add speech service

speech_service/.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
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+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
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+
+# Installer logs
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+# Unit test / coverage reports
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+.tox/
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+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
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+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
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+# PyBuilder
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+# IPython
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+# pyenv
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+# pipenv
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+# poetry
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+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
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+
+# pdm
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+#pdm.lock
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+#   https://pdm.fming.dev/latest/usage/project/#working-with-version-control
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+__pypackages__/
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+/site
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+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
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+# Ruff stuff:
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+# PyPI configuration file
+.pypirc

speech_service/config.py

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+import os
+from dotenv import load_dotenv
+
+def load_config():
+    load_dotenv()
+    return {
+        "REDIS_HOST": os.getenv("REDIS_HOST", "localhost"),
+        "REDIS_PORT": int(os.getenv("REDIS_PORT", "6379")),
+        "WHISPER_MODEL": os.getenv("WHISPER_MODEL", "dvislobokov/whisper-large-v3-turbo-russian"),
+        "DEVICE": os.getenv("DEVICE", "cuda"),
+        "AUDIO_TASK_CHANNEL": os.getenv("AUDIO_TASK_CHANNEL", "audio_tasks"),
+        "TEXT_RESULT_CHANNEL": os.getenv("TEXT_RESULT_CHANNEL", "texts"),
+    }

speech_service/main.py

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+import asyncio
+import json
+from config import load_config
+from models import AudioTask
+from redis_client import RedisClient
+from transcriber import WhisperTranscriber
+
+async def process_audio_task(redis_client: RedisClient, transcriber: WhisperTranscriber, task_data: dict):
+    try:
+        task = AudioTask(**task_data)
+    except Exception as e:
+        print(f"Error creating AudioTask from data: {e}")
+        return
+
+    print(f"Processing task {task.uuid} ...")
+    loop = asyncio.get_running_loop()
+    text = await loop.run_in_executor(None, transcriber.transcribe, task.file_path)
+
+    result = {
+        "chat_id": task.chat_id,
+        "user_id": task.user_id,
+        "message_id": task.message_id,
+        "text": text
+    }
+    await redis_client.publish_result(result)
+    print(f"Published result for task {task.uuid}")
+
+async def main():
+    config = load_config()
+    redis_client = RedisClient(
+        host=config["REDIS_HOST"],
+        port=config["REDIS_PORT"],
+        task_channel=config["AUDIO_TASK_CHANNEL"],
+        result_channel=config["TEXT_RESULT_CHANNEL"]
+    )
+    transcriber = WhisperTranscriber(config["WHISPER_MODEL"], config["DEVICE"])
+    
+    pubsub = await redis_client.subscribe_tasks()
+    print("Subscribed to audio_tasks channel. Waiting for tasks...")
+
+    while True:
+        message = await pubsub.get_message(ignore_subscribe_messages=True, timeout=1.0)
+        if message:
+            try:
+                task_data = json.loads(message["data"])
+            except Exception as e:
+                print(f"Error parsing task message: {e}")
+                continue
+            asyncio.create_task(process_audio_task(redis_client, transcriber, task_data))
+        await asyncio.sleep(0.1)
+
+if __name__ == "__main__":
+    asyncio.run(main())

speech_service/models.py

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+from dataclasses import dataclass
+
+@dataclass
+class AudioTask:
+    uuid: str
+    file_path: str
+    user_id: int
+    chat_id: int
+    message_id: int

speech_service/redis_client.py

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+import json
+import redis.asyncio as redis
+
+class RedisClient:
+    def __init__(self, host: str, port: int, task_channel: str, result_channel: str):
+        self.client = redis.Redis(host=host, port=port, decode_responses=True)
+        self.task_channel = task_channel
+        self.result_channel = result_channel
+
+    async def subscribe_tasks(self):
+        pubsub = self.client.pubsub()
+        await pubsub.subscribe(self.task_channel)
+        return pubsub
+
+    async def publish_result(self, result: dict):
+        await self.client.publish(self.result_channel, json.dumps(result))

speech_service/requirements.txt

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+--index-url https://download.pytorch.org/whl/cu121
+
+torch==2.5.1
+torchvision==0.20.1
+torchaudio==2.5.1
+
+--index-url https://pypi.org/simple
+
+transformers
+redis>=4.2.0
+python-dotenv

speech_service/transcriber.py

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+from transformers import pipeline
+
+class WhisperTranscriber:
+    def __init__(self, model_name: str, device: str = "cuda"):
+        print("Loading Whisper model...")
+        self.pipe = pipeline(
+            task="automatic-speech-recognition",
+            model=model_name,
+            tokenizer=model_name,
+            device=0 if device == "cuda" else -1
+        )
+        print("Whisper model loaded.")
+
+    def transcribe(self, audio_file: str) -> str:
+        result = self.pipe(audio_file)
+        return result.get("text", "").strip()