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feat: add batches API with OpenAI compatibility (#3088)
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Add complete batches API implementation with protocol, providers, and tests: Core Infrastructure: - Add batches API protocol using OpenAI Batch types directly - Add Api.batches enum value and protocol mapping in resolver - Add OpenAI "batch" file purpose support - Include proper error handling (ConflictError, ResourceNotFoundError) Reference Provider: - Add ReferenceBatchesImpl with full CRUD operations (create, retrieve, cancel, list) - Implement background batch processing with configurable concurrency - Add SQLite KVStore backend for persistence - Support /v1/chat/completions endpoint with request validation Comprehensive Test Suite: - Add unit tests for provider implementation with validation - Add integration tests for end-to-end batch processing workflows - Add error handling tests for validation, malformed inputs, and edge cases Configuration: - Add max_concurrent_batches and max_concurrent_requests_per_batch options - Add provider documentation with sample configurations Test with - ``` $ uv run llama stack build --image-type venv --providers inference=YOU_PICK,files=inline::localfs,batches=inline::reference --run & $ LLAMA_STACK_CONFIG=http://localhost:8321 uv run pytest tests/unit/providers/batches tests/integration/batches --text-model YOU_PICK ``` addresses #3066
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26 changed files with 2707 additions and 2 deletions
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@ -8,6 +8,7 @@ import inspect
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from typing import Any
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from llama_stack.apis.agents import Agents
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from llama_stack.apis.batches import Batches
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from llama_stack.apis.benchmarks import Benchmarks
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from llama_stack.apis.datasetio import DatasetIO
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from llama_stack.apis.datasets import Datasets
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@ -75,6 +76,7 @@ def api_protocol_map(external_apis: dict[Api, ExternalApiSpec] | None = None) ->
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Api.agents: Agents,
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Api.inference: Inference,
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Api.inspect: Inspect,
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Api.batches: Batches,
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Api.vector_io: VectorIO,
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Api.vector_dbs: VectorDBs,
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Api.models: Models,
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@ -32,6 +32,7 @@ from fastapi.responses import JSONResponse, StreamingResponse
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from openai import BadRequestError
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from pydantic import BaseModel, ValidationError
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from llama_stack.apis.common.errors import ConflictError, ResourceNotFoundError
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from llama_stack.apis.common.responses import PaginatedResponse
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from llama_stack.cli.utils import add_config_distro_args, get_config_from_args
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from llama_stack.core.access_control.access_control import AccessDeniedError
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@ -128,6 +129,10 @@ def translate_exception(exc: Exception) -> HTTPException | RequestValidationErro
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]
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},
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)
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elif isinstance(exc, ConflictError):
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return HTTPException(status_code=409, detail=str(exc))
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elif isinstance(exc, ResourceNotFoundError):
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return HTTPException(status_code=404, detail=str(exc))
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elif isinstance(exc, ValueError):
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return HTTPException(status_code=httpx.codes.BAD_REQUEST, detail=f"Invalid value: {str(exc)}")
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elif isinstance(exc, BadRequestError):
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