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This commit refactors the Batches protocol to use Pydantic request models for both create_batch and list_batches methods, improving consistency, readability, and maintainability. - create_batch now accepts a single CreateBatchRequest parameter instead of individual arguments. This aligns the protocol with FastAPI’s request model pattern, allowing the router to pass the request object directly without unpacking parameters. Provider implementations now access fields via request.input_file_id, request.endpoint, etc. - list_batches now accepts a single ListBatchesRequest parameter, replacing individual query parameters. The model includes after and limit fields with proper OpenAPI descriptions. FastAPI automatically parses query parameters into the model for GET requests, keeping router code clean. Provider implementations access fields via request.after and request.limit. Signed-off-by: Sébastien Han <seb@redhat.com> |
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|---|---|---|
| .. | ||
| batches | ||
| common | ||
| __init__.py | ||
| agents.py | ||
| benchmarks.py | ||
| conversations.py | ||
| datasetio.py | ||
| datasets.py | ||
| datatypes.py | ||
| eval.py | ||
| files.py | ||
| inference.py | ||
| inspect.py | ||
| models.py | ||
| openai_responses.py | ||
| post_training.py | ||
| prompts.py | ||
| providers.py | ||
| py.typed | ||
| pyproject.toml | ||
| rag_tool.py | ||
| README.md | ||
| resource.py | ||
| router_utils.py | ||
| safety.py | ||
| schema_utils.py | ||
| scoring.py | ||
| scoring_functions.py | ||
| shields.py | ||
| tools.py | ||
| uv.lock | ||
| vector_io.py | ||
| vector_stores.py | ||
| version.py | ||
llama-stack-api
API and Provider specifications for Llama Stack - a lightweight package with protocol definitions and provider specs.
Overview
llama-stack-api is a minimal dependency package that contains:
- API Protocol Definitions: Type-safe protocol definitions for all Llama Stack APIs (inference, agents, safety, etc.)
- Provider Specifications: Provider spec definitions for building custom providers
- Data Types: Shared data types and models used across the Llama Stack ecosystem
- Type Utilities: Strong typing utilities and schema validation
What This Package Does NOT Include
- Server implementation (see
llama-stackpackage) - Provider implementations (see
llama-stackpackage) - CLI tools (see
llama-stackpackage) - Runtime orchestration (see
llama-stackpackage)
Use Cases
This package is designed for:
- Third-party Provider Developers: Build custom providers without depending on the full Llama Stack server
- Client Library Authors: Use type definitions without server dependencies
- Documentation Generation: Generate API docs from protocol definitions
- Type Checking: Validate implementations against the official specs
Installation
pip install llama-stack-api
Or with uv:
uv pip install llama-stack-api
Dependencies
Minimal dependencies:
pydantic>=2.11.9- For data validation and serializationjsonschema- For JSON schema utilities
Versioning
This package follows semantic versioning independently from the main llama-stack package:
- Patch versions (0.1.x): Documentation, internal improvements
- Minor versions (0.x.0): New APIs, backward-compatible changes
- Major versions (x.0.0): Breaking changes to existing APIs
Current version: 0.4.0.dev0
Usage Example
from llama_stack_api.inference import Inference, ChatCompletionRequest
from llama_stack_api.providers.datatypes import ProviderSpec, InlineProviderSpec
from llama_stack_api.datatypes import Api
# Use protocol definitions for type checking
class MyInferenceProvider(Inference):
async def chat_completion(self, request: ChatCompletionRequest):
# Your implementation
pass
# Define provider specifications
my_provider_spec = InlineProviderSpec(
api=Api.inference,
provider_type="inline::my-provider",
pip_packages=["my-dependencies"],
module="my_package.providers.inference",
config_class="my_package.providers.inference.MyConfig",
)
Relationship to llama-stack
The main llama-stack package depends on llama-stack-api and provides:
- Full server implementation
- Built-in provider implementations
- CLI tools for running and managing stacks
- Runtime provider resolution and orchestration
Contributing
See the main Llama Stack repository for contribution guidelines.
License
MIT License - see LICENSE file for details.