# Development Configuration

Source: https://langbot.app/docs/en/develop/dev-config

LangBot is divided into frontend and backend. The frontend is developed using Vite + React Router + shadcn, and the backend is developed using Quart (an asynchronous version of Flask).

## Backend

The code is located in the `pkg` directory and is started by the `main.py` file in the root directory.

Install dependencies, we use uv to manage dependencies.

```bash
pip install uv
uv sync --dev
```

Start the backend

```bash
uv run main.py
```

At this point, the configuration file will be automatically generated in the `data/config.yaml` file.

## Frontend

The code is located in the `web` directory and requires Node.js and [pnpm](https://pnpm.io/installation).

Copy `.env.example` to `.env` and fill in the values.

- Usage in Linux and other environments

```bash
cp .env.example .env
```

- Usage in Windows environments

```bash
copy .env.example .env
```

Install dependencies and start the frontend

```bash
pnpm install
pnpm dev

# If pnpm is not installed, you can also use npm to solve dependencies and start
npm install
npm run dev
```

Then according to the output information, visit `http://127.0.0.1:3000` to view the standalone frontend page.

> When using \`pnpm dev\` to start locally, the environment variable \`VITE\_API\_BASE\_URL\` will be automatically used by the frontend to ensure that the frontend can access the \`5300\` port of the locally running backend.:
>
> In production environments, the frontend will be precompiled into static files and provided by the backend, and the frontend will automatically access the backend address on the same domain.

## Code Formatting

The repository contains lint and format check workflows, and your code will be automatically checked when you push it. Please configure pre-commit to check your code locally before submitting.

```bash
uv run pre-commit install
```

## API Documentation

We will write API documentation in APIFox before developing each interface. Please refer to [API Documentation(Chinese)](https://ok52vhsenr.apifox.cn/).

## Database Migrations

LangBot uses [Alembic](https://alembic.sqlalchemy.org/) to manage database migrations, supporting both SQLite and PostgreSQL seamlessly without database-specific branching.

### Migration File Location

```
src/langbot/pkg/persistence/alembic/versions/
```

### Creating a New Migration

The recommended way is to use **autogenerate**, which compares ORM models against the database schema and generates a migration script:

```bash
# Run from the project root (requires data/config.yaml)
uv run python -m langbot.pkg.persistence.alembic_runner autogenerate "describe your changes"
```

The generated file will appear in `src/langbot/pkg/persistence/alembic/versions/`. Review and edit the generated script to confirm the changes are correct before committing.

> info:
>
> Autogenerate can automatically detect column additions/removals, table changes, type changes, etc. However, for **data migrations** (e.g., modifying JSON field content), you need to manually add code to the generated script.

You can also create migration files manually, following the naming convention `NNNN_description.py`:

```python
"""Describe your migration

Revision ID: 0003_add_bot_description
Revises: 0002_sample
Create Date: 2026-04-08
"""
from alembic import op
import sqlalchemy as sa

revision = '0003_add_bot_description'
down_revision = '0002_sample'  # Points to the previous migration's revision
branch_labels = None
depends_on = None


def upgrade() -> None:
    # Schema change (works on both SQLite and PostgreSQL)
    op.add_column('bots', sa.Column('description', sa.String(512), server_default=''))


def downgrade() -> None:
    op.drop_column('bots', 'description')
```

### Migration Patterns

**Schema Changes (add/drop columns, create tables)**

```python
def upgrade() -> None:
    # Add a column
    op.add_column('table_name', sa.Column('new_col', sa.String(255), server_default=''))
    
    # Create a new table
    op.create_table(
        'new_table',
        sa.Column('id', sa.Integer, primary_key=True, autoincrement=True),
        sa.Column('name', sa.String(255), nullable=False),
    )
```

> info:
>
> `env.py` sets `render_as_batch=True`, which makes Alembic automatically handle SQLite's ALTER TABLE limitations (via temporary table rebuild). No need to branch on database type.

**Data Migrations (read and modify data)**

```python
import json

def upgrade() -> None:
    conn = op.get_bind()
    rows = conn.execute(sa.text("SELECT uuid, config FROM pipelines")).fetchall()
    for row in rows:
        config = json.loads(row[1]) if isinstance(row[1], str) else row[1]
        config.setdefault('ai', {})['new_key'] = 'default_value'
        conn.execute(
            sa.text("UPDATE pipelines SET config = :cfg WHERE uuid = :uuid"),
            {"cfg": json.dumps(config), "uuid": row[0]}
        )
```

### How It Works

Migrations run automatically when LangBot starts — no manual commands needed:

1. On first startup, the baseline version is automatically stamped (marking the existing database)
2. On subsequent startups, all pending migrations are applied (`alembic upgrade head`)

### CI Testing

The repository includes a `test-migrations.yml` workflow that automatically tests migration scripts on both SQLite and PostgreSQL when `persistence/` related files change.

### CLI Tool

```bash
# Autogenerate migration (compare ORM models against DB)
uv run python -m langbot.pkg.persistence.alembic_runner autogenerate "description"

# Upgrade database
uv run python -m langbot.pkg.persistence.alembic_runner upgrade

# Show current revision
uv run python -m langbot.pkg.persistence.alembic_runner current

# Stamp revision (without running migrations)
uv run python -m langbot.pkg.persistence.alembic_runner stamp head
```