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feat: consolidate most distros into "starter" (#2516)
# What does this PR do? * Removes a bunch of distros * Removed distros were added into the "starter" distribution * Doc for "starter" has been added * Partially reverts https://github.com/meta-llama/llama-stack/pull/2482 since inference providers are disabled by default and can be turned on manually via env variable. * Disables safety in starter distro Closes: https://github.com/meta-llama/llama-stack/issues/2502. ~Needs: https://github.com/meta-llama/llama-stack/pull/2482 for Ollama to work properly in the CI.~ TODO: - [ ] We can only update `install.sh` when we get a new release. - [x] Update providers documentation - [ ] Update notebooks to reference starter instead of ollama Signed-off-by: Sébastien Han <seb@redhat.com>
This commit is contained in:
Sébastien Han
GitHub
parent
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commit
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132 changed files with 1009 additions and 10845 deletions
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# 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 .llama_api import get_distribution_template # noqa: F401
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version: 2
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distribution_spec:
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description: Distribution for running e2e tests in CI
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providers:
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inference:
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- remote::llama-openai-compat
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- inline::sentence-transformers
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vector_io:
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- inline::sqlite-vec
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- remote::chromadb
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- remote::pgvector
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safety:
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- inline::llama-guard
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agents:
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- inline::meta-reference
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telemetry:
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- inline::meta-reference
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eval:
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- inline::meta-reference
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datasetio:
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- remote::huggingface
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- inline::localfs
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scoring:
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- inline::basic
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- inline::llm-as-judge
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- inline::braintrust
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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::rag-runtime
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- remote::model-context-protocol
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image_type: conda
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additional_pip_packages:
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- aiosqlite
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- sqlalchemy[asyncio]
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# 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 llama_stack.apis.models import ModelType
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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.inline.inference.sentence_transformers import (
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SentenceTransformersInferenceConfig,
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)
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from llama_stack.providers.inline.vector_io.sqlite_vec.config import (
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SQLiteVectorIOConfig,
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)
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from llama_stack.providers.remote.inference.llama_openai_compat.config import (
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LlamaCompatConfig,
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)
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from llama_stack.providers.remote.inference.llama_openai_compat.models import (
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MODEL_ENTRIES as LLLAMA_MODEL_ENTRIES,
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)
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from llama_stack.providers.remote.vector_io.chroma.config import ChromaVectorIOConfig
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from llama_stack.providers.remote.vector_io.pgvector.config import (
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PGVectorVectorIOConfig,
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)
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from llama_stack.templates.template import (
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DistributionTemplate,
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RunConfigSettings,
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get_model_registry,
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)
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def get_inference_providers() -> tuple[list[Provider], list[ModelInput]]:
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# in this template, we allow each API key to be optional
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providers = [
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(
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"llama-openai-compat",
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LLLAMA_MODEL_ENTRIES,
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LlamaCompatConfig.sample_run_config(api_key="${env.LLAMA_API_KEY:=}"),
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),
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]
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inference_providers = []
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available_models = {}
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for provider_id, model_entries, config in providers:
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inference_providers.append(
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Provider(
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provider_id=provider_id,
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provider_type=f"remote::{provider_id}",
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config=config,
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)
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)
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available_models[provider_id] = model_entries
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return inference_providers, available_models
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def get_distribution_template() -> DistributionTemplate:
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inference_providers, available_models = get_inference_providers()
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providers = {
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"inference": ([p.provider_type for p in inference_providers] + ["inline::sentence-transformers"]),
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"vector_io": ["inline::sqlite-vec", "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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"eval": ["inline::meta-reference"],
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"datasetio": ["remote::huggingface", "inline::localfs"],
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"scoring": ["inline::basic", "inline::llm-as-judge", "inline::braintrust"],
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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::rag-runtime",
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"remote::model-context-protocol",
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],
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}
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name = "llama_api"
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vector_io_providers = [
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Provider(
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provider_id="sqlite-vec",
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provider_type="inline::sqlite-vec",
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config=SQLiteVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
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),
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Provider(
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provider_id="${env.ENABLE_CHROMADB:+chromadb}",
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provider_type="remote::chromadb",
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config=ChromaVectorIOConfig.sample_run_config(url="${env.CHROMADB_URL:=}"),
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),
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Provider(
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provider_id="${env.ENABLE_PGVECTOR:+pgvector}",
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provider_type="remote::pgvector",
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config=PGVectorVectorIOConfig.sample_run_config(
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db="${env.PGVECTOR_DB:=}",
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user="${env.PGVECTOR_USER:=}",
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password="${env.PGVECTOR_PASSWORD:=}",
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),
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),
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]
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embedding_provider = Provider(
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provider_id="sentence-transformers",
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provider_type="inline::sentence-transformers",
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config=SentenceTransformersInferenceConfig.sample_run_config(),
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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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]
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embedding_model = ModelInput(
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model_id="all-MiniLM-L6-v2",
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provider_id=embedding_provider.provider_id,
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model_type=ModelType.embedding,
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metadata={
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"embedding_dimension": 384,
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},
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)
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default_models = get_model_registry(available_models)
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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="Distribution for running e2e tests in CI",
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container_image=None,
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template_path=None,
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providers=providers,
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available_models_by_provider=available_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_providers + [embedding_provider],
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"vector_io": vector_io_providers,
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},
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default_models=default_models + [embedding_model],
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default_tool_groups=default_tool_groups,
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default_shields=[ShieldInput(shield_id="meta-llama/Llama-Guard-3-8B")],
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),
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},
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run_config_env_vars={
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"LLAMA_STACK_PORT": (
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"8321",
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"Port for the Llama Stack distribution server",
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),
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},
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)
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version: 2
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image_name: llama_api
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apis:
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- agents
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- datasetio
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- eval
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- inference
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- safety
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- scoring
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- telemetry
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- tool_runtime
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- vector_io
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providers:
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inference:
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- provider_id: llama-openai-compat
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provider_type: remote::llama-openai-compat
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config:
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openai_compat_api_base: https://api.llama.com/compat/v1/
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api_key: ${env.LLAMA_API_KEY:=}
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- provider_id: sentence-transformers
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provider_type: inline::sentence-transformers
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config: {}
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vector_io:
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- provider_id: sqlite-vec
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provider_type: inline::sqlite-vec
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config:
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db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/llama_api}/sqlite_vec.db
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- provider_id: ${env.ENABLE_CHROMADB:+chromadb}
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provider_type: remote::chromadb
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config:
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url: ${env.CHROMADB_URL:=}
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- provider_id: ${env.ENABLE_PGVECTOR:+pgvector}
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provider_type: remote::pgvector
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config:
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host: ${env.PGVECTOR_HOST:=localhost}
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port: ${env.PGVECTOR_PORT:=5432}
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db: ${env.PGVECTOR_DB:=}
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user: ${env.PGVECTOR_USER:=}
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password: ${env.PGVECTOR_PASSWORD:=}
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safety:
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- provider_id: llama-guard
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provider_type: inline::llama-guard
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config:
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excluded_categories: []
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agents:
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- provider_id: meta-reference
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provider_type: inline::meta-reference
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config:
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persistence_store:
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type: sqlite
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db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/llama_api}/agents_store.db
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responses_store:
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type: sqlite
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db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/llama_api}/responses_store.db
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telemetry:
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- provider_id: meta-reference
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provider_type: inline::meta-reference
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config:
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service_name: "${env.OTEL_SERVICE_NAME:=\u200B}"
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sinks: ${env.TELEMETRY_SINKS:=console,sqlite}
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sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/llama_api}/trace_store.db
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eval:
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- provider_id: meta-reference
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provider_type: inline::meta-reference
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config:
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kvstore:
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type: sqlite
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db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/llama_api}/meta_reference_eval.db
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datasetio:
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- provider_id: huggingface
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provider_type: remote::huggingface
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config:
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kvstore:
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type: sqlite
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db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/llama_api}/huggingface_datasetio.db
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- provider_id: localfs
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provider_type: inline::localfs
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config:
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kvstore:
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type: sqlite
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db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/llama_api}/localfs_datasetio.db
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scoring:
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- provider_id: basic
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provider_type: inline::basic
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config: {}
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- provider_id: llm-as-judge
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provider_type: inline::llm-as-judge
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config: {}
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- provider_id: braintrust
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provider_type: inline::braintrust
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config:
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openai_api_key: ${env.OPENAI_API_KEY:=}
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tool_runtime:
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- provider_id: brave-search
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provider_type: remote::brave-search
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config:
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api_key: ${env.BRAVE_SEARCH_API_KEY:=}
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max_results: 3
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- provider_id: tavily-search
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provider_type: remote::tavily-search
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config:
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api_key: ${env.TAVILY_SEARCH_API_KEY:=}
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max_results: 3
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- provider_id: rag-runtime
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provider_type: inline::rag-runtime
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config: {}
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- provider_id: model-context-protocol
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provider_type: remote::model-context-protocol
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config: {}
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metadata_store:
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type: sqlite
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db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/llama_api}/registry.db
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inference_store:
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type: sqlite
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db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/llama_api}/inference_store.db
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models:
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- metadata: {}
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model_id: Llama-3.3-70B-Instruct
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provider_id: llama-openai-compat
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provider_model_id: Llama-3.3-70B-Instruct
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model_type: llm
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- metadata: {}
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model_id: meta-llama/Llama-3.3-70B-Instruct
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provider_id: llama-openai-compat
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provider_model_id: Llama-3.3-70B-Instruct
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model_type: llm
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- metadata: {}
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model_id: Llama-4-Scout-17B-16E-Instruct-FP8
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provider_id: llama-openai-compat
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provider_model_id: Llama-4-Scout-17B-16E-Instruct-FP8
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model_type: llm
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- metadata: {}
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model_id: meta-llama/Llama-4-Scout-17B-16E-Instruct
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provider_id: llama-openai-compat
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provider_model_id: Llama-4-Scout-17B-16E-Instruct-FP8
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model_type: llm
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- metadata: {}
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model_id: Llama-4-Maverick-17B-128E-Instruct-FP8
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provider_id: llama-openai-compat
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provider_model_id: Llama-4-Maverick-17B-128E-Instruct-FP8
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model_type: llm
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- metadata: {}
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model_id: meta-llama/Llama-4-Maverick-17B-128E-Instruct
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provider_id: llama-openai-compat
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provider_model_id: Llama-4-Maverick-17B-128E-Instruct-FP8
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model_type: llm
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- metadata:
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embedding_dimension: 384
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model_id: all-MiniLM-L6-v2
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provider_id: sentence-transformers
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model_type: embedding
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shields:
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- shield_id: meta-llama/Llama-Guard-3-8B
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vector_dbs: []
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datasets: []
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scoring_fns: []
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benchmarks: []
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tool_groups:
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- toolgroup_id: builtin::websearch
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provider_id: tavily-search
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- toolgroup_id: builtin::rag
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provider_id: rag-runtime
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server:
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port: 8321
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