Spaces:
Sleeping
Sleeping
Update asr-tts_service.py
Browse files- asr-tts_service.py +16 -24
asr-tts_service.py
CHANGED
|
@@ -6,7 +6,7 @@ import logging
|
|
| 6 |
import numpy as np
|
| 7 |
import soundfile as sf
|
| 8 |
import torch
|
| 9 |
-
|
| 10 |
import requests
|
| 11 |
import tempfile
|
| 12 |
from flask import Flask, request, jsonify
|
|
@@ -14,17 +14,16 @@ from transformers import pipeline, AutoTokenizer
|
|
| 14 |
from parler_tts import ParlerTTSForConditionalGeneration
|
| 15 |
from pydub import AudioSegment
|
| 16 |
from dotenv import load_dotenv
|
| 17 |
-
from concurrent.futures import ThreadPoolExecutor
|
| 18 |
|
| 19 |
|
| 20 |
|
| 21 |
# Charger les variables d'environnement
|
| 22 |
load_dotenv()
|
| 23 |
|
| 24 |
-
# Configuration Gemini
|
| 25 |
google_api = os.getenv('GOOGLE_API_KEY')
|
| 26 |
-
|
| 27 |
-
|
| 28 |
|
| 29 |
# Configuration générale
|
| 30 |
device = "cpu"
|
|
@@ -77,19 +76,16 @@ def number_to_french(n: int) -> str:
|
|
| 77 |
if n == 80: return base
|
| 78 |
return base + "-" + number_to_french(n - 80)
|
| 79 |
|
| 80 |
-
# GESTION DES CENTAINES
|
| 81 |
if n < 1000:
|
| 82 |
hundreds, rest = divmod(n, 100)
|
| 83 |
base = "cent" if hundreds == 1 else UNITS.get(hundreds, str(hundreds)) + " cent"
|
| 84 |
return base if rest == 0 else base + " " + number_to_french(rest)
|
| 85 |
|
| 86 |
-
# GESTION DES MILLIERS ET PLUS (Sécurité pour éviter le KeyError)
|
| 87 |
if n < 1000000:
|
| 88 |
thousands, rest = divmod(n, 1000)
|
| 89 |
base = "mille" if thousands == 1 else number_to_french(thousands) + " mille"
|
| 90 |
return base if rest == 0 else base + " " + number_to_french(rest)
|
| 91 |
|
| 92 |
-
# Par sécurité, si le nombre est trop grand (millions), on le renvoie tel quel
|
| 93 |
return str(n)
|
| 94 |
|
| 95 |
def convert_digits_in_text(text: str) -> str:
|
|
@@ -97,11 +93,8 @@ def convert_digits_in_text(text: str) -> str:
|
|
| 97 |
|
| 98 |
def repl(match):
|
| 99 |
s = match.group(0)
|
| 100 |
-
# On épèle : "7 7 1 2 3..." au lieu de "Sept milliards..."
|
| 101 |
if len(s) > 4:
|
| 102 |
return " ".join([UNITS.get(int(digit), digit) for digit in s])
|
| 103 |
-
|
| 104 |
-
# SINON (Petit nombre comme 15, 100, 2024)
|
| 105 |
try:
|
| 106 |
val = int(s)
|
| 107 |
return number_to_french(val)
|
|
@@ -162,7 +155,7 @@ def generate_tts_optimized(text: str) -> str:
|
|
| 162 |
prompt_input_ids=prompt_ids,
|
| 163 |
max_new_tokens=2048,
|
| 164 |
do_sample=True,
|
| 165 |
-
temperature=
|
| 166 |
min_new_tokens=20
|
| 167 |
)
|
| 168 |
audio_np = audio.cpu().numpy().squeeze().astype(np.float32)
|
|
@@ -189,7 +182,10 @@ def french_to_wolof_with_gemini(text: str) -> str:
|
|
| 189 |
Texte : {text}"""
|
| 190 |
|
| 191 |
try:
|
| 192 |
-
response =
|
|
|
|
|
|
|
|
|
|
| 193 |
return response.text.strip()
|
| 194 |
except Exception as e:
|
| 195 |
return f"Erreur de traduction : {str(e)}"
|
|
@@ -205,7 +201,10 @@ def wolof_to_french_gemini(text: str) -> str:
|
|
| 205 |
|
| 206 |
Texte : {text}"""
|
| 207 |
try:
|
| 208 |
-
response =
|
|
|
|
|
|
|
|
|
|
| 209 |
return response.text.strip()
|
| 210 |
except Exception as e:
|
| 211 |
return 'Bonjour'
|
|
@@ -237,36 +236,30 @@ def transcribe_from_url():
|
|
| 237 |
if not audio_url: return "Bonjour", 400
|
| 238 |
|
| 239 |
try:
|
| 240 |
-
# Téléchargement du fichier
|
| 241 |
resp = requests.get(audio_url, stream=True)
|
| 242 |
if resp.status_code != 200:
|
| 243 |
logger.error(f"Erreur téléchargement audio: {resp.status_code}")
|
| 244 |
return "Bonjour"
|
| 245 |
|
| 246 |
-
# Utilisation d'un fichier temporaire sécurisé
|
| 247 |
with tempfile.NamedTemporaryFile(suffix=".ogg", delete=False) as tmp:
|
| 248 |
tmp.write(resp.content)
|
| 249 |
-
tmp.flush()
|
| 250 |
-
os.fsync(tmp.fileno())
|
| 251 |
tmp_path = tmp.name
|
| 252 |
|
| 253 |
try:
|
| 254 |
-
# Conversion via pydub (ffmpeg)
|
| 255 |
audio = AudioSegment.from_file(tmp_path)
|
| 256 |
wav_io = io.BytesIO()
|
| 257 |
audio.set_frame_rate(16000).set_channels(1).export(wav_io, format="wav")
|
| 258 |
wav_io.seek(0)
|
| 259 |
|
| 260 |
-
# Lecture des données audio
|
| 261 |
data, sr = sf.read(wav_io)
|
| 262 |
data = np.asarray(data, dtype=np.float32)
|
| 263 |
if data.ndim > 1: data = data.mean(axis=1)
|
| 264 |
|
| 265 |
-
# Traitement ASR
|
| 266 |
wolof_text = asr(normalize_audio(data))["text"]
|
| 267 |
|
| 268 |
finally:
|
| 269 |
-
# Nettoyage du fichier temporaire même en cas d'erreur de décodage
|
| 270 |
if os.path.exists(tmp_path):
|
| 271 |
os.remove(tmp_path)
|
| 272 |
|
|
@@ -277,7 +270,6 @@ def transcribe_from_url():
|
|
| 277 |
|
| 278 |
except Exception as e:
|
| 279 |
logger.error(f"Erreur WhatsApp ASR: {e}")
|
| 280 |
-
# Log supplémentaire pour débugger ffmpeg si l'erreur persiste
|
| 281 |
return "Bonjour"
|
| 282 |
|
| 283 |
@app.route("/tts", methods=["POST"])
|
|
@@ -291,4 +283,4 @@ def tts():
|
|
| 291 |
return jsonify({"wolof_text": wolof_text, "audio": audio_base64})
|
| 292 |
|
| 293 |
if __name__ == "__main__":
|
| 294 |
-
app.run(host="0.0.0.0", port=7860)
|
|
|
|
| 6 |
import numpy as np
|
| 7 |
import soundfile as sf
|
| 8 |
import torch
|
| 9 |
+
from google import genai as google_genai
|
| 10 |
import requests
|
| 11 |
import tempfile
|
| 12 |
from flask import Flask, request, jsonify
|
|
|
|
| 14 |
from parler_tts import ParlerTTSForConditionalGeneration
|
| 15 |
from pydub import AudioSegment
|
| 16 |
from dotenv import load_dotenv
|
|
|
|
| 17 |
|
| 18 |
|
| 19 |
|
| 20 |
# Charger les variables d'environnement
|
| 21 |
load_dotenv()
|
| 22 |
|
| 23 |
+
# Configuration Gemini (nouveau SDK google-genai)
|
| 24 |
google_api = os.getenv('GOOGLE_API_KEY')
|
| 25 |
+
gemini_client = google_genai.Client(api_key=google_api)
|
| 26 |
+
GEMINI_MODEL = "gemini-2.5-flash"
|
| 27 |
|
| 28 |
# Configuration générale
|
| 29 |
device = "cpu"
|
|
|
|
| 76 |
if n == 80: return base
|
| 77 |
return base + "-" + number_to_french(n - 80)
|
| 78 |
|
|
|
|
| 79 |
if n < 1000:
|
| 80 |
hundreds, rest = divmod(n, 100)
|
| 81 |
base = "cent" if hundreds == 1 else UNITS.get(hundreds, str(hundreds)) + " cent"
|
| 82 |
return base if rest == 0 else base + " " + number_to_french(rest)
|
| 83 |
|
|
|
|
| 84 |
if n < 1000000:
|
| 85 |
thousands, rest = divmod(n, 1000)
|
| 86 |
base = "mille" if thousands == 1 else number_to_french(thousands) + " mille"
|
| 87 |
return base if rest == 0 else base + " " + number_to_french(rest)
|
| 88 |
|
|
|
|
| 89 |
return str(n)
|
| 90 |
|
| 91 |
def convert_digits_in_text(text: str) -> str:
|
|
|
|
| 93 |
|
| 94 |
def repl(match):
|
| 95 |
s = match.group(0)
|
|
|
|
| 96 |
if len(s) > 4:
|
| 97 |
return " ".join([UNITS.get(int(digit), digit) for digit in s])
|
|
|
|
|
|
|
| 98 |
try:
|
| 99 |
val = int(s)
|
| 100 |
return number_to_french(val)
|
|
|
|
| 155 |
prompt_input_ids=prompt_ids,
|
| 156 |
max_new_tokens=2048,
|
| 157 |
do_sample=True,
|
| 158 |
+
temperature=0.8,
|
| 159 |
min_new_tokens=20
|
| 160 |
)
|
| 161 |
audio_np = audio.cpu().numpy().squeeze().astype(np.float32)
|
|
|
|
| 182 |
Texte : {text}"""
|
| 183 |
|
| 184 |
try:
|
| 185 |
+
response = gemini_client.models.generate_content(
|
| 186 |
+
model=GEMINI_MODEL,
|
| 187 |
+
contents=prompt
|
| 188 |
+
)
|
| 189 |
return response.text.strip()
|
| 190 |
except Exception as e:
|
| 191 |
return f"Erreur de traduction : {str(e)}"
|
|
|
|
| 201 |
|
| 202 |
Texte : {text}"""
|
| 203 |
try:
|
| 204 |
+
response = gemini_client.models.generate_content(
|
| 205 |
+
model=GEMINI_MODEL,
|
| 206 |
+
contents=prompt
|
| 207 |
+
)
|
| 208 |
return response.text.strip()
|
| 209 |
except Exception as e:
|
| 210 |
return 'Bonjour'
|
|
|
|
| 236 |
if not audio_url: return "Bonjour", 400
|
| 237 |
|
| 238 |
try:
|
|
|
|
| 239 |
resp = requests.get(audio_url, stream=True)
|
| 240 |
if resp.status_code != 200:
|
| 241 |
logger.error(f"Erreur téléchargement audio: {resp.status_code}")
|
| 242 |
return "Bonjour"
|
| 243 |
|
|
|
|
| 244 |
with tempfile.NamedTemporaryFile(suffix=".ogg", delete=False) as tmp:
|
| 245 |
tmp.write(resp.content)
|
| 246 |
+
tmp.flush()
|
| 247 |
+
os.fsync(tmp.fileno())
|
| 248 |
tmp_path = tmp.name
|
| 249 |
|
| 250 |
try:
|
|
|
|
| 251 |
audio = AudioSegment.from_file(tmp_path)
|
| 252 |
wav_io = io.BytesIO()
|
| 253 |
audio.set_frame_rate(16000).set_channels(1).export(wav_io, format="wav")
|
| 254 |
wav_io.seek(0)
|
| 255 |
|
|
|
|
| 256 |
data, sr = sf.read(wav_io)
|
| 257 |
data = np.asarray(data, dtype=np.float32)
|
| 258 |
if data.ndim > 1: data = data.mean(axis=1)
|
| 259 |
|
|
|
|
| 260 |
wolof_text = asr(normalize_audio(data))["text"]
|
| 261 |
|
| 262 |
finally:
|
|
|
|
| 263 |
if os.path.exists(tmp_path):
|
| 264 |
os.remove(tmp_path)
|
| 265 |
|
|
|
|
| 270 |
|
| 271 |
except Exception as e:
|
| 272 |
logger.error(f"Erreur WhatsApp ASR: {e}")
|
|
|
|
| 273 |
return "Bonjour"
|
| 274 |
|
| 275 |
@app.route("/tts", methods=["POST"])
|
|
|
|
| 283 |
return jsonify({"wolof_text": wolof_text, "audio": audio_base64})
|
| 284 |
|
| 285 |
if __name__ == "__main__":
|
| 286 |
+
app.run(host="0.0.0.0", port=7860)
|