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>

llama_stack/templates/ollama/__init__.py

@@ -1,7 +0,0 @@
-# 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 .ollama import get_distribution_template  # noqa: F401

llama_stack/templates/ollama/build.yaml

@@ -1,39 +0,0 @@
-version: 2
-distribution_spec:
-  description: Use (an external) Ollama server for running LLM inference
-  providers:
-    inference:
-    - remote::ollama
-    vector_io:
-    - inline::faiss
-    - remote::chromadb
-    - remote::pgvector
-    safety:
-    - inline::llama-guard
-    agents:
-    - inline::meta-reference
-    telemetry:
-    - inline::meta-reference
-    eval:
-    - inline::meta-reference
-    datasetio:
-    - remote::huggingface
-    - inline::localfs
-    scoring:
-    - inline::basic
-    - inline::llm-as-judge
-    - inline::braintrust
-    files:
-    - inline::localfs
-    post_training:
-    - inline::huggingface
-    tool_runtime:
-    - remote::brave-search
-    - remote::tavily-search
-    - inline::rag-runtime
-    - remote::model-context-protocol
-    - remote::wolfram-alpha
-image_type: conda
-additional_pip_packages:
-- aiosqlite
-- sqlalchemy[asyncio]

llama_stack/templates/ollama/doc_template.md

@@ -1,152 +0,0 @@
----
-orphan: true
----
-# Ollama Distribution
-
-```{toctree}
-:maxdepth: 2
-:hidden:
-
-self
-```
-
-The `llamastack/distribution-{{ name }}` distribution consists of the following provider configurations.
-
-{{ providers_table }}
-
-You should use this distribution if you have a regular desktop machine without very powerful GPUs. Of course, if you have powerful GPUs, you can still continue using this distribution since Ollama supports GPU acceleration.
-
-{% if run_config_env_vars %}
-### Environment Variables
-
-The following environment variables can be configured:
-
-{% for var, (default_value, description) in run_config_env_vars.items() %}
-- `{{ var }}`: {{ description }} (default: `{{ default_value }}`)
-{% endfor %}
-{% endif %}
-
-
-## Setting up Ollama server
-
-Please check the [Ollama Documentation](https://github.com/ollama/ollama) on how to install and run Ollama. After installing Ollama, you need to run `ollama serve` to start the server.
-
-In order to load models, you can run:
-
-```bash
-export INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct"
-
-# ollama names this model differently, and we must use the ollama name when loading the model
-export OLLAMA_INFERENCE_MODEL="llama3.2:3b-instruct-fp16"
-ollama run $OLLAMA_INFERENCE_MODEL --keepalive 60m
-```
-
-If you are using Llama Stack Safety / Shield APIs, you will also need to pull and run the safety model.
-
-```bash
-export SAFETY_MODEL="meta-llama/Llama-Guard-3-1B"
-
-# ollama names this model differently, and we must use the ollama name when loading the model
-export OLLAMA_SAFETY_MODEL="llama-guard3:1b"
-ollama run $OLLAMA_SAFETY_MODEL --keepalive 60m
-```
-
-## Running Llama Stack
-
-Now you are ready to run Llama Stack with Ollama as the inference provider. You can do this via Conda (build code) or Docker which has a pre-built image.
-
-### Via Docker
-
-This method allows you to get started quickly without having to build the distribution code.
-
-```bash
-export LLAMA_STACK_PORT=8321
-docker run \
-  -it \
-  --pull always \
-  -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-  -v ~/.llama:/root/.llama \
-  llamastack/distribution-{{ name }} \
-  --port $LLAMA_STACK_PORT \
-  --env INFERENCE_MODEL=$INFERENCE_MODEL \
-  --env OLLAMA_URL=http://host.docker.internal:11434
-```
-
-If you are using Llama Stack Safety / Shield APIs, use:
-
-```bash
-# You need a local checkout of llama-stack to run this, get it using
-# git clone https://github.com/meta-llama/llama-stack.git
-cd /path/to/llama-stack
-
-docker run \
-  -it \
-  --pull always \
-  -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-  -v ~/.llama:/root/.llama \
-  -v ./llama_stack/templates/ollama/run-with-safety.yaml:/root/my-run.yaml \
-  llamastack/distribution-{{ name }} \
-  --config /root/my-run.yaml \
-  --port $LLAMA_STACK_PORT \
-  --env INFERENCE_MODEL=$INFERENCE_MODEL \
-  --env SAFETY_MODEL=$SAFETY_MODEL \
-  --env OLLAMA_URL=http://host.docker.internal:11434
-```
-
-### Via Conda
-
-Make sure you have done `uv pip install llama-stack` and have the Llama Stack CLI available.
-
-```bash
-export LLAMA_STACK_PORT=8321
-
-llama stack build --template {{ name }} --image-type conda
-llama stack run ./run.yaml \
-  --port $LLAMA_STACK_PORT \
-  --env INFERENCE_MODEL=$INFERENCE_MODEL \
-  --env OLLAMA_URL=http://localhost:11434
-```
-
-If you are using Llama Stack Safety / Shield APIs, use:
-
-```bash
-llama stack run ./run-with-safety.yaml \
-  --port $LLAMA_STACK_PORT \
-  --env INFERENCE_MODEL=$INFERENCE_MODEL \
-  --env SAFETY_MODEL=$SAFETY_MODEL \
-  --env OLLAMA_URL=http://localhost:11434
-```
-
-
-### (Optional) Update Model Serving Configuration
-
-```{note}
-Please check the [model_entries](https://github.com/meta-llama/llama-stack/blob/main/llama_stack/providers/remote/inference/ollama/models.py) for the supported Ollama models.
-```
-
-To serve a new model with `ollama`
-```bash
-ollama run <model_name>
-```
-
-To make sure that the model is being served correctly, run `ollama ps` to get a list of models being served by ollama.
-```
-$ ollama ps
-NAME                         ID              SIZE      PROCESSOR    UNTIL
-llama3.2:3b-instruct-fp16    195a8c01d91e    8.6 GB    100% GPU     9 minutes from now
-```
-
-To verify that the model served by ollama is correctly connected to Llama Stack server
-```bash
-$ llama-stack-client models list
-
-Available Models
-
-┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━┓
-┃ model_type   ┃ identifier                           ┃ provider_resource_id         ┃ metadata  ┃ provider_id ┃
-┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━┩
-│ llm          │ meta-llama/Llama-3.2-3B-Instruct     │ llama3.2:3b-instruct-fp16    │           │ ollama      │
-└──────────────┴──────────────────────────────────────┴──────────────────────────────┴───────────┴─────────────┘
-
-Total models: 1
-```

llama_stack/templates/ollama/ollama.py

@@ -1,169 +0,0 @@
-# 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 pathlib import Path
-
-from llama_stack.apis.models import ModelType
-from llama_stack.distribution.datatypes import (
-    ModelInput,
-    Provider,
-    ShieldInput,
-    ToolGroupInput,
-)
-from llama_stack.providers.inline.files.localfs.config import LocalfsFilesImplConfig
-from llama_stack.providers.inline.post_training.huggingface import HuggingFacePostTrainingConfig
-from llama_stack.providers.inline.vector_io.faiss.config import FaissVectorIOConfig
-from llama_stack.providers.remote.inference.ollama import OllamaImplConfig
-from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
-
-
-def get_distribution_template() -> DistributionTemplate:
-    providers = {
-        "inference": ["remote::ollama"],
-        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
-        "safety": ["inline::llama-guard"],
-        "agents": ["inline::meta-reference"],
-        "telemetry": ["inline::meta-reference"],
-        "eval": ["inline::meta-reference"],
-        "datasetio": ["remote::huggingface", "inline::localfs"],
-        "scoring": ["inline::basic", "inline::llm-as-judge", "inline::braintrust"],
-        "files": ["inline::localfs"],
-        "post_training": ["inline::huggingface"],
-        "tool_runtime": [
-            "remote::brave-search",
-            "remote::tavily-search",
-            "inline::rag-runtime",
-            "remote::model-context-protocol",
-            "remote::wolfram-alpha",
-        ],
-    }
-    name = "ollama"
-    inference_provider = Provider(
-        provider_id="ollama",
-        provider_type="remote::ollama",
-        config=OllamaImplConfig.sample_run_config(),
-    )
-    vector_io_provider_faiss = Provider(
-        provider_id="faiss",
-        provider_type="inline::faiss",
-        config=FaissVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
-    )
-    files_provider = Provider(
-        provider_id="meta-reference-files",
-        provider_type="inline::localfs",
-        config=LocalfsFilesImplConfig.sample_run_config(f"~/.llama/distributions/{name}"),
-    )
-    posttraining_provider = Provider(
-        provider_id="huggingface",
-        provider_type="inline::huggingface",
-        config=HuggingFacePostTrainingConfig.sample_run_config(f"~/.llama/distributions/{name}"),
-    )
-    inference_model = ModelInput(
-        model_id="${env.INFERENCE_MODEL}",
-        provider_id="ollama",
-    )
-    safety_model = ModelInput(
-        model_id="${env.SAFETY_MODEL}",
-        provider_id="ollama",
-    )
-    embedding_model = ModelInput(
-        model_id="all-MiniLM-L6-v2",
-        provider_id="ollama",
-        provider_model_id="all-minilm:latest",
-        model_type=ModelType.embedding,
-        metadata={
-            "embedding_dimension": 384,
-        },
-    )
-    default_tool_groups = [
-        ToolGroupInput(
-            toolgroup_id="builtin::websearch",
-            provider_id="tavily-search",
-        ),
-        ToolGroupInput(
-            toolgroup_id="builtin::rag",
-            provider_id="rag-runtime",
-        ),
-        ToolGroupInput(
-            toolgroup_id="builtin::wolfram_alpha",
-            provider_id="wolfram-alpha",
-        ),
-    ]
-
-    return DistributionTemplate(
-        name=name,
-        distro_type="self_hosted",
-        description="Use (an external) Ollama server for running LLM inference",
-        container_image=None,
-        template_path=Path(__file__).parent / "doc_template.md",
-        providers=providers,
-        run_configs={
-            "run.yaml": RunConfigSettings(
-                provider_overrides={
-                    "inference": [inference_provider],
-                    "vector_io": [vector_io_provider_faiss],
-                    "files": [files_provider],
-                    "post_training": [posttraining_provider],
-                },
-                default_models=[inference_model, embedding_model],
-                default_tool_groups=default_tool_groups,
-            ),
-            "run-with-safety.yaml": RunConfigSettings(
-                provider_overrides={
-                    "inference": [inference_provider],
-                    "vector_io": [vector_io_provider_faiss],
-                    "files": [files_provider],
-                    "post_training": [posttraining_provider],
-                    "safety": [
-                        Provider(
-                            provider_id="llama-guard",
-                            provider_type="inline::llama-guard",
-                            config={},
-                        ),
-                        Provider(
-                            provider_id="code-scanner",
-                            provider_type="inline::code-scanner",
-                            config={},
-                        ),
-                    ],
-                },
-                default_models=[
-                    inference_model,
-                    safety_model,
-                    embedding_model,
-                ],
-                default_shields=[
-                    ShieldInput(
-                        shield_id="${env.SAFETY_MODEL}",
-                        provider_id="llama-guard",
-                    ),
-                    ShieldInput(
-                        shield_id="CodeScanner",
-                        provider_id="code-scanner",
-                    ),
-                ],
-                default_tool_groups=default_tool_groups,
-            ),
-        },
-        run_config_env_vars={
-            "LLAMA_STACK_PORT": (
-                "8321",
-                "Port for the Llama Stack distribution server",
-            ),
-            "OLLAMA_URL": (
-                "http://127.0.0.1:11434",
-                "URL of the Ollama server",
-            ),
-            "INFERENCE_MODEL": (
-                "meta-llama/Llama-3.2-3B-Instruct",
-                "Inference model loaded into the Ollama server",
-            ),
-            "SAFETY_MODEL": (
-                "meta-llama/Llama-Guard-3-1B",
-                "Safety model loaded into the Ollama server",
-            ),
-        },
-    )

llama_stack/templates/ollama/run-with-safety.yaml

@@ -1,158 +0,0 @@
-version: 2
-image_name: ollama
-apis:
-- agents
-- datasetio
-- eval
-- files
-- inference
-- post_training
-- safety
-- scoring
-- telemetry
-- tool_runtime
-- vector_io
-providers:
-  inference:
-  - provider_id: ollama
-    provider_type: remote::ollama
-    config:
-      url: ${env.OLLAMA_URL:=http://localhost:11434}
-      raise_on_connect_error: true
-  vector_io:
-  - provider_id: faiss
-    provider_type: inline::faiss
-    config:
-      kvstore:
-        type: sqlite
-        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/faiss_store.db
-  safety:
-  - provider_id: llama-guard
-    provider_type: inline::llama-guard
-    config: {}
-  - provider_id: code-scanner
-    provider_type: inline::code-scanner
-    config: {}
-  agents:
-  - provider_id: meta-reference
-    provider_type: inline::meta-reference
-    config:
-      persistence_store:
-        type: sqlite
-        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/agents_store.db
-      responses_store:
-        type: sqlite
-        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/responses_store.db
-  telemetry:
-  - provider_id: meta-reference
-    provider_type: inline::meta-reference
-    config:
-      service_name: "${env.OTEL_SERVICE_NAME:=\u200B}"
-      sinks: ${env.TELEMETRY_SINKS:=console,sqlite}
-      sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/trace_store.db
-  eval:
-  - provider_id: meta-reference
-    provider_type: inline::meta-reference
-    config:
-      kvstore:
-        type: sqlite
-        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/meta_reference_eval.db
-  datasetio:
-  - provider_id: huggingface
-    provider_type: remote::huggingface
-    config:
-      kvstore:
-        type: sqlite
-        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/huggingface_datasetio.db
-  - provider_id: localfs
-    provider_type: inline::localfs
-    config:
-      kvstore:
-        type: sqlite
-        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/localfs_datasetio.db
-  scoring:
-  - provider_id: basic
-    provider_type: inline::basic
-    config: {}
-  - provider_id: llm-as-judge
-    provider_type: inline::llm-as-judge
-    config: {}
-  - provider_id: braintrust
-    provider_type: inline::braintrust
-    config:
-      openai_api_key: ${env.OPENAI_API_KEY:=}
-  files:
-  - provider_id: meta-reference-files
-    provider_type: inline::localfs
-    config:
-      storage_dir: ${env.FILES_STORAGE_DIR:=~/.llama/distributions/ollama/files}
-      metadata_store:
-        type: sqlite
-        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/files_metadata.db
-  post_training:
-  - provider_id: huggingface
-    provider_type: inline::huggingface
-    config:
-      checkpoint_format: huggingface
-      distributed_backend: null
-      device: cpu
-  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
-    config: {}
-  - provider_id: model-context-protocol
-    provider_type: remote::model-context-protocol
-    config: {}
-  - provider_id: wolfram-alpha
-    provider_type: remote::wolfram-alpha
-    config:
-      api_key: ${env.WOLFRAM_ALPHA_API_KEY:=}
-metadata_store:
-  type: sqlite
-  db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/registry.db
-inference_store:
-  type: sqlite
-  db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/inference_store.db
-models:
-- metadata: {}
-  model_id: ${env.INFERENCE_MODEL}
-  provider_id: ollama
-  model_type: llm
-- metadata: {}
-  model_id: ${env.SAFETY_MODEL}
-  provider_id: ollama
-  model_type: llm
-- metadata:
-    embedding_dimension: 384
-  model_id: all-MiniLM-L6-v2
-  provider_id: ollama
-  provider_model_id: all-minilm:latest
-  model_type: embedding
-shields:
-- shield_id: ${env.SAFETY_MODEL}
-  provider_id: llama-guard
-- shield_id: CodeScanner
-  provider_id: code-scanner
-vector_dbs: []
-datasets: []
-scoring_fns: []
-benchmarks: []
-tool_groups:
-- toolgroup_id: builtin::websearch
-  provider_id: tavily-search
-- toolgroup_id: builtin::rag
-  provider_id: rag-runtime
-- toolgroup_id: builtin::wolfram_alpha
-  provider_id: wolfram-alpha
-server:
-  port: 8321

llama_stack/templates/ollama/run.yaml

@@ -1,148 +0,0 @@
-version: 2
-image_name: ollama
-apis:
-- agents
-- datasetio
-- eval
-- files
-- inference
-- post_training
-- safety
-- scoring
-- telemetry
-- tool_runtime
-- vector_io
-providers:
-  inference:
-  - provider_id: ollama
-    provider_type: remote::ollama
-    config:
-      url: ${env.OLLAMA_URL:=http://localhost:11434}
-      raise_on_connect_error: true
-  vector_io:
-  - provider_id: faiss
-    provider_type: inline::faiss
-    config:
-      kvstore:
-        type: sqlite
-        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/faiss_store.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/ollama}/agents_store.db
-      responses_store:
-        type: sqlite
-        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/responses_store.db
-  telemetry:
-  - provider_id: meta-reference
-    provider_type: inline::meta-reference
-    config:
-      service_name: "${env.OTEL_SERVICE_NAME:=\u200B}"
-      sinks: ${env.TELEMETRY_SINKS:=console,sqlite}
-      sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/trace_store.db
-  eval:
-  - provider_id: meta-reference
-    provider_type: inline::meta-reference
-    config:
-      kvstore:
-        type: sqlite
-        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/meta_reference_eval.db
-  datasetio:
-  - provider_id: huggingface
-    provider_type: remote::huggingface
-    config:
-      kvstore:
-        type: sqlite
-        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/huggingface_datasetio.db
-  - provider_id: localfs
-    provider_type: inline::localfs
-    config:
-      kvstore:
-        type: sqlite
-        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/localfs_datasetio.db
-  scoring:
-  - provider_id: basic
-    provider_type: inline::basic
-    config: {}
-  - provider_id: llm-as-judge
-    provider_type: inline::llm-as-judge
-    config: {}
-  - provider_id: braintrust
-    provider_type: inline::braintrust
-    config:
-      openai_api_key: ${env.OPENAI_API_KEY:=}
-  files:
-  - provider_id: meta-reference-files
-    provider_type: inline::localfs
-    config:
-      storage_dir: ${env.FILES_STORAGE_DIR:=~/.llama/distributions/ollama/files}
-      metadata_store:
-        type: sqlite
-        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/files_metadata.db
-  post_training:
-  - provider_id: huggingface
-    provider_type: inline::huggingface
-    config:
-      checkpoint_format: huggingface
-      distributed_backend: null
-      device: cpu
-  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
-    config: {}
-  - provider_id: model-context-protocol
-    provider_type: remote::model-context-protocol
-    config: {}
-  - provider_id: wolfram-alpha
-    provider_type: remote::wolfram-alpha
-    config:
-      api_key: ${env.WOLFRAM_ALPHA_API_KEY:=}
-metadata_store:
-  type: sqlite
-  db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/registry.db
-inference_store:
-  type: sqlite
-  db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/inference_store.db
-models:
-- metadata: {}
-  model_id: ${env.INFERENCE_MODEL}
-  provider_id: ollama
-  model_type: llm
-- metadata:
-    embedding_dimension: 384
-  model_id: all-MiniLM-L6-v2
-  provider_id: ollama
-  provider_model_id: all-minilm:latest
-  model_type: embedding
-shields: []
-vector_dbs: []
-datasets: []
-scoring_fns: []
-benchmarks: []
-tool_groups:
-- toolgroup_id: builtin::websearch
-  provider_id: tavily-search
-- toolgroup_id: builtin::rag
-  provider_id: rag-runtime
-- toolgroup_id: builtin::wolfram_alpha
-  provider_id: wolfram-alpha
-server:
-  port: 8321