192 lines
8.3 KiB
Python
192 lines
8.3 KiB
Python
"""
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Модуль routes.py содержит классы для регистрации маршрутов API
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для сервиса распознавания речи.
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"""
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from __future__ import annotations
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import os
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from typing import Dict, TYPE_CHECKING
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import logging
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from flask import Flask, request, jsonify
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from .core.transcription_service import TranscriptionService
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from .audio.sources import get_uploaded_file, get_url_file, get_base64_file
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from .infrastructure.validation import ValidationError
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from .infrastructure.storage import cleanup_temp_files
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from .infrastructure.async_tasks import transcribe_audio_async, task_manager
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if TYPE_CHECKING:
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from .core.transcriber import WhisperTranscriber
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from .infrastructure.validation import FileValidator
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logger = logging.getLogger('app.routes')
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class Routes:
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"""Класс для регистрации всех эндпоинтов API."""
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def __init__(self, app: Flask, transcriber: WhisperTranscriber,
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config: Dict, file_validator: FileValidator):
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self.app = app
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self.config = config
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self.transcription_service = TranscriptionService(transcriber, config)
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self.file_validator = file_validator
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self._max_size = self.config.get("file_validation", {}).get("max_file_size_mb", 100)
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self._register_routes()
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def _register_routes(self) -> None:
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@self.app.route('/', methods=['GET'])
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def index():
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"""Корень. Отдаёт HTML клиент."""
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return self.app.send_static_file('index.html')
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@self.app.route('/health', methods=['GET'])
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def health_check():
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"""Эндпоинт для проверки статуса сервиса."""
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return jsonify({"status": "ok", "version": "1.0.0"}), 200
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@self.app.route('/config', methods=['GET'])
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def get_config():
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"""Эндпоинт для получения конфигурации сервиса.
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Отдаёт полную конфигурацию включая model_path — это сознательное
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решение, сервис работает во внутренней сети."""
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return jsonify(self.config), 200
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@self.app.route('/v1/models', methods=['GET'])
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def list_models():
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"""Эндпоинт для получения списка доступных моделей."""
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return jsonify({
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"data": [{
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"id": os.path.basename(self.config["model_path"]),
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"object": "model",
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"owned_by": "openai",
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"permissions": []
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}],
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"object": "list"
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}), 200
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@self.app.route('/v1/models/<model_id>', methods=['GET'])
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def retrieve_model(model_id):
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"""Эндпоинт для получения информации о конкретной модели."""
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if model_id == os.path.basename(self.config["model_path"]):
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return jsonify({
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"id": model_id,
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"object": "model",
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"owned_by": "openai",
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"permissions": []
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}), 200
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return jsonify({
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"error": "Model not found",
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"details": f"Model '{model_id}' does not exist"
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}), 404
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@self.app.route('/v1/audio/transcriptions', methods=['POST'])
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def openai_transcribe_endpoint():
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"""Эндпоинт для транскрибации аудиофайла (multipart-форма)."""
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temp_path, filename, error = get_uploaded_file(request.files, self._max_size)
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if error:
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return jsonify({"error": error}), 400
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try:
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self.file_validator.validate_file_by_path(temp_path, filename)
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response, status_code = self.transcription_service.transcribe(temp_path, filename, dict(request.form))
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return jsonify(response), status_code
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except ValidationError as e:
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logger.warning("File validation failed for '%s': %s", filename, e)
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return jsonify({"error": str(e)}), 400
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finally:
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cleanup_temp_files([temp_path])
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@self.app.route('/v1/audio/transcriptions/url', methods=['POST'])
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def transcribe_from_url():
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"""Эндпоинт для транскрибации аудиофайла по URL."""
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data = request.json
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if not data or "url" not in data:
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return jsonify({
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"error": "No URL provided",
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"details": "Please provide 'url' in the JSON request"
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}), 400
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url = data["url"]
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params = {k: v for k, v in data.items() if k != "url"}
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temp_path, filename, error = get_url_file(url, self._max_size)
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if error:
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return jsonify({"error": error}), 400
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try:
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self.file_validator.validate_file_by_path(temp_path, filename)
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response, status_code = self.transcription_service.transcribe(temp_path, filename, params)
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return jsonify(response), status_code
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except ValidationError as e:
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logger.warning("File validation failed for '%s': %s", filename, e)
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return jsonify({"error": str(e)}), 400
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finally:
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cleanup_temp_files([temp_path])
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@self.app.route('/v1/audio/transcriptions/base64', methods=['POST'])
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def transcribe_from_base64():
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"""Эндпоинт для транскрибации аудио, закодированного в base64."""
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data = request.json
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if not data or "file" not in data:
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return jsonify({
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"error": "No base64 file provided",
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"details": "Please provide 'file' in the JSON request"
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}), 400
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base64_data = data["file"]
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params = {k: v for k, v in data.items() if k != "file"}
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temp_path, filename, error = get_base64_file(base64_data, self._max_size)
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if error:
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return jsonify({"error": error}), 400
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try:
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self.file_validator.validate_file_by_path(temp_path, filename)
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response, status_code = self.transcription_service.transcribe(temp_path, filename, params)
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return jsonify(response), status_code
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except ValidationError as e:
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logger.warning("File validation failed for '%s': %s", filename, e)
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return jsonify({"error": str(e)}), 400
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finally:
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cleanup_temp_files([temp_path])
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@self.app.route('/v1/audio/transcriptions/async', methods=['POST'])
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def transcribe_async():
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"""Эндпоинт для асинхронной транскрибации аудиофайла."""
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temp_path, filename, error = get_uploaded_file(request.files, self._max_size)
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if error:
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return jsonify({"error": error}), 400
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try:
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self.file_validator.validate_file_by_path(temp_path, filename)
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except ValidationError as e:
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cleanup_temp_files([temp_path])
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return jsonify({"error": str(e)}), 400
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params = dict(request.form)
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# Не чистим temp_path здесь — async task отвечает за cleanup
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task_id = transcribe_audio_async(temp_path, self.transcription_service, params)
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return jsonify({"task_id": task_id}), 202
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@self.app.route('/v1/tasks/<task_id>', methods=['GET'])
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def get_task_status(task_id):
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"""Эндпоинт для получения статуса асинхронной задачи."""
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task_info = task_manager.get_task_status(task_id)
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if not task_info:
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return jsonify({"error": "Task not found"}), 404
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response = {"task_id": task_id, "status": task_info["status"]}
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if task_info["status"] == "completed":
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response["result"] = task_info["result"]
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elif task_info["status"] == "failed":
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response["error"] = task_info["error"]
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return jsonify(response)
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