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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 ```
89 lines
2.7 KiB
Python
89 lines
2.7 KiB
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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"""
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Type-safe data interchange for Python data classes.
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:see: https://github.com/hunyadi/strong_typing
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"""
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from typing import Callable, Dict, Iterable, List, Optional, Set, TypeVar
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from .inspection import TypeCollector
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T = TypeVar("T")
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def topological_sort(graph: Dict[T, Set[T]]) -> List[T]:
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"""
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Performs a topological sort of a graph.
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Nodes with no outgoing edges are first. Nodes with no incoming edges are last.
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The topological ordering is not unique.
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:param graph: A dictionary of mappings from nodes to adjacent nodes. Keys and set members must be hashable.
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:returns: The list of nodes in topological order.
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"""
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# empty list that will contain the sorted nodes (in reverse order)
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ordered: List[T] = []
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seen: Dict[T, bool] = {}
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def _visit(n: T) -> None:
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status = seen.get(n)
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if status is not None:
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if status: # node has a permanent mark
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return
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else: # node has a temporary mark
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raise RuntimeError(f"cycle detected in graph for node {n}")
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seen[n] = False # apply temporary mark
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for m in graph[n]: # visit all adjacent nodes
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if m != n: # ignore self-referencing nodes
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_visit(m)
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seen[n] = True # apply permanent mark
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ordered.append(n)
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for n in graph.keys():
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_visit(n)
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return ordered
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def type_topological_sort(
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types: Iterable[type],
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dependency_fn: Optional[Callable[[type], Iterable[type]]] = None,
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) -> List[type]:
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"""
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Performs a topological sort of a list of types.
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Types that don't depend on other types (i.e. fundamental types) are first. Types on which no other types depend
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are last. The topological ordering is not unique.
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:param types: A list of types (simple or composite).
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:param dependency_fn: Returns a list of additional dependencies for a class (e.g. classes referenced by a foreign key).
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:returns: The list of types in topological order.
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"""
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if not all(isinstance(typ, type) for typ in types):
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raise TypeError("expected a list of types")
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collector = TypeCollector()
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collector.traverse_all(types)
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graph = collector.graph
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if dependency_fn:
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new_types: Set[type] = set()
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for source_type, references in graph.items():
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dependent_types = dependency_fn(source_type)
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references.update(dependent_types)
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new_types.update(dependent_types)
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for new_type in new_types:
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graph[new_type] = set()
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return topological_sort(graph)
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