docker build fix

- Add missing GraphQL mutations: retryJob, updateAsset, deleteAsset
- Add UpdateAssetRequest and DeleteResult to schema source of truth
- Move Lambda callback endpoint to main.py (only REST endpoint)
- Remove REST routes, pydantic schemas, and deps
- Remove pydantic target from modelgen.json
- Update architecture diagrams and documentation

.dockerignore

@@ -0,0 +1,30 @@
+# Python
+.venv/
+__pycache__/
+*.pyc
+*.egg-info/
+.pytest_cache/
+
+# Node
+node_modules/
+ui/*/node_modules/
+ui/*/dist/
+
+# Media (9.8GB — mounted via volume, never needed in image)
+media/
+
+# Git
+.git/
+
+# IDE / OS
+.idea/
+.vscode/
+*.swp
+.DS_Store
+
+# Docker
+ctrl/docker-compose.yml
+
+# Docs
+docs/
+*.md

README.md

@@ -71,12 +71,12 @@ docker compose logs -f
 docker compose logs -f celery
 
 # Create admin user
-docker compose exec django python manage.py createsuperuser
+docker compose exec django python admin/manage.py createsuperuser
 ```
 
 ## Code Generation
 
-Models are defined as dataclasses in `schema/models/` and generated via `modelgen`:
+Models are defined as dataclasses in `core/schema/models/` and generated via `modelgen`:
 - **Django ORM** models (`--include dataclasses,enums`)
 - **Pydantic** schemas (`--include dataclasses,enums`)
 - **TypeScript** types (`--include dataclasses,enums,api`)
@@ -113,26 +113,29 @@ See [docs/media-storage.md](docs/media-storage.md) for full details.
 
 ```
 mpr/
-├── api/                 # FastAPI application
+├── admin/               # Django project
-│   ├── routes/          # API endpoints
+│   ├── manage.py        # Django management script
-│   └── schemas/         # Pydantic models (generated)
+│   └── mpr/             # Django settings & app
-├── core/                # Core utilities
+│       └── media_assets/# Django app
-│   └── ffmpeg/          # FFmpeg wrappers
+├── core/                # Core application logic
+│   ├── api/             # FastAPI + GraphQL API
+│   │   └── schema/      # GraphQL types (generated)
+│   ├── ffmpeg/          # FFmpeg wrappers
+│   ├── rpc/             # gRPC server & client
+│   │   └── protos/      # Protobuf definitions (generated)
+│   ├── schema/          # Source of truth
+│   │   └── models/      # Dataclass definitions
+│   ├── storage/         # S3/GCP/local storage backends
+│   └── task/            # Celery job execution
+│       ├── executor.py  # Executor abstraction
+│       └── tasks.py     # Celery tasks
 ├── ctrl/                # Docker & deployment
 │   ├── docker-compose.yml
 │   └── nginx.conf
 ├── media/
 │   ├── in/              # Source media files
 │   └── out/             # Transcoded output
-├── rpc/                 # gRPC server & client
+├── modelgen/            # Code generation tool
-│   └── protos/          # Protobuf definitions (generated)
-├── mpr/                 # Django project
-│   └── media_assets/    # Django app
-├── schema/              # Source of truth
-│   └── models/          # Dataclass definitions
-├── task/                # Celery job execution
-│   ├── executor.py      # Executor abstraction
-│   └── tasks.py         # Celery tasks
 └── ui/                  # Frontend
     └── timeline/        # React app
 ```

admin/manage.py

@@ -6,7 +6,9 @@ import sys
 
 def main():
     """Run administrative tasks."""
-    os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'mpr.settings')
+    # Ensure project root is on sys.path
+    sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+    os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'admin.mpr.settings')
     try:
         from django.core.management import execute_from_command_line
     except ImportError as exc:

admin/mpr/asgi.py

@@ -11,6 +11,6 @@ import os
 
 from django.core.asgi import get_asgi_application
 
-os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'mpr.settings')
+os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'admin.mpr.settings')
 
 application = get_asgi_application()

admin/mpr/celery.py

@@ -2,9 +2,9 @@ import os
 
 from celery import Celery
 
-os.environ.setdefault("DJANGO_SETTINGS_MODULE", "mpr.settings")
+os.environ.setdefault("DJANGO_SETTINGS_MODULE", "admin.mpr.settings")
 
 app = Celery("mpr")
 app.config_from_object("django.conf:settings", namespace="CELERY")
 app.autodiscover_tasks()
-app.autodiscover_tasks(["task"])
+app.autodiscover_tasks(["core.task"])

admin/mpr/media_assets/apps.py

@@ -3,5 +3,6 @@ from django.apps import AppConfig
 
 class MediaAssetsConfig(AppConfig):
     default_auto_field = "django.db.models.BigAutoField"
-    name = "mpr.media_assets"
+    name = "admin.mpr.media_assets"
+    label = "media_assets"
     verbose_name = "Media Assets"

admin/mpr/media_assets/management/commands/loadbuiltins.py

@@ -4,10 +4,10 @@ from pathlib import Path
 
 from django.core.management.base import BaseCommand
 
-from mpr.media_assets.models import TranscodePreset
+from admin.mpr.media_assets.models import TranscodePreset
 
-sys.path.insert(0, str(Path(__file__).resolve().parent.parent.parent.parent.parent))
+sys.path.insert(0, str(Path(__file__).resolve().parent.parent.parent.parent.parent.parent))
-from schema.models import BUILTIN_PRESETS
+from core.schema.models import BUILTIN_PRESETS
 
 
 class Command(BaseCommand):

admin/mpr/media_assets/migrations/0001_initial.py

@@ -1,8 +1,7 @@
-# Generated by Django 6.0.1 on 2026-02-01 15:13
+# Generated by Django 4.2.29 on 2026-03-13 04:04
 
-import django.db.models.deletion
-import uuid
 from django.db import migrations, models
+import uuid
 
 
 class Migration(migrations.Migration):
@@ -13,47 +12,21 @@ class Migration(migrations.Migration):
     ]
 
     operations = [
-        migrations.CreateModel(
-            name='TranscodePreset',
-            fields=[
-                ('id', models.UUIDField(default=uuid.uuid4, editable=False, primary_key=True, serialize=False)),
-                ('name', models.CharField(max_length=100, unique=True)),
-                ('description', models.TextField(blank=True, default='')),
-                ('is_builtin', models.BooleanField(default=False)),
-                ('container', models.CharField(default='mp4', max_length=20)),
-                ('video_codec', models.CharField(default='libx264', max_length=50)),
-                ('video_bitrate', models.CharField(blank=True, max_length=20, null=True)),
-                ('video_crf', models.IntegerField(blank=True, null=True)),
-                ('video_preset', models.CharField(blank=True, max_length=20, null=True)),
-                ('resolution', models.CharField(blank=True, max_length=20, null=True)),
-                ('framerate', models.FloatField(blank=True, null=True)),
-                ('audio_codec', models.CharField(default='aac', max_length=50)),
-                ('audio_bitrate', models.CharField(blank=True, max_length=20, null=True)),
-                ('audio_channels', models.IntegerField(blank=True, null=True)),
-                ('audio_samplerate', models.IntegerField(blank=True, null=True)),
-                ('extra_args', models.JSONField(blank=True, default=list)),
-                ('created_at', models.DateTimeField(auto_now_add=True)),
-                ('updated_at', models.DateTimeField(auto_now=True)),
-            ],
-            options={
-                'ordering': ['name'],
-            },
-        ),
         migrations.CreateModel(
             name='MediaAsset',
             fields=[
                 ('id', models.UUIDField(default=uuid.uuid4, editable=False, primary_key=True, serialize=False)),
                 ('filename', models.CharField(max_length=500)),
                 ('file_path', models.CharField(max_length=1000)),
-                ('status', models.CharField(choices=[('pending', 'Pending Probe'), ('ready', 'Ready'), ('error', 'Error')], default='pending', max_length=20)),
+                ('status', models.CharField(choices=[('pending', 'Pending'), ('ready', 'Ready'), ('error', 'Error')], default='pending', max_length=20)),
-                ('error_message', models.TextField(blank=True, null=True)),
+                ('error_message', models.TextField(blank=True, default='')),
                 ('file_size', models.BigIntegerField(blank=True, null=True)),
-                ('duration', models.FloatField(blank=True, null=True)),
+                ('duration', models.FloatField(blank=True, default=None, null=True)),
-                ('video_codec', models.CharField(blank=True, max_length=50, null=True)),
+                ('video_codec', models.CharField(blank=True, max_length=255, null=True)),
-                ('audio_codec', models.CharField(blank=True, max_length=50, null=True)),
+                ('audio_codec', models.CharField(blank=True, max_length=255, null=True)),
-                ('width', models.IntegerField(blank=True, null=True)),
+                ('width', models.IntegerField(blank=True, default=None, null=True)),
-                ('height', models.IntegerField(blank=True, null=True)),
+                ('height', models.IntegerField(blank=True, default=None, null=True)),
-                ('framerate', models.FloatField(blank=True, null=True)),
+                ('framerate', models.FloatField(blank=True, default=None, null=True)),
                 ('bitrate', models.BigIntegerField(blank=True, null=True)),
                 ('properties', models.JSONField(blank=True, default=dict)),
                 ('comments', models.TextField(blank=True, default='')),
@@ -63,36 +36,61 @@ class Migration(migrations.Migration):
             ],
             options={
                 'ordering': ['-created_at'],
-                'indexes': [models.Index(fields=['status'], name='media_asset_status_9ea2f2_idx'), models.Index(fields=['created_at'], name='media_asset_created_368039_idx')],
             },
         ),
         migrations.CreateModel(
             name='TranscodeJob',
             fields=[
                 ('id', models.UUIDField(default=uuid.uuid4, editable=False, primary_key=True, serialize=False)),
+                ('source_asset_id', models.UUIDField()),
+                ('preset_id', models.UUIDField(blank=True, null=True)),
                 ('preset_snapshot', models.JSONField(blank=True, default=dict)),
-                ('trim_start', models.FloatField(blank=True, null=True)),
+                ('trim_start', models.FloatField(blank=True, default=None, null=True)),
-                ('trim_end', models.FloatField(blank=True, null=True)),
+                ('trim_end', models.FloatField(blank=True, default=None, null=True)),
                 ('output_filename', models.CharField(max_length=500)),
                 ('output_path', models.CharField(blank=True, max_length=1000, null=True)),
+                ('output_asset_id', models.UUIDField(blank=True, null=True)),
                 ('status', models.CharField(choices=[('pending', 'Pending'), ('processing', 'Processing'), ('completed', 'Completed'), ('failed', 'Failed'), ('cancelled', 'Cancelled')], default='pending', max_length=20)),
                 ('progress', models.FloatField(default=0.0)),
-                ('current_frame', models.IntegerField(blank=True, null=True)),
+                ('current_frame', models.IntegerField(blank=True, default=None, null=True)),
-                ('current_time', models.FloatField(blank=True, null=True)),
+                ('current_time', models.FloatField(blank=True, default=None, null=True)),
-                ('speed', models.CharField(blank=True, max_length=20, null=True)),
+                ('speed', models.CharField(blank=True, max_length=255, null=True)),
-                ('error_message', models.TextField(blank=True, null=True)),
+                ('error_message', models.TextField(blank=True, default='')),
-                ('celery_task_id', models.CharField(blank=True, max_length=100, null=True)),
+                ('celery_task_id', models.CharField(blank=True, max_length=255, null=True)),
+                ('execution_arn', models.CharField(blank=True, max_length=255, null=True)),
                 ('priority', models.IntegerField(default=0)),
                 ('created_at', models.DateTimeField(auto_now_add=True)),
                 ('started_at', models.DateTimeField(blank=True, null=True)),
                 ('completed_at', models.DateTimeField(blank=True, null=True)),
-                ('output_asset', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='source_jobs', to='media_assets.mediaasset')),
-                ('source_asset', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='transcode_jobs', to='media_assets.mediaasset')),
-                ('preset', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='jobs', to='media_assets.transcodepreset')),
             ],
             options={
-                'ordering': ['priority', 'created_at'],
+                'ordering': ['-created_at'],
-                'indexes': [models.Index(fields=['status', 'priority'], name='media_asset_status_e6ac18_idx'), models.Index(fields=['created_at'], name='media_asset_created_ba3a46_idx'), models.Index(fields=['celery_task_id'], name='media_asset_celery__81a88e_idx')],
+            },
+        ),
+        migrations.CreateModel(
+            name='TranscodePreset',
+            fields=[
+                ('id', models.UUIDField(default=uuid.uuid4, editable=False, primary_key=True, serialize=False)),
+                ('name', models.CharField(max_length=255)),
+                ('description', models.TextField(blank=True, default='')),
+                ('is_builtin', models.BooleanField(default=False)),
+                ('container', models.CharField(max_length=255)),
+                ('video_codec', models.CharField(max_length=255)),
+                ('video_bitrate', models.CharField(blank=True, max_length=255, null=True)),
+                ('video_crf', models.IntegerField(blank=True, default=None, null=True)),
+                ('video_preset', models.CharField(blank=True, max_length=255, null=True)),
+                ('resolution', models.CharField(blank=True, max_length=255, null=True)),
+                ('framerate', models.FloatField(blank=True, default=None, null=True)),
+                ('audio_codec', models.CharField(max_length=255)),
+                ('audio_bitrate', models.CharField(blank=True, max_length=255, null=True)),
+                ('audio_channels', models.IntegerField(blank=True, default=None, null=True)),
+                ('audio_samplerate', models.IntegerField(blank=True, default=None, null=True)),
+                ('extra_args', models.JSONField(blank=True, default=list)),
+                ('created_at', models.DateTimeField(auto_now_add=True)),
+                ('updated_at', models.DateTimeField(auto_now=True)),
+            ],
+            options={
+                'ordering': ['-created_at'],
             },
         ),
     ]

admin/mpr/settings.py

@@ -7,7 +7,7 @@ from pathlib import Path
 
 import environ
 
-BASE_DIR = Path(__file__).resolve().parent.parent
+BASE_DIR = Path(__file__).resolve().parent.parent.parent
 
 env = environ.Env(
     DEBUG=(bool, False),
@@ -27,7 +27,7 @@ INSTALLED_APPS = [
     "django.contrib.sessions",
     "django.contrib.messages",
     "django.contrib.staticfiles",
-    "mpr.media_assets",
+    "admin.mpr.media_assets",
 ]
 
 MIDDLEWARE = [
@@ -40,7 +40,7 @@ MIDDLEWARE = [
     "django.middleware.clickjacking.XFrameOptionsMiddleware",
 ]
 
-ROOT_URLCONF = "mpr.urls"
+ROOT_URLCONF = "admin.mpr.urls"
 
 TEMPLATES = [
     {
@@ -57,7 +57,7 @@ TEMPLATES = [
     },
 ]
 
-WSGI_APPLICATION = "mpr.wsgi.application"
+WSGI_APPLICATION = "admin.mpr.wsgi.application"
 
 # Database
 DATABASE_URL = env("DATABASE_URL", default="sqlite:///db.sqlite3")

admin/mpr/wsgi.py

@@ -11,6 +11,6 @@ import os
 
 from django.core.wsgi import get_wsgi_application
 
-os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'mpr.settings')
+os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'admin.mpr.settings')
 
 application = get_wsgi_application()

api/deps.py

@@ -1,54 +0,0 @@
-"""
-FastAPI dependencies.
-
-Provides database sessions, settings, and common dependencies.
-"""
-
-import os
-from functools import lru_cache
-from typing import Generator
-
-import django
-from django.conf import settings as django_settings
-
-# Initialize Django
-os.environ.setdefault("DJANGO_SETTINGS_MODULE", "mpr.settings")
-django.setup()
-
-from mpr.media_assets.models import MediaAsset, TranscodeJob, TranscodePreset
-
-
-@lru_cache
-def get_settings():
-    """Get Django settings."""
-    return django_settings
-
-
-def get_asset(asset_id: str) -> MediaAsset:
-    """Get asset by ID or raise 404."""
-    from fastapi import HTTPException
-
-    try:
-        return MediaAsset.objects.get(id=asset_id)
-    except MediaAsset.DoesNotExist:
-        raise HTTPException(status_code=404, detail="Asset not found")
-
-
-def get_preset(preset_id: str) -> TranscodePreset:
-    """Get preset by ID or raise 404."""
-    from fastapi import HTTPException
-
-    try:
-        return TranscodePreset.objects.get(id=preset_id)
-    except TranscodePreset.DoesNotExist:
-        raise HTTPException(status_code=404, detail="Preset not found")
-
-
-def get_job(job_id: str) -> TranscodeJob:
-    """Get job by ID or raise 404."""
-    from fastapi import HTTPException
-
-    try:
-        return TranscodeJob.objects.get(id=job_id)
-    except TranscodeJob.DoesNotExist:
-        raise HTTPException(status_code=404, detail="Job not found")

api/graphql.py

@@ -1,251 +0,0 @@
-"""
-GraphQL API using graphene, mounted on FastAPI/Starlette.
-
-Provides the same data as the REST API but via GraphQL queries and mutations.
-Uses Django ORM directly for data access.
-Types are generated from schema/ via modelgen — see api/schemas/graphql_types.py.
-"""
-
-import os
-
-import graphene
-
-from api.schemas.graphql import (
-    CreateJobInput,
-    MediaAssetType,
-    ScanResultType,
-    SystemStatusType,
-    TranscodeJobType,
-    TranscodePresetType,
-)
-from core.storage import BUCKET_IN, list_objects
-
-# Media extensions (same as assets route)
-VIDEO_EXTS = {".mp4", ".mkv", ".avi", ".mov", ".webm", ".flv", ".wmv", ".m4v"}
-AUDIO_EXTS = {".mp3", ".wav", ".flac", ".aac", ".ogg", ".m4a"}
-MEDIA_EXTS = VIDEO_EXTS | AUDIO_EXTS
-
-
-# ---------------------------------------------------------------------------
-# Queries
-# ---------------------------------------------------------------------------
-
-
-class Query(graphene.ObjectType):
-    assets = graphene.List(
-        MediaAssetType,
-        status=graphene.String(),
-        search=graphene.String(),
-    )
-    asset = graphene.Field(MediaAssetType, id=graphene.UUID(required=True))
-    jobs = graphene.List(
-        TranscodeJobType,
-        status=graphene.String(),
-        source_asset_id=graphene.UUID(),
-    )
-    job = graphene.Field(TranscodeJobType, id=graphene.UUID(required=True))
-    presets = graphene.List(TranscodePresetType)
-    system_status = graphene.Field(SystemStatusType)
-
-    def resolve_assets(self, info, status=None, search=None):
-        from mpr.media_assets.models import MediaAsset
-
-        qs = MediaAsset.objects.all()
-        if status:
-            qs = qs.filter(status=status)
-        if search:
-            qs = qs.filter(filename__icontains=search)
-        return qs
-
-    def resolve_asset(self, info, id):
-        from mpr.media_assets.models import MediaAsset
-
-        try:
-            return MediaAsset.objects.get(id=id)
-        except MediaAsset.DoesNotExist:
-            return None
-
-    def resolve_jobs(self, info, status=None, source_asset_id=None):
-        from mpr.media_assets.models import TranscodeJob
-
-        qs = TranscodeJob.objects.all()
-        if status:
-            qs = qs.filter(status=status)
-        if source_asset_id:
-            qs = qs.filter(source_asset_id=source_asset_id)
-        return qs
-
-    def resolve_job(self, info, id):
-        from mpr.media_assets.models import TranscodeJob
-
-        try:
-            return TranscodeJob.objects.get(id=id)
-        except TranscodeJob.DoesNotExist:
-            return None
-
-    def resolve_presets(self, info):
-        from mpr.media_assets.models import TranscodePreset
-
-        return TranscodePreset.objects.all()
-
-    def resolve_system_status(self, info):
-        return {"status": "ok", "version": "0.1.0"}
-
-
-# ---------------------------------------------------------------------------
-# Mutations
-# ---------------------------------------------------------------------------
-
-
-class ScanMediaFolder(graphene.Mutation):
-    class Arguments:
-        pass
-
-    Output = ScanResultType
-
-    def mutate(self, info):
-        from mpr.media_assets.models import MediaAsset
-
-        objects = list_objects(BUCKET_IN, extensions=MEDIA_EXTS)
-        existing = set(MediaAsset.objects.values_list("filename", flat=True))
-
-        registered = []
-        skipped = []
-
-        for obj in objects:
-            if obj["filename"] in existing:
-                skipped.append(obj["filename"])
-                continue
-            try:
-                MediaAsset.objects.create(
-                    filename=obj["filename"],
-                    file_path=obj["key"],
-                    file_size=obj["size"],
-                )
-                registered.append(obj["filename"])
-            except Exception:
-                pass
-
-        return ScanResultType(
-            found=len(objects),
-            registered=len(registered),
-            skipped=len(skipped),
-            files=registered,
-        )
-
-
-class CreateJob(graphene.Mutation):
-    class Arguments:
-        input = CreateJobInput(required=True)
-
-    Output = TranscodeJobType
-
-    def mutate(self, info, input):
-        from pathlib import Path
-
-        from mpr.media_assets.models import MediaAsset, TranscodeJob, TranscodePreset
-
-        try:
-            source = MediaAsset.objects.get(id=input.source_asset_id)
-        except MediaAsset.DoesNotExist:
-            raise Exception("Source asset not found")
-
-        preset = None
-        preset_snapshot = {}
-        if input.preset_id:
-            try:
-                preset = TranscodePreset.objects.get(id=input.preset_id)
-                preset_snapshot = {
-                    "name": preset.name,
-                    "container": preset.container,
-                    "video_codec": preset.video_codec,
-                    "audio_codec": preset.audio_codec,
-                }
-            except TranscodePreset.DoesNotExist:
-                raise Exception("Preset not found")
-
-        if not preset and not input.trim_start and not input.trim_end:
-            raise Exception("Must specify preset_id or trim_start/trim_end")
-
-        output_filename = input.output_filename
-        if not output_filename:
-            stem = Path(source.filename).stem
-            ext = preset_snapshot.get("container", "mp4") if preset else "mp4"
-            output_filename = f"{stem}_output.{ext}"
-
-        job = TranscodeJob.objects.create(
-            source_asset_id=source.id,
-            preset_id=preset.id if preset else None,
-            preset_snapshot=preset_snapshot,
-            trim_start=input.trim_start,
-            trim_end=input.trim_end,
-            output_filename=output_filename,
-            output_path=output_filename,
-            priority=input.priority or 0,
-        )
-
-        # Dispatch
-        executor_mode = os.environ.get("MPR_EXECUTOR", "local")
-        if executor_mode == "lambda":
-            from task.executor import get_executor
-
-            get_executor().run(
-                job_id=str(job.id),
-                source_path=source.file_path,
-                output_path=output_filename,
-                preset=preset_snapshot or None,
-                trim_start=input.trim_start,
-                trim_end=input.trim_end,
-                duration=source.duration,
-            )
-        else:
-            from task.tasks import run_transcode_job
-
-            result = run_transcode_job.delay(
-                job_id=str(job.id),
-                source_key=source.file_path,
-                output_key=output_filename,
-                preset=preset_snapshot or None,
-                trim_start=input.trim_start,
-                trim_end=input.trim_end,
-                duration=source.duration,
-            )
-            job.celery_task_id = result.id
-            job.save(update_fields=["celery_task_id"])
-
-        return job
-
-
-class CancelJob(graphene.Mutation):
-    class Arguments:
-        id = graphene.UUID(required=True)
-
-    Output = TranscodeJobType
-
-    def mutate(self, info, id):
-        from mpr.media_assets.models import TranscodeJob
-
-        try:
-            job = TranscodeJob.objects.get(id=id)
-        except TranscodeJob.DoesNotExist:
-            raise Exception("Job not found")
-
-        if job.status not in ("pending", "processing"):
-            raise Exception(f"Cannot cancel job with status: {job.status}")
-
-        job.status = "cancelled"
-        job.save(update_fields=["status"])
-        return job
-
-
-class Mutation(graphene.ObjectType):
-    scan_media_folder = ScanMediaFolder.Field()
-    create_job = CreateJob.Field()
-    cancel_job = CancelJob.Field()
-
-
-# ---------------------------------------------------------------------------
-# Schema
-# ---------------------------------------------------------------------------
-
-schema = graphene.Schema(query=Query, mutation=Mutation)

api/main.py

@@ -1,61 +0,0 @@
-"""
-MPR FastAPI Application
-
-Main entry point for the REST API.
-"""
-
-import os
-import sys
-
-# Add project root to path
-sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-
-# Initialize Django before importing models
-os.environ.setdefault("DJANGO_SETTINGS_MODULE", "mpr.settings")
-
-import django
-
-django.setup()
-
-from fastapi import FastAPI
-from fastapi.middleware.cors import CORSMiddleware
-
-from api.graphql import schema as graphql_schema
-from api.routes import assets_router, jobs_router, presets_router, system_router
-from starlette_graphene3 import GraphQLApp, make_graphiql_handler
-
-app = FastAPI(
-    title="MPR API",
-    description="Media Processor REST API",
-    version="0.1.0",
-    docs_url="/docs",
-    redoc_url="/redoc",
-)
-
-# CORS
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["http://mpr.local.ar", "http://localhost:5173"],
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
-# Routes - all under /api prefix
-app.include_router(system_router, prefix="/api")
-app.include_router(assets_router, prefix="/api")
-app.include_router(presets_router, prefix="/api")
-app.include_router(jobs_router, prefix="/api")
-
-# GraphQL
-app.mount("/graphql", GraphQLApp(schema=graphql_schema, on_get=make_graphiql_handler()))
-
-
-@app.get("/")
-def root():
-    """API root."""
-    return {
-        "name": "MPR API",
-        "version": "0.1.0",
-        "docs": "/docs",
-    }

api/routes/__init__.py

@@ -1,8 +0,0 @@
-"""API Routes."""
-
-from .assets import router as assets_router
-from .jobs import router as jobs_router
-from .presets import router as presets_router
-from .system import router as system_router
-
-__all__ = ["assets_router", "jobs_router", "presets_router", "system_router"]

api/routes/assets.py

@@ -1,117 +0,0 @@
-"""
-Asset endpoints - media file registration and metadata.
-"""
-
-from typing import Optional
-from uuid import UUID
-
-from fastapi import APIRouter, Depends, HTTPException, Query
-
-from api.deps import get_asset
-from api.schemas import AssetCreate, AssetResponse, AssetUpdate
-from core.storage import BUCKET_IN, list_objects
-
-router = APIRouter(prefix="/assets", tags=["assets"])
-
-# Supported media extensions
-VIDEO_EXTS = {".mp4", ".mkv", ".avi", ".mov", ".webm", ".flv", ".wmv", ".m4v"}
-AUDIO_EXTS = {".mp3", ".wav", ".flac", ".aac", ".ogg", ".m4a"}
-MEDIA_EXTS = VIDEO_EXTS | AUDIO_EXTS
-
-
-@router.post("/", response_model=AssetResponse, status_code=201)
-def create_asset(data: AssetCreate):
-    """Register a media file as an asset."""
-    from mpr.media_assets.models import MediaAsset
-
-    asset = MediaAsset.objects.create(
-        filename=data.filename or data.file_path.split("/")[-1],
-        file_path=data.file_path,
-        file_size=data.file_size,
-    )
-    return asset
-
-
-@router.get("/", response_model=list[AssetResponse])
-def list_assets(
-    status: Optional[str] = Query(None, description="Filter by status"),
-    limit: int = Query(50, ge=1, le=100),
-    offset: int = Query(0, ge=0),
-):
-    """List assets with optional filtering."""
-    from mpr.media_assets.models import MediaAsset
-
-    qs = MediaAsset.objects.all()
-    if status:
-        qs = qs.filter(status=status)
-    return list(qs[offset : offset + limit])
-
-
-@router.get("/{asset_id}", response_model=AssetResponse)
-def get_asset_detail(asset_id: UUID, asset=Depends(get_asset)):
-    """Get asset details."""
-    return asset
-
-
-@router.patch("/{asset_id}", response_model=AssetResponse)
-def update_asset(asset_id: UUID, data: AssetUpdate, asset=Depends(get_asset)):
-    """Update asset metadata (comments, tags)."""
-    update_fields = []
-
-    if data.comments is not None:
-        asset.comments = data.comments
-        update_fields.append("comments")
-
-    if data.tags is not None:
-        asset.tags = data.tags
-        update_fields.append("tags")
-
-    if update_fields:
-        asset.save(update_fields=update_fields)
-
-    return asset
-
-
-@router.delete("/{asset_id}", status_code=204)
-def delete_asset(asset_id: UUID, asset=Depends(get_asset)):
-    """Delete an asset."""
-    asset.delete()
-
-
-@router.post("/scan", response_model=dict)
-def scan_media_folder():
-    """
-    Scan the S3 media-in bucket for new video/audio files and register them as assets.
-    """
-    from mpr.media_assets.models import MediaAsset
-
-    # List objects from S3 bucket
-    objects = list_objects(BUCKET_IN, extensions=MEDIA_EXTS)
-
-    # Get existing filenames to avoid duplicates
-    existing_filenames = set(MediaAsset.objects.values_list("filename", flat=True))
-
-    registered_files = []
-    skipped_files = []
-
-    for obj in objects:
-        if obj["filename"] in existing_filenames:
-            skipped_files.append(obj["filename"])
-            continue
-
-        try:
-            MediaAsset.objects.create(
-                filename=obj["filename"],
-                file_path=obj["key"],
-                file_size=obj["size"],
-            )
-            registered_files.append(obj["filename"])
-        except Exception as e:
-            print(f"Error registering {obj['filename']}: {e}")
-
-    return {
-        "found": len(objects),
-        "registered": len(registered_files),
-        "skipped": len(skipped_files),
-        "files": registered_files,
-    }

api/routes/jobs.py

@@ -1,233 +0,0 @@
-"""
-Job endpoints - transcode/trim job management.
-"""
-
-import os
-from pathlib import Path
-from typing import Optional
-from uuid import UUID
-
-from fastapi import APIRouter, Depends, Header, HTTPException, Query
-
-from api.deps import get_asset, get_job, get_preset
-from api.schemas import JobCreate, JobResponse
-
-router = APIRouter(prefix="/jobs", tags=["jobs"])
-
-CALLBACK_API_KEY = os.environ.get("CALLBACK_API_KEY", "")
-
-
-@router.post("/", response_model=JobResponse, status_code=201)
-def create_job(data: JobCreate):
-    """
-    Create a transcode or trim job.
-
-    - With preset_id: Full transcode using preset settings
-    - Without preset_id but with trim_start/end: Trim only (stream copy)
-    """
-    from mpr.media_assets.models import MediaAsset, TranscodeJob, TranscodePreset
-
-    # Get source asset
-    try:
-        source = MediaAsset.objects.get(id=data.source_asset_id)
-    except MediaAsset.DoesNotExist:
-        raise HTTPException(status_code=404, detail="Source asset not found")
-
-    # Get preset if specified
-    preset = None
-    preset_snapshot = {}
-    if data.preset_id:
-        try:
-            preset = TranscodePreset.objects.get(id=data.preset_id)
-            preset_snapshot = {
-                "name": preset.name,
-                "container": preset.container,
-                "video_codec": preset.video_codec,
-                "video_bitrate": preset.video_bitrate,
-                "video_crf": preset.video_crf,
-                "video_preset": preset.video_preset,
-                "resolution": preset.resolution,
-                "framerate": preset.framerate,
-                "audio_codec": preset.audio_codec,
-                "audio_bitrate": preset.audio_bitrate,
-                "audio_channels": preset.audio_channels,
-                "audio_samplerate": preset.audio_samplerate,
-                "extra_args": preset.extra_args,
-            }
-        except TranscodePreset.DoesNotExist:
-            raise HTTPException(status_code=404, detail="Preset not found")
-
-    # Validate trim-only job
-    if not preset and not data.trim_start and not data.trim_end:
-        raise HTTPException(
-            status_code=400, detail="Must specify preset_id or trim_start/trim_end"
-        )
-
-    # Generate output filename - stored as S3 key in output bucket
-    output_filename = data.output_filename
-    if not output_filename:
-        stem = Path(source.filename).stem
-        ext = preset_snapshot.get("container", "mp4") if preset else "mp4"
-        output_filename = f"{stem}_output.{ext}"
-
-    # Create job
-    job = TranscodeJob.objects.create(
-        source_asset_id=source.id,
-        preset_id=preset.id if preset else None,
-        preset_snapshot=preset_snapshot,
-        trim_start=data.trim_start,
-        trim_end=data.trim_end,
-        output_filename=output_filename,
-        output_path=output_filename,  # S3 key in output bucket
-        priority=data.priority or 0,
-    )
-
-    # Dispatch based on executor mode
-    executor_mode = os.environ.get("MPR_EXECUTOR", "local")
-
-    if executor_mode == "lambda":
-        _dispatch_lambda(job, source, preset_snapshot)
-    else:
-        _dispatch_celery(job, source, preset_snapshot)
-
-    return job
-
-
-def _dispatch_celery(job, source, preset_snapshot):
-    """Dispatch job to Celery worker."""
-    from task.tasks import run_transcode_job
-
-    result = run_transcode_job.delay(
-        job_id=str(job.id),
-        source_key=source.file_path,
-        output_key=job.output_filename,
-        preset=preset_snapshot or None,
-        trim_start=job.trim_start,
-        trim_end=job.trim_end,
-        duration=source.duration,
-    )
-    job.celery_task_id = result.id
-    job.save(update_fields=["celery_task_id"])
-
-
-def _dispatch_lambda(job, source, preset_snapshot):
-    """Dispatch job to AWS Step Functions."""
-    from task.executor import get_executor
-
-    executor = get_executor()
-    executor.run(
-        job_id=str(job.id),
-        source_path=source.file_path,
-        output_path=job.output_filename,
-        preset=preset_snapshot or None,
-        trim_start=job.trim_start,
-        trim_end=job.trim_end,
-        duration=source.duration,
-    )
-
-
-@router.post("/{job_id}/callback")
-def job_callback(
-    job_id: UUID,
-    payload: dict,
-    x_api_key: Optional[str] = Header(None),
-):
-    """
-    Callback endpoint for Lambda to report job completion.
-    Protected by API key.
-    """
-    if CALLBACK_API_KEY and x_api_key != CALLBACK_API_KEY:
-        raise HTTPException(status_code=403, detail="Invalid API key")
-
-    from django.utils import timezone
-
-    from mpr.media_assets.models import TranscodeJob
-
-    try:
-        job = TranscodeJob.objects.get(id=job_id)
-    except TranscodeJob.DoesNotExist:
-        raise HTTPException(status_code=404, detail="Job not found")
-
-    status = payload.get("status", "failed")
-    job.status = status
-    job.progress = 100.0 if status == "completed" else job.progress
-    update_fields = ["status", "progress"]
-
-    if payload.get("error"):
-        job.error_message = payload["error"]
-        update_fields.append("error_message")
-
-    if status == "completed":
-        job.completed_at = timezone.now()
-        update_fields.append("completed_at")
-    elif status == "failed":
-        job.completed_at = timezone.now()
-        update_fields.append("completed_at")
-
-    job.save(update_fields=update_fields)
-
-    return {"ok": True}
-
-
-@router.get("/", response_model=list[JobResponse])
-def list_jobs(
-    status: Optional[str] = Query(None, description="Filter by status"),
-    source_asset_id: Optional[UUID] = Query(None),
-    limit: int = Query(50, ge=1, le=100),
-    offset: int = Query(0, ge=0),
-):
-    """List jobs with optional filtering."""
-    from mpr.media_assets.models import TranscodeJob
-
-    qs = TranscodeJob.objects.all()
-    if status:
-        qs = qs.filter(status=status)
-    if source_asset_id:
-        qs = qs.filter(source_asset_id=source_asset_id)
-    return list(qs[offset : offset + limit])
-
-
-@router.get("/{job_id}", response_model=JobResponse)
-def get_job_detail(job_id: UUID, job=Depends(get_job)):
-    """Get job details including progress."""
-    return job
-
-
-@router.get("/{job_id}/progress")
-def get_job_progress(job_id: UUID, job=Depends(get_job)):
-    """Get real-time job progress."""
-    return {
-        "job_id": str(job.id),
-        "status": job.status,
-        "progress": job.progress,
-        "current_frame": job.current_frame,
-        "current_time": job.current_time,
-        "speed": job.speed,
-    }
-
-
-@router.post("/{job_id}/cancel", response_model=JobResponse)
-def cancel_job(job_id: UUID, job=Depends(get_job)):
-    """Cancel a pending or processing job."""
-    if job.status not in ("pending", "processing"):
-        raise HTTPException(
-            status_code=400, detail=f"Cannot cancel job with status: {job.status}"
-        )
-
-    job.status = "cancelled"
-    job.save(update_fields=["status"])
-    return job
-
-
-@router.post("/{job_id}/retry", response_model=JobResponse)
-def retry_job(job_id: UUID, job=Depends(get_job)):
-    """Retry a failed job."""
-    if job.status != "failed":
-        raise HTTPException(status_code=400, detail="Only failed jobs can be retried")
-
-    job.status = "pending"
-    job.progress = 0
-    job.error_message = None
-    job.save(update_fields=["status", "progress", "error_message"])
-
-    return job

api/routes/presets.py

@@ -1,100 +0,0 @@
-"""
-Preset endpoints - transcode configuration templates.
-"""
-
-from uuid import UUID
-
-from fastapi import APIRouter, Depends, HTTPException
-
-from api.deps import get_preset
-from api.schemas import PresetCreate, PresetResponse, PresetUpdate
-
-router = APIRouter(prefix="/presets", tags=["presets"])
-
-
-@router.post("/", response_model=PresetResponse, status_code=201)
-def create_preset(data: PresetCreate):
-    """Create a custom preset."""
-    from mpr.media_assets.models import TranscodePreset
-
-    preset = TranscodePreset.objects.create(
-        name=data.name,
-        description=data.description or "",
-        container=data.container or "mp4",
-        video_codec=data.video_codec or "libx264",
-        video_bitrate=data.video_bitrate,
-        video_crf=data.video_crf,
-        video_preset=data.video_preset,
-        resolution=data.resolution,
-        framerate=data.framerate,
-        audio_codec=data.audio_codec or "aac",
-        audio_bitrate=data.audio_bitrate,
-        audio_channels=data.audio_channels,
-        audio_samplerate=data.audio_samplerate,
-        extra_args=data.extra_args or [],
-        is_builtin=False,
-    )
-
-    return preset
-
-
-@router.get("/", response_model=list[PresetResponse])
-def list_presets(include_builtin: bool = True):
-    """List all presets."""
-    from mpr.media_assets.models import TranscodePreset
-
-    qs = TranscodePreset.objects.all()
-
-    if not include_builtin:
-        qs = qs.filter(is_builtin=False)
-
-    return list(qs)
-
-
-@router.get("/{preset_id}", response_model=PresetResponse)
-def get_preset_detail(preset_id: UUID, preset=Depends(get_preset)):
-    """Get preset details."""
-    return preset
-
-
-@router.patch("/{preset_id}", response_model=PresetResponse)
-def update_preset(preset_id: UUID, data: PresetUpdate, preset=Depends(get_preset)):
-    """Update a custom preset. Builtin presets cannot be modified."""
-    if preset.is_builtin:
-        raise HTTPException(status_code=403, detail="Cannot modify builtin preset")
-
-    update_fields = []
-    for field in [
-        "name",
-        "description",
-        "container",
-        "video_codec",
-        "video_bitrate",
-        "video_crf",
-        "video_preset",
-        "resolution",
-        "framerate",
-        "audio_codec",
-        "audio_bitrate",
-        "audio_channels",
-        "audio_samplerate",
-        "extra_args",
-    ]:
-        value = getattr(data, field, None)
-        if value is not None:
-            setattr(preset, field, value)
-            update_fields.append(field)
-
-    if update_fields:
-        preset.save(update_fields=update_fields)
-
-    return preset
-
-
-@router.delete("/{preset_id}", status_code=204)
-def delete_preset(preset_id: UUID, preset=Depends(get_preset)):
-    """Delete a custom preset. Builtin presets cannot be deleted."""
-    if preset.is_builtin:
-        raise HTTPException(status_code=403, detail="Cannot delete builtin preset")
-
-    preset.delete()

api/routes/system.py

@@ -1,51 +0,0 @@
-"""
-System endpoints - health checks and FFmpeg capabilities.
-"""
-
-from fastapi import APIRouter
-
-from core.ffmpeg import get_decoders, get_encoders, get_formats
-
-router = APIRouter(prefix="/system", tags=["system"])
-
-
-@router.get("/health")
-def health_check():
-    """Health check endpoint."""
-    return {"status": "healthy"}
-
-
-@router.get("/status")
-def system_status():
-    """System status for UI."""
-    return {"status": "ok", "version": "0.1.0"}
-
-
-@router.get("/worker")
-def worker_status():
-    """Worker status from gRPC."""
-    try:
-        from rpc.client import get_client
-
-        client = get_client()
-        status = client.get_worker_status()
-        if status:
-            return status
-        return {"available": False, "error": "No response from worker"}
-    except Exception as e:
-        return {"available": False, "error": str(e)}
-
-
-@router.get("/ffmpeg/codecs")
-def ffmpeg_codecs():
-    """Get available FFmpeg encoders and decoders."""
-    return {
-        "encoders": get_encoders(),
-        "decoders": get_decoders(),
-    }
-
-
-@router.get("/ffmpeg/formats")
-def ffmpeg_formats():
-    """Get available FFmpeg muxers and demuxers."""
-    return get_formats()

api/schemas/__init__.py

@@ -1,10 +0,0 @@
-"""API Schemas - GENERATED FILE"""
-
-from .base import BaseSchema
-from .asset import AssetCreate, AssetUpdate, AssetResponse
-from .asset import AssetStatus
-from .preset import PresetCreate, PresetUpdate, PresetResponse
-from .job import JobCreate, JobUpdate, JobResponse
-from .job import JobStatus
-
-__all__ = ["BaseSchema", "AssetCreate", "AssetUpdate", "AssetResponse", "AssetStatus", "PresetCreate", "PresetUpdate", "PresetResponse", "JobCreate", "JobUpdate", "JobResponse", "JobStatus"]

api/schemas/asset.py

@@ -1,69 +0,0 @@
-"""MediaAsset Schemas - GENERATED FILE"""
-
-from datetime import datetime
-from typing import Any, Dict, List, Optional
-from uuid import UUID
-
-from .base import BaseSchema
-from .models import AssetStatus
-
-
-class AssetCreate(BaseSchema):
-    """AssetCreate schema."""
-
-    filename: str
-    file_path: str
-    file_size: Optional[int] = None
-    duration: Optional[float] = None
-    video_codec: Optional[str] = None
-    audio_codec: Optional[str] = None
-    width: Optional[int] = None
-    height: Optional[int] = None
-    framerate: Optional[float] = None
-    bitrate: Optional[int] = None
-    properties: Dict[str, Any]
-    comments: str = ""
-    tags: List[str]
-
-
-class AssetUpdate(BaseSchema):
-    """AssetUpdate schema."""
-
-    filename: Optional[str] = None
-    file_path: Optional[str] = None
-    status: Optional[AssetStatus] = None
-    error_message: Optional[str] = None
-    file_size: Optional[int] = None
-    duration: Optional[float] = None
-    video_codec: Optional[str] = None
-    audio_codec: Optional[str] = None
-    width: Optional[int] = None
-    height: Optional[int] = None
-    framerate: Optional[float] = None
-    bitrate: Optional[int] = None
-    properties: Optional[Dict[str, Any]] = None
-    comments: Optional[str] = None
-    tags: Optional[List[str]] = None
-
-
-class AssetResponse(BaseSchema):
-    """AssetResponse schema."""
-
-    id: UUID
-    filename: str
-    file_path: str
-    status: AssetStatus = "AssetStatus.PENDING"
-    error_message: Optional[str] = None
-    file_size: Optional[int] = None
-    duration: Optional[float] = None
-    video_codec: Optional[str] = None
-    audio_codec: Optional[str] = None
-    width: Optional[int] = None
-    height: Optional[int] = None
-    framerate: Optional[float] = None
-    bitrate: Optional[int] = None
-    properties: Dict[str, Any]
-    comments: str = ""
-    tags: List[str]
-    created_at: Optional[datetime] = None
-    updated_at: Optional[datetime] = None

api/schemas/base.py

@@ -1,8 +0,0 @@
-"""Pydantic Base Schema - GENERATED FILE"""
-
-from pydantic import BaseModel, ConfigDict
-
-
-class BaseSchema(BaseModel):
-    """Base schema with ORM mode."""
-    model_config = ConfigDict(from_attributes=True)

api/schemas/graphql.py

@@ -1,129 +0,0 @@
-"""
-Graphene Types - GENERATED FILE
-
-Do not edit directly. Regenerate using modelgen.
-"""
-
-import graphene
-
-
-class AssetStatus(graphene.Enum):
-    PENDING = "pending"
-    READY = "ready"
-    ERROR = "error"
-
-
-class JobStatus(graphene.Enum):
-    PENDING = "pending"
-    PROCESSING = "processing"
-    COMPLETED = "completed"
-    FAILED = "failed"
-    CANCELLED = "cancelled"
-
-
-class MediaAssetType(graphene.ObjectType):
-    """A video/audio file registered in the system."""
-
-    id = graphene.UUID()
-    filename = graphene.String()
-    file_path = graphene.String()
-    status = graphene.String()
-    error_message = graphene.String()
-    file_size = graphene.Int()
-    duration = graphene.Float()
-    video_codec = graphene.String()
-    audio_codec = graphene.String()
-    width = graphene.Int()
-    height = graphene.Int()
-    framerate = graphene.Float()
-    bitrate = graphene.Int()
-    properties = graphene.JSONString()
-    comments = graphene.String()
-    tags = graphene.List(graphene.String)
-    created_at = graphene.DateTime()
-    updated_at = graphene.DateTime()
-
-
-class TranscodePresetType(graphene.ObjectType):
-    """A reusable transcoding configuration (like Handbrake presets)."""
-
-    id = graphene.UUID()
-    name = graphene.String()
-    description = graphene.String()
-    is_builtin = graphene.Boolean()
-    container = graphene.String()
-    video_codec = graphene.String()
-    video_bitrate = graphene.String()
-    video_crf = graphene.Int()
-    video_preset = graphene.String()
-    resolution = graphene.String()
-    framerate = graphene.Float()
-    audio_codec = graphene.String()
-    audio_bitrate = graphene.String()
-    audio_channels = graphene.Int()
-    audio_samplerate = graphene.Int()
-    extra_args = graphene.List(graphene.String)
-    created_at = graphene.DateTime()
-    updated_at = graphene.DateTime()
-
-
-class TranscodeJobType(graphene.ObjectType):
-    """A transcoding or trimming job in the queue."""
-
-    id = graphene.UUID()
-    source_asset_id = graphene.UUID()
-    preset_id = graphene.UUID()
-    preset_snapshot = graphene.JSONString()
-    trim_start = graphene.Float()
-    trim_end = graphene.Float()
-    output_filename = graphene.String()
-    output_path = graphene.String()
-    output_asset_id = graphene.UUID()
-    status = graphene.String()
-    progress = graphene.Float()
-    current_frame = graphene.Int()
-    current_time = graphene.Float()
-    speed = graphene.String()
-    error_message = graphene.String()
-    celery_task_id = graphene.String()
-    execution_arn = graphene.String()
-    priority = graphene.Int()
-    created_at = graphene.DateTime()
-    started_at = graphene.DateTime()
-    completed_at = graphene.DateTime()
-
-
-class CreateJobInput(graphene.InputObjectType):
-    """Request body for creating a transcode/trim job."""
-
-    source_asset_id = graphene.UUID(required=True)
-    preset_id = graphene.UUID()
-    trim_start = graphene.Float()
-    trim_end = graphene.Float()
-    output_filename = graphene.String()
-    priority = graphene.Int(default_value=0)
-
-
-class SystemStatusType(graphene.ObjectType):
-    """System status response."""
-
-    status = graphene.String()
-    version = graphene.String()
-
-
-class ScanResultType(graphene.ObjectType):
-    """Result of scanning the media input bucket."""
-
-    found = graphene.Int()
-    registered = graphene.Int()
-    skipped = graphene.Int()
-    files = graphene.List(graphene.String)
-
-
-class WorkerStatusType(graphene.ObjectType):
-    """Worker health and capabilities."""
-
-    available = graphene.Boolean()
-    active_jobs = graphene.Int()
-    supported_codecs = graphene.List(graphene.String)
-    gpu_available = graphene.Boolean()

api/schemas/job.py

@@ -1,67 +0,0 @@
-"""TranscodeJob Schemas - GENERATED FILE"""
-
-from datetime import datetime
-from typing import Any, Dict, List, Optional
-from uuid import UUID
-
-from .base import BaseSchema
-from .models import JobStatus
-
-
-class JobCreate(BaseSchema):
-    """Client-facing job creation request."""
-
-    source_asset_id: UUID
-    preset_id: Optional[UUID] = None
-    trim_start: Optional[float] = None
-    trim_end: Optional[float] = None
-    output_filename: Optional[str] = None
-    priority: int = 0
-
-
-class JobUpdate(BaseSchema):
-    """JobUpdate schema."""
-
-    source_asset_id: Optional[UUID] = None
-    preset_id: Optional[UUID] = None
-    preset_snapshot: Optional[Dict[str, Any]] = None
-    trim_start: Optional[float] = None
-    trim_end: Optional[float] = None
-    output_filename: Optional[str] = None
-    output_path: Optional[str] = None
-    output_asset_id: Optional[UUID] = None
-    status: Optional[JobStatus] = None
-    progress: Optional[float] = None
-    current_frame: Optional[int] = None
-    current_time: Optional[float] = None
-    speed: Optional[str] = None
-    error_message: Optional[str] = None
-    celery_task_id: Optional[str] = None
-    priority: Optional[int] = None
-    started_at: Optional[datetime] = None
-    completed_at: Optional[datetime] = None
-
-
-class JobResponse(BaseSchema):
-    """JobResponse schema."""
-
-    id: UUID
-    source_asset_id: UUID
-    preset_id: Optional[UUID] = None
-    preset_snapshot: Dict[str, Any]
-    trim_start: Optional[float] = None
-    trim_end: Optional[float] = None
-    output_filename: str = ""
-    output_path: Optional[str] = None
-    output_asset_id: Optional[UUID] = None
-    status: JobStatus = "JobStatus.PENDING"
-    progress: float = 0.0
-    current_frame: Optional[int] = None
-    current_time: Optional[float] = None
-    speed: Optional[str] = None
-    error_message: Optional[str] = None
-    celery_task_id: Optional[str] = None
-    priority: int = 0
-    created_at: Optional[datetime] = None
-    started_at: Optional[datetime] = None
-    completed_at: Optional[datetime] = None

api/schemas/models.py

@@ -1,90 +0,0 @@
-"""
-Pydantic Models - GENERATED FILE
-
-Do not edit directly. Regenerate using modelgen.
-"""
-
-from datetime import datetime
-from enum import Enum
-from typing import Any, Dict, List, Optional
-from uuid import UUID
-
-from pydantic import BaseModel, Field
-
-class AssetStatus(str, Enum):
-    PENDING = "pending"
-    READY = "ready"
-    ERROR = "error"
-
-class JobStatus(str, Enum):
-    PENDING = "pending"
-    PROCESSING = "processing"
-    COMPLETED = "completed"
-    FAILED = "failed"
-    CANCELLED = "cancelled"
-
-class MediaAsset(BaseModel):
-    """A video/audio file registered in the system."""
-    id: UUID
-    filename: str
-    file_path: str
-    status: AssetStatus = "AssetStatus.PENDING"
-    error_message: Optional[str] = None
-    file_size: Optional[int] = None
-    duration: Optional[float] = None
-    video_codec: Optional[str] = None
-    audio_codec: Optional[str] = None
-    width: Optional[int] = None
-    height: Optional[int] = None
-    framerate: Optional[float] = None
-    bitrate: Optional[int] = None
-    properties: Dict[str, Any]
-    comments: str = ""
-    tags: List[str] = Field(default_factory=list)
-    created_at: Optional[datetime] = None
-    updated_at: Optional[datetime] = None
-
-class TranscodePreset(BaseModel):
-    """A reusable transcoding configuration (like Handbrake presets)."""
-    id: UUID
-    name: str
-    description: str = ""
-    is_builtin: bool = False
-    container: str = "mp4"
-    video_codec: str = "libx264"
-    video_bitrate: Optional[str] = None
-    video_crf: Optional[int] = None
-    video_preset: Optional[str] = None
-    resolution: Optional[str] = None
-    framerate: Optional[float] = None
-    audio_codec: str = "aac"
-    audio_bitrate: Optional[str] = None
-    audio_channels: Optional[int] = None
-    audio_samplerate: Optional[int] = None
-    extra_args: List[str] = Field(default_factory=list)
-    created_at: Optional[datetime] = None
-    updated_at: Optional[datetime] = None
-
-class TranscodeJob(BaseModel):
-    """A transcoding or trimming job in the queue."""
-    id: UUID
-    source_asset_id: UUID
-    preset_id: Optional[UUID] = None
-    preset_snapshot: Dict[str, Any]
-    trim_start: Optional[float] = None
-    trim_end: Optional[float] = None
-    output_filename: str = ""
-    output_path: Optional[str] = None
-    output_asset_id: Optional[UUID] = None
-    status: JobStatus = "JobStatus.PENDING"
-    progress: float = 0.0
-    current_frame: Optional[int] = None
-    current_time: Optional[float] = None
-    speed: Optional[str] = None
-    error_message: Optional[str] = None
-    celery_task_id: Optional[str] = None
-    execution_arn: Optional[str] = None
-    priority: int = 0
-    created_at: Optional[datetime] = None
-    started_at: Optional[datetime] = None
-    completed_at: Optional[datetime] = None

api/schemas/preset.py

@@ -1,66 +0,0 @@
-"""TranscodePreset Schemas - GENERATED FILE"""
-
-from datetime import datetime
-from enum import Enum
-from typing import Any, Dict, List, Optional
-from uuid import UUID
-
-from .base import BaseSchema
-
-
-class PresetCreate(BaseSchema):
-    """PresetCreate schema."""
-    name: str
-    description: str = ""
-    is_builtin: bool = False
-    container: str = "mp4"
-    video_codec: str = "libx264"
-    video_bitrate: Optional[str] = None
-    video_crf: Optional[int] = None
-    video_preset: Optional[str] = None
-    resolution: Optional[str] = None
-    framerate: Optional[float] = None
-    audio_codec: str = "aac"
-    audio_bitrate: Optional[str] = None
-    audio_channels: Optional[int] = None
-    audio_samplerate: Optional[int] = None
-    extra_args: List[str]
-
-class PresetUpdate(BaseSchema):
-    """PresetUpdate schema."""
-    name: Optional[str] = None
-    description: Optional[str] = None
-    is_builtin: Optional[bool] = None
-    container: Optional[str] = None
-    video_codec: Optional[str] = None
-    video_bitrate: Optional[str] = None
-    video_crf: Optional[int] = None
-    video_preset: Optional[str] = None
-    resolution: Optional[str] = None
-    framerate: Optional[float] = None
-    audio_codec: Optional[str] = None
-    audio_bitrate: Optional[str] = None
-    audio_channels: Optional[int] = None
-    audio_samplerate: Optional[int] = None
-    extra_args: Optional[List[str]] = None
-
-class PresetResponse(BaseSchema):
-    """PresetResponse schema."""
-    id: UUID
-    name: str
-    description: str = ""
-    is_builtin: bool = False
-    container: str = "mp4"
-    video_codec: str = "libx264"
-    video_bitrate: Optional[str] = None
-    video_crf: Optional[int] = None
-    video_preset: Optional[str] = None
-    resolution: Optional[str] = None
-    framerate: Optional[float] = None
-    audio_codec: str = "aac"
-    audio_bitrate: Optional[str] = None
-    audio_channels: Optional[int] = None
-    audio_samplerate: Optional[int] = None
-    extra_args: List[str]
-    created_at: Optional[datetime] = None
-    updated_at: Optional[datetime] = None

core/api/graphql.py

@@ -0,0 +1,273 @@
+"""
+GraphQL API using strawberry, served via FastAPI.
+
+Primary API for MPR — all client interactions go through GraphQL.
+Uses core.db for data access.
+Types are generated from schema/ via modelgen — see api/schema/graphql.py.
+"""
+
+import os
+from typing import List, Optional
+from uuid import UUID
+
+import strawberry
+from strawberry.schema.config import StrawberryConfig
+from strawberry.types import Info
+
+from core.api.schema.graphql import (
+    CreateJobInput,
+    DeleteResultType,
+    MediaAssetType,
+    ScanResultType,
+    SystemStatusType,
+    TranscodeJobType,
+    TranscodePresetType,
+    UpdateAssetInput,
+)
+from core.storage import BUCKET_IN, list_objects
+
+VIDEO_EXTS = {".mp4", ".mkv", ".avi", ".mov", ".webm", ".flv", ".wmv", ".m4v"}
+AUDIO_EXTS = {".mp3", ".wav", ".flac", ".aac", ".ogg", ".m4a"}
+MEDIA_EXTS = VIDEO_EXTS | AUDIO_EXTS
+
+
+# ---------------------------------------------------------------------------
+# Queries
+# ---------------------------------------------------------------------------
+
+
+@strawberry.type
+class Query:
+    @strawberry.field
+    def assets(
+        self,
+        info: Info,
+        status: Optional[str] = None,
+        search: Optional[str] = None,
+    ) -> List[MediaAssetType]:
+        from core.db import list_assets
+
+        return list_assets(status=status, search=search)
+
+    @strawberry.field
+    def asset(self, info: Info, id: UUID) -> Optional[MediaAssetType]:
+        from core.db import get_asset
+
+        try:
+            return get_asset(id)
+        except Exception:
+            return None
+
+    @strawberry.field
+    def jobs(
+        self,
+        info: Info,
+        status: Optional[str] = None,
+        source_asset_id: Optional[UUID] = None,
+    ) -> List[TranscodeJobType]:
+        from core.db import list_jobs
+
+        return list_jobs(status=status, source_asset_id=source_asset_id)
+
+    @strawberry.field
+    def job(self, info: Info, id: UUID) -> Optional[TranscodeJobType]:
+        from core.db import get_job
+
+        try:
+            return get_job(id)
+        except Exception:
+            return None
+
+    @strawberry.field
+    def presets(self, info: Info) -> List[TranscodePresetType]:
+        from core.db import list_presets
+
+        return list_presets()
+
+    @strawberry.field
+    def system_status(self, info: Info) -> SystemStatusType:
+        return SystemStatusType(status="ok", version="0.1.0")
+
+
+# ---------------------------------------------------------------------------
+# Mutations
+# ---------------------------------------------------------------------------
+
+
+@strawberry.type
+class Mutation:
+    @strawberry.mutation
+    def scan_media_folder(self, info: Info) -> ScanResultType:
+        from core.db import create_asset, get_asset_filenames
+
+        objects = list_objects(BUCKET_IN, extensions=MEDIA_EXTS)
+        existing = get_asset_filenames()
+
+        registered = []
+        skipped = []
+
+        for obj in objects:
+            if obj["filename"] in existing:
+                skipped.append(obj["filename"])
+                continue
+            try:
+                create_asset(
+                    filename=obj["filename"],
+                    file_path=obj["key"],
+                    file_size=obj["size"],
+                )
+                registered.append(obj["filename"])
+            except Exception:
+                pass
+
+        return ScanResultType(
+            found=len(objects),
+            registered=len(registered),
+            skipped=len(skipped),
+            files=registered,
+        )
+
+    @strawberry.mutation
+    def create_job(self, info: Info, input: CreateJobInput) -> TranscodeJobType:
+        from pathlib import Path
+
+        from core.db import create_job, get_asset, get_preset
+
+        try:
+            source = get_asset(input.source_asset_id)
+        except Exception:
+            raise Exception("Source asset not found")
+
+        preset = None
+        preset_snapshot = {}
+        if input.preset_id:
+            try:
+                preset = get_preset(input.preset_id)
+                preset_snapshot = {
+                    "name": preset.name,
+                    "container": preset.container,
+                    "video_codec": preset.video_codec,
+                    "audio_codec": preset.audio_codec,
+                }
+            except Exception:
+                raise Exception("Preset not found")
+
+        if not preset and not input.trim_start and not input.trim_end:
+            raise Exception("Must specify preset_id or trim_start/trim_end")
+
+        output_filename = input.output_filename
+        if not output_filename:
+            stem = Path(source.filename).stem
+            ext = preset_snapshot.get("container", "mp4") if preset else "mp4"
+            output_filename = f"{stem}_output.{ext}"
+
+        job = create_job(
+            source_asset_id=source.id,
+            preset_id=preset.id if preset else None,
+            preset_snapshot=preset_snapshot,
+            trim_start=input.trim_start,
+            trim_end=input.trim_end,
+            output_filename=output_filename,
+            output_path=output_filename,
+            priority=input.priority or 0,
+        )
+
+        executor_mode = os.environ.get("MPR_EXECUTOR", "local")
+        if executor_mode in ("lambda", "gcp"):
+            from core.task.executor import get_executor
+
+            get_executor().run(
+                job_id=str(job.id),
+                source_path=source.file_path,
+                output_path=output_filename,
+                preset=preset_snapshot or None,
+                trim_start=input.trim_start,
+                trim_end=input.trim_end,
+                duration=source.duration,
+            )
+        else:
+            from core.task.tasks import run_transcode_job
+
+            result = run_transcode_job.delay(
+                job_id=str(job.id),
+                source_key=source.file_path,
+                output_key=output_filename,
+                preset=preset_snapshot or None,
+                trim_start=input.trim_start,
+                trim_end=input.trim_end,
+                duration=source.duration,
+            )
+            job.celery_task_id = result.id
+            job.save(update_fields=["celery_task_id"])
+
+        return job
+
+    @strawberry.mutation
+    def cancel_job(self, info: Info, id: UUID) -> TranscodeJobType:
+        from core.db import get_job, update_job
+
+        try:
+            job = get_job(id)
+        except Exception:
+            raise Exception("Job not found")
+
+        if job.status not in ("pending", "processing"):
+            raise Exception(f"Cannot cancel job with status: {job.status}")
+
+        return update_job(job, status="cancelled")
+
+    @strawberry.mutation
+    def retry_job(self, info: Info, id: UUID) -> TranscodeJobType:
+        from core.db import get_job, update_job
+
+        try:
+            job = get_job(id)
+        except Exception:
+            raise Exception("Job not found")
+
+        if job.status != "failed":
+            raise Exception("Only failed jobs can be retried")
+
+        return update_job(job, status="pending", progress=0, error_message=None)
+
+    @strawberry.mutation
+    def update_asset(self, info: Info, id: UUID, input: UpdateAssetInput) -> MediaAssetType:
+        from core.db import get_asset, update_asset
+
+        try:
+            asset = get_asset(id)
+        except Exception:
+            raise Exception("Asset not found")
+
+        fields = {}
+        if input.comments is not None:
+            fields["comments"] = input.comments
+        if input.tags is not None:
+            fields["tags"] = input.tags
+
+        if fields:
+            asset = update_asset(asset, **fields)
+
+        return asset
+
+    @strawberry.mutation
+    def delete_asset(self, info: Info, id: UUID) -> DeleteResultType:
+        from core.db import delete_asset, get_asset
+
+        try:
+            asset = get_asset(id)
+            delete_asset(asset)
+            return DeleteResultType(ok=True)
+        except Exception:
+            raise Exception("Asset not found")
+
+
+# ---------------------------------------------------------------------------
+# Schema
+# ---------------------------------------------------------------------------
+
+schema = strawberry.Schema(
+    query=Query,
+    mutation=Mutation,
+    config=StrawberryConfig(auto_camel_case=False),
+)

core/api/main.py

@@ -0,0 +1,98 @@
+"""
+MPR FastAPI Application
+
+Serves GraphQL API and Lambda callback endpoint.
+"""
+
+import os
+import sys
+from typing import Optional
+from uuid import UUID
+
+# Add project root to path
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
+
+# Initialize Django before importing models
+os.environ.setdefault("DJANGO_SETTINGS_MODULE", "admin.mpr.settings")
+
+import django
+
+django.setup()
+
+from fastapi import FastAPI, Header, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from strawberry.fastapi import GraphQLRouter
+
+from core.api.graphql import schema as graphql_schema
+
+CALLBACK_API_KEY = os.environ.get("CALLBACK_API_KEY", "")
+
+app = FastAPI(
+    title="MPR API",
+    description="Media Processor — GraphQL API",
+    version="0.1.0",
+    docs_url="/docs",
+    redoc_url="/redoc",
+)
+
+# CORS
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["http://mpr.local.ar", "http://localhost:5173"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# GraphQL
+graphql_router = GraphQLRouter(schema=graphql_schema, graphql_ide="graphiql")
+app.include_router(graphql_router, prefix="/graphql")
+
+
+@app.get("/")
+def root():
+    """API root."""
+    return {
+        "name": "MPR API",
+        "version": "0.1.0",
+        "graphql": "/graphql",
+    }
+
+
+@app.post("/api/jobs/{job_id}/callback")
+def job_callback(
+    job_id: UUID,
+    payload: dict,
+    x_api_key: Optional[str] = Header(None),
+):
+    """
+    Callback endpoint for Lambda to report job completion.
+    Protected by API key.
+    """
+    if CALLBACK_API_KEY and x_api_key != CALLBACK_API_KEY:
+        raise HTTPException(status_code=403, detail="Invalid API key")
+
+    from django.utils import timezone
+
+    from core.db import get_job, update_job
+
+    try:
+        job = get_job(job_id)
+    except Exception:
+        raise HTTPException(status_code=404, detail="Job not found")
+
+    status = payload.get("status", "failed")
+    fields = {
+        "status": status,
+        "progress": 100.0 if status == "completed" else job.progress,
+    }
+
+    if payload.get("error"):
+        fields["error_message"] = payload["error"]
+
+    if status in ("completed", "failed"):
+        fields["completed_at"] = timezone.now()
+
+    update_job(job, **fields)
+
+    return {"ok": True}

core/api/schema/graphql.py

@@ -0,0 +1,158 @@
+"""
+Strawberry Types - GENERATED FILE
+
+Do not edit directly. Regenerate using modelgen.
+"""
+
+import strawberry
+from enum import Enum
+from typing import List, Optional
+from uuid import UUID
+from datetime import datetime
+from strawberry.scalars import JSON
+
+
+@strawberry.enum
+class AssetStatus(Enum):
+    PENDING = "pending"
+    READY = "ready"
+    ERROR = "error"
+
+
+@strawberry.enum
+class JobStatus(Enum):
+    PENDING = "pending"
+    PROCESSING = "processing"
+    COMPLETED = "completed"
+    FAILED = "failed"
+    CANCELLED = "cancelled"
+
+
+@strawberry.type
+class MediaAssetType:
+    """A video/audio file registered in the system."""
+
+    id: Optional[UUID] = None
+    filename: Optional[str] = None
+    file_path: Optional[str] = None
+    status: Optional[str] = None
+    error_message: Optional[str] = None
+    file_size: Optional[int] = None
+    duration: Optional[float] = None
+    video_codec: Optional[str] = None
+    audio_codec: Optional[str] = None
+    width: Optional[int] = None
+    height: Optional[int] = None
+    framerate: Optional[float] = None
+    bitrate: Optional[int] = None
+    properties: Optional[JSON] = None
+    comments: Optional[str] = None
+    tags: Optional[List[str]] = None
+    created_at: Optional[datetime] = None
+    updated_at: Optional[datetime] = None
+
+
+@strawberry.type
+class TranscodePresetType:
+    """A reusable transcoding configuration (like Handbrake presets)."""
+
+    id: Optional[UUID] = None
+    name: Optional[str] = None
+    description: Optional[str] = None
+    is_builtin: Optional[bool] = None
+    container: Optional[str] = None
+    video_codec: Optional[str] = None
+    video_bitrate: Optional[str] = None
+    video_crf: Optional[int] = None
+    video_preset: Optional[str] = None
+    resolution: Optional[str] = None
+    framerate: Optional[float] = None
+    audio_codec: Optional[str] = None
+    audio_bitrate: Optional[str] = None
+    audio_channels: Optional[int] = None
+    audio_samplerate: Optional[int] = None
+    extra_args: Optional[List[str]] = None
+    created_at: Optional[datetime] = None
+    updated_at: Optional[datetime] = None
+
+
+@strawberry.type
+class TranscodeJobType:
+    """A transcoding or trimming job in the queue."""
+
+    id: Optional[UUID] = None
+    source_asset_id: Optional[UUID] = None
+    preset_id: Optional[UUID] = None
+    preset_snapshot: Optional[JSON] = None
+    trim_start: Optional[float] = None
+    trim_end: Optional[float] = None
+    output_filename: Optional[str] = None
+    output_path: Optional[str] = None
+    output_asset_id: Optional[UUID] = None
+    status: Optional[str] = None
+    progress: Optional[float] = None
+    current_frame: Optional[int] = None
+    current_time: Optional[float] = None
+    speed: Optional[str] = None
+    error_message: Optional[str] = None
+    celery_task_id: Optional[str] = None
+    execution_arn: Optional[str] = None
+    priority: Optional[int] = None
+    created_at: Optional[datetime] = None
+    started_at: Optional[datetime] = None
+    completed_at: Optional[datetime] = None
+
+
+@strawberry.input
+class CreateJobInput:
+    """Request body for creating a transcode/trim job."""
+
+    source_asset_id: UUID
+    preset_id: Optional[UUID] = None
+    trim_start: Optional[float] = None
+    trim_end: Optional[float] = None
+    output_filename: Optional[str] = None
+    priority: int = 0
+
+
+@strawberry.input
+class UpdateAssetInput:
+    """Request body for updating asset metadata."""
+
+    comments: Optional[str] = None
+    tags: Optional[List[str]] = None
+
+
+@strawberry.type
+class SystemStatusType:
+    """System status response."""
+
+    status: Optional[str] = None
+    version: Optional[str] = None
+
+
+@strawberry.type
+class ScanResultType:
+    """Result of scanning the media input bucket."""
+
+    found: Optional[int] = None
+    registered: Optional[int] = None
+    skipped: Optional[int] = None
+    files: Optional[List[str]] = None
+
+
+@strawberry.type
+class DeleteResultType:
+    """Result of a delete operation."""
+
+    ok: Optional[bool] = None
+
+
+@strawberry.type
+class WorkerStatusType:
+    """Worker health and capabilities."""
+
+    available: Optional[bool] = None
+    active_jobs: Optional[int] = None
+    supported_codecs: Optional[List[str]] = None
+    gpu_available: Optional[bool] = None

core/db/__init__.py

@@ -0,0 +1,19 @@
+from .assets import (
+    create_asset,
+    delete_asset,
+    get_asset,
+    get_asset_filenames,
+    list_assets,
+    update_asset,
+)
+from .jobs import (
+    create_job,
+    get_job,
+    list_jobs,
+    update_job,
+    update_job_fields,
+)
+from .presets import (
+    get_preset,
+    list_presets,
+)

core/db/assets.py

@@ -0,0 +1,48 @@
+"""Database operations for MediaAsset."""
+
+from typing import Optional
+from uuid import UUID
+
+
+def list_assets(status: Optional[str] = None, search: Optional[str] = None):
+    from admin.mpr.media_assets.models import MediaAsset
+
+    qs = MediaAsset.objects.all()
+    if status:
+        qs = qs.filter(status=status)
+    if search:
+        qs = qs.filter(filename__icontains=search)
+    return list(qs)
+
+
+def get_asset(id: UUID):
+    from admin.mpr.media_assets.models import MediaAsset
+
+    return MediaAsset.objects.get(id=id)
+
+
+def get_asset_filenames() -> set[str]:
+    from admin.mpr.media_assets.models import MediaAsset
+
+    return set(MediaAsset.objects.values_list("filename", flat=True))
+
+
+def create_asset(*, filename: str, file_path: str, file_size: int):
+    from admin.mpr.media_assets.models import MediaAsset
+
+    return MediaAsset.objects.create(
+        filename=filename,
+        file_path=file_path,
+        file_size=file_size,
+    )
+
+
+def update_asset(asset, **fields):
+    for key, value in fields.items():
+        setattr(asset, key, value)
+    asset.save(update_fields=list(fields.keys()))
+    return asset
+
+
+def delete_asset(asset):
+    asset.delete()

core/db/jobs.py

@@ -0,0 +1,40 @@
+"""Database operations for TranscodeJob."""
+
+from typing import Optional
+from uuid import UUID
+
+
+def list_jobs(status: Optional[str] = None, source_asset_id: Optional[UUID] = None):
+    from admin.mpr.media_assets.models import TranscodeJob
+
+    qs = TranscodeJob.objects.all()
+    if status:
+        qs = qs.filter(status=status)
+    if source_asset_id:
+        qs = qs.filter(source_asset_id=source_asset_id)
+    return list(qs)
+
+
+def get_job(id: UUID):
+    from admin.mpr.media_assets.models import TranscodeJob
+
+    return TranscodeJob.objects.get(id=id)
+
+
+def create_job(**fields):
+    from admin.mpr.media_assets.models import TranscodeJob
+
+    return TranscodeJob.objects.create(**fields)
+
+
+def update_job(job, **fields):
+    for key, value in fields.items():
+        setattr(job, key, value)
+    job.save(update_fields=list(fields.keys()))
+    return job
+
+
+def update_job_fields(job_id, **fields):
+    from admin.mpr.media_assets.models import TranscodeJob
+
+    TranscodeJob.objects.filter(id=job_id).update(**fields)

core/db/presets.py

@@ -0,0 +1,15 @@
+"""Database operations for TranscodePreset."""
+
+from uuid import UUID
+
+
+def list_presets():
+    from admin.mpr.media_assets.models import TranscodePreset
+
+    return list(TranscodePreset.objects.all())
+
+
+def get_preset(id: UUID):
+    from admin.mpr.media_assets.models import TranscodePreset
+
+    return TranscodePreset.objects.get(id=id)

core/rpc/server.py

@@ -59,7 +59,7 @@ class WorkerServicer(worker_pb2_grpc.WorkerServiceServicer):
 
             # Dispatch to Celery if available
             if self.celery_app:
-                from task.tasks import run_transcode_job
+                from core.task.tasks import run_transcode_job
 
                 task = run_transcode_job.delay(
                     job_id=job_id,
@@ -219,9 +219,8 @@ def update_job_progress(
     try:
         from django.utils import timezone
 
-        from mpr.media_assets.models import TranscodeJob
+        from core.db import update_job_fields
 
-        update_fields = ["progress", "current_frame", "current_time", "speed", "status"]
         updates = {
             "progress": progress,
             "current_frame": current_frame,
@@ -232,16 +231,13 @@ def update_job_progress(
 
         if error:
             updates["error_message"] = error
-            update_fields.append("error_message")
 
         if status == "processing":
             updates["started_at"] = timezone.now()
-            update_fields.append("started_at")
         elif status in ("completed", "failed"):
             updates["completed_at"] = timezone.now()
-            update_fields.append("completed_at")
 
-        TranscodeJob.objects.filter(id=job_id).update(**updates)
+        update_job_fields(job_id, **updates)
     except Exception as e:
         logger.warning(f"Failed to update job {job_id} in DB: {e}")
 

core/schema/__init__.py

@@ -4,7 +4,7 @@ MPR Schema Definitions - Source of Truth
 This package defines the core data models as Python dataclasses.
 These definitions are used to generate:
 - Django ORM models (mpr/media_assets/models.py)
-- Pydantic schemas (api/schemas/*.py)
+- Pydantic schemas (api/schema/*.py)
 - TypeScript types (ui/timeline/src/types.ts)
 - Protobuf definitions (grpc/protos/worker.proto)
 

core/schema/modelgen.json

@@ -0,0 +1,25 @@
+{
+  "schema": "core/schema/models",
+  "targets": [
+    {
+      "target": "django",
+      "output": "admin/mpr/media_assets/models.py",
+      "include": ["dataclasses", "enums"]
+    },
+    {
+      "target": "graphene",
+      "output": "core/api/schema/graphql.py",
+      "include": ["dataclasses", "enums", "api"]
+    },
+    {
+      "target": "typescript",
+      "output": "ui/timeline/src/types.ts",
+      "include": ["dataclasses", "enums", "api"]
+    },
+    {
+      "target": "protobuf",
+      "output": "core/rpc/protos/worker.proto",
+      "include": ["grpc"]
+    }
+  ]
+}

core/schema/models/__init__.py

@@ -5,7 +5,13 @@ This module exports all dataclasses, enums, and constants that the generator
 should process. Add new models here to have them included in generation.
 """
 
-from .api import CreateJobRequest, ScanResult, SystemStatus
+from .api import (
+    CreateJobRequest,
+    DeleteResult,
+    ScanResult,
+    SystemStatus,
+    UpdateAssetRequest,
+)
 from .grpc import (
     GRPC_SERVICE,
     CancelRequest,
@@ -26,7 +32,14 @@ DATACLASSES = [MediaAsset, TranscodePreset, TranscodeJob]
 
 # API request/response models - generates TypeScript only (no Django)
 # WorkerStatus from grpc.py is reused here
-API_MODELS = [CreateJobRequest, SystemStatus, ScanResult, WorkerStatus]
+API_MODELS = [
+    CreateJobRequest,
+    UpdateAssetRequest,
+    SystemStatus,
+    ScanResult,
+    DeleteResult,
+    WorkerStatus,
+]
 
 # Status enums - included in generated code
 ENUMS = [AssetStatus, JobStatus]
@@ -50,6 +63,8 @@ __all__ = [
     "TranscodeJob",
     # API Models
     "CreateJobRequest",
+    "UpdateAssetRequest",
+    "DeleteResult",
     "ScanResult",
     "SystemStatus",
     # Enums

core/schema/models/api.py

@@ -40,4 +40,19 @@ class ScanResult:
     files: List[str] = field(default_factory=list)
 
 
+@dataclass
+class UpdateAssetRequest:
+    """Request body for updating asset metadata."""
+
+    comments: Optional[str] = None
+    tags: Optional[List[str]] = None
+
+
+@dataclass
+class DeleteResult:
+    """Result of a delete operation."""
+
+    ok: bool = False
+
+
 # Note: WorkerStatus is defined in grpc.py and reused here

core/storage/__init__.py

@@ -0,0 +1,10 @@
+from .s3 import (
+    BUCKET_IN,
+    BUCKET_OUT,
+    download_file,
+    download_to_temp,
+    get_presigned_url,
+    get_s3_client,
+    list_objects,
+    upload_file,
+)

core/storage/gcp.py

@@ -0,0 +1 @@
+"""GCP Cloud Storage backend (placeholder)."""

core/storage/local.py

@@ -0,0 +1 @@
+"""Local filesystem storage backend (placeholder)."""

core/task/executor.py

@@ -156,8 +156,81 @@ class LambdaExecutor(Executor):
         # Store execution ARN on the job
         execution_arn = response["executionArn"]
         try:
-            from mpr.media_assets.models import TranscodeJob
+            from core.db import update_job_fields
-            TranscodeJob.objects.filter(id=job_id).update(execution_arn=execution_arn)
+            update_job_fields(job_id, execution_arn=execution_arn)
+        except Exception:
+            pass
+
+        return True
+
+
+class GCPExecutor(Executor):
+    """Execute jobs via Google Cloud Run Jobs."""
+
+    def __init__(self):
+        from google.cloud import run_v2
+
+        self.client = run_v2.JobsClient()
+        self.project_id = os.environ["GCP_PROJECT_ID"]
+        self.region = os.environ.get("GCP_REGION", "us-central1")
+        self.job_name = os.environ["CLOUD_RUN_JOB"]
+        self.callback_url = os.environ.get("CALLBACK_URL", "")
+        self.callback_api_key = os.environ.get("CALLBACK_API_KEY", "")
+
+    def run(
+        self,
+        job_id: str,
+        source_path: str,
+        output_path: str,
+        preset: Optional[Dict[str, Any]] = None,
+        trim_start: Optional[float] = None,
+        trim_end: Optional[float] = None,
+        duration: Optional[float] = None,
+        progress_callback: Optional[Callable[[int, Dict[str, Any]], None]] = None,
+    ) -> bool:
+        """Trigger a Cloud Run Job execution for this job."""
+        import json
+
+        from google.cloud import run_v2
+
+        payload = {
+            "job_id": job_id,
+            "source_key": source_path,
+            "output_key": output_path,
+            "preset": preset,
+            "trim_start": trim_start,
+            "trim_end": trim_end,
+            "duration": duration,
+            "callback_url": self.callback_url,
+            "api_key": self.callback_api_key,
+        }
+
+        job_path = (
+            f"projects/{self.project_id}/locations/{self.region}/jobs/{self.job_name}"
+        )
+
+        request = run_v2.RunJobRequest(
+            name=job_path,
+            overrides=run_v2.RunJobRequest.Overrides(
+                container_overrides=[
+                    run_v2.RunJobRequest.Overrides.ContainerOverride(
+                        env=[
+                            run_v2.EnvVar(
+                                name="MPR_JOB_PAYLOAD", value=json.dumps(payload)
+                            )
+                        ]
+                    )
+                ]
+            ),
+        )
+
+        operation = self.client.run_job(request=request)
+        execution_name = operation.metadata.name
+
+        try:
+            from core.db import update_job_fields
+
+            update_job_fields(job_id, execution_arn=execution_name)
         except Exception:
             pass
 
@@ -168,6 +241,7 @@ class LambdaExecutor(Executor):
 _executors: Dict[str, type] = {
     "local": LocalExecutor,
     "lambda": LambdaExecutor,
+    "gcp": GCPExecutor,
 }
 
 _executor_instance: Optional[Executor] = None

core/task/gcp_handler.py

@@ -0,0 +1,121 @@
+"""
+Google Cloud Run Job handler for media transcoding.
+
+Reads job payload from the MPR_JOB_PAYLOAD env var (injected by GCPExecutor),
+downloads source from S3-compatible storage (GCS via HMAC + S3 API),
+runs FFmpeg, uploads result, and calls back to the API.
+
+Uses core/storage and core/ffmpeg — same modules as the Celery worker.
+No cloud-provider SDK required here; storage goes through core.storage (boto3 + S3 compat).
+
+Entry point: python -m task.gcp_handler  (set as Cloud Run Job command)
+"""
+
+import json
+import logging
+import os
+import sys
+import tempfile
+from pathlib import Path
+
+import requests
+
+from core.ffmpeg.transcode import TranscodeConfig, transcode
+from core.storage import BUCKET_IN, BUCKET_OUT, download_to_temp, upload_file
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+
+def main() -> None:
+    raw = os.environ.get("MPR_JOB_PAYLOAD")
+    if not raw:
+        logger.error("MPR_JOB_PAYLOAD not set")
+        sys.exit(1)
+
+    event = json.loads(raw)
+    job_id = event["job_id"]
+    source_key = event["source_key"]
+    output_key = event["output_key"]
+    preset = event.get("preset")
+    trim_start = event.get("trim_start")
+    trim_end = event.get("trim_end")
+    duration = event.get("duration")
+    callback_url = event.get("callback_url", "")
+    api_key = event.get("api_key", "")
+
+    logger.info(f"Starting job {job_id}: {source_key} -> {output_key}")
+
+    tmp_source = download_to_temp(BUCKET_IN, source_key)
+    ext_out = Path(output_key).suffix or ".mp4"
+    fd, tmp_output = tempfile.mkstemp(suffix=ext_out)
+    os.close(fd)
+
+    try:
+        if preset:
+            config = TranscodeConfig(
+                input_path=tmp_source,
+                output_path=tmp_output,
+                video_codec=preset.get("video_codec", "libx264"),
+                video_bitrate=preset.get("video_bitrate"),
+                video_crf=preset.get("video_crf"),
+                video_preset=preset.get("video_preset"),
+                resolution=preset.get("resolution"),
+                framerate=preset.get("framerate"),
+                audio_codec=preset.get("audio_codec", "aac"),
+                audio_bitrate=preset.get("audio_bitrate"),
+                audio_channels=preset.get("audio_channels"),
+                audio_samplerate=preset.get("audio_samplerate"),
+                container=preset.get("container", "mp4"),
+                extra_args=preset.get("extra_args", []),
+                trim_start=trim_start,
+                trim_end=trim_end,
+            )
+        else:
+            config = TranscodeConfig(
+                input_path=tmp_source,
+                output_path=tmp_output,
+                video_codec="copy",
+                audio_codec="copy",
+                trim_start=trim_start,
+                trim_end=trim_end,
+            )
+
+        success = transcode(config, duration=duration)
+        if not success:
+            raise RuntimeError("Transcode returned False")
+
+        logger.info(f"Uploading to {BUCKET_OUT}/{output_key}")
+        upload_file(tmp_output, BUCKET_OUT, output_key)
+
+        _callback(callback_url, job_id, api_key, {"status": "completed"})
+        logger.info(f"Job {job_id} completed")
+        sys.exit(0)
+
+    except Exception as e:
+        logger.exception(f"Job {job_id} failed: {e}")
+        _callback(callback_url, job_id, api_key, {"status": "failed", "error": str(e)})
+        sys.exit(1)
+
+    finally:
+        for f in [tmp_source, tmp_output]:
+            try:
+                os.unlink(f)
+            except OSError:
+                pass
+
+
+def _callback(callback_url: str, job_id: str, api_key: str, payload: dict) -> None:
+    if not callback_url:
+        return
+    try:
+        url = f"{callback_url}/jobs/{job_id}/callback"
+        headers = {"X-API-Key": api_key} if api_key else {}
+        resp = requests.post(url, json=payload, headers=headers, timeout=10)
+        logger.info(f"Callback response: {resp.status_code}")
+    except Exception as e:
+        logger.warning(f"Callback failed: {e}")
+
+
+if __name__ == "__main__":
+    main()

core/task/tasks.py

@@ -9,8 +9,8 @@ from typing import Any, Dict, Optional
 from celery import shared_task
 
 from core.storage import BUCKET_IN, BUCKET_OUT, download_to_temp, upload_file
-from rpc.server import update_job_progress
+from core.rpc.server import update_job_progress
-from task.executor import get_executor
+from core.task.executor import get_executor
 
 logger = logging.getLogger(__name__)
 

ctrl/.env.template

@@ -16,7 +16,7 @@ REDIS_URL=redis://redis:6379/0
 
 # Django
 DEBUG=1
-DJANGO_SETTINGS_MODULE=mpr.settings
+DJANGO_SETTINGS_MODULE=admin.mpr.settings
 SECRET_KEY=change-this-in-production
 
 # Worker

ctrl/Dockerfile

@@ -1,14 +1,10 @@
 FROM python:3.11-slim
 
-RUN apt-get update && apt-get install -y \
-    ffmpeg \
-    && rm -rf /var/lib/apt/lists/*
-
 WORKDIR /app
 
 COPY requirements.txt .
 RUN pip install --no-cache-dir -r requirements.txt
 
-COPY . .
+# No COPY . . — code is volume-mounted in dev (..:/app)
 
-CMD ["python", "manage.py", "runserver", "0.0.0.0:8000"]
+CMD ["python", "admin/manage.py", "runserver", "0.0.0.0:8000"]

ctrl/Dockerfile.worker

@@ -0,0 +1,14 @@
+FROM python:3.11-slim
+
+RUN apt-get update && apt-get install -y \
+    ffmpeg \
+    && rm -rf /var/lib/apt/lists/*
+
+WORKDIR /app
+
+COPY requirements.txt requirements-worker.txt ./
+RUN pip install --no-cache-dir -r requirements-worker.txt
+
+# No COPY . . — code is volume-mounted in dev (..:/app)
+
+CMD ["celery", "-A", "admin.mpr", "worker", "--loglevel=info"]

ctrl/docker-compose.yml

@@ -1,7 +1,7 @@
 x-common-env: &common-env
   DATABASE_URL: postgresql://mpr_user:mpr_pass@postgres:5432/mpr
   REDIS_URL: redis://redis:6379/0
-  DJANGO_SETTINGS_MODULE: mpr.settings
+  DJANGO_SETTINGS_MODULE: admin.mpr.settings
   DEBUG: 1
   GRPC_HOST: grpc
   GRPC_PORT: 50051
@@ -96,9 +96,9 @@ services:
       context: ..
       dockerfile: ctrl/Dockerfile
     command: >
-      bash -c "python manage.py migrate &&
+      bash -c "python admin/manage.py migrate &&
-               python manage.py loadbuiltins || true &&
+               python admin/manage.py loadbuiltins || true &&
-               python manage.py runserver 0.0.0.0:8701"
+               python admin/manage.py runserver 0.0.0.0:8701"
     ports:
       - "8701:8701"
     environment:
@@ -115,11 +115,12 @@ services:
     build:
       context: ..
       dockerfile: ctrl/Dockerfile
-    command: uvicorn api.main:app --host 0.0.0.0 --port 8702 --reload
+    command: uvicorn core.api.main:app --host 0.0.0.0 --port 8702 --reload
     ports:
       - "8702:8702"
     environment:
       <<: *common-env
+      DJANGO_ALLOW_ASYNC_UNSAFE: "true"
     volumes:
       - ..:/app
     depends_on:
@@ -132,7 +133,7 @@ services:
     build:
       context: ..
       dockerfile: ctrl/Dockerfile
-    command: python -m rpc.server
+    command: python -m core.rpc.server
     ports:
       - "50052:50051"
     environment:
@@ -150,8 +151,8 @@ services:
   celery:
     build:
       context: ..
-      dockerfile: ctrl/Dockerfile
+      dockerfile: ctrl/Dockerfile.worker
-    command: celery -A mpr worker -l info -Q transcode -c 2
+    command: celery -A admin.mpr worker -l info -Q transcode -c 2
     environment:
       <<: *common-env
       MPR_EXECUTOR: local

ctrl/generate.sh

@@ -1,57 +1,22 @@
 #!/bin/bash
 # Model generation script for MPR
-# Generates Django, Pydantic, TypeScript, and Protobuf from schema/models
+# Generates all targets from core/schema/modelgen.json config
 
 set -e
-
 cd "$(dirname "$0")/.."
 
-echo "Generating models from schema/models..."
+echo "Generating models from core/schema/models..."
-
+python -m modelgen generate --config core/schema/modelgen.json
-# Django ORM models: domain models + enums
-python -m modelgen from-schema \
-    --schema schema/models \
-    --output mpr/media_assets/models.py \
-    --targets django \
-    --include dataclasses,enums
-
-# Pydantic schemas for FastAPI: domain models + enums
-python -m modelgen from-schema \
-    --schema schema/models \
-    --output api/schemas/models.py \
-    --targets pydantic \
-    --include dataclasses,enums
-
-# TypeScript types for Timeline UI: domain models + enums + API types
-python -m modelgen from-schema \
-    --schema schema/models \
-    --output ui/timeline/src/types.ts \
-    --targets typescript \
-    --include dataclasses,enums,api
-
-# Graphene types for GraphQL: domain models + enums + API types
-python -m modelgen from-schema \
-    --schema schema/models \
-    --output api/schemas/graphql.py \
-    --targets graphene \
-    --include dataclasses,enums,api
-
-# Protobuf for gRPC: gRPC messages + service
-python -m modelgen from-schema \
-    --schema schema/models \
-    --output rpc/protos/worker.proto \
-    --targets proto \
-    --include grpc
 
 # Generate gRPC stubs from proto
 echo "Generating gRPC stubs..."
 python -m grpc_tools.protoc \
-    -I rpc/protos \
+    -I core/rpc/protos \
-    --python_out=rpc \
+    --python_out=core/rpc \
-    --grpc_python_out=rpc \
+    --grpc_python_out=core/rpc \
-    rpc/protos/worker.proto
+    core/rpc/protos/worker.proto
 
 # Fix relative import in generated grpc stub
-sed -i 's/^import worker_pb2/from . import worker_pb2/' rpc/worker_pb2_grpc.py
+sed -i 's/^import worker_pb2/from . import worker_pb2/' core/rpc/worker_pb2_grpc.py
 
 echo "Done!"

ctrl/lambda/Dockerfile

@@ -14,8 +14,8 @@ COPY ctrl/lambda/requirements.txt .
 RUN pip install --no-cache-dir -r requirements.txt
 
 # Copy application code
-COPY task/lambda_handler.py ${LAMBDA_TASK_ROOT}/task/lambda_handler.py
+COPY core/task/lambda_handler.py ${LAMBDA_TASK_ROOT}/core/task/lambda_handler.py
-COPY task/__init__.py ${LAMBDA_TASK_ROOT}/task/__init__.py
+COPY core/task/__init__.py ${LAMBDA_TASK_ROOT}/core/task/__init__.py
 COPY core/ ${LAMBDA_TASK_ROOT}/core/
 
-CMD ["task.lambda_handler.handler"]
+CMD ["core.task.lambda_handler.handler"]

ctrl/nginx.conf

@@ -44,9 +44,9 @@ http {
             proxy_set_header Host $host;
         }
 
-        # FastAPI
+        # FastAPI — trailing slash strips /api prefix before forwarding
         location /api/ {
-            proxy_pass http://fastapi;
+            proxy_pass http://fastapi/;
             proxy_set_header Host $host;
             proxy_set_header X-Real-IP $remote_addr;
             proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;

docs/architecture/01-system-overview.dot

@@ -1,114 +0,0 @@
-digraph system_overview {
-    rankdir=TB
-    node [shape=box, style=rounded, fontname="Helvetica"]
-    edge [fontname="Helvetica", fontsize=10]
-
-    labelloc="t"
-    label="MPR - System Overview"
-    fontsize=16
-    fontname="Helvetica-Bold"
-
-    graph [splines=ortho, nodesep=0.8, ranksep=0.8]
-
-    // External
-    subgraph cluster_external {
-        label="External"
-        style=dashed
-        color=gray
-
-        browser [label="Browser\nmpr.local.ar / mpr.mcrn.ar", shape=ellipse]
-    }
-
-    // Nginx reverse proxy
-    subgraph cluster_proxy {
-        label="Reverse Proxy"
-        style=filled
-        fillcolor="#e8f4f8"
-
-        nginx [label="nginx\nport 80"]
-    }
-
-    // Application layer
-    subgraph cluster_apps {
-        label="Application Layer"
-        style=filled
-        fillcolor="#f0f8e8"
-
-        django [label="Django\n/admin\nport 8701"]
-        fastapi [label="FastAPI\n/api + /graphql\nport 8702"]
-        timeline [label="Timeline UI\n/ui\nport 5173"]
-    }
-
-    // Worker layer
-    subgraph cluster_workers {
-        label="Worker Layer"
-        style=filled
-        fillcolor="#fff8e8"
-
-        grpc_server [label="gRPC Server\nport 50051"]
-        celery [label="Celery Worker\n(local mode)"]
-    }
-
-    // AWS layer
-    subgraph cluster_aws {
-        label="AWS (lambda mode)"
-        style=filled
-        fillcolor="#fde8d0"
-
-        step_functions [label="Step Functions\nstate machine"]
-        lambda [label="Lambda\nFFmpeg container"]
-    }
-
-    // Data layer
-    subgraph cluster_data {
-        label="Data Layer"
-        style=filled
-        fillcolor="#f8e8f0"
-
-        postgres [label="PostgreSQL\nport 5436", shape=cylinder]
-        redis [label="Redis\nport 6381", shape=cylinder]
-    }
-
-    // Storage
-    subgraph cluster_storage {
-        label="S3 Storage"
-        style=filled
-        fillcolor="#f0f0f0"
-
-        minio [label="MinIO (local)\nport 9000", shape=folder]
-        s3 [label="AWS S3 (cloud)", shape=folder, style="dashed,rounded"]
-        bucket_in [label="mpr-media-in", shape=note]
-        bucket_out [label="mpr-media-out", shape=note]
-    }
-
-    // Connections
-    browser -> nginx
-
-    nginx -> django [xlabel="/admin"]
-    nginx -> fastapi [xlabel="/api, /graphql"]
-    nginx -> timeline [xlabel="/ui"]
-    nginx -> minio [xlabel="/media/*"]
-
-    timeline -> fastapi [xlabel="REST API"]
-
-    fastapi -> postgres
-    fastapi -> grpc_server [xlabel="gRPC\nprogress"]
-
-    // Local mode
-    grpc_server -> celery [xlabel="task dispatch"]
-    celery -> redis [xlabel="queue"]
-    celery -> postgres [xlabel="job updates"]
-    celery -> minio [xlabel="S3 API\ndownload/upload"]
-
-    // Lambda mode
-    fastapi -> step_functions [xlabel="boto3\nstart_execution", style=dashed]
-    step_functions -> lambda [style=dashed]
-    lambda -> s3 [xlabel="download/upload", style=dashed]
-    lambda -> fastapi [xlabel="callback\nPOST /jobs/{id}/callback", style=dashed]
-
-    // Storage details
-    minio -> bucket_in [style=dotted, arrowhead=none]
-    minio -> bucket_out [style=dotted, arrowhead=none]
-    s3 -> bucket_in [style=dotted, arrowhead=none]
-    s3 -> bucket_out [style=dotted, arrowhead=none]
-}

docs/architecture/01-system-overview.svg

@@ -1,293 +0,0 @@
-<?xml version="1.0" encoding="UTF-8" standalone="no"?>
-<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN"
- "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
-<!-- Generated by graphviz version 14.1.2 (0)
- -->
-<!-- Title: system_overview Pages: 1 -->
-<svg width="620pt" height="903pt"
- viewBox="0.00 0.00 620.00 903.00" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
-<g id="graph0" class="graph" transform="scale(1 1) rotate(0) translate(4 898.54)">
-<title>system_overview</title>
-<polygon fill="white" stroke="none" points="-4,4 -4,-898.54 616,-898.54 616,4 -4,4"/>
-<text xml:space="preserve" text-anchor="middle" x="306" y="-875.34" font-family="Helvetica,sans-Serif" font-weight="bold" font-size="16.00">MPR &#45; System Overview</text>
-<g id="clust1" class="cluster">
-<title>cluster_external</title>
-<polygon fill="none" stroke="gray" stroke-dasharray="5,2" points="246,-755.44 246,-859.04 540,-859.04 540,-755.44 246,-755.44"/>
-<text xml:space="preserve" text-anchor="middle" x="393" y="-839.84" font-family="Helvetica,sans-Serif" font-weight="bold" font-size="16.00">External</text>
-</g>
-<g id="clust2" class="cluster">
-<title>cluster_proxy</title>
-<polygon fill="#e8f4f8" stroke="black" points="320,-654.94 320,-740.94 466,-740.94 466,-654.94 320,-654.94"/>
-<text xml:space="preserve" text-anchor="middle" x="393" y="-721.74" font-family="Helvetica,sans-Serif" font-weight="bold" font-size="16.00">Reverse Proxy</text>
-</g>
-<g id="clust3" class="cluster">
-<title>cluster_apps</title>
-<polygon fill="#f0f8e8" stroke="black" points="278,-419.44 278,-640.44 532,-640.44 532,-419.44 278,-419.44"/>
-<text xml:space="preserve" text-anchor="middle" x="405" y="-621.24" font-family="Helvetica,sans-Serif" font-weight="bold" font-size="16.00">Application Layer</text>
-</g>
-<g id="clust4" class="cluster">
-<title>cluster_workers</title>
-<polygon fill="#fff8e8" stroke="black" points="142,-218.44 142,-404.94 280,-404.94 280,-218.44 142,-218.44"/>
-<text xml:space="preserve" text-anchor="middle" x="211" y="-385.74" font-family="Helvetica,sans-Serif" font-weight="bold" font-size="16.00">Worker Layer</text>
-</g>
-<g id="clust5" class="cluster">
-<title>cluster_aws</title>
-<polygon fill="#fde8d0" stroke="black" points="383,-218.44 383,-404.94 581,-404.94 581,-218.44 383,-218.44"/>
-<text xml:space="preserve" text-anchor="middle" x="482" y="-385.74" font-family="Helvetica,sans-Serif" font-weight="bold" font-size="16.00">AWS (lambda mode)</text>
-</g>
-<g id="clust6" class="cluster">
-<title>cluster_data</title>
-<polygon fill="#f8e8f0" stroke="black" points="8,-102 8,-203.94 263,-203.94 263,-102 8,-102"/>
-<text xml:space="preserve" text-anchor="middle" x="135.5" y="-184.74" font-family="Helvetica,sans-Serif" font-weight="bold" font-size="16.00">Data Layer</text>
-</g>
-<g id="clust7" class="cluster">
-<title>cluster_storage</title>
-<polygon fill="#f0f0f0" stroke="black" points="302,-8 302,-195.97 604,-195.97 604,-8 302,-8"/>
-<text xml:space="preserve" text-anchor="middle" x="453" y="-176.77" font-family="Helvetica,sans-Serif" font-weight="bold" font-size="16.00">S3 Storage</text>
-</g>
-<!-- browser -->
-<g id="node1" class="node">
-<title>browser</title>
-<ellipse fill="none" stroke="black" cx="393" cy="-793.49" rx="139.12" ry="30.05"/>
-<text xml:space="preserve" text-anchor="middle" x="393" y="-797.44" font-family="Helvetica,sans-Serif" font-size="14.00">Browser</text>
-<text xml:space="preserve" text-anchor="middle" x="393" y="-780.19" font-family="Helvetica,sans-Serif" font-size="14.00">mpr.local.ar / mpr.mcrn.ar</text>
-</g>
-<!-- nginx -->
-<g id="node2" class="node">
-<title>nginx</title>
-<path fill="none" stroke="black" d="M414.5,-705.44C414.5,-705.44 371.5,-705.44 371.5,-705.44 365.5,-705.44 359.5,-699.44 359.5,-693.44 359.5,-693.44 359.5,-674.94 359.5,-674.94 359.5,-668.94 365.5,-662.94 371.5,-662.94 371.5,-662.94 414.5,-662.94 414.5,-662.94 420.5,-662.94 426.5,-668.94 426.5,-674.94 426.5,-674.94 426.5,-693.44 426.5,-693.44 426.5,-699.44 420.5,-705.44 414.5,-705.44"/>
-<text xml:space="preserve" text-anchor="middle" x="393" y="-688.14" font-family="Helvetica,sans-Serif" font-size="14.00">nginx</text>
-<text xml:space="preserve" text-anchor="middle" x="393" y="-670.89" font-family="Helvetica,sans-Serif" font-size="14.00">port 80</text>
-</g>
-<!-- browser&#45;&gt;nginx -->
-<g id="edge1" class="edge">
-<title>browser&#45;&gt;nginx</title>
-<path fill="none" stroke="black" d="M393,-763.04C393,-763.04 393,-717.33 393,-717.33"/>
-<polygon fill="black" stroke="black" points="396.5,-717.33 393,-707.33 389.5,-717.33 396.5,-717.33"/>
-</g>
-<!-- django -->
-<g id="node3" class="node">
-<title>django</title>
-<path fill="none" stroke="black" d="M359.5,-604.94C359.5,-604.94 298.5,-604.94 298.5,-604.94 292.5,-604.94 286.5,-598.94 286.5,-592.94 286.5,-592.94 286.5,-557.19 286.5,-557.19 286.5,-551.19 292.5,-545.19 298.5,-545.19 298.5,-545.19 359.5,-545.19 359.5,-545.19 365.5,-545.19 371.5,-551.19 371.5,-557.19 371.5,-557.19 371.5,-592.94 371.5,-592.94 371.5,-598.94 365.5,-604.94 359.5,-604.94"/>
-<text xml:space="preserve" text-anchor="middle" x="329" y="-587.64" font-family="Helvetica,sans-Serif" font-size="14.00">Django</text>
-<text xml:space="preserve" text-anchor="middle" x="329" y="-570.39" font-family="Helvetica,sans-Serif" font-size="14.00">/admin</text>
-<text xml:space="preserve" text-anchor="middle" x="329" y="-553.14" font-family="Helvetica,sans-Serif" font-size="14.00">port 8701</text>
-</g>
-<!-- nginx&#45;&gt;django -->
-<g id="edge2" class="edge">
-<title>nginx&#45;&gt;django</title>
-<path fill="none" stroke="black" d="M365.5,-662.63C365.5,-662.63 365.5,-616.77 365.5,-616.77"/>
-<polygon fill="black" stroke="black" points="369,-616.77 365.5,-606.77 362,-616.77 369,-616.77"/>
-<text xml:space="preserve" text-anchor="middle" x="348.62" y="-642.95" font-family="Helvetica,sans-Serif" font-size="10.00">/admin</text>
-</g>
-<!-- fastapi -->
-<g id="node4" class="node">
-<title>fastapi</title>
-<path fill="none" stroke="black" d="M395.5,-487.19C395.5,-487.19 298.5,-487.19 298.5,-487.19 292.5,-487.19 286.5,-481.19 286.5,-475.19 286.5,-475.19 286.5,-439.44 286.5,-439.44 286.5,-433.44 292.5,-427.44 298.5,-427.44 298.5,-427.44 395.5,-427.44 395.5,-427.44 401.5,-427.44 407.5,-433.44 407.5,-439.44 407.5,-439.44 407.5,-475.19 407.5,-475.19 407.5,-481.19 401.5,-487.19 395.5,-487.19"/>
-<text xml:space="preserve" text-anchor="middle" x="347" y="-469.89" font-family="Helvetica,sans-Serif" font-size="14.00">FastAPI</text>
-<text xml:space="preserve" text-anchor="middle" x="347" y="-452.64" font-family="Helvetica,sans-Serif" font-size="14.00">/api + /graphql</text>
-<text xml:space="preserve" text-anchor="middle" x="347" y="-435.39" font-family="Helvetica,sans-Serif" font-size="14.00">port 8702</text>
-</g>
-<!-- nginx&#45;&gt;fastapi -->
-<g id="edge3" class="edge">
-<title>nginx&#45;&gt;fastapi</title>
-<path fill="none" stroke="black" d="M383.5,-662.84C383.5,-662.84 383.5,-498.82 383.5,-498.82"/>
-<polygon fill="black" stroke="black" points="387,-498.82 383.5,-488.82 380,-498.82 387,-498.82"/>
-<text xml:space="preserve" text-anchor="middle" x="399.44" y="-571.33" font-family="Helvetica,sans-Serif" font-size="10.00">/api, /graphql</text>
-</g>
-<!-- timeline -->
-<g id="node5" class="node">
-<title>timeline</title>
-<path fill="none" stroke="black" d="M512,-604.94C512,-604.94 442,-604.94 442,-604.94 436,-604.94 430,-598.94 430,-592.94 430,-592.94 430,-557.19 430,-557.19 430,-551.19 436,-545.19 442,-545.19 442,-545.19 512,-545.19 512,-545.19 518,-545.19 524,-551.19 524,-557.19 524,-557.19 524,-592.94 524,-592.94 524,-598.94 518,-604.94 512,-604.94"/>
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-<text xml:space="preserve" text-anchor="middle" x="477" y="-570.39" font-family="Helvetica,sans-Serif" font-size="14.00">/ui</text>
-<text xml:space="preserve" text-anchor="middle" x="477" y="-553.14" font-family="Helvetica,sans-Serif" font-size="14.00">port 5173</text>
-</g>
-<!-- nginx&#45;&gt;timeline -->
-<g id="edge4" class="edge">
-<title>nginx&#45;&gt;timeline</title>
-<path fill="none" stroke="black" d="M422.62,-662.67C422.62,-633.49 422.62,-585 422.62,-585 422.62,-585 423.34,-585 423.34,-585"/>
-<polygon fill="black" stroke="black" points="418.22,-588.5 428.22,-585 418.22,-581.5 418.22,-588.5"/>
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-</g>
-<!-- minio -->
-<g id="node12" class="node">
-<title>minio</title>
-<polygon fill="none" stroke="black" points="415.5,-160.47 412.5,-164.47 391.5,-164.47 388.5,-160.47 312.5,-160.47 312.5,-117.97 415.5,-117.97 415.5,-160.47"/>
-<text xml:space="preserve" text-anchor="middle" x="364" y="-143.17" font-family="Helvetica,sans-Serif" font-size="14.00">MinIO (local)</text>
-<text xml:space="preserve" text-anchor="middle" x="364" y="-125.92" font-family="Helvetica,sans-Serif" font-size="14.00">port 9000</text>
-</g>
-<!-- nginx&#45;&gt;minio -->
-<g id="edge5" class="edge">
-<title>nginx&#45;&gt;minio</title>
-<path fill="none" stroke="black" d="M414.88,-662.68C414.88,-596.12 414.88,-398 414.88,-398 414.88,-398 344.17,-398 344.17,-398 344.17,-398 344.17,-172.35 344.17,-172.35"/>
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-<text xml:space="preserve" text-anchor="middle" x="378.03" y="-401.25" font-family="Helvetica,sans-Serif" font-size="10.00">/media/*</text>
-</g>
-<!-- grpc_server -->
-<g id="node6" class="node">
-<title>grpc_server</title>
-<path fill="none" stroke="black" d="M246.5,-369.44C246.5,-369.44 167.5,-369.44 167.5,-369.44 161.5,-369.44 155.5,-363.44 155.5,-357.44 155.5,-357.44 155.5,-338.94 155.5,-338.94 155.5,-332.94 161.5,-326.94 167.5,-326.94 167.5,-326.94 246.5,-326.94 246.5,-326.94 252.5,-326.94 258.5,-332.94 258.5,-338.94 258.5,-338.94 258.5,-357.44 258.5,-357.44 258.5,-363.44 252.5,-369.44 246.5,-369.44"/>
-<text xml:space="preserve" text-anchor="middle" x="207" y="-352.14" font-family="Helvetica,sans-Serif" font-size="14.00">gRPC Server</text>
-<text xml:space="preserve" text-anchor="middle" x="207" y="-334.89" font-family="Helvetica,sans-Serif" font-size="14.00">port 50051</text>
-</g>
-<!-- fastapi&#45;&gt;grpc_server -->
-<g id="edge8" class="edge">
-<title>fastapi&#45;&gt;grpc_server</title>
-<path fill="none" stroke="black" d="M298.5,-427.06C298.5,-392.59 298.5,-341 298.5,-341 298.5,-341 270.41,-341 270.41,-341"/>
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-<text xml:space="preserve" text-anchor="middle" x="319.5" y="-385.98" font-family="Helvetica,sans-Serif" font-size="10.00">gRPC</text>
-<text xml:space="preserve" text-anchor="middle" x="319.5" y="-373.23" font-family="Helvetica,sans-Serif" font-size="10.00">progress</text>
-</g>
-<!-- step_functions -->
-<g id="node8" class="node">
-<title>step_functions</title>
-<path fill="none" stroke="black" d="M541.38,-369.44C541.38,-369.44 446.62,-369.44 446.62,-369.44 440.62,-369.44 434.62,-363.44 434.62,-357.44 434.62,-357.44 434.62,-338.94 434.62,-338.94 434.62,-332.94 440.62,-326.94 446.62,-326.94 446.62,-326.94 541.38,-326.94 541.38,-326.94 547.38,-326.94 553.38,-332.94 553.38,-338.94 553.38,-338.94 553.38,-357.44 553.38,-357.44 553.38,-363.44 547.38,-369.44 541.38,-369.44"/>
-<text xml:space="preserve" text-anchor="middle" x="494" y="-352.14" font-family="Helvetica,sans-Serif" font-size="14.00">Step Functions</text>
-<text xml:space="preserve" text-anchor="middle" x="494" y="-334.89" font-family="Helvetica,sans-Serif" font-size="14.00">state machine</text>
-</g>
-<!-- fastapi&#45;&gt;step_functions -->
-<g id="edge13" class="edge">
-<title>fastapi&#45;&gt;step_functions</title>
-<path fill="none" stroke="black" stroke-dasharray="5,2" d="M375.83,-427.17C375.83,-396.99 375.83,-355 375.83,-355 375.83,-355 422.71,-355 422.71,-355"/>
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-<text xml:space="preserve" text-anchor="middle" x="338.33" y="-358.15" font-family="Helvetica,sans-Serif" font-size="10.00">boto3</text>
-<text xml:space="preserve" text-anchor="middle" x="338.33" y="-345.4" font-family="Helvetica,sans-Serif" font-size="10.00">start_execution</text>
-</g>
-<!-- postgres -->
-<g id="node10" class="node">
-<title>postgres</title>
-<path fill="none" stroke="black" d="M111.75,-163.12C111.75,-166.06 90.35,-168.44 64,-168.44 37.65,-168.44 16.25,-166.06 16.25,-163.12 16.25,-163.12 16.25,-115.31 16.25,-115.31 16.25,-112.38 37.65,-110 64,-110 90.35,-110 111.75,-112.38 111.75,-115.31 111.75,-115.31 111.75,-163.12 111.75,-163.12"/>
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-<text xml:space="preserve" text-anchor="middle" x="64" y="-143.17" font-family="Helvetica,sans-Serif" font-size="14.00">PostgreSQL</text>
-<text xml:space="preserve" text-anchor="middle" x="64" y="-125.92" font-family="Helvetica,sans-Serif" font-size="14.00">port 5436</text>
-</g>
-<!-- fastapi&#45;&gt;postgres -->
-<g id="edge7" class="edge">
-<title>fastapi&#45;&gt;postgres</title>
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-<!-- timeline&#45;&gt;fastapi -->
-<g id="edge6" class="edge">
-<title>timeline&#45;&gt;fastapi</title>
-<path fill="none" stroke="black" d="M429.59,-565C411.66,-565 395.5,-565 395.5,-565 395.5,-565 395.5,-499.11 395.5,-499.11"/>
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-</g>
-<!-- celery -->
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-<title>celery</title>
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-<!-- redis -->
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-</g>
-<!-- step_functions&#45;&gt;lambda -->
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docs/architecture/01a-local-architecture.dot

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+digraph local_architecture {
+    rankdir=TB
+    node [shape=box, style=rounded, fontname="Helvetica"]
+    edge [fontname="Helvetica", fontsize=10]
+
+    labelloc="t"
+    label="MPR - Local Architecture (Celery + MinIO)"
+    fontsize=16
+    fontname="Helvetica-Bold"
+
+    graph [splines=ortho, nodesep=0.8, ranksep=0.8]
+
+    // External
+    subgraph cluster_external {
+        label="External"
+        style=dashed
+        color=gray
+
+        browser [label="Browser\nmpr.local.ar", shape=ellipse]
+    }
+
+    // Nginx reverse proxy
+    subgraph cluster_proxy {
+        label="Reverse Proxy"
+        style=filled
+        fillcolor="#e8f4f8"
+
+        nginx [label="nginx\nport 80"]
+    }
+
+    // Application layer
+    subgraph cluster_apps {
+        label="Application Layer"
+        style=filled
+        fillcolor="#f0f8e8"
+
+        django [label="Django Admin\n/admin\nport 8701"]
+        fastapi [label="GraphQL API\n/graphql\nport 8702"]
+        timeline [label="Timeline UI\n/\nport 5173"]
+    }
+
+    // Worker layer
+    subgraph cluster_workers {
+        label="Worker Layer"
+        style=filled
+        fillcolor="#fff8e8"
+
+        grpc_server [label="gRPC Server\nport 50051"]
+        celery [label="Celery Worker\nFFmpeg transcoding"]
+    }
+
+    // Data layer
+    subgraph cluster_data {
+        label="Data Layer"
+        style=filled
+        fillcolor="#f8e8f0"
+
+        postgres [label="PostgreSQL\nport 5436", shape=cylinder]
+        redis [label="Redis\nCelery queue\nport 6381", shape=cylinder]
+    }
+
+    // Storage
+    subgraph cluster_storage {
+        label="S3 Storage (MinIO)"
+        style=filled
+        fillcolor="#f0f0f0"
+
+        minio [label="MinIO\nS3-compatible API\nport 9000", shape=folder]
+        bucket_in [label="mpr-media-in/\ninput videos", shape=note]
+        bucket_out [label="mpr-media-out/\ntranscoded output", shape=note]
+    }
+
+    // Connections
+    browser -> nginx [label="HTTP"]
+
+    nginx -> django [xlabel="/admin"]
+    nginx -> fastapi [xlabel="/graphql"]
+    nginx -> timeline [xlabel="/"]
+    nginx -> minio [xlabel="/media/*"]
+
+    timeline -> fastapi [label="GraphQL"]
+    django -> postgres
+
+    fastapi -> postgres [label="read/write jobs"]
+    fastapi -> grpc_server [label="gRPC\nprogress updates"]
+
+    grpc_server -> celery [label="dispatch tasks"]
+    celery -> redis [label="task queue"]
+    celery -> postgres [label="update job status"]
+    celery -> minio [label="S3 API\ndownload input\nupload output"]
+
+    minio -> bucket_in [style=dotted, arrowhead=none]
+    minio -> bucket_out [style=dotted, arrowhead=none]
+}

docs/architecture/01a-local-architecture.svg

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+<text xml:space="preserve" text-anchor="middle" x="347" y="-886.71" font-family="Helvetica,sans-Serif" font-weight="bold" font-size="16.00">Reverse Proxy</text>
+</g>
+<g id="clust3" class="cluster">
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+<polygon fill="#f0f8e8" stroke="black" points="19,-556.16 19,-789.91 301,-789.91 301,-556.16 19,-556.16"/>
+<text xml:space="preserve" text-anchor="middle" x="160" y="-770.71" font-family="Helvetica,sans-Serif" font-weight="bold" font-size="16.00">Application Layer</text>
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+<g id="clust6" class="cluster">
+<title>cluster_storage</title>
+<polygon fill="#f0f0f0" stroke="black" points="319,-8 319,-223.95 651,-223.95 651,-8 319,-8"/>
+<text xml:space="preserve" text-anchor="middle" x="485" y="-204.75" font-family="Helvetica,sans-Serif" font-weight="bold" font-size="16.00">S3 Storage (MinIO)</text>
+</g>
+<!-- browser -->
+<g id="node1" class="node">
+<title>browser</title>
+<ellipse fill="none" stroke="black" cx="347" cy="-985.71" rx="69.12" ry="30.05"/>
+<text xml:space="preserve" text-anchor="middle" x="347" y="-989.66" font-family="Helvetica,sans-Serif" font-size="14.00">Browser</text>
+<text xml:space="preserve" text-anchor="middle" x="347" y="-972.41" font-family="Helvetica,sans-Serif" font-size="14.00">mpr.local.ar</text>
+</g>
+<!-- nginx -->
+<g id="node2" class="node">
+<title>nginx</title>
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+<text xml:space="preserve" text-anchor="middle" x="347" y="-835.86" font-family="Helvetica,sans-Serif" font-size="14.00">port 80</text>
+</g>
+<!-- browser&#45;&gt;nginx -->
+<g id="edge1" class="edge">
+<title>browser&#45;&gt;nginx</title>
+<path fill="none" stroke="black" d="M347,-955.4C347,-955.4 347,-882.41 347,-882.41"/>
+<polygon fill="black" stroke="black" points="350.5,-882.41 347,-872.41 343.5,-882.41 350.5,-882.41"/>
+<text xml:space="preserve" text-anchor="middle" x="359.75" y="-917.16" font-family="Helvetica,sans-Serif" font-size="10.00">HTTP</text>
+</g>
+<!-- django -->
+<g id="node3" class="node">
+<title>django</title>
+<path fill="none" stroke="black" d="M128.75,-754.41C128.75,-754.41 39.25,-754.41 39.25,-754.41 33.25,-754.41 27.25,-748.41 27.25,-742.41 27.25,-742.41 27.25,-706.66 27.25,-706.66 27.25,-700.66 33.25,-694.66 39.25,-694.66 39.25,-694.66 128.75,-694.66 128.75,-694.66 134.75,-694.66 140.75,-700.66 140.75,-706.66 140.75,-706.66 140.75,-742.41 140.75,-742.41 140.75,-748.41 134.75,-754.41 128.75,-754.41"/>
+<text xml:space="preserve" text-anchor="middle" x="84" y="-737.11" font-family="Helvetica,sans-Serif" font-size="14.00">Django Admin</text>
+<text xml:space="preserve" text-anchor="middle" x="84" y="-719.86" font-family="Helvetica,sans-Serif" font-size="14.00">/admin</text>
+<text xml:space="preserve" text-anchor="middle" x="84" y="-702.61" font-family="Helvetica,sans-Serif" font-size="14.00">port 8701</text>
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+<text xml:space="preserve" text-anchor="middle" x="241" y="-572.11" font-family="Helvetica,sans-Serif" font-size="14.00">port 8702</text>
+</g>
+<!-- nginx&#45;&gt;fastapi -->
+<g id="edge3" class="edge">
+<title>nginx&#45;&gt;fastapi</title>
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+<!-- timeline -->
+<g id="node5" class="node">
+<title>timeline</title>
+<path fill="none" stroke="black" d="M281,-754.41C281,-754.41 211,-754.41 211,-754.41 205,-754.41 199,-748.41 199,-742.41 199,-742.41 199,-706.66 199,-706.66 199,-700.66 205,-694.66 211,-694.66 211,-694.66 281,-694.66 281,-694.66 287,-694.66 293,-700.66 293,-706.66 293,-706.66 293,-742.41 293,-742.41 293,-748.41 287,-754.41 281,-754.41"/>
+<text xml:space="preserve" text-anchor="middle" x="246" y="-737.11" font-family="Helvetica,sans-Serif" font-size="14.00">Timeline UI</text>
+<text xml:space="preserve" text-anchor="middle" x="246" y="-719.86" font-family="Helvetica,sans-Serif" font-size="14.00">/</text>
+<text xml:space="preserve" text-anchor="middle" x="246" y="-702.61" font-family="Helvetica,sans-Serif" font-size="14.00">port 5173</text>
+</g>
+<!-- nginx&#45;&gt;timeline -->
+<g id="edge4" class="edge">
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+<text xml:space="preserve" text-anchor="middle" x="415" y="-136.65" font-family="Helvetica,sans-Serif" font-size="14.00">port 9000</text>
+</g>
+<!-- nginx&#45;&gt;minio -->
+<g id="edge5" class="edge">
+<title>nginx&#45;&gt;minio</title>
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+</g>
+<!-- postgres -->
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+</g>
+<!-- django&#45;&gt;postgres -->
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+<text xml:space="preserve" text-anchor="middle" x="262" y="-431.61" font-family="Helvetica,sans-Serif" font-size="14.00">port 50051</text>
+</g>
+<!-- fastapi&#45;&gt;grpc_server -->
+<g id="edge9" class="edge">
+<title>fastapi&#45;&gt;grpc_server</title>
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+</g>
+<!-- fastapi&#45;&gt;postgres -->
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+<!-- timeline&#45;&gt;fastapi -->
+<g id="edge6" class="edge">
+<title>timeline&#45;&gt;fastapi</title>
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+<title>celery&#45;&gt;redis</title>
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+<text xml:space="preserve" text-anchor="middle" x="441.5" y="-246.41" font-family="Helvetica,sans-Serif" font-size="10.00">upload output</text>
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+<text xml:space="preserve" text-anchor="middle" x="384" y="-23.95" font-family="Helvetica,sans-Serif" font-size="14.00">input videos</text>
+</g>
+<!-- minio&#45;&gt;bucket_in -->
+<g id="edge14" class="edge">
+<title>minio&#45;&gt;bucket_in</title>
+<path fill="none" stroke="black" stroke-dasharray="1,5" d="M392.19,-128.27C392.19,-106.66 392.19,-78.11 392.19,-58.79"/>
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+<!-- minio&#45;&gt;bucket_out -->
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+<title>minio&#45;&gt;bucket_out</title>
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docs/architecture/01b-aws-architecture.dot

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+digraph aws_architecture {
+    rankdir=TB
+    node [shape=box, style=rounded, fontname="Helvetica"]
+    edge [fontname="Helvetica", fontsize=10]
+
+    labelloc="t"
+    label="MPR - AWS Architecture (Lambda + Step Functions)"
+    fontsize=16
+    fontname="Helvetica-Bold"
+
+    graph [splines=ortho, nodesep=0.8, ranksep=0.8]
+
+    // External
+    subgraph cluster_external {
+        label="External"
+        style=dashed
+        color=gray
+
+        browser [label="Browser\nmpr.mcrn.ar", shape=ellipse]
+    }
+
+    // Nginx reverse proxy
+    subgraph cluster_proxy {
+        label="Reverse Proxy"
+        style=filled
+        fillcolor="#e8f4f8"
+
+        nginx [label="nginx\nport 80"]
+    }
+
+    // Application layer
+    subgraph cluster_apps {
+        label="Application Layer"
+        style=filled
+        fillcolor="#f0f8e8"
+
+        django [label="Django Admin\n/admin\nport 8701"]
+        fastapi [label="GraphQL API\n/graphql\nport 8702"]
+        timeline [label="Timeline UI\n/\nport 5173"]
+    }
+
+    // Data layer (still local)
+    subgraph cluster_data {
+        label="Data Layer"
+        style=filled
+        fillcolor="#f8e8f0"
+
+        postgres [label="PostgreSQL\nport 5436", shape=cylinder]
+    }
+
+    // AWS layer
+    subgraph cluster_aws {
+        label="AWS Cloud"
+        style=filled
+        fillcolor="#fde8d0"
+
+        step_functions [label="Step Functions\nOrchestration\nstate machine"]
+        lambda [label="Lambda Function\nFFmpeg container\ntranscoding"]
+        s3 [label="S3 Buckets", shape=folder]
+        bucket_in [label="mpr-media-in/\ninput videos", shape=note]
+        bucket_out [label="mpr-media-out/\ntranscoded output", shape=note]
+    }
+
+    // Connections
+    browser -> nginx [label="HTTP"]
+
+    nginx -> django [xlabel="/admin"]
+    nginx -> fastapi [xlabel="/graphql"]
+    nginx -> timeline [xlabel="/"]
+
+    timeline -> fastapi [label="GraphQL"]
+    django -> postgres
+
+    fastapi -> postgres [label="read/write jobs"]
+    fastapi -> step_functions [label="boto3\nstart_execution()\nexecution_arn"]
+
+    step_functions -> lambda [label="invoke with\njob parameters"]
+    lambda -> s3 [label="download input\nupload output"]
+    lambda -> fastapi [label="POST /jobs/{id}/callback\nupdate status"]
+
+    fastapi -> postgres [label="callback updates\njob status"]
+
+    s3 -> bucket_in [style=dotted, arrowhead=none]
+    s3 -> bucket_out [style=dotted, arrowhead=none]
+}

docs/architecture/01b-aws-architecture.svg

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+<g id="node1" class="node">
+<title>browser</title>
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+</g>
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+<title>nginx</title>
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+<text xml:space="preserve" text-anchor="middle" x="235" y="-822.45" font-family="Helvetica,sans-Serif" font-size="14.00">port 80</text>
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+<text xml:space="preserve" text-anchor="middle" x="73" y="-689.2" font-family="Helvetica,sans-Serif" font-size="14.00">port 8701</text>
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+<title>nginx&#45;&gt;django</title>
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+<title>fastapi</title>
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+<text xml:space="preserve" text-anchor="middle" x="230" y="-558.7" font-family="Helvetica,sans-Serif" font-size="14.00">port 8702</text>
+</g>
+<!-- nginx&#45;&gt;fastapi -->
+<g id="edge3" class="edge">
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+<!-- timeline -->
+<g id="node5" class="node">
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+<text xml:space="preserve" text-anchor="middle" x="235" y="-723.7" font-family="Helvetica,sans-Serif" font-size="14.00">Timeline UI</text>
+<text xml:space="preserve" text-anchor="middle" x="235" y="-706.45" font-family="Helvetica,sans-Serif" font-size="14.00">/</text>
+<text xml:space="preserve" text-anchor="middle" x="235" y="-689.2" font-family="Helvetica,sans-Serif" font-size="14.00">port 5173</text>
+</g>
+<!-- nginx&#45;&gt;timeline -->
+<g id="edge4" class="edge">
+<title>nginx&#45;&gt;timeline</title>
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+<polygon fill="black" stroke="black" points="238.5,-752.97 235,-742.97 231.5,-752.97 238.5,-752.97"/>
+<text xml:space="preserve" text-anchor="middle" x="233.5" y="-786.75" font-family="Helvetica,sans-Serif" font-size="10.00">/</text>
+</g>
+<!-- postgres -->
+<g id="node6" class="node">
+<title>postgres</title>
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+<text xml:space="preserve" text-anchor="middle" x="84" y="-414.07" font-family="Helvetica,sans-Serif" font-size="14.00">PostgreSQL</text>
+<text xml:space="preserve" text-anchor="middle" x="84" y="-396.82" font-family="Helvetica,sans-Serif" font-size="14.00">port 5436</text>
+</g>
+<!-- django&#45;&gt;postgres -->
+<g id="edge6" class="edge">
+<title>django&#45;&gt;postgres</title>
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+<!-- fastapi&#45;&gt;postgres -->
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+</g>
+<!-- fastapi&#45;&gt;postgres -->
+<g id="edge12" class="edge">
+<title>fastapi&#45;&gt;postgres</title>
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+<text xml:space="preserve" text-anchor="middle" x="125.25" y="-493.12" font-family="Helvetica,sans-Serif" font-size="10.00">job status</text>
+</g>
+<!-- step_functions -->
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+</g>
+<!-- fastapi&#45;&gt;step_functions -->
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+<!-- timeline&#45;&gt;fastapi -->
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+</g>
+<!-- lambda&#45;&gt;fastapi -->
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+<text xml:space="preserve" text-anchor="middle" x="427" y="-130.82" font-family="Helvetica,sans-Serif" font-size="14.00">S3 Buckets</text>
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+<!-- lambda&#45;&gt;s3 -->
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+<!-- s3&#45;&gt;bucket_in -->
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+<title>s3&#45;&gt;bucket_in</title>
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docs/architecture/01c-gcp-architecture.dot

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+digraph gcp_architecture {
+    rankdir=TB
+    node [shape=box, style=rounded, fontname="Helvetica"]
+    edge [fontname="Helvetica", fontsize=10]
+
+    labelloc="t"
+    label="MPR - GCP Architecture (Cloud Run Jobs + GCS)"
+    fontsize=16
+    fontname="Helvetica-Bold"
+
+    graph [splines=ortho, nodesep=0.8, ranksep=0.8]
+
+    // External
+    subgraph cluster_external {
+        label="External"
+        style=dashed
+        color=gray
+
+        browser [label="Browser\nmpr.mcrn.ar", shape=ellipse]
+    }
+
+    // Nginx reverse proxy
+    subgraph cluster_proxy {
+        label="Reverse Proxy"
+        style=filled
+        fillcolor="#e8f4f8"
+
+        nginx [label="nginx\nport 80"]
+    }
+
+    // Application layer
+    subgraph cluster_apps {
+        label="Application Layer"
+        style=filled
+        fillcolor="#f0f8e8"
+
+        django [label="Django Admin\n/admin\nport 8701"]
+        fastapi [label="GraphQL API\n/graphql\nport 8702"]
+        timeline [label="Timeline UI\n/\nport 5173"]
+    }
+
+    // Data layer (still local)
+    subgraph cluster_data {
+        label="Data Layer"
+        style=filled
+        fillcolor="#f8e8f0"
+
+        postgres [label="PostgreSQL\nport 5436", shape=cylinder]
+    }
+
+    // GCP layer
+    subgraph cluster_gcp {
+        label="Google Cloud"
+        style=filled
+        fillcolor="#e8f0fd"
+
+        cloud_run_job [label="Cloud Run Job\nFFmpeg container\ntranscoding"]
+        gcs [label="GCS Buckets\n(S3-compat API)", shape=folder]
+        bucket_in [label="mpr-media-in/\ninput videos", shape=note]
+        bucket_out [label="mpr-media-out/\ntranscoded output", shape=note]
+    }
+
+    // Connections
+    browser -> nginx [label="HTTP"]
+
+    nginx -> django [xlabel="/admin"]
+    nginx -> fastapi [xlabel="/graphql"]
+    nginx -> timeline [xlabel="/"]
+
+    timeline -> fastapi [label="GraphQL"]
+    django -> postgres
+
+    fastapi -> postgres [label="read/write jobs"]
+    fastapi -> cloud_run_job [label="google-cloud-run\nrun_job() + payload\nexecution_name"]
+
+    cloud_run_job -> gcs [label="S3 compat (HMAC)\ndownload input\nupload output"]
+    cloud_run_job -> fastapi [label="POST /jobs/{id}/callback\nupdate status"]
+
+    fastapi -> postgres [label="callback updates\njob status"]
+
+    gcs -> bucket_in [style=dotted, arrowhead=none]
+    gcs -> bucket_out [style=dotted, arrowhead=none]
+}

docs/architecture/01c-gcp-architecture.svg

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+</g>
+<!-- browser -->
+<g id="node1" class="node">
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+<g id="edge2" class="edge">
+<title>nginx&#45;&gt;django</title>
+<path fill="none" stroke="black" d="M201.04,-719C153.54,-719 73,-719 73,-719 73,-719 73,-628.89 73,-628.89"/>
+<polygon fill="black" stroke="black" points="76.5,-628.89 73,-618.89 69.5,-628.89 76.5,-628.89"/>
+<text xml:space="preserve" text-anchor="middle" x="75.09" y="-722.25" font-family="Helvetica,sans-Serif" font-size="10.00">/admin</text>
+</g>
+<!-- fastapi -->
+<g id="node4" class="node">
+<title>fastapi</title>
+<path fill="none" stroke="black" d="M270.25,-486.5C270.25,-486.5 189.75,-486.5 189.75,-486.5 183.75,-486.5 177.75,-480.5 177.75,-474.5 177.75,-474.5 177.75,-438.75 177.75,-438.75 177.75,-432.75 183.75,-426.75 189.75,-426.75 189.75,-426.75 270.25,-426.75 270.25,-426.75 276.25,-426.75 282.25,-432.75 282.25,-438.75 282.25,-438.75 282.25,-474.5 282.25,-474.5 282.25,-480.5 276.25,-486.5 270.25,-486.5"/>
+<text xml:space="preserve" text-anchor="middle" x="230" y="-469.2" font-family="Helvetica,sans-Serif" font-size="14.00">GraphQL API</text>
+<text xml:space="preserve" text-anchor="middle" x="230" y="-451.95" font-family="Helvetica,sans-Serif" font-size="14.00">/graphql</text>
+<text xml:space="preserve" text-anchor="middle" x="230" y="-434.7" font-family="Helvetica,sans-Serif" font-size="14.00">port 8702</text>
+</g>
+<!-- nginx&#45;&gt;fastapi -->
+<g id="edge3" class="edge">
+<title>nginx&#45;&gt;fastapi</title>
+<path fill="none" stroke="black" d="M201.11,-705C191.15,-705 182.88,-705 182.88,-705 182.88,-705 182.88,-498.1 182.88,-498.1"/>
+<polygon fill="black" stroke="black" points="186.38,-498.1 182.88,-488.1 179.38,-498.1 186.38,-498.1"/>
+<text xml:space="preserve" text-anchor="middle" x="163" y="-613.91" font-family="Helvetica,sans-Serif" font-size="10.00">/graphql</text>
+</g>
+<!-- timeline -->
+<g id="node5" class="node">
+<title>timeline</title>
+<path fill="none" stroke="black" d="M270,-617C270,-617 200,-617 200,-617 194,-617 188,-611 188,-605 188,-605 188,-569.25 188,-569.25 188,-563.25 194,-557.25 200,-557.25 200,-557.25 270,-557.25 270,-557.25 276,-557.25 282,-563.25 282,-569.25 282,-569.25 282,-605 282,-605 282,-611 276,-617 270,-617"/>
+<text xml:space="preserve" text-anchor="middle" x="235" y="-599.7" font-family="Helvetica,sans-Serif" font-size="14.00">Timeline UI</text>
+<text xml:space="preserve" text-anchor="middle" x="235" y="-582.45" font-family="Helvetica,sans-Serif" font-size="14.00">/</text>
+<text xml:space="preserve" text-anchor="middle" x="235" y="-565.2" font-family="Helvetica,sans-Serif" font-size="14.00">port 5173</text>
+</g>
+<!-- nginx&#45;&gt;timeline -->
+<g id="edge4" class="edge">
+<title>nginx&#45;&gt;timeline</title>
+<path fill="none" stroke="black" d="M235,-690.04C235,-690.04 235,-628.97 235,-628.97"/>
+<polygon fill="black" stroke="black" points="238.5,-628.97 235,-618.97 231.5,-628.97 238.5,-628.97"/>
+<text xml:space="preserve" text-anchor="middle" x="233.5" y="-662.75" font-family="Helvetica,sans-Serif" font-size="10.00">/</text>
+</g>
+<!-- postgres -->
+<g id="node6" class="node">
+<title>postgres</title>
+<path fill="none" stroke="black" d="M131.75,-310.03C131.75,-312.96 110.35,-315.34 84,-315.34 57.65,-315.34 36.25,-312.96 36.25,-310.03 36.25,-310.03 36.25,-262.22 36.25,-262.22 36.25,-259.29 57.65,-256.91 84,-256.91 110.35,-256.91 131.75,-259.29 131.75,-262.22 131.75,-262.22 131.75,-310.03 131.75,-310.03"/>
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+<text xml:space="preserve" text-anchor="middle" x="84" y="-290.07" font-family="Helvetica,sans-Serif" font-size="14.00">PostgreSQL</text>
+<text xml:space="preserve" text-anchor="middle" x="84" y="-272.82" font-family="Helvetica,sans-Serif" font-size="14.00">port 5436</text>
+</g>
+<!-- django&#45;&gt;postgres -->
+<g id="edge6" class="edge">
+<title>django&#45;&gt;postgres</title>
+<path fill="none" stroke="black" d="M59.62,-556.89C59.62,-556.89 59.62,-326.97 59.62,-326.97"/>
+<polygon fill="black" stroke="black" points="63.13,-326.97 59.63,-316.97 56.13,-326.97 63.13,-326.97"/>
+</g>
+<!-- fastapi&#45;&gt;postgres -->
+<g id="edge7" class="edge">
+<title>fastapi&#45;&gt;postgres</title>
+<path fill="none" stroke="black" d="M177.34,-467C135.16,-467 83,-467 83,-467 83,-467 83,-327.1 83,-327.1"/>
+<polygon fill="black" stroke="black" points="86.5,-327.1 83,-317.1 79.5,-327.1 86.5,-327.1"/>
+<text xml:space="preserve" text-anchor="middle" x="266.38" y="-375.5" font-family="Helvetica,sans-Serif" font-size="10.00">read/write jobs</text>
+</g>
+<!-- fastapi&#45;&gt;postgres -->
+<g id="edge11" class="edge">
+<title>fastapi&#45;&gt;postgres</title>
+<path fill="none" stroke="black" d="M177.57,-447C143.88,-447 106.38,-447 106.38,-447 106.38,-447 106.38,-327.15 106.38,-327.15"/>
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+<text xml:space="preserve" text-anchor="middle" x="125.25" y="-381.88" font-family="Helvetica,sans-Serif" font-size="10.00">callback updates</text>
+<text xml:space="preserve" text-anchor="middle" x="125.25" y="-369.12" font-family="Helvetica,sans-Serif" font-size="10.00">job status</text>
+</g>
+<!-- cloud_run_job -->
+<g id="node7" class="node">
+<title>cloud_run_job</title>
+<path fill="none" stroke="black" d="M505,-316C505,-316 387,-316 387,-316 381,-316 375,-310 375,-304 375,-304 375,-268.25 375,-268.25 375,-262.25 381,-256.25 387,-256.25 387,-256.25 505,-256.25 505,-256.25 511,-256.25 517,-262.25 517,-268.25 517,-268.25 517,-304 517,-304 517,-310 511,-316 505,-316"/>
+<text xml:space="preserve" text-anchor="middle" x="446" y="-298.7" font-family="Helvetica,sans-Serif" font-size="14.00">Cloud Run Job</text>
+<text xml:space="preserve" text-anchor="middle" x="446" y="-281.45" font-family="Helvetica,sans-Serif" font-size="14.00">FFmpeg container</text>
+<text xml:space="preserve" text-anchor="middle" x="446" y="-264.2" font-family="Helvetica,sans-Serif" font-size="14.00">transcoding</text>
+</g>
+<!-- fastapi&#45;&gt;cloud_run_job -->
+<g id="edge8" class="edge">
+<title>fastapi&#45;&gt;cloud_run_job</title>
+<path fill="none" stroke="black" d="M247.42,-426.41C247.42,-379.88 247.42,-296 247.42,-296 247.42,-296 363.07,-296 363.07,-296"/>
+<polygon fill="black" stroke="black" points="363.07,-299.5 373.07,-296 363.07,-292.5 363.07,-299.5"/>
+<text xml:space="preserve" text-anchor="middle" x="414.38" y="-388.25" font-family="Helvetica,sans-Serif" font-size="10.00">google&#45;cloud&#45;run</text>
+<text xml:space="preserve" text-anchor="middle" x="414.38" y="-375.5" font-family="Helvetica,sans-Serif" font-size="10.00">run_job() + payload</text>
+<text xml:space="preserve" text-anchor="middle" x="414.38" y="-362.75" font-family="Helvetica,sans-Serif" font-size="10.00">execution_name</text>
+</g>
+<!-- timeline&#45;&gt;fastapi -->
+<g id="edge5" class="edge">
+<title>timeline&#45;&gt;fastapi</title>
+<path fill="none" stroke="black" d="M235,-556.86C235,-556.86 235,-498.24 235,-498.24"/>
+<polygon fill="black" stroke="black" points="238.5,-498.24 235,-488.24 231.5,-498.24 238.5,-498.24"/>
+<text xml:space="preserve" text-anchor="middle" x="253" y="-518.75" font-family="Helvetica,sans-Serif" font-size="10.00">GraphQL</text>
+</g>
+<!-- cloud_run_job&#45;&gt;fastapi -->
+<g id="edge10" class="edge">
+<title>cloud_run_job&#45;&gt;fastapi</title>
+<path fill="none" stroke="black" d="M374.7,-276C306.06,-276 212.58,-276 212.58,-276 212.58,-276 212.58,-414.88 212.58,-414.88"/>
+<polygon fill="black" stroke="black" points="209.08,-414.88 212.58,-424.88 216.08,-414.88 209.08,-414.88"/>
+<text xml:space="preserve" text-anchor="middle" x="585.62" y="-381.88" font-family="Helvetica,sans-Serif" font-size="10.00">POST /jobs/{id}/callback</text>
+<text xml:space="preserve" text-anchor="middle" x="585.62" y="-369.12" font-family="Helvetica,sans-Serif" font-size="10.00">update status</text>
+</g>
+<!-- gcs -->
+<g id="node8" class="node">
+<title>gcs</title>
+<polygon fill="none" stroke="black" points="510.25,-160 507.25,-164 486.25,-164 483.25,-160 381.75,-160 381.75,-117.5 510.25,-117.5 510.25,-160"/>
+<text xml:space="preserve" text-anchor="middle" x="446" y="-142.7" font-family="Helvetica,sans-Serif" font-size="14.00">GCS Buckets</text>
+<text xml:space="preserve" text-anchor="middle" x="446" y="-125.45" font-family="Helvetica,sans-Serif" font-size="14.00">(S3&#45;compat API)</text>
+</g>
+<!-- cloud_run_job&#45;&gt;gcs -->
+<g id="edge9" class="edge">
+<title>cloud_run_job&#45;&gt;gcs</title>
+<path fill="none" stroke="black" d="M446,-255.95C446,-255.95 446,-171.81 446,-171.81"/>
+<polygon fill="black" stroke="black" points="449.5,-171.81 446,-161.81 442.5,-171.81 449.5,-171.81"/>
+<text xml:space="preserve" text-anchor="middle" x="492.12" y="-217.75" font-family="Helvetica,sans-Serif" font-size="10.00">S3 compat (HMAC)</text>
+<text xml:space="preserve" text-anchor="middle" x="492.12" y="-205" font-family="Helvetica,sans-Serif" font-size="10.00">download input</text>
+<text xml:space="preserve" text-anchor="middle" x="492.12" y="-192.25" font-family="Helvetica,sans-Serif" font-size="10.00">upload output</text>
+</g>
+<!-- bucket_in -->
+<g id="node9" class="node">
+<title>bucket_in</title>
+<polygon fill="none" stroke="black" points="414.75,-58.5 307.25,-58.5 307.25,-16 420.75,-16 420.75,-52.5 414.75,-58.5"/>
+<polyline fill="none" stroke="black" points="414.75,-58.5 414.75,-52.5"/>
+<polyline fill="none" stroke="black" points="420.75,-52.5 414.75,-52.5"/>
+<text xml:space="preserve" text-anchor="middle" x="364" y="-41.2" font-family="Helvetica,sans-Serif" font-size="14.00">mpr&#45;media&#45;in/</text>
+<text xml:space="preserve" text-anchor="middle" x="364" y="-23.95" font-family="Helvetica,sans-Serif" font-size="14.00">input videos</text>
+</g>
+<!-- gcs&#45;&gt;bucket_in -->
+<g id="edge12" class="edge">
+<title>gcs&#45;&gt;bucket_in</title>
+<path fill="none" stroke="black" stroke-dasharray="1,5" d="M401.25,-117.22C401.25,-100 401.25,-75.96 401.25,-58.74"/>
+</g>
+<!-- bucket_out -->
+<g id="node10" class="node">
+<title>bucket_out</title>
+<polygon fill="none" stroke="black" points="617.12,-58.5 478.88,-58.5 478.88,-16 623.12,-16 623.12,-52.5 617.12,-58.5"/>
+<polyline fill="none" stroke="black" points="617.12,-58.5 617.12,-52.5"/>
+<polyline fill="none" stroke="black" points="623.12,-52.5 617.12,-52.5"/>
+<text xml:space="preserve" text-anchor="middle" x="551" y="-41.2" font-family="Helvetica,sans-Serif" font-size="14.00">mpr&#45;media&#45;out/</text>
+<text xml:space="preserve" text-anchor="middle" x="551" y="-23.95" font-family="Helvetica,sans-Serif" font-size="14.00">transcoded output</text>
+</g>
+<!-- gcs&#45;&gt;bucket_out -->
+<g id="edge13" class="edge">
+<title>gcs&#45;&gt;bucket_out</title>
+<path fill="none" stroke="black" stroke-dasharray="1,5" d="M494.56,-117.22C494.56,-100 494.56,-75.96 494.56,-58.74"/>
+</g>
+</g>
+</svg>

docs/architecture/04-media-storage.md

@@ -68,9 +68,50 @@ aws s3 cp video.mp4 s3://mpr-media-in/
 aws s3 sync /local/media/ s3://mpr-media-in/
 ```
 
+## GCP Production (GCS via S3 compatibility)
+
+GCS exposes an S3-compatible API. The same `core/storage/s3.py` boto3 code works
+with no changes — only the endpoint and credentials differ.
+
+### GCS HMAC Keys
+Generate under **Cloud Storage → Settings → Interoperability** in the GCP console.
+These act as `AWS_ACCESS_KEY_ID` / `AWS_SECRET_ACCESS_KEY`.
+
+### Configuration
+```bash
+S3_ENDPOINT_URL=https://storage.googleapis.com
+S3_BUCKET_IN=mpr-media-in
+S3_BUCKET_OUT=mpr-media-out
+AWS_ACCESS_KEY_ID=<GCS HMAC access key>
+AWS_SECRET_ACCESS_KEY=<GCS HMAC secret>
+
+# Executor
+MPR_EXECUTOR=gcp
+GCP_PROJECT_ID=my-project
+GCP_REGION=us-central1
+CLOUD_RUN_JOB=mpr-transcode
+CALLBACK_URL=https://mpr.mcrn.ar/api
+CALLBACK_API_KEY=<secret>
+```
+
+### Upload Files to GCS
+```bash
+gcloud storage cp video.mp4 gs://mpr-media-in/
+
+# Or with the aws CLI via compat endpoint
+aws --endpoint-url https://storage.googleapis.com s3 cp video.mp4 s3://mpr-media-in/
+```
+
+### Cloud Run Job Handler
+`core/task/gcp_handler.py` is the Cloud Run Job entrypoint. It reads the job payload
+from `MPR_JOB_PAYLOAD` (injected by `GCPExecutor`), uses `core/storage` for all
+GCS access (S3 compat), and POSTs the completion callback to the API.
+
+Set the Cloud Run Job command to: `python -m core.task.gcp_handler`
+
 ## Storage Module
 
-`core/storage.py` provides all S3 operations:
+`core/storage/` package provides all S3 operations:
 
 ```python
 from core.storage import (
@@ -114,7 +155,14 @@ mutation { scanMediaFolder { found registered skipped files } }
 4. Uploads result to `S3_BUCKET_OUT`
 5. Calls back to API with result
 
-Both paths use the same S3 buckets and key structure.
+### Cloud Run Job Mode (GCP)
+1. `GCPExecutor` triggers Cloud Run Job with payload in `MPR_JOB_PAYLOAD`
+2. `core/task/gcp_handler.py` downloads source from `S3_BUCKET_IN` (GCS S3 compat)
+3. Runs FFmpeg in container
+4. Uploads result to `S3_BUCKET_OUT` (GCS S3 compat)
+5. Calls back to API with result
+
+All three paths use the same S3-compatible bucket names and key structure.
 
 ## Supported File Types
 

docs/architecture/index.html

@@ -17,16 +17,32 @@
             <a href="#overview">System Overview</a>
             <a href="#data-model">Data Model</a>
             <a href="#job-flow">Job Flow</a>
+            <a href="#media-storage">Media Storage</a>
         </nav>
 
         <h2 id="overview">System Overview</h2>
         <div class="diagram-container">
             <div class="diagram">
-                <h3>Architecture</h3>
+                <h3>Local Architecture (Development)</h3>
-                <object type="image/svg+xml" data="01-system-overview.svg">
+                <object type="image/svg+xml" data="01a-local-architecture.svg">
-                    <img src="01-system-overview.svg" alt="System Overview" />
+                    <img
+                        src="01a-local-architecture.svg"
+                        alt="Local Architecture"
+                    />
                 </object>
-                <a href="01-system-overview.svg" target="_blank"
+                <a href="01a-local-architecture.svg" target="_blank"
+                    >Open full size</a
+                >
+            </div>
+            <div class="diagram">
+                <h3>AWS Architecture (Production)</h3>
+                <object type="image/svg+xml" data="01b-aws-architecture.svg">
+                    <img
+                        src="01b-aws-architecture.svg"
+                        alt="AWS Architecture"
+                    />
+                </object>
+                <a href="01b-aws-architecture.svg" target="_blank"
                     >Open full size</a
                 >
             </div>
@@ -41,8 +57,7 @@
                 </li>
                 <li>
                     <span class="color-box" style="background: #f0f8e8"></span>
-                    Application Layer (Django Admin, FastAPI + GraphQL, Timeline
+                    Application Layer (Django Admin, GraphQL API, Timeline UI)
-                    UI)
                 </li>
                 <li>
                     <span class="color-box" style="background: #fff8e8"></span>
@@ -141,24 +156,44 @@
             </ul>
         </div>
 
-        <h2>API Interfaces</h2>
+        <h2 id="media-storage">Media Storage</h2>
-        <pre><code># REST API
+        <div class="diagram-container">
-http://mpr.local.ar/api/docs     - Swagger UI
+            <p>
-POST /api/assets/scan             - Scan S3 bucket for media
+                MPR separates media into input and output paths for flexible
-POST /api/jobs/                   - Create transcode job
+                storage configuration.
-POST /api/jobs/{id}/callback      - Lambda completion callback
+            </p>
+            <p>
+                <a href="04-media-storage.md" target="_blank"
+                    >View Media Storage Documentation →</a
+                >
+            </p>
+        </div>
 
-# GraphQL (GraphiQL)
+        <h2>API (GraphQL)</h2>
-http://mpr.local.ar/graphql       - GraphiQL IDE
+        <pre><code># GraphiQL IDE
-query { assets { id filename } }
+http://mpr.local.ar/graphql
-mutation { createJob(input: {...}) { id status } }
+
-mutation { scanMediaFolder { found registered } }</code></pre>
+# Queries
+query { assets(status: "ready") { id filename duration } }
+query { jobs(status: "processing") { id status progress } }
+query { presets { id name container videoCodec } }
+query { systemStatus { status version } }
+
+# Mutations
+mutation { scanMediaFolder { found registered skipped } }
+mutation { createJob(input: { sourceAssetId: "...", presetId: "..." }) { id status } }
+mutation { cancelJob(id: "...") { id status } }
+mutation { retryJob(id: "...") { id status } }
+mutation { updateAsset(id: "...", input: { comments: "..." }) { id comments } }
+mutation { deleteAsset(id: "...") { ok } }
+
+# Lambda callback (REST)
+POST /api/jobs/{id}/callback      - Lambda completion webhook</code></pre>
 
         <h2>Access Points</h2>
         <pre><code># Local development
 127.0.0.1 mpr.local.ar
 http://mpr.local.ar/admin         - Django Admin
-http://mpr.local.ar/api/docs      - FastAPI Swagger
 http://mpr.local.ar/graphql       - GraphiQL
 http://mpr.local.ar/              - Timeline UI
 http://localhost:9001              - MinIO Console

docs/index.html

@@ -0,0 +1,279 @@
+<!doctype html>
+<html lang="en">
+    <head>
+        <meta charset="UTF-8" />
+        <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+        <title>MPR - Architecture</title>
+        <link rel="stylesheet" href="architecture/styles.css" />
+    </head>
+    <body>
+        <h1>MPR - Media Processor</h1>
+        <p>
+            Media transcoding platform with three execution modes: local (Celery
+            + MinIO), AWS (Step Functions + Lambda + S3), and GCP (Cloud Run
+            Jobs + GCS). Storage is S3-compatible across all environments.
+        </p>
+
+        <nav>
+            <a href="#overview">System Overview</a>
+            <a href="#data-model">Data Model</a>
+            <a href="#job-flow">Job Flow</a>
+            <a href="#media-storage">Media Storage</a>
+        </nav>
+
+        <h2 id="overview">System Overview</h2>
+        <div class="diagram-container">
+            <div class="diagram">
+                <h3>Local Architecture (Development)</h3>
+                <object
+                    type="image/svg+xml"
+                    data="architecture/01a-local-architecture.svg"
+                >
+                    <img
+                        src="architecture/01a-local-architecture.svg"
+                        alt="Local Architecture"
+                    />
+                </object>
+                <a
+                    href="architecture/01a-local-architecture.svg"
+                    target="_blank"
+                    >Open full size</a
+                >
+            </div>
+            <div class="diagram">
+                <h3>AWS Architecture (Production)</h3>
+                <object
+                    type="image/svg+xml"
+                    data="architecture/01b-aws-architecture.svg"
+                >
+                    <img
+                        src="architecture/01b-aws-architecture.svg"
+                        alt="AWS Architecture"
+                    />
+                </object>
+                <a href="architecture/01b-aws-architecture.svg" target="_blank"
+                    >Open full size</a
+                >
+            </div>
+            <div class="diagram">
+                <h3>GCP Architecture (Production)</h3>
+                <object
+                    type="image/svg+xml"
+                    data="architecture/01c-gcp-architecture.svg"
+                >
+                    <img
+                        src="architecture/01c-gcp-architecture.svg"
+                        alt="GCP Architecture"
+                    />
+                </object>
+                <a href="architecture/01c-gcp-architecture.svg" target="_blank"
+                    >Open full size</a
+                >
+            </div>
+        </div>
+
+        <div class="legend">
+            <h3>Components</h3>
+            <ul>
+                <li>
+                    <span class="color-box" style="background: #e8f4f8"></span>
+                    Reverse Proxy (nginx)
+                </li>
+                <li>
+                    <span class="color-box" style="background: #f0f8e8"></span>
+                    Application Layer (Django Admin, GraphQL API, Timeline UI)
+                </li>
+                <li>
+                    <span class="color-box" style="background: #fff8e8"></span>
+                    Worker Layer (Celery local mode)
+                </li>
+                <li>
+                    <span class="color-box" style="background: #fde8d0"></span>
+                    AWS (Step Functions, Lambda)
+                </li>
+                <li>
+                    <span class="color-box" style="background: #e8f0fd"></span>
+                    GCP (Cloud Run Jobs + GCS)
+                </li>
+                <li>
+                    <span class="color-box" style="background: #f8e8f0"></span>
+                    Data Layer (PostgreSQL, Redis)
+                </li>
+                <li>
+                    <span class="color-box" style="background: #f0f0f0"></span>
+                    S3-compatible Storage (MinIO / AWS S3 / GCS)
+                </li>
+            </ul>
+        </div>
+
+        <h2 id="data-model">Data Model</h2>
+        <div class="diagram-container">
+            <div class="diagram">
+                <h3>Entity Relationships</h3>
+                <object
+                    type="image/svg+xml"
+                    data="architecture/02-data-model.svg"
+                >
+                    <img
+                        src="architecture/02-data-model.svg"
+                        alt="Data Model"
+                    />
+                </object>
+                <a href="architecture/02-data-model.svg" target="_blank"
+                    >Open full size</a
+                >
+            </div>
+        </div>
+
+        <div class="legend">
+            <h3>Entities</h3>
+            <ul>
+                <li>
+                    <span class="color-box" style="background: #4a90d9"></span>
+                    MediaAsset - Video/audio files with metadata
+                </li>
+                <li>
+                    <span class="color-box" style="background: #50b050"></span>
+                    TranscodePreset - Encoding configurations
+                </li>
+                <li>
+                    <span class="color-box" style="background: #d9534f"></span>
+                    TranscodeJob - Processing queue items
+                </li>
+            </ul>
+        </div>
+
+        <h2 id="job-flow">Job Flow</h2>
+        <div class="diagram-container">
+            <div class="diagram">
+                <h3>Job Lifecycle</h3>
+                <object
+                    type="image/svg+xml"
+                    data="architecture/03-job-flow.svg"
+                >
+                    <img src="architecture/03-job-flow.svg" alt="Job Flow" />
+                </object>
+                <a href="architecture/03-job-flow.svg" target="_blank"
+                    >Open full size</a
+                >
+            </div>
+        </div>
+
+        <div class="legend">
+            <h3>Job States</h3>
+            <ul>
+                <li>
+                    <span class="color-box" style="background: #ffc107"></span>
+                    PENDING - Waiting in queue
+                </li>
+                <li>
+                    <span class="color-box" style="background: #17a2b8"></span>
+                    PROCESSING - Worker executing
+                </li>
+                <li>
+                    <span class="color-box" style="background: #28a745"></span>
+                    COMPLETED - Success
+                </li>
+                <li>
+                    <span class="color-box" style="background: #dc3545"></span>
+                    FAILED - Error occurred
+                </li>
+                <li>
+                    <span class="color-box" style="background: #6c757d"></span>
+                    CANCELLED - User cancelled
+                </li>
+            </ul>
+        </div>
+
+        <h2 id="media-storage">Media Storage</h2>
+        <div class="diagram-container">
+            <p>
+                MPR separates media into <strong>input</strong> and
+                <strong>output</strong> paths, each independently configurable.
+                File paths are stored
+                <strong>relative to their respective root</strong> to ensure
+                portability between local development and cloud deployments (AWS
+                S3, etc.).
+            </p>
+        </div>
+
+        <div class="legend">
+            <h3>Input / Output Separation</h3>
+            <ul>
+                <li>
+                    <span class="color-box" style="background: #4a90d9"></span>
+                    <code>MEDIA_IN</code> - Source media files to process
+                </li>
+                <li>
+                    <span class="color-box" style="background: #50b050"></span>
+                    <code>MEDIA_OUT</code> - Transcoded/trimmed output files
+                </li>
+            </ul>
+            <p><strong>Why Relative Paths?</strong></p>
+            <ul>
+                <li>Portability: Same database works locally and in cloud</li>
+                <li>Flexibility: Easy to switch between storage backends</li>
+                <li>Simplicity: No need to update paths when migrating</li>
+            </ul>
+        </div>
+
+        <div class="legend">
+            <h3>Local Development</h3>
+            <pre><code>MEDIA_IN=/app/media/in
+MEDIA_OUT=/app/media/out
+
+/app/media/
+├── in/                    # Source files
+│   ├── video1.mp4
+│   └── subfolder/video3.mp4
+└── out/                   # Transcoded output
+    └── video1_h264.mp4</code></pre>
+        </div>
+
+        <div class="legend">
+            <h3>AWS/Cloud Deployment</h3>
+            <pre><code>MEDIA_IN=s3://source-bucket/media/
+MEDIA_OUT=s3://output-bucket/transcoded/
+MEDIA_BASE_URL=https://source-bucket.s3.amazonaws.com/media/</code></pre>
+            <p>
+                Database paths remain unchanged (already relative). Just upload
+                files to S3 and update environment variables.
+            </p>
+        </div>
+
+        <div class="legend">
+            <h3>API (GraphQL)</h3>
+            <p>
+                All client interactions go through GraphQL at
+                <code>/graphql</code>.
+            </p>
+            <ul>
+                <li>
+                    <code>scanMediaFolder</code> - Scan S3 bucket for media
+                    files
+                </li>
+                <li><code>createJob</code> - Create transcode/trim job</li>
+                <li>
+                    <code>cancelJob / retryJob</code> - Job lifecycle management
+                </li>
+                <li>
+                    <code>updateAsset / deleteAsset</code> - Asset management
+                </li>
+            </ul>
+            <p><strong>Supported File Types:</strong></p>
+            <p>
+                Video: mp4, mkv, avi, mov, webm, flv, wmv, m4v<br />
+                Audio: mp3, wav, flac, aac, ogg, m4a
+            </p>
+        </div>
+
+        <h2>Access Points</h2>
+        <pre><code># Add to /etc/hosts
+127.0.0.1 mpr.local.ar
+
+# URLs
+http://mpr.local.ar/admin    - Django Admin
+http://mpr.local.ar/graphql  - GraphiQL IDE
+http://mpr.local.ar/         - Timeline UI</code></pre>
+    </body>
+</html>

docs/media-storage.html

@@ -0,0 +1,125 @@
+<h1>Media Storage Architecture</h1>
+<h2>Overview</h2>
+<p>MPR separates media into <strong>input</strong> and <strong>output</strong> paths, each independently configurable. File paths are stored <strong>relative to their respective root</strong> to ensure portability between local development and cloud deployments (AWS S3, etc.).</p>
+<h2>Storage Strategy</h2>
+<h3>Input / Output Separation</h3>
+<p>| Path | Env Var | Purpose |
+|------|---------|---------|
+| <code>MEDIA_IN</code> | <code>/app/media/in</code> | Source media files to process |
+| <code>MEDIA_OUT</code> | <code>/app/media/out</code> | Transcoded/trimmed output files |</p>
+<p>These can point to different locations or even different servers/buckets in production.</p>
+<h3>File Path Storage</h3>
+<ul>
+<li><strong>Database</strong>: Stores only the relative path (e.g., <code>videos/sample.mp4</code>)</li>
+<li><strong>Input Root</strong>: Configurable via <code>MEDIA_IN</code> env var</li>
+<li><strong>Output Root</strong>: Configurable via <code>MEDIA_OUT</code> env var</li>
+<li><strong>Serving</strong>: Base URL configurable via <code>MEDIA_BASE_URL</code> env var</li>
+</ul>
+<h3>Why Relative Paths?</h3>
+<ol>
+<li><strong>Portability</strong>: Same database works locally and in cloud</li>
+<li><strong>Flexibility</strong>: Easy to switch between storage backends</li>
+<li><strong>Simplicity</strong>: No need to update paths when migrating</li>
+</ol>
+<h2>Local Development</h2>
+<h3>Configuration</h3>
+<p><code>bash
+MEDIA_IN=/app/media/in
+MEDIA_OUT=/app/media/out</code></p>
+<h3>File Structure</h3>
+<p><code>/app/media/
+├── in/                    # Source files
+│   ├── video1.mp4
+│   ├── video2.mp4
+│   └── subfolder/
+│       └── video3.mp4
+└── out/                   # Transcoded output
+    ├── video1_h264.mp4
+    └── video2_trimmed.mp4</code></p>
+<h3>Database Storage</h3>
+<p>```</p>
+<h1>Source assets (scanned from media/in)</h1>
+<p>filename: video1.mp4
+file_path: video1.mp4</p>
+<p>filename: video3.mp4
+file_path: subfolder/video3.mp4
+```</p>
+<h3>URL Serving</h3>
+<ul>
+<li>Nginx serves input via <code>location /media/in { alias /app/media/in; }</code></li>
+<li>Nginx serves output via <code>location /media/out { alias /app/media/out; }</code></li>
+<li>Frontend accesses: <code>http://mpr.local.ar/media/in/video1.mp4</code></li>
+<li>Video player: <code>&lt;video src="/media/in/video1.mp4" /&gt;</code></li>
+</ul>
+<h2>AWS/Cloud Deployment</h2>
+<h3>S3 Configuration</h3>
+<p>```bash</p>
+<h1>Input and output can be different buckets/paths</h1>
+<p>MEDIA_IN=s3://source-bucket/media/
+MEDIA_OUT=s3://output-bucket/transcoded/
+MEDIA_BASE_URL=https://source-bucket.s3.amazonaws.com/media/
+```</p>
+<h3>S3 Structure</h3>
+<p>```
+s3://source-bucket/media/
+├── video1.mp4
+└── subfolder/
+    └── video3.mp4</p>
+<p>s3://output-bucket/transcoded/
+├── video1_h264.mp4
+└── video2_trimmed.mp4
+```</p>
+<h3>Database Storage (Same!)</h3>
+<p>```
+filename: video1.mp4
+file_path: video1.mp4</p>
+<p>filename: video3.mp4
+file_path: subfolder/video3.mp4
+```</p>
+<h2>API Endpoints</h2>
+<h3>Scan Media Folder</h3>
+<p><code>http
+POST /api/assets/scan</code></p>
+<p><strong>Behavior:</strong>
+1. Recursively scans <code>MEDIA_IN</code> directory
+2. Finds all video/audio files (mp4, mkv, avi, mov, mp3, wav, etc.)
+3. Stores paths <strong>relative to MEDIA_IN</strong>
+4. Skips already-registered files (by filename)
+5. Returns summary: <code>{ found, registered, skipped, files }</code></p>
+<h3>Create Job</h3>
+<p>```http
+POST /api/jobs/
+Content-Type: application/json</p>
+<p>{
+  "source_asset_id": "uuid",
+  "preset_id": "uuid",
+  "trim_start": 10.0,
+  "trim_end": 30.0
+}
+```</p>
+<p><strong>Behavior:</strong>
+- Server sets <code>output_path</code> using <code>MEDIA_OUT</code> + generated filename
+- Output goes to the output directory, not alongside source files</p>
+<h2>Migration Guide</h2>
+<h3>Moving from Local to S3</h3>
+<ol>
+<li>
+<p><strong>Upload source files to S3:</strong>
+   <code>bash
+   aws s3 sync /app/media/in/ s3://source-bucket/media/
+   aws s3 sync /app/media/out/ s3://output-bucket/transcoded/</code></p>
+</li>
+<li>
+<p><strong>Update environment variables:</strong>
+   <code>bash
+   MEDIA_IN=s3://source-bucket/media/
+   MEDIA_OUT=s3://output-bucket/transcoded/
+   MEDIA_BASE_URL=https://source-bucket.s3.amazonaws.com/media/</code></p>
+</li>
+<li>
+<p><strong>Database paths remain unchanged</strong> (already relative)</p>
+</li>
+</ol>
+<h2>Supported File Types</h2>
+<p><strong>Video:</strong> <code>.mp4</code>, <code>.mkv</code>, <code>.avi</code>, <code>.mov</code>, <code>.webm</code>, <code>.flv</code>, <code>.wmv</code>, <code>.m4v</code>
+<strong>Audio:</strong> <code>.mp3</code>, <code>.wav</code>, <code>.flac</code>, <code>.aac</code>, <code>.ogg</code>, <code>.m4a</code></p>

modelgen/__init__.py

@@ -16,10 +16,10 @@ Output formats:
 - prisma: Prisma schema
 
 Usage:
-    python -m modelgen from-config -c config.json -o models.py
+    python -m soleprint.station.tools.modelgen from-config -c config.json -o models.py
-    python -m modelgen from-schema -o models/ --targets pydantic,typescript
+    python -m soleprint.station.tools.modelgen from-schema -o models/ --targets pydantic,typescript
-    python -m modelgen extract --source /path/to/django --targets pydantic
+    python -m soleprint.station.tools.modelgen extract --source /path/to/django --targets pydantic
-    python -m modelgen list-formats
+    python -m soleprint.station.tools.modelgen list-formats
 """
 
 __version__ = "0.2.0"

modelgen/__main__.py

@@ -16,10 +16,11 @@ Output formats:
 - prisma: Prisma schema
 
 Usage:
-    python -m modelgen --help
+    python -m soleprint.station.tools.modelgen --help
-    python -m modelgen from-config -c config.json -o models.py
+    python -m soleprint.station.tools.modelgen from-config -c config.json -o models.py
-    python -m modelgen from-schema -o models/ --targets pydantic,typescript
+    python -m soleprint.station.tools.modelgen from-schema -o models/ --targets pydantic,typescript
-    python -m modelgen extract --source /path/to/django --targets pydantic
+    python -m soleprint.station.tools.modelgen extract --source /path/to/django --targets pydantic
+    python -m soleprint.station.tools.modelgen generate --config schema/modelgen.json
 """
 
 import argparse
@@ -177,6 +178,47 @@ def cmd_extract(args):
     print("Done!")
 
 
+def cmd_generate(args):
+    """Generate all targets from a JSON config file."""
+    import json
+    from .loader import load_schema
+
+    config_path = Path(args.config)
+    if not config_path.exists():
+        print(f"Error: Config file not found: {config_path}", file=sys.stderr)
+        sys.exit(1)
+
+    with open(config_path) as f:
+        config = json.load(f)
+
+    # Resolve paths relative to current working directory
+    schema_path = Path(config["schema"])
+    if not schema_path.exists():
+        print(f"Error: Schema folder not found: {schema_path}", file=sys.stderr)
+        sys.exit(1)
+
+    print(f"Loading schema: {schema_path}")
+
+    for target_conf in config["targets"]:
+        target = target_conf["target"]
+        output = Path(target_conf["output"])
+        include = set(target_conf.get("include", []))
+        name_map = target_conf.get("name_map", {})
+
+        if target not in GENERATORS:
+            print(f"Warning: Unknown target '{target}', skipping", file=sys.stderr)
+            continue
+
+        # Load schema with this target's include filter
+        schema = load_schema(schema_path, include=include or None)
+
+        generator = GENERATORS[target](name_map=name_map)
+        print(f"Generating {target} to: {output}")
+        generator.generate(schema, output)
+
+    print("Done!")
+
+
 def cmd_list_formats(args):
     """List available output formats."""
     print("Available output formats:")
@@ -295,6 +337,21 @@ def main():
     )
     extract_parser.set_defaults(func=cmd_extract)
 
+
+    # generate command (config-driven multi-target)
+    gen_parser = subparsers.add_parser(
+        "generate",
+        help="Generate all targets from a JSON config file",
+    )
+    gen_parser.add_argument(
+        "--config",
+        "-c",
+        type=str,
+        required=True,
+        help="Path to generation config file (e.g., schema/modelgen.json)",
+    )
+    gen_parser.set_defaults(func=cmd_generate)
+
     # list-formats command
     formats_parser = subparsers.add_parser(
         "list-formats",

modelgen/generator/__init__.py

@@ -7,16 +7,17 @@ Supported generators:
 - TypeScriptGenerator: TypeScript interfaces
 - ProtobufGenerator: Protocol Buffer definitions
 - PrismaGenerator: Prisma schema
+- StrawberryGenerator: Strawberry type/input/enum classes
 """
 
 from typing import Dict, Type
 
 from .base import BaseGenerator
 from .django import DjangoGenerator
-from .graphene import GrapheneGenerator
 from .prisma import PrismaGenerator
 from .protobuf import ProtobufGenerator
 from .pydantic import PydanticGenerator
+from .strawberry import StrawberryGenerator
 from .typescript import TypeScriptGenerator
 
 # Registry of available generators
@@ -28,14 +29,14 @@ GENERATORS: Dict[str, Type[BaseGenerator]] = {
     "protobuf": ProtobufGenerator,
     "proto": ProtobufGenerator,  # Alias
     "prisma": PrismaGenerator,
-    "graphene": GrapheneGenerator,
+    "strawberry": StrawberryGenerator,
 }
 
 __all__ = [
     "BaseGenerator",
     "PydanticGenerator",
     "DjangoGenerator",
-    "GrapheneGenerator",
+    "StrawberryGenerator",
     "TypeScriptGenerator",
     "ProtobufGenerator",
     "PrismaGenerator",

modelgen/generator/base.py

@@ -6,12 +6,19 @@ Abstract base class for all code generators.
 
 from abc import ABC, abstractmethod
 from pathlib import Path
-from typing import Any
+from typing import Any, Dict
 
 
 class BaseGenerator(ABC):
     """Abstract base for code generators."""
 
+    def __init__(self, name_map: Dict[str, str] = None):
+        self.name_map = name_map or {}
+
+    def map_name(self, name: str) -> str:
+        """Apply name_map to a model name."""
+        return self.name_map.get(name, name)
+
     @abstractmethod
     def generate(self, models: Any, output_path: Path) -> None:
         """Generate code for the given models to the specified path."""

modelgen/generator/django.py

@@ -224,7 +224,8 @@ class DjangoGenerator(BaseGenerator):
             if default is not dc.MISSING and isinstance(default, Enum):
                 extra.append(f"default={enum_name}.{default.name}")
             return DJANGO_TYPES["enum"].format(
-                enum_name=enum_name, opts=", " + ", ".join(extra) if extra else ""
+                enum_name=enum_name,
+                opts=", " + ", ".join(extra) if extra else ""
             )
 
         # Text fields (based on name heuristics)

modelgen/generator/pydantic.py

@@ -2,8 +2,12 @@
 Pydantic Generator
 
 Generates Pydantic BaseModel classes from model definitions.
+Supports two output modes:
+- File output: flat models (backwards compatible)
+- Directory output: CRUD variants (Create/Update/Response) per model
 """
 
+import dataclasses as dc
 from enum import Enum
 from pathlib import Path
 from typing import Any, List, get_type_hints
@@ -13,6 +17,13 @@ from ..loader.schema import EnumDefinition, FieldDefinition, ModelDefinition
 from ..types import PYDANTIC_RESOLVERS
 from .base import BaseGenerator
 
+# Fields to skip per CRUD variant
+SKIP_FIELDS = {
+    "Create": {"id", "created_at", "updated_at", "status", "error_message"},
+    "Update": {"id", "created_at", "updated_at"},
+    "Response": set(),
+}
+
 
 class PydanticGenerator(BaseGenerator):
     """Generates Pydantic model files."""
@@ -21,52 +32,187 @@ class PydanticGenerator(BaseGenerator):
         return ".py"
 
     def generate(self, models, output_path: Path) -> None:
-        """Generate Pydantic models to output_path."""
+        """Generate Pydantic models to output_path.
+
+        If output_path is a directory (or doesn't end in .py), generate
+        multi-file CRUD variants. Otherwise, generate flat models to a
+        single file.
+        """
+        output_path = Path(output_path)
+
+        if output_path.suffix != ".py":
+            # Directory mode: CRUD variants
+            self._generate_crud_directory(models, output_path)
+        else:
+            # File mode: flat models (backwards compatible)
+            self._generate_flat_file(models, output_path)
+
+    def _generate_flat_file(self, models, output_path: Path) -> None:
+        """Generate flat models to a single file (original behavior)."""
         output_path.parent.mkdir(parents=True, exist_ok=True)
 
-        # Detect input type and generate accordingly
         if hasattr(models, "get_shared_component"):
-            # ConfigLoader (soleprint config)
             content = self._generate_from_config(models)
         elif hasattr(models, "models"):
-            # SchemaLoader
             content = self._generate_from_definitions(
                 models.models, getattr(models, "enums", [])
             )
         elif isinstance(models, tuple):
-            # (models, enums) tuple from extractor
             content = self._generate_from_definitions(models[0], models[1])
         elif isinstance(models, list):
-            # List of dataclasses (MPR style)
             content = self._generate_from_dataclasses(models)
         else:
             raise ValueError(f"Unsupported input type: {type(models)}")
 
         output_path.write_text(content)
 
+    def _generate_crud_directory(self, models, output_dir: Path) -> None:
+        """Generate CRUD variant files in a directory."""
+        output_dir.mkdir(parents=True, exist_ok=True)
+
+        if hasattr(models, "models"):
+            model_defs = models.models
+            enum_defs = getattr(models, "enums", [])
+        elif isinstance(models, tuple):
+            model_defs = models[0]
+            enum_defs = models[1]
+        else:
+            raise ValueError(f"Unsupported input type for CRUD mode: {type(models)}")
+
+        # base.py
+        base_content = "\n".join([
+            '"""Pydantic Base Schema - GENERATED FILE"""',
+            "",
+            "from pydantic import BaseModel, ConfigDict",
+            "",
+            "",
+            "class BaseSchema(BaseModel):",
+            '    """Base schema with ORM mode."""',
+            "    model_config = ConfigDict(from_attributes=True)",
+            "",
+        ])
+        (output_dir / "base.py").write_text(base_content)
+
+        # Per-model files
+        imports = ["from .base import BaseSchema"]
+        all_exports = ['"BaseSchema"']
+
+        for model_def in model_defs:
+            mapped = self.map_name(model_def.name)
+            module_name = mapped.lower()
+
+            lines = [
+                f'"""{model_def.name} Schemas - GENERATED FILE"""',
+                "",
+                "from datetime import datetime",
+                "from enum import Enum",
+                "from typing import Any, Dict, List, Optional",
+                "from uuid import UUID",
+                "",
+                "from .base import BaseSchema",
+                "",
+            ]
+
+            # Inline enums used by this model
+            model_enums = self._collect_model_enums(model_def, enum_defs)
+            for enum_def in model_enums:
+                lines.append("")
+                lines.extend(self._generate_enum(enum_def))
+                lines.append("")
+
+            # CRUD variants
+            for suffix in ["Create", "Update", "Response"]:
+                lines.append("")
+                lines.extend(self._generate_crud_model(model_def, mapped, suffix))
+
+            lines.append("")
+            content = "\n".join(lines)
+            (output_dir / f"{module_name}.py").write_text(content)
+
+            # Track imports
+            imports.append(
+                f"from .{module_name} import {mapped}Create, {mapped}Update, {mapped}Response"
+            )
+            all_exports.extend([
+                f'"{mapped}Create"', f'"{mapped}Update"', f'"{mapped}Response"'
+            ])
+
+            for enum_def in model_enums:
+                imports.append(f"from .{module_name} import {enum_def.name}")
+                all_exports.append(f'"{enum_def.name}"')
+
+        # __init__.py
+        init_content = "\n".join([
+            '"""API Schemas - GENERATED FILE"""',
+            "",
+            *imports,
+            "",
+            f"__all__ = [{', '.join(all_exports)}]",
+            "",
+        ])
+        (output_dir / "__init__.py").write_text(init_content)
+
+    def _collect_model_enums(
+        self, model_def: ModelDefinition, enum_defs: List[EnumDefinition]
+    ) -> List[EnumDefinition]:
+        """Find enums referenced by a model's fields."""
+        enum_names = set()
+        for field in model_def.fields:
+            base, _ = unwrap_optional(field.type_hint)
+            if isinstance(base, type) and issubclass(base, Enum):
+                enum_names.add(base.__name__)
+        return [e for e in enum_defs if e.name in enum_names]
+
+    def _generate_crud_model(
+        self, model_def: ModelDefinition, mapped_name: str, suffix: str
+    ) -> List[str]:
+        """Generate a single CRUD variant (Create/Update/Response)."""
+        class_name = f"{mapped_name}{suffix}"
+        skip = SKIP_FIELDS.get(suffix, set())
+
+        lines = [
+            f"class {class_name}(BaseSchema):",
+            f'    """{class_name} schema."""',
+        ]
+
+        has_fields = False
+        for field in model_def.fields:
+            if field.name.startswith("_") or field.name in skip:
+                continue
+
+            has_fields = True
+            py_type = self._resolve_type(field.type_hint, field.optional)
+
+            # Update variant: all fields optional
+            if suffix == "Update" and "Optional" not in py_type:
+                py_type = f"Optional[{py_type}]"
+
+            default = self._format_default(field.default, "Optional" in py_type)
+            lines.append(f"    {field.name}: {py_type}{default}")
+
+        if not has_fields:
+            lines.append("    pass")
+
+        return lines
+
+    # =========================================================================
+    # Flat file generation (original behavior)
+    # =========================================================================
+
     def _generate_from_definitions(
         self, models: List[ModelDefinition], enums: List[EnumDefinition]
     ) -> str:
-        """Generate from ModelDefinition objects (schema/extract mode)."""
         lines = self._generate_header()
-
-        # Generate enums
         for enum_def in enums:
             lines.extend(self._generate_enum(enum_def))
             lines.append("")
-
-        # Generate models
         for model_def in models:
             lines.extend(self._generate_model_from_definition(model_def))
             lines.append("")
-
         return "\n".join(lines)
 
     def _generate_from_dataclasses(self, dataclasses: List[type]) -> str:
-        """Generate from Python dataclasses (MPR style)."""
         lines = self._generate_header()
-
-        # Collect and generate enums first
         enums_generated = set()
         for cls in dataclasses:
             hints = get_type_hints(cls)
@@ -77,16 +223,12 @@ class PydanticGenerator(BaseGenerator):
                         lines.extend(self._generate_enum_from_python(base))
                         lines.append("")
                         enums_generated.add(base.__name__)
-
-        # Generate models
         for cls in dataclasses:
             lines.extend(self._generate_model_from_dataclass(cls))
             lines.append("")
-
         return "\n".join(lines)
 
     def _generate_header(self) -> List[str]:
-        """Generate file header."""
         return [
             '"""',
             "Pydantic Models - GENERATED FILE",
@@ -104,27 +246,23 @@ class PydanticGenerator(BaseGenerator):
         ]
 
     def _generate_enum(self, enum_def: EnumDefinition) -> List[str]:
-        """Generate Pydantic enum from EnumDefinition."""
         lines = [f"class {enum_def.name}(str, Enum):"]
         for name, value in enum_def.values:
             lines.append(f'    {name} = "{value}"')
         return lines
 
     def _generate_enum_from_python(self, enum_cls: type) -> List[str]:
-        """Generate Pydantic enum from Python Enum."""
         lines = [f"class {enum_cls.__name__}(str, Enum):"]
         for member in enum_cls:
             lines.append(f'    {member.name} = "{member.value}"')
         return lines
 
     def _generate_model_from_definition(self, model_def: ModelDefinition) -> List[str]:
-        """Generate Pydantic model from ModelDefinition."""
         docstring = model_def.docstring or model_def.name
         lines = [
             f"class {model_def.name}(BaseModel):",
             f'    """{docstring.strip().split(chr(10))[0]}"""',
         ]
-
         if not model_def.fields:
             lines.append("    pass")
         else:
@@ -132,46 +270,34 @@ class PydanticGenerator(BaseGenerator):
                 py_type = self._resolve_type(field.type_hint, field.optional)
                 default = self._format_default(field.default, field.optional)
                 lines.append(f"    {field.name}: {py_type}{default}")
-
         return lines
 
     def _generate_model_from_dataclass(self, cls: type) -> List[str]:
-        """Generate Pydantic model from a dataclass."""
-        import dataclasses as dc
-
         docstring = cls.__doc__ or cls.__name__
         lines = [
             f"class {cls.__name__}(BaseModel):",
             f'    """{docstring.strip().split(chr(10))[0]}"""',
         ]
-
         hints = get_type_hints(cls)
         fields = {f.name: f for f in dc.fields(cls)}
-
         for name, type_hint in hints.items():
             if name.startswith("_"):
                 continue
-
             field = fields.get(name)
             default_val = dc.MISSING
             if field:
                 if field.default is not dc.MISSING:
                     default_val = field.default
-
             py_type = self._resolve_type(type_hint, False)
             default = self._format_default(default_val, "Optional" in py_type)
             lines.append(f"    {name}: {py_type}{default}")
-
         return lines
 
     def _resolve_type(self, type_hint: Any, optional: bool) -> str:
-        """Resolve Python type to Pydantic type string."""
         base, is_optional = unwrap_optional(type_hint)
         optional = optional or is_optional
         origin = get_origin_name(base)
         type_name = get_type_name(base)
-
-        # Look up resolver
         resolver = (
             PYDANTIC_RESOLVERS.get(origin)
             or PYDANTIC_RESOLVERS.get(type_name)
@@ -182,14 +308,10 @@ class PydanticGenerator(BaseGenerator):
                 else None
             )
         )
-
         result = resolver(base) if resolver else "str"
         return f"Optional[{result}]" if optional else result
 
     def _format_default(self, default: Any, optional: bool) -> str:
-        """Format default value for field."""
-        import dataclasses as dc
-
         if optional:
             return " = None"
         if default is dc.MISSING or default is None:
@@ -204,7 +326,6 @@ class PydanticGenerator(BaseGenerator):
 
     def _generate_from_config(self, config) -> str:
         """Generate from ConfigLoader (soleprint config.json mode)."""
-        # Get component names from config
         config_comp = config.get_shared_component("config")
         data_comp = config.get_shared_component("data")
 

modelgen/generator/strawberry.py

@@ -1,28 +1,29 @@
 """
-Graphene Generator
+Strawberry Generator
 
-Generates graphene ObjectType and InputObjectType classes from model definitions.
+Generates strawberry type, input, and enum classes from model definitions.
 Only generates type definitions — queries, mutations, and resolvers are hand-written.
 """
 
+import dataclasses as dc
 from enum import Enum
 from pathlib import Path
 from typing import Any, List, get_type_hints
 
 from ..helpers import get_origin_name, get_type_name, unwrap_optional
 from ..loader.schema import EnumDefinition, FieldDefinition, ModelDefinition
-from ..types import GRAPHENE_RESOLVERS
+from ..types import STRAWBERRY_RESOLVERS
 from .base import BaseGenerator
 
 
-class GrapheneGenerator(BaseGenerator):
+class StrawberryGenerator(BaseGenerator):
-    """Generates graphene type definition files."""
+    """Generates strawberry type definition files."""
 
     def file_extension(self) -> str:
         return ".py"
 
     def generate(self, models, output_path: Path) -> None:
-        """Generate graphene types to output_path."""
+        """Generate strawberry types to output_path."""
         output_path.parent.mkdir(parents=True, exist_ok=True)
 
         if hasattr(models, "models"):
@@ -47,22 +48,18 @@ class GrapheneGenerator(BaseGenerator):
         enums: List[EnumDefinition],
         api_models: List[ModelDefinition],
     ) -> str:
-        """Generate from ModelDefinition objects."""
         lines = self._generate_header()
 
-        # Generate enums as graphene.Enum
         for enum_def in enums:
             lines.extend(self._generate_enum(enum_def))
             lines.append("")
             lines.append("")
 
-        # Generate domain models as ObjectType
         for model_def in models:
             lines.extend(self._generate_object_type(model_def))
             lines.append("")
             lines.append("")
 
-        # Generate API models — request types as InputObjectType, others as ObjectType
         for model_def in api_models:
             if model_def.name.endswith("Request"):
                 lines.extend(self._generate_input_type(model_def))
@@ -74,7 +71,6 @@ class GrapheneGenerator(BaseGenerator):
         return "\n".join(lines).rstrip() + "\n"
 
     def _generate_from_dataclasses(self, dataclasses: List[type]) -> str:
-        """Generate from Python dataclasses."""
         lines = self._generate_header()
 
         enums_generated = set()
@@ -99,37 +95,38 @@ class GrapheneGenerator(BaseGenerator):
     def _generate_header(self) -> List[str]:
         return [
             '"""',
-            "Graphene Types - GENERATED FILE",
+            "Strawberry Types - GENERATED FILE",
             "",
             "Do not edit directly. Regenerate using modelgen.",
             '"""',
             "",
-            "import graphene",
+            "import strawberry",
+            "from enum import Enum",
+            "from typing import List, Optional",
+            "from uuid import UUID",
+            "from datetime import datetime",
+            "from strawberry.scalars import JSON",
             "",
             "",
         ]
 
     def _generate_enum(self, enum_def: EnumDefinition) -> List[str]:
-        """Generate graphene.Enum from EnumDefinition."""
+        lines = ["@strawberry.enum", f"class {enum_def.name}(Enum):"]
-        lines = [f"class {enum_def.name}(graphene.Enum):"]
         for name, value in enum_def.values:
             lines.append(f'    {name} = "{value}"')
         return lines
 
     def _generate_enum_from_python(self, enum_cls: type) -> List[str]:
-        """Generate graphene.Enum from Python Enum."""
+        lines = ["@strawberry.enum", f"class {enum_cls.__name__}(Enum):"]
-        lines = [f"class {enum_cls.__name__}(graphene.Enum):"]
         for member in enum_cls:
             lines.append(f'    {member.name} = "{member.value}"')
         return lines
 
     def _generate_object_type(self, model_def: ModelDefinition) -> List[str]:
-        """Generate graphene.ObjectType from ModelDefinition."""
         name = model_def.name
-        # Append Type suffix if not already present
         type_name = f"{name}Type" if not name.endswith("Type") else name
 
-        lines = [f"class {type_name}(graphene.ObjectType):"]
+        lines = ["@strawberry.type", f"class {type_name}:"]
         if model_def.docstring:
             doc = model_def.docstring.strip().split("\n")[0]
             lines.append(f'    """{doc}"""')
@@ -139,23 +136,19 @@ class GrapheneGenerator(BaseGenerator):
             lines.append("    pass")
         else:
             for field in model_def.fields:
-                graphene_type = self._resolve_type(field.type_hint, field.optional)
+                type_str = self._resolve_type(field.type_hint, optional=True)
-                lines.append(f"    {field.name} = {graphene_type}")
+                lines.append(f"    {field.name}: {type_str} = None")
 
         return lines
 
     def _generate_input_type(self, model_def: ModelDefinition) -> List[str]:
-        """Generate graphene.InputObjectType from ModelDefinition."""
-        import dataclasses as dc
-
         name = model_def.name
-        # Convert FooRequest -> FooInput
         if name.endswith("Request"):
             input_name = name[: -len("Request")] + "Input"
         else:
             input_name = f"{name}Input"
 
-        lines = [f"class {input_name}(graphene.InputObjectType):"]
+        lines = ["@strawberry.input", f"class {input_name}:"]
         if model_def.docstring:
             doc = model_def.docstring.strip().split("\n")[0]
             lines.append(f'    """{doc}"""')
@@ -164,73 +157,64 @@ class GrapheneGenerator(BaseGenerator):
         if not model_def.fields:
             lines.append("    pass")
         else:
+            # Required fields first, then optional/defaulted
+            required = []
+            optional = []
             for field in model_def.fields:
-                graphene_type = self._resolve_type(field.type_hint, field.optional)
-                # Required only if not optional AND no default value
                 has_default = field.default is not dc.MISSING
                 if not field.optional and not has_default:
-                    graphene_type = self._make_required(graphene_type)
+                    required.append(field)
-                elif has_default and not field.optional:
+                else:
-                    graphene_type = self._add_default(graphene_type, field.default)
+                    optional.append(field)
-                lines.append(f"    {field.name} = {graphene_type}")
+
+            for field in required:
+                type_str = self._resolve_type(field.type_hint, optional=False)
+                lines.append(f"    {field.name}: {type_str}")
+
+            for field in optional:
+                has_default = field.default is not dc.MISSING
+                if has_default and not callable(field.default):
+                    type_str = self._resolve_type(field.type_hint, optional=False)
+                    lines.append(f"    {field.name}: {type_str} = {field.default!r}")
+                else:
+                    type_str = self._resolve_type(field.type_hint, optional=True)
+                    lines.append(f"    {field.name}: {type_str} = None")
 
         return lines
 
     def _generate_object_type_from_dataclass(self, cls: type) -> List[str]:
-        """Generate graphene.ObjectType from a dataclass."""
-        import dataclasses as dc
-
         type_name = f"{cls.__name__}Type"
-        lines = [f"class {type_name}(graphene.ObjectType):"]
+        lines = ["@strawberry.type", f"class {type_name}:"]
 
         hints = get_type_hints(cls)
         for name, type_hint in hints.items():
             if name.startswith("_"):
                 continue
-            graphene_type = self._resolve_type(type_hint, False)
+            type_str = self._resolve_type(type_hint, optional=True)
-            lines.append(f"    {name} = {graphene_type}")
+            lines.append(f"    {name}: {type_str} = None")
 
         return lines
 
     def _resolve_type(self, type_hint: Any, optional: bool) -> str:
-        """Resolve Python type to graphene field call string."""
+        """Resolve Python type hint to a strawberry annotation string."""
         base, is_optional = unwrap_optional(type_hint)
         optional = optional or is_optional
         origin = get_origin_name(base)
         type_name = get_type_name(base)
 
-        # Look up resolver
         resolver = (
-            GRAPHENE_RESOLVERS.get(origin)
+            STRAWBERRY_RESOLVERS.get(origin)
-            or GRAPHENE_RESOLVERS.get(type_name)
+            or STRAWBERRY_RESOLVERS.get(type_name)
-            or GRAPHENE_RESOLVERS.get(base)
+            or STRAWBERRY_RESOLVERS.get(base)
             or (
-                GRAPHENE_RESOLVERS["enum"]
+                STRAWBERRY_RESOLVERS["enum"]
                 if isinstance(base, type) and issubclass(base, Enum)
                 else None
             )
         )
 
-        result = resolver(base) if resolver else "graphene.String"
+        inner = resolver(base) if resolver else "str"
 
-        # List types already have () syntax from resolver
+        if optional:
-        if result.startswith("graphene.List("):
+            return f"Optional[{inner}]"
-            return result
+        return inner
-
-        # Scalar types: add () call
-        return f"{result}()"
-
-    def _make_required(self, field_str: str) -> str:
-        """Add required=True to a graphene field."""
-        if field_str.endswith("()"):
-            return field_str[:-1] + "required=True)"
-        return field_str
-
-    def _add_default(self, field_str: str, default: Any) -> str:
-        """Add default_value to a graphene field."""
-        if callable(default):
-            # default_factory — skip, graphene doesn't support factories
-            return field_str
-        if field_str.endswith("()"):
-            return field_str[:-1] + f"default_value={default!r})"
-        return field_str

modelgen/generator/typescript.py

@@ -26,11 +26,10 @@ class TypeScriptGenerator(BaseGenerator):
 
         # Handle different input types
         if hasattr(models, "models"):
-            # SchemaLoader
+            # SchemaLoader — include api_models if present
+            all_models = models.models + getattr(models, "api_models", [])
             content = self._generate_from_definitions(
-                models.models,
+                all_models, getattr(models, "enums", [])
-                getattr(models, "enums", []),
-                api_models=getattr(models, "api_models", []),
             )
         elif isinstance(models, tuple):
             # (models, enums) tuple
@@ -44,10 +43,7 @@ class TypeScriptGenerator(BaseGenerator):
         output_path.write_text(content)
 
     def _generate_from_definitions(
-        self,
+        self, models: List[ModelDefinition], enums: List[EnumDefinition]
-        models: List[ModelDefinition],
-        enums: List[EnumDefinition],
-        api_models: List[ModelDefinition] = None,
     ) -> str:
         """Generate from ModelDefinition objects."""
         lines = self._generate_header()
@@ -63,14 +59,6 @@ class TypeScriptGenerator(BaseGenerator):
             lines.extend(self._generate_interface_from_definition(model_def))
             lines.append("")
 
-        # Generate API request/response interfaces
-        if api_models:
-            lines.append("// API request/response types")
-            lines.append("")
-            for model_def in api_models:
-                lines.extend(self._generate_interface_from_definition(model_def))
-                lines.append("")
-
         return "\n".join(lines)
 
     def _generate_from_dataclasses(self, dataclasses: List[type]) -> str:

modelgen/loader/schema.py

@@ -5,6 +5,7 @@ Loads Python dataclasses from a schema/ folder.
 Expects the folder to have an __init__.py that exports:
 - DATACLASSES: List of dataclass types to generate
 - ENUMS: List of Enum types to include
+- API_MODELS: (optional) List of API request/response types
 - GRPC_MESSAGES: (optional) List of gRPC message types
 - GRPC_SERVICE: (optional) gRPC service definition dict
 """
@@ -88,7 +89,7 @@ class SchemaLoader:
             for cls in dataclasses:
                 self.models.append(self._parse_dataclass(cls))
 
-        # Extract API_MODELS (TypeScript-only request/response types)
+        # Extract API_MODELS (request/response types)
         if load_all or "api" in include:
             api_models = getattr(module, "API_MODELS", [])
             for cls in api_models:

modelgen/types.py

@@ -139,34 +139,34 @@ PRISMA_SPECIAL: dict[str, str] = {
 }
 
 # =============================================================================
-# Graphene Type Resolvers
+# Strawberry Type Resolvers
 # =============================================================================
 
 
-def _resolve_graphene_list(base: Any) -> str:
+def _resolve_strawberry_list(base: Any) -> str:
-    """Resolve graphene List type."""
+    """Resolve strawberry List type annotation."""
     args = get_args(base)
     if args:
         inner = args[0]
         if inner is str:
-            return "graphene.List(graphene.String)"
+            return "List[str]"
         elif inner is int:
-            return "graphene.List(graphene.Int)"
+            return "List[int]"
         elif inner is float:
-            return "graphene.List(graphene.Float)"
+            return "List[float]"
         elif inner is bool:
-            return "graphene.List(graphene.Boolean)"
+            return "List[bool]"
-    return "graphene.List(graphene.String)"
+    return "List[str]"
 
 
-GRAPHENE_RESOLVERS: dict[Any, Callable[[Any], str]] = {
+STRAWBERRY_RESOLVERS: dict[Any, Callable[[Any], str]] = {
-    str: lambda _: "graphene.String",
+    str: lambda _: "str",
-    int: lambda _: "graphene.Int",
+    int: lambda _: "int",
-    float: lambda _: "graphene.Float",
+    float: lambda _: "float",
-    bool: lambda _: "graphene.Boolean",
+    bool: lambda _: "bool",
-    "UUID": lambda _: "graphene.UUID",
+    "UUID": lambda _: "UUID",
-    "datetime": lambda _: "graphene.DateTime",
+    "datetime": lambda _: "datetime",
-    "dict": lambda _: "graphene.JSONString",
+    "dict": lambda _: "JSON",
-    "list": _resolve_graphene_list,
+    "list": _resolve_strawberry_list,
-    "enum": lambda base: f"graphene.String",  # Enums exposed as strings in GQL
+    "enum": lambda base: base.__name__,
 }

requirements-worker.txt

@@ -0,0 +1,2 @@
+-r requirements.txt
+ffmpeg-python>=0.2.0

requirements.txt

@@ -12,19 +12,19 @@ pydantic>=2.5.0
 celery[redis]>=5.3.0
 redis>=5.0.0
 
-# FFmpeg
-ffmpeg-python>=0.2.0
-
 # gRPC
 grpcio>=1.60.0
 grpcio-tools>=1.60.0
 
 # AWS
 boto3>=1.34.0
+requests>=2.31.0
+
+# GCP (optional — only needed when MPR_EXECUTOR=gcp)
+google-cloud-run>=0.10.0
 
 # GraphQL
-graphene>=3.3
+strawberry-graphql[fastapi]>=0.311.0
-starlette-graphene3>=0.6.0
 
 # Testing
 pytest>=7.4.0

schema/generate.py

@@ -1,718 +0,0 @@
-#!/usr/bin/env python3
-"""
-MPR Model Generator
-
-Generates framework-specific models from schema/models/:
-- Django ORM models -> mpr/media_assets/models.py
-- Pydantic schemas -> api/schemas/*.py
-- TypeScript types -> ui/timeline/src/types.ts
-- Protobuf -> grpc/protos/worker.proto
-
-Usage:
-    python schema/generate.py [--django] [--pydantic] [--typescript] [--proto] [--all]
-"""
-
-import argparse
-import dataclasses as dc
-import subprocess
-import sys
-from enum import Enum
-from pathlib import Path
-from typing import Any, Callable, Union, get_args, get_origin, get_type_hints
-
-PROJECT_ROOT = Path(__file__).parent.parent
-sys.path.insert(0, str(PROJECT_ROOT))
-
-from schema.models import API_MODELS, DATACLASSES, ENUMS, GRPC_MESSAGES, GRPC_SERVICE
-
-# =============================================================================
-# Type Dispatch Tables
-# =============================================================================
-
-DJANGO_TYPES: dict[Any, str] = {
-    str: "models.CharField(max_length={max_length}{opts})",
-    int: "models.IntegerField({opts})",
-    float: "models.FloatField({opts})",
-    bool: "models.BooleanField(default={default})",
-    "UUID": "models.UUIDField({opts})",
-    "datetime": "models.DateTimeField({opts})",
-    "dict": "models.JSONField(default=dict, blank=True)",
-    "list": "models.JSONField(default=list, blank=True)",
-    "text": "models.TextField(blank=True, default='')",
-    "bigint": "models.BigIntegerField({opts})",
-    "enum": "models.CharField(max_length=20, choices={enum_name}.choices{opts})",
-}
-
-DJANGO_SPECIAL: dict[str, str] = {
-    "id": "models.UUIDField(primary_key=True, default=uuid.uuid4, editable=False)",
-    "created_at": "models.DateTimeField(auto_now_add=True)",
-    "updated_at": "models.DateTimeField(auto_now=True)",
-}
-
-PYDANTIC_RESOLVERS: dict[Any, Callable[[Any], str]] = {
-    str: lambda _: "str",
-    int: lambda _: "int",
-    float: lambda _: "float",
-    bool: lambda _: "bool",
-    "UUID": lambda _: "UUID",
-    "datetime": lambda _: "datetime",
-    "dict": lambda _: "Dict[str, Any]",
-    "list": lambda base: f"List[{get_list_inner(base)}]",
-    "enum": lambda base: base.__name__,
-}
-
-TS_RESOLVERS: dict[Any, Callable[[Any], str]] = {
-    str: lambda _: "string",
-    int: lambda _: "number",
-    float: lambda _: "number",
-    bool: lambda _: "boolean",
-    "UUID": lambda _: "string",
-    "datetime": lambda _: "string",
-    "dict": lambda _: "Record<string, unknown>",
-    "list": lambda base: (
-        f"{TS_RESOLVERS.get(get_args(base)[0], lambda _: 'string')(None)}[]"
-        if get_args(base)
-        else "string[]"
-    ),
-    "enum": lambda base: base.__name__,
-}
-
-PROTO_RESOLVERS: dict[Any, Callable[[Any], str]] = {
-    str: lambda _: "string",
-    int: lambda _: "int32",
-    float: lambda _: "float",
-    bool: lambda _: "bool",
-    "list": lambda base: (
-        f"repeated {PROTO_RESOLVERS.get(get_args(base)[0], lambda _: 'string')(None)}"
-        if get_args(base)
-        else "repeated string"
-    ),
-}
-
-
-# =============================================================================
-# Type Helpers
-# =============================================================================
-
-
-def unwrap_optional(type_hint: Any) -> tuple[Any, bool]:
-    """Unwrap Optional[T] -> (T, True) or (T, False) if not optional."""
-    origin = get_origin(type_hint)
-    if origin is Union:
-        args = [a for a in get_args(type_hint) if a is not type(None)]
-        return (args[0] if args else str, True)
-    return (type_hint, False)
-
-
-def get_origin_name(type_hint: Any) -> str | None:
-    """Get origin type name: 'dict', 'list', or None."""
-    origin = get_origin(type_hint)
-    if origin is dict:
-        return "dict"
-    if origin is list:
-        return "list"
-    return None
-
-
-def get_type_name(type_hint: Any) -> str | None:
-    """Get type name for special types like UUID, datetime."""
-    if hasattr(type_hint, "__name__"):
-        return type_hint.__name__
-    return None
-
-
-def get_list_inner(type_hint: Any) -> str:
-    """Get inner type of List[T]."""
-    args = get_args(type_hint)
-    if args and args[0] in (str, int, float, bool):
-        return {str: "str", int: "int", float: "float", bool: "bool"}[args[0]]
-    return "str"
-
-
-def get_field_default(field: dc.Field) -> Any:
-    """Get default value from dataclass field."""
-    if field.default is not dc.MISSING:
-        return field.default
-    return dc.MISSING
-
-
-def format_opts(optional: bool, extra: list[str] | None = None) -> str:
-    """Format field options string."""
-    parts = []
-    if optional:
-        parts.append("null=True, blank=True")
-    if extra:
-        parts.extend(extra)
-    return ", ".join(parts)
-
-
-# =============================================================================
-# Django Generator
-# =============================================================================
-
-
-def resolve_django_type(name: str, type_hint: Any, default: Any) -> str:
-    """Resolve Python type to Django field."""
-    # Special fields
-    if name in DJANGO_SPECIAL:
-        return DJANGO_SPECIAL[name]
-
-    base, optional = unwrap_optional(type_hint)
-    origin = get_origin_name(base)
-    type_name = get_type_name(base)
-    opts = format_opts(optional)
-
-    # Container types
-    if origin == "dict":
-        return DJANGO_TYPES["dict"]
-    if origin == "list":
-        return DJANGO_TYPES["list"]
-
-    # UUID / datetime
-    if type_name == "UUID":
-        return DJANGO_TYPES["UUID"].format(opts=opts)
-    if type_name == "datetime":
-        return DJANGO_TYPES["datetime"].format(opts=opts)
-
-    # Enum
-    if isinstance(base, type) and issubclass(base, Enum):
-        enum_name = base.__name__
-        extra = []
-        if optional:
-            extra.append("null=True, blank=True")
-        if default is not dc.MISSING and isinstance(default, Enum):
-            extra.append(f"default={enum_name}.{default.name}")
-        return DJANGO_TYPES["enum"].format(
-            enum_name=enum_name, opts=", " + ", ".join(extra) if extra else ""
-        )
-
-    # Text fields
-    if base is str and any(x in name for x in ("message", "comments", "description")):
-        return DJANGO_TYPES["text"]
-
-    # BigInt fields
-    if base is int and name in ("file_size", "bitrate"):
-        return DJANGO_TYPES["bigint"].format(opts=opts)
-
-    # Basic types
-    if base is str:
-        max_length = 1000 if "path" in name else 500 if "filename" in name else 255
-        return DJANGO_TYPES[str].format(
-            max_length=max_length, opts=", " + opts if opts else ""
-        )
-
-    if base is int:
-        extra = [opts] if opts else []
-        if default is not dc.MISSING and not callable(default):
-            extra.append(f"default={default}")
-        return DJANGO_TYPES[int].format(opts=", ".join(extra))
-
-    if base is float:
-        extra = [opts] if opts else []
-        if default is not dc.MISSING and not callable(default):
-            extra.append(f"default={default}")
-        return DJANGO_TYPES[float].format(opts=", ".join(extra))
-
-    if base is bool:
-        default_val = default if default is not dc.MISSING else False
-        return DJANGO_TYPES[bool].format(default=default_val)
-
-    # Fallback
-    return DJANGO_TYPES[str].format(max_length=255, opts=", " + opts if opts else "")
-
-
-def generate_django_enum(enum_cls: type) -> list[str]:
-    """Generate Django TextChoices enum."""
-    lines = [f"class {enum_cls.__name__}(models.TextChoices):"]
-    for member in enum_cls:
-        label = member.name.replace("_", " ").title()
-        lines.append(f'    {member.name} = "{member.value}", "{label}"')
-    return lines
-
-
-def generate_django_model(cls: type) -> list[str]:
-    """Generate Django model lines from dataclass."""
-    lines = [
-        f"class {cls.__name__}(models.Model):",
-        f'    """{(cls.__doc__ or cls.__name__).strip().split(chr(10))[0]}"""',
-        "",
-    ]
-
-    hints = get_type_hints(cls)
-    fields = {f.name: f for f in dc.fields(cls)}
-
-    # Fields
-    for name, type_hint in hints.items():
-        if name.startswith("_"):
-            continue
-        field = fields.get(name)
-        default = get_field_default(field) if field else dc.MISSING
-        django_field = resolve_django_type(name, type_hint, default)
-        lines.append(f"    {name} = {django_field}")
-
-    # Meta and __str__
-    lines.extend(
-        [
-            "",
-            "    class Meta:",
-            '        ordering = ["-created_at"]',
-            "",
-            "    def __str__(self):",
-        ]
-    )
-
-    if "filename" in hints:
-        lines.append("        return self.filename")
-    elif "name" in hints:
-        lines.append("        return self.name")
-    else:
-        lines.append("        return str(self.id)")
-
-    return lines
-
-
-def generate_django() -> str:
-    """Generate complete Django models file."""
-    header = [
-        '"""',
-        "Django ORM Models - GENERATED FILE",
-        "",
-        "Do not edit directly. Modify schema/models/*.py and run:",
-        "    python schema/generate.py --django",
-        '"""',
-        "",
-        "import uuid",
-        "from django.db import models",
-        "",
-    ]
-
-    # Generate enums first
-    body = []
-    for enum_cls in ENUMS:
-        body.extend(generate_django_enum(enum_cls))
-        body.extend(["", ""])
-
-    # Generate models
-    for cls in DATACLASSES:
-        body.extend(generate_django_model(cls))
-        body.extend(["", ""])
-
-    return "\n".join(header + body)
-
-
-# =============================================================================
-# Pydantic Generator
-# =============================================================================
-
-
-def resolve_pydantic_type(type_hint: Any) -> str:
-    """Resolve Python type to Pydantic type string."""
-    base, optional = unwrap_optional(type_hint)
-    origin = get_origin_name(base)
-    type_name = get_type_name(base)
-
-    # Look up resolver by origin, type name, base type, or enum
-    resolver = (
-        PYDANTIC_RESOLVERS.get(origin)
-        or PYDANTIC_RESOLVERS.get(type_name)
-        or PYDANTIC_RESOLVERS.get(base)
-        or (
-            PYDANTIC_RESOLVERS["enum"]
-            if isinstance(base, type) and issubclass(base, Enum)
-            else None
-        )
-    )
-
-    result = resolver(base) if resolver else "str"
-    return f"Optional[{result}]" if optional else result
-
-
-def generate_pydantic_schema(cls: type, suffix: str) -> list[str]:
-    """Generate Pydantic schema lines from dataclass."""
-    name = cls.__name__.replace("Transcode", "").replace("Media", "")
-    class_name = f"{name}{suffix}"
-
-    skip_fields = {
-        "Create": {"id", "created_at", "updated_at", "status", "error_message"},
-        "Update": {"id", "created_at", "updated_at"},
-        "Response": set(),
-    }
-
-    lines = [
-        f"class {class_name}(BaseSchema):",
-        f'    """{class_name} schema."""',
-    ]
-
-    hints = get_type_hints(cls)
-    fields = {f.name: f for f in dc.fields(cls)}
-
-    for name, type_hint in hints.items():
-        if name.startswith("_") or name in skip_fields.get(suffix, set()):
-            continue
-
-        py_type = resolve_pydantic_type(type_hint)
-
-        # Update schemas: all fields optional
-        if suffix == "Update" and "Optional" not in py_type:
-            py_type = f"Optional[{py_type}]"
-
-        field = fields.get(name)
-        default = get_field_default(field) if field else dc.MISSING
-
-        if "Optional" in py_type:
-            lines.append(f"    {name}: {py_type} = None")
-        elif default is not dc.MISSING and not callable(default):
-            if isinstance(default, str):
-                lines.append(f'    {name}: {py_type} = "{default}"')
-            elif isinstance(default, Enum):
-                lines.append(
-                    f"    {name}: {py_type} = {default.__class__.__name__}.{default.name}"
-                )
-            else:
-                lines.append(f"    {name}: {py_type} = {default!r}")
-        else:
-            lines.append(f"    {name}: {py_type}")
-
-    return lines
-
-
-def generate_pydantic() -> dict[str, str]:
-    """Generate all Pydantic schema files."""
-    files = {}
-
-    # base.py
-    files["base.py"] = "\n".join(
-        [
-            '"""Pydantic Base Schema - GENERATED FILE"""',
-            "",
-            "from pydantic import BaseModel, ConfigDict",
-            "",
-            "",
-            "class BaseSchema(BaseModel):",
-            '    """Base schema with ORM mode."""',
-            "    model_config = ConfigDict(from_attributes=True)",
-            "",
-        ]
-    )
-
-    # Schema files per model
-    for cls in DATACLASSES:
-        module_name = cls.__name__.replace("Transcode", "").replace("Media", "").lower()
-
-        lines = [
-            f'"""{cls.__name__} Schemas - GENERATED FILE"""',
-            "",
-            "from datetime import datetime",
-            "from enum import Enum",
-            "from typing import Any, Dict, List, Optional",
-            "from uuid import UUID",
-            "",
-            "from .base import BaseSchema",
-            "",
-        ]
-
-        # Add enum if present
-        hints = get_type_hints(cls)
-        for type_hint in hints.values():
-            base, _ = unwrap_optional(type_hint)
-            if isinstance(base, type) and issubclass(base, Enum):
-                lines.extend(
-                    [
-                        "",
-                        f"class {base.__name__}(str, Enum):",
-                    ]
-                )
-                for m in base:
-                    lines.append(f'    {m.name} = "{m.value}"')
-                lines.append("")
-                break
-
-        # Schemas
-        for suffix in ["Create", "Update", "Response"]:
-            lines.append("")
-            lines.extend(generate_pydantic_schema(cls, suffix))
-
-        lines.append("")
-        files[f"{module_name}.py"] = "\n".join(lines)
-
-    # __init__.py
-    imports = ["from .base import BaseSchema"]
-    all_exports = ['"BaseSchema"']
-
-    for cls in DATACLASSES:
-        name = cls.__name__.replace("Transcode", "").replace("Media", "")
-        module = name.lower()
-        imports.append(
-            f"from .{module} import {name}Create, {name}Update, {name}Response"
-        )
-        all_exports.extend([f'"{name}Create"', f'"{name}Update"', f'"{name}Response"'])
-
-        # Add enum export
-        hints = get_type_hints(cls)
-        for type_hint in hints.values():
-            base, _ = unwrap_optional(type_hint)
-            if isinstance(base, type) and issubclass(base, Enum):
-                imports.append(f"from .{module} import {base.__name__}")
-                all_exports.append(f'"{base.__name__}"')
-                break
-
-    files["__init__.py"] = "\n".join(
-        [
-            '"""API Schemas - GENERATED FILE"""',
-            "",
-            *imports,
-            "",
-            f"__all__ = [{', '.join(all_exports)}]",
-            "",
-        ]
-    )
-
-    return files
-
-
-# =============================================================================
-# TypeScript Generator
-# =============================================================================
-
-
-def resolve_ts_type(type_hint: Any) -> str:
-    """Resolve Python type to TypeScript type string."""
-    base, optional = unwrap_optional(type_hint)
-    origin = get_origin_name(base)
-    type_name = get_type_name(base)
-
-    # Look up resolver by origin, type name, base type, or enum
-    resolver = (
-        TS_RESOLVERS.get(origin)
-        or TS_RESOLVERS.get(type_name)
-        or TS_RESOLVERS.get(base)
-        or (
-            TS_RESOLVERS["enum"]
-            if isinstance(base, type) and issubclass(base, Enum)
-            else None
-        )
-    )
-
-    result = resolver(base) if resolver else "string"
-    return f"{result} | null" if optional else result
-
-
-def generate_ts_interface(cls: type) -> list[str]:
-    """Generate TypeScript interface lines from dataclass."""
-    lines = [f"export interface {cls.__name__} {{"]
-
-    for name, type_hint in get_type_hints(cls).items():
-        if name.startswith("_"):
-            continue
-        ts_type = resolve_ts_type(type_hint)
-        lines.append(f"  {name}: {ts_type};")
-
-    lines.append("}")
-    return lines
-
-
-def generate_typescript() -> str:
-    """Generate complete TypeScript file."""
-    lines = [
-        "/**",
-        " * MPR TypeScript Types - GENERATED FILE",
-        " *",
-        " * Do not edit directly. Modify schema/models/*.py and run:",
-        " *     python schema/generate.py --typescript",
-        " */",
-        "",
-    ]
-
-    # Enums as union types
-    for enum in ENUMS:
-        values = " | ".join(f'"{m.value}"' for m in enum)
-        lines.append(f"export type {enum.__name__} = {values};")
-    lines.append("")
-
-    # Interfaces - domain models
-    for cls in DATACLASSES:
-        lines.extend(generate_ts_interface(cls))
-        lines.append("")
-
-    # Interfaces - API request/response models
-    lines.append("// API Request/Response Types")
-    lines.append("")
-    for cls in API_MODELS:
-        lines.extend(generate_ts_interface(cls))
-        lines.append("")
-
-    return "\n".join(lines)
-
-
-# =============================================================================
-# Proto Generator
-# =============================================================================
-
-
-def resolve_proto_type(type_hint: Any) -> tuple[str, bool]:
-    """Resolve Python type to proto type. Returns (type, is_optional)."""
-    base, optional = unwrap_optional(type_hint)
-    origin = get_origin_name(base)
-
-    # Look up resolver by origin or base type
-    resolver = PROTO_RESOLVERS.get(origin) or PROTO_RESOLVERS.get(base)
-
-    if resolver:
-        result = resolver(base)
-        is_repeated = result.startswith("repeated")
-        return result, optional and not is_repeated
-
-    return "string", optional
-
-
-def generate_proto_message(cls: type) -> list[str]:
-    """Generate proto message lines from dataclass."""
-    lines = [f"message {cls.__name__} {{"]
-
-    hints = get_type_hints(cls)
-    if not hints:
-        lines.append("    // Empty")
-    else:
-        for i, (name, type_hint) in enumerate(hints.items(), 1):
-            proto_type, optional = resolve_proto_type(type_hint)
-            prefix = (
-                "optional "
-                if optional and not proto_type.startswith("repeated")
-                else ""
-            )
-            lines.append(f"    {prefix}{proto_type} {name} = {i};")
-
-    lines.append("}")
-    return lines
-
-
-def generate_proto() -> str:
-    """Generate complete proto file."""
-    lines = [
-        "// MPR Worker Service - GENERATED FILE",
-        "//",
-        "// Do not edit directly. Modify schema/models/grpc.py and run:",
-        "//     python schema/generate.py --proto",
-        "",
-        'syntax = "proto3";',
-        "",
-        f"package {GRPC_SERVICE['package']};",
-        "",
-        f"service {GRPC_SERVICE['name']} {{",
-    ]
-
-    # Methods
-    for m in GRPC_SERVICE["methods"]:
-        req = m["request"].__name__
-        resp = m["response"].__name__
-        returns = f"stream {resp}" if m["stream_response"] else resp
-        lines.append(f"    rpc {m['name']}({req}) returns ({returns});")
-
-    lines.extend(["}", ""])
-
-    # Messages
-    for cls in GRPC_MESSAGES:
-        lines.extend(generate_proto_message(cls))
-        lines.append("")
-
-    return "\n".join(lines)
-
-
-# =============================================================================
-# Writers
-# =============================================================================
-
-
-def write_file(path: Path, content: str) -> None:
-    """Write content to file, creating directories as needed."""
-    path.parent.mkdir(parents=True, exist_ok=True)
-    path.write_text(content)
-    print(f"  {path}")
-
-
-def write_django(output_dir: Path) -> None:
-    """Write Django models."""
-    write_file(output_dir / "mpr" / "media_assets" / "models.py", generate_django())
-
-
-def write_pydantic(output_dir: Path) -> None:
-    """Write Pydantic schemas."""
-    schemas_dir = output_dir / "api" / "schemas"
-    for filename, content in generate_pydantic().items():
-        write_file(schemas_dir / filename, content)
-
-
-def write_typescript(output_dir: Path) -> None:
-    """Write TypeScript types."""
-    write_file(
-        output_dir / "ui" / "timeline" / "src" / "types.ts", generate_typescript()
-    )
-
-
-def write_proto(output_dir: Path) -> None:
-    """Write proto and generate stubs."""
-    proto_dir = output_dir / "grpc" / "protos"
-    proto_path = proto_dir / "worker.proto"
-    write_file(proto_path, generate_proto())
-
-    # Generate Python stubs
-    grpc_dir = output_dir / "grpc"
-    result = subprocess.run(
-        [
-            sys.executable,
-            "-m",
-            "grpc_tools.protoc",
-            f"-I{proto_dir}",
-            f"--python_out={grpc_dir}",
-            f"--grpc_python_out={grpc_dir}",
-            str(proto_path),
-        ],
-        capture_output=True,
-        text=True,
-    )
-
-    if result.returncode == 0:
-        print(f"  {grpc_dir}/worker_pb2.py")
-        print(f"  {grpc_dir}/worker_pb2_grpc.py")
-    else:
-        print("  Warning: grpc_tools failed - pip install grpcio-tools")
-
-
-# =============================================================================
-# Main
-# =============================================================================
-
-
-def main() -> None:
-    parser = argparse.ArgumentParser(description="Generate from schema")
-    parser.add_argument("--django", action="store_true")
-    parser.add_argument("--pydantic", action="store_true")
-    parser.add_argument("--typescript", action="store_true")
-    parser.add_argument("--proto", action="store_true")
-    parser.add_argument("--all", action="store_true")
-    parser.add_argument("--output", type=Path, default=PROJECT_ROOT)
-    args = parser.parse_args()
-
-    if not any([args.django, args.pydantic, args.typescript, args.proto, args.all]):
-        args.all = True
-
-    print(f"Generating to {args.output}\n")
-
-    targets: list[tuple[bool, str, Callable]] = [
-        (args.django or args.all, "Django", write_django),
-        (args.pydantic or args.all, "Pydantic", write_pydantic),
-        (args.typescript or args.all, "TypeScript", write_typescript),
-        (args.proto or args.all, "Proto", write_proto),
-    ]
-
-    for enabled, name, writer in targets:
-        if enabled:
-            print(f"{name}:")
-            writer(args.output)
-            print()
-
-    print("Done!")
-
-
-if __name__ == "__main__":
-    main()

ui/timeline/.dockerignore

@@ -0,0 +1,2 @@
+node_modules/
+dist/

ui/timeline/src/api.ts

@@ -1,5 +1,5 @@
 /**
- * API client for FastAPI backend
+ * GraphQL API client
  */
 
 import type {
@@ -8,34 +8,51 @@ import type {
   TranscodeJob,
   CreateJobRequest,
   SystemStatus,
-  WorkerStatus,
 } from "./types";
 
-const API_BASE = "/api";
+const GRAPHQL_URL = "/api/graphql";
 
-async function request<T>(path: string, options?: RequestInit): Promise<T> {
+async function gql<T>(query: string, variables?: Record<string, unknown>): Promise<T> {
-  const response = await fetch(`${API_BASE}${path}`, {
+  const response = await fetch(GRAPHQL_URL, {
-    headers: {
+    method: "POST",
-      "Content-Type": "application/json",
+    headers: { "Content-Type": "application/json" },
-    },
+    body: JSON.stringify({ query, variables }),
-    ...options,
   });
 
-  if (!response.ok) {
+  const json = await response.json();
-    const error = await response.text();
+
-    throw new Error(`API error: ${response.status} - ${error}`);
+  if (json.errors?.length) {
+    throw new Error(json.errors[0].message);
   }
 
-  return response.json();
+  return json.data as T;
 }
 
 // Assets
 export async function getAssets(): Promise<MediaAsset[]> {
-  return request("/assets/");
+  const data = await gql<{ assets: MediaAsset[] }>(`
+    query {
+      assets {
+        id filename file_path status error_message file_size duration
+        video_codec audio_codec width height framerate bitrate
+        properties comments tags created_at updated_at
+      }
+    }
+  `);
+  return data.assets;
 }
 
 export async function getAsset(id: string): Promise<MediaAsset> {
-  return request(`/assets/${id}`);
+  const data = await gql<{ asset: MediaAsset }>(`
+    query($id: UUID!) {
+      asset(id: $id) {
+        id filename file_path status error_message file_size duration
+        video_codec audio_codec width height framerate bitrate
+        properties comments tags created_at updated_at
+      }
+    }
+  `, { id });
+  return data.asset;
 }
 
 export async function scanMediaFolder(): Promise<{
@@ -44,43 +61,95 @@ export async function scanMediaFolder(): Promise<{
   skipped: number;
   files: string[];
 }> {
-  return request("/assets/scan", {
+  const data = await gql<{ scan_media_folder: { found: number; registered: number; skipped: number; files: string[] } }>(`
-    method: "POST",
+    mutation {
-  });
+      scan_media_folder { found registered skipped files }
+    }
+  `);
+  return data.scan_media_folder;
 }
 
 // Presets
 export async function getPresets(): Promise<TranscodePreset[]> {
-  return request("/presets/");
+  const data = await gql<{ presets: TranscodePreset[] }>(`
+    query {
+      presets {
+        id name description is_builtin container
+        video_codec video_bitrate video_crf video_preset resolution framerate
+        audio_codec audio_bitrate audio_channels audio_samplerate
+        extra_args created_at updated_at
+      }
+    }
+  `);
+  return data.presets;
 }
 
 // Jobs
 export async function getJobs(): Promise<TranscodeJob[]> {
-  return request("/jobs/");
+  const data = await gql<{ jobs: TranscodeJob[] }>(`
+    query {
+      jobs {
+        id source_asset_id preset_id preset_snapshot trim_start trim_end
+        output_filename output_path output_asset_id status progress
+        current_frame current_time speed error_message celery_task_id
+        execution_arn priority created_at started_at completed_at
+      }
+    }
+  `);
+  return data.jobs;
 }
 
 export async function getJob(id: string): Promise<TranscodeJob> {
-  return request(`/jobs/${id}`);
+  const data = await gql<{ job: TranscodeJob }>(`
+    query($id: UUID!) {
+      job(id: $id) {
+        id source_asset_id preset_id preset_snapshot trim_start trim_end
+        output_filename output_path output_asset_id status progress
+        current_frame current_time speed error_message celery_task_id
+        execution_arn priority created_at started_at completed_at
+      }
+    }
+  `, { id });
+  return data.job;
 }
 
-export async function createJob(data: CreateJobRequest): Promise<TranscodeJob> {
+export async function createJob(req: CreateJobRequest): Promise<TranscodeJob> {
-  return request("/jobs/", {
+  const data = await gql<{ create_job: TranscodeJob }>(`
-    method: "POST",
+    mutation($input: CreateJobInput!) {
-    body: JSON.stringify(data),
+      create_job(input: $input) {
+        id source_asset_id status output_filename progress created_at
+      }
+    }
+  `, {
+    input: {
+      source_asset_id: req.source_asset_id,
+      preset_id: req.preset_id,
+      trim_start: req.trim_start,
+      trim_end: req.trim_end,
+      output_filename: req.output_filename ?? null,
+      priority: req.priority ?? 0,
+    },
   });
+  return data.create_job;
 }
 
 export async function cancelJob(id: string): Promise<TranscodeJob> {
-  return request(`/jobs/${id}/cancel`, {
+  const data = await gql<{ cancel_job: TranscodeJob }>(`
-    method: "POST",
+    mutation($id: UUID!) {
-  });
+      cancel_job(id: $id) {
+        id status
+      }
+    }
+  `, { id });
+  return data.cancel_job;
 }
 
 // System
 export async function getSystemStatus(): Promise<SystemStatus> {
-  return request("/system/status");
+  const data = await gql<{ system_status: SystemStatus }>(`
-}
+    query {
-
+      system_status { status version }
-export async function getWorkerStatus(): Promise<WorkerStatus> {
+    }
-  return request("/system/worker");
+  `);
+  return data.system_status;
 }