forked from phoenix-oss/llama-stack-mirror
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 ```
61 lines
1.8 KiB
Python
61 lines
1.8 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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import argparse
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from llama_stack.cli.subcommand import Subcommand
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from llama_stack.cli.table import print_table
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from llama_stack.models.llama.sku_list import all_registered_models
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class ModelList(Subcommand):
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"""List available llama models"""
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def __init__(self, subparsers: argparse._SubParsersAction):
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super().__init__()
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self.parser = subparsers.add_parser(
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"list",
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prog="llama model list",
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description="Show available llama models",
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formatter_class=argparse.RawTextHelpFormatter,
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)
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self._add_arguments()
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self.parser.set_defaults(func=self._run_model_list_cmd)
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def _add_arguments(self):
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self.parser.add_argument(
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"--show-all",
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action="store_true",
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help="Show all models (not just defaults)",
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)
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def _run_model_list_cmd(self, args: argparse.Namespace) -> None:
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from .safety_models import prompt_guard_model_sku
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headers = [
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"Model Descriptor",
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"Model ID",
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"Context Length",
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]
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rows = []
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for model in all_registered_models() + [prompt_guard_model_sku()]:
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if not args.show_all and not model.is_featured:
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continue
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descriptor = model.descriptor()
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rows.append(
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[
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descriptor,
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model.huggingface_repo,
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f"{model.max_seq_length // 1024}K",
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]
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)
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print_table(
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rows,
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headers,
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separate_rows=True,
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)
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