chore: rename templates to distributions (#3035)

As the title says. Distributions is in, Templates is out. `llama stack build --template` --> `llama stack build --distro`. For backward compatibility, the previous option is kept but results in a warning. Updated `server.py` to remove the "config_or_template" backward compatibility since it has been a couple releases since that change.
2025-08-13 05:17:26 +00:00 · 2025-08-04 11:34:17 -07:00 · 2025-08-04 11:34:17 -07:00 · cc87995e2b
commit cc87995e2b
parent 12f964437a
87 changed files with 263 additions and 330 deletions
--- a/llama_stack/distributions/open-benchmark/init.py
+++ b/llama_stack/distributions/open-benchmark/init.py
@ -0,0 +1,7 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from .open_benchmark import get_distribution_template  # noqa: F401
--- a/llama_stack/distributions/open-benchmark/build.yaml
+++ b/llama_stack/distributions/open-benchmark/build.yaml
@ -0,0 +1,38 @@
+version: 2
+distribution_spec:
+  description: Distribution for running open benchmarks
+  providers:
+    inference:
+    - provider_type: remote::openai
+    - provider_type: remote::anthropic
+    - provider_type: remote::gemini
+    - provider_type: remote::groq
+    - provider_type: remote::together
+    vector_io:
+    - provider_type: inline::sqlite-vec
+    - provider_type: remote::chromadb
+    - provider_type: remote::pgvector
+    safety:
+    - provider_type: inline::llama-guard
+    agents:
+    - provider_type: inline::meta-reference
+    telemetry:
+    - provider_type: inline::meta-reference
+    eval:
+    - provider_type: inline::meta-reference
+    datasetio:
+    - provider_type: remote::huggingface
+    - provider_type: inline::localfs
+    scoring:
+    - provider_type: inline::basic
+    - provider_type: inline::llm-as-judge
+    - provider_type: inline::braintrust
+    tool_runtime:
+    - provider_type: remote::brave-search
+    - provider_type: remote::tavily-search
+    - provider_type: inline::rag-runtime
+    - provider_type: remote::model-context-protocol
+image_type: venv
+additional_pip_packages:
+- aiosqlite
+- sqlalchemy[asyncio]
--- a/llama_stack/distributions/open-benchmark/open_benchmark.py
+++ b/llama_stack/distributions/open-benchmark/open_benchmark.py
@ -0,0 +1,316 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+
+from llama_stack.apis.datasets import DatasetPurpose, URIDataSource
+from llama_stack.apis.models import ModelType
+from llama_stack.core.datatypes import (
+    BenchmarkInput,
+    BuildProvider,
+    DatasetInput,
+    ModelInput,
+    Provider,
+    ShieldInput,
+    ToolGroupInput,
+)
+from llama_stack.distributions.template import (
+    DistributionTemplate,
+    RunConfigSettings,
+    get_model_registry,
+)
+from llama_stack.providers.inline.vector_io.sqlite_vec.config import (
+    SQLiteVectorIOConfig,
+)
+from llama_stack.providers.remote.inference.anthropic.config import AnthropicConfig
+from llama_stack.providers.remote.inference.gemini.config import GeminiConfig
+from llama_stack.providers.remote.inference.groq.config import GroqConfig
+from llama_stack.providers.remote.inference.openai.config import OpenAIConfig
+from llama_stack.providers.remote.inference.together.config import TogetherImplConfig
+from llama_stack.providers.remote.vector_io.chroma.config import ChromaVectorIOConfig
+from llama_stack.providers.remote.vector_io.pgvector.config import (
+    PGVectorVectorIOConfig,
+)
+from llama_stack.providers.utils.inference.model_registry import ProviderModelEntry
+
+
+def get_inference_providers() -> tuple[list[Provider], dict[str, list[ProviderModelEntry]]]:
+    # in this template, we allow each API key to be optional
+    providers = [
+        (
+            "openai",
+            [
+                ProviderModelEntry(
+                    provider_model_id="openai/gpt-4o",
+                    model_type=ModelType.llm,
+                )
+            ],
+            OpenAIConfig.sample_run_config(api_key="${env.OPENAI_API_KEY:=}"),
+        ),
+        (
+            "anthropic",
+            [
+                ProviderModelEntry(
+                    provider_model_id="anthropic/claude-3-5-sonnet-latest",
+                    model_type=ModelType.llm,
+                )
+            ],
+            AnthropicConfig.sample_run_config(api_key="${env.ANTHROPIC_API_KEY:=}"),
+        ),
+        (
+            "gemini",
+            [
+                ProviderModelEntry(
+                    provider_model_id="gemini/gemini-1.5-flash",
+                    model_type=ModelType.llm,
+                )
+            ],
+            GeminiConfig.sample_run_config(api_key="${env.GEMINI_API_KEY:=}"),
+        ),
+        (
+            "groq",
+            [],
+            GroqConfig.sample_run_config(api_key="${env.GROQ_API_KEY:=}"),
+        ),
+        (
+            "together",
+            [],
+            TogetherImplConfig.sample_run_config(api_key="${env.TOGETHER_API_KEY:=}"),
+        ),
+    ]
+    inference_providers = []
+    available_models = {}
+    for provider_id, model_entries, config in providers:
+        inference_providers.append(
+            Provider(
+                provider_id=provider_id,
+                provider_type=f"remote::{provider_id}",
+                config=config,
+            )
+        )
+        available_models[provider_id] = model_entries
+    return inference_providers, available_models
+
+
+def get_distribution_template() -> DistributionTemplate:
+    inference_providers, available_models = get_inference_providers()
+    providers = {
+        "inference": [BuildProvider(provider_type=p.provider_type, module=p.module) for p in inference_providers],
+        "vector_io": [
+            BuildProvider(provider_type="inline::sqlite-vec"),
+            BuildProvider(provider_type="remote::chromadb"),
+            BuildProvider(provider_type="remote::pgvector"),
+        ],
+        "safety": [BuildProvider(provider_type="inline::llama-guard")],
+        "agents": [BuildProvider(provider_type="inline::meta-reference")],
+        "telemetry": [BuildProvider(provider_type="inline::meta-reference")],
+        "eval": [BuildProvider(provider_type="inline::meta-reference")],
+        "datasetio": [
+            BuildProvider(provider_type="remote::huggingface"),
+            BuildProvider(provider_type="inline::localfs"),
+        ],
+        "scoring": [
+            BuildProvider(provider_type="inline::basic"),
+            BuildProvider(provider_type="inline::llm-as-judge"),
+            BuildProvider(provider_type="inline::braintrust"),
+        ],
+        "tool_runtime": [
+            BuildProvider(provider_type="remote::brave-search"),
+            BuildProvider(provider_type="remote::tavily-search"),
+            BuildProvider(provider_type="inline::rag-runtime"),
+            BuildProvider(provider_type="remote::model-context-protocol"),
+        ],
+    }
+    name = "open-benchmark"
+
+    vector_io_providers = [
+        Provider(
+            provider_id="sqlite-vec",
+            provider_type="inline::sqlite-vec",
+            config=SQLiteVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
+        ),
+        Provider(
+            provider_id="${env.ENABLE_CHROMADB:+chromadb}",
+            provider_type="remote::chromadb",
+            config=ChromaVectorIOConfig.sample_run_config(
+                f"~/.llama/distributions/{name}", url="${env.CHROMADB_URL:=}"
+            ),
+        ),
+        Provider(
+            provider_id="${env.ENABLE_PGVECTOR:+pgvector}",
+            provider_type="remote::pgvector",
+            config=PGVectorVectorIOConfig.sample_run_config(
+                f"~/.llama/distributions/{name}",
+                db="${env.PGVECTOR_DB:=}",
+                user="${env.PGVECTOR_USER:=}",
+                password="${env.PGVECTOR_PASSWORD:=}",
+            ),
+        ),
+    ]
+
+    default_tool_groups = [
+        ToolGroupInput(
+            toolgroup_id="builtin::websearch",
+            provider_id="tavily-search",
+        ),
+        ToolGroupInput(
+            toolgroup_id="builtin::rag",
+            provider_id="rag-runtime",
+        ),
+    ]
+
+    models, _ = get_model_registry(available_models)
+    default_models = models + [
+        ModelInput(
+            model_id="meta-llama/Llama-3.3-70B-Instruct",
+            provider_id="groq",
+            provider_model_id="groq/llama-3.3-70b-versatile",
+            model_type=ModelType.llm,
+        ),
+        ModelInput(
+            model_id="meta-llama/Llama-3.1-405B-Instruct",
+            provider_id="together",
+            provider_model_id="meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo",
+            model_type=ModelType.llm,
+        ),
+    ]
+
+    default_datasets = [
+        DatasetInput(
+            dataset_id="simpleqa",
+            purpose=DatasetPurpose.eval_messages_answer,
+            source=URIDataSource(
+                uri="huggingface://datasets/llamastack/simpleqa?split=train",
+            ),
+        ),
+        DatasetInput(
+            dataset_id="mmlu_cot",
+            purpose=DatasetPurpose.eval_messages_answer,
+            source=URIDataSource(
+                uri="huggingface://datasets/llamastack/mmlu_cot?split=test&name=all",
+            ),
+        ),
+        DatasetInput(
+            dataset_id="gpqa_cot",
+            purpose=DatasetPurpose.eval_messages_answer,
+            source=URIDataSource(
+                uri="huggingface://datasets/llamastack/gpqa_0shot_cot?split=test&name=gpqa_main",
+            ),
+        ),
+        DatasetInput(
+            dataset_id="math_500",
+            purpose=DatasetPurpose.eval_messages_answer,
+            source=URIDataSource(
+                uri="huggingface://datasets/llamastack/math_500?split=test",
+            ),
+        ),
+        DatasetInput(
+            dataset_id="bfcl",
+            purpose=DatasetPurpose.eval_messages_answer,
+            source=URIDataSource(
+                uri="huggingface://datasets/llamastack/bfcl_v3?split=train",
+            ),
+        ),
+        DatasetInput(
+            dataset_id="ifeval",
+            purpose=DatasetPurpose.eval_messages_answer,
+            source=URIDataSource(
+                uri="huggingface://datasets/llamastack/IfEval?split=train",
+            ),
+        ),
+        DatasetInput(
+            dataset_id="docvqa",
+            purpose=DatasetPurpose.eval_messages_answer,
+            source=URIDataSource(
+                uri="huggingface://datasets/llamastack/docvqa?split=val",
+            ),
+        ),
+    ]
+
+    default_benchmarks = [
+        BenchmarkInput(
+            benchmark_id="meta-reference-simpleqa",
+            dataset_id="simpleqa",
+            scoring_functions=["llm-as-judge::405b-simpleqa"],
+        ),
+        BenchmarkInput(
+            benchmark_id="meta-reference-mmlu-cot",
+            dataset_id="mmlu_cot",
+            scoring_functions=["basic::regex_parser_multiple_choice_answer"],
+        ),
+        BenchmarkInput(
+            benchmark_id="meta-reference-gpqa-cot",
+            dataset_id="gpqa_cot",
+            scoring_functions=["basic::regex_parser_multiple_choice_answer"],
+        ),
+        BenchmarkInput(
+            benchmark_id="meta-reference-math-500",
+            dataset_id="math_500",
+            scoring_functions=["basic::regex_parser_math_response"],
+        ),
+        BenchmarkInput(
+            benchmark_id="meta-reference-bfcl",
+            dataset_id="bfcl",
+            scoring_functions=["basic::bfcl"],
+        ),
+        BenchmarkInput(
+            benchmark_id="meta-reference-ifeval",
+            dataset_id="ifeval",
+            scoring_functions=["basic::ifeval"],
+        ),
+        BenchmarkInput(
+            benchmark_id="meta-reference-docvqa",
+            dataset_id="docvqa",
+            scoring_functions=["basic::docvqa"],
+        ),
+    ]
+    return DistributionTemplate(
+        name=name,
+        distro_type="self_hosted",
+        description="Distribution for running open benchmarks",
+        container_image=None,
+        template_path=None,
+        providers=providers,
+        available_models_by_provider=available_models,
+        run_configs={
+            "run.yaml": RunConfigSettings(
+                provider_overrides={
+                    "inference": inference_providers,
+                    "vector_io": vector_io_providers,
+                },
+                default_models=default_models,
+                default_tool_groups=default_tool_groups,
+                default_shields=[ShieldInput(shield_id="meta-llama/Llama-Guard-3-8B")],
+                default_datasets=default_datasets,
+                default_benchmarks=default_benchmarks,
+            ),
+        },
+        run_config_env_vars={
+            "LLAMA_STACK_PORT": (
+                "8321",
+                "Port for the Llama Stack distribution server",
+            ),
+            "TOGETHER_API_KEY": (
+                "",
+                "Together API Key",
+            ),
+            "OPENAI_API_KEY": (
+                "",
+                "OpenAI API Key",
+            ),
+            "GEMINI_API_KEY": (
+                "",
+                "Gemini API Key",
+            ),
+            "ANTHROPIC_API_KEY": (
+                "",
+                "Anthropic API Key",
+            ),
+            "GROQ_API_KEY": (
+                "",
+                "Groq API Key",
+            ),
+        },
+    )
--- a/llama_stack/distributions/open-benchmark/run.yaml
+++ b/llama_stack/distributions/open-benchmark/run.yaml
@ -0,0 +1,252 @@
+version: 2
+image_name: open-benchmark
+apis:
+- agents
+- datasetio
+- eval
+- inference
+- safety
+- scoring
+- telemetry
+- tool_runtime
+- vector_io
+providers:
+  inference:
+  - provider_id: openai
+    provider_type: remote::openai
+    config:
+      api_key: ${env.OPENAI_API_KEY:=}
+      base_url: ${env.OPENAI_BASE_URL:=https://api.openai.com/v1}
+  - provider_id: anthropic
+    provider_type: remote::anthropic
+    config:
+      api_key: ${env.ANTHROPIC_API_KEY:=}
+  - provider_id: gemini
+    provider_type: remote::gemini
+    config:
+      api_key: ${env.GEMINI_API_KEY:=}
+  - provider_id: groq
+    provider_type: remote::groq
+    config:
+      url: https://api.groq.com
+      api_key: ${env.GROQ_API_KEY:=}
+  - provider_id: together
+    provider_type: remote::together
+    config:
+      url: https://api.together.xyz/v1
+      api_key: ${env.TOGETHER_API_KEY:=}
+  vector_io:
+  - provider_id: sqlite-vec
+    provider_type: inline::sqlite-vec
+    config:
+      db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/sqlite_vec.db
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/sqlite_vec_registry.db
+  - provider_id: ${env.ENABLE_CHROMADB:+chromadb}
+    provider_type: remote::chromadb
+    config:
+      url: ${env.CHROMADB_URL:=}
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/chroma_remote_registry.db
+  - provider_id: ${env.ENABLE_PGVECTOR:+pgvector}
+    provider_type: remote::pgvector
+    config:
+      host: ${env.PGVECTOR_HOST:=localhost}
+      port: ${env.PGVECTOR_PORT:=5432}
+      db: ${env.PGVECTOR_DB:=}
+      user: ${env.PGVECTOR_USER:=}
+      password: ${env.PGVECTOR_PASSWORD:=}
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/pgvector_registry.db
+  safety:
+  - provider_id: llama-guard
+    provider_type: inline::llama-guard
+    config:
+      excluded_categories: []
+  agents:
+  - provider_id: meta-reference
+    provider_type: inline::meta-reference
+    config:
+      persistence_store:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/agents_store.db
+      responses_store:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/responses_store.db
+  telemetry:
+  - provider_id: meta-reference
+    provider_type: inline::meta-reference
+    config:
+      service_name: "${env.OTEL_SERVICE_NAME:=\u200B}"
+      sinks: ${env.TELEMETRY_SINKS:=console,sqlite}
+      sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/trace_store.db
+      otel_exporter_otlp_endpoint: ${env.OTEL_EXPORTER_OTLP_ENDPOINT:=}
+  eval:
+  - provider_id: meta-reference
+    provider_type: inline::meta-reference
+    config:
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/meta_reference_eval.db
+  datasetio:
+  - provider_id: huggingface
+    provider_type: remote::huggingface
+    config:
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/huggingface_datasetio.db
+  - provider_id: localfs
+    provider_type: inline::localfs
+    config:
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/localfs_datasetio.db
+  scoring:
+  - provider_id: basic
+    provider_type: inline::basic
+  - provider_id: llm-as-judge
+    provider_type: inline::llm-as-judge
+  - provider_id: braintrust
+    provider_type: inline::braintrust
+    config:
+      openai_api_key: ${env.OPENAI_API_KEY:=}
+  tool_runtime:
+  - provider_id: brave-search
+    provider_type: remote::brave-search
+    config:
+      api_key: ${env.BRAVE_SEARCH_API_KEY:=}
+      max_results: 3
+  - provider_id: tavily-search
+    provider_type: remote::tavily-search
+    config:
+      api_key: ${env.TAVILY_SEARCH_API_KEY:=}
+      max_results: 3
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
+metadata_store:
+  type: sqlite
+  db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/registry.db
+inference_store:
+  type: sqlite
+  db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/inference_store.db
+models:
+- metadata: {}
+  model_id: openai/gpt-4o
+  provider_id: openai
+  provider_model_id: openai/gpt-4o
+  model_type: llm
+- metadata: {}
+  model_id: anthropic/claude-3-5-sonnet-latest
+  provider_id: anthropic
+  provider_model_id: anthropic/claude-3-5-sonnet-latest
+  model_type: llm
+- metadata: {}
+  model_id: gemini/gemini-1.5-flash
+  provider_id: gemini
+  provider_model_id: gemini/gemini-1.5-flash
+  model_type: llm
+- metadata: {}
+  model_id: meta-llama/Llama-3.3-70B-Instruct
+  provider_id: groq
+  provider_model_id: groq/llama-3.3-70b-versatile
+  model_type: llm
+- metadata: {}
+  model_id: meta-llama/Llama-3.1-405B-Instruct
+  provider_id: together
+  provider_model_id: meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo
+  model_type: llm
+shields:
+- shield_id: meta-llama/Llama-Guard-3-8B
+vector_dbs: []
+datasets:
+- purpose: eval/messages-answer
+  source:
+    type: uri
+    uri: huggingface://datasets/llamastack/simpleqa?split=train
+  metadata: {}
+  dataset_id: simpleqa
+- purpose: eval/messages-answer
+  source:
+    type: uri
+    uri: huggingface://datasets/llamastack/mmlu_cot?split=test&name=all
+  metadata: {}
+  dataset_id: mmlu_cot
+- purpose: eval/messages-answer
+  source:
+    type: uri
+    uri: huggingface://datasets/llamastack/gpqa_0shot_cot?split=test&name=gpqa_main
+  metadata: {}
+  dataset_id: gpqa_cot
+- purpose: eval/messages-answer
+  source:
+    type: uri
+    uri: huggingface://datasets/llamastack/math_500?split=test
+  metadata: {}
+  dataset_id: math_500
+- purpose: eval/messages-answer
+  source:
+    type: uri
+    uri: huggingface://datasets/llamastack/bfcl_v3?split=train
+  metadata: {}
+  dataset_id: bfcl
+- purpose: eval/messages-answer
+  source:
+    type: uri
+    uri: huggingface://datasets/llamastack/IfEval?split=train
+  metadata: {}
+  dataset_id: ifeval
+- purpose: eval/messages-answer
+  source:
+    type: uri
+    uri: huggingface://datasets/llamastack/docvqa?split=val
+  metadata: {}
+  dataset_id: docvqa
+scoring_fns: []
+benchmarks:
+- dataset_id: simpleqa
+  scoring_functions:
+  - llm-as-judge::405b-simpleqa
+  metadata: {}
+  benchmark_id: meta-reference-simpleqa
+- dataset_id: mmlu_cot
+  scoring_functions:
+  - basic::regex_parser_multiple_choice_answer
+  metadata: {}
+  benchmark_id: meta-reference-mmlu-cot
+- dataset_id: gpqa_cot
+  scoring_functions:
+  - basic::regex_parser_multiple_choice_answer
+  metadata: {}
+  benchmark_id: meta-reference-gpqa-cot
+- dataset_id: math_500
+  scoring_functions:
+  - basic::regex_parser_math_response
+  metadata: {}
+  benchmark_id: meta-reference-math-500
+- dataset_id: bfcl
+  scoring_functions:
+  - basic::bfcl
+  metadata: {}
+  benchmark_id: meta-reference-bfcl
+- dataset_id: ifeval
+  scoring_functions:
+  - basic::ifeval
+  metadata: {}
+  benchmark_id: meta-reference-ifeval
+- dataset_id: docvqa
+  scoring_functions:
+  - basic::docvqa
+  metadata: {}
+  benchmark_id: meta-reference-docvqa
+tool_groups:
+- toolgroup_id: builtin::websearch
+  provider_id: tavily-search
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
+server:
+  port: 8321