-bit PCM WAV"
+            if not normalized
+            else "Already in the correct 16 kHz mono 16-bit PCM WAV format"
+        ),
+    }
+
 def _clear_training_log():
     """
     Truncate recorder_training.log for a fresh session.
@@ -405,6 +786,8 @@ def _run_training_background(safe_word: str, allow_no_personal: bool):
     try:
         _ensure_training_venv(log_path)
         _ensure_training_datasets(log_path)
+        if language != "en":
+            _ensure_non_english_language_voices(language, _append_train_log)
 
         if wake_word_title:
             cmd_str = f"{TRAIN_CMD} --language='{language}' '{safe_word}' '{wake_word_title}'"
@@ -474,7 +857,8 @@ def start_session(payload: Dict[str, Any]):
 
     speakers_total = int(payload.get("speakers_total") or SPEAKERS_TOTAL_DEFAULT)
     takes_per_speaker = int(payload.get("takes_per_speaker") or TAKES_PER_SPEAKER_DEFAULT)
-    language = (payload.get("language") or DEFAULT_LANGUAGE).strip().lower()
+    language = _normalize_language(payload.get("language"))
+    available_languages = _available_languages()
 
     speakers_total = max(1, min(10, speakers_total))
     takes_per_speaker = max(1, min(50, takes_per_speaker))
@@ -485,10 +869,8 @@ def start_session(payload: Dict[str, Any]):
         STATE["language"] = language
         STATE["speakers_total"] = speakers_total
         STATE["takes_per_speaker"] = takes_per_speaker
-        STATE["takes_received"] = 0
-        STATE["takes"] = []
 
-    _reset_personal_samples_dir()
+    takes = _sync_personal_samples_state()
 
     # Always wipe log on start_session (even if same wakeword)
     _clear_training_log()
@@ -501,6 +883,9 @@ def start_session(payload: Dict[str, Any]):
         "speakers_total": speakers_total,
         "takes_per_speaker": takes_per_speaker,
         "takes_total": speakers_total * takes_per_speaker,
+        "takes_received": len(takes),
+        "takes": takes,
+        "available_languages": available_languages,
         "personal_dir": str(PERSONAL_DIR),
         "data_dir": str(DATA_DIR),
     }
@@ -508,17 +893,22 @@ def start_session(payload: Dict[str, Any]):
 
 @app.get("/api/session")
 def get_session():
+    takes = _sync_personal_samples_state()
+    available_languages = _available_languages()
     with STATE_LOCK:
+        current_language = _normalize_language(STATE["language"])
+        STATE["language"] = current_language
         return {
             "ok": True,
             "raw_phrase": STATE["raw_phrase"],
             "safe_word": STATE["safe_word"],
-            "language": STATE["language"],
+            "language": current_language,
             "speakers_total": STATE["speakers_total"],
             "takes_per_speaker": STATE["takes_per_speaker"],
-            "takes_received": STATE["takes_received"],
-            "takes": list(STATE["takes"]),
+            "takes_received": len(takes),
+            "takes": list(takes),
             "training": dict(STATE["training"]),
+            "available_languages": available_languages,
         }
 
 
@@ -542,23 +932,34 @@ async def upload_take(
     if take_index < 1 or take_index > takes_per_speaker:
         return JSONResponse({"ok": False, "error": f"take_index must be 1..{takes_per_speaker}"}, status_code=400)
 
-    PERSONAL_DIR.mkdir(parents=True, exist_ok=True)
-
     out_name = f"speaker{speaker_index:02d}_take{take_index:02d}.wav"
-    out_path = PERSONAL_DIR / out_name
 
     data = await file.read()
-    if not data or len(data) < 44:
-        return JSONResponse({"ok": False, "error": "Empty/invalid file"}, status_code=400)
+    try:
+        result = _save_personal_sample(data, file.filename or out_name, out_name=out_name)
+    except Exception as e:
+        return JSONResponse({"ok": False, "error": str(e)}, status_code=400)
 
-    out_path.write_bytes(data)
+    takes = _sync_personal_samples_state()
+    return {"ok": True, **result, "takes_received": len(takes)}
 
+
+@app.post("/api/upload_personal_sample")
+async def upload_personal_sample(file: UploadFile = File(...)):
     with STATE_LOCK:
-        if out_name not in STATE["takes"]:
-            STATE["takes"].append(out_name)
-            STATE["takes_received"] = len(STATE["takes"])
+        safe_word = STATE["safe_word"]
 
-    return {"ok": True, "saved_as": out_name, "takes_received": STATE["takes_received"]}
+    if not safe_word:
+        return JSONResponse({"ok": False, "error": "No active session. Call /api/start_session first."}, status_code=400)
+
+    data = await file.read()
+    try:
+        result = _save_personal_sample(data, file.filename or "sample")
+    except Exception as e:
+        return JSONResponse({"ok": False, "error": str(e)}, status_code=400)
+
+    takes = _sync_personal_samples_state()
+    return {"ok": True, **result, "takes_received": len(takes)}
 
 
 @app.post("/api/train")
@@ -581,27 +982,13 @@ def train_now(payload: Dict[str, Any] = None):
     if not safe_word:
         return JSONResponse({"ok": False, "error": "No active session"}, status_code=400)
 
-    min_required = max(1, min(3, takes_total))
-
     if takes_received == 0 and not allow_no_personal:
         return JSONResponse(
             {
                 "ok": False,
-                "error": f"No personal voice samples recorded (0/{takes_total}).",
+                "error": "No personal voice samples uploaded yet.",
                 "code": "NO_PERSONAL_SAMPLES",
-                "message": "You can train without personal voices, or record samples first.",
-                "takes_total": takes_total,
-            },
-            status_code=400,
-        )
-
-    if 0 < takes_received < min_required:
-        return JSONResponse(
-            {
-                "ok": False,
-                "error": f"Not enough takes yet ({takes_received}/{takes_total}).",
-                "code": "NOT_ENOUGH_TAKES",
-                "min_required": min_required,
+                "message": "You can train without personal voices, or upload samples first.",
                 "takes_total": takes_total,
             },
             status_code=400,
@@ -614,7 +1001,7 @@ def train_now(payload: Dict[str, Any] = None):
         "ok": True,
         "started": True,
         "safe_word": safe_word,
-        "personal_samples_used": takes_received >= min_required,
+        "personal_samples_used": takes_received > 0,
         "allow_no_personal": allow_no_personal,
     }
 
@@ -656,13 +1043,12 @@ def train_status():
 
     tr["log_text"] = "\n".join(new_lines)  # ONLY new lines
     tr["log_tail_preview"] = "\n".join(full_tail)  # optional: handy for debugging
+    tr["log_lines"] = full_tail
     return {"ok": True, "training": tr}
 
 
 @app.post("/api/reset_recordings")
 def reset_recordings():
     _reset_personal_samples_dir()
-    with STATE_LOCK:
-        STATE["takes_received"] = 0
-        STATE["takes"] = []
-    return {"ok": True}
+    takes = _sync_personal_samples_state()
+    return {"ok": True, "takes_received": len(takes), "takes": takes}