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https://github.com/meta-llama/llama-stack.git
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314ee09ae3
llama-models should have extremely minimal cruft. Its sole purpose should be didactic -- show the simplest implementation of the llama models and document the prompt formats, etc. This PR is the complement to https://github.com/meta-llama/llama-models/pull/279 ## Test Plan Ensure all `llama` CLI `model` sub-commands work: ```bash llama model list llama model download --model-id ... llama model prompt-format -m ... ``` Ran tests: ```bash cd tests/client-sdk LLAMA_STACK_CONFIG=fireworks pytest -s -v inference/ LLAMA_STACK_CONFIG=fireworks pytest -s -v vector_io/ LLAMA_STACK_CONFIG=fireworks pytest -s -v agents/ ``` Create a fresh venv `uv venv && source .venv/bin/activate` and run `llama stack build --template fireworks --image-type venv` followed by `llama stack run together --image-type venv` <-- the server runs Also checked that the OpenAPI generator can run and there is no change in the generated files as a result. ```bash cd docs/openapi_generator sh run_openapi_generator.sh ```
27 lines
936 B
Python
27 lines
936 B
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from typing import Any, Dict, Tuple, Type, TypeVar
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T = TypeVar("T")
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class SlotsMeta(type):
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def __new__(cls: Type[T], name: str, bases: Tuple[type, ...], ns: Dict[str, Any]) -> T:
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# caller may have already provided slots, in which case just retain them and keep going
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slots: Tuple[str, ...] = ns.get("__slots__", ())
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# add fields with type annotations to slots
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annotations: Dict[str, Any] = ns.get("__annotations__", {})
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members = tuple(member for member in annotations.keys() if member not in slots)
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# assign slots
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ns["__slots__"] = slots + tuple(members)
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return super().__new__(cls, name, bases, ns) # type: ignore
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class Slots(metaclass=SlotsMeta):
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pass
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