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100 lines
3 KiB
Python
100 lines
3 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_models.sku_list import all_registered_models
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from llama_stack.distribution.datatypes import (
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ModelInput,
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Provider,
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ShieldInput,
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ToolGroupInput,
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)
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from llama_stack.providers.remote.inference.sambanova import SambaNovaImplConfig
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from llama_stack.providers.remote.inference.sambanova.sambanova import MODEL_ALIASES
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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::sambanova"],
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"vector_io": ["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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"tool_runtime": [
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"remote::brave-search",
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"remote::tavily-search",
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"inline::code-interpreter",
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"inline::rag-runtime",
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],
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}
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name = "sambanova"
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inference_provider = Provider(
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provider_id=name,
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provider_type=f"remote::{name}",
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config=SambaNovaImplConfig.sample_run_config(),
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)
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core_model_to_hf_repo = {
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m.descriptor(): m.huggingface_repo for m in all_registered_models()
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}
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default_models = [
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ModelInput(
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model_id=core_model_to_hf_repo[m.llama_model],
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provider_model_id=m.provider_model_id,
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provider_id=name,
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)
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for m in MODEL_ALIASES
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]
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default_tool_groups = [
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ToolGroupInput(
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toolgroup_id="builtin::websearch",
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provider_id="tavily-search",
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),
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ToolGroupInput(
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toolgroup_id="builtin::rag",
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provider_id="rag-runtime",
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),
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ToolGroupInput(
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toolgroup_id="builtin::code_interpreter",
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provider_id="code-interpreter",
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),
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]
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return DistributionTemplate(
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name=name,
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distro_type="self_hosted",
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description="Use SambaNova.AI for running LLM inference",
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docker_image=None,
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template_path=Path(__file__).parent / "doc_template.md",
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providers=providers,
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default_models=default_models,
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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=default_models,
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default_shields=[ShieldInput(shield_id="meta-llama/Llama-Guard-3-8B")],
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default_tool_groups=default_tool_groups,
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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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"SAMBANOVA_API_KEY": (
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"",
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"SambaNova.AI API Key",
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),
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},
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)
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