diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json deleted file mode 100644 index 799544c..0000000 --- a/.devcontainer/devcontainer.json +++ /dev/null @@ -1,33 +0,0 @@ -// For format details, see https://aka.ms/devcontainer.json. For config options, see the -// README at: https://github.com/devcontainers/templates/tree/main/src/python -{ - "name": "transcribo-backend", - // Or use a Dockerfile or Docker Compose file. More info: https://containers.dev/guide/dockerfile - "image": "mcr.microsoft.com/devcontainers/python:2-3.12-bullseye", - "features": {}, - // Use 'postCreateCommand' to run commands after the container is created. - "postCreateCommand": "./.devcontainer/postCreateCommand.sh", - // Configure tool-specific properties. - "customizations": { - "vscode": { - "extensions": [ - "ms-python.python", - "editorconfig.editorconfig", - "ms-python.vscode-pylance", - "ms-python.black-formatter", - "ms-python.isort", - "charliermarsh.ruff", - "detachhead.basedpyright" - ], - "settings": { - "python.testing.pytestArgs": [ - "tests" - ], - "python.testing.unittestEnabled": false, - "python.testing.pytestEnabled": true, - "python.defaultInterpreterPath": "/workspaces/transcribo-backend/.venv/bin/python", - "python.testing.pytestPath": "/workspaces/transcribo-backend/.venv/bin/pytest" - } - } - } -} diff --git a/.devcontainer/postCreateCommand.sh b/.devcontainer/postCreateCommand.sh deleted file mode 100644 index 0f40854..0000000 --- a/.devcontainer/postCreateCommand.sh +++ /dev/null @@ -1,10 +0,0 @@ -#! /usr/bin/env bash - -# Install uv -curl -LsSf https://astral.sh/uv/install.sh | sh - -# Install Dependencies -uv sync - -# Install pre-commit hooks -uv run pre-commit install --install-hooks diff --git a/.env.example b/.env.example index ea3a5cb..6444d4d 100644 --- a/.env.example +++ b/.env.example @@ -1,8 +1,11 @@ -LLM_API="http://localhost:9000/v1" -WHISPER_API="http://localhost:50001/v1" -API_KEY="your api token here" +LLM_API_PORT=8001 +LLM_BASE_URL=http://localhost:${LLM_API_PORT}/v1 +API_KEY='none' +WHISPER_URL="http://localhost:50001/v1" +LLM_MODEL='Qwen/Qwen3-32B-AWQ' HMAC_SECRET="YOUR HMAC SECRET" # Used to pseudonymize user id. Create with openssl rand 32 | base64 HF_AUTH_TOKEN="" +CLIENT_PORT=3000 +CLIENT_URL=http://localhost:${CLIENT_PORT} PORT="" -LLM_HEALTH_CHECK="http://localhost:9000/health" -WHISPER_HEALTH_CHECK="http://localhost:50001/healthz" +IS_PROD=False diff --git a/.github/workflows/docker-publish.yml b/.github/workflows/docker-publish.yml index bf859b9..c83203a 100644 --- a/.github/workflows/docker-publish.yml +++ b/.github/workflows/docker-publish.yml @@ -1,16 +1,9 @@ name: Build and Publish Docker Image on: workflow_dispatch: - inputs: - version_bump: - description: Version bump type - required: true - default: patch - type: choice - options: [major, minor, patch] permissions: - contents: write + contents: read packages: write jobs: @@ -18,9 +11,7 @@ jobs: uses: DCC-BS/ci-workflows/.github/workflows/publish-docker.yml@v7 secrets: inherit with: - release_type: ${{ inputs.version_bump }} # major|minor|patch version_project_type: "python" # or "node" - version_uv_version: "0.9.14" registry: ghcr.io image_name: ghcr.io/${{ github.repository }} context: . diff --git a/Dockerfile b/Dockerfile index 9f2e385..6bc71f4 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,6 +1,6 @@ # Stage 1: Builder -FROM python:3.14-alpine AS builder -COPY --from=ghcr.io/astral-sh/uv:0.9.14 /uv /uvx /bin/ +FROM python:3.13-alpine AS builder +COPY --from=ghcr.io/astral-sh/uv:0.9.25 /uv /uvx /bin/ ENV UV_COMPILE_BYTECODE=1 ENV UV_LINK_MODE=copy @@ -28,7 +28,7 @@ RUN --mount=type=cache,target=/root/.cache/uv \ uv sync --locked --no-dev # Stage 2: Runtime -FROM python:3.14-alpine +FROM python:3.13-alpine ENV PYTHONDONTWRITEBYTECODE=1 ENV PYTHONUNBUFFERED=1 diff --git a/Makefile b/Makefile index 9457251..0f5d637 100644 --- a/Makefile +++ b/Makefile @@ -10,8 +10,8 @@ check: ## Run code quality tools. @uv lock --locked @echo "🚀 Linting code: Running pre-commit" @uv run pre-commit run -a - @echo "🚀 Static type checking: Running pyrefly" - @uv run pyrefly check ./src/transcribo_backend + @echo "🚀 Static type checking: Running ty" + @uv run ty check .PHONY: test test: ## Test the code with pytest @@ -36,7 +36,7 @@ run: ## Run the application .PHONY: dev dev: ## Run the application in development mode @echo "🚀 Running the application in development mode" - @uv run fastapi dev ./src/transcribo_backend/app.py --port 8000 + @uv run --env-file .env fastapi dev ./src/transcribo_backend/app.py --port 8000 .PHONY: build build: clean-build ## Build wheel file diff --git a/README.md b/README.md index f87246e..e2f101a 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,8 @@ +# TODO +returns library +api error from backend common + + # Transcribo Backend Transcribo Backend is a powerful Python FastAPI service that provides advanced audio and video transcription capabilities with speaker diarization and AI-powered text summarization. This backend service enables high-quality transcription using OpenAI's Whisper API and intelligent summarization using large language models. diff --git a/pyproject.toml b/pyproject.toml index 5ebbc67..878702d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,28 +2,28 @@ name = "transcribo-backend" version = "0.5.8" description = "The backend of the transcribo app" -authors = [{name = "Data Competence Center Basel-Stadt", email = "dcc@bs.ch" },{ name = "Tobias Bollinger", email = "tobias.bollinger@gmail.com" }] +authors = [{name = "Data Competence Center Basel-Stadt", email = "dcc@bs.ch" },{ name = "Tobias Bollinger", email = "tobias.bollinger@bs.ch" }, { name = "Yanick Schraner", email = "yanick.schraner@bs.ch" }] readme = "README.md" keywords = ['python'] -requires-python = ">=3.12,<4.0" +requires-python = ">=3.12,<3.14" license = "MIT" license-files = ["LICEN[CS]E*"] classifiers = [ "Intended Audience :: Developers", "Programming Language :: Python", "Programming Language :: Python :: 3", - "Programming Language :: Python :: 3.10", - "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3.13", "Topic :: Software Development :: Libraries :: Python Modules", ] dependencies = [ - "aiohttp>=3.11.13", - "fastapi[standard]>=0.123.5", - "structlog>=25.1.0", "audioop-lts; python_version >= '3.13'", - "openai>=1.97.1", + "cachetools>=6.2.4", + "dcc-backend-common>=0.1.4", + "dependency-injector>=4.48.3", + "fastapi[standard]>=0.128.0", + "pydantic-ai>=1.43.0", + "returns>=0.26.0", ] [project.urls] @@ -38,14 +38,12 @@ dev = [ "pre-commit>=2.20.0", "tox-uv>=1.11.3", "deptry>=0.22.0", - "basedpyright>=1.27.1", "pytest-cov>=6.0.0", "ruff>=0.9.2", "mkdocs>=1.4.2", "mkdocs-material>=8.5.10", "mkdocstrings[python]>=0.26.1", - "mypy>=1.15.0", - "pyrefly>=0.43.1", + "ty>=0.0.12", ] [build-system] @@ -100,11 +98,6 @@ ignore = [ "E731", ] -[tool.pyrefly] -project-includes = [ - "src/**.py*", -] - [tool.ruff.lint.per-file-ignores] "tests/*" = ["S101"] diff --git a/pyrefly.toml b/pyrefly.toml deleted file mode 100644 index e3c992a..0000000 --- a/pyrefly.toml +++ /dev/null @@ -1,10 +0,0 @@ -ignore-missing-imports = [ - "pydub", -] -untyped-def-behavior = "skip-and-infer-return-any" - -project-includes = [ - "./src", -] - -python-interpreter-path = ".venv/bin/python3" diff --git a/run.sh b/run.sh index dc6f3a2..69e2df6 100644 --- a/run.sh +++ b/run.sh @@ -1,43 +1,52 @@ #!/bin/sh set -e -if [ -f .env ]; then - # Load environment variables from .env file - . .env -fi - -# Ensure PORT has a value (in case .env sets it to empty) -PORT="${PORT:-8000}" +# Default values (allow env overrides) +DEV_MODE=${DEV_MODE:-false} +PORT=${PORT:-8000} # Function to display help information show_help() { echo "Usage: $0 [options]" echo "" echo "Options:" + echo " --dev Run in development mode using 'fastapi dev'" echo " --port NUMBER Specify the port number (default: 8000)" echo " --help Display this help message" echo "" echo "Examples:" echo " $0 # Run in production mode on port 8000" + echo " $0 --dev # Run in development mode on port 8000" echo " $0 --port 9000 # Run in production mode on port 9000" + echo " $0 --dev --port 5000 # Run in development mode on port 5000" echo "" } # Parse command line arguments while [ "$#" -gt 0 ]; do - case $1 in + case "$1" in + --dev) DEV_MODE=true; shift ;; --port) - if [ -z "$2" ] || echo "$2" | grep -q "^-"; then + if [ -z "${2:-}" ]; then echo "Error: --port requires a numeric argument" show_help exit 1 fi - if ! echo "$2" | grep -Eq "^[0-9]+$"; then + case "$2" in + ''|*[!0-9]*) + echo "Error: port must be a valid number" + show_help + exit 1 + ;; + esac + if [ "$2" -lt 1 ] || [ "$2" -gt 65535 ]; then echo "Error: port must be a valid number" show_help exit 1 fi - PORT="$2"; shift 2 ;; + PORT="$2" + shift 2 + ;; --help) show_help exit 0 @@ -50,5 +59,11 @@ while [ "$#" -gt 0 ]; do esac done -echo "Starting in production mode on port $PORT" -fastapi run ./src/transcribo_backend/app.py --port "$PORT" +# Choose command based on dev mode +if [ "$DEV_MODE" = true ]; then + echo "Starting in development mode on port $PORT" + fastapi dev ./src/transcribo_backend/app.py --port "$PORT" +else + echo "Starting in production mode on port $PORT" + fastapi run ./src/transcribo_backend/app.py --port "$PORT" +fi diff --git a/src/transcribo_backend/agents/__init__.py b/src/transcribo_backend/agents/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/src/transcribo_backend/agents/summarize_agent.py b/src/transcribo_backend/agents/summarize_agent.py new file mode 100644 index 0000000..dd5a948 --- /dev/null +++ b/src/transcribo_backend/agents/summarize_agent.py @@ -0,0 +1,34 @@ +from openai import AsyncOpenAI +from pydantic_ai import Agent, TextOutput +from pydantic_ai.models.openai import OpenAIChatModel +from pydantic_ai.providers.openai import OpenAIProvider + +from transcribo_backend.utils.app_config import AppConfig + + +def transform_to_swissgerman_style(text: str) -> str: + return text.replace("ß", "ss") + + +def create_summarize_agent(app_config: AppConfig) -> Agent: + client = AsyncOpenAI(max_retries=3, base_url=app_config.llm_base_url, api_key=app_config.api_key) + model = OpenAIChatModel(model_name=app_config.llm_model, provider=OpenAIProvider(openai_client=client)) + summarize_agent: Agent = Agent( + model=model, + output_type=TextOutput(transform_to_swissgerman_style), + ) + + @summarize_agent.instructions + def get_instructions() -> str: + return """ +You are a meeting summary expert. +You are given a transcript of a meeting and you need to summarize it. +You need to summarize the meeting in a way that is easy to understand and use. +You need to include the main points of the meeting, the decisions made, and the action items. +You need to include the names of the participants. +You use markdown to format the summary. +Use the same language as used in the transcript to summarize the meeting. +If you are not sure about the language, use German. +""" + + return summarize_agent diff --git a/src/transcribo_backend/app.py b/src/transcribo_backend/app.py index 9382421..41ec96d 100644 --- a/src/transcribo_backend/app.py +++ b/src/transcribo_backend/app.py @@ -1,233 +1,146 @@ -import logging -import time -from datetime import UTC, datetime -from http import HTTPStatus -from pathlib import Path -from typing import Annotated, Any +from collections.abc import AsyncGenerator +from contextlib import asynccontextmanager -import aiohttp -from fastapi import FastAPI, Header, HTTPException, Response, UploadFile +from dcc_backend_common.fastapi_error_handling import inject_api_error_handler +from dcc_backend_common.fastapi_health_probes import health_probe_router +from dcc_backend_common.fastapi_health_probes.router import ServiceDependency +from dcc_backend_common.logger import get_logger, init_logger +from fastapi import FastAPI +from fastapi.middleware.cors import CORSMiddleware +from structlog.stdlib import BoundLogger -from transcribo_backend.config import settings -from transcribo_backend.helpers.file_type import is_audio_file, is_video_file -from transcribo_backend.models.summary import Summary, SummaryRequest -from transcribo_backend.models.task_status import TaskStatus -from transcribo_backend.models.transcription_response import TranscriptionResponse -from transcribo_backend.services import summary_service -from transcribo_backend.services.whisper_service import ( - transcribe_get_task_result, - transcribe_get_task_status, - transcribe_submit_task, -) -from transcribo_backend.utils.logger import get_logger, init_logger -from transcribo_backend.utils.usage_tracking import get_pseudonymized_user_id +from transcribo_backend.container import Container +from transcribo_backend.routes import summarize_route, transcribe_route +from transcribo_backend.utils.app_config import AppConfig -START_TIME = time.time() -init_logger() -logger = get_logger("app") - - -# Create a custom filter -class EndpointFilter(logging.Filter): - def filter(self, record: logging.LogRecord) -> bool: - # Endpoints to exclude from logging - skip_paths = {"/health"} - - # Extract the request path from the log message - return all(skip_path not in record.getMessage() for skip_path in skip_paths) - - -# Configure the filter -logging.getLogger("uvicorn.access").addFilter(EndpointFilter()) - -# Initialize FastAPI app -app = FastAPI() - - -class HealthCheckError(Exception): - """Custom exception for health check failures.""" +@asynccontextmanager +async def _lifespan(app: FastAPI) -> AsyncGenerator[None, None]: + """ + Lifespan context manager for startup and shutdown events. + """ + # Startup: nothing to do here, container is configured synchronously + yield + # Shutdown: close resources + logger = get_logger("app") + logger.info("Shutting down application, closing resources...") + container: Container = app.state.container + whisper_service = container.whisper_service() + await whisper_service.aclose() + logger.info("Resources closed successfully") + + +def _build_fastapi_app() -> FastAPI: + """ + Instantiate the FastAPI application with metadata and lifespan. + """ + app = FastAPI( + title="Transcribo", + description="API for transcription service with AI-powered language processing", + version="0.1.0", + docs_url="/docs", + redoc_url="/redoc", + lifespan=_lifespan, + ) - pass + return app -@app.get("/task/{task_id}/status") -async def get_task_status(task_id: str) -> TaskStatus: +def _register_health_routes(app: FastAPI, config: AppConfig) -> None: """ - Endpoint to get the status of a task by task_id. + Register health routes for the application. """ - status = await transcribe_get_task_status(task_id) - return status - - -@app.get("/task/{task_id}/result") -async def get_task_result(task_id: str) -> TranscriptionResponse: + whisper_base_url = config.whisper_url.removesuffix("v1") + llm_base_url = config.llm_base_url.removesuffix("v1") + service_dependencies: list[ServiceDependency] = [ + ServiceDependency( + name="whisper", + health_check_url=f"{whisper_base_url}readyz", + api_key=config.api_key, + ), + ServiceDependency( + name="llm", + health_check_url=f"{llm_base_url}health", + api_key=config.api_key, + ), + ] + app.include_router(health_probe_router(service_dependencies=service_dependencies)) + + +def _configure_container(app: FastAPI, logger: BoundLogger) -> Container: """ - Endpoint to get the status of a task by task_id. + Configure the dependency injection container and attach it to app state. """ - status = await transcribe_get_task_result(task_id) - return status + logger.debug("Configuring dependency injection container") + container = Container() + container.wire(modules=[transcribe_route, summarize_route]) + container.check_dependencies() + logger.info("Dependency injection configured") + app.state.container = container + return container -@app.post("/transcribe") -async def submit_transcribe( - audio_file: UploadFile, - num_speakers: int | None = None, - language: str | None = None, - x_client_id: Annotated[str | None, Header()] = None, -) -> TaskStatus: +def _register_routes(app: FastAPI, logger: BoundLogger) -> None: """ - Endpoint to submit a transcription task. + Register API routers. """ + logger.debug("Registering API routers") + app.include_router(summarize_route.create_router()) + app.include_router(transcribe_route.create_router()) + logger.info("All routers registered") - if audio_file.content_type is None: - raise HTTPException(status_code=HTTPStatus.BAD_REQUEST, detail="Content type of the audio file is None") - if audio_file.filename is None: - raise HTTPException(status_code=HTTPStatus.BAD_REQUEST, detail="Filename of the audio file is None") +def _configure_cors(app: FastAPI, client_url: str, logger: BoundLogger) -> None: + """ + Apply CORS middleware configuration. + """ + logger.debug("Setting up CORS middleware") + + app.add_middleware( + CORSMiddleware, # ty:ignore[invalid-argument-type] + allow_origins=[client_url], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], + ) + logger.info(f"CORS configured with origin: {client_url}") - if not is_audio_file(audio_file.content_type) and not is_video_file(audio_file.content_type): - raise HTTPException(status_code=HTTPStatus.UNSUPPORTED_MEDIA_TYPE, detail="Unsupported file type") - # Read the uploaded file content - audio_data = await audio_file.read() +def create_app() -> FastAPI: + """ + Create and configure the FastAPI application. - # Extract X-Client-Id from the request headers - pseudonym_id = get_pseudonymized_user_id(x_client_id or "unknown") - logger.info( - "app_event", - extra={ - "pseudonym_id": pseudonym_id, - "event": "transcribe", - "num_speakers": num_speakers, - "file_size": len(audio_data), - }, - ) + This function initializes the FastAPI application with: + - Environment variables loading + - Logging configuration + - Dependency injection container setup + - CORS middleware configuration + - API route registration - # Submit the transcription task - extension = Path(audio_file.filename).suffix.lower().strip(".") - try: - status = await transcribe_submit_task( - audio_data, extension, diarization_speaker_count=num_speakers, language=language - ) - except HTTPException as e: - logger.exception("Failed to submit transcription task", exc_info=e) - if e.status_code == HTTPStatus.TOO_MANY_REQUESTS: - raise HTTPException(status_code=HTTPStatus.TOO_MANY_REQUESTS, detail="Too many requests") from None - if e.status_code == HTTPStatus.REQUEST_ENTITY_TOO_LARGE: - raise HTTPException(status_code=HTTPStatus.REQUEST_ENTITY_TOO_LARGE, detail="File is too large") from None - raise HTTPException( - status_code=HTTPStatus.INTERNAL_SERVER_ERROR, detail="Failed to submit transcription task" - ) from None - except Exception as e: - logger.exception("Failed to submit transcription task", exc_info=e) - raise HTTPException( - status_code=HTTPStatus.INTERNAL_SERVER_ERROR, detail="Failed to submit transcription task" - ) from None - return status - - -@app.post("/summarize") -async def summarize(request: SummaryRequest, x_client_id: Annotated[str | None, Header()] = None) -> Summary: - """ - Endpoint to summarize a text. + Returns: + FastAPI: Configured FastAPI application instance """ - model_context_length = 32_000 - - if not request.transcript or not request.transcript.strip(): - raise HTTPException(status_code=HTTPStatus.BAD_REQUEST, detail="Transcript is empty") - if len(request.transcript) > model_context_length * 4: - raise HTTPException( - status_code=HTTPStatus.BAD_REQUEST, - detail=f"Transcript is too long. Maximum length is {model_context_length * 4} characters.", - ) - # Extract X-Client-Id from the request headers - pseudonym_id = get_pseudonymized_user_id(x_client_id or "unknown") - logger.info( - "app_event", - extra={"pseudonym_id": pseudonym_id, "event": "summarize", "transcript_length": len(request.transcript)}, - ) - try: - summary = await summary_service.summarize(request.transcript) - except Exception as e: - logger.exception("Failed to summarize transcript", exc_info=e) - raise HTTPException(status_code=HTTPStatus.INTERNAL_SERVER_ERROR, detail="Failed to generate summary") from None - else: - return summary + init_logger() + logger = get_logger("app") + logger.info("Starting Transcribo API") -@app.get("/health/liveness") -async def liveness_probe(): - """ - Liveness Probe - * Purpose: Checks if the application process is running and not deadlocked. - * K8s Action: If this fails, the container is KILLED and RESTARTED. - * Rule: Keep it simple. Do NOT check databases here. - """ - return {"status": "up", "uptime_seconds": time.time() - START_TIME} + app = _build_fastapi_app() + inject_api_error_handler(app) -@app.get("/health/readiness") -async def readiness_probe(response: Response): - """ - Readiness Probe - * Purpose: Checks if the app is ready to handle user requests (e.g., external APIs). - * K8s Action: If this fails, traffic stops sending to this pod. - * Rule: Check critical dependencies here. - """ + container = _configure_container(app=app, logger=logger) + config = container.app_config() + logger.info(f"AppConfig loaded: {config}") - health_check: dict[str, Any] = {"status": "ready", "checks": {"llm_api": "unknown", "whisper_api": "unknown"}} - - try: - timeout = aiohttp.ClientTimeout(total=5.0) - async with aiohttp.ClientSession( - timeout=timeout, headers={"Authorization": f"Bearer {settings.api_key}"} - ) as session: - # Check LLM API health - try: - async with session.get(f"{settings.llm_health_check}") as llm_response: - if llm_response.status == 200: - health_check["checks"]["llm_api"] = "healthy" - else: - health_check["checks"]["llm_api"] = f"unhealthy (status: {llm_response.status})" - raise HealthCheckError(f"LLM API returned status {llm_response.status}") - except aiohttp.ClientError as e: - health_check["checks"]["llm_api"] = f"error: {e!s}" - raise - - # Check Whisper API readiness - try: - async with session.get(f"{settings.whisper_health_check}") as whisper_response: - if whisper_response.status == 200: - health_check["checks"]["whisper_api"] = "healthy" - else: - health_check["checks"]["whisper_api"] = f"unhealthy (status: {whisper_response.status})" - raise HealthCheckError(f"Whisper API returned status {whisper_response.status}") - except aiohttp.ClientError as e: - health_check["checks"]["whisper_api"] = f"error: {e!s}" - raise - except Exception as e: - # If a critical dependency fails, we must return a 503. - # This tells K8s to stop sending traffic to this specific pod. - response.status_code = HTTPStatus.SERVICE_UNAVAILABLE - return {"status": "unhealthy", "checks": health_check["checks"], "error": str(e)} - else: - return health_check - - -@app.get("/health/startup") -async def startup_probe(): - """ - Startup Probe - * Purpose: Checks if the application has finished initialization. - * K8s Action: Blocks Liveness/Readiness probes until this returns 200. - * Rule: Useful for apps that need to load large ML models or caches on boot. - """ - return {"status": "started", "timestamp": datetime.now(UTC).isoformat()} + _register_health_routes(app=app, config=config) + + _configure_cors(app=app, client_url=config.client_url, logger=logger) + _register_routes(app=app, logger=logger) + logger.info("API setup complete") + return app -if __name__ == "__main__": # pragma: no cover - import uvicorn - uvicorn.run("transcribo_backend:app", host="127.0.0.1", port=8000, reload=True) +app = create_app() diff --git a/src/transcribo_backend/config.py b/src/transcribo_backend/config.py deleted file mode 100644 index fd15080..0000000 --- a/src/transcribo_backend/config.py +++ /dev/null @@ -1,79 +0,0 @@ -"""Configuration module for the Transcribo backend. - -This module loads configuration values from environment variables. -""" - -import os -from dataclasses import dataclass - -from dotenv import load_dotenv - - -@dataclass -class Settings: - """Application settings loaded from environment variables.""" - - whisper_api: str - llm_api: str - api_key: str - hmac_secret: str - llm_health_check: str - whisper_health_check: str - - def __repr__(self) -> str: - """Custom repr that masks sensitive data.""" - return ( - f"Settings(whisper_api={self.whisper_api}, llm_api={self.llm_api}, api_key=********, hmac_secret=********)" - ) - - @classmethod - def from_env(cls) -> "Settings": - """Create settings from environment variables. - - Returns: - Settings: Application settings object - - Raises: - ValueError: If a required environment variable is missing - """ - if os.path.exists(".env"): - load_dotenv() # Load .env file if present - - whisper_api = os.getenv("WHISPER_API") - llm_api = os.getenv("LLM_API") - api_key = os.getenv("API_KEY") - hmac_secret = os.getenv("HMAC_SECRET") - llm_health_check = os.getenv("LLM_HEALTH_CHECK") - whisper_health_check = os.getenv("WHISPER_HEALTH_CHECK") - - if not whisper_api: - raise ValueError("WHISPER_API environment variable is required") - - if not llm_api: - raise ValueError("LLM_API environment variable is required") - - if not api_key: - raise ValueError("API_KEY environment variable is required") - - if not hmac_secret: - raise ValueError("HMAC_SECRET environment variable is required") - - if not llm_health_check: - raise ValueError("LLM_HEALTH_CHECK environment variable is required") - - if not whisper_health_check: - raise ValueError("WHISPER_HEALTH_CHECK environment variable is required") - - return cls( - whisper_api=whisper_api, - llm_api=llm_api, - api_key=api_key, - hmac_secret=hmac_secret, - llm_health_check=llm_health_check, - whisper_health_check=whisper_health_check, - ) - - -# Create a global settings instance for easy import -settings = Settings.from_env() -print(f"Settings loaded: {settings}") diff --git a/src/transcribo_backend/container.py b/src/transcribo_backend/container.py new file mode 100644 index 0000000..0d2e0de --- /dev/null +++ b/src/transcribo_backend/container.py @@ -0,0 +1,25 @@ +from dcc_backend_common.usage_tracking import UsageTrackingService +from dependency_injector import containers, providers + +from transcribo_backend.services.summarization_service import SummarizationService +from transcribo_backend.services.whisper_service import WhisperService +from transcribo_backend.utils.app_config import AppConfig + + +class Container(containers.DeclarativeContainer): + app_config: providers.Object[AppConfig] = providers.Object(AppConfig.from_env()) + + usage_tracking_service: providers.Singleton[UsageTrackingService] = providers.Singleton( + UsageTrackingService, + hmac_secret=app_config.provided.hmac_secret, + ) + + whisper_service: providers.Singleton[WhisperService] = providers.Singleton( + WhisperService, + app_config=app_config, + ) + + summarization_service: providers.Singleton[SummarizationService] = providers.Singleton( + SummarizationService, + app_config=app_config, + ) diff --git a/src/transcribo_backend/routes/__init__.py b/src/transcribo_backend/routes/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/src/transcribo_backend/routes/summarize_route.py b/src/transcribo_backend/routes/summarize_route.py new file mode 100644 index 0000000..0811093 --- /dev/null +++ b/src/transcribo_backend/routes/summarize_route.py @@ -0,0 +1,67 @@ +from http import HTTPStatus +from typing import Annotated + +from dcc_backend_common.fastapi_error_handling import ApiErrorCodes, api_error_exception +from dcc_backend_common.logger import get_logger +from dcc_backend_common.usage_tracking import UsageTrackingService +from dependency_injector.wiring import Provide, inject +from fastapi import APIRouter, Header +from returns.io import IOSuccess + +from transcribo_backend.container import Container +from transcribo_backend.models.summary import Summary, SummaryRequest +from transcribo_backend.services.summarization_service import SummarizationService + +logger = get_logger(__name__) + + +@inject +def create_router( + summarization_service: SummarizationService = Provide[Container.summarization_service], + usage_tracking_service: UsageTrackingService = Provide[Container.usage_tracking_service], +) -> APIRouter: + """Create the router for the summarize endpoint.""" + logger.info("Creating router for summarize endpoint") + router = APIRouter() + + @router.post("/summarize") + async def summarize(request: SummaryRequest, x_client_id: Annotated[str | None, Header()] = None) -> Summary: + """ + Endpoint to summarize a text. + """ + model_context_length = 32_000 + + if not request.transcript or not request.transcript.strip(): + raise api_error_exception( + errorId=ApiErrorCodes.INVALID_REQUEST, + status=HTTPStatus.BAD_REQUEST, + debugMessage="Transcript cannot be empty", + ) + if len(request.transcript) > model_context_length * 4: + raise api_error_exception( + errorId=ApiErrorCodes.INVALID_REQUEST, + status=HTTPStatus.BAD_REQUEST, + debugMessage=f"Transcript is too long. Maximum length is {model_context_length * 4} characters.", + ) + # Extract X-Client-Id from the request headers + usage_tracking_service.log_event( + module="summarize_route", + func="summarize", + user_id=x_client_id or "unknown", + transcript_length=len(request.transcript), + ) + + result = await summarization_service.summarize(request.transcript) + + if isinstance(result, IOSuccess): + return result.unwrap()._inner_value + + error = result.failure()._inner_value + logger.exception("Failed to summarize transcript", exc_info=error) + raise api_error_exception( + errorId=ApiErrorCodes.UNEXPECTED_ERROR, + status=HTTPStatus.INTERNAL_SERVER_ERROR, + debugMessage="Failed to generate summary", + ) from error + + return router diff --git a/src/transcribo_backend/routes/transcribe_route.py b/src/transcribo_backend/routes/transcribe_route.py new file mode 100644 index 0000000..a0dcb8a --- /dev/null +++ b/src/transcribo_backend/routes/transcribe_route.py @@ -0,0 +1,157 @@ +from http import HTTPStatus +from typing import Annotated + +import httpx +from dcc_backend_common.fastapi_error_handling import ApiErrorCodes, api_error_exception +from dcc_backend_common.logger import get_logger +from dcc_backend_common.usage_tracking import UsageTrackingService +from dependency_injector.wiring import Provide, inject +from fastapi import APIRouter, Header, HTTPException, UploadFile +from returns.io import IOSuccess + +from transcribo_backend.container import Container +from transcribo_backend.helpers.file_type import is_audio_file, is_video_file +from transcribo_backend.models.task_status import TaskStatus +from transcribo_backend.models.transcription_response import TranscriptionResponse +from transcribo_backend.services.whisper_service import WhisperService + + +def _is_not_found_error(error: Exception) -> bool: + """Check if the error represents a 'not found' condition (404).""" + if isinstance(error, HTTPException): + return error.status_code == HTTPStatus.NOT_FOUND + if isinstance(error, httpx.HTTPStatusError): + return error.response.status_code == HTTPStatus.NOT_FOUND + return False + + +@inject +def create_router( # noqa: C901 + whisper_service: WhisperService = Provide[Container.whisper_service], + usage_tracking_service: UsageTrackingService = Provide[Container.usage_tracking_service], +) -> APIRouter: + """ + Create the router for the transcription API. + """ + logger = get_logger(__name__) + logger.info("Creating transcription router") + router = APIRouter() + + @router.get("/task/{task_id}/status") + async def get_task_status(task_id: str) -> TaskStatus: + """ + Endpoint to get the status of a task by task_id. + """ + result = await whisper_service.transcribe_get_task_status(task_id) + if isinstance(result, IOSuccess): + return result.unwrap()._inner_value + + error = result.failure()._inner_value + logger.exception(f"Failed to get task status for {task_id}", exc_info=error) + if _is_not_found_error(error): + raise api_error_exception( + errorId=ApiErrorCodes.RESOURCE_NOT_FOUND, + status=HTTPStatus.NOT_FOUND, + debugMessage=f"Task {task_id} not found", + ) from error + + raise api_error_exception( + errorId=ApiErrorCodes.UNEXPECTED_ERROR, + status=HTTPStatus.INTERNAL_SERVER_ERROR, + debugMessage="Failed to get task status", + ) from error + + @router.get("/task/{task_id}/result") + async def get_task_result(task_id: str) -> TranscriptionResponse: + """ + Endpoint to get the result of a task by task_id. + """ + result = await whisper_service.transcribe_get_task_result(task_id) + if isinstance(result, IOSuccess): + return result.unwrap()._inner_value + + error = result.failure()._inner_value + logger.exception(f"Failed to get task result for {task_id}", exc_info=error) + if _is_not_found_error(error): + raise api_error_exception( + errorId=ApiErrorCodes.RESOURCE_NOT_FOUND, + status=HTTPStatus.NOT_FOUND, + debugMessage=f"Task result for {task_id} not found", + ) from error + + raise api_error_exception( + errorId=ApiErrorCodes.UNEXPECTED_ERROR, + status=HTTPStatus.INTERNAL_SERVER_ERROR, + debugMessage="Failed to get task result", + ) from error + + @router.post("/transcribe") + async def submit_transcribe( + audio_file: UploadFile, + num_speakers: int | None = None, + language: str | None = None, + x_client_id: Annotated[str | None, Header()] = None, + ) -> TaskStatus: + """ + Endpoint to submit a transcription task. + """ + if audio_file.content_type is None: + raise api_error_exception( + errorId=ApiErrorCodes.INVALID_REQUEST, + status=HTTPStatus.BAD_REQUEST, + debugMessage="Content type of the audio file is None", + ) + + if audio_file.filename is None: + raise api_error_exception( + errorId=ApiErrorCodes.INVALID_REQUEST, + status=HTTPStatus.BAD_REQUEST, + debugMessage="Filename of the audio file is None", + ) + + if not is_audio_file(audio_file.content_type) and not is_video_file(audio_file.content_type): + raise api_error_exception( + errorId=ApiErrorCodes.VALIDATION_ERROR, + status=HTTPStatus.UNSUPPORTED_MEDIA_TYPE, + debugMessage="Unsupported file type", + ) + + # Read the uploaded file content + audio_data = await audio_file.read() + usage_tracking_service.log_event( + module="transcribe_route", + func="transcribe", + user_id=x_client_id or "unknown", + num_speakers=num_speakers, + file_size=len(audio_data), + ) + + # Submit the transcription task + result = await whisper_service.transcribe_submit_task( + audio_data, diarization_speaker_count=num_speakers, language=language + ) + + if isinstance(result, IOSuccess): + return result.unwrap()._inner_value + + error = result.failure()._inner_value + logger.exception("Failed to submit transcription task", exc_info=error) + + status_code = HTTPStatus.INTERNAL_SERVER_ERROR + error_code = ApiErrorCodes.UNEXPECTED_ERROR + message = "Failed to submit transcription task" + + if isinstance(error, HTTPException): + status_code = error.status_code + if status_code == HTTPStatus.TOO_MANY_REQUESTS: + message = "Too many requests" + elif status_code == HTTPStatus.REQUEST_ENTITY_TOO_LARGE: + message = "File is too large" + + raise api_error_exception( + errorId=error_code, + status=status_code, + debugMessage=message, + ) from error + + return router diff --git a/src/transcribo_backend/services/audio_converter.py b/src/transcribo_backend/services/audio_converter.py index 9eca0dc..5d80e6a 100644 --- a/src/transcribo_backend/services/audio_converter.py +++ b/src/transcribo_backend/services/audio_converter.py @@ -2,9 +2,8 @@ import tempfile from pathlib import Path -from fastapi import HTTPException - -from transcribo_backend.utils.logger import get_logger +from dcc_backend_common.logger import get_logger +from returns.io import impure_safe logger = get_logger(__name__) @@ -12,7 +11,8 @@ class AudioConversionError(Exception): """Custom exception for audio conversion errors.""" - pass + def __init__(self, error_message: str): + super().__init__(f"FFmpeg conversion failed: {error_message}") def is_mp3_format(audio_data: bytes) -> bool: @@ -45,6 +45,7 @@ def is_mp3_format(audio_data: bytes) -> bool: return False +@impure_safe def convert_to_mp3(file_data: bytes) -> bytes: """ Convert audio or video data to MP3 format using FFmpeg with balanced quality settings. @@ -53,11 +54,10 @@ def convert_to_mp3(file_data: bytes) -> bytes: file_data: The audio/video bytes Returns: - Bytes of the audio in MP3 format + IOResult[bytes, Exception]: The converted audio in MP3 format or an error Raises: - AudioConversionError: If conversion fails - HTTPException: For HTTP-specific errors + AudioConversionError: If conversion fails (inside the Result) """ try: file_size_mb = len(file_data) / (1024 * 1024) @@ -96,7 +96,7 @@ def convert_to_mp3(file_data: bytes) -> bytes: logger.info("Running FFmpeg conversion with balanced quality (64k bitrate)") # Run FFmpeg - result = subprocess.run( + result = subprocess.run( # noqa: S603 cmd, capture_output=True, text=True, @@ -106,10 +106,11 @@ def convert_to_mp3(file_data: bytes) -> bytes: if result.returncode != 0: error_msg = result.stderr or "Unknown FFmpeg error" logger.error(f"FFmpeg conversion failed: {error_msg}") - raise AudioConversionError(f"FFmpeg conversion failed: {error_msg}") + raise AudioConversionError(error_msg) # Read the converted file with open(output_path, "rb") as f: + print(type(f)) converted_data = f.read() output_size_mb = len(converted_data) / (1024 * 1024) @@ -129,11 +130,5 @@ def convert_to_mp3(file_data: bytes) -> bytes: logger.warning(f"Failed to clean up temporary files: {e}") except (subprocess.TimeoutExpired, subprocess.SubprocessError) as e: - logger.error(f"FFmpeg subprocess error: {e}") - raise AudioConversionError(f"FFmpeg subprocess error: {e}") from e - except AudioConversionError: - # Re-raise our custom exceptions as-is - raise - except Exception as e: - logger.exception("Unexpected error during audio conversion") - raise HTTPException(status_code=500, detail=f"Error converting to MP3: {e!s}") from e + logger.exception("FFmpeg subprocess error") + raise AudioConversionError(str(e)) from e diff --git a/src/transcribo_backend/services/summarization_service.py b/src/transcribo_backend/services/summarization_service.py new file mode 100644 index 0000000..d8ef8e5 --- /dev/null +++ b/src/transcribo_backend/services/summarization_service.py @@ -0,0 +1,19 @@ +from returns.future import future_safe + +from transcribo_backend.agents.summarize_agent import create_summarize_agent +from transcribo_backend.models.summary import Summary +from transcribo_backend.utils.app_config import AppConfig + + +class SummarizationService: + def __init__(self, app_config: AppConfig): + self.app_config = app_config + self.agent = create_summarize_agent(app_config) + + @future_safe + async def summarize(self, transcript: str) -> Summary: + """ + Summarize a transcript of a meeting. + """ + result = await self.agent.run(transcript) + return Summary(summary=result.output) diff --git a/src/transcribo_backend/services/summary_service.py b/src/transcribo_backend/services/summary_service.py deleted file mode 100644 index 7a3419b..0000000 --- a/src/transcribo_backend/services/summary_service.py +++ /dev/null @@ -1,49 +0,0 @@ -from openai import AsyncOpenAI - -from transcribo_backend.config import settings -from transcribo_backend.models.summary import Summary - -system_prompt = """ -You are a meeting summary expert. -You are given a transcript of a meeting and you need to summarize it. -You need to summarize the meeting in a way that is easy to understand and use. -You need to include the main points of the meeting, the decisions made, and the action items. -You need to include the names of the participants. -You use markdown to format the summary. -Use the same language as used in the transcript to summarize the meeting. -If you are not sure about the language, use German. -""" - - -async def summarize(transcript: str) -> Summary: - """ - Summarize a transcript of a meeting. - """ - - -async def summarize(transcript: str) -> Summary: - """ - Summarize a transcript of a meeting. - """ - try: - client = AsyncOpenAI(api_key=settings.api_key, base_url=settings.llm_api) - models = await client.models.list() - - if not models.data: - raise ValueError("Could not find any models available from the API") - - model = models.data[0].id - except Exception as e: - raise RuntimeError("Failed to initialize OpenAI client or fetch models.") from e - - # Disable Qwen3 thinking mode for faster response - transcript = transcript + "\nothink" - - try: - response = await client.chat.completions.create( - model=model, - messages=[{"role": "system", "content": system_prompt}, {"role": "user", "content": transcript}], - ) - return Summary(summary=response.choices[0].message.content) - except Exception as e: - raise RuntimeError("Failed to generate summary.") from e diff --git a/src/transcribo_backend/services/whisper_service.py b/src/transcribo_backend/services/whisper_service.py index b9b432c..6dd245c 100644 --- a/src/transcribo_backend/services/whisper_service.py +++ b/src/transcribo_backend/services/whisper_service.py @@ -2,10 +2,11 @@ import uuid from typing import Any -import aiohttp +import httpx +from cachetools import TTLCache from fastapi import HTTPException +from returns.future import future_safe -from transcribo_backend.config import settings from transcribo_backend.models.progress import ProgressResponse from transcribo_backend.models.response_format import ResponseFormat from transcribo_backend.models.task_status import TaskStatus, TaskStatusEnum @@ -15,64 +16,75 @@ convert_to_mp3, is_mp3_format, ) - -taskId_to_progressId: dict[str, str] = {} - - -async def transcribe_get_task_status(task_id: str) -> TaskStatus: - """ - Checks the status of an ongoing transcription task. - - Args: - task_id: The ID of the task to check - - Returns: - TaskStatus: The current status of the task - """ - if task_id not in taskId_to_progressId: - raise HTTPException(status_code=404, detail="Task not found") - - url = f"{settings.whisper_api}/audio/transcriptions/task/status?task_id={task_id}" - progress_url = f"{settings.whisper_api}/progress/{taskId_to_progressId[task_id]}" - - # Get the status of the transcription task - async with ( - aiohttp.ClientSession() as session, - session.get(url) as response, - session.get(progress_url) as progress_response, - ): - if response.status == 404: +from transcribo_backend.utils.app_config import AppConfig + + +class WhisperService: + def __init__(self, app_config: AppConfig) -> None: + self.app_config = app_config + one_day = 60 * 60 * 24 + self.taskId_to_progressId: TTLCache[str, str] = TTLCache(maxsize=1024, ttl=one_day) + timeout = httpx.Timeout(10.0) + limits = httpx.Limits(max_connections=100, max_keepalive_connections=20) + api_key_header = {"Authorization": f"Bearer {self.app_config.api_key}"} + self.client = httpx.AsyncClient(timeout=timeout, limits=limits, headers=api_key_header) + + async def aclose(self) -> None: + """Close the HTTP client to prevent connection leaks.""" + await self.client.aclose() + + @future_safe + async def transcribe_get_task_status(self, task_id: str) -> TaskStatus: + """ + Checks the status of an ongoing transcription task. + + Args: + task_id: The ID of the task to check + + Returns: + TaskStatus: The current status of the task + """ + if task_id not in self.taskId_to_progressId: + raise HTTPException(status_code=404, detail="Task not found") + whisper_url = self.app_config.whisper_url + url = f"{whisper_url}/audio/transcriptions/task/status?task_id={task_id}" + progress_url = f"{whisper_url}/progress/{self.taskId_to_progressId[task_id]}" + + # Get the status of the transcription task + response = await self.client.get(url) + if response.status_code == 404: return TaskStatus(task_id=task_id, status=TaskStatusEnum.FAILED) response.raise_for_status() - if progress_response.status == 404: + + progress_response = await self.client.get(progress_url) + if progress_response.status_code == 404: raise HTTPException(status_code=404, detail="Progress not found") progress_response.raise_for_status() - progress = ProgressResponse(**await progress_response.json()) - return TaskStatus(**await response.json(), progress=progress.progress) - + progress = ProgressResponse(**progress_response.json()) + return TaskStatus(**response.json(), progress=progress.progress) -async def transcribe_get_task_result(task_id: str) -> TranscriptionResponse: - """ - Retrieves the result of a completed transcription task. + @future_safe + async def transcribe_get_task_result(self, task_id: str) -> TranscriptionResponse: + """ + Retrieves the result of a completed transcription task. - Args: - task_id: The ID of the completed task + Args: + task_id: The ID of the completed task - Returns: - TranscriptionVerboseJsonResponse: The parsed transcription result - """ - url = f"{settings.whisper_api}/audio/transcriptions/task/get?task_id={task_id}" + Returns: + TranscriptionVerboseJsonResponse: The parsed transcription result + """ + whisper_url = self.app_config.whisper_url + url = f"{whisper_url}/audio/transcriptions/task/get?task_id={task_id}" - # Get the transcription result - async with ( - aiohttp.ClientSession() as session, - session.get(url) as response, - ): + # Get the transcription result + response = await self.client.get(url) response.raise_for_status() - result_data = await response.json() + result_data = response.json() - taskId_to_progressId.pop(task_id, None) + if task_id in self.taskId_to_progressId: + del self.taskId_to_progressId[task_id] transcription = TranscriptionResponse(**result_data) for segment in transcription.segments: @@ -83,129 +95,121 @@ async def transcribe_get_task_result(task_id: str) -> TranscriptionResponse: return TranscriptionResponse(**result_data) + @future_safe + async def transcribe_retry_task(self, task_id: str) -> TaskStatus: + """ + Retries a failed transcription task. -async def transcribe_retry_task(task_id: str) -> TaskStatus: - """ - Retries a failed transcription task. + Args: + task_id: The ID of the task to retry - Args: - task_id: The ID of the task to retry + Returns: + TaskStatus: The updated status of the task + """ + whisper_url = self.app_config.whisper_url + url = f"{whisper_url}/audio/transcriptions/task/retry?task_id={task_id}" - Returns: - TaskStatus: The updated status of the task - """ - url = f"{settings.whisper_api}/audio/transcriptions/task/retry?task_id={task_id}" - - async with ( - aiohttp.ClientSession() as session, - session.post(url) as response, - ): + response = await self.client.post(url) response.raise_for_status() - return TaskStatus(**await response.json()) - + return TaskStatus(**response.json()) -async def transcribe_cancel_task(task_id: str) -> TaskStatus: - """ - Cancels an ongoing transcription task. + @future_safe + async def transcribe_cancel_task(self, task_id: str) -> TaskStatus: + """ + Cancels an ongoing transcription task. - Args: - task_id: The ID of the task to cancel + Args: + task_id: The ID of the task to cancel - Returns: - TaskStatus: The updated status of the task - """ - url = f"{settings.whisper_api}/audio/transcriptions/task/cancel?task_id={task_id}" + Returns: + TaskStatus: The updated status of the task + """ + whisper_url = self.app_config.whisper_url + url = f"{whisper_url}/audio/transcriptions/task/cancel?task_id={task_id}" - async with ( - aiohttp.ClientSession() as session, - session.put(url) as response, - ): + response = await self.client.put(url) response.raise_for_status() - return TaskStatus(**await response.json()) - - -async def transcribe_submit_task( - audio_data: bytes, - file_format: str, - model: str = "large-v2", - language: str | None = None, - prompt: str | None = None, - response_format: ResponseFormat = ResponseFormat.JSON_DIARIZED, - temperature: float | list[float] | None = None, - vad_filter: bool = True, - diarization: bool = True, - diarization_speaker_count: int | None = None, - timestamp_granularities: str = "segment", - **kwargs: Any, -) -> TaskStatus: - """ - Submits a new transcription task with additional parameters. - - Args: - audio_data: The binary audio data to transcribe - file_format: The format of the audio data - model: The Whisper model to use - language: The language code for transcription - prompt: Optional prompt for the model - response_format: Format of the output (enum: ResponseFormat) - temperature: Temperature value(s) for sampling - vad_filter: Whether to use voice activity detection - diarization: Whether to separate speakers - diarization_speaker_count: Number of speakers to separate - **kwargs: Additional parameters to pass to the API - - Returns: - TaskStatus: The status of the created task - """ - url = f"{settings.whisper_api}/audio/transcriptions/task/submit" - - if temperature is None: - temperature = [0.0, 0.2, 0.4, 0.6, 0.8, 1.0] - - # Convert to MP3 if not already in MP3 format - if not is_mp3_format(audio_data): - try: - # Convert with balanced quality settings - audio_data = convert_to_mp3(audio_data) - except AudioConversionError as e: - raise HTTPException(status_code=400, detail=f"Audio conversion failed: {e}") from e - - # Prepare form data - form_data = aiohttp.FormData() - form_data.add_field("file", audio_data, filename="audio.mp3") - form_data.add_field("model", model) - - progress_id = uuid.uuid4().hex - form_data.add_field("progress_id", progress_id) - if language: - form_data.add_field("language", language) - if prompt: - form_data.add_field("prompt", prompt) - form_data.add_field("response_format", response_format.value) # Use the enum value - form_data.add_field("timestamp_granularities[]", timestamp_granularities) - - form_data.add_field("temperature", str(temperature)) - - if diarization_speaker_count: - form_data.add_field("diarization_speaker_count", str(diarization_speaker_count)) - - # Add boolean parameters - form_data.add_field("vad_filter", str(vad_filter)) - form_data.add_field("diarization", str(diarization)) - - # Add any additional parameters - for key, value in kwargs.items(): - if isinstance(value, list | dict): - form_data.add_field(key, json.dumps(value)) - else: - form_data.add_field(key, str(value)) - - # Send the request - async with ( - aiohttp.ClientSession() as session, - session.post(url, data=form_data) as response, - ): + return TaskStatus(**response.json()) + + @future_safe + async def transcribe_submit_task( + self, + audio_data: bytes, + model: str = "large-v2", + language: str | None = None, + prompt: str | None = None, + response_format: ResponseFormat = ResponseFormat.JSON_DIARIZED, + temperature: float | list[float] | None = None, + vad_filter: bool = True, + diarization: bool = True, + diarization_speaker_count: int | None = None, + timestamp_granularities: str = "segment", + **kwargs: Any, + ) -> TaskStatus: + """ + Submits a new transcription task with additional parameters. + + Args: + audio_data: The binary audio data to transcribe + model: The Whisper model to use + language: The language code for transcription + prompt: Optional prompt for the model + response_format: Format of the output (enum: ResponseFormat) + temperature: Temperature value(s) for sampling + vad_filter: Whether to use voice activity detection + diarization: Whether to separate speakers + diarization_speaker_count: Number of speakers to separate + **kwargs: Additional parameters to pass to the API + + Returns: + TaskStatus: The status of the created task + """ + whisper_url = self.app_config.whisper_url + url = f"{whisper_url}/audio/transcriptions/task/submit" + + if temperature is None: + temperature = [0.0, 0.2, 0.4, 0.6, 0.8, 1.0] + + # Convert to MP3 if not already in MP3 format + if not is_mp3_format(audio_data): + try: + # Convert with balanced quality settings + # convert_to_mp3 now returns IOResult, we unwrap it to get the value or raise exception + audio_data = convert_to_mp3(audio_data).unwrap()._inner_value + except AudioConversionError as e: + raise HTTPException(status_code=400, detail=f"Audio conversion failed: {e}") from e + + # Prepare form data + data: dict[str, Any] = {"model": model} + files = {"file": ("audio.mp3", audio_data, "audio/mpeg")} + + progress_id = uuid.uuid4().hex + data["progress_id"] = progress_id + if language: + data["language"] = language + if prompt: + data["prompt"] = prompt + data["response_format"] = response_format.value + data["timestamp_granularities[]"] = timestamp_granularities + data["temperature"] = str(temperature) + + if diarization_speaker_count: + data["diarization_speaker_count"] = str(diarization_speaker_count) + + # Add boolean parameters + data["vad_filter"] = str(vad_filter) + data["diarization"] = str(diarization) + + # Add any additional parameters + for key, value in kwargs.items(): + if isinstance(value, list | dict): + data[key] = json.dumps(value) + else: + data[key] = str(value) + + # Send the request + response = await self.client.post(url, data=data, files=files) response.raise_for_status() - status = TaskStatus(**await response.json()) - taskId_to_progressId[status.task_id] = progress_id + status = TaskStatus(**response.json()) + self.taskId_to_progressId[status.task_id] = progress_id return status diff --git a/src/transcribo_backend/utils/__init__.py b/src/transcribo_backend/utils/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/src/transcribo_backend/utils/app_config.py b/src/transcribo_backend/utils/app_config.py new file mode 100644 index 0000000..6b8dac5 --- /dev/null +++ b/src/transcribo_backend/utils/app_config.py @@ -0,0 +1,41 @@ +from dcc_backend_common.config import AbstractAppConfig, get_env_or_throw, log_secret +from pydantic import Field + + +class AppConfig(AbstractAppConfig): + llm_base_url: str = Field(description="The base URL for the OpenAI API") + api_key: str = Field(description="The API key for authenticating with OpenAI") + llm_model: str = Field(description="The language model to use for text generation") + client_url: str = Field(description="The URL for the client application") + hmac_secret: str = Field(description="The secret key for HMAC authentication") + whisper_url: str = Field(description="The URL for the Whisper API") + + @classmethod + def from_env(cls) -> "AppConfig": + llm_base_url: str = get_env_or_throw("LLM_BASE_URL") + api_key: str = get_env_or_throw("API_KEY") + llm_model: str = get_env_or_throw("LLM_MODEL") + client_url: str = get_env_or_throw("CLIENT_URL") + hmac_secret: str = get_env_or_throw("HMAC_SECRET") + whisper_url: str = get_env_or_throw("WHISPER_URL") + + return cls( + llm_base_url=llm_base_url, + api_key=api_key, + llm_model=llm_model, + client_url=client_url, + hmac_secret=hmac_secret, + whisper_url=whisper_url, + ) + + def __str__(self) -> str: + return f""" + AppConfig( + client_url={self.client_url}, + openai_api_base_url={self.llm_base_url}, + openai_api_key={log_secret(self.api_key)}, + llm_model={self.llm_model}, + hmac_secret={log_secret(self.hmac_secret)}, + whisper_url={self.whisper_url} + ) + """ diff --git a/src/transcribo_backend/utils/logger.py b/src/transcribo_backend/utils/logger.py deleted file mode 100644 index 91c0244..0000000 --- a/src/transcribo_backend/utils/logger.py +++ /dev/null @@ -1,85 +0,0 @@ -import logging -import os - -import structlog -import structlog.processors -from structlog.processors import CallsiteParameter -from structlog.stdlib import BoundLogger -from structlog.types import Processor - - -# Standard library logging setup -def setup_stdlib_logging() -> None: - """Configure standard library logging to work with structlog.""" - log_level = os.getenv("LOG_LEVEL", "INFO").upper() - level = getattr(logging, log_level, logging.INFO) - - # Create a handler for console output - handler = logging.StreamHandler() - - # Configure root logger - root_logger = logging.getLogger() - root_logger.setLevel(level) - root_logger.addHandler(handler) - - # Disable propagation for libraries that are too verbose - for logger_name in ["uvicorn.access"]: - lib_logger = logging.getLogger(logger_name) - lib_logger.propagate = False - - -def init_logger() -> None: - """ - Initialize the logger configuration based on environment. - Uses JSON renderer in production environment for compatibility with fluentbit. - Adds the module name as context to the logger. - """ - # Set up standard library logging first - setup_stdlib_logging() - - # Define processors list for structlog - processors: list[Processor] = [ - structlog.stdlib.filter_by_level, # Filter logs by configured level - structlog.processors.add_log_level, - structlog.processors.StackInfoRenderer(), - structlog.processors.CallsiteParameterAdder( - parameters=[ - CallsiteParameter.MODULE, - CallsiteParameter.FUNC_NAME, - CallsiteParameter.LINENO, - ] - ), - structlog.processors.UnicodeDecoder(), - ] - - # Use different renderers for development vs production - if os.getenv("PROD"): - # JSON renderer for production to be fluentbit compatible - processors.append(structlog.processors.JSONRenderer()) - else: - # For development, use a colored console renderer - processors.append(structlog.dev.ConsoleRenderer(colors=True)) - - # Configure structlog - structlog.configure( - processors=processors, - context_class=dict, - logger_factory=structlog.stdlib.LoggerFactory(), - wrapper_class=structlog.stdlib.BoundLogger, - cache_logger_on_first_use=True, - ) - - -def get_logger(name: str | None = None) -> BoundLogger: - """ - Get a structured logger instance. - - Args: - name: Optional name for the logger, typically the module name - - Returns: - A bound logger instance for structured logging - """ - if name: - return structlog.get_logger(name) # type: ignore - return structlog.get_logger() # type: ignore diff --git a/src/transcribo_backend/utils/usage_tracking.py b/src/transcribo_backend/utils/usage_tracking.py deleted file mode 100644 index 0c21125..0000000 --- a/src/transcribo_backend/utils/usage_tracking.py +++ /dev/null @@ -1,15 +0,0 @@ -import hashlib -import hmac - -from transcribo_backend.config import settings - - -def get_pseudonymized_user_id(user_id: str) -> str: - """ - Generates a consistent, one-way pseudonym for a given user ID. - """ - if user_id is None: - user_id = "unknown" - message = user_id.encode("utf-8") - signature = hmac.new(settings.hmac_secret.encode("utf-8"), message, hashlib.sha256).hexdigest() - return signature diff --git a/tests/test_audio_converter.py b/tests/test_audio_converter.py index b819bce..4965b2a 100644 --- a/tests/test_audio_converter.py +++ b/tests/test_audio_converter.py @@ -1,9 +1,11 @@ """Tests for the improved audio converter module.""" import pytest +from returns.io import IOResult from transcribo_backend.services.audio_converter import ( AudioConversionError, + convert_to_mp3, ) @@ -14,3 +16,11 @@ def test_audio_conversion_error(self): """Test AudioConversionError can be raised and caught.""" with pytest.raises(AudioConversionError): raise AudioConversionError("Test error message") + + +def test_convert_to_mp3_returns_io_result(): + """Test that convert_to_mp3 returns an IOResult.""" + # We don't necessarily need to run ffmpeg here, just check the type if we mock or pass empty data + # Passing empty data will likely fail in ffmpeg but should still return a Failure(IOResult) + result = convert_to_mp3(b"") + assert isinstance(result, IOResult) diff --git a/tests/test_summarization_service_agent.py b/tests/test_summarization_service_agent.py new file mode 100644 index 0000000..f32495b --- /dev/null +++ b/tests/test_summarization_service_agent.py @@ -0,0 +1,43 @@ +from unittest.mock import AsyncMock, MagicMock, patch + +import pytest + +from transcribo_backend.services.summarization_service import SummarizationService +from transcribo_backend.utils.app_config import AppConfig + + +@pytest.mark.anyio +async def test_summarize_calls_agent(): + # Mock AppConfig + app_config = MagicMock(spec=AppConfig) + + # Mock the Agent and its run method + mock_agent = MagicMock() + mock_run_result = MagicMock() + mock_run_result.output = "This is a summary." + mock_agent.run = AsyncMock(return_value=mock_run_result) + + # Patch create_summarize_agent to return our mock agent + with patch( + "transcribo_backend.services.summarization_service.create_summarize_agent", return_value=mock_agent + ) as mock_create: + service = SummarizationService(app_config) + + # Verify agent creation was called + mock_create.assert_called_once_with(app_config) + + transcript = "Some meeting transcript." + # Awaiting a FutureResult returns a Result (e.g., IOResult) + # Result.unwrap() should give the value. + result = (await service.summarize(transcript)).unwrap() + + # If result is an IO container, we get its value. + # In 'returns', IO is often used to wrap values in IOResult. + if hasattr(result, "_inner_value"): + result = result._inner_value + + # Verify run was called + mock_agent.run.assert_called_once_with(transcript) + + # Verify result + assert result.summary == "This is a summary." diff --git a/uv.lock b/uv.lock index a32b2a6..b958185 100644 --- a/uv.lock +++ b/uv.lock @@ -1,9 +1,25 @@ version = 1 revision = 3 -requires-python = ">=3.12, <4.0" +requires-python = ">=3.12, <3.14" resolution-markers = [ - "python_full_version >= '3.13'", - "python_full_version < '3.13'", + "python_full_version >= '3.13' and sys_platform == 'win32'", + "python_full_version >= '3.13' and sys_platform == 'emscripten'", + "python_full_version >= '3.13' and sys_platform != 'emscripten' and sys_platform != 'win32'", + "python_full_version < '3.13' and sys_platform == 'win32'", + "python_full_version < '3.13' and sys_platform == 'emscripten'", + "python_full_version < '3.13' and sys_platform != 'emscripten' and sys_platform != 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