fix: voice STT path fix + execSync error handling + fetch download
This commit is contained in:
108
scripts/stt.py
108
scripts/stt.py
@@ -1,83 +1,70 @@
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#!/usr/bin/env python3
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"""
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Vosk STT — Transcribe OGG/voice to text.
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Usage: python3 stt.py <input_file> [language]
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input_file: path to audio file (ogg, wav, mp3, etc.)
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language: 'en' (default) or 'ge' — Georgian model
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Output: JSON to stdout: {"text": "...", "confidence": 0.95}
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Exit codes: 0=success, 1=no speech, 2=error
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"""
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"""Vosk STT — transcribe audio file to text. Optimized for speed."""
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import sys, os, json, subprocess, tempfile, wave
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os.environ['VOSK_LOG_LEVEL'] = '-1'
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def main():
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if len(sys.argv) < 2:
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print(json.dumps({"error": "Usage: stt.py <audio_file> [en|ge]"}))
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print(json.dumps({"error": "Usage: stt.py <audio_file>"}))
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sys.exit(2)
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audio_file = sys.argv[1]
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lang = sys.argv[2] if len(sys.argv) > 2 else 'en'
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model_path = '/home/uroma2/vosk-model'
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# Suppress vosk logging
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os.environ['VOSK_LOG_LEVEL'] = '-1'
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model_path = {
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'en': '/home/uroma2/vosk-model',
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'ge': '/home/uroma2/vosk-model-ge',
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}.get(lang, '/home/uroma2/vosk-model')
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if not os.path.isdir(model_path):
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print(json.dumps({"error": f"Model not found: {model_path}"}))
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# Convert to 16kHz mono WAV via ffmpeg — fast pipe, no temp file overhead
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try:
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proc = subprocess.Popen(
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['ffmpeg', '-y', '-i', audio_file, '-ar', '16000', '-ac', '1',
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'-f', 'wav', '-v', 'error', '-'],
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stdout=subprocess.PIPE, stderr=subprocess.PIPE
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)
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wav_data = proc.stdout.read()
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proc.wait(timeout=15)
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if proc.returncode != 0 or len(wav_data) < 44:
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print(json.dumps({"error": "ffmpeg conversion failed"}))
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sys.exit(2)
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except Exception as e:
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print(json.dumps({"error": str(e)}))
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sys.exit(2)
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# Convert to 16kHz mono WAV using ffmpeg
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with tempfile.NamedTemporaryFile(suffix='.wav', delete=False) as tmp:
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wav_path = tmp.name
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# Write wav_data to temp file for wave module (it needs a file path)
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tmp = tempfile.NamedTemporaryFile(suffix='.wav', delete=False)
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try:
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result = subprocess.run(
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['ffmpeg', '-y', '-i', audio_file, '-ar', '16000', '-ac', '1', '-f', 'wav', wav_path],
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capture_output=True, timeout=30
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)
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if result.returncode != 0:
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print(json.dumps({"error": f"ffmpeg failed: {result.stderr.decode()[:200]}"}))
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sys.exit(2)
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tmp.write(wav_data)
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tmp.close()
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import vosk
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model = vosk.Model(model_path)
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rec = vosk.KaldiRecognizer(model, 16000)
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wf = wave.open(wav_path, 'rb')
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if wf.getnchannels() != 1 or wf.getsampwidth() != 2 or wf.getframerate() != 16000:
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print(json.dumps({"error": "Audio format mismatch after conversion"}))
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sys.exit(2)
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results = []
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while True:
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data = wf.readframes(4000)
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if len(data) == 0:
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break
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if rec.AcceptWaveform(data):
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results.append(json.loads(rec.Result()))
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# Final result
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final = json.loads(rec.FinalResult())
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results.append(final)
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# Extract text
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wf = wave.open(tmp.name, 'rb')
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text_parts = []
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total_conf = 0
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conf_count = 0
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for r in results:
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t = r.get('text', '').strip()
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if t:
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text_parts.append(t)
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# Confidence from final result
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if 'result' in r:
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for word in r.get('result', []):
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if 'conf' in word:
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total_conf += word['conf']
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while True:
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data = wf.readframes(4000)
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if not data:
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break
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if rec.AcceptWaveform(data):
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r = json.loads(rec.Result())
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t = r.get('text', '').strip()
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if t:
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text_parts.append(t)
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for w in r.get('result', []):
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total_conf += w.get('conf', 0)
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conf_count += 1
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# Final partial
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r = json.loads(rec.FinalResult())
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t = r.get('text', '').strip()
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if t:
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text_parts.append(t)
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for w in r.get('result', []):
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total_conf += w.get('conf', 0)
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conf_count += 1
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text = ' '.join(text_parts).strip()
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confidence = round(total_conf / conf_count, 2) if conf_count > 0 else 0.0
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@@ -86,13 +73,12 @@ def main():
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sys.exit(1)
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print(json.dumps({"text": text, "confidence": confidence}))
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except Exception as e:
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print(json.dumps({"error": str(e)}))
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sys.exit(2)
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finally:
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if os.path.exists(wav_path):
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os.unlink(wav_path)
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try: os.unlink(tmp.name)
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except: pass
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if __name__ == '__main__':
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main()
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@@ -1088,21 +1088,36 @@ export async function initBot(config, api, tools, skills, agents) {
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const url = `https://api.telegram.org/file/bot${botToken}/${file.file_path}`;
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const oggPath = `/tmp/zcode-voice-${Date.now()}.ogg`;
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// Download voice file
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// Download voice file via fetch (faster than curl subprocess)
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const { execSync } = await import('child_process');
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execSync(`curl -sL "${url}" -o "${oggPath}"`, { timeout: 15000 });
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const voiceResp = await fetch(url);
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if (!voiceResp.ok) throw new Error(`Download failed: ${voiceResp.status}`);
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const { writeFileSync, unlinkSync } = await import('fs');
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writeFileSync(oggPath, Buffer.from(await voiceResp.arrayBuffer()));
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logger.info(`Voice downloaded: ${oggPath}`);
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// Run Vosk STT via Python script
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const sttScript = new URL('../scripts/stt.py', import.meta.url).pathname;
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const result = execSync(
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`python3 "${sttScript}" "${oggPath}" 2>/dev/null`,
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{ timeout: 30000, encoding: 'utf-8' }
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);
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const parsed = JSON.parse(result.trim());
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// Cleanup
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execSync(`rm -f "${oggPath}"`);
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// Run Vosk STT — path is ../../scripts/stt.py from src/bot/
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const sttScript = new URL('../../scripts/stt.py', import.meta.url).pathname;
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let parsed;
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try {
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const result = execSync(
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`python3 "${sttScript}" "${oggPath}"`,
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{ timeout: 30000, encoding: 'utf-8', stdio: ['pipe', 'pipe', 'pipe'] }
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);
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parsed = JSON.parse(result.trim());
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} catch (e) {
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// exit code 1 = no speech detected, stdout still has JSON
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const stdout = e.stdout?.trim();
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if (stdout) {
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try { parsed = JSON.parse(stdout); } catch { parsed = null; }
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}
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if (!parsed || !parsed.text) {
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await ctx.api.editMessageText(ctx.chat.id, statusMsg.message_id,
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'🎤 Could not detect speech in the voice message.');
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return;
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}
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}
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unlinkSync(oggPath);
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if (parsed.error) {
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logger.error(`STT error: ${parsed.error}`);
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