forked from phoenix-oss/llama-stack-mirror
refactor: move all llama code to models/llama out of meta reference (#1887)
# What does this PR do? Move around bits. This makes the copies from llama-models _much_ easier to maintain and ensures we don't entangle meta-reference specific tidbits into llama-models code even by accident. Also, kills the meta-reference-quantized-gpu distro and rolls quantization deps into meta-reference-gpu. ## Test Plan ``` LLAMA_MODELS_DEBUG=1 \ with-proxy llama stack run meta-reference-gpu \ --env INFERENCE_MODEL=meta-llama/Llama-4-Scout-17B-16E-Instruct \ --env INFERENCE_CHECKPOINT_DIR=<DIR> \ --env MODEL_PARALLEL_SIZE=4 \ --env QUANTIZATION_TYPE=fp8_mixed ``` Start a server with and without quantization. Point integration tests to it using: ``` pytest -s -v tests/integration/inference/test_text_inference.py \ --stack-config http://localhost:8321 --text-model meta-llama/Llama-4-Scout-17B-16E-Instruct ```
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85 changed files with 1267 additions and 1683 deletions
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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, Optional
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from typing import Any, Dict
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from pydantic import BaseModel, ConfigDict, Field
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from llama_stack.models.llama.datatypes import CheckpointQuantizationFormat, SamplingParams
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from llama_stack.models.llama.sku_list import LlamaDownloadInfo
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from llama_stack.models.llama.sku_types import CheckpointQuantizationFormat
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class PromptGuardModel(BaseModel):
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@ -23,7 +23,6 @@ class PromptGuardModel(BaseModel):
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is_instruct_model: bool = False
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quantization_format: CheckpointQuantizationFormat = CheckpointQuantizationFormat.bf16
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arch_args: Dict[str, Any] = Field(default_factory=dict)
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recommended_sampling_params: Optional[SamplingParams] = None
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def descriptor(self) -> str:
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return self.model_id
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