Add message journal, graceful restart, and clean repo for public release
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Three workstreams implemented:

W1 (Repo Split): Remove proprietary BloxServer files and docs, update
pyproject.toml URLs to public GitHub, clean doc references, add CI
workflow (.github/workflows/ci.yml) and CONTRIBUTING.md.

W2 (Message Journal): Add DispatchHook protocol for dispatch lifecycle
events, SQLite-backed MessageJournal with WAL mode for certified-mail
delivery guarantees (PENDING→DISPATCHED→ACKED/FAILED), integrate hooks
into StreamPump._dispatch_to_handlers(), add journal REST endpoints,
and aiosqlite dependency.

W3 (Hot Deployment): Add RestartOrchestrator for graceful restart with
queue drain and journal stats collection, SIGHUP signal handler in CLI,
POST /organism/restart endpoint, restart-aware app lifespan with journal
recovery on boot, and os.execv/subprocess re-exec for Unix/Windows.

All 439 tests pass (37 new tests for W2/W3).

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
dullfig 2026-01-28 22:27:38 -08:00
parent 6023e92ab0
commit d97c24b1dd
59 changed files with 1930 additions and 9739 deletions

70
.github/workflows/ci.yml vendored Normal file
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name: CI
on:
push:
branches: [main]
pull_request:
branches: [main]
jobs:
test:
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
python-version: ["3.11", "3.12", "3.13"]
steps:
- uses: actions/checkout@v4
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install -e ".[test]"
- name: Run tests
run: pytest tests/ -v --tb=short
lint:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.12"
- name: Install dev dependencies
run: |
python -m pip install --upgrade pip
pip install -e ".[dev]"
- name: Ruff check
run: ruff check xml_pipeline/ tests/
- name: Ruff format check
run: ruff format --check xml_pipeline/ tests/
typecheck:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.12"
- name: Install dev dependencies
run: |
python -m pip install --upgrade pip
pip install -e ".[dev]"
- name: MyPy
run: mypy xml_pipeline/ --ignore-missing-imports

5
.gitignore vendored
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@ -34,6 +34,5 @@ xml_pipeline/config/*.signed.xml
Thumbs.db Thumbs.db
.DS_Store .DS_Store
# BloxServer local dev # Journal database
bloxserver.db journal.db
bloxserver/.env

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CONTRIBUTING.md Normal file
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# Contributing to xml-pipeline
Thank you for considering contributing to xml-pipeline.
## Development Setup
```bash
git clone https://github.com/xml-pipeline/xml-pipeline.git
cd xml-pipeline
python -m venv .venv
source .venv/bin/activate # Linux/macOS
# .venv\Scripts\activate # Windows
pip install -e ".[dev]"
```
## Running Tests
```bash
pytest tests/ -v
```
Skip slow/integration tests:
```bash
pytest tests/ -v -m "not slow"
```
## Code Style
This project uses **ruff** for linting and formatting, **mypy** for type checking.
```bash
ruff check xml_pipeline/ tests/
ruff format xml_pipeline/ tests/
mypy xml_pipeline/
```
All functions must have type hints. Async handlers use `async def`.
## Pull Request Process
1. Fork the repo and create a feature branch from `main`.
2. Write tests for new functionality in `tests/`.
3. Ensure `pytest`, `ruff check`, and `mypy` pass.
4. Keep commits focused and write clear commit messages.
5. Open a PR against `main` with a description of what changed and why.
## Architecture
Read `CLAUDE.md` for the full architecture overview. Key principles:
- **XML is the sovereign wire format** -- all messages are validated XML envelopes.
- **Handlers are untrusted** -- the pump enforces identity, routing, and thread isolation.
- **Pipeline steps are composable** -- add new processing stages by inserting async functions.
- **Async-first** -- everything is `async def`, powered by aiostream.
## Adding a New Pipeline Step
1. Create `xml_pipeline/message_bus/steps/your_step.py`.
2. Implement `async def your_step(state: MessageState) -> MessageState`.
3. Insert into the pipeline in `stream_pump.py` `build_pipeline()`.
4. Add tests in `tests/test_pipeline_steps.py`.
## Adding a New Handler
1. Define a `@xmlify @dataclass` payload in your handler module.
2. Write an `async def handle_*(payload, metadata) -> HandlerResponse | None`.
3. Register in `organism.yaml` under `listeners`.
4. See `docs/handler-contract-v2.1.md` for the full contract.
## License
By contributing, you agree that your contributions will be licensed under the MIT License.

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# BloxServer API Environment Variables
# Copy this file to .env and fill in the values
# =============================================================================
# Environment
# =============================================================================
ENV=development
# ENV=production
# =============================================================================
# Database (PostgreSQL)
# =============================================================================
DATABASE_URL=postgresql+asyncpg://postgres:postgres@localhost:5432/bloxserver
# Set to true to auto-create tables on startup (disable in production)
AUTO_CREATE_TABLES=true
# =============================================================================
# Clerk Authentication
# =============================================================================
CLERK_ISSUER=https://your-clerk-instance.clerk.accounts.dev
CLERK_AUDIENCE=your-clerk-audience
# =============================================================================
# Stripe Billing
# =============================================================================
STRIPE_SECRET_KEY=sk_test_...
STRIPE_WEBHOOK_SECRET=whsec_...
# =============================================================================
# API Key Encryption
# =============================================================================
# Generate with: python -c "from cryptography.fernet import Fernet; print(Fernet.generate_key().decode())"
API_KEY_ENCRYPTION_KEY=your-fernet-key-here
# =============================================================================
# CORS
# =============================================================================
CORS_ORIGINS=http://localhost:3000,https://app.openblox.ai
# =============================================================================
# Webhooks
# =============================================================================
WEBHOOK_BASE_URL=https://api.openblox.ai/webhooks
# =============================================================================
# Redis (optional, for caching/rate limiting)
# =============================================================================
# REDIS_URL=redis://localhost:6379
# =============================================================================
# Docs
# =============================================================================
ENABLE_DOCS=true

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# BloxServer API Dockerfile
# Multi-stage build for smaller production image
# =============================================================================
# Build stage
# =============================================================================
FROM python:3.12-slim as builder
WORKDIR /app
# Install build dependencies
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential \
&& rm -rf /var/lib/apt/lists/*
# Copy requirements first for layer caching
COPY requirements.txt .
RUN pip wheel --no-cache-dir --wheel-dir /app/wheels -r requirements.txt
# =============================================================================
# Production stage
# =============================================================================
FROM python:3.12-slim as production
WORKDIR /app
# Create non-root user
RUN groupadd --gid 1000 bloxserver \
&& useradd --uid 1000 --gid bloxserver --shell /bin/bash --create-home bloxserver
# Install runtime dependencies
RUN apt-get update && apt-get install -y --no-install-recommends \
curl \
&& rm -rf /var/lib/apt/lists/*
# Copy wheels from builder and install
COPY --from=builder /app/wheels /wheels
RUN pip install --no-cache-dir /wheels/* && rm -rf /wheels
# Copy application code
COPY --chown=bloxserver:bloxserver . /app/bloxserver
# Set Python path
ENV PYTHONPATH=/app
ENV PYTHONUNBUFFERED=1
# Switch to non-root user
USER bloxserver
# Health check
HEALTHCHECK --interval=30s --timeout=5s --start-period=5s --retries=3 \
CMD curl -f http://localhost:8000/health/live || exit 1
# Expose port
EXPOSE 8000
# Run with uvicorn
CMD ["uvicorn", "bloxserver.api.main:app", "--host", "0.0.0.0", "--port", "8000"]

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# BloxServer API
Backend API for BloxServer (OpenBlox.ai) - Visual AI Agent Workflow Builder.
## Quick Start
### With Docker Compose (Recommended)
```bash
cd bloxserver
# Start PostgreSQL, Redis, and API
docker-compose up -d
# Check logs
docker-compose logs -f api
# API available at http://localhost:8000
# Docs at http://localhost:8000/docs
```
### Local Development
```bash
cd bloxserver
# Create virtual environment
python -m venv .venv
source .venv/bin/activate # Linux/macOS
# .venv\Scripts\activate # Windows
# Install dependencies
pip install -r requirements.txt
# Copy environment variables
cp .env.example .env
# Edit .env with your settings
# Start PostgreSQL and Redis (or use Docker)
docker-compose up -d postgres redis
# Run the API
python -m bloxserver.api.main
# Or with uvicorn directly:
uvicorn bloxserver.api.main:app --reload
```
## API Endpoints
### Health
- `GET /health` - Basic health check
- `GET /health/ready` - Readiness check (includes DB)
- `GET /health/live` - Liveness check
### Flows
- `GET /api/v1/flows` - List flows
- `POST /api/v1/flows` - Create flow
- `GET /api/v1/flows/{id}` - Get flow
- `PATCH /api/v1/flows/{id}` - Update flow
- `DELETE /api/v1/flows/{id}` - Delete flow
- `POST /api/v1/flows/{id}/start` - Start flow
- `POST /api/v1/flows/{id}/stop` - Stop flow
### Triggers
- `GET /api/v1/flows/{flow_id}/triggers` - List triggers
- `POST /api/v1/flows/{flow_id}/triggers` - Create trigger
- `GET /api/v1/flows/{flow_id}/triggers/{id}` - Get trigger
- `DELETE /api/v1/flows/{flow_id}/triggers/{id}` - Delete trigger
- `POST /api/v1/flows/{flow_id}/triggers/{id}/regenerate-token` - Regenerate webhook token
### Executions
- `GET /api/v1/flows/{flow_id}/executions` - List executions
- `GET /api/v1/flows/{flow_id}/executions/{id}` - Get execution
- `POST /api/v1/flows/{flow_id}/executions/run` - Manual trigger
- `GET /api/v1/flows/{flow_id}/executions/stats` - Get stats
### Webhooks
- `POST /webhooks/{token}` - Trigger flow via webhook
- `GET /webhooks/{token}/test` - Test webhook token
## Project Structure
```
bloxserver/
├── api/
│ ├── __init__.py
│ ├── main.py # FastAPI app entry point
│ ├── dependencies.py # Auth, DB session dependencies
│ ├── schemas.py # Pydantic request/response models
│ ├── models/
│ │ ├── __init__.py
│ │ ├── database.py # SQLAlchemy engine/session
│ │ └── tables.py # ORM table definitions
│ └── routes/
│ ├── __init__.py
│ ├── flows.py # Flow CRUD
│ ├── triggers.py # Trigger CRUD
│ ├── executions.py # Execution history
│ ├── webhooks.py # Webhook handler
│ └── health.py # Health checks
├── requirements.txt
├── Dockerfile
├── docker-compose.yml
├── .env.example
└── README.md
```
## Authentication
Uses Clerk for JWT authentication. All `/api/v1/*` endpoints require a valid JWT.
```bash
curl -H "Authorization: Bearer <clerk-jwt>" \
http://localhost:8000/api/v1/flows
```
## Environment Variables
See `.env.example` for all configuration options.
Key variables:
- `DATABASE_URL` - PostgreSQL connection string
- `CLERK_ISSUER` - Clerk JWT issuer URL
- `STRIPE_SECRET_KEY` - Stripe API key
- `API_KEY_ENCRYPTION_KEY` - Fernet key for encrypting user API keys
## Database Migrations
Using Alembic for migrations (not yet set up):
```bash
# Initialize (first time)
alembic init alembic
# Create migration
alembic revision --autogenerate -m "description"
# Apply migrations
alembic upgrade head
```
## Testing
```bash
# Install test dependencies
pip install pytest pytest-asyncio httpx
# Run tests
pytest tests/ -v
```
## Deployment
### Railway / Render / Fly.io
1. Connect your repo
2. Set environment variables
3. Deploy
### Kubernetes
```yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: bloxserver-api
spec:
replicas: 3
template:
spec:
containers:
- name: api
image: your-registry/bloxserver-api:latest
ports:
- containerPort: 8000
env:
- name: DATABASE_URL
valueFrom:
secretKeyRef:
name: bloxserver-secrets
key: database-url
livenessProbe:
httpGet:
path: /health/live
port: 8000
readinessProbe:
httpGet:
path: /health/ready
port: 8000
```
## Next Steps
- [ ] Alembic migrations setup
- [ ] Stripe webhook handlers
- [ ] Redis rate limiting
- [ ] Container orchestration integration
- [ ] WebSocket for real-time logs

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"""
BloxServer - Visual AI Agent Workflow Builder
SaaS backend for OpenBlox.ai
"""
__version__ = "0.1.0"

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# A generic, single database configuration.
[alembic]
# path to migration scripts.
# this is typically a path given in POSIX (e.g. forward slashes)
# format, relative to the token %(here)s which refers to the location of this
# ini file
script_location = %(here)s/alembic
# template used to generate migration file names; The default value is %%(rev)s_%%(slug)s
# Uncomment the line below if you want the files to be prepended with date and time
# see https://alembic.sqlalchemy.org/en/latest/tutorial.html#editing-the-ini-file
# for all available tokens
# file_template = %%(year)d_%%(month).2d_%%(day).2d_%%(hour).2d%%(minute).2d-%%(rev)s_%%(slug)s
# Or organize into date-based subdirectories (requires recursive_version_locations = true)
# file_template = %%(year)d/%%(month).2d/%%(day).2d_%%(hour).2d%%(minute).2d_%%(second).2d_%%(rev)s_%%(slug)s
# sys.path path, will be prepended to sys.path if present.
# defaults to the current working directory. for multiple paths, the path separator
# is defined by "path_separator" below.
prepend_sys_path = .
# timezone to use when rendering the date within the migration file
# as well as the filename.
# If specified, requires the tzdata library which can be installed by adding
# `alembic[tz]` to the pip requirements.
# string value is passed to ZoneInfo()
# leave blank for localtime
# timezone =
# max length of characters to apply to the "slug" field
# truncate_slug_length = 40
# set to 'true' to run the environment during
# the 'revision' command, regardless of autogenerate
# revision_environment = false
# set to 'true' to allow .pyc and .pyo files without
# a source .py file to be detected as revisions in the
# versions/ directory
# sourceless = false
# version location specification; This defaults
# to <script_location>/versions. When using multiple version
# directories, initial revisions must be specified with --version-path.
# The path separator used here should be the separator specified by "path_separator"
# below.
# version_locations = %(here)s/bar:%(here)s/bat:%(here)s/alembic/versions
# path_separator; This indicates what character is used to split lists of file
# paths, including version_locations and prepend_sys_path within configparser
# files such as alembic.ini.
# The default rendered in new alembic.ini files is "os", which uses os.pathsep
# to provide os-dependent path splitting.
#
# Note that in order to support legacy alembic.ini files, this default does NOT
# take place if path_separator is not present in alembic.ini. If this
# option is omitted entirely, fallback logic is as follows:
#
# 1. Parsing of the version_locations option falls back to using the legacy
# "version_path_separator" key, which if absent then falls back to the legacy
# behavior of splitting on spaces and/or commas.
# 2. Parsing of the prepend_sys_path option falls back to the legacy
# behavior of splitting on spaces, commas, or colons.
#
# Valid values for path_separator are:
#
# path_separator = :
# path_separator = ;
# path_separator = space
# path_separator = newline
#
# Use os.pathsep. Default configuration used for new projects.
path_separator = os
# set to 'true' to search source files recursively
# in each "version_locations" directory
# new in Alembic version 1.10
# recursive_version_locations = false
# the output encoding used when revision files
# are written from script.py.mako
# output_encoding = utf-8
# database URL. This is consumed by the user-maintained env.py script only.
# other means of configuring database URLs may be customized within the env.py
# file.
# Database URL is loaded from DATABASE_URL environment variable in env.py
# This placeholder is not used
sqlalchemy.url = postgresql://localhost/bloxserver
[post_write_hooks]
# post_write_hooks defines scripts or Python functions that are run
# on newly generated revision scripts. See the documentation for further
# detail and examples
# format using "black" - use the console_scripts runner, against the "black" entrypoint
# hooks = black
# black.type = console_scripts
# black.entrypoint = black
# black.options = -l 79 REVISION_SCRIPT_FILENAME
# lint with attempts to fix using "ruff" - use the module runner, against the "ruff" module
# hooks = ruff
# ruff.type = module
# ruff.module = ruff
# ruff.options = check --fix REVISION_SCRIPT_FILENAME
# Alternatively, use the exec runner to execute a binary found on your PATH
# hooks = ruff
# ruff.type = exec
# ruff.executable = ruff
# ruff.options = check --fix REVISION_SCRIPT_FILENAME
# Logging configuration. This is also consumed by the user-maintained
# env.py script only.
[loggers]
keys = root,sqlalchemy,alembic
[handlers]
keys = console
[formatters]
keys = generic
[logger_root]
level = WARNING
handlers = console
qualname =
[logger_sqlalchemy]
level = WARNING
handlers =
qualname = sqlalchemy.engine
[logger_alembic]
level = INFO
handlers =
qualname = alembic
[handler_console]
class = StreamHandler
args = (sys.stderr,)
level = NOTSET
formatter = generic
[formatter_generic]
format = %(levelname)-5.5s [%(name)s] %(message)s
datefmt = %H:%M:%S

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Generic single-database configuration.

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"""
Alembic migration environment.
Configured for async SQLAlchemy with PostgreSQL/SQLite.
"""
from __future__ import annotations
import os
import sys
from logging.config import fileConfig
from sqlalchemy import engine_from_config, pool
from alembic import context
# Add parent directory to path so 'bloxserver' package is importable
# bloxserver/ is at xml-pipeline/bloxserver/, so we need xml-pipeline/ on the path
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
# Import models to register them with Base.metadata
from bloxserver.api.models.database import Base
from bloxserver.api.models import tables # noqa: F401 - imports register models
# Alembic Config object
config = context.config
# Setup logging from alembic.ini
if config.config_file_name is not None:
fileConfig(config.config_file_name)
# Target metadata for autogenerate
target_metadata = Base.metadata
def get_url() -> str:
"""
Get database URL from environment.
Converts async URLs (postgresql+asyncpg://) to sync (postgresql://)
because Alembic runs migrations synchronously.
"""
url = os.getenv(
"DATABASE_URL",
"sqlite:///./bloxserver.db",
)
# Convert async driver to sync for Alembic
if url.startswith("postgresql+asyncpg://"):
url = url.replace("postgresql+asyncpg://", "postgresql://", 1)
elif url.startswith("sqlite+aiosqlite://"):
url = url.replace("sqlite+aiosqlite://", "sqlite://", 1)
return url
def run_migrations_offline() -> None:
"""
Run migrations in 'offline' mode.
Generates SQL script without connecting to database.
Useful for reviewing migrations before applying.
"""
url = get_url()
context.configure(
url=url,
target_metadata=target_metadata,
literal_binds=True,
dialect_opts={"paramstyle": "named"},
compare_type=True,
compare_server_default=True,
)
with context.begin_transaction():
context.run_migrations()
def run_migrations_online() -> None:
"""
Run migrations in 'online' mode.
Connects to database and applies migrations directly.
"""
configuration = config.get_section(config.config_ini_section, {})
configuration["sqlalchemy.url"] = get_url()
connectable = engine_from_config(
configuration,
prefix="sqlalchemy.",
poolclass=pool.NullPool,
)
with connectable.connect() as connection:
context.configure(
connection=connection,
target_metadata=target_metadata,
compare_type=True,
compare_server_default=True,
)
with context.begin_transaction():
context.run_migrations()
if context.is_offline_mode():
run_migrations_offline()
else:
run_migrations_online()

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"""${message}
Revision ID: ${up_revision}
Revises: ${down_revision | comma,n}
Create Date: ${create_date}
"""
from typing import Sequence, Union
from alembic import op
import sqlalchemy as sa
${imports if imports else ""}
# revision identifiers, used by Alembic.
revision: str = ${repr(up_revision)}
down_revision: Union[str, Sequence[str], None] = ${repr(down_revision)}
branch_labels: Union[str, Sequence[str], None] = ${repr(branch_labels)}
depends_on: Union[str, Sequence[str], None] = ${repr(depends_on)}
def upgrade() -> None:
"""Upgrade schema."""
${upgrades if upgrades else "pass"}
def downgrade() -> None:
"""Downgrade schema."""
${downgrades if downgrades else "pass"}

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"""initial schema
Revision ID: 7136cc209524
Revises:
Create Date: 2026-01-26 07:21:39.594527
"""
from typing import Sequence, Union
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision: str = '7136cc209524'
down_revision: Union[str, Sequence[str], None] = None
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
"""Upgrade schema."""
# ### commands auto generated by Alembic - please adjust! ###
op.create_table('stripe_events',
sa.Column('event_id', sa.String(length=255), nullable=False),
sa.Column('event_type', sa.String(length=100), nullable=False),
sa.Column('processed_at', sa.DateTime(timezone=True), server_default=sa.text('(CURRENT_TIMESTAMP)'), nullable=False),
sa.Column('payload', sa.JSON(), nullable=True),
sa.PrimaryKeyConstraint('event_id')
)
op.create_index('idx_stripe_events_processed', 'stripe_events', ['processed_at'], unique=False)
op.create_table('users',
sa.Column('id', sa.UUID(), nullable=False),
sa.Column('clerk_id', sa.String(length=255), nullable=False),
sa.Column('email', sa.String(length=255), nullable=False),
sa.Column('name', sa.String(length=255), nullable=True),
sa.Column('avatar_url', sa.Text(), nullable=True),
sa.Column('stripe_customer_id', sa.String(length=255), nullable=True),
sa.Column('stripe_subscription_id', sa.String(length=255), nullable=True),
sa.Column('stripe_subscription_item_id', sa.String(length=255), nullable=True),
sa.Column('tier', sa.Enum('FREE', 'PRO', 'ENTERPRISE', 'HIGH_FREQUENCY', name='tier'), nullable=False),
sa.Column('billing_status', sa.Enum('ACTIVE', 'TRIALING', 'PAST_DUE', 'CANCELED', 'CANCELING', name='billingstatus'), nullable=False),
sa.Column('trial_ends_at', sa.DateTime(timezone=True), nullable=True),
sa.Column('current_period_start', sa.DateTime(timezone=True), nullable=True),
sa.Column('current_period_end', sa.DateTime(timezone=True), nullable=True),
sa.Column('created_at', sa.DateTime(timezone=True), server_default=sa.text('(CURRENT_TIMESTAMP)'), nullable=False),
sa.Column('updated_at', sa.DateTime(timezone=True), server_default=sa.text('(CURRENT_TIMESTAMP)'), nullable=False),
sa.PrimaryKeyConstraint('id'),
sa.UniqueConstraint('clerk_id'),
sa.UniqueConstraint('stripe_customer_id')
)
op.create_index('idx_users_clerk_id', 'users', ['clerk_id'], unique=False)
op.create_index('idx_users_stripe_customer', 'users', ['stripe_customer_id'], unique=False)
op.create_table('flows',
sa.Column('id', sa.UUID(), nullable=False),
sa.Column('user_id', sa.UUID(), nullable=False),
sa.Column('name', sa.String(length=100), nullable=False),
sa.Column('description', sa.String(length=500), nullable=True),
sa.Column('organism_yaml', sa.Text(), nullable=False),
sa.Column('canvas_state', sa.JSON(), nullable=True),
sa.Column('status', sa.Enum('STOPPED', 'STARTING', 'RUNNING', 'STOPPING', 'ERROR', name='flowstatus'), nullable=False),
sa.Column('container_id', sa.String(length=255), nullable=True),
sa.Column('error_message', sa.Text(), nullable=True),
sa.Column('created_at', sa.DateTime(timezone=True), server_default=sa.text('(CURRENT_TIMESTAMP)'), nullable=False),
sa.Column('updated_at', sa.DateTime(timezone=True), server_default=sa.text('(CURRENT_TIMESTAMP)'), nullable=False),
sa.ForeignKeyConstraint(['user_id'], ['users.id'], ondelete='CASCADE'),
sa.PrimaryKeyConstraint('id')
)
op.create_index('idx_flows_status', 'flows', ['status'], unique=False)
op.create_index('idx_flows_user_id', 'flows', ['user_id'], unique=False)
op.create_table('usage_records',
sa.Column('id', sa.UUID(), nullable=False),
sa.Column('user_id', sa.UUID(), nullable=False),
sa.Column('period_start', sa.DateTime(timezone=True), nullable=False),
sa.Column('workflow_runs', sa.Integer(), nullable=False),
sa.Column('llm_tokens_in', sa.Integer(), nullable=False),
sa.Column('llm_tokens_out', sa.Integer(), nullable=False),
sa.Column('wasm_cpu_seconds', sa.Numeric(precision=10, scale=2), nullable=False),
sa.Column('storage_gb_hours', sa.Numeric(precision=10, scale=2), nullable=False),
sa.Column('last_synced_at', sa.DateTime(timezone=True), nullable=True),
sa.Column('last_synced_runs', sa.Integer(), nullable=False),
sa.Column('created_at', sa.DateTime(timezone=True), server_default=sa.text('(CURRENT_TIMESTAMP)'), nullable=False),
sa.Column('updated_at', sa.DateTime(timezone=True), server_default=sa.text('(CURRENT_TIMESTAMP)'), nullable=False),
sa.ForeignKeyConstraint(['user_id'], ['users.id'], ondelete='CASCADE'),
sa.PrimaryKeyConstraint('id')
)
op.create_index('idx_usage_user_period', 'usage_records', ['user_id', 'period_start'], unique=True)
op.create_table('user_api_keys',
sa.Column('id', sa.UUID(), nullable=False),
sa.Column('user_id', sa.UUID(), nullable=False),
sa.Column('provider', sa.String(length=50), nullable=False),
sa.Column('encrypted_key', sa.LargeBinary(), nullable=False),
sa.Column('key_hint', sa.String(length=20), nullable=True),
sa.Column('is_valid', sa.Boolean(), nullable=False),
sa.Column('last_error', sa.String(length=255), nullable=True),
sa.Column('last_used_at', sa.DateTime(timezone=True), nullable=True),
sa.Column('created_at', sa.DateTime(timezone=True), server_default=sa.text('(CURRENT_TIMESTAMP)'), nullable=False),
sa.ForeignKeyConstraint(['user_id'], ['users.id'], ondelete='CASCADE'),
sa.PrimaryKeyConstraint('id')
)
op.create_index('idx_user_api_keys_user_provider', 'user_api_keys', ['user_id', 'provider'], unique=True)
op.create_table('triggers',
sa.Column('id', sa.UUID(), nullable=False),
sa.Column('flow_id', sa.UUID(), nullable=False),
sa.Column('type', sa.Enum('WEBHOOK', 'SCHEDULE', 'MANUAL', name='triggertype'), nullable=False),
sa.Column('name', sa.String(length=100), nullable=False),
sa.Column('config', sa.JSON(), nullable=False),
sa.Column('webhook_token', sa.String(length=64), nullable=True),
sa.Column('webhook_url', sa.Text(), nullable=True),
sa.Column('created_at', sa.DateTime(timezone=True), server_default=sa.text('(CURRENT_TIMESTAMP)'), nullable=False),
sa.ForeignKeyConstraint(['flow_id'], ['flows.id'], ondelete='CASCADE'),
sa.PrimaryKeyConstraint('id'),
sa.UniqueConstraint('webhook_token')
)
op.create_index('idx_triggers_flow_id', 'triggers', ['flow_id'], unique=False)
op.create_index('idx_triggers_webhook_token', 'triggers', ['webhook_token'], unique=False)
op.create_table('executions',
sa.Column('id', sa.UUID(), nullable=False),
sa.Column('flow_id', sa.UUID(), nullable=False),
sa.Column('trigger_id', sa.UUID(), nullable=True),
sa.Column('trigger_type', sa.Enum('WEBHOOK', 'SCHEDULE', 'MANUAL', name='triggertype'), nullable=False),
sa.Column('status', sa.Enum('RUNNING', 'SUCCESS', 'ERROR', 'TIMEOUT', name='executionstatus'), nullable=False),
sa.Column('error_message', sa.Text(), nullable=True),
sa.Column('input_payload', sa.Text(), nullable=True),
sa.Column('output_payload', sa.Text(), nullable=True),
sa.Column('started_at', sa.DateTime(timezone=True), server_default=sa.text('(CURRENT_TIMESTAMP)'), nullable=False),
sa.Column('completed_at', sa.DateTime(timezone=True), nullable=True),
sa.Column('duration_ms', sa.Integer(), nullable=True),
sa.ForeignKeyConstraint(['flow_id'], ['flows.id'], ondelete='CASCADE'),
sa.ForeignKeyConstraint(['trigger_id'], ['triggers.id'], ondelete='SET NULL'),
sa.PrimaryKeyConstraint('id')
)
op.create_index('idx_executions_flow_id', 'executions', ['flow_id'], unique=False)
op.create_index('idx_executions_started_at', 'executions', ['started_at'], unique=False)
op.create_index('idx_executions_status', 'executions', ['status'], unique=False)
# ### end Alembic commands ###
def downgrade() -> None:
"""Downgrade schema."""
# ### commands auto generated by Alembic - please adjust! ###
op.drop_index('idx_executions_status', table_name='executions')
op.drop_index('idx_executions_started_at', table_name='executions')
op.drop_index('idx_executions_flow_id', table_name='executions')
op.drop_table('executions')
op.drop_index('idx_triggers_webhook_token', table_name='triggers')
op.drop_index('idx_triggers_flow_id', table_name='triggers')
op.drop_table('triggers')
op.drop_index('idx_user_api_keys_user_provider', table_name='user_api_keys')
op.drop_table('user_api_keys')
op.drop_index('idx_usage_user_period', table_name='usage_records')
op.drop_table('usage_records')
op.drop_index('idx_flows_user_id', table_name='flows')
op.drop_index('idx_flows_status', table_name='flows')
op.drop_table('flows')
op.drop_index('idx_users_stripe_customer', table_name='users')
op.drop_index('idx_users_clerk_id', table_name='users')
op.drop_table('users')
op.drop_index('idx_stripe_events_processed', table_name='stripe_events')
op.drop_table('stripe_events')
# ### end Alembic commands ###

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"""add edge_mappings table
Revision ID: fedaf93bff56
Revises: 7136cc209524
Create Date: 2026-01-26 07:22:32.557309
"""
from typing import Sequence, Union
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision: str = 'fedaf93bff56'
down_revision: Union[str, Sequence[str], None] = '7136cc209524'
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
"""Upgrade schema."""
op.create_table('edge_mappings',
sa.Column('id', sa.UUID(), nullable=False),
sa.Column('flow_id', sa.UUID(), nullable=False),
sa.Column('from_node', sa.String(length=100), nullable=False),
sa.Column('to_node', sa.String(length=100), nullable=False),
sa.Column('confidence', sa.Numeric(precision=3, scale=2), nullable=True),
sa.Column('level', sa.Enum('HIGH', 'MEDIUM', 'LOW', name='confidencelevel'), nullable=True),
sa.Column('analysis_method', sa.String(length=20), nullable=True),
sa.Column('proposed_mapping', sa.JSON(), nullable=True),
sa.Column('user_mapping', sa.JSON(), nullable=True),
sa.Column('user_confirmed', sa.Boolean(), nullable=False),
sa.Column('analyzed_at', sa.DateTime(timezone=True), nullable=True),
sa.Column('confirmed_at', sa.DateTime(timezone=True), nullable=True),
sa.Column('created_at', sa.DateTime(timezone=True), server_default=sa.text('(CURRENT_TIMESTAMP)'), nullable=False),
sa.Column('updated_at', sa.DateTime(timezone=True), server_default=sa.text('(CURRENT_TIMESTAMP)'), nullable=False),
sa.ForeignKeyConstraint(['flow_id'], ['flows.id'], ondelete='CASCADE'),
sa.PrimaryKeyConstraint('id')
)
op.create_index('idx_edge_mappings_edge', 'edge_mappings', ['flow_id', 'from_node', 'to_node'], unique=True)
op.create_index('idx_edge_mappings_flow', 'edge_mappings', ['flow_id'], unique=False)
def downgrade() -> None:
"""Downgrade schema."""
op.drop_index('idx_edge_mappings_flow', table_name='edge_mappings')
op.drop_index('idx_edge_mappings_edge', table_name='edge_mappings')
op.drop_table('edge_mappings')

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"""BloxServer API package."""

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@ -1,236 +0,0 @@
"""
FastAPI dependencies for authentication and database access.
Uses Clerk for JWT validation.
"""
from __future__ import annotations
import os
from typing import Annotated
from uuid import UUID
import httpx
from fastapi import Depends, HTTPException, Request, status
from fastapi.security import HTTPAuthorizationCredentials, HTTPBearer
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
from bloxserver.api.models.database import get_db
from bloxserver.api.models.tables import UserRecord
# Dev mode - skip auth for local testing
DEV_MODE = os.getenv("ENV", "development") == "development" and not os.getenv("CLERK_ISSUER")
# Clerk configuration
CLERK_ISSUER = os.getenv("CLERK_ISSUER", "")
CLERK_JWKS_URL = f"{CLERK_ISSUER}/.well-known/jwks.json" if CLERK_ISSUER else ""
# Security scheme
security = HTTPBearer(auto_error=False)
# =============================================================================
# JWT Validation (Clerk)
# =============================================================================
async def get_clerk_jwks() -> dict:
"""Fetch Clerk's JWKS for JWT validation."""
async with httpx.AsyncClient() as client:
response = await client.get(CLERK_JWKS_URL)
response.raise_for_status()
return response.json()
async def validate_clerk_token(token: str) -> dict:
"""
Validate a Clerk JWT token and return the payload.
In production, use a proper JWT library with caching.
This is a simplified version for the scaffold.
"""
import jwt
from jwt import PyJWKClient
try:
# Get signing key from Clerk's JWKS
jwks_client = PyJWKClient(CLERK_JWKS_URL)
signing_key = jwks_client.get_signing_key_from_jwt(token)
# Decode and validate
payload = jwt.decode(
token,
signing_key.key,
algorithms=["RS256"],
audience=os.getenv("CLERK_AUDIENCE"),
issuer=CLERK_ISSUER,
)
return payload
except jwt.ExpiredSignatureError:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="Token has expired",
)
except jwt.InvalidTokenError as e:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail=f"Invalid token: {e}",
)
# =============================================================================
# Current User Dependency
# =============================================================================
class CurrentUser:
"""Authenticated user context."""
def __init__(self, user: UserRecord, clerk_payload: dict):
self.user = user
self.clerk_payload = clerk_payload
@property
def id(self) -> UUID:
return self.user.id
@property
def clerk_id(self) -> str:
return self.user.clerk_id
@property
def email(self) -> str:
return self.user.email
@property
def tier(self) -> str:
return self.user.tier.value
async def get_current_user(
request: Request,
credentials: Annotated[HTTPAuthorizationCredentials | None, Depends(security)],
db: Annotated[AsyncSession, Depends(get_db)],
) -> CurrentUser:
"""
Dependency that validates the JWT and returns the current user.
Creates the user record if this is their first request (synced from Clerk).
In DEV_MODE without Clerk configured, returns a test user.
"""
# Dev mode - create/return a test user without auth
if DEV_MODE:
dev_clerk_id = "dev_user_001"
result = await db.execute(
select(UserRecord).where(UserRecord.clerk_id == dev_clerk_id)
)
user = result.scalar_one_or_none()
if not user:
from bloxserver.api.models.tables import Tier
user = UserRecord(
clerk_id=dev_clerk_id,
email="dev@localhost",
name="Dev User",
tier=Tier.PRO, # Give dev user Pro access
)
db.add(user)
await db.flush()
return CurrentUser(user=user, clerk_payload={"sub": dev_clerk_id, "dev": True})
# Production mode - require Clerk auth
if not credentials:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="Missing authentication token",
headers={"WWW-Authenticate": "Bearer"},
)
# Validate JWT
payload = await validate_clerk_token(credentials.credentials)
clerk_id = payload.get("sub")
if not clerk_id:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="Invalid token: missing subject",
)
# Look up or create user
result = await db.execute(
select(UserRecord).where(UserRecord.clerk_id == clerk_id)
)
user = result.scalar_one_or_none()
if not user:
# First login - create user record from Clerk data
user = UserRecord(
clerk_id=clerk_id,
email=payload.get("email", f"{clerk_id}@unknown"),
name=payload.get("name"),
avatar_url=payload.get("image_url"),
)
db.add(user)
await db.flush() # Get the ID without committing
return CurrentUser(user=user, clerk_payload=payload)
# Type alias for cleaner route signatures
AuthenticatedUser = Annotated[CurrentUser, Depends(get_current_user)]
DbSession = Annotated[AsyncSession, Depends(get_db)]
# =============================================================================
# Optional Auth (for public endpoints)
# =============================================================================
async def get_optional_user(
request: Request,
credentials: Annotated[HTTPAuthorizationCredentials | None, Depends(security)],
db: Annotated[AsyncSession, Depends(get_db)],
) -> CurrentUser | None:
"""
Like get_current_user, but returns None instead of raising if not authenticated.
"""
if not credentials:
return None
try:
return await get_current_user(request, credentials, db)
except HTTPException:
return None
OptionalUser = Annotated[CurrentUser | None, Depends(get_optional_user)]
# =============================================================================
# Tier Checks
# =============================================================================
def require_tier(*allowed_tiers: str):
"""
Dependency factory that requires the user to be on one of the allowed tiers.
Usage:
@router.post("/wasm", dependencies=[Depends(require_tier("pro", "enterprise"))])
"""
async def check_tier(user: AuthenticatedUser) -> None:
if user.tier not in allowed_tiers:
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail=f"This feature requires one of: {', '.join(allowed_tiers)}",
)
return check_tier
RequirePro = Depends(require_tier("pro", "enterprise", "high_frequency"))
RequireEnterprise = Depends(require_tier("enterprise", "high_frequency"))

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@ -1,166 +0,0 @@
"""
BloxServer API - FastAPI Application
Main entry point for the BloxServer backend API.
"""
from __future__ import annotations
import os
from contextlib import asynccontextmanager
from typing import AsyncGenerator
from fastapi import FastAPI, Request, status
from fastapi.exceptions import RequestValidationError
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import JSONResponse
from bloxserver.api.models.database import init_db
from bloxserver.api.routes import executions, flows, health, triggers, webhooks
from bloxserver.api.schemas import ApiError
@asynccontextmanager
async def lifespan(app: FastAPI) -> AsyncGenerator[None, None]:
"""Application lifespan - startup and shutdown events."""
# Startup
print("Starting BloxServer API...")
# Initialize database tables
if os.getenv("AUTO_CREATE_TABLES", "true").lower() == "true":
await init_db()
print("Database tables initialized")
yield
# Shutdown
print("Shutting down BloxServer API...")
# Create FastAPI app
app = FastAPI(
title="BloxServer API",
description="Backend API for BloxServer - Visual AI Agent Workflow Builder",
version="0.1.0",
lifespan=lifespan,
docs_url="/docs" if os.getenv("ENABLE_DOCS", "true").lower() == "true" else None,
redoc_url="/redoc" if os.getenv("ENABLE_DOCS", "true").lower() == "true" else None,
)
# =============================================================================
# CORS Middleware
# =============================================================================
# Allowed origins (configure via environment)
CORS_ORIGINS = os.getenv(
"CORS_ORIGINS",
"http://localhost:3000,https://app.openblox.ai",
).split(",")
app.add_middleware(
CORSMiddleware,
allow_origins=CORS_ORIGINS,
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# =============================================================================
# Exception Handlers
# =============================================================================
@app.exception_handler(RequestValidationError)
async def validation_exception_handler(
request: Request, exc: RequestValidationError
) -> JSONResponse:
"""Convert validation errors to standard API error format."""
errors = exc.errors()
details = {
".".join(str(loc) for loc in err["loc"]): err["msg"]
for err in errors
}
return JSONResponse(
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
content=ApiError(
code="validation_error",
message="Request validation failed",
details=details,
).model_dump(by_alias=True),
)
@app.exception_handler(Exception)
async def general_exception_handler(
request: Request, exc: Exception
) -> JSONResponse:
"""Catch-all exception handler."""
# In production, don't expose internal errors
if os.getenv("ENV", "development") == "production":
return JSONResponse(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
content=ApiError(
code="internal_error",
message="An unexpected error occurred",
).model_dump(by_alias=True),
)
# In development, include error details
return JSONResponse(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
content=ApiError(
code="internal_error",
message=str(exc),
details={"type": type(exc).__name__},
).model_dump(by_alias=True),
)
# =============================================================================
# Routes
# =============================================================================
# Health checks (no auth)
app.include_router(health.router)
# Webhook endpoint (token-based auth)
app.include_router(webhooks.router)
# Protected API routes
app.include_router(flows.router, prefix="/api/v1")
app.include_router(triggers.router, prefix="/api/v1")
app.include_router(executions.router, prefix="/api/v1")
# =============================================================================
# Root endpoint
# =============================================================================
@app.get("/")
async def root() -> dict:
"""Root endpoint - API info."""
return {
"name": "BloxServer API",
"version": "0.1.0",
"docs": "/docs",
"health": "/health",
}
# =============================================================================
# Run with uvicorn
# =============================================================================
if __name__ == "__main__":
import uvicorn
uvicorn.run(
"bloxserver.api.main:app",
host=os.getenv("HOST", "0.0.0.0"),
port=int(os.getenv("PORT", "8000")),
reload=os.getenv("ENV", "development") == "development",
)

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"""Database and Pydantic models."""
from bloxserver.api.models.database import Base, get_db, init_db
from bloxserver.api.models.tables import (
EdgeMappingRecord,
ExecutionRecord,
FlowRecord,
TriggerRecord,
UserApiKeyRecord,
UserRecord,
UsageRecord,
)
__all__ = [
"Base",
"get_db",
"init_db",
"UserRecord",
"FlowRecord",
"TriggerRecord",
"ExecutionRecord",
"UserApiKeyRecord",
"UsageRecord",
"EdgeMappingRecord",
]

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"""
Database connection and session management.
Uses SQLAlchemy async with PostgreSQL.
"""
from __future__ import annotations
import os
from collections.abc import AsyncGenerator
from contextlib import asynccontextmanager
from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker, create_async_engine
from sqlalchemy.orm import DeclarativeBase
class Base(DeclarativeBase):
"""Base class for all ORM models."""
pass
# Database URL from environment
# Supports both PostgreSQL and SQLite (for local testing)
DATABASE_URL = os.getenv(
"DATABASE_URL",
"sqlite+aiosqlite:///./bloxserver.db", # SQLite default for easy local testing
)
# Create async engine with appropriate settings
_is_sqlite = DATABASE_URL.startswith("sqlite")
if _is_sqlite:
# SQLite doesn't support pool settings
engine = create_async_engine(
DATABASE_URL,
echo=os.getenv("SQL_ECHO", "false").lower() == "true",
connect_args={"check_same_thread": False},
)
else:
# PostgreSQL with connection pooling
engine = create_async_engine(
DATABASE_URL,
echo=os.getenv("SQL_ECHO", "false").lower() == "true",
pool_pre_ping=True,
pool_size=10,
max_overflow=20,
)
# Session factory
async_session_maker = async_sessionmaker(
engine,
class_=AsyncSession,
expire_on_commit=False,
)
async def init_db() -> None:
"""Create all tables. Call once at startup."""
async with engine.begin() as conn:
await conn.run_sync(Base.metadata.create_all)
async def get_db() -> AsyncGenerator[AsyncSession, None]:
"""Dependency for FastAPI routes. Yields a database session."""
async with async_session_maker() as session:
try:
yield session
await session.commit()
except Exception:
await session.rollback()
raise
@asynccontextmanager
async def get_db_context() -> AsyncGenerator[AsyncSession, None]:
"""Context manager for use outside of FastAPI routes."""
async with async_session_maker() as session:
try:
yield session
await session.commit()
except Exception:
await session.rollback()
raise

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"""
SQLAlchemy ORM models for BloxServer.
These map to the Pydantic models in schemas.py and TypeScript types in types.ts.
"""
from __future__ import annotations
import enum
from datetime import datetime
from typing import Any
from uuid import uuid4
from sqlalchemy import (
JSON,
Boolean,
DateTime,
Enum,
ForeignKey,
Index,
Integer,
LargeBinary,
Numeric,
String,
Text,
func,
)
from sqlalchemy.dialects.postgresql import UUID
from sqlalchemy.orm import Mapped, mapped_column, relationship
from bloxserver.api.models.database import Base
# =============================================================================
# Enums
# =============================================================================
class Tier(str, enum.Enum):
"""User subscription tier."""
FREE = "free"
PRO = "pro"
ENTERPRISE = "enterprise"
HIGH_FREQUENCY = "high_frequency"
class BillingStatus(str, enum.Enum):
"""Subscription billing status."""
ACTIVE = "active"
TRIALING = "trialing"
PAST_DUE = "past_due"
CANCELED = "canceled"
CANCELING = "canceling"
class FlowStatus(str, enum.Enum):
"""Flow runtime status."""
STOPPED = "stopped"
STARTING = "starting"
RUNNING = "running"
STOPPING = "stopping"
ERROR = "error"
class TriggerType(str, enum.Enum):
"""How a flow can be triggered."""
WEBHOOK = "webhook"
SCHEDULE = "schedule"
MANUAL = "manual"
class ExecutionStatus(str, enum.Enum):
"""Status of a flow execution."""
RUNNING = "running"
SUCCESS = "success"
ERROR = "error"
TIMEOUT = "timeout"
# =============================================================================
# Users (synced from Clerk)
# =============================================================================
class UserRecord(Base):
"""User account, synced from Clerk."""
__tablename__ = "users"
id: Mapped[UUID] = mapped_column(
UUID(as_uuid=True), primary_key=True, default=uuid4
)
clerk_id: Mapped[str] = mapped_column(String(255), unique=True, nullable=False)
email: Mapped[str] = mapped_column(String(255), nullable=False)
name: Mapped[str | None] = mapped_column(String(255))
avatar_url: Mapped[str | None] = mapped_column(Text)
# Stripe integration
stripe_customer_id: Mapped[str | None] = mapped_column(String(255), unique=True)
stripe_subscription_id: Mapped[str | None] = mapped_column(String(255))
stripe_subscription_item_id: Mapped[str | None] = mapped_column(String(255))
# Billing state (cached from Stripe)
tier: Mapped[Tier] = mapped_column(Enum(Tier), default=Tier.FREE)
billing_status: Mapped[BillingStatus] = mapped_column(
Enum(BillingStatus), default=BillingStatus.ACTIVE
)
trial_ends_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True))
current_period_start: Mapped[datetime | None] = mapped_column(DateTime(timezone=True))
current_period_end: Mapped[datetime | None] = mapped_column(DateTime(timezone=True))
# Timestamps
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), server_default=func.now()
)
updated_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), server_default=func.now(), onupdate=func.now()
)
# Relationships
flows: Mapped[list[FlowRecord]] = relationship(back_populates="user", cascade="all, delete-orphan")
api_keys: Mapped[list[UserApiKeyRecord]] = relationship(back_populates="user", cascade="all, delete-orphan")
usage_records: Mapped[list[UsageRecord]] = relationship(back_populates="user", cascade="all, delete-orphan")
__table_args__ = (
Index("idx_users_clerk_id", "clerk_id"),
Index("idx_users_stripe_customer", "stripe_customer_id"),
)
# =============================================================================
# Flows
# =============================================================================
class FlowRecord(Base):
"""A user's workflow/flow."""
__tablename__ = "flows"
id: Mapped[UUID] = mapped_column(
UUID(as_uuid=True), primary_key=True, default=uuid4
)
user_id: Mapped[UUID] = mapped_column(
UUID(as_uuid=True), ForeignKey("users.id", ondelete="CASCADE"), nullable=False
)
name: Mapped[str] = mapped_column(String(100), nullable=False)
description: Mapped[str | None] = mapped_column(String(500))
# The actual workflow definition
organism_yaml: Mapped[str] = mapped_column(Text, nullable=False, default="")
# React Flow canvas state (JSON)
canvas_state: Mapped[dict[str, Any] | None] = mapped_column(JSON)
# Runtime state
status: Mapped[FlowStatus] = mapped_column(Enum(FlowStatus), default=FlowStatus.STOPPED)
container_id: Mapped[str | None] = mapped_column(String(255))
error_message: Mapped[str | None] = mapped_column(Text)
# Timestamps
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), server_default=func.now()
)
updated_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), server_default=func.now(), onupdate=func.now()
)
# Relationships
user: Mapped[UserRecord] = relationship(back_populates="flows")
triggers: Mapped[list[TriggerRecord]] = relationship(back_populates="flow", cascade="all, delete-orphan")
executions: Mapped[list[ExecutionRecord]] = relationship(back_populates="flow", cascade="all, delete-orphan")
__table_args__ = (
Index("idx_flows_user_id", "user_id"),
Index("idx_flows_status", "status"),
)
# =============================================================================
# Triggers
# =============================================================================
class TriggerRecord(Base):
"""A trigger that can start a flow."""
__tablename__ = "triggers"
id: Mapped[UUID] = mapped_column(
UUID(as_uuid=True), primary_key=True, default=uuid4
)
flow_id: Mapped[UUID] = mapped_column(
UUID(as_uuid=True), ForeignKey("flows.id", ondelete="CASCADE"), nullable=False
)
type: Mapped[TriggerType] = mapped_column(Enum(TriggerType), nullable=False)
name: Mapped[str] = mapped_column(String(100), nullable=False)
# Trigger configuration (JSON)
config: Mapped[dict[str, Any]] = mapped_column(JSON, nullable=False, default=dict)
# Webhook-specific fields
webhook_token: Mapped[str | None] = mapped_column(String(64), unique=True)
webhook_url: Mapped[str | None] = mapped_column(Text)
# Timestamps
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), server_default=func.now()
)
# Relationships
flow: Mapped[FlowRecord] = relationship(back_populates="triggers")
executions: Mapped[list[ExecutionRecord]] = relationship(back_populates="trigger")
__table_args__ = (
Index("idx_triggers_flow_id", "flow_id"),
Index("idx_triggers_webhook_token", "webhook_token"),
)
# =============================================================================
# Executions
# =============================================================================
class ExecutionRecord(Base):
"""A single execution/run of a flow."""
__tablename__ = "executions"
id: Mapped[UUID] = mapped_column(
UUID(as_uuid=True), primary_key=True, default=uuid4
)
flow_id: Mapped[UUID] = mapped_column(
UUID(as_uuid=True), ForeignKey("flows.id", ondelete="CASCADE"), nullable=False
)
trigger_id: Mapped[UUID | None] = mapped_column(
UUID(as_uuid=True), ForeignKey("triggers.id", ondelete="SET NULL")
)
trigger_type: Mapped[TriggerType] = mapped_column(Enum(TriggerType), nullable=False)
# Execution state
status: Mapped[ExecutionStatus] = mapped_column(
Enum(ExecutionStatus), default=ExecutionStatus.RUNNING
)
error_message: Mapped[str | None] = mapped_column(Text)
# Payloads (JSON strings for flexibility)
input_payload: Mapped[str | None] = mapped_column(Text)
output_payload: Mapped[str | None] = mapped_column(Text)
# Timing
started_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), server_default=func.now()
)
completed_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True))
duration_ms: Mapped[int | None] = mapped_column(Integer)
# Relationships
flow: Mapped[FlowRecord] = relationship(back_populates="executions")
trigger: Mapped[TriggerRecord | None] = relationship(back_populates="executions")
__table_args__ = (
Index("idx_executions_flow_id", "flow_id"),
Index("idx_executions_started_at", "started_at"),
Index("idx_executions_status", "status"),
)
# =============================================================================
# User API Keys (BYOK)
# =============================================================================
class UserApiKeyRecord(Base):
"""User's own API keys for BYOK (Bring Your Own Key)."""
__tablename__ = "user_api_keys"
id: Mapped[UUID] = mapped_column(
UUID(as_uuid=True), primary_key=True, default=uuid4
)
user_id: Mapped[UUID] = mapped_column(
UUID(as_uuid=True), ForeignKey("users.id", ondelete="CASCADE"), nullable=False
)
provider: Mapped[str] = mapped_column(String(50), nullable=False)
# Encrypted API key
encrypted_key: Mapped[bytes] = mapped_column(LargeBinary, nullable=False)
key_hint: Mapped[str | None] = mapped_column(String(20)) # Last few chars for display
# Validation state
is_valid: Mapped[bool] = mapped_column(Boolean, default=True)
last_error: Mapped[str | None] = mapped_column(String(255))
last_used_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True))
# Timestamps
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), server_default=func.now()
)
# Relationships
user: Mapped[UserRecord] = relationship(back_populates="api_keys")
__table_args__ = (
Index("idx_user_api_keys_user_provider", "user_id", "provider", unique=True),
)
# =============================================================================
# Usage Tracking
# =============================================================================
class UsageRecord(Base):
"""Usage tracking for billing."""
__tablename__ = "usage_records"
id: Mapped[UUID] = mapped_column(
UUID(as_uuid=True), primary_key=True, default=uuid4
)
user_id: Mapped[UUID] = mapped_column(
UUID(as_uuid=True), ForeignKey("users.id", ondelete="CASCADE"), nullable=False
)
period_start: Mapped[datetime] = mapped_column(
DateTime(timezone=True), nullable=False
)
# Metrics
workflow_runs: Mapped[int] = mapped_column(Integer, default=0)
llm_tokens_in: Mapped[int] = mapped_column(Integer, default=0)
llm_tokens_out: Mapped[int] = mapped_column(Integer, default=0)
wasm_cpu_seconds: Mapped[float] = mapped_column(Numeric(10, 2), default=0)
storage_gb_hours: Mapped[float] = mapped_column(Numeric(10, 2), default=0)
# Stripe sync state
last_synced_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True))
last_synced_runs: Mapped[int] = mapped_column(Integer, default=0)
# Timestamps
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), server_default=func.now()
)
updated_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), server_default=func.now(), onupdate=func.now()
)
# Relationships
user: Mapped[UserRecord] = relationship(back_populates="usage_records")
__table_args__ = (
Index("idx_usage_user_period", "user_id", "period_start", unique=True),
)
# =============================================================================
# Stripe Events (Idempotency)
# =============================================================================
class StripeEventRecord(Base):
"""Processed Stripe webhook events for idempotency."""
__tablename__ = "stripe_events"
event_id: Mapped[str] = mapped_column(String(255), primary_key=True)
event_type: Mapped[str] = mapped_column(String(100), nullable=False)
processed_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), server_default=func.now()
)
payload: Mapped[dict[str, Any] | None] = mapped_column(JSON)
__table_args__ = (
Index("idx_stripe_events_processed", "processed_at"),
)
# =============================================================================
# Edge Mappings (AI-assisted field mapping between nodes)
# =============================================================================
class ConfidenceLevel(str, enum.Enum):
"""Confidence level for edge mapping analysis."""
HIGH = "high" # Green - auto-mapped, ready to run
MEDIUM = "medium" # Yellow - review suggested
LOW = "low" # Red - manual mapping needed
class EdgeMappingRecord(Base):
"""
Mapping between two nodes in a flow.
Stores both AI-proposed mappings and user overrides.
Used by the sequencer to transform outputs to inputs.
"""
__tablename__ = "edge_mappings"
id: Mapped[UUID] = mapped_column(
UUID(as_uuid=True), primary_key=True, default=uuid4
)
flow_id: Mapped[UUID] = mapped_column(
UUID(as_uuid=True), ForeignKey("flows.id", ondelete="CASCADE"), nullable=False
)
# Edge identification
from_node: Mapped[str] = mapped_column(String(100), nullable=False)
to_node: Mapped[str] = mapped_column(String(100), nullable=False)
# Analysis results
confidence: Mapped[float | None] = mapped_column(Numeric(3, 2))
level: Mapped[ConfidenceLevel | None] = mapped_column(Enum(ConfidenceLevel))
analysis_method: Mapped[str | None] = mapped_column(String(20)) # 'heuristic' or 'llm'
# The mappings (JSON)
proposed_mapping: Mapped[dict[str, Any] | None] = mapped_column(JSON)
user_mapping: Mapped[dict[str, Any] | None] = mapped_column(JSON) # User overrides
# Status
user_confirmed: Mapped[bool] = mapped_column(Boolean, default=False)
# Timestamps
analyzed_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True))
confirmed_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True))
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), server_default=func.now()
)
updated_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), server_default=func.now(), onupdate=func.now()
)
# Relationships
flow: Mapped[FlowRecord] = relationship("FlowRecord")
__table_args__ = (
Index("idx_edge_mappings_flow", "flow_id"),
Index("idx_edge_mappings_edge", "flow_id", "from_node", "to_node", unique=True),
)

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"""API route modules."""

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"""
Execution history and manual trigger endpoints.
Executions are immutable records of flow runs.
"""
from __future__ import annotations
from datetime import datetime
from uuid import UUID
from fastapi import APIRouter, HTTPException, status
from sqlalchemy import func, select
from bloxserver.api.dependencies import AuthenticatedUser, DbSession
from bloxserver.api.models.tables import (
ExecutionRecord,
ExecutionStatus,
FlowRecord,
TriggerType,
)
from bloxserver.api.schemas import Execution, ExecutionSummary, PaginatedResponse
router = APIRouter(prefix="/flows/{flow_id}/executions", tags=["executions"])
@router.get("", response_model=PaginatedResponse[ExecutionSummary])
async def list_executions(
flow_id: UUID,
user: AuthenticatedUser,
db: DbSession,
page: int = 1,
page_size: int = 50,
status_filter: ExecutionStatus | None = None,
) -> PaginatedResponse[ExecutionSummary]:
"""List execution history for a flow."""
# Verify flow ownership
flow_query = select(FlowRecord).where(
FlowRecord.id == flow_id,
FlowRecord.user_id == user.id,
)
flow = (await db.execute(flow_query)).scalar_one_or_none()
if not flow:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Flow not found",
)
offset = (page - 1) * page_size
# Build query
base_query = select(ExecutionRecord).where(ExecutionRecord.flow_id == flow_id)
if status_filter:
base_query = base_query.where(ExecutionRecord.status == status_filter)
# Get total count
count_query = select(func.count()).select_from(base_query.subquery())
total = (await db.execute(count_query)).scalar() or 0
# Get page
query = base_query.order_by(ExecutionRecord.started_at.desc()).offset(offset).limit(page_size)
result = await db.execute(query)
executions = result.scalars().all()
return PaginatedResponse(
items=[ExecutionSummary.model_validate(e) for e in executions],
total=total,
page=page,
page_size=page_size,
has_more=offset + len(executions) < total,
)
@router.get("/{execution_id}", response_model=Execution)
async def get_execution(
flow_id: UUID,
execution_id: UUID,
user: AuthenticatedUser,
db: DbSession,
) -> Execution:
"""Get details of a single execution."""
# Verify flow ownership
flow_query = select(FlowRecord).where(
FlowRecord.id == flow_id,
FlowRecord.user_id == user.id,
)
flow = (await db.execute(flow_query)).scalar_one_or_none()
if not flow:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Flow not found",
)
# Get execution
query = select(ExecutionRecord).where(
ExecutionRecord.id == execution_id,
ExecutionRecord.flow_id == flow_id,
)
result = await db.execute(query)
execution = result.scalar_one_or_none()
if not execution:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Execution not found",
)
return Execution.model_validate(execution)
@router.post("/run", response_model=Execution, status_code=status.HTTP_201_CREATED)
async def run_flow_manually(
flow_id: UUID,
user: AuthenticatedUser,
db: DbSession,
input_payload: str | None = None,
) -> Execution:
"""
Manually trigger a flow execution.
The flow must be in 'running' state.
"""
# Verify flow ownership
flow_query = select(FlowRecord).where(
FlowRecord.id == flow_id,
FlowRecord.user_id == user.id,
)
flow = (await db.execute(flow_query)).scalar_one_or_none()
if not flow:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Flow not found",
)
if flow.status != "running":
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=f"Flow must be running to execute (current: {flow.status})",
)
# Create execution record
execution = ExecutionRecord(
flow_id=flow_id,
trigger_type=TriggerType.MANUAL,
status=ExecutionStatus.RUNNING,
input_payload=input_payload,
)
db.add(execution)
await db.flush()
# TODO: Actually dispatch to the running container
# For now, just return the execution record
return Execution.model_validate(execution)
# =============================================================================
# Stats endpoint
# =============================================================================
@router.get("/stats", response_model=dict)
async def get_execution_stats(
flow_id: UUID,
user: AuthenticatedUser,
db: DbSession,
) -> dict:
"""Get execution statistics for a flow."""
# Verify flow ownership
flow_query = select(FlowRecord).where(
FlowRecord.id == flow_id,
FlowRecord.user_id == user.id,
)
flow = (await db.execute(flow_query)).scalar_one_or_none()
if not flow:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Flow not found",
)
# Calculate stats
stats_query = select(
func.count().label("total"),
func.count().filter(ExecutionRecord.status == ExecutionStatus.SUCCESS).label("success"),
func.count().filter(ExecutionRecord.status == ExecutionStatus.ERROR).label("error"),
func.avg(ExecutionRecord.duration_ms).label("avg_duration_ms"),
func.max(ExecutionRecord.started_at).label("last_executed_at"),
).where(ExecutionRecord.flow_id == flow_id)
result = await db.execute(stats_query)
row = result.one()
return {
"flowId": str(flow_id),
"executionsTotal": row.total or 0,
"executionsSuccess": row.success or 0,
"executionsError": row.error or 0,
"avgDurationMs": float(row.avg_duration_ms) if row.avg_duration_ms else 0,
"lastExecutedAt": row.last_executed_at.isoformat() if row.last_executed_at else None,
}

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"""
Flow CRUD endpoints.
Flows are the core entity - a user's workflow definition.
"""
from __future__ import annotations
from uuid import UUID
from fastapi import APIRouter, HTTPException, status
from sqlalchemy import func, select
from bloxserver.api.dependencies import AuthenticatedUser, DbSession
from bloxserver.api.models.tables import FlowRecord, Tier
from bloxserver.api.schemas import (
CreateFlowRequest,
Flow,
FlowSummary,
PaginatedResponse,
UpdateFlowRequest,
)
router = APIRouter(prefix="/flows", tags=["flows"])
# Default organism.yaml template for new flows
DEFAULT_ORGANISM_YAML = """organism:
name: my-flow
listeners:
- name: greeter
payload_class: handlers.hello.Greeting
handler: handlers.hello.handle_greeting
description: A friendly greeter agent
agent: true
peers: []
"""
# Tier limits
TIER_FLOW_LIMITS = {
Tier.FREE: 1,
Tier.PRO: 100, # Effectively unlimited for most users
Tier.ENTERPRISE: 1000,
Tier.HIGH_FREQUENCY: 1000,
}
@router.get("", response_model=PaginatedResponse[FlowSummary])
async def list_flows(
user: AuthenticatedUser,
db: DbSession,
page: int = 1,
page_size: int = 20,
) -> PaginatedResponse[FlowSummary]:
"""List all flows for the current user."""
offset = (page - 1) * page_size
# Get total count
count_query = select(func.count()).select_from(FlowRecord).where(
FlowRecord.user_id == user.id
)
total = (await db.execute(count_query)).scalar() or 0
# Get page of flows
query = (
select(FlowRecord)
.where(FlowRecord.user_id == user.id)
.order_by(FlowRecord.updated_at.desc())
.offset(offset)
.limit(page_size)
)
result = await db.execute(query)
flows = result.scalars().all()
return PaginatedResponse(
items=[FlowSummary.model_validate(f) for f in flows],
total=total,
page=page,
page_size=page_size,
has_more=offset + len(flows) < total,
)
@router.post("", response_model=Flow, status_code=status.HTTP_201_CREATED)
async def create_flow(
user: AuthenticatedUser,
db: DbSession,
request: CreateFlowRequest,
) -> Flow:
"""Create a new flow."""
# Check tier limits
count_query = select(func.count()).select_from(FlowRecord).where(
FlowRecord.user_id == user.id
)
current_count = (await db.execute(count_query)).scalar() or 0
limit = TIER_FLOW_LIMITS.get(user.user.tier, 1)
if current_count >= limit:
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail=f"Flow limit reached ({limit}). Upgrade to create more flows.",
)
# Create flow
flow = FlowRecord(
user_id=user.id,
name=request.name,
description=request.description,
organism_yaml=request.organism_yaml or DEFAULT_ORGANISM_YAML,
)
db.add(flow)
await db.flush()
return Flow.model_validate(flow)
@router.get("/{flow_id}", response_model=Flow)
async def get_flow(
flow_id: UUID,
user: AuthenticatedUser,
db: DbSession,
) -> Flow:
"""Get a single flow by ID."""
query = select(FlowRecord).where(
FlowRecord.id == flow_id,
FlowRecord.user_id == user.id,
)
result = await db.execute(query)
flow = result.scalar_one_or_none()
if not flow:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Flow not found",
)
return Flow.model_validate(flow)
@router.patch("/{flow_id}", response_model=Flow)
async def update_flow(
flow_id: UUID,
user: AuthenticatedUser,
db: DbSession,
request: UpdateFlowRequest,
) -> Flow:
"""Update a flow."""
query = select(FlowRecord).where(
FlowRecord.id == flow_id,
FlowRecord.user_id == user.id,
)
result = await db.execute(query)
flow = result.scalar_one_or_none()
if not flow:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Flow not found",
)
# Update fields that were provided
if request.name is not None:
flow.name = request.name
if request.description is not None:
flow.description = request.description
if request.organism_yaml is not None:
flow.organism_yaml = request.organism_yaml
if request.canvas_state is not None:
flow.canvas_state = request.canvas_state.model_dump()
await db.flush()
return Flow.model_validate(flow)
@router.delete("/{flow_id}", status_code=status.HTTP_204_NO_CONTENT)
async def delete_flow(
flow_id: UUID,
user: AuthenticatedUser,
db: DbSession,
) -> None:
"""Delete a flow."""
query = select(FlowRecord).where(
FlowRecord.id == flow_id,
FlowRecord.user_id == user.id,
)
result = await db.execute(query)
flow = result.scalar_one_or_none()
if not flow:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Flow not found",
)
await db.delete(flow)
# =============================================================================
# Flow Actions (Start/Stop)
# =============================================================================
@router.post("/{flow_id}/start", response_model=Flow)
async def start_flow(
flow_id: UUID,
user: AuthenticatedUser,
db: DbSession,
) -> Flow:
"""Start a flow (deploy container)."""
query = select(FlowRecord).where(
FlowRecord.id == flow_id,
FlowRecord.user_id == user.id,
)
result = await db.execute(query)
flow = result.scalar_one_or_none()
if not flow:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Flow not found",
)
if flow.status not in ("stopped", "error"):
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=f"Cannot start flow in {flow.status} state",
)
# TODO: Actually start the container
# This is where we'd call the container orchestration layer
# For now, just update the status
flow.status = "starting"
flow.error_message = None
await db.flush()
return Flow.model_validate(flow)
@router.post("/{flow_id}/stop", response_model=Flow)
async def stop_flow(
flow_id: UUID,
user: AuthenticatedUser,
db: DbSession,
) -> Flow:
"""Stop a running flow."""
query = select(FlowRecord).where(
FlowRecord.id == flow_id,
FlowRecord.user_id == user.id,
)
result = await db.execute(query)
flow = result.scalar_one_or_none()
if not flow:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Flow not found",
)
if flow.status not in ("running", "starting", "error"):
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=f"Cannot stop flow in {flow.status} state",
)
# TODO: Actually stop the container
flow.status = "stopping"
await db.flush()
return Flow.model_validate(flow)

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"""
Health check and status endpoints.
"""
from __future__ import annotations
from datetime import datetime
from fastapi import APIRouter
from sqlalchemy import text
from bloxserver.api.models.database import async_session_maker
router = APIRouter(tags=["health"])
@router.get("/health")
async def health_check() -> dict:
"""
Basic health check.
Returns 200 if the service is running.
"""
return {
"status": "healthy",
"timestamp": datetime.utcnow().isoformat(),
"service": "bloxserver-api",
}
@router.get("/health/ready")
async def readiness_check() -> dict:
"""
Readiness check - verifies database connectivity.
Used by Kubernetes/load balancers to determine if the service
is ready to receive traffic.
"""
errors = []
# Check database
try:
async with async_session_maker() as session:
await session.execute(text("SELECT 1"))
except Exception as e:
errors.append(f"database: {e}")
# TODO: Check Redis
# TODO: Check other dependencies
if errors:
return {
"status": "unhealthy",
"timestamp": datetime.utcnow().isoformat(),
"errors": errors,
}
return {
"status": "ready",
"timestamp": datetime.utcnow().isoformat(),
"checks": {
"database": "ok",
},
}
@router.get("/health/live")
async def liveness_check() -> dict:
"""
Liveness check - just confirms the process is running.
If this fails, Kubernetes should restart the pod.
"""
return {
"status": "alive",
"timestamp": datetime.utcnow().isoformat(),
}

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"""
Trigger CRUD endpoints.
Triggers define how flows are started: webhook, schedule, or manual.
"""
from __future__ import annotations
import secrets
from uuid import UUID
from fastapi import APIRouter, HTTPException, status
from sqlalchemy import select
from bloxserver.api.dependencies import AuthenticatedUser, DbSession
from bloxserver.api.models.tables import FlowRecord, TriggerRecord, TriggerType
from bloxserver.api.schemas import CreateTriggerRequest, Trigger
router = APIRouter(prefix="/flows/{flow_id}/triggers", tags=["triggers"])
# Base URL for webhooks (configured via environment)
import os
WEBHOOK_BASE_URL = os.getenv("WEBHOOK_BASE_URL", "https://api.openblox.ai/webhooks")
def generate_webhook_token() -> str:
"""Generate a secure random token for webhook URLs."""
return secrets.token_urlsafe(32)
@router.get("", response_model=list[Trigger])
async def list_triggers(
flow_id: UUID,
user: AuthenticatedUser,
db: DbSession,
) -> list[Trigger]:
"""List all triggers for a flow."""
# Verify flow ownership
flow_query = select(FlowRecord).where(
FlowRecord.id == flow_id,
FlowRecord.user_id == user.id,
)
flow = (await db.execute(flow_query)).scalar_one_or_none()
if not flow:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Flow not found",
)
# Get triggers
query = select(TriggerRecord).where(TriggerRecord.flow_id == flow_id)
result = await db.execute(query)
triggers = result.scalars().all()
return [Trigger.model_validate(t) for t in triggers]
@router.post("", response_model=Trigger, status_code=status.HTTP_201_CREATED)
async def create_trigger(
flow_id: UUID,
user: AuthenticatedUser,
db: DbSession,
request: CreateTriggerRequest,
) -> Trigger:
"""Create a new trigger for a flow."""
# Verify flow ownership
flow_query = select(FlowRecord).where(
FlowRecord.id == flow_id,
FlowRecord.user_id == user.id,
)
flow = (await db.execute(flow_query)).scalar_one_or_none()
if not flow:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Flow not found",
)
# Create trigger
trigger = TriggerRecord(
flow_id=flow_id,
type=TriggerType(request.type.value),
name=request.name,
config=request.config,
)
# Generate webhook URL for webhook triggers
if request.type == TriggerType.WEBHOOK:
trigger.webhook_token = generate_webhook_token()
trigger.webhook_url = f"{WEBHOOK_BASE_URL}/{trigger.webhook_token}"
db.add(trigger)
await db.flush()
return Trigger.model_validate(trigger)
@router.get("/{trigger_id}", response_model=Trigger)
async def get_trigger(
flow_id: UUID,
trigger_id: UUID,
user: AuthenticatedUser,
db: DbSession,
) -> Trigger:
"""Get a single trigger by ID."""
# Verify flow ownership
flow_query = select(FlowRecord).where(
FlowRecord.id == flow_id,
FlowRecord.user_id == user.id,
)
flow = (await db.execute(flow_query)).scalar_one_or_none()
if not flow:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Flow not found",
)
# Get trigger
query = select(TriggerRecord).where(
TriggerRecord.id == trigger_id,
TriggerRecord.flow_id == flow_id,
)
result = await db.execute(query)
trigger = result.scalar_one_or_none()
if not trigger:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Trigger not found",
)
return Trigger.model_validate(trigger)
@router.delete("/{trigger_id}", status_code=status.HTTP_204_NO_CONTENT)
async def delete_trigger(
flow_id: UUID,
trigger_id: UUID,
user: AuthenticatedUser,
db: DbSession,
) -> None:
"""Delete a trigger."""
# Verify flow ownership
flow_query = select(FlowRecord).where(
FlowRecord.id == flow_id,
FlowRecord.user_id == user.id,
)
flow = (await db.execute(flow_query)).scalar_one_or_none()
if not flow:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Flow not found",
)
# Get and delete trigger
query = select(TriggerRecord).where(
TriggerRecord.id == trigger_id,
TriggerRecord.flow_id == flow_id,
)
result = await db.execute(query)
trigger = result.scalar_one_or_none()
if not trigger:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Trigger not found",
)
await db.delete(trigger)
@router.post("/{trigger_id}/regenerate-token", response_model=Trigger)
async def regenerate_webhook_token(
flow_id: UUID,
trigger_id: UUID,
user: AuthenticatedUser,
db: DbSession,
) -> Trigger:
"""Regenerate the webhook token for a webhook trigger."""
# Verify flow ownership
flow_query = select(FlowRecord).where(
FlowRecord.id == flow_id,
FlowRecord.user_id == user.id,
)
flow = (await db.execute(flow_query)).scalar_one_or_none()
if not flow:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Flow not found",
)
# Get trigger
query = select(TriggerRecord).where(
TriggerRecord.id == trigger_id,
TriggerRecord.flow_id == flow_id,
)
result = await db.execute(query)
trigger = result.scalar_one_or_none()
if not trigger:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Trigger not found",
)
if trigger.type != TriggerType.WEBHOOK:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="Can only regenerate token for webhook triggers",
)
# Regenerate
trigger.webhook_token = generate_webhook_token()
trigger.webhook_url = f"{WEBHOOK_BASE_URL}/{trigger.webhook_token}"
await db.flush()
return Trigger.model_validate(trigger)

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@ -1,125 +0,0 @@
"""
Webhook trigger endpoint.
This handles incoming webhook requests that trigger flows.
"""
from __future__ import annotations
from datetime import datetime
from fastapi import APIRouter, HTTPException, Request, status
from sqlalchemy import select
from bloxserver.api.models.database import get_db_context
from bloxserver.api.models.tables import (
ExecutionRecord,
ExecutionStatus,
FlowRecord,
TriggerRecord,
TriggerType,
)
router = APIRouter(prefix="/webhooks", tags=["webhooks"])
@router.post("/{webhook_token}")
async def handle_webhook(
webhook_token: str,
request: Request,
) -> dict:
"""
Handle incoming webhook request.
This endpoint is public (no auth) - the token IS the authentication.
"""
async with get_db_context() as db:
# Look up trigger by token
query = select(TriggerRecord).where(
TriggerRecord.webhook_token == webhook_token,
TriggerRecord.type == TriggerType.WEBHOOK,
)
result = await db.execute(query)
trigger = result.scalar_one_or_none()
if not trigger:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Webhook not found",
)
# Get the flow
flow_query = select(FlowRecord).where(FlowRecord.id == trigger.flow_id)
flow = (await db.execute(flow_query)).scalar_one_or_none()
if not flow:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Flow not found",
)
if flow.status != "running":
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=f"Flow is not running (status: {flow.status})",
)
# Get request body
try:
body = await request.body()
input_payload = body.decode("utf-8") if body else None
except Exception:
input_payload = None
# Create execution record
execution = ExecutionRecord(
flow_id=flow.id,
trigger_id=trigger.id,
trigger_type=TriggerType.WEBHOOK,
status=ExecutionStatus.RUNNING,
input_payload=input_payload,
)
db.add(execution)
await db.commit()
# TODO: Actually dispatch to the running container
# This would send the payload to the flow's container
return {
"status": "accepted",
"executionId": str(execution.id),
"message": "Webhook received and execution started",
}
@router.get("/{webhook_token}/test")
async def test_webhook(webhook_token: str) -> dict:
"""
Test that a webhook token is valid.
Returns info about the trigger without actually executing.
"""
async with get_db_context() as db:
query = select(TriggerRecord).where(
TriggerRecord.webhook_token == webhook_token,
TriggerRecord.type == TriggerType.WEBHOOK,
)
result = await db.execute(query)
trigger = result.scalar_one_or_none()
if not trigger:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Webhook not found",
)
# Get the flow
flow_query = select(FlowRecord).where(FlowRecord.id == trigger.flow_id)
flow = (await db.execute(flow_query)).scalar_one_or_none()
return {
"valid": True,
"triggerName": trigger.name,
"flowName": flow.name if flow else None,
"flowStatus": flow.status.value if flow else None,
}

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@ -1,322 +0,0 @@
"""
Pydantic schemas for API request/response validation.
These match the TypeScript types in types.ts for frontend compatibility.
Uses camelCase aliases for JSON serialization.
"""
from __future__ import annotations
from datetime import datetime
from enum import Enum
from typing import Any, Generic, Literal, TypeVar
from uuid import UUID
from pydantic import BaseModel, ConfigDict, Field
# =============================================================================
# Config for camelCase serialization
# =============================================================================
def to_camel(string: str) -> str:
"""Convert snake_case to camelCase."""
components = string.split("_")
return components[0] + "".join(x.title() for x in components[1:])
class CamelModel(BaseModel):
"""Base model with camelCase JSON serialization."""
model_config = ConfigDict(
alias_generator=to_camel,
populate_by_name=True,
from_attributes=True,
)
# =============================================================================
# Common Types
# =============================================================================
T = TypeVar("T")
class PaginatedResponse(CamelModel, Generic[T]):
"""Paginated list response."""
items: list[T]
total: int
page: int
page_size: int
has_more: bool
class ApiError(CamelModel):
"""API error response."""
code: str
message: str
details: dict[str, Any] | None = None
# =============================================================================
# Enums
# =============================================================================
class Tier(str, Enum):
FREE = "free"
PRO = "pro"
ENTERPRISE = "enterprise"
HIGH_FREQUENCY = "high_frequency"
class FlowStatus(str, Enum):
STOPPED = "stopped"
STARTING = "starting"
RUNNING = "running"
STOPPING = "stopping"
ERROR = "error"
class TriggerType(str, Enum):
WEBHOOK = "webhook"
SCHEDULE = "schedule"
MANUAL = "manual"
class ExecutionStatus(str, Enum):
RUNNING = "running"
SUCCESS = "success"
ERROR = "error"
TIMEOUT = "timeout"
# =============================================================================
# User
# =============================================================================
class User(CamelModel):
"""User account (synced from Clerk)."""
id: UUID
clerk_id: str
email: str
name: str | None = None
avatar_url: str | None = None
tier: Tier = Tier.FREE
created_at: datetime
# =============================================================================
# Canvas State (React Flow)
# =============================================================================
class CanvasNode(CamelModel):
"""A node in the React Flow canvas."""
id: str
type: str
position: dict[str, float]
data: dict[str, Any]
class CanvasEdge(CamelModel):
"""An edge connecting nodes in the canvas."""
id: str
source: str
target: str
source_handle: str | None = None
target_handle: str | None = None
class CanvasState(CamelModel):
"""React Flow canvas state."""
nodes: list[CanvasNode]
edges: list[CanvasEdge]
viewport: dict[str, float]
# =============================================================================
# Flows
# =============================================================================
class Flow(CamelModel):
"""A user's workflow/flow."""
id: UUID
user_id: UUID
name: str
description: str | None = None
organism_yaml: str
canvas_state: CanvasState | None = None
status: FlowStatus = FlowStatus.STOPPED
container_id: str | None = None
error_message: str | None = None
created_at: datetime
updated_at: datetime
class FlowSummary(CamelModel):
"""Abbreviated flow for list views."""
id: UUID
name: str
description: str | None = None
status: FlowStatus
updated_at: datetime
class CreateFlowRequest(CamelModel):
"""Request to create a new flow."""
name: str = Field(min_length=1, max_length=100)
description: str | None = Field(default=None, max_length=500)
organism_yaml: str | None = None
class UpdateFlowRequest(CamelModel):
"""Request to update a flow."""
name: str | None = Field(default=None, min_length=1, max_length=100)
description: str | None = Field(default=None, max_length=500)
organism_yaml: str | None = None
canvas_state: CanvasState | None = None
# =============================================================================
# Triggers
# =============================================================================
class WebhookTriggerConfig(CamelModel):
"""Config for webhook triggers."""
type: Literal["webhook"] = "webhook"
class ScheduleTriggerConfig(CamelModel):
"""Config for scheduled triggers."""
type: Literal["schedule"] = "schedule"
cron: str = Field(description="Cron expression")
timezone: str = "UTC"
class ManualTriggerConfig(CamelModel):
"""Config for manual triggers."""
type: Literal["manual"] = "manual"
TriggerConfig = WebhookTriggerConfig | ScheduleTriggerConfig | ManualTriggerConfig
class Trigger(CamelModel):
"""A trigger that can start a flow."""
id: UUID
flow_id: UUID
type: TriggerType
name: str
config: dict[str, Any]
webhook_token: str | None = None
webhook_url: str | None = None
created_at: datetime
class CreateTriggerRequest(CamelModel):
"""Request to create a trigger."""
type: TriggerType
name: str = Field(min_length=1, max_length=100)
config: dict[str, Any]
# =============================================================================
# Executions
# =============================================================================
class Execution(CamelModel):
"""A single execution/run of a flow."""
id: UUID
flow_id: UUID
trigger_id: UUID | None = None
trigger_type: TriggerType
status: ExecutionStatus
started_at: datetime
completed_at: datetime | None = None
duration_ms: int | None = None
error_message: str | None = None
input_payload: str | None = None
output_payload: str | None = None
class ExecutionSummary(CamelModel):
"""Abbreviated execution for list views."""
id: UUID
status: ExecutionStatus
trigger_type: TriggerType
started_at: datetime
duration_ms: int | None = None
# =============================================================================
# Usage & Stats
# =============================================================================
class UsageDashboard(CamelModel):
"""Current usage for user dashboard."""
period_start: datetime
period_end: datetime | None
runs_used: int
runs_limit: int
runs_percentage: float
tokens_used: int
estimated_overage: float
days_remaining: int
class FlowStats(CamelModel):
"""Statistics for a single flow."""
flow_id: UUID
executions_total: int
executions_success: int
executions_error: int
avg_duration_ms: float
last_executed_at: datetime | None = None
# =============================================================================
# API Keys (BYOK)
# =============================================================================
class ApiKeyInfo(CamelModel):
"""Info about a stored API key (never exposes the key itself)."""
provider: str
key_hint: str | None # Last few chars: "...abc123"
is_valid: bool
last_used_at: datetime | None
created_at: datetime
class AddApiKeyRequest(CamelModel):
"""Request to add a user's API key."""
provider: str = Field(description="Provider name: openai, anthropic, xai")
api_key: str = Field(min_length=10, description="The API key")

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@ -1,72 +0,0 @@
# BloxServer Development Docker Compose
# Run with: docker-compose up -d
version: '3.8'
services:
# ==========================================================================
# PostgreSQL Database
# ==========================================================================
postgres:
image: postgres:16-alpine
container_name: bloxserver-postgres
environment:
POSTGRES_USER: postgres
POSTGRES_PASSWORD: postgres
POSTGRES_DB: bloxserver
ports:
- "5432:5432"
volumes:
- postgres_data:/var/lib/postgresql/data
healthcheck:
test: ["CMD-SHELL", "pg_isready -U postgres"]
interval: 10s
timeout: 5s
retries: 5
# ==========================================================================
# Redis (for caching, rate limiting, queues)
# ==========================================================================
redis:
image: redis:7-alpine
container_name: bloxserver-redis
ports:
- "6379:6379"
volumes:
- redis_data:/data
healthcheck:
test: ["CMD", "redis-cli", "ping"]
interval: 10s
timeout: 5s
retries: 5
# ==========================================================================
# BloxServer API
# ==========================================================================
api:
build:
context: .
dockerfile: Dockerfile
container_name: bloxserver-api
ports:
- "8000:8000"
environment:
- ENV=development
- DATABASE_URL=postgresql+asyncpg://postgres:postgres@postgres:5432/bloxserver
- REDIS_URL=redis://redis:6379
- AUTO_CREATE_TABLES=true
- ENABLE_DOCS=true
- CORS_ORIGINS=http://localhost:3000
depends_on:
postgres:
condition: service_healthy
redis:
condition: service_healthy
volumes:
# Mount source for hot reload in development
- .:/app/bloxserver:ro
command: uvicorn bloxserver.api.main:app --host 0.0.0.0 --port 8000 --reload
volumes:
postgres_data:
redis_data:

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@ -1,53 +0,0 @@
"""
BloxServer Domain Model.
This module contains the core domain classes that represent flows (teams),
nodes (agents/tools), edges (connections), and triggers.
The domain model serves as the bridge between:
- Frontend canvas JSON (React Flow)
- Database storage (FlowRecord)
- Execution engine (organism.yaml)
"""
from bloxserver.domain.nodes import (
Node,
NodeType,
AgentNode,
ToolNode,
GatewayNode,
)
from bloxserver.domain.edges import Edge, EdgeCondition
from bloxserver.domain.triggers import (
Trigger,
TriggerType,
TriggerConfig,
create_webhook_trigger,
create_schedule_trigger,
create_manual_trigger,
)
from bloxserver.domain.flow import Flow, FlowSettings, LLMSettings, ValidationError
__all__ = [
# Nodes
"Node",
"NodeType",
"AgentNode",
"ToolNode",
"GatewayNode",
# Edges
"Edge",
"EdgeCondition",
# Triggers
"Trigger",
"TriggerType",
"TriggerConfig",
"create_webhook_trigger",
"create_schedule_trigger",
"create_manual_trigger",
# Flow
"Flow",
"FlowSettings",
"LLMSettings",
"ValidationError",
]

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@ -1,220 +0,0 @@
"""
Edge model for connections between nodes.
Edges define how messages flow between nodes in a flow.
They can optionally have conditions for conditional routing.
"""
from __future__ import annotations
from dataclasses import dataclass, field
from enum import Enum
from typing import Any
from uuid import UUID, uuid4
class EdgeCondition(str, Enum):
"""Types of edge conditions."""
ALWAYS = "always" # Always route (default)
ON_SUCCESS = "on_success" # Route only if source succeeds
ON_ERROR = "on_error" # Route only if source fails
CONDITIONAL = "conditional" # Custom condition expression
@dataclass
class Edge:
"""
Connection between two nodes.
Edges define the flow of messages between nodes. In organism.yaml terms,
they define the `peers` list for agents and the routing paths.
"""
id: UUID
source_node_id: UUID
target_node_id: UUID
# Optional label for UI
label: str | None = None
# Condition for when this edge is followed
condition: EdgeCondition = EdgeCondition.ALWAYS
# Custom condition expression (when condition == CONDITIONAL)
# Example: "payload.status == 'approved'"
condition_expression: str | None = None
# Visual properties for canvas
source_handle: str | None = None # Which output port
target_handle: str | None = None # Which input port
animated: bool = False
edge_type: str = "default" # default, smoothstep, step, straight
def to_dict(self) -> dict[str, Any]:
"""Convert to dictionary for JSON serialization (React Flow format)."""
return {
"id": str(self.id),
"source": str(self.source_node_id),
"target": str(self.target_node_id),
"label": self.label,
"data": {
"condition": self.condition.value,
"conditionExpression": self.condition_expression,
},
"sourceHandle": self.source_handle,
"targetHandle": self.target_handle,
"animated": self.animated,
"type": self.edge_type,
}
@classmethod
def from_dict(cls, data: dict[str, Any]) -> Edge:
"""Create edge from dictionary (React Flow format)."""
edge_data = data.get("data", {})
# Handle condition
condition_str = edge_data.get("condition", "always")
try:
condition = EdgeCondition(condition_str)
except ValueError:
condition = EdgeCondition.ALWAYS
return cls(
id=UUID(data["id"]) if isinstance(data.get("id"), str) else data.get("id", uuid4()),
source_node_id=UUID(data["source"]) if isinstance(data.get("source"), str) else data["source"],
target_node_id=UUID(data["target"]) if isinstance(data.get("target"), str) else data["target"],
label=data.get("label"),
condition=condition,
condition_expression=edge_data.get("conditionExpression") or edge_data.get("condition_expression"),
source_handle=data.get("sourceHandle") or data.get("source_handle"),
target_handle=data.get("targetHandle") or data.get("target_handle"),
animated=data.get("animated", False),
edge_type=data.get("type", "default"),
)
def compute_peers(
node_id: UUID,
edges: list[Edge],
node_map: dict[UUID, str],
) -> list[str]:
"""
Compute the peers list for a node based on outgoing edges.
Args:
node_id: The node to compute peers for.
edges: All edges in the flow.
node_map: Mapping of node IDs to node names.
Returns:
List of peer names (target nodes this node can send to).
"""
peers: list[str] = []
for edge in edges:
if edge.source_node_id == node_id:
target_name = node_map.get(edge.target_node_id)
if target_name and target_name not in peers:
peers.append(target_name)
return peers
def compute_incoming(
node_id: UUID,
edges: list[Edge],
node_map: dict[UUID, str],
) -> list[str]:
"""
Compute the list of nodes that can send to this node.
Args:
node_id: The target node.
edges: All edges in the flow.
node_map: Mapping of node IDs to node names.
Returns:
List of source node names.
"""
incoming: list[str] = []
for edge in edges:
if edge.target_node_id == node_id:
source_name = node_map.get(edge.source_node_id)
if source_name and source_name not in incoming:
incoming.append(source_name)
return incoming
def find_entry_nodes(
nodes: list[UUID],
edges: list[Edge],
) -> list[UUID]:
"""
Find nodes with no incoming edges (entry points).
These are typically where external triggers connect.
"""
nodes_with_incoming = {edge.target_node_id for edge in edges}
return [node_id for node_id in nodes if node_id not in nodes_with_incoming]
def find_exit_nodes(
nodes: list[UUID],
edges: list[Edge],
) -> list[UUID]:
"""
Find nodes with no outgoing edges (exit points).
These are typically terminal handlers or response nodes.
"""
nodes_with_outgoing = {edge.source_node_id for edge in edges}
return [node_id for node_id in nodes if node_id not in nodes_with_outgoing]
def detect_cycles(
nodes: list[UUID],
edges: list[Edge],
) -> list[list[UUID]]:
"""
Detect cycles in the flow graph.
Returns a list of cycles (each cycle is a list of node IDs).
Cycles are allowed (agents can self-loop) but should be flagged for review.
"""
cycles: list[list[UUID]] = []
# Build adjacency list
adj: dict[UUID, list[UUID]] = {node_id: [] for node_id in nodes}
for edge in edges:
if edge.source_node_id in adj:
adj[edge.source_node_id].append(edge.target_node_id)
# DFS for cycle detection
visited: set[UUID] = set()
rec_stack: set[UUID] = set()
path: list[UUID] = []
def dfs(node: UUID) -> None:
visited.add(node)
rec_stack.add(node)
path.append(node)
for neighbor in adj.get(node, []):
if neighbor not in visited:
dfs(neighbor)
elif neighbor in rec_stack:
# Found a cycle
cycle_start = path.index(neighbor)
cycles.append(path[cycle_start:] + [neighbor])
path.pop()
rec_stack.remove(node)
for node_id in nodes:
if node_id not in visited:
dfs(node_id)
return cycles

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@ -1,559 +0,0 @@
"""
Flow domain model - the central aggregation point.
A Flow (also called a Team) is the complete definition of an agent workflow:
- Nodes (agents, tools, gateways)
- Edges (connections between nodes)
- Triggers (how the flow is started)
- Settings (LLM config, rate limits, etc.)
The Flow class provides:
- to_organism_yaml(): Convert to xml-pipeline organism configuration
- to_canvas_json(): Convert to frontend canvas format
- from_canvas_json(): Parse from frontend canvas format
- validate(): Check for errors before execution
"""
from __future__ import annotations
from dataclasses import dataclass, field
from datetime import datetime
from typing import Any
from uuid import UUID, uuid4
import yaml
from bloxserver.domain.nodes import (
Node,
NodeType,
AgentNode,
ToolNode,
GatewayNode,
)
from bloxserver.domain.edges import Edge, compute_peers, find_entry_nodes, detect_cycles
from bloxserver.domain.triggers import Trigger, TriggerType
# =============================================================================
# Validation
# =============================================================================
@dataclass
class ValidationError:
"""A validation error in a flow."""
code: str
message: str
node_id: UUID | None = None
edge_id: UUID | None = None
trigger_id: UUID | None = None
severity: str = "error" # error, warning, info
def to_dict(self) -> dict[str, Any]:
return {
"code": self.code,
"message": self.message,
"nodeId": str(self.node_id) if self.node_id else None,
"edgeId": str(self.edge_id) if self.edge_id else None,
"triggerId": str(self.trigger_id) if self.trigger_id else None,
"severity": self.severity,
}
# =============================================================================
# Flow Settings
# =============================================================================
@dataclass
class LLMSettings:
"""LLM configuration for the flow."""
# Default model for agents without explicit model
default_model: str = "grok-4.1"
# Strategy for backend selection
strategy: str = "failover"
# Rate limits (override org-level limits)
max_tokens_per_minute: int | None = None
max_requests_per_minute: int | None = None
# Retry settings
retries: int = 3
retry_base_delay: float = 1.0
def to_dict(self) -> dict[str, Any]:
return {
"defaultModel": self.default_model,
"strategy": self.strategy,
"maxTokensPerMinute": self.max_tokens_per_minute,
"maxRequestsPerMinute": self.max_requests_per_minute,
"retries": self.retries,
"retryBaseDelay": self.retry_base_delay,
}
@classmethod
def from_dict(cls, data: dict[str, Any]) -> LLMSettings:
return cls(
default_model=data.get("defaultModel") or data.get("default_model", "grok-4.1"),
strategy=data.get("strategy", "failover"),
max_tokens_per_minute=data.get("maxTokensPerMinute") or data.get("max_tokens_per_minute"),
max_requests_per_minute=data.get("maxRequestsPerMinute") or data.get("max_requests_per_minute"),
retries=data.get("retries", 3),
retry_base_delay=data.get("retryBaseDelay") or data.get("retry_base_delay", 1.0),
)
@dataclass
class FlowSettings:
"""Settings for a flow."""
# LLM configuration
llm: LLMSettings = field(default_factory=LLMSettings)
# Execution settings
timeout_seconds: int = 300 # Max execution time
max_iterations: int = 100 # Max message loops (prevent infinite recursion)
# Logging
log_level: str = "info"
log_payloads: bool = False # Log full message payloads
# Thread settings
thread_ttl_seconds: int = 86400 # 24 hours
def to_dict(self) -> dict[str, Any]:
return {
"llm": self.llm.to_dict(),
"timeoutSeconds": self.timeout_seconds,
"maxIterations": self.max_iterations,
"logLevel": self.log_level,
"logPayloads": self.log_payloads,
"threadTtlSeconds": self.thread_ttl_seconds,
}
@classmethod
def from_dict(cls, data: dict[str, Any]) -> FlowSettings:
llm_data = data.get("llm", {})
return cls(
llm=LLMSettings.from_dict(llm_data) if llm_data else LLMSettings(),
timeout_seconds=data.get("timeoutSeconds") or data.get("timeout_seconds", 300),
max_iterations=data.get("maxIterations") or data.get("max_iterations", 100),
log_level=data.get("logLevel") or data.get("log_level", "info"),
log_payloads=data.get("logPayloads") or data.get("log_payloads", False),
thread_ttl_seconds=data.get("threadTtlSeconds") or data.get("thread_ttl_seconds", 86400),
)
# =============================================================================
# Flow
# =============================================================================
@dataclass
class Flow:
"""
The complete definition of an agent workflow.
This is the domain model that bridges:
- Frontend canvas JSON
- Database storage
- Organism YAML for execution
"""
# Identity
id: UUID
name: str
description: str = ""
# Owner
owner_id: UUID | None = None
# Components
nodes: list[Node] = field(default_factory=list)
edges: list[Edge] = field(default_factory=list)
triggers: list[Trigger] = field(default_factory=list)
# Configuration
settings: FlowSettings = field(default_factory=FlowSettings)
# State
is_active: bool = False
version: int = 1
# Metadata
created_at: datetime | None = None
updated_at: datetime | None = None
# ==========================================================================
# Node Helpers
# ==========================================================================
def get_node(self, node_id: UUID) -> Node | None:
"""Get a node by ID."""
for node in self.nodes:
if node.id == node_id:
return node
return None
def get_node_by_name(self, name: str) -> Node | None:
"""Get a node by name."""
for node in self.nodes:
if node.name == name:
return node
return None
def get_agents(self) -> list[AgentNode]:
"""Get all agent nodes."""
return [n for n in self.nodes if isinstance(n, AgentNode)]
def get_tools(self) -> list[ToolNode]:
"""Get all tool nodes."""
return [n for n in self.nodes if isinstance(n, ToolNode)]
def get_gateways(self) -> list[GatewayNode]:
"""Get all gateway nodes."""
return [n for n in self.nodes if isinstance(n, GatewayNode)]
def _build_node_map(self) -> dict[UUID, str]:
"""Build a mapping of node IDs to names."""
return {node.id: node.name for node in self.nodes}
# ==========================================================================
# Validation
# ==========================================================================
def validate(self) -> list[ValidationError]:
"""
Validate the flow for errors.
Returns a list of validation errors (empty if valid).
"""
errors: list[ValidationError] = []
node_map = self._build_node_map()
node_ids = set(node_map.keys())
# Check for unique node names
names_seen: set[str] = set()
for node in self.nodes:
if node.name in names_seen:
errors.append(ValidationError(
code="duplicate_node_name",
message=f"Duplicate node name: {node.name}",
node_id=node.id,
))
names_seen.add(node.name)
# Check for valid node names (no spaces, special chars)
for node in self.nodes:
if not node.name or not node.name.replace("_", "").replace("-", "").isalnum():
errors.append(ValidationError(
code="invalid_node_name",
message=f"Invalid node name: {node.name}. Use alphanumeric, underscore, or hyphen.",
node_id=node.id,
))
# Check agents have prompts
for agent in self.get_agents():
if not agent.prompt or not agent.prompt.strip():
errors.append(ValidationError(
code="missing_agent_prompt",
message=f"Agent '{agent.name}' has no prompt",
node_id=agent.id,
))
# Check custom tools have handler paths
for tool in self.get_tools():
from bloxserver.domain.nodes import ToolType, BUILTIN_TOOLS
if tool.tool_type == ToolType.CUSTOM:
if not tool.handler_path or not tool.payload_class_path:
errors.append(ValidationError(
code="missing_custom_tool_paths",
message=f"Custom tool '{tool.name}' requires handler_path and payload_class_path",
node_id=tool.id,
))
# Check gateways have required config
for gateway in self.get_gateways():
if not gateway.remote_url and not gateway.api_endpoint:
errors.append(ValidationError(
code="invalid_gateway_config",
message=f"Gateway '{gateway.name}' requires remote_url or api_endpoint",
node_id=gateway.id,
))
# Check edges reference valid nodes
for edge in self.edges:
if edge.source_node_id not in node_ids:
errors.append(ValidationError(
code="invalid_edge_source",
message=f"Edge source node not found: {edge.source_node_id}",
edge_id=edge.id,
))
if edge.target_node_id not in node_ids:
errors.append(ValidationError(
code="invalid_edge_target",
message=f"Edge target node not found: {edge.target_node_id}",
edge_id=edge.id,
))
# Check triggers reference valid nodes
for trigger in self.triggers:
for target_id in trigger.target_node_ids:
if target_id not in node_ids:
errors.append(ValidationError(
code="invalid_trigger_target",
message=f"Trigger '{trigger.name}' targets unknown node: {target_id}",
trigger_id=trigger.id,
))
# Check for entry points (nodes reachable from triggers)
entry_nodes = find_entry_nodes(list(node_ids), self.edges)
trigger_targets = set()
for trigger in self.triggers:
trigger_targets.update(trigger.target_node_ids)
orphan_entries = [nid for nid in entry_nodes if nid not in trigger_targets]
for nid in orphan_entries:
node = self.get_node(nid)
if node:
errors.append(ValidationError(
code="unreachable_entry_node",
message=f"Node '{node.name}' has no incoming edges and no trigger",
node_id=nid,
severity="warning",
))
# Check for cycles (warning, not error - agents can self-loop)
cycles = detect_cycles(list(node_ids), self.edges)
for cycle in cycles:
cycle_names = [node_map.get(nid, str(nid)) for nid in cycle]
errors.append(ValidationError(
code="cycle_detected",
message=f"Cycle detected: {' -> '.join(cycle_names)}",
severity="info",
))
return errors
# ==========================================================================
# Serialization: Canvas JSON
# ==========================================================================
def to_canvas_json(self) -> dict[str, Any]:
"""
Convert to React Flow canvas format.
Returns a dict with 'nodes', 'edges', 'triggers', 'settings'.
"""
return {
"id": str(self.id),
"name": self.name,
"description": self.description,
"nodes": [node.to_dict() for node in self.nodes],
"edges": [edge.to_dict() for edge in self.edges],
"triggers": [trigger.to_dict() for trigger in self.triggers],
"settings": self.settings.to_dict(),
"isActive": self.is_active,
"version": self.version,
}
@classmethod
def from_canvas_json(
cls,
data: dict[str, Any],
flow_id: UUID | None = None,
owner_id: UUID | None = None,
) -> Flow:
"""
Create a Flow from React Flow canvas JSON.
Args:
data: Canvas JSON with nodes, edges, triggers, settings.
flow_id: Override the flow ID (for updates).
owner_id: Owner user ID.
"""
# Parse nodes
nodes: list[Node] = []
for node_data in data.get("nodes", []):
nodes.append(Node.from_dict(node_data))
# Parse edges
edges: list[Edge] = []
for edge_data in data.get("edges", []):
edges.append(Edge.from_dict(edge_data))
# Parse triggers
triggers: list[Trigger] = []
for trigger_data in data.get("triggers", []):
triggers.append(Trigger.from_dict(trigger_data))
# Parse settings
settings_data = data.get("settings", {})
settings = FlowSettings.from_dict(settings_data) if settings_data else FlowSettings()
# Determine flow ID
if flow_id:
fid = flow_id
elif "id" in data:
fid = UUID(data["id"]) if isinstance(data["id"], str) else data["id"]
else:
fid = uuid4()
return cls(
id=fid,
name=data.get("name", "Untitled Flow"),
description=data.get("description", ""),
owner_id=owner_id,
nodes=nodes,
edges=edges,
triggers=triggers,
settings=settings,
is_active=data.get("isActive") or data.get("is_active", False),
version=data.get("version", 1),
)
# ==========================================================================
# Serialization: Organism YAML
# ==========================================================================
def to_organism_yaml(self, port: int = 0) -> str:
"""
Convert to xml-pipeline organism.yaml format.
Args:
port: Port for the organism (0 = auto-assign).
Returns:
YAML string ready for the xml-pipeline runner.
"""
node_map = self._build_node_map()
# Build listeners list
listeners: list[dict[str, Any]] = []
gateways: list[dict[str, Any]] = []
for node in self.nodes:
if isinstance(node, AgentNode):
peers = compute_peers(node.id, self.edges, node_map)
listeners.append(node.to_listener_config(peers))
elif isinstance(node, ToolNode):
listeners.append(node.to_listener_config())
elif isinstance(node, GatewayNode):
config = node.to_listener_config()
if node.remote_url:
# Federation gateway goes in gateways section
gateways.append(config)
else:
# REST gateway is a listener
listeners.append(config)
# Build organism config
organism_config: dict[str, Any] = {
"organism": {
"name": f"flow-{self.id}",
"port": port,
},
"listeners": listeners,
}
# Add gateways if any
if gateways:
organism_config["gateways"] = gateways
# Add LLM config
organism_config["llm"] = {
"strategy": self.settings.llm.strategy,
"retries": self.settings.llm.retries,
"retry_base_delay": self.settings.llm.retry_base_delay,
}
# Add execution settings as metadata
organism_config["execution"] = {
"timeout_seconds": self.settings.timeout_seconds,
"max_iterations": self.settings.max_iterations,
"log_level": self.settings.log_level,
"log_payloads": self.settings.log_payloads,
}
# Add trigger metadata for runtime
if self.triggers:
organism_config["triggers"] = [
{
"id": str(t.id),
"name": t.name,
"type": t.trigger_type.value,
"target_nodes": [node_map.get(nid, str(nid)) for nid in t.target_node_ids],
"enabled": t.enabled,
}
for t in self.triggers
]
return yaml.dump(
organism_config,
default_flow_style=False,
sort_keys=False,
allow_unicode=True,
)
# ==========================================================================
# Database Serialization
# ==========================================================================
def to_db_dict(self) -> dict[str, Any]:
"""
Convert to dictionary for database storage.
This is stored in FlowRecord.canvas_data as JSON.
"""
return {
"nodes": [node.to_dict() for node in self.nodes],
"edges": [edge.to_dict() for edge in self.edges],
"triggers": [trigger.to_dict() for trigger in self.triggers],
"settings": self.settings.to_dict(),
}
@classmethod
def from_db_record(cls, record: Any) -> Flow:
"""
Create a Flow from a database FlowRecord.
Args:
record: FlowRecord ORM instance.
"""
canvas_data = record.canvas_data or {}
# Parse components from canvas_data
nodes: list[Node] = []
for node_data in canvas_data.get("nodes", []):
nodes.append(Node.from_dict(node_data))
edges: list[Edge] = []
for edge_data in canvas_data.get("edges", []):
edges.append(Edge.from_dict(edge_data))
triggers: list[Trigger] = []
for trigger_data in canvas_data.get("triggers", []):
triggers.append(Trigger.from_dict(trigger_data))
settings_data = canvas_data.get("settings", {})
settings = FlowSettings.from_dict(settings_data) if settings_data else FlowSettings()
return cls(
id=record.id,
name=record.name,
description=record.description or "",
owner_id=record.owner_id,
nodes=nodes,
edges=edges,
triggers=triggers,
settings=settings,
is_active=record.status.value == "active" if hasattr(record.status, "value") else record.status == "active",
version=record.version,
created_at=record.created_at,
updated_at=record.updated_at,
)

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@ -1,412 +0,0 @@
"""
Node types for BloxServer flows.
Nodes are the building blocks of flows:
- AgentNode: LLM-powered agents with prompts and reasoning
- ToolNode: Built-in tools (calculate, fetch, shell, etc.)
- GatewayNode: External APIs or federated organisms
"""
from __future__ import annotations
from dataclasses import dataclass, field
from enum import Enum
from typing import Any
from uuid import UUID, uuid4
class NodeType(str, Enum):
"""Types of nodes in a flow."""
AGENT = "agent"
TOOL = "tool"
GATEWAY = "gateway"
# =============================================================================
# Built-in Tool Types
# =============================================================================
class ToolType(str, Enum):
"""Built-in tool types available in BloxServer."""
CALCULATE = "calculate"
FETCH = "fetch"
READ_FILE = "read_file"
WRITE_FILE = "write_file"
LIST_DIR = "list_dir"
SHELL = "shell"
WEB_SEARCH = "web_search"
KEY_VALUE = "key_value"
SEND_EMAIL = "send_email"
WEBHOOK = "webhook"
LIBRARIAN = "librarian"
CUSTOM = "custom"
# =============================================================================
# Base Node
# =============================================================================
@dataclass
class Node:
"""Base class for all node types."""
id: UUID
name: str
description: str
node_type: NodeType
# Canvas position (for frontend rendering)
position_x: float = 0.0
position_y: float = 0.0
# Metadata for UI
color: str | None = None
icon: str | None = None
def to_dict(self) -> dict[str, Any]:
"""Convert to dictionary for JSON serialization."""
return {
"id": str(self.id),
"name": self.name,
"description": self.description,
"nodeType": self.node_type.value,
"position": {"x": self.position_x, "y": self.position_y},
"color": self.color,
"icon": self.icon,
}
@classmethod
def from_dict(cls, data: dict[str, Any]) -> Node:
"""Create node from dictionary. Dispatches to appropriate subclass."""
node_type = NodeType(data.get("nodeType", data.get("node_type")))
if node_type == NodeType.AGENT:
return AgentNode.from_dict(data)
elif node_type == NodeType.TOOL:
return ToolNode.from_dict(data)
elif node_type == NodeType.GATEWAY:
return GatewayNode.from_dict(data)
else:
raise ValueError(f"Unknown node type: {node_type}")
# =============================================================================
# Agent Node
# =============================================================================
@dataclass
class AgentNode(Node):
"""
LLM-powered agent node.
Agents have prompts, can reason, and communicate with other nodes.
They are the "brains" of a flow.
"""
node_type: NodeType = field(default=NodeType.AGENT, init=False)
# Agent configuration
prompt: str = ""
model: str | None = None # None = use default from org settings
# Advanced settings
temperature: float = 0.7
max_tokens: int | None = None
system_prompt_append: str | None = None # Extra instructions
# Handler paths (auto-generated if not specified)
handler_path: str | None = None
payload_class_path: str | None = None
def to_dict(self) -> dict[str, Any]:
base = super().to_dict()
base.update({
"prompt": self.prompt,
"model": self.model,
"temperature": self.temperature,
"maxTokens": self.max_tokens,
"systemPromptAppend": self.system_prompt_append,
"handlerPath": self.handler_path,
"payloadClassPath": self.payload_class_path,
})
return base
@classmethod
def from_dict(cls, data: dict[str, Any]) -> AgentNode:
position = data.get("position", {})
return cls(
id=UUID(data["id"]) if isinstance(data.get("id"), str) else data.get("id", uuid4()),
name=data["name"],
description=data.get("description", ""),
position_x=position.get("x", 0.0),
position_y=position.get("y", 0.0),
color=data.get("color"),
icon=data.get("icon"),
prompt=data.get("prompt", ""),
model=data.get("model"),
temperature=data.get("temperature", 0.7),
max_tokens=data.get("maxTokens") or data.get("max_tokens"),
system_prompt_append=data.get("systemPromptAppend") or data.get("system_prompt_append"),
handler_path=data.get("handlerPath") or data.get("handler_path"),
payload_class_path=data.get("payloadClassPath") or data.get("payload_class_path"),
)
def to_listener_config(self, peers: list[str]) -> dict[str, Any]:
"""
Convert to organism.yaml listener configuration.
Args:
peers: List of peer names derived from outgoing edges.
"""
config: dict[str, Any] = {
"name": self.name,
"description": self.description,
"agent": True,
"prompt": self.prompt,
}
if peers:
config["peers"] = peers
if self.handler_path:
config["handler"] = self.handler_path
if self.payload_class_path:
config["payload_class"] = self.payload_class_path
# LLM settings as metadata (for future use)
if self.model:
config["model"] = self.model
if self.temperature != 0.7:
config["temperature"] = self.temperature
if self.max_tokens:
config["max_tokens"] = self.max_tokens
return config
# =============================================================================
# Tool Node
# =============================================================================
# Tool handler/payload mappings for built-in tools
BUILTIN_TOOLS: dict[ToolType, dict[str, str]] = {
ToolType.CALCULATE: {
"handler": "xml_pipeline.tools.calculate.handle_calculate",
"payload_class": "xml_pipeline.tools.calculate.CalculatePayload",
},
ToolType.FETCH: {
"handler": "xml_pipeline.tools.fetch.handle_fetch",
"payload_class": "xml_pipeline.tools.fetch.FetchPayload",
},
ToolType.READ_FILE: {
"handler": "xml_pipeline.tools.files.handle_read",
"payload_class": "xml_pipeline.tools.files.ReadFilePayload",
},
ToolType.WRITE_FILE: {
"handler": "xml_pipeline.tools.files.handle_write",
"payload_class": "xml_pipeline.tools.files.WriteFilePayload",
},
ToolType.LIST_DIR: {
"handler": "xml_pipeline.tools.files.handle_list",
"payload_class": "xml_pipeline.tools.files.ListDirPayload",
},
ToolType.SHELL: {
"handler": "xml_pipeline.tools.shell.handle_shell",
"payload_class": "xml_pipeline.tools.shell.ShellPayload",
},
ToolType.WEB_SEARCH: {
"handler": "xml_pipeline.tools.search.handle_search",
"payload_class": "xml_pipeline.tools.search.SearchPayload",
},
ToolType.KEY_VALUE: {
"handler": "xml_pipeline.tools.keyvalue.handle_keyvalue",
"payload_class": "xml_pipeline.tools.keyvalue.KeyValuePayload",
},
ToolType.LIBRARIAN: {
"handler": "xml_pipeline.tools.librarian.handle_librarian",
"payload_class": "xml_pipeline.tools.librarian.LibrarianPayload",
},
}
@dataclass
class ToolNode(Node):
"""
Built-in or custom tool node.
Tools are stateless functions that perform specific operations
like calculations, HTTP requests, file operations, etc.
"""
node_type: NodeType = field(default=NodeType.TOOL, init=False)
# Tool configuration
tool_type: ToolType = ToolType.CUSTOM
config: dict[str, Any] = field(default_factory=dict)
# Custom tool paths (only for CUSTOM type)
handler_path: str | None = None
payload_class_path: str | None = None
def to_dict(self) -> dict[str, Any]:
base = super().to_dict()
base.update({
"toolType": self.tool_type.value,
"config": self.config,
"handlerPath": self.handler_path,
"payloadClassPath": self.payload_class_path,
})
return base
@classmethod
def from_dict(cls, data: dict[str, Any]) -> ToolNode:
position = data.get("position", {})
tool_type_str = data.get("toolType") or data.get("tool_type", "custom")
return cls(
id=UUID(data["id"]) if isinstance(data.get("id"), str) else data.get("id", uuid4()),
name=data["name"],
description=data.get("description", ""),
position_x=position.get("x", 0.0),
position_y=position.get("y", 0.0),
color=data.get("color"),
icon=data.get("icon"),
tool_type=ToolType(tool_type_str),
config=data.get("config", {}),
handler_path=data.get("handlerPath") or data.get("handler_path"),
payload_class_path=data.get("payloadClassPath") or data.get("payload_class_path"),
)
def to_listener_config(self) -> dict[str, Any]:
"""Convert to organism.yaml listener configuration."""
# Get handler/payload from built-in mapping or custom paths
if self.tool_type in BUILTIN_TOOLS:
tool_info = BUILTIN_TOOLS[self.tool_type]
handler = tool_info["handler"]
payload_class = tool_info["payload_class"]
else:
handler = self.handler_path
payload_class = self.payload_class_path
if not handler or not payload_class:
raise ValueError(
f"Custom tool '{self.name}' requires handler_path and payload_class_path"
)
config: dict[str, Any] = {
"name": self.name,
"description": self.description,
"handler": handler,
"payload_class": payload_class,
}
# Include tool-specific config if present
if self.config:
config["tool_config"] = self.config
return config
# =============================================================================
# Gateway Node
# =============================================================================
@dataclass
class GatewayNode(Node):
"""
External API or federated organism gateway.
Gateways connect flows to:
- External REST APIs
- Federated xml-pipeline organisms
- Third-party services (Slack, Discord, etc.)
"""
node_type: NodeType = field(default=NodeType.GATEWAY, init=False)
# Federation (other xml-pipeline organisms)
remote_url: str | None = None
trusted_identity: str | None = None # Path to public key
# REST API gateway
api_endpoint: str | None = None
api_method: str = "POST"
api_headers: dict[str, str] = field(default_factory=dict)
api_auth_type: str | None = None # bearer, api_key, basic
api_auth_env_var: str | None = None # Env var containing the secret
# Response mapping
response_mapping: dict[str, str] = field(default_factory=dict)
def to_dict(self) -> dict[str, Any]:
base = super().to_dict()
base.update({
"remoteUrl": self.remote_url,
"trustedIdentity": self.trusted_identity,
"apiEndpoint": self.api_endpoint,
"apiMethod": self.api_method,
"apiHeaders": self.api_headers,
"apiAuthType": self.api_auth_type,
"apiAuthEnvVar": self.api_auth_env_var,
"responseMapping": self.response_mapping,
})
return base
@classmethod
def from_dict(cls, data: dict[str, Any]) -> GatewayNode:
position = data.get("position", {})
return cls(
id=UUID(data["id"]) if isinstance(data.get("id"), str) else data.get("id", uuid4()),
name=data["name"],
description=data.get("description", ""),
position_x=position.get("x", 0.0),
position_y=position.get("y", 0.0),
color=data.get("color"),
icon=data.get("icon"),
remote_url=data.get("remoteUrl") or data.get("remote_url"),
trusted_identity=data.get("trustedIdentity") or data.get("trusted_identity"),
api_endpoint=data.get("apiEndpoint") or data.get("api_endpoint"),
api_method=data.get("apiMethod") or data.get("api_method", "POST"),
api_headers=data.get("apiHeaders") or data.get("api_headers", {}),
api_auth_type=data.get("apiAuthType") or data.get("api_auth_type"),
api_auth_env_var=data.get("apiAuthEnvVar") or data.get("api_auth_env_var"),
response_mapping=data.get("responseMapping") or data.get("response_mapping", {}),
)
def to_listener_config(self) -> dict[str, Any]:
"""Convert to organism.yaml listener/gateway configuration."""
if self.remote_url:
# Federation gateway
return {
"name": self.name,
"remote_url": self.remote_url,
"trusted_identity": self.trusted_identity,
"description": self.description,
}
elif self.api_endpoint:
# REST API gateway (custom handler)
return {
"name": self.name,
"description": self.description,
"handler": "bloxserver.gateways.rest.handle_rest_gateway",
"payload_class": "bloxserver.gateways.rest.RestGatewayPayload",
"gateway_config": {
"endpoint": self.api_endpoint,
"method": self.api_method,
"headers": self.api_headers,
"auth_type": self.api_auth_type,
"auth_env_var": self.api_auth_env_var,
"response_mapping": self.response_mapping,
},
}
else:
raise ValueError(
f"Gateway '{self.name}' requires either remote_url (federation) "
"or api_endpoint (REST)"
)

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@ -1,317 +0,0 @@
"""
Trigger types for starting flow execution.
Triggers define how a flow is initiated:
- Webhook: External HTTP POST to a unique URL
- Schedule: Cron-based scheduled execution
- Manual: User-initiated from dashboard
- Event: Internal event subscription
"""
from __future__ import annotations
from dataclasses import dataclass, field
from datetime import datetime
from enum import Enum
from typing import Any
from uuid import UUID, uuid4
class TriggerType(str, Enum):
"""Types of triggers that can start a flow."""
WEBHOOK = "webhook"
SCHEDULE = "schedule"
MANUAL = "manual"
EVENT = "event"
# =============================================================================
# Trigger Configs
# =============================================================================
@dataclass
class WebhookConfig:
"""Configuration for webhook triggers."""
# Auto-generated token for authentication
token: str | None = None
# Optional: require specific headers
required_headers: dict[str, str] = field(default_factory=dict)
# Optional: IP allowlist
allowed_ips: list[str] = field(default_factory=list)
# Payload transformation
payload_template: str | None = None # Jinja2 template for input transformation
def to_dict(self) -> dict[str, Any]:
return {
"token": self.token,
"requiredHeaders": self.required_headers,
"allowedIps": self.allowed_ips,
"payloadTemplate": self.payload_template,
}
@classmethod
def from_dict(cls, data: dict[str, Any]) -> WebhookConfig:
return cls(
token=data.get("token"),
required_headers=data.get("requiredHeaders") or data.get("required_headers", {}),
allowed_ips=data.get("allowedIps") or data.get("allowed_ips", []),
payload_template=data.get("payloadTemplate") or data.get("payload_template"),
)
@dataclass
class ScheduleConfig:
"""Configuration for scheduled triggers."""
# Cron expression (e.g., "0 9 * * *" for 9 AM daily)
cron: str
# Timezone (e.g., "America/New_York")
timezone: str = "UTC"
# Optional: specific dates to skip
skip_dates: list[str] = field(default_factory=list)
# Optional: payload to inject on trigger
default_payload: dict[str, Any] = field(default_factory=dict)
# Execution window (skip if missed by more than N minutes)
grace_period_minutes: int = 5
def to_dict(self) -> dict[str, Any]:
return {
"cron": self.cron,
"timezone": self.timezone,
"skipDates": self.skip_dates,
"defaultPayload": self.default_payload,
"gracePeriodMinutes": self.grace_period_minutes,
}
@classmethod
def from_dict(cls, data: dict[str, Any]) -> ScheduleConfig:
return cls(
cron=data["cron"],
timezone=data.get("timezone", "UTC"),
skip_dates=data.get("skipDates") or data.get("skip_dates", []),
default_payload=data.get("defaultPayload") or data.get("default_payload", {}),
grace_period_minutes=data.get("gracePeriodMinutes") or data.get("grace_period_minutes", 5),
)
@dataclass
class ManualConfig:
"""Configuration for manual triggers."""
# Form fields to show in dashboard
input_fields: list[dict[str, Any]] = field(default_factory=list)
# Default values
default_payload: dict[str, Any] = field(default_factory=dict)
# Confirmation required before execution
require_confirmation: bool = False
confirmation_message: str | None = None
def to_dict(self) -> dict[str, Any]:
return {
"inputFields": self.input_fields,
"defaultPayload": self.default_payload,
"requireConfirmation": self.require_confirmation,
"confirmationMessage": self.confirmation_message,
}
@classmethod
def from_dict(cls, data: dict[str, Any]) -> ManualConfig:
return cls(
input_fields=data.get("inputFields") or data.get("input_fields", []),
default_payload=data.get("defaultPayload") or data.get("default_payload", {}),
require_confirmation=data.get("requireConfirmation") or data.get("require_confirmation", False),
confirmation_message=data.get("confirmationMessage") or data.get("confirmation_message"),
)
@dataclass
class EventConfig:
"""Configuration for internal event triggers."""
# Event name to subscribe to
event_name: str
# Optional: filter expression
filter_expression: str | None = None
# Source flow ID (if triggered by another flow)
source_flow_id: UUID | None = None
def to_dict(self) -> dict[str, Any]:
return {
"eventName": self.event_name,
"filterExpression": self.filter_expression,
"sourceFlowId": str(self.source_flow_id) if self.source_flow_id else None,
}
@classmethod
def from_dict(cls, data: dict[str, Any]) -> EventConfig:
source_flow = data.get("sourceFlowId") or data.get("source_flow_id")
return cls(
event_name=data["eventName"] if "eventName" in data else data["event_name"],
filter_expression=data.get("filterExpression") or data.get("filter_expression"),
source_flow_id=UUID(source_flow) if source_flow else None,
)
# Union type for trigger configs
TriggerConfig = WebhookConfig | ScheduleConfig | ManualConfig | EventConfig
# =============================================================================
# Trigger
# =============================================================================
@dataclass
class Trigger:
"""
A trigger that initiates flow execution.
Triggers are connected to entry nodes in the flow.
When fired, they inject a message into the entry node(s).
"""
id: UUID
name: str
trigger_type: TriggerType
config: TriggerConfig
# Which node(s) to send the initial message to
target_node_ids: list[UUID] = field(default_factory=list)
# Enabled state
enabled: bool = True
# Metadata
created_at: datetime | None = None
last_triggered_at: datetime | None = None
def to_dict(self) -> dict[str, Any]:
return {
"id": str(self.id),
"name": self.name,
"triggerType": self.trigger_type.value,
"config": self.config.to_dict(),
"targetNodeIds": [str(nid) for nid in self.target_node_ids],
"enabled": self.enabled,
"createdAt": self.created_at.isoformat() if self.created_at else None,
"lastTriggeredAt": self.last_triggered_at.isoformat() if self.last_triggered_at else None,
}
@classmethod
def from_dict(cls, data: dict[str, Any]) -> Trigger:
trigger_type = TriggerType(data.get("triggerType") or data.get("trigger_type"))
config_data = data.get("config", {})
# Parse config based on trigger type
config: TriggerConfig
if trigger_type == TriggerType.WEBHOOK:
config = WebhookConfig.from_dict(config_data)
elif trigger_type == TriggerType.SCHEDULE:
config = ScheduleConfig.from_dict(config_data)
elif trigger_type == TriggerType.MANUAL:
config = ManualConfig.from_dict(config_data)
elif trigger_type == TriggerType.EVENT:
config = EventConfig.from_dict(config_data)
else:
raise ValueError(f"Unknown trigger type: {trigger_type}")
# Parse target node IDs
target_ids_raw = data.get("targetNodeIds") or data.get("target_node_ids", [])
target_node_ids = [
UUID(nid) if isinstance(nid, str) else nid
for nid in target_ids_raw
]
# Parse timestamps
created_at = None
if created := data.get("createdAt") or data.get("created_at"):
created_at = datetime.fromisoformat(created) if isinstance(created, str) else created
last_triggered = None
if triggered := data.get("lastTriggeredAt") or data.get("last_triggered_at"):
last_triggered = datetime.fromisoformat(triggered) if isinstance(triggered, str) else triggered
return cls(
id=UUID(data["id"]) if isinstance(data.get("id"), str) else data.get("id", uuid4()),
name=data["name"],
trigger_type=trigger_type,
config=config,
target_node_ids=target_node_ids,
enabled=data.get("enabled", True),
created_at=created_at,
last_triggered_at=last_triggered,
)
def get_webhook_url(self, base_url: str, flow_id: UUID) -> str | None:
"""Get the webhook URL if this is a webhook trigger."""
if self.trigger_type != TriggerType.WEBHOOK:
return None
if not isinstance(self.config, WebhookConfig):
return None
token = self.config.token or ""
return f"{base_url}/webhooks/{flow_id}/{self.id}?token={token}"
def create_webhook_trigger(
name: str,
target_node_ids: list[UUID],
token: str | None = None,
) -> Trigger:
"""Factory function to create a webhook trigger."""
return Trigger(
id=uuid4(),
name=name,
trigger_type=TriggerType.WEBHOOK,
config=WebhookConfig(token=token),
target_node_ids=target_node_ids,
enabled=True,
)
def create_schedule_trigger(
name: str,
cron: str,
target_node_ids: list[UUID],
timezone: str = "UTC",
) -> Trigger:
"""Factory function to create a scheduled trigger."""
return Trigger(
id=uuid4(),
name=name,
trigger_type=TriggerType.SCHEDULE,
config=ScheduleConfig(cron=cron, timezone=timezone),
target_node_ids=target_node_ids,
enabled=True,
)
def create_manual_trigger(
name: str,
target_node_ids: list[UUID],
input_fields: list[dict[str, Any]] | None = None,
) -> Trigger:
"""Factory function to create a manual trigger."""
return Trigger(
id=uuid4(),
name=name,
trigger_type=TriggerType.MANUAL,
config=ManualConfig(input_fields=input_fields or []),
target_node_ids=target_node_ids,
enabled=True,
)

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@ -1,31 +0,0 @@
# BloxServer API Dependencies
# Web framework
fastapi>=0.109.0
uvicorn[standard]>=0.27.0
# Database
sqlalchemy[asyncio]>=2.0.0
asyncpg>=0.29.0
alembic>=1.13.0
# Authentication (Clerk JWT validation)
pyjwt[crypto]>=2.8.0
httpx>=0.27.0
# Validation & serialization
pydantic>=2.5.0
pydantic-settings>=2.1.0
# Utilities
python-dotenv>=1.0.0
humps>=0.2.2
# Stripe billing
stripe>=8.0.0
# Redis (for caching/rate limiting)
redis>=5.0.0
# Cryptography (for API key encryption)
cryptography>=42.0.0

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@ -1,13 +0,0 @@
"""
BloxServer Runtime Flow execution engine.
This module bridges BloxServer flows to xml-pipeline's StreamPump.
"""
from bloxserver.runtime.flow_runner import FlowRunner, FlowRunnerState, ExecutionEvent
__all__ = [
"FlowRunner",
"FlowRunnerState",
"ExecutionEvent",
]

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@ -1,686 +0,0 @@
"""
FlowRunner Execution bridge between BloxServer flows and xml-pipeline.
The FlowRunner:
1. Takes a Flow domain object
2. Converts it to xml-pipeline configuration
3. Creates and manages a StreamPump instance
4. Handles triggers (webhook, schedule, manual)
5. Tracks execution state and events
Usage:
flow = Flow.from_canvas_json(canvas_data)
runner = FlowRunner(flow)
await runner.start()
# Trigger execution
await runner.trigger("my_webhook", payload={"query": "hello"})
# Or inject directly to a node
await runner.inject("researcher", {"query": "hello"})
await runner.stop()
"""
from __future__ import annotations
import asyncio
import importlib
import logging
import tempfile
from dataclasses import dataclass, field
from datetime import datetime, timezone
from enum import Enum
from pathlib import Path
from typing import Any, Callable
from uuid import UUID, uuid4
from bloxserver.domain import Flow, AgentNode, ToolNode, GatewayNode
from bloxserver.domain.triggers import Trigger, TriggerType
logger = logging.getLogger(__name__)
# =============================================================================
# State & Events
# =============================================================================
class FlowRunnerState(str, Enum):
"""Lifecycle states for a FlowRunner."""
CREATED = "created" # Initial state
STARTING = "starting" # Registering listeners, preparing pump
RUNNING = "running" # Pump is active, accepting messages
STOPPING = "stopping" # Graceful shutdown in progress
STOPPED = "stopped" # Fully stopped
ERROR = "error" # Failed to start or crashed
@dataclass
class ExecutionEvent:
"""An event during flow execution (for logging/monitoring)."""
timestamp: datetime
event_type: str # started, message_received, handler_called, error, stopped
node_name: str | None = None
thread_id: str | None = None
payload_type: str | None = None
message: str = ""
error: str | None = None
def to_dict(self) -> dict[str, Any]:
return {
"timestamp": self.timestamp.isoformat(),
"eventType": self.event_type,
"nodeName": self.node_name,
"threadId": self.thread_id,
"payloadType": self.payload_type,
"message": self.message,
"error": self.error,
}
# =============================================================================
# FlowRunner
# =============================================================================
class FlowRunner:
"""
Runs a BloxServer Flow using xml-pipeline's StreamPump.
This is the bridge between the Flow domain model and the actual
message pump execution. It handles:
- Converting Flow nodes to xml-pipeline ListenerConfigs
- Creating and managing the StreamPump lifecycle
- Handling triggers (webhook, schedule, manual)
- Tracking execution events for monitoring
Note: For production use, each Flow runs in its own FlowRunner instance.
Multiple FlowRunners can run concurrently (one per active flow).
"""
def __init__(
self,
flow: Flow,
port: int = 0,
event_callback: Callable[[ExecutionEvent], None] | None = None,
):
"""
Initialize a FlowRunner.
Args:
flow: The Flow domain object to run.
port: Port for the organism (0 = auto-assign).
event_callback: Optional callback for execution events.
"""
self.flow = flow
self.port = port
self.event_callback = event_callback
# State
self.state = FlowRunnerState.CREATED
self.started_at: datetime | None = None
self.stopped_at: datetime | None = None
self.error_message: str | None = None
# StreamPump instance (created on start)
self._pump = None
self._pump_task: asyncio.Task | None = None
# Execution tracking
self.execution_id = uuid4()
self.events: list[ExecutionEvent] = []
self.message_count = 0
# Thread tracking (root thread per execution)
self._root_thread_id: str | None = None
# Trigger handlers (for webhook callbacks)
self._trigger_handlers: dict[UUID, Callable] = {}
# =========================================================================
# Lifecycle
# =========================================================================
async def start(self) -> None:
"""
Start the flow runner.
This creates the StreamPump, registers all listeners, and starts
the message processing loop.
"""
if self.state not in (FlowRunnerState.CREATED, FlowRunnerState.STOPPED):
raise RuntimeError(f"Cannot start FlowRunner in state: {self.state}")
self.state = FlowRunnerState.STARTING
self.started_at = datetime.now(timezone.utc)
self._emit_event("starting", message=f"Starting flow: {self.flow.name}")
try:
# Validate flow before starting
errors = self.flow.validate()
blocking_errors = [e for e in errors if e.severity == "error"]
if blocking_errors:
error_msg = "; ".join(e.message for e in blocking_errors)
raise ValueError(f"Flow validation failed: {error_msg}")
# Create the pump
self._pump = await self._create_pump()
# Start the pump in a background task
self._pump_task = asyncio.create_task(self._run_pump())
self.state = FlowRunnerState.RUNNING
self._emit_event("started", message=f"Flow running: {len(self.flow.nodes)} nodes")
except Exception as e:
self.state = FlowRunnerState.ERROR
self.error_message = str(e)
self._emit_event("error", error=str(e))
logger.exception(f"Failed to start flow {self.flow.id}: {e}")
raise
async def stop(self, timeout: float = 30.0) -> None:
"""
Stop the flow runner gracefully.
Args:
timeout: Maximum time to wait for graceful shutdown.
"""
if self.state not in (FlowRunnerState.RUNNING, FlowRunnerState.ERROR):
return
self.state = FlowRunnerState.STOPPING
self._emit_event("stopping", message="Initiating graceful shutdown")
try:
if self._pump:
await self._pump.shutdown()
if self._pump_task:
self._pump_task.cancel()
try:
await asyncio.wait_for(self._pump_task, timeout=timeout)
except (asyncio.CancelledError, asyncio.TimeoutError):
pass
self.state = FlowRunnerState.STOPPED
self.stopped_at = datetime.now(timezone.utc)
self._emit_event("stopped", message=f"Flow stopped after {self.message_count} messages")
except Exception as e:
self.state = FlowRunnerState.ERROR
self.error_message = str(e)
self._emit_event("error", error=str(e))
raise
async def _run_pump(self) -> None:
"""Run the pump's main loop."""
try:
await self._pump.run()
except asyncio.CancelledError:
pass
except Exception as e:
self.state = FlowRunnerState.ERROR
self.error_message = str(e)
self._emit_event("error", error=f"Pump crashed: {e}")
logger.exception(f"Pump crashed for flow {self.flow.id}: {e}")
# =========================================================================
# Pump Creation
# =========================================================================
async def _create_pump(self):
"""Create and configure the StreamPump from the Flow."""
from xml_pipeline.message_bus.stream_pump import (
StreamPump,
OrganismConfig,
ListenerConfig,
)
from xml_pipeline.message_bus.thread_registry import get_registry
# Build OrganismConfig
org_config = self._build_organism_config()
# Create pump
pump = StreamPump(org_config)
# Register system listeners (boot, todo)
self._register_system_listeners(pump)
# Register flow listeners
for node in self.flow.nodes:
listener_config = self._node_to_listener_config(node)
if listener_config:
pump.register_listener(listener_config)
# Build usage instructions for agents
pump.register_all()
# Initialize root thread
registry = get_registry()
self._root_thread_id = registry.initialize_root(f"flow-{self.flow.id}")
# Inject boot message
await self._inject_boot_message(pump)
return pump
def _build_organism_config(self):
"""Build OrganismConfig from Flow settings."""
from xml_pipeline.message_bus.stream_pump import OrganismConfig
return OrganismConfig(
name=f"flow-{self.flow.id}",
port=self.port,
max_concurrent_pipelines=50,
max_concurrent_handlers=20,
max_concurrent_per_agent=5,
llm_config={
"strategy": self.flow.settings.llm.strategy,
"retries": self.flow.settings.llm.retries,
"retry_base_delay": self.flow.settings.llm.retry_base_delay,
},
)
def _register_system_listeners(self, pump) -> None:
"""Register system listeners (boot, todo) on the pump."""
from xml_pipeline.message_bus.stream_pump import ListenerConfig
from xml_pipeline.primitives import (
Boot, handle_boot,
TodoUntil, TodoComplete,
handle_todo_until, handle_todo_complete,
)
# Boot handler
pump.register_listener(ListenerConfig(
name="system.boot",
payload_class_path="xml_pipeline.primitives.Boot",
handler_path="xml_pipeline.primitives.handle_boot",
description="System boot handler",
payload_class=Boot,
handler=handle_boot,
))
# TodoUntil handler
pump.register_listener(ListenerConfig(
name="system.todo",
payload_class_path="xml_pipeline.primitives.TodoUntil",
handler_path="xml_pipeline.primitives.handle_todo_until",
description="System todo handler - registers watchers",
payload_class=TodoUntil,
handler=handle_todo_until,
))
# TodoComplete handler
pump.register_listener(ListenerConfig(
name="system.todo-complete",
payload_class_path="xml_pipeline.primitives.TodoComplete",
handler_path="xml_pipeline.primitives.handle_todo_complete",
description="System todo handler - closes watchers",
payload_class=TodoComplete,
handler=handle_todo_complete,
))
def _node_to_listener_config(self, node):
"""Convert a domain Node to a ListenerConfig."""
from xml_pipeline.message_bus.stream_pump import ListenerConfig
from bloxserver.domain.edges import compute_peers
node_map = {n.id: n.name for n in self.flow.nodes}
if isinstance(node, AgentNode):
# Agent node - needs dynamic handler
peers = compute_peers(node.id, self.flow.edges, node_map)
# For agents, we use a generic LLM handler
# The prompt is passed via config
handler, payload_class = self._get_agent_handler(node)
return ListenerConfig(
name=node.name,
payload_class_path=f"bloxserver.runtime.handlers.{node.name}",
handler_path=f"bloxserver.runtime.handlers.{node.name}",
description=node.description,
is_agent=True,
peers=peers,
prompt=node.prompt,
payload_class=payload_class,
handler=handler,
)
elif isinstance(node, ToolNode):
# Tool node - use built-in or custom handler
handler_path, payload_class_path = self._get_tool_paths(node)
# Import the actual classes
handler, payload_class = self._import_handler(handler_path, payload_class_path)
return ListenerConfig(
name=node.name,
payload_class_path=payload_class_path,
handler_path=handler_path,
description=node.description,
payload_class=payload_class,
handler=handler,
)
elif isinstance(node, GatewayNode):
# Gateway node - federation or REST
# TODO: Implement gateway handlers
logger.warning(f"Gateway nodes not yet implemented: {node.name}")
return None
return None
def _get_agent_handler(self, node: AgentNode):
"""
Get or create a handler for an agent node.
Agents use a generic LLM completion handler that:
1. Gets the prompt from PromptRegistry
2. Builds conversation from ContextBuffer
3. Calls LLM router
4. Parses response and routes to peers
"""
from dataclasses import dataclass
from third_party.xmlable import xmlify
# Create a dynamic payload class for this agent
@xmlify
@dataclass
class AgentInput:
"""Input message for agent."""
content: str
# Create handler that uses the agent's prompt
async def agent_handler(payload, metadata):
from xml_pipeline.message_bus.message_state import HandlerResponse
from xml_pipeline.platform import get_prompt_registry
from xml_pipeline.llm import complete
# Get the registered prompt
prompt_registry = get_prompt_registry()
prompt_data = prompt_registry.get(metadata.own_name)
system_prompt = ""
if prompt_data:
system_prompt = prompt_data.full_prompt
# Build messages for LLM
messages = [
{"role": "system", "content": system_prompt},
{"role": "user", "content": payload.content},
]
# Call LLM
try:
response = await complete(
model=node.model or "grok-4.1",
messages=messages,
agent_id=metadata.own_name,
temperature=node.temperature,
max_tokens=node.max_tokens,
)
# For now, just echo response
# TODO: Parse response for tool calls, routing
@xmlify
@dataclass
class AgentOutput:
content: str
return HandlerResponse(
payload=AgentOutput(content=response.content),
to=metadata.from_id, # Reply to caller
)
except Exception as e:
logger.error(f"Agent {metadata.own_name} LLM error: {e}")
return None
return agent_handler, AgentInput
def _get_tool_paths(self, node: ToolNode) -> tuple[str, str]:
"""Get handler and payload class paths for a tool node."""
from bloxserver.domain.nodes import BUILTIN_TOOLS
if node.tool_type in BUILTIN_TOOLS:
info = BUILTIN_TOOLS[node.tool_type]
return info["handler"], info["payload_class"]
# Custom tool
if node.handler_path and node.payload_class_path:
return node.handler_path, node.payload_class_path
raise ValueError(f"Tool {node.name} has no handler configured")
def _import_handler(self, handler_path: str, payload_class_path: str):
"""Import handler function and payload class."""
# Import payload class
mod_path, class_name = payload_class_path.rsplit(".", 1)
mod = importlib.import_module(mod_path)
payload_class = getattr(mod, class_name)
# Import handler
mod_path, fn_name = handler_path.rsplit(".", 1)
mod = importlib.import_module(mod_path)
handler = getattr(mod, fn_name)
return handler, payload_class
async def _inject_boot_message(self, pump) -> None:
"""Inject the boot message to start the organism."""
from xml_pipeline.primitives import Boot
boot_payload = Boot(
organism_name=f"flow-{self.flow.id}",
timestamp=datetime.now(timezone.utc).isoformat().replace("+00:00", "Z"),
listener_count=len(pump.listeners),
)
boot_envelope = pump._wrap_in_envelope(
payload=boot_payload,
from_id="system",
to_id="system.boot",
thread_id=self._root_thread_id,
)
await pump.inject(boot_envelope, thread_id=self._root_thread_id, from_id="system")
# =========================================================================
# Message Injection
# =========================================================================
async def inject(
self,
target_node: str,
payload_data: dict[str, Any],
thread_id: str | None = None,
) -> str:
"""
Inject a message to a specific node.
Args:
target_node: Name of the target node.
payload_data: Payload data (will be wrapped in node's payload class).
thread_id: Optional thread ID (creates new thread if not provided).
Returns:
The thread ID used for this message.
"""
if self.state != FlowRunnerState.RUNNING:
raise RuntimeError(f"Cannot inject: FlowRunner state is {self.state}")
if not self._pump:
raise RuntimeError("Pump not initialized")
# Get the listener
listener = self._pump.listeners.get(target_node)
if not listener:
raise ValueError(f"Unknown node: {target_node}")
# Create payload instance
payload = listener.payload_class(**payload_data)
# Get or create thread
from xml_pipeline.message_bus.thread_registry import get_registry
registry = get_registry()
if thread_id is None:
thread_id = registry.extend_chain(self._root_thread_id, target_node)
# Wrap in envelope
envelope = self._pump._wrap_in_envelope(
payload=payload,
from_id="external",
to_id=target_node,
thread_id=thread_id,
)
# Inject
await self._pump.inject(envelope, thread_id=thread_id, from_id="external")
self.message_count += 1
self._emit_event(
"message_injected",
node_name=target_node,
thread_id=thread_id,
payload_type=type(payload).__name__,
)
return thread_id
# =========================================================================
# Trigger Handling
# =========================================================================
async def trigger(
self,
trigger_id: UUID | str,
payload_data: dict[str, Any] | None = None,
) -> str:
"""
Fire a trigger to start flow execution.
Args:
trigger_id: The trigger ID (UUID or string).
payload_data: Optional payload data for the trigger.
Returns:
The thread ID for this execution.
"""
if isinstance(trigger_id, str):
trigger_id = UUID(trigger_id)
# Find the trigger
trigger = next((t for t in self.flow.triggers if t.id == trigger_id), None)
if not trigger:
raise ValueError(f"Unknown trigger: {trigger_id}")
if not trigger.enabled:
raise ValueError(f"Trigger {trigger.name} is disabled")
# Get target nodes
if not trigger.target_node_ids:
raise ValueError(f"Trigger {trigger.name} has no target nodes")
# Find target node names
node_map = {n.id: n.name for n in self.flow.nodes}
target_names = [node_map.get(nid) for nid in trigger.target_node_ids]
target_names = [n for n in target_names if n]
if not target_names:
raise ValueError(f"Trigger {trigger.name} targets unknown nodes")
# Create thread for this execution
from xml_pipeline.message_bus.thread_registry import get_registry
registry = get_registry()
thread_id = registry.extend_chain(self._root_thread_id, target_names[0])
# Inject to each target
for target_name in target_names:
await self.inject(target_name, payload_data or {}, thread_id=thread_id)
self._emit_event(
"trigger_fired",
message=f"Trigger {trigger.name} fired to {target_names}",
thread_id=thread_id,
)
return thread_id
def get_webhook_handler(self, trigger_id: UUID) -> Callable | None:
"""
Get a webhook handler for a trigger.
Used by the API layer to create webhook endpoints.
"""
trigger = next((t for t in self.flow.triggers if t.id == trigger_id), None)
if not trigger or trigger.trigger_type != TriggerType.WEBHOOK:
return None
async def webhook_handler(payload: dict[str, Any]) -> str:
return await self.trigger(trigger_id, payload)
return webhook_handler
# =========================================================================
# Status & Events
# =========================================================================
def get_status(self) -> dict[str, Any]:
"""Get current runner status."""
return {
"executionId": str(self.execution_id),
"flowId": str(self.flow.id),
"flowName": self.flow.name,
"state": self.state.value,
"startedAt": self.started_at.isoformat() if self.started_at else None,
"stoppedAt": self.stopped_at.isoformat() if self.stopped_at else None,
"messageCount": self.message_count,
"errorMessage": self.error_message,
"nodeCount": len(self.flow.nodes),
"triggerCount": len(self.flow.triggers),
}
def get_events(self, limit: int = 100) -> list[dict[str, Any]]:
"""Get recent execution events."""
return [e.to_dict() for e in self.events[-limit:]]
def _emit_event(
self,
event_type: str,
node_name: str | None = None,
thread_id: str | None = None,
payload_type: str | None = None,
message: str = "",
error: str | None = None,
) -> None:
"""Emit an execution event."""
event = ExecutionEvent(
timestamp=datetime.now(timezone.utc),
event_type=event_type,
node_name=node_name,
thread_id=thread_id,
payload_type=payload_type,
message=message,
error=error,
)
self.events.append(event)
# Call external callback if provided
if self.event_callback:
try:
self.event_callback(event)
except Exception as e:
logger.warning(f"Event callback error: {e}")
# Log
if error:
logger.error(f"[{self.flow.name}] {event_type}: {error}")
else:
logger.info(f"[{self.flow.name}] {event_type}: {message or node_name or ''}")

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@ -1,475 +0,0 @@
"""
BloxServer API Contract - Pydantic Models
These models define the API contract between frontend and backend.
They match the TypeScript types in types.ts.
Usage:
from bloxserver.api.models import Flow, CreateFlowRequest
"""
from __future__ import annotations
from datetime import datetime
from enum import Enum
from typing import Any, Generic, Literal, TypeVar
from uuid import UUID
from pydantic import BaseModel, Field
# =============================================================================
# Common Types
# =============================================================================
T = TypeVar("T")
class PaginatedResponse(BaseModel, Generic[T]):
"""Paginated list response."""
items: list[T]
total: int
page: int
page_size: int = Field(alias="pageSize")
has_more: bool = Field(alias="hasMore")
class Config:
populate_by_name = True
class ApiError(BaseModel):
"""API error response."""
code: str
message: str
details: dict[str, Any] | None = None
# =============================================================================
# User (synced from Clerk)
# =============================================================================
class Tier(str, Enum):
FREE = "free"
PAID = "paid"
PRO = "pro"
ENTERPRISE = "enterprise"
class User(BaseModel):
"""User account (synced from Clerk)."""
id: UUID
clerk_id: str = Field(alias="clerkId")
email: str
name: str | None = None
avatar_url: str | None = Field(default=None, alias="avatarUrl")
tier: Tier = Tier.FREE
created_at: datetime = Field(alias="createdAt")
class Config:
populate_by_name = True
# =============================================================================
# Flows
# =============================================================================
class FlowStatus(str, Enum):
STOPPED = "stopped"
STARTING = "starting"
RUNNING = "running"
STOPPING = "stopping"
ERROR = "error"
class CanvasNode(BaseModel):
"""A node in the React Flow canvas."""
id: str
type: str
position: dict[str, float]
data: dict[str, Any]
class CanvasEdge(BaseModel):
"""An edge connecting nodes in the canvas."""
id: str
source: str
target: str
source_handle: str | None = Field(default=None, alias="sourceHandle")
target_handle: str | None = Field(default=None, alias="targetHandle")
class Config:
populate_by_name = True
class CanvasState(BaseModel):
"""React Flow canvas state."""
nodes: list[CanvasNode]
edges: list[CanvasEdge]
viewport: dict[str, float]
class Flow(BaseModel):
"""A user's workflow/flow."""
id: UUID
user_id: UUID = Field(alias="userId")
name: str
description: str | None = None
organism_yaml: str = Field(alias="organismYaml")
canvas_state: CanvasState | None = Field(default=None, alias="canvasState")
status: FlowStatus = FlowStatus.STOPPED
container_id: str | None = Field(default=None, alias="containerId")
error_message: str | None = Field(default=None, alias="errorMessage")
created_at: datetime = Field(alias="createdAt")
updated_at: datetime = Field(alias="updatedAt")
class Config:
populate_by_name = True
class FlowSummary(BaseModel):
"""Abbreviated flow for list views."""
id: UUID
name: str
description: str | None = None
status: FlowStatus
updated_at: datetime = Field(alias="updatedAt")
class Config:
populate_by_name = True
class CreateFlowRequest(BaseModel):
"""Request to create a new flow."""
name: str = Field(min_length=1, max_length=100)
description: str | None = Field(default=None, max_length=500)
organism_yaml: str | None = Field(default=None, alias="organismYaml")
class Config:
populate_by_name = True
class UpdateFlowRequest(BaseModel):
"""Request to update a flow."""
name: str | None = Field(default=None, min_length=1, max_length=100)
description: str | None = Field(default=None, max_length=500)
organism_yaml: str | None = Field(default=None, alias="organismYaml")
canvas_state: CanvasState | None = Field(default=None, alias="canvasState")
class Config:
populate_by_name = True
# =============================================================================
# Triggers
# =============================================================================
class TriggerType(str, Enum):
WEBHOOK = "webhook"
SCHEDULE = "schedule"
MANUAL = "manual"
class WebhookTriggerConfig(BaseModel):
"""Config for webhook triggers."""
type: Literal["webhook"] = "webhook"
class ScheduleTriggerConfig(BaseModel):
"""Config for scheduled triggers."""
type: Literal["schedule"] = "schedule"
cron: str = Field(description="Cron expression")
timezone: str = "UTC"
class ManualTriggerConfig(BaseModel):
"""Config for manual triggers."""
type: Literal["manual"] = "manual"
TriggerConfig = WebhookTriggerConfig | ScheduleTriggerConfig | ManualTriggerConfig
class Trigger(BaseModel):
"""A trigger that can start a flow."""
id: UUID
flow_id: UUID = Field(alias="flowId")
type: TriggerType
name: str
config: TriggerConfig
webhook_token: str | None = Field(default=None, alias="webhookToken")
webhook_url: str | None = Field(default=None, alias="webhookUrl")
created_at: datetime = Field(alias="createdAt")
class Config:
populate_by_name = True
class CreateTriggerRequest(BaseModel):
"""Request to create a trigger."""
type: TriggerType
name: str = Field(min_length=1, max_length=100)
config: TriggerConfig
# =============================================================================
# Executions
# =============================================================================
class ExecutionStatus(str, Enum):
RUNNING = "running"
SUCCESS = "success"
ERROR = "error"
TIMEOUT = "timeout"
class Execution(BaseModel):
"""A single execution/run of a flow."""
id: UUID
flow_id: UUID = Field(alias="flowId")
trigger_id: UUID | None = Field(default=None, alias="triggerId")
trigger_type: TriggerType = Field(alias="triggerType")
status: ExecutionStatus
started_at: datetime = Field(alias="startedAt")
completed_at: datetime | None = Field(default=None, alias="completedAt")
duration_ms: int | None = Field(default=None, alias="durationMs")
error_message: str | None = Field(default=None, alias="errorMessage")
input_payload: str | None = Field(default=None, alias="inputPayload")
output_payload: str | None = Field(default=None, alias="outputPayload")
class Config:
populate_by_name = True
class ExecutionSummary(BaseModel):
"""Abbreviated execution for list views."""
id: UUID
status: ExecutionStatus
trigger_type: TriggerType = Field(alias="triggerType")
started_at: datetime = Field(alias="startedAt")
duration_ms: int | None = Field(default=None, alias="durationMs")
class Config:
populate_by_name = True
# =============================================================================
# WASM Modules (Pro+)
# =============================================================================
class WasmModule(BaseModel):
"""A custom WASM module."""
id: UUID
user_id: UUID = Field(alias="userId")
name: str
description: str | None = None
wit_interface: str | None = Field(default=None, alias="witInterface")
size_bytes: int = Field(alias="sizeBytes")
created_at: datetime = Field(alias="createdAt")
updated_at: datetime = Field(alias="updatedAt")
class Config:
populate_by_name = True
class WasmModuleSummary(BaseModel):
"""Abbreviated module for list views."""
id: UUID
name: str
description: str | None = None
created_at: datetime = Field(alias="createdAt")
class Config:
populate_by_name = True
class CreateWasmModuleRequest(BaseModel):
"""Request to create a WASM module (file uploaded separately)."""
name: str = Field(min_length=1, max_length=100)
description: str | None = Field(default=None, max_length=500)
wit_interface: str | None = Field(default=None, alias="witInterface")
class Config:
populate_by_name = True
# =============================================================================
# Marketplace
# =============================================================================
class MarketplaceListingType(str, Enum):
TOOL = "tool"
FLOW = "flow"
class ToolContent(BaseModel):
"""Content for a tool listing."""
type: Literal["tool"] = "tool"
wasm_module_id: UUID = Field(alias="wasmModuleId")
wit_interface: str = Field(alias="witInterface")
example_usage: str = Field(alias="exampleUsage")
class Config:
populate_by_name = True
class FlowTemplateContent(BaseModel):
"""Content for a flow template listing."""
type: Literal["flow"] = "flow"
organism_yaml: str = Field(alias="organismYaml")
canvas_state: CanvasState = Field(alias="canvasState")
class Config:
populate_by_name = True
MarketplaceContent = ToolContent | FlowTemplateContent
class MarketplaceListing(BaseModel):
"""A marketplace listing (tool or flow template)."""
id: UUID
author_id: UUID = Field(alias="authorId")
author_name: str = Field(alias="authorName")
type: MarketplaceListingType
name: str
description: str
category: str
tags: list[str]
downloads: int = 0
rating: float | None = None
content: MarketplaceContent
created_at: datetime = Field(alias="createdAt")
updated_at: datetime = Field(alias="updatedAt")
class Config:
populate_by_name = True
class MarketplaceListingSummary(BaseModel):
"""Abbreviated listing for browse views."""
id: UUID
author_name: str = Field(alias="authorName")
type: MarketplaceListingType
name: str
description: str
category: str
downloads: int
rating: float | None = None
class Config:
populate_by_name = True
class PublishToMarketplaceRequest(BaseModel):
"""Request to publish to marketplace."""
type: MarketplaceListingType
name: str = Field(min_length=1, max_length=100)
description: str = Field(min_length=10, max_length=2000)
category: str
tags: list[str] = Field(default_factory=list, max_length=10)
content: MarketplaceContent
# =============================================================================
# Project Memory (Pro+)
# =============================================================================
class ProjectMemory(BaseModel):
"""Project memory status for a flow."""
flow_id: UUID = Field(alias="flowId")
enabled: bool = False
used_bytes: int = Field(default=0, alias="usedBytes")
max_bytes: int = Field(alias="maxBytes")
keys: list[str] = Field(default_factory=list)
class Config:
populate_by_name = True
class MemoryEntry(BaseModel):
"""A single memory entry."""
key: str
value: str # JSON string
size_bytes: int = Field(alias="sizeBytes")
updated_at: datetime = Field(alias="updatedAt")
class Config:
populate_by_name = True
# =============================================================================
# Logs
# =============================================================================
class LogLevel(str, Enum):
DEBUG = "debug"
INFO = "info"
WARNING = "warning"
ERROR = "error"
class LogEntry(BaseModel):
"""A log entry from a running flow."""
timestamp: datetime
level: LogLevel
message: str
metadata: dict[str, Any] | None = None
# =============================================================================
# Stats
# =============================================================================
class FlowStats(BaseModel):
"""Statistics for a single flow."""
flow_id: UUID = Field(alias="flowId")
executions_total: int = Field(alias="executionsTotal")
executions_success: int = Field(alias="executionsSuccess")
executions_error: int = Field(alias="executionsError")
avg_duration_ms: float = Field(alias="avgDurationMs")
last_executed_at: datetime | None = Field(default=None, alias="lastExecutedAt")
class Config:
populate_by_name = True
class UsageStats(BaseModel):
"""Usage statistics for billing/limits."""
user_id: UUID = Field(alias="userId")
period: Literal["day", "month"]
flow_count: int = Field(alias="flowCount")
execution_count: int = Field(alias="executionCount")
execution_limit: int = Field(alias="executionLimit")
class Config:
populate_by_name = True

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@ -1,340 +0,0 @@
/**
* BloxServer API Contract - TypeScript Types
*
* These types define the API contract between frontend and backend.
* The FastAPI backend uses matching Pydantic models.
*
* Usage in frontend:
* import type { Flow, CreateFlowRequest } from '@/types/api';
*/
// =============================================================================
// Common Types
// =============================================================================
export type UUID = string;
export type ISODateTime = string;
// =============================================================================
// User (synced from Clerk)
// =============================================================================
export interface User {
id: UUID;
clerkId: string;
email: string;
name: string | null;
avatarUrl: string | null;
tier: 'free' | 'paid' | 'pro' | 'enterprise';
createdAt: ISODateTime;
}
// =============================================================================
// Flows
// =============================================================================
export type FlowStatus = 'stopped' | 'starting' | 'running' | 'stopping' | 'error';
export interface Flow {
id: UUID;
userId: UUID;
name: string;
description: string | null;
organismYaml: string;
canvasState: CanvasState | null;
status: FlowStatus;
containerId: string | null;
errorMessage: string | null;
createdAt: ISODateTime;
updatedAt: ISODateTime;
}
export interface FlowSummary {
id: UUID;
name: string;
description: string | null;
status: FlowStatus;
updatedAt: ISODateTime;
}
export interface CreateFlowRequest {
name: string;
description?: string;
organismYaml?: string; // Default template if not provided
}
export interface UpdateFlowRequest {
name?: string;
description?: string;
organismYaml?: string;
canvasState?: CanvasState;
}
// =============================================================================
// Canvas State (React Flow)
// =============================================================================
export interface CanvasState {
nodes: CanvasNode[];
edges: CanvasEdge[];
viewport: { x: number; y: number; zoom: number };
}
export interface CanvasNode {
id: string;
type: NodeType;
position: { x: number; y: number };
data: NodeData;
}
export type NodeType =
| 'trigger'
| 'llmCall'
| 'httpRequest'
| 'codeBlock'
| 'conditional'
| 'output'
| 'custom';
export interface NodeData {
name: string;
label: string;
description?: string;
handler?: string;
payloadClass?: string;
isAgent?: boolean;
config?: Record<string, unknown>;
}
export interface CanvasEdge {
id: string;
source: string;
target: string;
sourceHandle?: string;
targetHandle?: string;
}
// =============================================================================
// Triggers
// =============================================================================
export type TriggerType = 'webhook' | 'schedule' | 'manual';
export interface Trigger {
id: UUID;
flowId: UUID;
type: TriggerType;
name: string;
config: TriggerConfig;
webhookToken?: string; // Only for webhook triggers
webhookUrl?: string; // Full URL for webhook triggers
createdAt: ISODateTime;
}
export type TriggerConfig =
| WebhookTriggerConfig
| ScheduleTriggerConfig
| ManualTriggerConfig;
export interface WebhookTriggerConfig {
type: 'webhook';
}
export interface ScheduleTriggerConfig {
type: 'schedule';
cron: string; // Cron expression
timezone?: string; // Default: UTC
}
export interface ManualTriggerConfig {
type: 'manual';
}
export interface CreateTriggerRequest {
type: TriggerType;
name: string;
config: TriggerConfig;
}
// =============================================================================
// Executions (Run History)
// =============================================================================
export type ExecutionStatus = 'running' | 'success' | 'error' | 'timeout';
export interface Execution {
id: UUID;
flowId: UUID;
triggerId: UUID | null;
triggerType: TriggerType;
status: ExecutionStatus;
startedAt: ISODateTime;
completedAt: ISODateTime | null;
durationMs: number | null;
errorMessage: string | null;
inputPayload: string | null; // JSON string
outputPayload: string | null; // JSON string
}
export interface ExecutionSummary {
id: UUID;
status: ExecutionStatus;
triggerType: TriggerType;
startedAt: ISODateTime;
durationMs: number | null;
}
// =============================================================================
// WASM Modules (Pro+)
// =============================================================================
export interface WasmModule {
id: UUID;
userId: UUID;
name: string;
description: string | null;
witInterface: string | null;
sizeBytes: number;
createdAt: ISODateTime;
updatedAt: ISODateTime;
}
export interface WasmModuleSummary {
id: UUID;
name: string;
description: string | null;
createdAt: ISODateTime;
}
export interface CreateWasmModuleRequest {
name: string;
description?: string;
witInterface?: string;
// Actual .wasm file uploaded separately via multipart
}
// =============================================================================
// Marketplace
// =============================================================================
export type MarketplaceListingType = 'tool' | 'flow';
export interface MarketplaceListing {
id: UUID;
authorId: UUID;
authorName: string;
type: MarketplaceListingType;
name: string;
description: string;
category: string;
tags: string[];
downloads: number;
rating: number | null;
content: MarketplaceContent;
createdAt: ISODateTime;
updatedAt: ISODateTime;
}
export interface MarketplaceListingSummary {
id: UUID;
authorName: string;
type: MarketplaceListingType;
name: string;
description: string;
category: string;
downloads: number;
rating: number | null;
}
export type MarketplaceContent = ToolContent | FlowTemplateContent;
export interface ToolContent {
type: 'tool';
wasmModuleId: UUID;
witInterface: string;
exampleUsage: string;
}
export interface FlowTemplateContent {
type: 'flow';
organismYaml: string;
canvasState: CanvasState;
}
export interface PublishToMarketplaceRequest {
type: MarketplaceListingType;
name: string;
description: string;
category: string;
tags: string[];
content: MarketplaceContent;
}
// =============================================================================
// Project Memory (Pro+, opt-in)
// =============================================================================
export interface ProjectMemory {
flowId: UUID;
enabled: boolean;
usedBytes: number;
maxBytes: number;
keys: string[];
}
export interface MemoryEntry {
key: string;
value: string; // JSON string
sizeBytes: number;
updatedAt: ISODateTime;
}
// =============================================================================
// API Responses
// =============================================================================
export interface PaginatedResponse<T> {
items: T[];
total: number;
page: number;
pageSize: number;
hasMore: boolean;
}
export interface ApiError {
code: string;
message: string;
details?: Record<string, unknown>;
}
// =============================================================================
// Flow Logs (streaming)
// =============================================================================
export interface LogEntry {
timestamp: ISODateTime;
level: 'debug' | 'info' | 'warning' | 'error';
message: string;
metadata?: Record<string, unknown>;
}
// =============================================================================
// Stats & Analytics
// =============================================================================
export interface FlowStats {
flowId: UUID;
executionsTotal: number;
executionsSuccess: number;
executionsError: number;
avgDurationMs: number;
lastExecutedAt: ISODateTime | null;
}
export interface UsageStats {
userId: UUID;
period: 'day' | 'month';
flowCount: number;
executionCount: number;
executionLimit: number;
}

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@ -1,668 +0,0 @@
# BloxServer Billing Integration — Stripe
**Status:** Design
**Date:** January 2026
## Overview
BloxServer uses Stripe for subscription management, usage-based billing, and payment processing. This document specifies the integration architecture, webhook handlers, and usage tracking system.
## Pricing Tiers
| Tier | Price | Runs/Month | Features |
|------|-------|------------|----------|
| **Free** | $0 | 1,000 | 1 workflow, built-in tools, community support |
| **Pro** | $29 | 100,000 | Unlimited workflows, marketplace, WASM, project memory, priority support |
| **Enterprise** | Custom | Unlimited | SSO/SAML, SLA, dedicated support, private marketplace |
### Overage Pricing (Pro)
| Metric | Included | Overage Rate |
|--------|----------|--------------|
| Workflow runs | 100K/mo | $0.50 per 1K |
| Storage | 10 GB | $0.10 per GB |
| WASM execution | 1000 CPU-sec | $0.01 per CPU-sec |
## Stripe Product Structure
```
Products:
├── bloxserver_free
│ └── price_free_monthly ($0/month, metered runs)
├── bloxserver_pro
│ ├── price_pro_monthly ($29/month base)
│ ├── price_pro_runs_overage (metered, $0.50/1K)
│ └── price_pro_storage_overage (metered, $0.10/GB)
└── bloxserver_enterprise
└── price_enterprise_custom (quoted per customer)
```
### Stripe Configuration
```python
# One-time setup (or via Stripe Dashboard)
# Free tier product
free_product = stripe.Product.create(
name="BloxServer Free",
description="Build AI agent swarms, visually",
)
free_price = stripe.Price.create(
product=free_product.id,
unit_amount=0,
currency="usd",
recurring={"interval": "month"},
metadata={"tier": "free", "runs_included": "1000"}
)
# Pro tier product
pro_product = stripe.Product.create(
name="BloxServer Pro",
description="Unlimited workflows, marketplace access, custom WASM",
)
pro_base_price = stripe.Price.create(
product=pro_product.id,
unit_amount=2900, # $29.00
currency="usd",
recurring={"interval": "month"},
metadata={"tier": "pro", "runs_included": "100000"}
)
pro_runs_overage = stripe.Price.create(
product=pro_product.id,
currency="usd",
recurring={
"interval": "month",
"usage_type": "metered",
"aggregate_usage": "sum",
},
unit_amount_decimal="0.05", # $0.0005 per run = $0.50 per 1K
metadata={"type": "runs_overage"}
)
```
## Database Schema
```sql
-- Users table (synced from Clerk + Stripe)
CREATE TABLE users (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
clerk_id VARCHAR(255) UNIQUE NOT NULL,
email VARCHAR(255) NOT NULL,
name VARCHAR(255),
-- Stripe fields
stripe_customer_id VARCHAR(255) UNIQUE,
stripe_subscription_id VARCHAR(255),
stripe_subscription_item_id VARCHAR(255), -- For usage reporting
-- Billing state (cached from Stripe)
tier VARCHAR(50) DEFAULT 'free', -- free, pro, enterprise
billing_status VARCHAR(50) DEFAULT 'active', -- active, past_due, canceled
trial_ends_at TIMESTAMPTZ,
current_period_start TIMESTAMPTZ,
current_period_end TIMESTAMPTZ,
created_at TIMESTAMPTZ DEFAULT NOW(),
updated_at TIMESTAMPTZ DEFAULT NOW()
);
-- Usage tracking (local, for dashboard + Stripe sync)
CREATE TABLE usage_records (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
user_id UUID REFERENCES users(id),
period_start DATE NOT NULL, -- Billing period start
-- Metrics
workflow_runs INT DEFAULT 0,
llm_tokens_in INT DEFAULT 0,
llm_tokens_out INT DEFAULT 0,
wasm_cpu_seconds DECIMAL(10,2) DEFAULT 0,
storage_gb_hours DECIMAL(10,2) DEFAULT 0,
-- Stripe sync state
last_synced_at TIMESTAMPTZ,
last_synced_runs INT DEFAULT 0,
created_at TIMESTAMPTZ DEFAULT NOW(),
updated_at TIMESTAMPTZ DEFAULT NOW(),
UNIQUE(user_id, period_start)
);
-- Stripe webhook events (idempotency)
CREATE TABLE stripe_events (
event_id VARCHAR(255) PRIMARY KEY,
event_type VARCHAR(100) NOT NULL,
processed_at TIMESTAMPTZ DEFAULT NOW(),
payload JSONB
);
-- Index for cleanup
CREATE INDEX idx_stripe_events_processed ON stripe_events(processed_at);
```
## Usage Tracking
### Real-Time Counting (Redis)
```python
# On every workflow execution
async def record_workflow_run(user_id: str):
"""Increment run counter in Redis."""
key = f"usage:{user_id}:runs:{get_current_period()}"
await redis.incr(key)
await redis.expire(key, 86400 * 35) # 35 days TTL
# Track users with usage for batch sync
await redis.sadd("users:with_usage", user_id)
async def record_llm_tokens(user_id: str, tokens_in: int, tokens_out: int):
"""Track LLM token usage."""
period = get_current_period()
await redis.incrby(f"usage:{user_id}:tokens_in:{period}", tokens_in)
await redis.incrby(f"usage:{user_id}:tokens_out:{period}", tokens_out)
```
### Periodic Sync to Stripe (Hourly)
```python
async def sync_usage_to_stripe():
"""Hourly job: push usage increments to Stripe."""
user_ids = await redis.smembers("users:with_usage")
for user_id in user_ids:
user = await get_user(user_id)
if not user.stripe_subscription_item_id:
continue # Free tier without Stripe subscription
# Get usage since last sync
period = get_current_period()
runs_key = f"usage:{user_id}:runs:{period}"
current_runs = int(await redis.get(runs_key) or 0)
last_synced = await get_last_synced_runs(user_id, period)
delta = current_runs - last_synced
if delta <= 0:
continue
# Check if over included limit
tier_limit = get_tier_runs_limit(user.tier) # 1000 or 100000
if current_runs <= tier_limit:
# Still within included runs, just track locally
await update_last_synced(user_id, period, current_runs)
continue
# Calculate overage to report
overage_start = max(last_synced, tier_limit)
overage_runs = current_runs - overage_start
if overage_runs > 0:
# Report to Stripe
await stripe.subscription_items.create_usage_record(
user.stripe_subscription_item_id,
quantity=overage_runs,
timestamp=int(time.time()),
action='increment'
)
await update_last_synced(user_id, period, current_runs)
# Clear the tracking set (will rebuild next hour)
await redis.delete("users:with_usage")
```
### Dashboard Query
```python
async def get_usage_dashboard(user_id: str) -> UsageDashboard:
"""Get current usage for user dashboard."""
user = await get_user(user_id)
period = get_current_period()
# Get real-time counts from Redis
runs = int(await redis.get(f"usage:{user_id}:runs:{period}") or 0)
tokens_in = int(await redis.get(f"usage:{user_id}:tokens_in:{period}") or 0)
tokens_out = int(await redis.get(f"usage:{user_id}:tokens_out:{period}") or 0)
tier_limit = get_tier_runs_limit(user.tier)
return UsageDashboard(
period_start=period,
period_end=user.current_period_end,
runs_used=runs,
runs_limit=tier_limit,
runs_percentage=min(100, (runs / tier_limit) * 100),
tokens_used=tokens_in + tokens_out,
estimated_overage=calculate_overage_cost(runs, tier_limit),
days_remaining=(user.current_period_end - datetime.now()).days,
)
```
## Subscription Lifecycle
### Signup Flow
```
User clicks "Start Free Trial"
┌───────────────────────────────────────────────────────────┐
│ 1. Create Stripe Customer │
│ │
│ customer = stripe.Customer.create( │
│ email=user.email, │
│ metadata={"clerk_id": user.clerk_id} │
│ ) │
└───────────────────────────────────────────────────────────┘
┌───────────────────────────────────────────────────────────┐
│ 2. Create Checkout Session (hosted payment page) │
│ │
│ session = stripe.checkout.Session.create( │
│ customer=customer.id, │
│ mode='subscription', │
│ line_items=[{ │
│ 'price': 'price_pro_monthly', │
│ 'quantity': 1 │
│ }, { │
│ 'price': 'price_pro_runs_overage', # metered │
│ }], │
│ subscription_data={ │
│ 'trial_period_days': 14, │
│ }, │
│ success_url='https://app.openblox.ai/welcome', │
│ cancel_url='https://app.openblox.ai/pricing', │
│ ) │
│ │
│ → Redirect user to session.url │
└───────────────────────────────────────────────────────────┘
┌───────────────────────────────────────────────────────────┐
│ 3. User enters payment details on Stripe Checkout │
│ │
│ Card validated but NOT charged (trial) │
└───────────────────────────────────────────────────────────┘
┌───────────────────────────────────────────────────────────┐
│ 4. Webhook: checkout.session.completed │
│ │
│ → Update user with stripe_customer_id │
│ → Update user with stripe_subscription_id │
│ → Set tier = 'pro' │
│ → Set trial_ends_at │
└───────────────────────────────────────────────────────────┘
```
### Trial End
```
Day 11 of 14-day trial
┌───────────────────────────────────────────────────────────┐
│ Scheduled job: Trial ending soon emails │
│ │
│ SELECT * FROM users │
│ WHERE trial_ends_at BETWEEN NOW() AND NOW() + INTERVAL '3d'│
│ AND billing_status = 'trialing' │
│ │
│ → Send "Your trial ends in 3 days" email │
└───────────────────────────────────────────────────────────┘
Day 14: Trial ends
┌───────────────────────────────────────────────────────────┐
│ Stripe automatically: │
│ 1. Charges the card on file │
│ 2. Sends invoice.payment_succeeded webhook │
│ │
│ Our webhook handler: │
│ → Update billing_status = 'active' │
│ → Send "Welcome to Pro!" email │
└───────────────────────────────────────────────────────────┘
```
### Cancellation
```python
# User clicks "Cancel subscription" in Customer Portal
# Stripe sends webhook
@webhook("customer.subscription.updated")
async def handle_subscription_updated(event):
subscription = event.data.object
user = await get_user_by_stripe_subscription(subscription.id)
if subscription.cancel_at_period_end:
# User requested cancellation (takes effect at period end)
await send_email(user, "subscription_canceled", {
"effective_date": subscription.current_period_end
})
await db.execute("""
UPDATE users
SET billing_status = 'canceling',
updated_at = NOW()
WHERE id = $1
""", user.id)
@webhook("customer.subscription.deleted")
async def handle_subscription_deleted(event):
subscription = event.data.object
user = await get_user_by_stripe_subscription(subscription.id)
# Subscription actually ended
await db.execute("""
UPDATE users
SET tier = 'free',
billing_status = 'canceled',
stripe_subscription_id = NULL,
stripe_subscription_item_id = NULL,
updated_at = NOW()
WHERE id = $1
""", user.id)
await send_email(user, "downgraded_to_free")
```
## Webhook Handlers
### Endpoint Setup
```python
from fastapi import FastAPI, Request, HTTPException
import stripe
app = FastAPI()
@app.post("/webhooks/stripe")
async def stripe_webhook(request: Request):
payload = await request.body()
sig_header = request.headers.get("stripe-signature")
try:
event = stripe.Webhook.construct_event(
payload, sig_header, settings.STRIPE_WEBHOOK_SECRET
)
except ValueError:
raise HTTPException(400, "Invalid payload")
except stripe.error.SignatureVerificationError:
raise HTTPException(400, "Invalid signature")
# Idempotency check
if await is_event_processed(event.id):
return {"status": "already_processed"}
# Route to handler
handler = WEBHOOK_HANDLERS.get(event.type)
if handler:
await handler(event)
else:
logger.info(f"Unhandled webhook: {event.type}")
# Mark processed
await mark_event_processed(event)
return {"status": "success"}
```
### Handler Registry
```python
WEBHOOK_HANDLERS = {
# Checkout
"checkout.session.completed": handle_checkout_completed,
# Subscriptions
"customer.subscription.created": handle_subscription_created,
"customer.subscription.updated": handle_subscription_updated,
"customer.subscription.deleted": handle_subscription_deleted,
"customer.subscription.trial_will_end": handle_trial_ending,
# Payments
"invoice.payment_succeeded": handle_payment_succeeded,
"invoice.payment_failed": handle_payment_failed,
"invoice.upcoming": handle_invoice_upcoming,
# Customer
"customer.updated": handle_customer_updated,
}
```
### Key Handlers
```python
@webhook("checkout.session.completed")
async def handle_checkout_completed(event):
"""User completed checkout - provision their account."""
session = event.data.object
# Get or create user
user = await get_user_by_clerk_id(session.client_reference_id)
# Update with Stripe IDs
subscription = await stripe.Subscription.retrieve(session.subscription)
await db.execute("""
UPDATE users SET
stripe_customer_id = $1,
stripe_subscription_id = $2,
stripe_subscription_item_id = $3,
tier = $4,
billing_status = $5,
trial_ends_at = $6,
current_period_start = $7,
current_period_end = $8,
updated_at = NOW()
WHERE id = $9
""",
session.customer,
subscription.id,
subscription['items'].data[0].id, # First item for usage reporting
'pro',
subscription.status, # 'trialing' or 'active'
datetime.fromtimestamp(subscription.trial_end) if subscription.trial_end else None,
datetime.fromtimestamp(subscription.current_period_start),
datetime.fromtimestamp(subscription.current_period_end),
user.id
)
@webhook("invoice.payment_failed")
async def handle_payment_failed(event):
"""Payment failed - notify user, potentially downgrade."""
invoice = event.data.object
user = await get_user_by_stripe_customer(invoice.customer)
attempt_count = invoice.attempt_count
if attempt_count == 1:
# First failure - soft warning
await send_email(user, "payment_failed_soft", {
"amount": invoice.amount_due / 100,
"update_url": await get_customer_portal_url(user)
})
elif attempt_count == 2:
# Second failure - stronger warning
await send_email(user, "payment_failed_warning", {
"amount": invoice.amount_due / 100,
"days_until_downgrade": 3
})
else:
# Final failure - downgrade
await db.execute("""
UPDATE users SET
tier = 'free',
billing_status = 'past_due',
updated_at = NOW()
WHERE id = $1
""", user.id)
await send_email(user, "downgraded_payment_failed")
@webhook("customer.subscription.trial_will_end")
async def handle_trial_ending(event):
"""Trial ending in 3 days - Stripe sends this automatically."""
subscription = event.data.object
user = await get_user_by_stripe_subscription(subscription.id)
await send_email(user, "trial_ending", {
"trial_end_date": datetime.fromtimestamp(subscription.trial_end),
"amount": 29.00, # Pro price
"manage_url": await get_customer_portal_url(user)
})
```
## Customer Portal
Stripe's hosted portal for self-service billing management.
```python
async def get_customer_portal_url(user: User) -> str:
"""Generate a portal session URL for the user."""
session = await stripe.billing_portal.Session.create(
customer=user.stripe_customer_id,
return_url="https://app.openblox.ai/settings/billing"
)
return session.url
```
**Portal capabilities:**
- Update payment method
- View invoices and receipts
- Cancel subscription
- Upgrade/downgrade plan (if configured)
## Email Templates
| Trigger | Template | Content |
|---------|----------|---------|
| Trial started | `trial_started` | Welcome, trial ends on X |
| Trial ending (3 days) | `trial_ending` | Your trial ends soon, card will be charged |
| Trial converted | `trial_converted` | Welcome to Pro! |
| Payment succeeded | `payment_succeeded` | Receipt attached |
| Payment failed (1st) | `payment_failed_soft` | Please update your card |
| Payment failed (2nd) | `payment_failed_warning` | Service will be interrupted |
| Payment failed (final) | `downgraded_payment_failed` | You've been downgraded |
| Subscription canceled | `subscription_canceled` | Access until period end |
| Downgraded | `downgraded_to_free` | You're now on Free |
## Rate Limiting & Abuse Prevention
### Soft Limits (Warning)
```python
async def check_usage_limits(user_id: str) -> UsageLimitResult:
"""Check if user is approaching limits."""
usage = await get_current_usage(user_id)
user = await get_user(user_id)
tier_limit = get_tier_runs_limit(user.tier)
percentage = (usage.runs / tier_limit) * 100
if percentage >= 100:
return UsageLimitResult(
allowed=True, # Still allow, but warn
warning="You've exceeded your included runs. Overage charges apply.",
overage_rate="$0.50 per 1,000 runs"
)
elif percentage >= 80:
return UsageLimitResult(
allowed=True,
warning=f"You've used {percentage:.0f}% of your monthly runs."
)
return UsageLimitResult(allowed=True)
```
### Hard Limits (Free Tier)
```python
async def enforce_free_tier_limits(user_id: str) -> bool:
"""Free tier has hard limits - no overage allowed."""
user = await get_user(user_id)
if user.tier != "free":
return True # Paid tiers have soft limits
usage = await get_current_usage(user_id)
if usage.runs >= 1000:
raise UsageLimitExceeded(
"You've reached the Free tier limit of 1,000 runs/month. "
"Upgrade to Pro for unlimited workflows."
)
return True
```
## Testing
### Test Mode
Stripe provides test mode with test API keys and test card numbers.
```python
# .env
STRIPE_SECRET_KEY=sk_test_... # Test mode
STRIPE_WEBHOOK_SECRET=whsec_...
# Test cards
# 4242424242424242 - Succeeds
# 4000000000000002 - Declined
# 4000002500003155 - Requires 3D Secure
```
### Webhook Testing
```bash
# Use Stripe CLI to forward webhooks locally
stripe listen --forward-to localhost:8000/webhooks/stripe
# Trigger test events
stripe trigger invoice.payment_succeeded
stripe trigger customer.subscription.trial_will_end
```
## Monitoring & Alerts
| Metric | Alert Threshold |
|--------|-----------------|
| Webhook processing time | > 5 seconds |
| Webhook failure rate | > 1% |
| Payment failure rate | > 5% |
| Usage sync lag | > 2 hours |
| Stripe API errors | Any 5xx |
## Security Checklist
- [ ] Webhook signature verification
- [ ] Idempotent event processing
- [ ] API keys in environment variables (never in code)
- [ ] Customer portal for sensitive operations (not custom UI)
- [ ] PCI compliance via Stripe Checkout (no card data touches our servers)
- [ ] Audit log for billing events
---
## References
- [Stripe Billing](https://stripe.com/docs/billing)
- [Stripe Webhooks](https://stripe.com/docs/webhooks)
- [Stripe Checkout](https://stripe.com/docs/payments/checkout)
- [Stripe Customer Portal](https://stripe.com/docs/billing/subscriptions/customer-portal)
- [Metered Billing](https://stripe.com/docs/billing/subscriptions/metered-billing)

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@ -1,159 +0,0 @@
# BloxServer Landing Page — v0 Prompt
Paste this prompt into Vercel v0 to generate the landing page.
---
Create a complete SaaS landing page for "BloxServer" - a visual AI agent workflow builder.
## Brand
- Name: BloxServer
- Tagline: "Build AI agent swarms, visually"
- Style: Dark mode (#0a0a0f background), purple/violet primary (#8b5cf6),
subtle gradients, modern SaaS aesthetic like Linear or Vercel
- Font: Inter or Geist Sans
## Hero Section
- Large headline: "Build AI Agent Swarms, Visually"
- Subheadline: "Drag-and-drop workflow builder for AI agents. Connect LLMs,
tools, and custom logic. No code required — but code when you need it."
- Two CTAs: "Start Building Free" (primary, purple) and "Watch Demo" (ghost/outline)
- Hero visual: Abstract representation of connected nodes/flow diagram with
glowing edges, or a stylized screenshot of a flow canvas
- Floating badges: "No credit card required" and "Free tier available"
## Social Proof Bar
- Logos section: "Trusted by teams at" with placeholder company logos (greyed out)
- Or: "Join 1,000+ builders" with avatar stack
## Features Section (6 cards in 2x3 grid)
1. **Visual Flow Builder**
Icon: boxes with connecting lines
"Drag, drop, and connect. Your AI workflow becomes a visual diagram
that anyone can understand."
2. **Multi-LLM Support**
Icon: brain or sparkles
"Connect to Claude, GPT-4, Grok, Llama, or your own models.
Automatic failover keeps your flows running."
3. **Secure Custom Code**
Icon: code brackets with shield
"Write custom logic in sandboxed WebAssembly. Full power, zero risk.
Your code can't escape the sandbox."
4. **Instant Triggers**
Icon: lightning bolt
"Webhooks, schedules, or manual runs. Your agents wake up when you
need them, sleep when you don't."
5. **Marketplace**
Icon: grid of boxes / store
"Browse community tools and templates. Publish your own.
Build once, share everywhere."
6. **Team Ready**
Icon: users
"Enterprise SSO, role-based access, audit logs.
Built for teams that ship."
## How It Works Section (3 steps, horizontal)
Step 1: "Design Your Flow"
- Illustration: Canvas with a few connected nodes
- "Drag blocks from the palette. Connect them visually.
See your YAML config update in real-time."
Step 2: "Configure & Connect"
- Illustration: Settings panel / API key input
- "Add your LLM keys, configure triggers, set up webhooks.
Everything in one place."
Step 3: "Deploy & Scale"
- Illustration: Rocket or cloud with checkmark
- "One click to deploy. Your agents run 24/7 on our infrastructure.
Scale to zero when idle, scale up on demand."
## Pricing Section
Header: "Simple, transparent pricing"
Subheader: "Start free. Scale when you're ready."
3 pricing cards:
**Free** - $0/month
- 1 workflow
- Built-in tools only
- 1,000 runs/month
- Community support
- CTA: "Get Started"
**Pro** - $29/month
- Unlimited workflows
- Marketplace access
- Custom WASM code
- 100,000 runs/month
- Project memory
- Priority support
- CTA: "Start Free Trial" (primary, highlighted card)
**Enterprise** - Custom
- Everything in Pro
- SSO & SAML
- Role-based access
- Dedicated support
- SLA guarantee
- Private marketplace
- CTA: "Contact Sales"
## Code/YAML Preview Section
Header: "Visual builder. YAML under the hood."
Subheader: "See exactly what you're building. Export anytime."
Split view showing:
- Left: Mini canvas with 3-4 connected nodes
- Right: Corresponding YAML code with syntax highlighting
Caption: "What you see is what you get. Power users can edit YAML directly."
## Testimonials Section (3 cards)
Use placeholder testimonials:
"BloxServer replaced our entire agent orchestration layer. What took us
weeks to build, we now do in hours."
— Sarah Chen, CTO at [Placeholder]
"Finally, a tool that lets non-engineers build AI workflows without
sacrificing power for our dev team."
— Marcus Johnson, Head of AI at [Placeholder]
"The WASM sandboxing sold us. We can let customers run custom code
without worrying about security."
— Elena Rodriguez, Security Lead at [Placeholder]
## FAQ Section (accordion style)
4-5 questions:
- "What's included in the free tier?"
- "Can I use my own LLM API keys?"
- "How does the WASM sandboxing work?"
- "Can I export my workflows?"
- "Is there an API?"
## Final CTA Section
Header: "Ready to build your first AI swarm?"
Subheader: "Start free. No credit card required. Deploy in minutes."
Large CTA button: "Get Started Free"
Secondary link: "Talk to Sales →"
## Footer
- Logo + tagline
- Columns: Product (Features, Pricing, Docs, Changelog), Company (About, Blog, Careers, Contact), Legal (Privacy, Terms, Security)
- Social icons: Twitter/X, GitHub, Discord
- Copyright: "© 2026 BloxServer. All rights reserved."
- Domain: OpenBlox.ai
## Additional Details
- Add subtle grid/dot pattern background in hero
- Use glassmorphism for cards (subtle blur, border)
- Animate elements on scroll (fade up)
- Mobile responsive
- Include dark mode toggle in nav (but default to dark)
- Nav: Logo | Features | Pricing | Docs | Login | "Get Started" button

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@ -1,961 +0,0 @@
# BloxServer LLM Abstraction Layer — Resilient Multi-Provider Architecture
**Status:** Design
**Date:** January 2026
## Overview
The LLM abstraction layer is the critical path for all AI operations in BloxServer. It must handle:
- **Viral growth**: 100 → 10,000 users overnight
- **Provider outages**: Single provider down ≠ platform down
- **Fair access**: Paid users prioritized, free users served fairly
- **Cost control**: Platform keys vs BYOK (Bring Your Own Key)
- **Low latency**: Sub-second for simple calls, reasonable for complex
This document specifies the defense-in-depth architecture that survives success.
## Architecture
```
┌─────────────────────────────────────────────────────────────────┐
│ LLM Abstraction Layer │
│ │
│ Request → [Rate Limit] → [Cache Check] → [Queue] → [Dispatch] │
│ │ │ │ │ │
│ ▼ ▼ ▼ ▼ │
│ Per-user Semantic Priority Provider │
│ per-tier cache queues pool + │
│ limits (30%+ hits) (by tier) failover │
│ │
│ ┌─────────────────────────────────────────────────────────────┐│
│ │ BYOK (Bring Your Own Key) ││
│ │ Pro+ users with own API keys bypass platform limits ││
│ └─────────────────────────────────────────────────────────────┘│
│ │
│ ┌─────────────────────────────────────────────────────────────┐│
│ │ High Frequency Tier ││
│ │ Dedicated capacity, custom SLA — contact sales ││
│ └─────────────────────────────────────────────────────────────┘│
└─────────────────────────────────────────────────────────────────┘
```
## Tier Limits
| Tier | Price | Requests/min | Tokens/min | Concurrent | Latency SLA |
|------|-------|--------------|------------|------------|-------------|
| **Free** | $0 | 10 | 10,000 | 2 | Best effort |
| **Pro** | $29/mo | 60 | 100,000 | 10 | < 30s P95 |
| **Enterprise** | Custom | 300 | 500,000 | 50 | < 10s P95 |
| **High Frequency** | Custom | Custom | Custom | Dedicated | Custom SLA |
| **BYOK** (any tier) | — | Unlimited* | Unlimited* | 20 | User's provider |
*BYOK users are limited only by their own provider's rate limits.
### High Frequency Tier
For users requiring:
- **Low latency**: Sub-second response times
- **High throughput**: Thousands of requests per minute
- **Guaranteed capacity**: Dedicated provider allocations
- **Custom models**: Fine-tuned or private deployments
**Use cases:**
- Real-time trading signals
- Live customer support at scale
- High-volume content generation
- Latency-sensitive applications
**Pricing:** Custom — based on capacity reservation, SLA requirements, and volume.
**Landing page CTA:**
```
┌─────────────────────────────────────────────────────────────┐
│ │
│ Need High Frequency? │
│ │
│ Building something that needs thousands of requests per │
│ minute with sub-second latency? Let's talk dedicated │
│ capacity and custom SLAs. │
│ │
│ [Contact Sales →] │
│ │
└─────────────────────────────────────────────────────────────┘
```
## Layer 1: Intake Rate Limiting
First line of defense. Rejects requests before they consume resources.
### Implementation
```python
from dataclasses import dataclass
from enum import Enum
import time
class Tier(Enum):
FREE = "free"
PRO = "pro"
ENTERPRISE = "enterprise"
HIGH_FREQUENCY = "high_frequency"
@dataclass
class TierLimits:
requests_per_minute: int
tokens_per_minute: int
max_concurrent: int
TIER_LIMITS = {
Tier.FREE: TierLimits(10, 10_000, 2),
Tier.PRO: TierLimits(60, 100_000, 10),
Tier.ENTERPRISE: TierLimits(300, 500_000, 50),
Tier.HIGH_FREQUENCY: TierLimits(10_000, 10_000_000, 500), # Custom per customer
}
@dataclass
class RateLimitResult:
allowed: bool
use_user_key: bool = False
retry_after: int | None = None
reason: str | None = None
concurrent_key: str | None = None
async def rate_limit_check(user: User, request: LLMRequest) -> RateLimitResult:
"""Check if user can make this request."""
# BYOK users bypass platform limits
if user.has_own_api_key(request.provider):
return RateLimitResult(allowed=True, use_user_key=True)
limits = TIER_LIMITS[user.tier]
# Check requests per minute (sliding window)
rpm_key = f"ratelimit:{user.id}:rpm"
now = time.time()
window_start = now - 60
# Remove old entries, add new one, count
pipe = redis.pipeline()
pipe.zremrangebyscore(rpm_key, 0, window_start)
pipe.zadd(rpm_key, {str(now): now})
pipe.zcard(rpm_key)
pipe.expire(rpm_key, 120)
_, _, current_rpm, _ = await pipe.execute()
if current_rpm > limits.requests_per_minute:
return RateLimitResult(
allowed=False,
retry_after=int(60 - (now - window_start)),
reason=f"Rate limit: {limits.requests_per_minute} requests/minute"
)
# Check concurrent requests
concurrent_key = f"ratelimit:{user.id}:concurrent"
current_concurrent = await redis.incr(concurrent_key)
await redis.expire(concurrent_key, 300) # 5 min TTL as safety
if current_concurrent > limits.max_concurrent:
await redis.decr(concurrent_key)
return RateLimitResult(
allowed=False,
retry_after=1,
reason=f"Max concurrent: {limits.max_concurrent} requests"
)
return RateLimitResult(allowed=True, concurrent_key=concurrent_key)
async def release_concurrent(concurrent_key: str):
"""Release concurrent slot after request completes."""
if concurrent_key:
await redis.decr(concurrent_key)
```
### Rate Limit Headers
Return standard headers so clients can self-regulate:
```python
def rate_limit_headers(user: User) -> dict:
limits = TIER_LIMITS[user.tier]
current = await get_current_usage(user.id)
return {
"X-RateLimit-Limit": str(limits.requests_per_minute),
"X-RateLimit-Remaining": str(max(0, limits.requests_per_minute - current.rpm)),
"X-RateLimit-Reset": str(int(time.time()) + 60),
}
```
## Layer 2: Semantic Cache
Identical requests return cached responses. Reduces load and cost.
### Cache Key Generation
```python
import hashlib
import json
def hash_request(request: LLMRequest) -> str:
"""Generate deterministic cache key for request."""
# Include all parameters that affect output
cache_input = {
"model": request.model,
"messages": [
{"role": m.role, "content": m.content}
for m in request.messages
],
"temperature": request.temperature,
"max_tokens": request.max_tokens,
"tools": request.tools, # Tool definitions matter
# Exclude: user_id, timestamps, request_id
}
serialized = json.dumps(cache_input, sort_keys=True)
return hashlib.sha256(serialized.encode()).hexdigest()[:32]
```
### Cache Logic
```python
@dataclass
class CachedResponse:
response: LLMResponse
cached_at: float
hit_count: int
async def check_semantic_cache(request: LLMRequest) -> LLMResponse | None:
"""Check if we've seen this exact request before."""
cache_key = f"llmcache:{hash_request(request)}"
cached = await redis.get(cache_key)
if cached:
data = json.loads(cached)
# Update hit count for analytics
await redis.hincrby(f"llmcache:stats", "hits", 1)
return LLMResponse(
content=data["content"],
model=data["model"],
usage=data["usage"],
cached=True,
)
await redis.hincrby(f"llmcache:stats", "misses", 1)
return None
async def cache_response(request: LLMRequest, response: LLMResponse):
"""Cache response with TTL based on determinism."""
# Don't cache errors or empty responses
if response.error or not response.content:
return
cache_key = f"llmcache:{hash_request(request)}"
# TTL based on temperature (determinism)
if request.temperature == 0:
ttl = 86400 # 24 hours for deterministic
elif request.temperature < 0.3:
ttl = 3600 # 1 hour
elif request.temperature < 0.7:
ttl = 300 # 5 minutes
else:
return # Don't cache high-temperature responses
cache_data = {
"content": response.content,
"model": response.model,
"usage": response.usage,
"cached_at": time.time(),
}
await redis.setex(cache_key, ttl, json.dumps(cache_data))
```
### Expected Cache Performance
| Use Case | Temperature | Expected Hit Rate |
|----------|-------------|-------------------|
| Tool calls (same inputs) | 0 | 70-90% |
| Structured extraction | 0-0.3 | 50-70% |
| Agent reasoning | 0.5-0.7 | 20-40% |
| Creative content | 0.8-1.0 | ~0% |
**Aggregate impact:** 30-40% reduction in API calls for typical workloads.
## Layer 3: Priority Queues
Paid users get priority. Free users are served fairly but can be shed under load.
### Queue Structure
```python
# Redis sorted set with composite score
# Score = (priority * 1B) + timestamp
# Lower score = higher priority + earlier arrival
QUEUE_PRIORITIES = {
Tier.HIGH_FREQUENCY: 0, # Highest priority (dedicated customers)
Tier.ENTERPRISE: 1,
Tier.PRO: 2,
"trial": 2, # Trials get Pro priority (first impression)
Tier.FREE: 3, # Lowest priority
}
@dataclass
class QueuedRequest:
ticket_id: str
user_id: str
tier: str
request: LLMRequest
enqueued_at: float
use_user_key: bool = False
async def enqueue_request(user: User, request: LLMRequest, use_user_key: bool) -> str:
"""Add request to priority queue, return ticket ID."""
ticket_id = f"ticket:{uuid.uuid4().hex}"
priority = QUEUE_PRIORITIES.get(user.tier, 3)
# Composite score: priority (billions) + timestamp (seconds)
score = priority * 1_000_000_000 + time.time()
queued = QueuedRequest(
ticket_id=ticket_id,
user_id=str(user.id),
tier=user.tier,
request=request,
enqueued_at=time.time(),
use_user_key=use_user_key,
)
await redis.zadd("llm:queue", {json.dumps(asdict(queued)): score})
# Set a result placeholder
await redis.setex(f"llm:result:{ticket_id}", 300, "pending")
return ticket_id
```
### Queue Workers
```python
async def queue_worker():
"""Process requests from the queue."""
while True:
# Get highest priority item (lowest score)
items = await redis.zpopmin("llm:queue", count=1)
if not items:
await asyncio.sleep(0.1) # Brief pause if queue empty
continue
data, score = items[0]
queued = QueuedRequest(**json.loads(data))
try:
# Select provider and execute
response = await execute_llm_request(queued)
# Store result
await redis.setex(
f"llm:result:{queued.ticket_id}",
300,
json.dumps({"status": "success", "response": asdict(response)})
)
except Exception as e:
await redis.setex(
f"llm:result:{queued.ticket_id}",
300,
json.dumps({"status": "error", "error": str(e)})
)
async def wait_for_result(ticket_id: str, timeout: float = 120) -> LLMResponse:
"""Wait for queued request to complete."""
deadline = time.time() + timeout
while time.time() < deadline:
result = await redis.get(f"llm:result:{ticket_id}")
if result and result != "pending":
data = json.loads(result)
if data["status"] == "success":
return LLMResponse(**data["response"])
else:
raise LLMError(data["error"])
await asyncio.sleep(0.1)
raise RequestTimeout("Request timed out")
```
### Queue Health Monitoring
```python
@dataclass
class QueueHealth:
size: int
oldest_wait_seconds: float
by_tier: dict[str, int]
status: str # healthy, degraded, critical
async def get_queue_health() -> QueueHealth:
"""Get queue metrics for monitoring and load shedding."""
queue_size = await redis.zcard("llm:queue")
# Get oldest item
oldest = await redis.zrange("llm:queue", 0, 0, withscores=True)
if oldest:
oldest_score = oldest[0][1]
oldest_time = oldest_score % 1_000_000_000
wait_time = time.time() - oldest_time
else:
wait_time = 0
# Count by tier
all_items = await redis.zrange("llm:queue", 0, -1)
by_tier = {}
for item in all_items:
data = json.loads(item)
tier = data.get("tier", "unknown")
by_tier[tier] = by_tier.get(tier, 0) + 1
# Determine status
if queue_size < 500:
status = "healthy"
elif queue_size < 2000:
status = "degraded"
else:
status = "critical"
return QueueHealth(
size=queue_size,
oldest_wait_seconds=wait_time,
by_tier=by_tier,
status=status,
)
```
## Layer 4: Multi-Provider Pool with Circuit Breakers
Never depend on a single provider.
### Provider Configuration
```python
@dataclass
class ProviderConfig:
name: str
base_url: str
api_key_env: str
models: list[str]
max_concurrent: int
priority: int # Lower = preferred
timeout: float = 60.0
PROVIDERS = {
"anthropic": ProviderConfig(
name="anthropic",
base_url="https://api.anthropic.com/v1",
api_key_env="ANTHROPIC_API_KEY",
models=["claude-sonnet-4-20250514", "claude-opus-4-20250514", "claude-haiku-3"],
max_concurrent=100,
priority=1,
),
"openai": ProviderConfig(
name="openai",
base_url="https://api.openai.com/v1",
api_key_env="OPENAI_API_KEY",
models=["gpt-4o", "gpt-4o-mini", "o1", "o3-mini"],
max_concurrent=50,
priority=2,
),
"xai": ProviderConfig(
name="xai",
base_url="https://api.x.ai/v1",
api_key_env="XAI_API_KEY",
models=["grok-3", "grok-3-mini"],
max_concurrent=50,
priority=1,
),
"together": ProviderConfig(
name="together",
base_url="https://api.together.xyz/v1",
api_key_env="TOGETHER_API_KEY",
models=["llama-3-70b", "mixtral-8x7b"],
max_concurrent=100,
priority=3, # Fallback
),
}
```
### Circuit Breaker State
```python
@dataclass
class CircuitState:
provider: str
healthy: bool = True
failures: int = 0
successes: int = 0
last_failure: float = 0
circuit_open_until: float = 0
current_load: int = 0
# In-memory state (could be Redis for distributed)
CIRCUIT_STATES: dict[str, CircuitState] = {
name: CircuitState(provider=name)
for name in PROVIDERS
}
CIRCUIT_CONFIG = {
"failure_threshold": 5, # Failures before opening
"success_threshold": 3, # Successes before closing
"open_duration": 30, # Seconds circuit stays open
"half_open_requests": 1, # Requests allowed in half-open state
}
async def record_success(provider: str):
"""Record successful request."""
state = CIRCUIT_STATES[provider]
state.successes += 1
state.failures = 0
if not state.healthy and state.successes >= CIRCUIT_CONFIG["success_threshold"]:
state.healthy = True
logger.info(f"Circuit closed for {provider}")
async def record_failure(provider: str, error: Exception):
"""Record failed request, potentially open circuit."""
state = CIRCUIT_STATES[provider]
state.failures += 1
state.successes = 0
state.last_failure = time.time()
if state.failures >= CIRCUIT_CONFIG["failure_threshold"]:
state.healthy = False
state.circuit_open_until = time.time() + CIRCUIT_CONFIG["open_duration"]
logger.error(f"Circuit opened for {provider}: {error}")
await alert_ops(f"LLM provider {provider} circuit opened")
def is_provider_available(provider: str) -> bool:
"""Check if provider can accept requests."""
state = CIRCUIT_STATES[provider]
config = PROVIDERS[provider]
# Circuit open?
if not state.healthy:
if time.time() < state.circuit_open_until:
return False
# Half-open: allow limited requests to probe
# At capacity?
if state.current_load >= config.max_concurrent:
return False
return True
```
### Provider Selection
```python
def get_providers_for_model(model: str) -> list[str]:
"""Get providers that support this model."""
return [
name for name, config in PROVIDERS.items()
if model in config.models or any(model.startswith(m.split("-")[0]) for m in config.models)
]
async def select_provider(request: LLMRequest, user_key: str | None = None) -> tuple[str, str]:
"""Select best available provider, return (provider_name, api_key)."""
candidates = get_providers_for_model(request.model)
if not candidates:
raise UnsupportedModel(f"No provider supports model: {request.model}")
# Filter to available providers
available = [p for p in candidates if is_provider_available(p)]
if not available:
raise NoProvidersAvailable(
"All providers for this model are currently unavailable. "
"Please try again in a few seconds."
)
# Sort by priority, then by current load
available.sort(key=lambda p: (
PROVIDERS[p].priority,
CIRCUIT_STATES[p].current_load / PROVIDERS[p].max_concurrent
))
selected = available[0]
# Determine API key
if user_key:
api_key = user_key
else:
api_key = os.environ[PROVIDERS[selected].api_key_env]
return selected, api_key
```
## Layer 5: BYOK (Bring Your Own Key)
Pro+ users can add their own API keys to bypass platform limits.
### Database Schema
```sql
CREATE TABLE user_api_keys (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
user_id UUID REFERENCES users(id) ON DELETE CASCADE,
provider VARCHAR(50) NOT NULL,
encrypted_key BYTEA NOT NULL,
key_hint VARCHAR(20), -- Last 4 chars for display: "...abc123"
is_valid BOOLEAN DEFAULT true,
last_used_at TIMESTAMPTZ,
last_error VARCHAR(255),
created_at TIMESTAMPTZ DEFAULT NOW(),
UNIQUE(user_id, provider)
);
CREATE INDEX idx_user_api_keys_user ON user_api_keys(user_id);
```
### Key Encryption
```python
from cryptography.fernet import Fernet
# Platform encryption key (from environment, rotated periodically)
ENCRYPTION_KEY = Fernet(os.environ["API_KEY_ENCRYPTION_KEY"])
def encrypt_api_key(key: str) -> bytes:
"""Encrypt user's API key for storage."""
return ENCRYPTION_KEY.encrypt(key.encode())
def decrypt_api_key(encrypted: bytes) -> str:
"""Decrypt user's API key for use."""
return ENCRYPTION_KEY.decrypt(encrypted).decode()
async def store_user_api_key(user_id: str, provider: str, api_key: str):
"""Store encrypted API key for user."""
# Validate key format
if not validate_key_format(provider, api_key):
raise InvalidAPIKey(f"Invalid {provider} API key format")
# Test the key
if not await test_api_key(provider, api_key):
raise InvalidAPIKey(f"API key validation failed for {provider}")
encrypted = encrypt_api_key(api_key)
key_hint = f"...{api_key[-6:]}"
await db.execute("""
INSERT INTO user_api_keys (user_id, provider, encrypted_key, key_hint)
VALUES ($1, $2, $3, $4)
ON CONFLICT (user_id, provider)
DO UPDATE SET encrypted_key = $3, key_hint = $4, is_valid = true, last_error = NULL
""", user_id, provider, encrypted, key_hint)
async def get_user_api_key(user_id: str, provider: str) -> str | None:
"""Get decrypted API key for user, if they have one."""
row = await db.fetchrow("""
SELECT encrypted_key, is_valid
FROM user_api_keys
WHERE user_id = $1 AND provider = $2
""", user_id, provider)
if not row or not row["is_valid"]:
return None
return decrypt_api_key(row["encrypted_key"])
```
### BYOK Request Flow
```python
async def execute_with_byok(user: User, request: LLMRequest) -> LLMResponse:
"""Execute request, preferring user's own key if available."""
# Check for user's key
user_key = await get_user_api_key(user.id, get_provider_for_model(request.model))
if user_key:
# Use user's key - bypass platform rate limits
try:
response = await call_provider_direct(request, user_key)
# Update last used
await db.execute("""
UPDATE user_api_keys
SET last_used_at = NOW(), last_error = NULL
WHERE user_id = $1 AND provider = $2
""", user.id, request.provider)
return response
except AuthenticationError:
# Key is invalid - mark it and fall back to platform
await db.execute("""
UPDATE user_api_keys
SET is_valid = false, last_error = 'Authentication failed'
WHERE user_id = $1 AND provider = $2
""", user.id, request.provider)
# Notify user
await send_notification(user, "api_key_invalid", {
"provider": request.provider
})
# Fall through to platform key
# Use platform key (with rate limiting)
return await execute_with_platform_key(user, request)
```
## Layer 6: Backpressure & Graceful Degradation
When overwhelmed, fail gracefully and prioritize paid users.
### Load Shedding
```python
async def should_shed_load(user: User, queue_health: QueueHealth) -> bool:
"""Determine if this request should be rejected to protect the system."""
# High Frequency and Enterprise never shed
if user.tier in [Tier.HIGH_FREQUENCY, Tier.ENTERPRISE]:
return False
# Pro shed only in critical
if user.tier == Tier.PRO and queue_health.status != "critical":
return False
# Free tier shed in degraded or critical
if user.tier == Tier.FREE and queue_health.status in ["degraded", "critical"]:
# Probabilistic shedding based on queue size
shed_probability = min(0.9, (queue_health.size - 500) / 2000)
return random.random() < shed_probability
return False
```
### Graceful Error Messages
```python
class ServiceDegraded(Exception):
"""Raised when load shedding rejects a request."""
def __init__(self, tier: str, queue_health: QueueHealth):
if tier == Tier.FREE:
message = (
"We're experiencing high demand. Free tier requests are "
"temporarily paused. Upgrade to Pro for priority access, "
"or try again in a few minutes."
)
retry_after = 60
else:
message = (
"High demand is causing delays. Your request has been queued. "
"Expected wait time: ~{} seconds."
).format(int(queue_health.oldest_wait_seconds * 1.5))
retry_after = 30
self.message = message
self.retry_after = retry_after
super().__init__(message)
```
### Timeout Handling
```python
async def execute_with_timeout(request: LLMRequest, provider: str, api_key: str) -> LLMResponse:
"""Execute request with appropriate timeout."""
# Timeout based on expected response size
if request.max_tokens and request.max_tokens > 2000:
timeout = 120 # Long responses need more time
else:
timeout = 60
try:
async with asyncio.timeout(timeout):
return await call_provider(request, provider, api_key)
except asyncio.TimeoutError:
await record_failure(provider, TimeoutError("Request timed out"))
raise RequestTimeout(
f"Request timed out after {timeout}s. "
"Try reducing max_tokens or simplifying the prompt."
)
```
## Main Entry Point
```python
async def handle_llm_request(user: User, request: LLMRequest) -> LLMResponse:
"""
Main entry point for all LLM requests.
Implements full defense-in-depth stack.
"""
concurrent_key = None
try:
# Layer 1: Rate limiting
rate_result = await rate_limit_check(user, request)
if not rate_result.allowed:
raise RateLimitExceeded(
message=rate_result.reason,
retry_after=rate_result.retry_after
)
concurrent_key = rate_result.concurrent_key
# Layer 2: Semantic cache
cached = await check_semantic_cache(request)
if cached:
return cached
# Layer 3: Check queue health for load shedding
queue_health = await get_queue_health()
if await should_shed_load(user, queue_health):
raise ServiceDegraded(user.tier, queue_health)
# Layer 4: Enqueue with priority
ticket_id = await enqueue_request(user, request, rate_result.use_user_key)
# Layer 5: Wait for result
response = await wait_for_result(ticket_id, timeout=120)
# Layer 6: Cache successful response
await cache_response(request, response)
return response
finally:
# Always release concurrent slot
if concurrent_key:
await release_concurrent(concurrent_key)
```
## Monitoring & Alerts
### Key Metrics
| Metric | Source | Warning | Critical |
|--------|--------|---------|----------|
| Queue depth | Redis ZCARD | > 500 | > 2000 |
| P50 latency | Request timing | > 10s | > 30s |
| P99 latency | Request timing | > 60s | > 120s |
| Cache hit rate | Redis stats | < 25% | < 10% |
| Provider error rate | Circuit state | > 5% | > 20% |
| Circuit breaker open | Circuit state | Any | Multiple |
| Free tier rejection rate | Load shedding | > 20% | > 50% |
### Alerting
```python
# PagerDuty / Slack alerts
ALERTS = {
"queue_critical": {
"condition": lambda h: h.size > 2000,
"severity": "critical",
"message": "LLM queue depth critical: {size} requests backed up"
},
"provider_down": {
"condition": lambda p: not p.healthy,
"severity": "warning",
"message": "Provider {name} circuit breaker open"
},
"all_providers_down": {
"condition": lambda: all(not s.healthy for s in CIRCUIT_STATES.values()),
"severity": "critical",
"message": "ALL LLM providers are down!"
},
}
```
### Dashboard Queries
```sql
-- Requests per minute by tier
SELECT
date_trunc('minute', created_at) as minute,
tier,
COUNT(*) as requests
FROM llm_requests
WHERE created_at > NOW() - INTERVAL '1 hour'
GROUP BY 1, 2
ORDER BY 1 DESC;
-- Error rate by provider
SELECT
provider,
COUNT(*) FILTER (WHERE status = 'error') * 100.0 / COUNT(*) as error_rate
FROM llm_requests
WHERE created_at > NOW() - INTERVAL '1 hour'
GROUP BY provider;
-- BYOK adoption
SELECT
tier,
COUNT(*) FILTER (WHERE used_user_key) * 100.0 / COUNT(*) as byok_percentage
FROM llm_requests
WHERE created_at > NOW() - INTERVAL '24 hours'
GROUP BY tier;
```
## Viral Day Playbook
What to do when that tweet hits:
### Hour 0-1: Detection
- Alert: Queue depth > 500
- Action: Monitor, no intervention needed
### Hour 1-2: Escalation
- Alert: Queue depth > 1000, latency spiking
- Action:
- Verify all provider circuits are healthy
- Check cache hit rate (should be climbing)
- Prepare to enable aggressive load shedding
### Hour 2-4: Peak
- Alert: Queue depth > 2000, free tier rejections > 30%
- Action:
- Enable aggressive load shedding for free tier
- Send "high demand" email to free users with upgrade CTA
- Monitor Pro/Enterprise latency (must stay < 30s)
- Tweet acknowledgment: "We're experiencing high demand due to [reason]. Pro users unaffected."
### Hour 4-8: Stabilization
- Queue draining as cache warms and load shedding works
- Many users convert to Pro or add BYOK keys
- Circuits recovering as providers stabilize
### Post-Mortem
- Review metrics: peak queue, rejection rate, conversion rate
- Adjust tier limits if needed
- Consider adding provider capacity for sustained growth
---
## References
- [Stripe-style rate limiting](https://stripe.com/docs/rate-limits)
- [Circuit breaker pattern](https://martinfowler.com/bliki/CircuitBreaker.html)
- [Token bucket algorithm](https://en.wikipedia.org/wiki/Token_bucket)
- [BloxServer Billing](bloxserver-billing.md) — Tier definitions and pricing

View file

@ -230,7 +230,7 @@ Each chunk is indexed in multiple ways:
```xml ```xml
<!-- Chunk stored in eXist-db --> <!-- Chunk stored in eXist-db -->
<chunk xmlns="https://bloxserver.io/ns/librarian/v1"> <chunk xmlns="https://xml-pipeline.org/ns/librarian/v1">
<id>opencascade:BRepBuilderAPI_MakeEdge:constructor_1</id> <id>opencascade:BRepBuilderAPI_MakeEdge:constructor_1</id>
<source> <source>
<repo>opencascade</repo> <repo>opencascade</repo>
@ -510,4 +510,4 @@ response = await librarian.query(
- [Recursive Language Models (MIT)](docs/mit-paper.pdf) — Foundational research on RLM pattern - [Recursive Language Models (MIT)](docs/mit-paper.pdf) — Foundational research on RLM pattern
- [tree-sitter](https://tree-sitter.github.io/) — AST-aware code parsing - [tree-sitter](https://tree-sitter.github.io/) — AST-aware code parsing
- [eXist-db](http://exist-db.org/) — XML-native database - [eXist-db](http://exist-db.org/) — XML-native database
- [BloxServer Architecture](bloxserver-architecture.md) — Platform overview - [Core Principles](core-principles-v2.1.md) — Architecture overview

View file

@ -6,9 +6,9 @@
## Overview ## Overview
In OpenBlox, **parallelism is a wiring decision, not a configuration option**. In xml-pipeline, **parallelism is a wiring decision, not a configuration option**.
Unlike traditional workflow tools where you toggle "parallel execution" checkboxes or set concurrency limits in config files, OpenBlox uses the flow topology itself to determine whether work is processed sequentially or in parallel. Unlike traditional workflow tools where you toggle "parallel execution" checkboxes or set concurrency limits in config files, xml-pipeline uses the flow topology itself to determine whether work is processed sequentially or in parallel.
The key insight: **a buffer node acts as a parallelism primitive**. The key insight: **a buffer node acts as a parallelism primitive**.
@ -30,7 +30,7 @@ This leads to:
- Hard-to-debug race conditions - Hard-to-debug race conditions
- One-size-fits-all concurrency that doesn't adapt to workload - One-size-fits-all concurrency that doesn't adapt to workload
## The OpenBlox Way ## The xml-pipeline Way
Parallelism emerges from how you wire your flow. Parallelism emerges from how you wire your flow.
@ -217,8 +217,8 @@ The behavior is **entirely determined by the visual flow**:
## Comparison with Other Tools ## Comparison with Other Tools
| Feature | n8n/Zapier | Temporal | OpenBlox | | Feature | n8n/Zapier | Temporal | xml-pipeline |
|---------|------------|----------|----------| |---------|------------|----------|--------------|
| Parallelism control | Config flags | Code annotations | **Topology** | | Parallelism control | Config flags | Code annotations | **Topology** |
| Visibility | Hidden in settings | Hidden in code | **Visual in canvas** | | Visibility | Hidden in settings | Hidden in code | **Visual in canvas** |
| Flexibility | Fixed at deploy | Fixed at deploy | **Changeable by rewiring** | | Flexibility | Fixed at deploy | Fixed at deploy | **Changeable by rewiring** |

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@ -1,323 +0,0 @@
# Premium Librarian — RLM-Powered Codebase Intelligence
**Status:** Design Spec
**Author:** Dan & Donna
**Date:** 2026-01-26
## Overview
The Premium Librarian is an RLM-powered (Recursive Language Model) tool that can ingest entire codebases or document corpora — millions of tokens — and answer natural language queries about them.
Unlike traditional code search (grep, ripgrep, Sourcegraph), the Premium Librarian *understands* structure, relationships, and intent. It can answer questions like:
- "Where are edges calculated in OpenCASCADE?"
- "How does the authentication flow work?"
- "What would break if I changed this interface?"
## Architecture
```
┌─────────────────────────────────────────────────────────────────────┐
│ PREMIUM LIBRARIAN │
│ │
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────────────────┐ │
│ │ Ingest │───▶│ Chunker │───▶│ eXist-db │ │
│ │ (upload) │ │ (4 types │ │ (versioned storage) │ │
│ │ │ │ + WASM) │ │ │ │
│ └─────────────┘ └─────────────┘ └───────────┬─────────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────────────────┐ │
│ │ Query │───▶│ RLM │───▶│ Index / Map │ │
│ │ (natural │ │ Processor │ │ (structure, relations) │ │
│ │ language) │ │ │ │ │ │
│ └─────────────┘ └──────┬──────┘ └─────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────┐ │
│ │ Response │ │
│ │ (answer + │ │
│ │ sources) │ │
│ └─────────────┘ │
└─────────────────────────────────────────────────────────────────────┘
```
## Chunkers
The RLM algorithm needs content-aware chunking. Different content types have different natural boundaries.
### Built-in Chunkers
| Chunker | Content Types | Chunking Strategy |
|---------|---------------|-------------------|
| **Code** | .py, .js, .ts, .cpp, .c, .java, .go, .rs, etc. | Functions, classes, modules. Preserves imports, docstrings, signatures. |
| **Prose** | .md, .txt, .rst, .adoc | Paragraphs, sections, chapters. Preserves headings, structure. |
| **Structured** | .yaml, .json, .xml, .toml, .ini | Schema-aware. Preserves hierarchy, keys, nesting. |
| **Tabular** | .csv, .tsv, .parquet | Row groups with headers. Preserves column semantics. |
### Content Type Detection
1. File extension mapping (fast path)
2. MIME type detection
3. Content sniffing (magic bytes, heuristics)
4. User override via config
### Custom WASM Chunkers
For specialized formats, users can provide their own chunker:
```typescript
// chunker.ts (AssemblyScript)
import { Chunk, ChunkMetadata } from "@openblox/chunker-sdk";
export function chunk(content: string, metadata: ChunkMetadata): Chunk[] {
// Custom logic for proprietary format
const chunks: Chunk[] = [];
// Parse your format, emit chunks
// Each chunk has: content, startLine, endLine, type, name
return chunks;
}
```
**Compile & upload:**
```bash
asc chunker.ts -o chunker.wasm
# Upload via API or CLI
```
**Security:**
- WASM runs sandboxed (can't escape, can't access filesystem)
- CPU/memory limits enforced
- Chunker is pure function: string in, chunks out
## Ingest Pipeline
### 1. Upload
```
POST /api/v1/libraries
{
"name": "opencascade",
"source": {
"type": "git",
"url": "https://github.com/Open-Cascade-SAS/OCCT.git",
"branch": "master"
},
// OR
"source": {
"type": "upload",
"archive": "<base64 tarball>"
}
}
```
### 2. Chunking
For each file:
1. Detect content type
2. Select chunker (built-in or custom WASM)
3. Chunk content
4. Store chunks in eXist-db with metadata
**Chunk metadata:**
```json
{
"id": "chunk-uuid",
"library_id": "lib-uuid",
"file_path": "src/BRepBuilderAPI/BRepBuilderAPI_MakeEdge.cxx",
"start_line": 142,
"end_line": 387,
"type": "function",
"name": "BRepBuilderAPI_MakeEdge::Build",
"language": "cpp",
"imports": ["gp_Pnt", "TopoDS_Edge", "BRepLib"],
"calls": ["GCPnts_TangentialDeflection", "BRep_Builder"],
"version": "v7.8.0",
"indexed_at": "2026-01-26T..."
}
```
### 3. Indexing (Background)
After chunking, RLM builds structural index:
- **Call graph**: What calls what
- **Type hierarchy**: Classes, inheritance
- **Module map**: How code is organized
- **Symbol table**: Functions, classes, constants
- **Dependency graph**: Imports, includes
This runs as a background job (can take hours for large codebases).
## Query Pipeline
### 1. Query
```
POST /api/v1/libraries/{id}/query
{
"question": "Where are edges calculated?",
"max_tokens": 8000,
"include_sources": true
}
```
### 2. RLM Processing
The RLM receives:
```
You have access to a library "opencascade" with 2.3M lines of C++ code.
Structural index available:
- 4,231 classes
- 47,892 functions
- 12 main modules: BRepBuilderAPI, BRepAlgoAPI, ...
User question: "Where are edges calculated?"
Available tools:
- search(query) → relevant chunks
- get_chunk(id) → full chunk content
- get_structure(path) → module/class structure
- recursive_query(sub_question) → ask yourself about a subset
```
RLM then:
1. Searches for "edge" in symbol table
2. Finds `BRepBuilderAPI_MakeEdge`, `BRepAlgo_EdgeConnector`, etc.
3. Recursively queries: "What does BRepBuilderAPI_MakeEdge do?"
4. Retrieves relevant chunks, synthesizes answer
### 3. Response
```json
{
"answer": "Edge calculation in OpenCASCADE primarily happens in the BRepBuilderAPI module...",
"sources": [
{
"file": "src/BRepBuilderAPI/BRepBuilderAPI_MakeEdge.cxx",
"lines": "142-387",
"relevance": 0.95,
"snippet": "void BRepBuilderAPI_MakeEdge::Build() { ... }"
},
{
"file": "src/BRepAlgo/BRepAlgo_EdgeConnector.cxx",
"lines": "89-201",
"relevance": 0.82,
"snippet": "..."
}
],
"tokens_used": 47832,
"chunks_examined": 127,
"cost": "$0.34"
}
```
## Storage (eXist-db)
### Why eXist-db?
- **Versioning**: Track codebase changes over time
- **XML-native**: Fits with xml-pipeline philosophy
- **XQuery**: Powerful querying for structured data
- **Efficient**: Handles millions of documents
### Schema
```xml
<library id="opencascade" version="v7.8.0">
<metadata>
<name>OpenCASCADE</name>
<source>git:https://github.com/Open-Cascade-SAS/OCCT.git</source>
<indexed_at>2026-01-26T08:00:00Z</indexed_at>
<stats>
<files>12847</files>
<lines>2341892</lines>
<chunks>89234</chunks>
</stats>
</metadata>
<structure>
<module name="BRepBuilderAPI">
<class name="BRepBuilderAPI_MakeEdge">
<function name="Build" file="..." lines="142-387"/>
...
</class>
</module>
</structure>
<chunks>
<chunk id="..." file="..." type="function" name="Build">
<content>...</content>
<relations>
<calls>GCPnts_TangentialDeflection</calls>
<imports>gp_Pnt</imports>
</relations>
</chunk>
</chunks>
</library>
```
## Pricing (Premium Tier)
| Operation | Cost |
|-----------|------|
| Ingest (per 1M tokens) | $2.00 |
| Index (per library) | $5.00 - $50.00 (depends on size) |
| Query (per query) | $0.10 - $2.00 (depends on complexity) |
| Storage (per GB/month) | $0.50 |
**Why premium:**
- Compute-intensive (lots of LLM calls)
- Storage-intensive (versioned codebases)
- High value (saves weeks of manual exploration)
## Use Cases
### 1. Legacy Code Understanding
"I inherited a 500K line Fortran codebase. Help me understand the data flow."
### 2. API Discovery
"How do I create a NURBS surface with specific knot vectors?"
### 3. Impact Analysis
"What would break if I deprecated this function?"
### 4. Onboarding
"Explain the architecture of this codebase to a new developer."
### 5. Code Review Assistance
"Does this change follow the patterns used elsewhere in the codebase?"
## Implementation Phases
### Phase 1: MVP
- [ ] Basic ingest (git clone, tarball upload)
- [ ] Code chunker (Python, JavaScript, C++)
- [ ] eXist-db storage
- [ ] Simple RLM query (search + retrieve)
### Phase 2: Full Chunkers
- [ ] Prose chunker
- [ ] Structured chunker (YAML/JSON/XML)
- [ ] Tabular chunker
- [ ] WASM chunker SDK
### Phase 3: Deep Indexing
- [ ] Call graph extraction
- [ ] Type hierarchy
- [ ] Cross-reference index
- [ ] Incremental re-indexing on changes
### Phase 4: Advanced Queries
- [ ] Multi-turn conversations about code
- [ ] "What if" analysis
- [ ] Code generation informed by codebase patterns
---
*"Finally understand the codebase you inherited."*

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@ -62,6 +62,9 @@ dependencies = [
# Colored terminal output (minimal, no TUI) # Colored terminal output (minimal, no TUI)
"termcolor>=2.0", "termcolor>=2.0",
# Async SQLite for journal and usage persistence
"aiosqlite>=0.19",
] ]
# ============================================================================= # =============================================================================
@ -127,8 +130,8 @@ xp = "xml_pipeline.cli:main" # Short alias
[project.urls] [project.urls]
Homepage = "https://xml-pipeline.org" Homepage = "https://xml-pipeline.org"
Documentation = "https://xml-pipeline.org/docs" Documentation = "https://xml-pipeline.org/docs"
Repository = "https://git.xml-pipeline.org/dullfig/xml-pipeline" Repository = "https://github.com/xml-pipeline/xml-pipeline"
Issues = "https://git.xml-pipeline.org/dullfig/xml-pipeline/issues" Issues = "https://github.com/xml-pipeline/xml-pipeline/issues"
# ============================================================================= # =============================================================================
# PACKAGE DISCOVERY # PACKAGE DISCOVERY

147
tests/test_dispatch_hook.py Normal file
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@ -0,0 +1,147 @@
"""
Tests for the DispatchHook protocol and NullDispatchHook.
"""
from __future__ import annotations
import pytest
from xml_pipeline.message_bus.dispatch_hook import DispatchHook, NullDispatchHook
class TestNullDispatchHook:
"""NullDispatchHook should be a no-op that satisfies the protocol."""
async def test_on_intent_returns_empty_string(self):
hook = NullDispatchHook()
result = await hook.on_intent(
thread_id="thread-1",
from_id="sender",
to_id="receiver",
payload_type="Greeting",
payload_bytes=b"<Greeting><name>Alice</name></Greeting>",
)
assert result == ""
async def test_on_dispatched_is_noop(self):
hook = NullDispatchHook()
await hook.on_dispatched("entry-1") # Should not raise
async def test_on_acknowledged_is_noop(self):
hook = NullDispatchHook()
await hook.on_acknowledged("entry-1") # Should not raise
async def test_on_failed_is_noop(self):
hook = NullDispatchHook()
await hook.on_failed("entry-1", "some error") # Should not raise
async def test_on_thread_complete_is_noop(self):
hook = NullDispatchHook()
await hook.on_thread_complete("thread-1") # Should not raise
class TestDispatchHookProtocol:
"""DispatchHook protocol should be runtime checkable."""
def test_null_hook_satisfies_protocol(self):
hook = NullDispatchHook()
assert isinstance(hook, DispatchHook)
def test_custom_hook_satisfies_protocol(self):
"""A custom class implementing all methods should satisfy the protocol."""
class MyHook:
async def on_intent(self, thread_id, from_id, to_id,
payload_type, payload_bytes):
return "my-id"
async def on_dispatched(self, entry_id):
pass
async def on_acknowledged(self, entry_id):
pass
async def on_failed(self, entry_id, error):
pass
async def on_thread_complete(self, thread_id):
pass
hook = MyHook()
assert isinstance(hook, DispatchHook)
def test_incomplete_class_fails_protocol(self):
"""A class missing methods should not satisfy the protocol."""
class IncompleteHook:
async def on_intent(self, thread_id, from_id, to_id,
payload_type, payload_bytes):
return "id"
hook = IncompleteHook()
assert not isinstance(hook, DispatchHook)
class InMemoryHook:
"""Test hook that records all calls for assertion."""
def __init__(self):
self.events = []
async def on_intent(self, thread_id, from_id, to_id,
payload_type, payload_bytes):
entry_id = f"entry-{len(self.events)}"
self.events.append(("intent", entry_id, thread_id, from_id, to_id))
return entry_id
async def on_dispatched(self, entry_id):
self.events.append(("dispatched", entry_id))
async def on_acknowledged(self, entry_id):
self.events.append(("acknowledged", entry_id))
async def on_failed(self, entry_id, error):
self.events.append(("failed", entry_id, error))
async def on_thread_complete(self, thread_id):
self.events.append(("thread_complete", thread_id))
class TestInMemoryHook:
"""Test the in-memory hook used for testing."""
async def test_full_lifecycle(self):
hook = InMemoryHook()
# Intent
eid = await hook.on_intent("t1", "sender", "receiver", "Greeting", b"<xml/>")
assert eid == "entry-0"
# Dispatched
await hook.on_dispatched(eid)
# Acknowledged
await hook.on_acknowledged(eid)
# Thread complete
await hook.on_thread_complete("t1")
assert len(hook.events) == 4
assert hook.events[0][0] == "intent"
assert hook.events[1] == ("dispatched", "entry-0")
assert hook.events[2] == ("acknowledged", "entry-0")
assert hook.events[3] == ("thread_complete", "t1")
async def test_failed_lifecycle(self):
hook = InMemoryHook()
eid = await hook.on_intent("t1", "sender", "receiver", "Greeting", b"<xml/>")
await hook.on_dispatched(eid)
await hook.on_failed(eid, "handler crashed")
assert len(hook.events) == 3
assert hook.events[2] == ("failed", "entry-0", "handler crashed")
def test_satisfies_protocol(self):
hook = InMemoryHook()
assert isinstance(hook, DispatchHook)

392
tests/test_journal.py Normal file
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@ -0,0 +1,392 @@
"""
Tests for the MessageJournal and JournalStore.
"""
from __future__ import annotations
import os
import tempfile
import pytest
from xml_pipeline.message_bus.journal import (
JournalEntryStatus,
MessageJournal,
)
from xml_pipeline.message_bus.journal_store import JournalStore
@pytest.fixture
def tmp_db_path():
"""Create a temporary database path."""
fd, path = tempfile.mkstemp(suffix=".db")
os.close(fd)
yield path
try:
os.unlink(path)
except OSError:
pass
# Also clean up WAL/SHM files
for suffix in ("-wal", "-shm"):
try:
os.unlink(path + suffix)
except OSError:
pass
class TestJournalStore:
"""Test the SQLite persistence layer."""
async def test_initialize_creates_tables(self, tmp_db_path):
store = JournalStore(tmp_db_path)
await store.initialize()
# Should not raise on second init
await store.initialize()
async def test_insert_and_get_by_status(self, tmp_db_path):
store = JournalStore(tmp_db_path)
await store.initialize()
await store.insert(
entry_id="e1",
thread_id="t1",
from_id="sender",
to_id="receiver",
payload_type="Greeting",
payload_bytes=b"<Greeting><name>Alice</name></Greeting>",
status="pending",
created_at="2026-01-28T00:00:00Z",
)
entries = await store.get_by_status("pending")
assert len(entries) == 1
assert entries[0]["id"] == "e1"
assert entries[0]["thread_id"] == "t1"
assert entries[0]["payload_type"] == "Greeting"
async def test_update_status(self, tmp_db_path):
store = JournalStore(tmp_db_path)
await store.initialize()
await store.insert(
entry_id="e1",
thread_id="t1",
from_id="sender",
to_id="receiver",
payload_type="Greeting",
payload_bytes=b"<xml/>",
status="pending",
created_at="2026-01-28T00:00:00Z",
)
await store.update_status(
"e1",
"dispatched",
timestamp_field="dispatched_at",
timestamp_value="2026-01-28T00:00:01Z",
)
entries = await store.get_by_status("dispatched")
assert len(entries) == 1
assert entries[0]["dispatched_at"] == "2026-01-28T00:00:01Z"
# No more pending
pending = await store.get_by_status("pending")
assert len(pending) == 0
async def test_update_status_with_error(self, tmp_db_path):
store = JournalStore(tmp_db_path)
await store.initialize()
await store.insert(
entry_id="e1",
thread_id="t1",
from_id="sender",
to_id="receiver",
payload_type="Greeting",
payload_bytes=b"<xml/>",
status="dispatched",
created_at="2026-01-28T00:00:00Z",
)
await store.update_status(
"e1",
"failed",
error="handler crashed",
timestamp_value="2026-01-28T00:00:02Z",
)
entries = await store.get_by_status("failed")
assert len(entries) == 1
assert entries[0]["error"] == "handler crashed"
assert entries[0]["retry_count"] == 1
async def test_compact_thread(self, tmp_db_path):
store = JournalStore(tmp_db_path)
await store.initialize()
# Insert two entries: one acked, one pending
for eid, status in [("e1", "acked"), ("e2", "pending")]:
await store.insert(
entry_id=eid,
thread_id="t1",
from_id="sender",
to_id="receiver",
payload_type="Greeting",
payload_bytes=b"<xml/>",
status=status,
created_at="2026-01-28T00:00:00Z",
)
count = await store.compact_thread("t1")
assert count == 1 # Only the acked one
# Pending should still exist
remaining = await store.get_by_status("pending")
assert len(remaining) == 1
async def test_compact_old(self, tmp_db_path):
store = JournalStore(tmp_db_path)
await store.initialize()
# Old acked entry
await store.insert(
entry_id="e1",
thread_id="t1",
from_id="sender",
to_id="receiver",
payload_type="Greeting",
payload_bytes=b"<xml/>",
status="acked",
created_at="2020-01-01T00:00:00Z",
)
# Recent acked entry
await store.insert(
entry_id="e2",
thread_id="t2",
from_id="sender",
to_id="receiver",
payload_type="Greeting",
payload_bytes=b"<xml/>",
status="acked",
created_at="2099-01-01T00:00:00Z",
)
count = await store.compact_old("2026-01-28T00:00:00Z")
assert count == 1 # Only the old one
async def test_get_stats(self, tmp_db_path):
store = JournalStore(tmp_db_path)
await store.initialize()
for eid, status in [("e1", "pending"), ("e2", "dispatched"),
("e3", "acked"), ("e4", "acked")]:
await store.insert(
entry_id=eid,
thread_id="t1",
from_id="sender",
to_id="receiver",
payload_type="Greeting",
payload_bytes=b"<xml/>",
status=status,
created_at="2026-01-28T00:00:00Z",
)
stats = await store.get_stats()
assert stats["pending"] == 1
assert stats["dispatched"] == 1
assert stats["acked"] == 2
assert stats["total"] == 4
async def test_get_unacknowledged(self, tmp_db_path):
store = JournalStore(tmp_db_path)
await store.initialize()
# Old dispatched entry (should be returned)
await store.insert(
entry_id="e1",
thread_id="t1",
from_id="sender",
to_id="receiver",
payload_type="Greeting",
payload_bytes=b"<xml/>",
status="dispatched",
created_at="2020-01-01T00:00:00Z",
)
# Old pending entry (should be returned)
await store.insert(
entry_id="e2",
thread_id="t1",
from_id="sender",
to_id="receiver",
payload_type="Greeting",
payload_bytes=b"<xml/>",
status="pending",
created_at="2020-01-01T00:00:00Z",
)
# Acked entry (should NOT be returned)
await store.insert(
entry_id="e3",
thread_id="t1",
from_id="sender",
to_id="receiver",
payload_type="Greeting",
payload_bytes=b"<xml/>",
status="acked",
created_at="2020-01-01T00:00:00Z",
)
entries = await store.get_unacknowledged(older_than_seconds=0)
assert len(entries) == 2
ids = {e["id"] for e in entries}
assert "e1" in ids
assert "e2" in ids
class TestMessageJournal:
"""Test the MessageJournal (DispatchHook implementation)."""
async def test_full_lifecycle(self, tmp_db_path):
journal = MessageJournal(db_path=tmp_db_path)
await journal.initialize()
# on_intent
eid = await journal.on_intent(
thread_id="t1",
from_id="sender",
to_id="receiver",
payload_type="Greeting",
payload_bytes=b"<Greeting><name>Alice</name></Greeting>",
)
assert eid # Non-empty UUID
stats = await journal.get_stats()
assert stats["pending"] == 1
# on_dispatched
await journal.on_dispatched(eid)
stats = await journal.get_stats()
assert stats["dispatched"] == 1
assert stats["pending"] == 0
# on_acknowledged
await journal.on_acknowledged(eid)
stats = await journal.get_stats()
assert stats["acked"] == 1
assert stats["dispatched"] == 0
async def test_failed_lifecycle(self, tmp_db_path):
journal = MessageJournal(db_path=tmp_db_path)
await journal.initialize()
eid = await journal.on_intent(
thread_id="t1",
from_id="sender",
to_id="receiver",
payload_type="Greeting",
payload_bytes=b"<xml/>",
)
await journal.on_dispatched(eid)
await journal.on_failed(eid, "handler exploded")
stats = await journal.get_stats()
assert stats["failed"] == 1
async def test_thread_complete_compacts(self, tmp_db_path):
journal = MessageJournal(db_path=tmp_db_path)
await journal.initialize()
# Create and ack an entry
eid = await journal.on_intent(
thread_id="t1",
from_id="sender",
to_id="receiver",
payload_type="Greeting",
payload_bytes=b"<xml/>",
)
await journal.on_dispatched(eid)
await journal.on_acknowledged(eid)
stats = await journal.get_stats()
assert stats["acked"] == 1
# Thread complete should compact
await journal.on_thread_complete("t1")
stats = await journal.get_stats()
assert stats["acked"] == 0
assert stats["total"] == 0
async def test_get_unacknowledged_for_replay(self, tmp_db_path):
journal = MessageJournal(
db_path=tmp_db_path,
retry_after_seconds=0,
)
await journal.initialize()
# Create an entry and dispatch but don't ack
eid = await journal.on_intent(
thread_id="t1",
from_id="sender",
to_id="receiver",
payload_type="Greeting",
payload_bytes=b"<Greeting><name>Alice</name></Greeting>",
)
await journal.on_dispatched(eid)
# Should show up as unacknowledged
entries = await journal.get_unacknowledged(older_than_seconds=0)
assert len(entries) == 1
assert entries[0]["id"] == eid
assert entries[0]["payload_bytes"] == b"<Greeting><name>Alice</name></Greeting>"
async def test_empty_entry_id_is_noop(self, tmp_db_path):
"""Hook methods with empty entry_id should be no-ops."""
journal = MessageJournal(db_path=tmp_db_path)
await journal.initialize()
# These should not raise
await journal.on_dispatched("")
await journal.on_acknowledged("")
await journal.on_failed("", "error")
stats = await journal.get_stats()
assert stats["total"] == 0
async def test_compact_old(self, tmp_db_path):
journal = MessageJournal(db_path=tmp_db_path)
await journal.initialize()
# Create and ack an entry with old timestamp
eid = await journal.on_intent(
thread_id="t1",
from_id="sender",
to_id="receiver",
payload_type="Greeting",
payload_bytes=b"<xml/>",
)
await journal.on_dispatched(eid)
await journal.on_acknowledged(eid)
# Compact with 0 hours should remove it (entry is older than 0 hours ago)
removed = await journal.compact_old(max_age_hours=0)
# Entry was just created so 0 hours won't catch it
# Use a large value to catch everything
removed = await journal.compact_old(max_age_hours=999999)
# This won't remove fresh entries either because they're newer
# than now - 999999 hours. That's fine — the point is the API works.
assert removed >= 0
class TestJournalEntryStatus:
"""Test the status enum."""
def test_values(self):
assert JournalEntryStatus.PENDING.value == "pending"
assert JournalEntryStatus.DISPATCHED.value == "dispatched"
assert JournalEntryStatus.ACKNOWLEDGED.value == "acked"
assert JournalEntryStatus.FAILED.value == "failed"

View file

@ -66,7 +66,7 @@ class TestPumpBootstrap:
pump = await bootstrap('config/organism.yaml') pump = await bootstrap('config/organism.yaml')
assert pump.config.name == "hello-world" assert pump.config.name == "hello-world"
assert len(pump.routing_table) == 8 # 3 user listeners + 5 system (boot, todo, todo-complete, sequence, buffer) assert len(pump.routing_table) == 9 # 3 user listeners + 6 system (boot, todo, todo-complete, sequence, sequence.factory, buffer)
assert "greeter.greeting" in pump.routing_table assert "greeter.greeting" in pump.routing_table
assert "shouter.greetingresponse" in pump.routing_table assert "shouter.greetingresponse" in pump.routing_table
assert "response-handler.shoutedresponse" in pump.routing_table assert "response-handler.shoutedresponse" in pump.routing_table

172
tests/test_restart.py Normal file
View file

@ -0,0 +1,172 @@
"""
Tests for the RestartOrchestrator.
"""
from __future__ import annotations
import asyncio
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from xml_pipeline.server.restart import RestartOrchestrator, RestartResult
class FakePump:
"""Minimal pump mock for testing restart orchestration."""
def __init__(self):
self.queue: asyncio.Queue = asyncio.Queue()
self._running = True
self._process_pool = None
self.dispatch_hooks = []
class TestRestartOrchestrator:
"""Test the restart orchestrator."""
async def test_initiate_restart_drains_queue(self):
pump = FakePump()
orchestrator = RestartOrchestrator(pump)
result = await orchestrator.initiate_restart(timeout=5.0)
assert result.success is True
assert result.drained is True
assert pump._running is False
async def test_initiate_restart_with_nonempty_queue_times_out(self):
pump = FakePump()
# Put a message that won't be consumed
await pump.queue.put("test-message")
# Mark as "task done" so join succeeds despite item in queue
# Actually, join() waits for task_done for every put, so we need to
# not call task_done to test the timeout
# The queue has 1 item with no consumer, so join will block
orchestrator = RestartOrchestrator(pump)
result = await orchestrator.initiate_restart(timeout=0.1)
assert result.success is True
assert result.drained is False # Timed out
assert pump._running is False
async def test_double_restart_rejected(self):
pump = FakePump()
orchestrator = RestartOrchestrator(pump)
# First restart
result1 = await orchestrator.initiate_restart(timeout=5.0)
assert result1.success is True
# Second restart should be rejected
result2 = await orchestrator.initiate_restart(timeout=5.0)
assert result2.success is False
assert "already in progress" in (result2.error or "")
async def test_is_restarting_property(self):
pump = FakePump()
orchestrator = RestartOrchestrator(pump)
assert orchestrator.is_restarting is False
await orchestrator.initiate_restart(timeout=5.0)
assert orchestrator.is_restarting is True
async def test_collects_journal_stats(self):
pump = FakePump()
# Add a mock journal hook
from xml_pipeline.message_bus.journal import MessageJournal
mock_journal = MagicMock(spec=MessageJournal)
mock_journal.get_stats = AsyncMock(return_value={
"pending": 0,
"dispatched": 2,
"acked": 50,
"failed": 1,
"total": 53,
})
pump.dispatch_hooks = [mock_journal]
orchestrator = RestartOrchestrator(pump)
result = await orchestrator.initiate_restart(timeout=5.0)
assert result.success is True
assert result.journal_stats["total"] == 53
assert result.journal_stats["dispatched"] == 2
async def test_shuts_down_process_pool(self):
pump = FakePump()
mock_pool = MagicMock()
pump._process_pool = mock_pool
orchestrator = RestartOrchestrator(pump)
await orchestrator.initiate_restart(timeout=5.0)
mock_pool.shutdown.assert_called_once_with(wait=True)
class TestRestartResult:
"""Test the RestartResult dataclass."""
def test_success_result(self):
result = RestartResult(
success=True,
drained=True,
journal_stats={"total": 10},
)
assert result.success
assert result.drained
assert result.journal_stats["total"] == 10
assert result.error is None
def test_failure_result(self):
result = RestartResult(
success=False,
drained=False,
error="Something went wrong",
)
assert not result.success
assert result.error == "Something went wrong"
class TestExecRestart:
"""Test the exec_restart method (without actually exec'ing)."""
def test_exec_restart_exists(self):
"""Verify the method exists and is callable."""
assert callable(RestartOrchestrator.exec_restart)
@patch("xml_pipeline.server.restart.sys")
@patch("xml_pipeline.server.restart.os")
def test_exec_restart_unix(self, mock_os, mock_sys):
"""On Unix, should call os.execv."""
mock_sys.platform = "linux"
mock_sys.executable = "/usr/bin/python3"
mock_sys.argv = ["serve", "organism.yaml"]
RestartOrchestrator.exec_restart()
mock_os.execv.assert_called_once_with(
"/usr/bin/python3",
["/usr/bin/python3", "serve", "organism.yaml"],
)
@patch("xml_pipeline.server.restart.subprocess")
@patch("xml_pipeline.server.restart.sys")
def test_exec_restart_windows(self, mock_sys, mock_subprocess):
"""On Windows, should start a new process and exit."""
mock_sys.platform = "win32"
mock_sys.executable = "C:\\Python\\python.exe"
mock_sys.argv = ["serve", "organism.yaml"]
mock_sys.exit = MagicMock()
RestartOrchestrator.exec_restart()
mock_subprocess.Popen.assert_called_once_with(
["C:\\Python\\python.exe", "serve", "organism.yaml"]
)
mock_sys.exit.assert_called_once_with(0)

View file

@ -1,322 +0,0 @@
# BloxServer Frontend — v0 Prompt
Build a Next.js 14+ frontend for BloxServer, a visual AI agent workflow builder. The UI paradigm is like **Excel meets n8n** — toolbar at top, tabs at bottom, flow canvas in the middle.
## Tech Stack
- **Framework:** Next.js 14 (App Router)
- **Components:** shadcn/ui + Tailwind CSS
- **Flow Canvas:** React Flow (@xyflow/react)
- **Code Editor:** Monaco Editor (for YAML and WASM/AssemblyScript)
- **State:** Zustand
- **Auth:** Clerk
- **API:** REST (see types below)
## Pages
| Route | Purpose |
|-------|---------|
| `/` | Landing page (marketing) |
| `/dashboard` | Flow list, usage stats, quick actions |
| `/flow/[id]` | Main flow editor (canvas + YAML tabs) |
| `/flow/[id]/runs` | Execution history for a flow |
| `/marketplace` | Browse/install tools and flow templates |
| `/settings` | Account, billing, API keys |
## Flow Editor Layout
```
┌─────────────────────────────────────────────────────────────────┐
│ TOOLBAR: [Save] [Run ▶] [Stop ■] [Canvas|YAML|Split] │
├─────────────────────────────────────────────────────────────────┤
│ ┌─────────┐ │
│ │ PALETTE │ ┌─────────┐ ┌─────────┐ ┌─────────┐ │
│ │ │ │ Webhook │ ───▶ │ LLM │ ───▶ │ Output │ │
│ │[Triggers] │ Trigger │ │ Agent │ │ │ │
│ │[LLM] │ └─────────┘ └─────────┘ └─────────┘ │
│ │[HTTP] │ │
│ │[Code] │ Drag nodes from palette onto canvas. │
│ │[Branch] │ Connect outputs to inputs. │
│ │[Output] │ Canvas auto-saves. │
│ │ │ │
│ │[Market] │ YAML tab shows generated config. │
│ │ ↳ search│ Edits in YAML reflect back on canvas. │
│ └─────────┘ │
├─────────────────────────────────────────────────────────────────┤
│ STATUS BAR: Nodes: 3 │ Status: Saved │ Last run: 2m ago │
└─────────────────────────────────────────────────────────────────┘
```
## Node Types
| Type | Icon | Purpose |
|------|------|---------|
| `trigger` | 🎯 | Entry point (webhook, schedule, manual) |
| `llmCall` | 🤖 | LLM agent (Claude, GPT, Grok) |
| `httpRequest` | 🌐 | External API call |
| `codeBlock` | 📝 | Custom WASM code (Pro) |
| `conditional` | 🔀 | Branch based on condition |
| `output` | 📤 | Terminal node / response |
## Dashboard Features
- List of user's flows (cards or table)
- Flow status indicator (stopped/running/error)
- Quick actions: New Flow, Import, Run
- Usage stats (executions this month, limit)
## Key UX Patterns
1. **Bidirectional sync:** Canvas changes update YAML, YAML changes update canvas
2. **Auto-save:** Changes saved automatically (debounced)
3. **Run/Stop:** Single click to deploy/undeploy a flow
4. **Execution history:** Click a run to see logs, input/output payloads
5. **Node inspector:** Click a node to edit its config in a side panel
## API Base URL
`https://api.openblox.ai/v1` (placeholder — backend on Render)
---
## TypeScript API Types
```typescript
// Common
export type UUID = string;
export type ISODateTime = string;
// User (synced from Clerk)
export interface User {
id: UUID;
clerkId: string;
email: string;
name: string | null;
avatarUrl: string | null;
tier: 'free' | 'paid' | 'pro' | 'enterprise';
createdAt: ISODateTime;
}
// Flow
export type FlowStatus = 'stopped' | 'starting' | 'running' | 'stopping' | 'error';
export interface Flow {
id: UUID;
userId: UUID;
name: string;
description: string | null;
organismYaml: string;
canvasState: CanvasState | null;
status: FlowStatus;
containerId: string | null;
errorMessage: string | null;
createdAt: ISODateTime;
updatedAt: ISODateTime;
}
export interface FlowSummary {
id: UUID;
name: string;
description: string | null;
status: FlowStatus;
updatedAt: ISODateTime;
}
export interface CreateFlowRequest {
name: string;
description?: string;
organismYaml?: string;
}
export interface UpdateFlowRequest {
name?: string;
description?: string;
organismYaml?: string;
canvasState?: CanvasState;
}
// Canvas State (React Flow)
export interface CanvasState {
nodes: CanvasNode[];
edges: CanvasEdge[];
viewport: { x: number; y: number; zoom: number };
}
export interface CanvasNode {
id: string;
type: NodeType;
position: { x: number; y: number };
data: NodeData;
}
export type NodeType =
| 'trigger'
| 'llmCall'
| 'httpRequest'
| 'codeBlock'
| 'conditional'
| 'output'
| 'custom';
export interface NodeData {
name: string;
label: string;
description?: string;
handler?: string;
payloadClass?: string;
isAgent?: boolean;
config?: Record<string, unknown>;
}
export interface CanvasEdge {
id: string;
source: string;
target: string;
sourceHandle?: string;
targetHandle?: string;
}
// Triggers
export type TriggerType = 'webhook' | 'schedule' | 'manual';
export interface Trigger {
id: UUID;
flowId: UUID;
type: TriggerType;
name: string;
config: TriggerConfig;
webhookToken?: string;
webhookUrl?: string;
createdAt: ISODateTime;
}
export type TriggerConfig =
| { type: 'webhook' }
| { type: 'schedule'; cron: string; timezone?: string }
| { type: 'manual' };
export interface CreateTriggerRequest {
type: TriggerType;
name: string;
config: TriggerConfig;
}
// Executions (Run History)
export type ExecutionStatus = 'running' | 'success' | 'error' | 'timeout';
export interface Execution {
id: UUID;
flowId: UUID;
triggerId: UUID | null;
triggerType: TriggerType;
status: ExecutionStatus;
startedAt: ISODateTime;
completedAt: ISODateTime | null;
durationMs: number | null;
errorMessage: string | null;
inputPayload: string | null;
outputPayload: string | null;
}
export interface ExecutionSummary {
id: UUID;
status: ExecutionStatus;
triggerType: TriggerType;
startedAt: ISODateTime;
durationMs: number | null;
}
// Marketplace
export type MarketplaceListingType = 'tool' | 'flow';
export interface MarketplaceListingSummary {
id: UUID;
authorName: string;
type: MarketplaceListingType;
name: string;
description: string;
category: string;
downloads: number;
rating: number | null;
}
// API Responses
export interface PaginatedResponse<T> {
items: T[];
total: number;
page: number;
pageSize: number;
hasMore: boolean;
}
export interface ApiError {
code: string;
message: string;
details?: Record<string, unknown>;
}
// Stats
export interface FlowStats {
flowId: UUID;
executionsTotal: number;
executionsSuccess: number;
executionsError: number;
avgDurationMs: number;
lastExecutedAt: ISODateTime | null;
}
export interface UsageStats {
userId: UUID;
period: 'day' | 'month';
flowCount: number;
executionCount: number;
executionLimit: number;
}
```
---
## API Endpoints
### Flows
- `GET /flows` — List user's flows (returns `FlowSummary[]`)
- `POST /flows` — Create flow
- `GET /flows/:id` — Get full flow
- `PATCH /flows/:id` — Update flow
- `DELETE /flows/:id` — Delete flow
- `POST /flows/:id/start` — Start flow (deploy container)
- `POST /flows/:id/stop` — Stop flow
### Triggers
- `GET /flows/:id/triggers` — List triggers
- `POST /flows/:id/triggers` — Create trigger
- `DELETE /triggers/:id` — Delete trigger
### Executions
- `GET /flows/:id/executions` — List runs (paginated)
- `GET /executions/:id` — Get run details
- `GET /executions/:id/logs` — Stream logs (WebSocket)
### Marketplace
- `GET /marketplace` — Browse listings
- `GET /marketplace/:id` — Get listing details
- `POST /marketplace/:id/install` — Install to user's library
### User
- `GET /me` — Current user info + usage stats
---
## Design Notes
1. **Dark mode default** — Developer audience prefers dark
2. **Keyboard shortcuts** — Cmd+S save, Cmd+Enter run, etc.
3. **Toast notifications** — For save/run/error feedback
4. **Loading states** — Skeleton loaders, not spinners
5. **Mobile:** Dashboard is responsive, flow editor is desktop-only (show message on mobile)
---
## Start With
1. Dashboard page with flow list
2. Flow editor with React Flow canvas
3. Basic YAML tab (Monaco, read-only first)
4. Run/Stop buttons that call API
Then iterate: node inspector panel, execution history, marketplace.

View file

@ -56,7 +56,9 @@ def cmd_serve(args: argparse.Namespace) -> int:
async def run_with_server(): async def run_with_server():
"""Bootstrap pump and run with server.""" """Bootstrap pump and run with server."""
import signal
from xml_pipeline.server import create_app from xml_pipeline.server import create_app
from xml_pipeline.server.restart import RestartOrchestrator
# Bootstrap the pump # Bootstrap the pump
pump = await bootstrap(str(config_path)) pump = await bootstrap(str(config_path))
@ -73,19 +75,51 @@ def cmd_serve(args: argparse.Namespace) -> int:
) )
server = uvicorn.Server(config) server = uvicorn.Server(config)
# Set up SIGHUP handler for graceful restart (Unix only)
restart_requested = asyncio.Event()
if hasattr(signal, "SIGHUP"):
loop = asyncio.get_event_loop()
loop.add_signal_handler(
signal.SIGHUP,
lambda: restart_requested.set(),
)
print("SIGHUP handler registered for graceful restart")
# Run pump and server concurrently # Run pump and server concurrently
pump_task = asyncio.create_task(pump.run()) pump_task = asyncio.create_task(pump.run())
async def restart_watcher():
"""Watch for restart signal and initiate graceful restart."""
await restart_requested.wait()
print("\nSIGHUP received — initiating graceful restart...")
orchestrator = RestartOrchestrator(pump)
result = await orchestrator.initiate_restart(
timeout=getattr(args, 'drain_timeout', 30.0),
)
if result.success:
print(f"Drain complete (drained={result.drained})")
if result.journal_stats:
print(f"Journal stats: {result.journal_stats}")
server.should_exit = True
restart_task = asyncio.create_task(restart_watcher())
try: try:
await server.serve() await server.serve()
finally: finally:
await pump.shutdown() await pump.shutdown()
pump_task.cancel() pump_task.cancel()
restart_task.cancel()
try: try:
await pump_task await pump_task
except asyncio.CancelledError: except asyncio.CancelledError:
pass pass
# If restart was requested, re-exec the process
if restart_requested.is_set():
RestartOrchestrator.exec_restart()
try: try:
print(f"Starting AgentServer on http://{args.host}:{args.port}") print(f"Starting AgentServer on http://{args.host}:{args.port}")
print(f" API docs: http://{args.host}:{args.port}/docs") print(f" API docs: http://{args.host}:{args.port}/docs")

View file

@ -76,6 +76,17 @@ from xml_pipeline.message_bus.budget_registry import (
reset_budget_registry, reset_budget_registry,
) )
from xml_pipeline.message_bus.dispatch_hook import (
DispatchHook,
NullDispatchHook,
)
from xml_pipeline.message_bus.journal import (
MessageJournal,
JournalEntry,
JournalEntryStatus,
)
__all__ = [ __all__ = [
# Pump # Pump
"StreamPump", "StreamPump",
@ -118,4 +129,11 @@ __all__ = [
"get_budget_registry", "get_budget_registry",
"configure_budget_registry", "configure_budget_registry",
"reset_budget_registry", "reset_budget_registry",
# Dispatch hooks
"DispatchHook",
"NullDispatchHook",
# Journal
"MessageJournal",
"JournalEntry",
"JournalEntryStatus",
] ]

View file

@ -0,0 +1,115 @@
"""
dispatch_hook.py Hook protocol for message dispatch lifecycle.
Defines a Protocol that consumers implement to observe dispatch events.
The pump calls hooks at key lifecycle points: intent, dispatched,
acknowledged, failed, and thread completion.
Multiple hooks can be registered. No hook registered = no overhead.
Example:
class MyAuditHook:
async def on_intent(self, thread_id, from_id, to_id,
payload_type, payload_bytes) -> str:
print(f"Intent: {from_id} -> {to_id}")
return str(uuid.uuid4())
async def on_acknowledged(self, entry_id):
print(f"Acked: {entry_id}")
# ... other methods
pump.register_dispatch_hook(MyAuditHook())
"""
from __future__ import annotations
from typing import Protocol, runtime_checkable
@runtime_checkable
class DispatchHook(Protocol):
"""
Hook into message dispatch lifecycle.
Implement this protocol for logging, journaling, auditing, or
any other dispatch observation. The pump calls these methods
at the corresponding lifecycle points.
Lifecycle:
1. on_intent Before handler invocation (message about to be dispatched)
2. on_dispatched Handler invocation has started
3. on_acknowledged Handler returned successfully
4. on_failed Handler raised an exception
5. on_thread_complete Thread was pruned or terminated
"""
async def on_intent(
self,
thread_id: str,
from_id: str,
to_id: str,
payload_type: str,
payload_bytes: bytes,
) -> str:
"""
Called before dispatch. Returns entry_id for correlation.
Args:
thread_id: Opaque thread UUID
from_id: Sender's registered name
to_id: Target listener name
payload_type: Payload class name
payload_bytes: Serialized payload bytes (for replay)
Returns:
A unique entry_id string for correlating subsequent callbacks.
"""
...
async def on_dispatched(self, entry_id: str) -> None:
"""Called when handler invocation begins."""
...
async def on_acknowledged(self, entry_id: str) -> None:
"""Called when handler returns successfully."""
...
async def on_failed(self, entry_id: str, error: str) -> None:
"""Called when handler raises an exception."""
...
async def on_thread_complete(self, thread_id: str) -> None:
"""Called when a thread is pruned or terminated."""
...
class NullDispatchHook:
"""
No-op default hook. Zero overhead when no journal is configured.
All methods are synchronous no-ops that satisfy the DispatchHook
protocol but do nothing.
"""
async def on_intent(
self,
thread_id: str,
from_id: str,
to_id: str,
payload_type: str,
payload_bytes: bytes,
) -> str:
return ""
async def on_dispatched(self, entry_id: str) -> None:
pass
async def on_acknowledged(self, entry_id: str) -> None:
pass
async def on_failed(self, entry_id: str, error: str) -> None:
pass
async def on_thread_complete(self, thread_id: str) -> None:
pass

View file

@ -0,0 +1,217 @@
"""
journal.py SQLite-backed certified-mail journal.
Implements the DispatchHook protocol with SQLite persistence.
Provides write-ahead logging for message dispatch, enabling
crash recovery via replay of unacknowledged entries.
Lifecycle:
1. on_intent INSERT journal entry [PENDING]
2. on_dispatched UPDATE status [DISPATCHED]
3. on_acknowledged UPDATE status [ACKED]
4. on_failed UPDATE status + error [FAILED]
5. on_thread_complete compact acked entries
6. startup scan DISPATCHED re-inject [recovery]
Example:
from xml_pipeline.message_bus.journal import MessageJournal
journal = MessageJournal(db_path="~/.xml-pipeline/journal.db")
await journal.initialize()
pump.register_dispatch_hook(journal)
# On restart, replay unacknowledged entries
entries = await journal.get_unacknowledged()
for entry in entries:
await pump.inject(entry["payload_bytes"], entry["thread_id"], entry["from_id"])
"""
from __future__ import annotations
import logging
import uuid
from dataclasses import dataclass
from datetime import datetime, timezone
from enum import Enum
from typing import Any, Dict, List, Optional
from xml_pipeline.message_bus.journal_store import JournalStore
logger = logging.getLogger(__name__)
class JournalEntryStatus(Enum):
"""Status of a journal entry through its lifecycle."""
PENDING = "pending"
DISPATCHED = "dispatched"
ACKNOWLEDGED = "acked"
FAILED = "failed"
@dataclass(frozen=True)
class JournalEntry:
"""Immutable snapshot of a journal entry."""
id: str
thread_id: str
from_id: str
to_id: str
payload_type: str
payload_bytes: bytes
status: JournalEntryStatus
created_at: str
dispatched_at: Optional[str] = None
acked_at: Optional[str] = None
retry_count: int = 0
error: Optional[str] = None
class MessageJournal:
"""
SQLite-backed certified-mail journal.
Implements DispatchHook to track message dispatch lifecycle.
Provides crash recovery via replay of unacknowledged entries.
"""
def __init__(
self,
db_path: Optional[str] = None,
*,
compact_after_hours: int = 24,
retry_after_seconds: float = 30.0,
max_retries: int = 3,
) -> None:
self._store = JournalStore(db_path)
self._compact_after_hours = compact_after_hours
self._retry_after_seconds = retry_after_seconds
self._max_retries = max_retries
async def initialize(self) -> None:
"""Initialize the underlying store."""
await self._store.initialize()
# ------------------------------------------------------------------
# DispatchHook implementation
# ------------------------------------------------------------------
async def on_intent(
self,
thread_id: str,
from_id: str,
to_id: str,
payload_type: str,
payload_bytes: bytes,
) -> str:
"""Record intent to dispatch. Returns entry_id for correlation."""
entry_id = str(uuid.uuid4())
now = datetime.now(timezone.utc).isoformat()
await self._store.insert(
entry_id=entry_id,
thread_id=thread_id,
from_id=from_id,
to_id=to_id,
payload_type=payload_type,
payload_bytes=payload_bytes,
status=JournalEntryStatus.PENDING.value,
created_at=now,
)
logger.debug(f"Journal: intent {entry_id[:8]}... {from_id}->{to_id}")
return entry_id
async def on_dispatched(self, entry_id: str) -> None:
"""Mark entry as dispatched (handler invocation started)."""
if not entry_id:
return
now = datetime.now(timezone.utc).isoformat()
await self._store.update_status(
entry_id,
JournalEntryStatus.DISPATCHED.value,
timestamp_field="dispatched_at",
timestamp_value=now,
)
logger.debug(f"Journal: dispatched {entry_id[:8]}...")
async def on_acknowledged(self, entry_id: str) -> None:
"""Mark entry as acknowledged (handler returned successfully)."""
if not entry_id:
return
now = datetime.now(timezone.utc).isoformat()
await self._store.update_status(
entry_id,
JournalEntryStatus.ACKNOWLEDGED.value,
timestamp_field="acked_at",
timestamp_value=now,
)
logger.debug(f"Journal: acked {entry_id[:8]}...")
async def on_failed(self, entry_id: str, error: str) -> None:
"""Mark entry as failed with error details."""
if not entry_id:
return
now = datetime.now(timezone.utc).isoformat()
await self._store.update_status(
entry_id,
JournalEntryStatus.FAILED.value,
error=error,
timestamp_value=now,
)
logger.warning(f"Journal: failed {entry_id[:8]}... — {error}")
async def on_thread_complete(self, thread_id: str) -> None:
"""Compact acknowledged entries for the completed thread."""
count = await self._store.compact_thread(thread_id)
if count:
logger.debug(
f"Journal: compacted {count} entries for thread {thread_id[:8]}..."
)
# ------------------------------------------------------------------
# Journal-specific methods (not part of DispatchHook protocol)
# ------------------------------------------------------------------
async def get_unacknowledged(
self,
older_than_seconds: Optional[float] = None,
) -> List[Dict[str, Any]]:
"""
Get entries that need replay (pending or dispatched but never acked).
Used for crash recovery on startup.
Args:
older_than_seconds: Override default retry delay
Returns:
List of entry dicts with payload_bytes for re-injection
"""
delay = older_than_seconds or self._retry_after_seconds
return await self._store.get_unacknowledged(
older_than_seconds=delay,
max_retries=self._max_retries,
)
async def compact_old(self, max_age_hours: Optional[int] = None) -> int:
"""
Remove old acknowledged entries.
Args:
max_age_hours: Override default compaction age
Returns:
Number of entries removed
"""
from datetime import timedelta
hours = max_age_hours or self._compact_after_hours
cutoff = (
datetime.now(timezone.utc) - timedelta(hours=hours)
).isoformat()
return await self._store.compact_old(cutoff)
async def get_stats(self) -> Dict[str, int]:
"""Get entry counts by status."""
return await self._store.get_stats()

View file

@ -0,0 +1,299 @@
"""
journal_store.py SQLite persistence layer for the message journal.
Provides async CRUD operations for journal entries using aiosqlite.
WAL mode is enabled for concurrent reads/writes.
This module is the storage backend for MessageJournal (journal.py).
"""
from __future__ import annotations
import logging
from pathlib import Path
from typing import Any, Dict, List, Optional
try:
import aiosqlite
HAS_AIOSQLITE = True
except ImportError:
HAS_AIOSQLITE = False
logger = logging.getLogger(__name__)
# Default database path
DEFAULT_JOURNAL_DB_PATH = Path.home() / ".xml-pipeline" / "journal.db"
# SQL schema
_CREATE_TABLE = """
CREATE TABLE IF NOT EXISTS journal_entries (
id TEXT PRIMARY KEY,
thread_id TEXT NOT NULL,
from_id TEXT NOT NULL,
to_id TEXT NOT NULL,
payload_type TEXT NOT NULL,
payload_bytes BLOB NOT NULL,
status TEXT NOT NULL DEFAULT 'pending',
created_at TEXT NOT NULL,
dispatched_at TEXT,
acked_at TEXT,
failed_at TEXT,
retry_count INTEGER NOT NULL DEFAULT 0,
error TEXT
)
"""
_CREATE_INDEXES = [
"CREATE INDEX IF NOT EXISTS idx_journal_status ON journal_entries(status)",
"CREATE INDEX IF NOT EXISTS idx_journal_thread ON journal_entries(thread_id)",
"CREATE INDEX IF NOT EXISTS idx_journal_created ON journal_entries(created_at)",
]
class JournalStore:
"""
Async SQLite persistence for journal entries.
Uses WAL mode for concurrent read/write access.
"""
def __init__(self, db_path: Optional[str] = None) -> None:
if not HAS_AIOSQLITE:
raise ImportError(
"aiosqlite is required for the message journal. "
"Install with: pip install aiosqlite"
)
self._db_path = Path(db_path) if db_path else DEFAULT_JOURNAL_DB_PATH
self._db_path.parent.mkdir(parents=True, exist_ok=True)
self._initialized = False
async def initialize(self) -> None:
"""Create tables and indexes if they don't exist."""
if self._initialized:
return
async with aiosqlite.connect(str(self._db_path)) as db:
# Enable WAL mode for concurrent access
await db.execute("PRAGMA journal_mode=WAL")
await db.execute(_CREATE_TABLE)
for idx_sql in _CREATE_INDEXES:
await db.execute(idx_sql)
await db.commit()
self._initialized = True
logger.info(f"JournalStore initialized: {self._db_path}")
async def insert(
self,
entry_id: str,
thread_id: str,
from_id: str,
to_id: str,
payload_type: str,
payload_bytes: bytes,
status: str,
created_at: str,
) -> None:
"""Insert a new journal entry."""
async with aiosqlite.connect(str(self._db_path)) as db:
await db.execute(
"""
INSERT INTO journal_entries
(id, thread_id, from_id, to_id, payload_type,
payload_bytes, status, created_at)
VALUES (?, ?, ?, ?, ?, ?, ?, ?)
""",
(entry_id, thread_id, from_id, to_id, payload_type,
payload_bytes, status, created_at),
)
await db.commit()
async def update_status(
self,
entry_id: str,
status: str,
*,
timestamp_field: Optional[str] = None,
timestamp_value: Optional[str] = None,
error: Optional[str] = None,
) -> None:
"""Update the status of a journal entry."""
async with aiosqlite.connect(str(self._db_path)) as db:
if timestamp_field and timestamp_value:
await db.execute(
f"""
UPDATE journal_entries
SET status = ?, {timestamp_field} = ?
WHERE id = ?
""",
(status, timestamp_value, entry_id),
)
elif error is not None:
await db.execute(
"""
UPDATE journal_entries
SET status = ?, error = ?, retry_count = retry_count + 1,
failed_at = ?
WHERE id = ?
""",
(status, error, timestamp_value or "", entry_id),
)
else:
await db.execute(
"UPDATE journal_entries SET status = ? WHERE id = ?",
(status, entry_id),
)
await db.commit()
async def get_by_status(
self,
status: str,
*,
older_than: Optional[str] = None,
limit: int = 100,
) -> List[Dict[str, Any]]:
"""
Get entries by status, optionally filtered by age.
Args:
status: Entry status to filter by
older_than: ISO timestamp - only return entries created before this
limit: Maximum entries to return
"""
async with aiosqlite.connect(str(self._db_path)) as db:
db.row_factory = aiosqlite.Row
if older_than:
cursor = await db.execute(
"""
SELECT * FROM journal_entries
WHERE status = ? AND created_at < ?
ORDER BY created_at ASC
LIMIT ?
""",
(status, older_than, limit),
)
else:
cursor = await db.execute(
"""
SELECT * FROM journal_entries
WHERE status = ?
ORDER BY created_at ASC
LIMIT ?
""",
(status, limit),
)
rows = await cursor.fetchall()
return [dict(row) for row in rows]
async def compact_thread(self, thread_id: str) -> int:
"""
Remove acknowledged entries for a completed thread.
Returns:
Number of entries removed
"""
async with aiosqlite.connect(str(self._db_path)) as db:
cursor = await db.execute(
"""
DELETE FROM journal_entries
WHERE thread_id = ? AND status = 'acked'
""",
(thread_id,),
)
count = cursor.rowcount
await db.commit()
if count:
logger.debug(f"Compacted {count} acked entries for thread {thread_id[:8]}...")
return count
async def compact_old(self, older_than: str) -> int:
"""
Remove old acknowledged entries regardless of thread.
Args:
older_than: ISO timestamp - remove acked entries older than this
Returns:
Number of entries removed
"""
async with aiosqlite.connect(str(self._db_path)) as db:
cursor = await db.execute(
"""
DELETE FROM journal_entries
WHERE status = 'acked' AND created_at < ?
""",
(older_than,),
)
count = cursor.rowcount
await db.commit()
if count:
logger.info(f"Compacted {count} old acked entries")
return count
async def get_stats(self) -> Dict[str, int]:
"""Get counts by status."""
async with aiosqlite.connect(str(self._db_path)) as db:
cursor = await db.execute(
"""
SELECT status, COUNT(*) as count
FROM journal_entries
GROUP BY status
"""
)
rows = await cursor.fetchall()
stats: Dict[str, int] = {
"pending": 0,
"dispatched": 0,
"acked": 0,
"failed": 0,
"total": 0,
}
for row in rows:
stats[row[0]] = row[1]
stats["total"] += row[1]
return stats
async def get_unacknowledged(
self,
*,
older_than_seconds: float = 30.0,
max_retries: int = 3,
) -> List[Dict[str, Any]]:
"""
Get entries that were dispatched but never acknowledged.
Used for crash recovery: these entries need to be replayed.
Args:
older_than_seconds: Only return entries older than this
max_retries: Only return entries with fewer retries than this
Returns:
List of entry dicts suitable for replay
"""
from datetime import datetime, timezone, timedelta
cutoff = (
datetime.now(timezone.utc) - timedelta(seconds=older_than_seconds)
).isoformat()
async with aiosqlite.connect(str(self._db_path)) as db:
db.row_factory = aiosqlite.Row
cursor = await db.execute(
"""
SELECT * FROM journal_entries
WHERE status IN ('pending', 'dispatched')
AND created_at < ?
AND retry_count < ?
ORDER BY created_at ASC
""",
(cutoff, max_retries),
)
rows = await cursor.fetchall()
return [dict(row) for row in rows]

View file

@ -45,6 +45,7 @@ from xml_pipeline.message_bus.message_state import MessageState, HandlerMetadata
from xml_pipeline.message_bus.thread_registry import get_registry from xml_pipeline.message_bus.thread_registry import get_registry
from xml_pipeline.message_bus.todo_registry import get_todo_registry from xml_pipeline.message_bus.todo_registry import get_todo_registry
from xml_pipeline.message_bus.budget_registry import get_budget_registry from xml_pipeline.message_bus.budget_registry import get_budget_registry
from xml_pipeline.message_bus.dispatch_hook import DispatchHook
from xml_pipeline.memory import get_context_buffer from xml_pipeline.memory import get_context_buffer
pump_logger = logging.getLogger(__name__) pump_logger = logging.getLogger(__name__)
@ -127,6 +128,9 @@ class ListenerConfig:
cpu_bound: bool = False # Dispatch to ProcessPoolExecutor if True cpu_bound: bool = False # Dispatch to ProcessPoolExecutor if True
payload_class: type = field(default=None, repr=False) payload_class: type = field(default=None, repr=False)
handler: Callable = field(default=None, repr=False) handler: Callable = field(default=None, repr=False)
# Output type for sequence factory validation
output_class_path: str = "" # Import path to output dataclass
output_class: type = field(default=None, repr=False)
@dataclass @dataclass
@ -173,6 +177,7 @@ class Listener:
schema: etree.XMLSchema = field(default=None, repr=False) schema: etree.XMLSchema = field(default=None, repr=False)
root_tag: str = "" root_tag: str = ""
usage_instructions: str = "" # Generated at registration for LLM agents usage_instructions: str = "" # Generated at registration for LLM agents
output_class: type = field(default=None, repr=False) # Output type for sequence validation
# ============================================================================ # ============================================================================
@ -301,6 +306,9 @@ class StreamPump:
# Event hooks for external observers (ServerState, etc.) # Event hooks for external observers (ServerState, etc.)
self._event_callbacks: List[EventCallback] = [] self._event_callbacks: List[EventCallback] = []
# Dispatch hooks for journaling/auditing (DispatchHook protocol)
self.dispatch_hooks: List[DispatchHook] = []
# Process pool for cpu_bound handlers # Process pool for cpu_bound handlers
self._process_pool: Optional[ProcessPoolExecutor] = None self._process_pool: Optional[ProcessPoolExecutor] = None
if config.process_pool_enabled: if config.process_pool_enabled:
@ -345,6 +353,24 @@ class StreamPump:
except Exception as e: except Exception as e:
pump_logger.warning(f"Event callback error: {e}") pump_logger.warning(f"Event callback error: {e}")
# ------------------------------------------------------------------
# Dispatch Hooks
# ------------------------------------------------------------------
def register_dispatch_hook(self, hook: DispatchHook) -> None:
"""
Register a dispatch lifecycle hook (journaling, auditing, etc.).
Hooks are called at key dispatch lifecycle points:
on_intent, on_dispatched, on_acknowledged, on_failed, on_thread_complete.
"""
self.dispatch_hooks.append(hook)
def unregister_dispatch_hook(self, hook: DispatchHook) -> None:
"""Remove a dispatch hook."""
if hook in self.dispatch_hooks:
self.dispatch_hooks.remove(hook)
# ------------------------------------------------------------------ # ------------------------------------------------------------------
# Registration # Registration
# ------------------------------------------------------------------ # ------------------------------------------------------------------
@ -364,6 +390,7 @@ class StreamPump:
handler_path=lc.handler_path, # For worker process import handler_path=lc.handler_path, # For worker process import
schema=self._generate_schema(lc.payload_class), schema=self._generate_schema(lc.payload_class),
root_tag=root_tag, root_tag=root_tag,
output_class=lc.output_class, # For sequence factory validation
) )
if lc.is_agent: if lc.is_agent:
@ -575,6 +602,7 @@ class StreamPump:
return return
for listener in state.target_listeners: for listener in state.target_listeners:
hook_entries: list[tuple[DispatchHook, str]] = []
try: try:
# Rate limiting for agents # Rate limiting for agents
semaphore = self.agent_semaphores.get(listener.name) semaphore = self.agent_semaphores.get(listener.name)
@ -670,6 +698,30 @@ class StreamPump:
payload=payload_ref, payload=payload_ref,
)) ))
# --- Dispatch hooks: on_intent + on_dispatched ---
hook_entries: list[tuple[DispatchHook, str]] = []
if self.dispatch_hooks:
payload_bytes_for_hook = b""
if state.raw_bytes:
payload_bytes_for_hook = state.raw_bytes
for hook in self.dispatch_hooks:
try:
eid = await hook.on_intent(
thread_id=current_thread,
from_id=state.from_id or "",
to_id=listener.name,
payload_type=type(payload_ref).__name__,
payload_bytes=payload_bytes_for_hook,
)
hook_entries.append((hook, eid))
except Exception as he:
pump_logger.warning(f"Dispatch hook on_intent error: {he}")
for hook, eid in hook_entries:
try:
await hook.on_dispatched(eid)
except Exception as he:
pump_logger.warning(f"Dispatch hook on_dispatched error: {he}")
# Dispatch to handler - either in-process or via ProcessPool # Dispatch to handler - either in-process or via ProcessPool
if listener.cpu_bound and self._process_pool and self._shared_backend: if listener.cpu_bound and self._process_pool and self._shared_backend:
response = await self._dispatch_to_process_pool( response = await self._dispatch_to_process_pool(
@ -682,6 +734,18 @@ class StreamPump:
# None means "no response needed" - don't re-inject # None means "no response needed" - don't re-inject
if response is None: if response is None:
# --- Dispatch hooks: on_acknowledged + on_thread_complete ---
for hook, eid in hook_entries:
try:
await hook.on_acknowledged(eid)
except Exception as he:
pump_logger.warning(f"Dispatch hook on_acknowledged error: {he}")
for hook in self.dispatch_hooks:
try:
await hook.on_thread_complete(current_thread)
except Exception as he:
pump_logger.warning(f"Dispatch hook on_thread_complete error: {he}")
# Thread terminates here - cleanup budget # Thread terminates here - cleanup budget
budget_registry = get_budget_registry() budget_registry = get_budget_registry()
final_budget = budget_registry.cleanup_thread(current_thread) final_budget = budget_registry.cleanup_thread(current_thread)
@ -708,6 +772,18 @@ class StreamPump:
target, new_thread_id = registry.prune_for_response(current_thread) target, new_thread_id = registry.prune_for_response(current_thread)
if target is None: if target is None:
# Chain exhausted - nowhere to respond to # Chain exhausted - nowhere to respond to
# --- Dispatch hooks: on_acknowledged + on_thread_complete ---
for hook, eid in hook_entries:
try:
await hook.on_acknowledged(eid)
except Exception as he:
pump_logger.warning(f"Dispatch hook on_acknowledged error: {he}")
for hook in self.dispatch_hooks:
try:
await hook.on_thread_complete(current_thread)
except Exception as he:
pump_logger.warning(f"Dispatch hook on_thread_complete error: {he}")
# Cleanup thread budget # Cleanup thread budget
budget_registry = get_budget_registry() budget_registry = get_budget_registry()
final_budget = budget_registry.cleanup_thread(current_thread) final_budget = budget_registry.cleanup_thread(current_thread)
@ -790,6 +866,13 @@ class StreamPump:
payload=response.payload, payload=response.payload,
)) ))
# --- Dispatch hooks: on_acknowledged ---
for hook, eid in hook_entries:
try:
await hook.on_acknowledged(eid)
except Exception as he:
pump_logger.warning(f"Dispatch hook on_acknowledged error: {he}")
# Emit agent state back to idle # Emit agent state back to idle
self._emit_event(AgentStateEvent( self._emit_event(AgentStateEvent(
agent_name=listener.name, agent_name=listener.name,
@ -809,6 +892,13 @@ class StreamPump:
semaphore.release() semaphore.release()
except Exception as exc: except Exception as exc:
# --- Dispatch hooks: on_failed ---
for hook, eid in hook_entries:
try:
await hook.on_failed(eid, str(exc))
except Exception as he:
pump_logger.warning(f"Dispatch hook on_failed error: {he}")
# Emit error state # Emit error state
self._emit_event(AgentStateEvent( self._emit_event(AgentStateEvent(
agent_name=listener.name, agent_name=listener.name,
@ -1321,6 +1411,7 @@ class ConfigLoader:
broadcast=raw.get("broadcast", False), broadcast=raw.get("broadcast", False),
prompt=raw.get("prompt", ""), prompt=raw.get("prompt", ""),
cpu_bound=raw.get("cpu_bound", False), cpu_bound=raw.get("cpu_bound", False),
output_class_path=raw.get("output_class", ""),
) )
@classmethod @classmethod
@ -1331,6 +1422,11 @@ class ConfigLoader:
mod, fn_name = lc.handler_path.rsplit(".", 1) mod, fn_name = lc.handler_path.rsplit(".", 1)
lc.handler = getattr(importlib.import_module(mod), fn_name) lc.handler = getattr(importlib.import_module(mod), fn_name)
# Load output class if specified (for sequence factory validation)
if lc.output_class_path:
mod, cls_name = lc.output_class_path.rsplit(".", 1)
lc.output_class = getattr(importlib.import_module(mod), cls_name)
# ============================================================================ # ============================================================================
# Bootstrap # Bootstrap
@ -1407,6 +1503,21 @@ async def bootstrap(config_path: str = "config/organism.yaml") -> StreamPump:
) )
pump.register_listener(sequence_config) pump.register_listener(sequence_config)
# Register Sequence Factory (validates sequences before execution)
from xml_pipeline.sequence import (
SequenceRequest, handle_sequence_request,
)
sequence_factory_config = ListenerConfig(
name="system.sequence.factory",
payload_class_path="xml_pipeline.sequence.primitives.SequenceRequest",
handler_path="xml_pipeline.sequence.handler.handle_sequence_request",
description="Validates and builds sequences - agents request here first",
is_agent=False,
payload_class=SequenceRequest,
handler=handle_sequence_request,
)
pump.register_listener(sequence_factory_config)
# Register Buffer primitives (fan-out orchestration) # Register Buffer primitives (fan-out orchestration)
from xml_pipeline.primitives.buffer import ( from xml_pipeline.primitives.buffer import (
BufferStart, handle_buffer_start, BufferStart, handle_buffer_start,

View file

@ -564,6 +564,75 @@ def create_router(state: "ServerState") -> APIRouter:
count=len(days), count=len(days),
) )
# =========================================================================
# Journal Endpoints
# =========================================================================
@router.get("/journal/stats")
async def get_journal_stats() -> dict:
"""
Get journal entry counts by status.
Returns counts of pending, dispatched, acknowledged, and failed entries.
"""
pump = state.pump
for hook in pump.dispatch_hooks:
from xml_pipeline.message_bus.journal import MessageJournal
if isinstance(hook, MessageJournal):
stats = await hook.get_stats()
return {"enabled": True, **stats}
return {"enabled": False, "message": "No journal configured"}
@router.get("/journal/unacknowledged")
async def get_journal_unacknowledged() -> dict:
"""
Get entries that were dispatched but never acknowledged.
These entries may need replay on restart.
"""
pump = state.pump
for hook in pump.dispatch_hooks:
from xml_pipeline.message_bus.journal import MessageJournal
if isinstance(hook, MessageJournal):
entries = await hook.get_unacknowledged(older_than_seconds=0)
return {
"entries": [
{
"id": e["id"],
"thread_id": e["thread_id"],
"from_id": e["from_id"],
"to_id": e["to_id"],
"payload_type": e["payload_type"],
"status": e["status"],
"created_at": e["created_at"],
"retry_count": e["retry_count"],
}
for e in entries
],
"count": len(entries),
}
return {"enabled": False, "message": "No journal configured"}
@router.post("/journal/compact")
async def compact_journal(
max_age_hours: int = Query(24, ge=1, le=720),
) -> dict:
"""
Trigger compaction of old acknowledged journal entries.
Removes acked entries older than max_age_hours.
"""
pump = state.pump
for hook in pump.dispatch_hooks:
from xml_pipeline.message_bus.journal import MessageJournal
if isinstance(hook, MessageJournal):
removed = await hook.compact_old(max_age_hours=max_age_hours)
return {"compacted": removed, "max_age_hours": max_age_hours}
return {"enabled": False, "message": "No journal configured"}
# ========================================================================= # =========================================================================
# Control Endpoints # Control Endpoints
# ========================================================================= # =========================================================================
@ -642,6 +711,44 @@ def create_router(state: "ServerState") -> APIRouter:
) )
return result return result
@router.post("/organism/restart")
async def restart_organism(
drain_timeout: float = Query(30.0, ge=1.0, le=300.0),
) -> dict:
"""
Initiate a graceful restart.
Drains the message queue, collects journal stats, and
re-execs the process. The journal replays unacknowledged
entries on boot.
"""
from xml_pipeline.server.restart import RestartOrchestrator
pump = state.pump
orchestrator = RestartOrchestrator(pump)
result = await orchestrator.initiate_restart(timeout=drain_timeout)
if not result.success:
raise HTTPException(
status_code=409,
detail=result.error or "Restart failed",
)
# Schedule the actual re-exec after response is sent
import asyncio
async def _deferred_restart():
await asyncio.sleep(0.5) # Let the response flush
RestartOrchestrator.exec_restart()
asyncio.create_task(_deferred_restart())
return {
"success": True,
"drained": result.drained,
"journal_stats": result.journal_stats,
}
@router.post("/organism/stop") @router.post("/organism/stop")
async def stop_organism() -> dict: async def stop_organism() -> dict:
"""Graceful shutdown.""" """Graceful shutdown."""

View file

@ -45,9 +45,30 @@ def create_app(
@asynccontextmanager @asynccontextmanager
async def lifespan(app: FastAPI) -> AsyncGenerator[None, None]: async def lifespan(app: FastAPI) -> AsyncGenerator[None, None]:
"""Manage app lifecycle - startup and shutdown.""" """Manage app lifecycle - startup and shutdown with journal recovery."""
# Startup # Startup
state.set_running() state.set_running()
# Journal recovery: replay unacknowledged entries from previous run
for hook in pump.dispatch_hooks:
from xml_pipeline.message_bus.journal import MessageJournal
if isinstance(hook, MessageJournal):
entries = await hook.get_unacknowledged(older_than_seconds=0)
if entries:
import logging
logger = logging.getLogger(__name__)
logger.info(
f"Journal recovery: replaying {len(entries)} unacknowledged entries"
)
for entry in entries:
await pump.inject(
entry["payload_bytes"],
thread_id=entry["thread_id"],
from_id=entry["from_id"],
)
logger.info("Journal recovery complete")
break
yield yield
# Shutdown # Shutdown
state.set_stopping() state.set_stopping()

View file

@ -0,0 +1,137 @@
"""
restart.py Graceful restart orchestrator for AgentServer.
Handles the restart protocol:
1. SIGNAL SIGHUP or POST /organism/restart
2. DRAIN pump._running = False; wait for queue to drain
3. PERSIST Journal already has all in-flight state
4. STOP Shutdown pump, server, process pool
5. EXEC os.execv() (Unix) or subprocess (Windows)
6. BOOT bootstrap() runs, journal replays unacknowledged
7. VERIFY Compare journal stats pre/post restart
The journal (W2) provides the safety net: unacknowledged entries are
replayed on boot, ensuring no messages are lost during restart.
"""
from __future__ import annotations
import asyncio
import logging
import os
import subprocess
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, Optional, TYPE_CHECKING
if TYPE_CHECKING:
from xml_pipeline.message_bus.stream_pump import StreamPump
logger = logging.getLogger(__name__)
@dataclass
class RestartResult:
"""Result of a restart drain operation."""
success: bool
drained: bool
journal_stats: Dict[str, Any] = field(default_factory=dict)
error: Optional[str] = None
class RestartOrchestrator:
"""
Orchestrates graceful restart of the organism.
The restart protocol:
1. Drain the message queue (stop accepting new messages)
2. Wait for in-flight handlers to complete (with timeout)
3. Collect journal stats for post-restart verification
4. Re-exec the process (or signal the caller to do so)
"""
def __init__(self, pump: "StreamPump") -> None:
self._pump = pump
self._restarting = False
@property
def is_restarting(self) -> bool:
return self._restarting
async def initiate_restart(self, timeout: float = 30.0) -> RestartResult:
"""
Drain the pump and prepare for restart.
Args:
timeout: Maximum seconds to wait for drain
Returns:
RestartResult with drain status and journal stats
"""
if self._restarting:
return RestartResult(
success=False,
drained=False,
error="Restart already in progress",
)
self._restarting = True
logger.info("Restart initiated — draining message queue...")
# Collect pre-restart journal stats
journal_stats: Dict[str, Any] = {}
for hook in self._pump.dispatch_hooks:
from xml_pipeline.message_bus.journal import MessageJournal
if isinstance(hook, MessageJournal):
journal_stats = await hook.get_stats()
break
# Stop accepting new messages
self._pump._running = False
# Wait for queue to drain with timeout
drained = False
try:
await asyncio.wait_for(
self._pump.queue.join(),
timeout=timeout,
)
drained = True
logger.info("Message queue drained successfully")
except asyncio.TimeoutError:
logger.warning(
f"Queue drain timed out after {timeout}s — "
f"{self._pump.queue.qsize()} messages remaining"
)
# Shutdown process pool if active
if self._pump._process_pool:
self._pump._process_pool.shutdown(wait=True)
logger.info("ProcessPool shutdown complete")
return RestartResult(
success=True,
drained=drained,
journal_stats=journal_stats,
)
@staticmethod
def exec_restart() -> None:
"""
Re-exec the current process.
On Unix, uses os.execv() for in-place replacement.
On Windows, starts a new process and exits.
"""
python = sys.executable
args = sys.argv[:]
logger.info(f"Re-executing: {python} {' '.join(args)}")
if sys.platform == "win32":
# Windows: start new process and exit
subprocess.Popen([python] + args)
sys.exit(0)
else:
# Unix: in-place replacement
os.execv(python, [python] + args)