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100 lines
3.5 KiB
Python
100 lines
3.5 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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from pathlib import Path
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from llama_stack.distribution.datatypes import ModelInput, Provider, ShieldInput
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from llama_stack.providers.remote.inference.vllm import VLLMInferenceAdapterConfig
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from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
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def get_distribution_template() -> DistributionTemplate:
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providers = {
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"inference": ["remote::vllm"],
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"memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
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"safety": ["inline::llama-guard"],
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"agents": ["inline::meta-reference"],
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"telemetry": ["inline::meta-reference"],
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}
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inference_provider = Provider(
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provider_id="vllm-inference",
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provider_type="remote::vllm",
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config=VLLMInferenceAdapterConfig.sample_run_config(
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url="${env.VLLM_URL}",
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),
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)
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inference_model = ModelInput(
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model_id="${env.INFERENCE_MODEL}",
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provider_id="vllm-inference",
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)
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safety_model = ModelInput(
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model_id="${env.SAFETY_MODEL}",
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provider_id="vllm-safety",
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)
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return DistributionTemplate(
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name="remote-vllm",
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distro_type="self_hosted",
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description="Use (an external) vLLM server for running LLM inference",
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template_path=Path(__file__).parent / "doc_template.md",
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providers=providers,
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default_models=[inference_model, safety_model],
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run_configs={
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"run.yaml": RunConfigSettings(
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provider_overrides={
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"inference": [inference_provider],
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},
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default_models=[inference_model],
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),
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"run-with-safety.yaml": RunConfigSettings(
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provider_overrides={
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"inference": [
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inference_provider,
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Provider(
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provider_id="vllm-safety",
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provider_type="remote::vllm",
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config=VLLMInferenceAdapterConfig.sample_run_config(
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url="${env.SAFETY_VLLM_URL}",
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),
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),
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],
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},
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default_models=[
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inference_model,
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safety_model,
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],
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default_shields=[ShieldInput(shield_id="${env.SAFETY_MODEL}")],
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),
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},
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run_config_env_vars={
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"LLAMASTACK_PORT": (
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"5001",
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"Port for the Llama Stack distribution server",
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),
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"INFERENCE_MODEL": (
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"meta-llama/Llama-3.2-3B-Instruct",
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"Inference model loaded into the vLLM server",
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),
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"VLLM_URL": (
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"http://host.docker.internal:5100}/v1",
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"URL of the vLLM server with the main inference model",
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),
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"MAX_TOKENS": (
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"4096",
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"Maximum number of tokens for generation",
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),
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"SAFETY_VLLM_URL": (
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"http://host.docker.internal:5101/v1",
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"URL of the vLLM server with the safety model",
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),
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"SAFETY_MODEL": (
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"meta-llama/Llama-Guard-3-1B",
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"Name of the safety (Llama-Guard) model to use",
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),
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},
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)
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