llama-stack-mirror/docs/docs/concepts/apis/external.mdx
Charlie Doern 840ad75fe9
feat: split API and provider specs into separate llama-stack-api pkg (#3895)
# What does this PR do?

Extract API definitions and provider specifications into a standalone
llama-stack-api package that can be published to PyPI independently of
the main llama-stack server.


see: https://github.com/llamastack/llama-stack/pull/2978 and
https://github.com/llamastack/llama-stack/pull/2978#issuecomment-3145115942

Motivation

External providers currently import from llama-stack, which overrides
the installed version and causes dependency conflicts. This separation
allows external providers to:

- Install only the type definitions they need without server
dependencies
- Avoid version conflicts with the installed llama-stack package
- Be versioned and released independently

This enables us to re-enable external provider module tests that were
previously blocked by these import conflicts.

Changes

- Created llama-stack-api package with minimal dependencies (pydantic,
jsonschema)
- Moved APIs, providers datatypes, strong_typing, and schema_utils
- Updated all imports from llama_stack.* to llama_stack_api.*
- Configured local editable install for development workflow
- Updated linting and type-checking configuration for both packages

Next Steps

- Publish llama-stack-api to PyPI
- Update external provider dependencies
- Re-enable external provider module tests


Pre-cursor PRs to this one:

- #4093 
- #3954 
- #4064 

These PRs moved key pieces _out_ of the Api pkg, limiting the scope of
change here.


relates to #3237 

## Test Plan

Package builds successfully and can be imported independently. All
pre-commit hooks pass with expected exclusions maintained.

---------

Signed-off-by: Charlie Doern <cdoern@redhat.com>
2025-11-13 11:51:17 -08:00

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8.9 KiB
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---
title: External APIs
description: Understanding external APIs in Llama Stack
sidebar_label: External APIs
sidebar_position: 3
---
# External APIs
Llama Stack supports external APIs that live outside of the main codebase. This allows you to:
- Create and maintain your own APIs independently
- Share APIs with others without contributing to the main codebase
- Keep API-specific code separate from the core Llama Stack code
## Configuration
To enable external APIs, you need to configure the `external_apis_dir` in your Llama Stack configuration. This directory should contain your external API specifications:
```yaml
external_apis_dir: ~/.llama/apis.d/
```
## Directory Structure
The external APIs directory should follow this structure:
```
apis.d/
custom_api1.yaml
custom_api2.yaml
```
Each YAML file in these directories defines an API specification.
## API Specification
Here's an example of an external API specification for a weather API:
```yaml
module: weather
api_dependencies:
- inference
protocol: WeatherAPI
name: weather
pip_packages:
- llama-stack-api-weather
```
### API Specification Fields
- `module`: Python module containing the API implementation
- `protocol`: Name of the protocol class for the API
- `name`: Name of the API
- `pip_packages`: List of pip packages to install the API, typically a single package
## Required Implementation
External APIs must expose a `available_providers()` function in their module that returns a list of provider names:
```python
# llama_stack_api_weather/api.py
from llama_stack_api import Api, InlineProviderSpec, ProviderSpec
def available_providers() -> list[ProviderSpec]:
return [
InlineProviderSpec(
api=Api.weather,
provider_type="inline::darksky",
pip_packages=[],
module="llama_stack_provider_darksky",
config_class="llama_stack_provider_darksky.DarkSkyWeatherImplConfig",
),
]
```
A Protocol class like so:
```python
# llama_stack_api_weather/api.py
from typing import Protocol
from llama_stack_api import webmethod
class WeatherAPI(Protocol):
"""
A protocol for the Weather API.
"""
@webmethod(route="/locations", method="GET")
async def get_available_locations() -> dict[str, list[str]]:
"""
Get the available locations.
"""
...
```
## Example: Custom API
Here's a complete example of creating and using a custom API:
1. First, create the API package:
```bash
mkdir -p llama-stack-api-weather
cd llama-stack-api-weather
mkdir src/llama_stack_api_weather
git init
uv init
```
2. Edit `pyproject.toml`:
```toml
[project]
name = "llama-stack-api-weather"
version = "0.1.0"
description = "Weather API for Llama Stack"
readme = "README.md"
requires-python = ">=3.12"
dependencies = ["llama-stack", "pydantic"]
[build-system]
requires = ["setuptools"]
build-backend = "setuptools.build_meta"
[tool.setuptools.packages.find]
where = ["src"]
include = ["llama_stack_api_weather", "llama_stack_api_weather.*"]
```
3. Create the initial files:
```bash
touch src/llama_stack_api_weather/__init__.py
touch src/llama_stack_api_weather/api.py
```
```python
# llama-stack-api-weather/src/llama_stack_api_weather/__init__.py
"""Weather API for Llama Stack."""
from .api import WeatherAPI, available_providers
__all__ = ["WeatherAPI", "available_providers"]
```
4. Create the API implementation:
```python
# llama-stack-api-weather/src/llama_stack_api_weather/weather.py
from typing import Protocol
from llama_stack_api import (
Api,
ProviderSpec,
RemoteProviderSpec,
webmethod,
)
def available_providers() -> list[ProviderSpec]:
return [
RemoteProviderSpec(
api=Api.weather,
provider_type="remote::kaze",
config_class="llama_stack_provider_kaze.KazeProviderConfig",
adapter_type="kaze",
module="llama_stack_provider_kaze",
pip_packages=["llama_stack_provider_kaze"],
config_class="llama_stack_provider_kaze.KazeProviderConfig",
),
]
class WeatherProvider(Protocol):
"""
A protocol for the Weather API.
"""
@webmethod(route="/weather/locations", method="GET")
async def get_available_locations() -> dict[str, list[str]]:
"""
Get the available locations.
"""
...
```
5. Create the API specification:
```yaml
# ~/.llama/apis.d/weather.yaml
module: llama_stack_api_weather
name: weather
pip_packages: ["llama-stack-api-weather"]
protocol: WeatherProvider
```
6. Install the API package:
```bash
uv pip install -e .
```
7. Configure Llama Stack to use external APIs:
```yaml
version: "2"
image_name: "llama-stack-api-weather"
apis:
- weather
providers: {}
external_apis_dir: ~/.llama/apis.d
```
The API will now be available at `/v1/weather/locations`.
## Example: custom provider for the weather API
1. Create the provider package:
```bash
mkdir -p llama-stack-provider-kaze
cd llama-stack-provider-kaze
uv init
```
2. Edit `pyproject.toml`:
```toml
[project]
name = "llama-stack-provider-kaze"
version = "0.1.0"
description = "Kaze weather provider for Llama Stack"
readme = "README.md"
requires-python = ">=3.12"
dependencies = ["llama-stack", "pydantic", "aiohttp"]
[build-system]
requires = ["setuptools"]
build-backend = "setuptools.build_meta"
[tool.setuptools.packages.find]
where = ["src"]
include = ["llama_stack_provider_kaze", "llama_stack_provider_kaze.*"]
```
3. Create the initial files:
```bash
touch src/llama_stack_provider_kaze/__init__.py
touch src/llama_stack_provider_kaze/kaze.py
```
4. Create the provider implementation:
Initialization function:
```python
# llama-stack-provider-kaze/src/llama_stack_provider_kaze/__init__.py
"""Kaze weather provider for Llama Stack."""
from .config import KazeProviderConfig
from .kaze import WeatherKazeAdapter
__all__ = ["KazeProviderConfig", "WeatherKazeAdapter"]
async def get_adapter_impl(config: KazeProviderConfig, _deps):
from .kaze import WeatherKazeAdapter
impl = WeatherKazeAdapter(config)
await impl.initialize()
return impl
```
Configuration:
```python
# llama-stack-provider-kaze/src/llama_stack_provider_kaze/config.py
from pydantic import BaseModel, Field
class KazeProviderConfig(BaseModel):
"""Configuration for the Kaze weather provider."""
base_url: str = Field(
"https://api.kaze.io/v1",
description="Base URL for the Kaze weather API",
)
```
Main implementation:
```python
# llama-stack-provider-kaze/src/llama_stack_provider_kaze/kaze.py
from llama_stack_api_weather.api import WeatherProvider
from .config import KazeProviderConfig
class WeatherKazeAdapter(WeatherProvider):
"""Kaze weather provider implementation."""
def __init__(
self,
config: KazeProviderConfig,
) -> None:
self.config = config
async def initialize(self) -> None:
pass
async def get_available_locations(self) -> dict[str, list[str]]:
"""Get available weather locations."""
return {"locations": ["Paris", "Tokyo"]}
```
5. Create the provider specification:
```yaml
# ~/.llama/providers.d/remote/weather/kaze.yaml
adapter_type: kaze
pip_packages: ["llama_stack_provider_kaze"]
config_class: llama_stack_provider_kaze.config.KazeProviderConfig
module: llama_stack_provider_kaze
optional_api_dependencies: []
```
6. Install the provider package:
```bash
uv pip install -e .
```
7. Configure Llama Stack to use the provider:
```yaml
# ~/.llama/run-byoa.yaml
version: "2"
image_name: "llama-stack-api-weather"
apis:
- weather
providers:
weather:
- provider_id: kaze
provider_type: remote::kaze
config: {}
external_apis_dir: ~/.llama/apis.d
external_providers_dir: ~/.llama/providers.d
server:
port: 8321
```
8. Run the server:
```bash
llama stack run ~/.llama/run-byoa.yaml
```
9. Test the API:
```bash
curl -sSf http://127.0.0.1:8321/v1/weather/locations
{"locations":["Paris","Tokyo"]}%
```
## Best Practices
1. **Package Naming**: Use a clear and descriptive name for your API package.
2. **Version Management**: Keep your API package versioned and compatible with the Llama Stack version you're using.
3. **Dependencies**: Only include the minimum required dependencies in your API package.
4. **Documentation**: Include clear documentation in your API package about:
- Installation requirements
- Configuration options
- API endpoints and usage
- Any limitations or known issues
5. **Testing**: Include tests in your API package to ensure it works correctly with Llama Stack.
## Troubleshooting
If your external API isn't being loaded:
1. Check that the `external_apis_dir` path is correct and accessible.
2. Verify that the YAML files are properly formatted.
3. Ensure all required Python packages are installed.
4. Check the Llama Stack server logs for any error messages - turn on debug logging to get more information using `LLAMA_STACK_LOGGING=all=debug`.
5. Verify that the API package is installed in your Python environment.