fix: Some missed env variable changes from PR 2490 (#2538)

# What does this PR do?

Some templates were still using the old environment variable substition
syntax instead of the new one and were not getting substituted properly.

Also, some places didn't handle the new None vs old empty string ("")
values that come from the conditional environment variable substitution.

This gets the starter and remote-vllm distributions starting again, and
I tested various permutations of the starter as chroma and pgvector
needed some adjustments to their config classes to handle the new
possible `None` values. And, I had to tweak our `Provider` class to also
handle `None` values, for cases where we disable providers in the
starter config via environment variables.

This may not have caught everything that was missed, but I did grep
around quite a bit to try and find anything lingering.

## Test Plan

The following permutations now all run (or attempt to run to the point
of complaining that they can't connect to chroma, vllm, etc) when before
they failed immediately on startup because of bad environment variable
substitions:

```
uv run llama stack run llama_stack/templates/starter/run.yaml
ENABLE_SQLITE_VEC=true uv run llama stack run llama_stack/templates/starter/run.yaml
ENABLE_PGVECTOR=true uv run llama stack run llama_stack/templates/starter/run.yaml
ENABLE_CHROMADB=true uv run llama stack run llama_stack/templates/starter/run.yaml

uv run llama stack run llama_stack/templates/remote-vllm/run.yaml
```
<!-- Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.* -->

Signed-off-by: Ben Browning <bbrownin@redhat.com>
Co-authored-by: raghotham <rsm@meta.com>

llama_stack/distribution/datatypes.py

@@ -146,7 +146,9 @@ in the runtime configuration to help route to the correct provider.""",
 
 
 class Provider(BaseModel):
-    provider_id: str
+    # provider_id of None means that the provider is not enabled - this happens
+    # when the provider is enabled via a conditional environment variable
+    provider_id: str | None
     provider_type: str
     config: dict[str, Any]
 

llama_stack/distribution/providers.py

@@ -48,6 +48,9 @@ class ProviderImpl(Providers):
         ret = []
         for api, providers in safe_config.providers.items():
             for p in providers:
+                # Skip providers that are not enabled
+                if p.provider_id is None:
+                    continue
                 ret.append(
                     ProviderInfo(
                         api=api,

llama_stack/distribution/resolver.py

@@ -255,6 +255,10 @@ async def instantiate_providers(
     impls: dict[Api, Any] = {}
     inner_impls_by_provider_id: dict[str, dict[str, Any]] = {f"inner-{x.value}": {} for x in router_apis}
     for api_str, provider in sorted_providers:
+        # Skip providers that are not enabled
+        if provider.provider_id is None:
+            continue
+
         deps = {a: impls[a] for a in provider.spec.api_dependencies}
         for a in provider.spec.optional_api_dependencies:
             if a in impls:

llama_stack/providers/remote/vector_io/chroma/chroma.py

@@ -137,6 +137,9 @@ class ChromaVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
 
     async def initialize(self) -> None:
         if isinstance(self.config, RemoteChromaVectorIOConfig):
+            if not self.config.url:
+                raise ValueError("URL is a required parameter for the remote Chroma provider's config")
+
             log.info(f"Connecting to Chroma server at: {self.config.url}")
             url = self.config.url.rstrip("/")
             parsed = urlparse(url)

llama_stack/providers/remote/vector_io/chroma/config.py

@@ -10,7 +10,7 @@ from pydantic import BaseModel
 
 
 class ChromaVectorIOConfig(BaseModel):
-    url: str
+    url: str | None
 
     @classmethod
     def sample_run_config(cls, url: str = "${env.CHROMADB_URL}", **kwargs: Any) -> dict[str, Any]:

llama_stack/providers/remote/vector_io/pgvector/config.py

@@ -13,11 +13,11 @@ from llama_stack.schema_utils import json_schema_type
 
 @json_schema_type
 class PGVectorVectorIOConfig(BaseModel):
-    host: str = Field(default="localhost")
-    port: int = Field(default=5432)
-    db: str = Field(default="postgres")
-    user: str = Field(default="postgres")
-    password: str = Field(default="mysecretpassword")
+    host: str | None = Field(default="localhost")
+    port: int | None = Field(default=5432)
+    db: str | None = Field(default="postgres")
+    user: str | None = Field(default="postgres")
+    password: str | None = Field(default="mysecretpassword")
 
     @classmethod
     def sample_run_config(

llama_stack/templates/experimental-post-training/run.yaml

@@ -24,7 +24,7 @@ providers:
   - provider_id: ollama
     provider_type: remote::ollama
     config:
-      url: ${env.OLLAMA_URL:http://localhost:11434}
+      url: ${env.OLLAMA_URL:=http://localhost:11434}
   eval:
   - provider_id: meta-reference
     provider_type: inline::meta-reference
@@ -32,7 +32,7 @@ providers:
       kvstore:
         type: sqlite
         namespace: null
-        db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/meta-reference-gpu}/meta_reference_eval.db
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/meta-reference-gpu}/meta_reference_eval.db
   scoring:
   - provider_id: basic
     provider_type: inline::basic
@@ -40,7 +40,7 @@ providers:
   - provider_id: braintrust
     provider_type: inline::braintrust
     config:
-      openai_api_key: ${env.OPENAI_API_KEY:}
+      openai_api_key: ${env.OPENAI_API_KEY:+}
   datasetio:
   - provider_id: localfs
     provider_type: inline::localfs
@@ -48,14 +48,14 @@ providers:
       kvstore:
         type: sqlite
         namespace: null
-        db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/experimental-post-training}/localfs_datasetio.db
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/experimental-post-training}/localfs_datasetio.db
   - provider_id: huggingface
     provider_type: remote::huggingface
     config:
       kvstore:
         type: sqlite
         namespace: null
-        db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/huggingface}/huggingface_datasetio.db
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/huggingface}/huggingface_datasetio.db
   telemetry:
   - provider_id: meta-reference
     provider_type: inline::meta-reference
@@ -74,7 +74,7 @@ providers:
       persistence_store:
         type: sqlite
         namespace: null
-        db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/experimental-post-training}/agents_store.db
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/experimental-post-training}/agents_store.db
   safety:
   - provider_id: llama-guard
     provider_type: inline::llama-guard
@@ -86,19 +86,19 @@ providers:
       kvstore:
         type: sqlite
         namespace: null
-        db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/experimental-post-training}/faiss_store.db
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/experimental-post-training}/faiss_store.db
   tool_runtime:
   - provider_id: brave-search
     provider_type: remote::brave-search
     config:
-      api_key: ${env.BRAVE_SEARCH_API_KEY:}
+      api_key: ${env.BRAVE_SEARCH_API_KEY:+}
       max_results: 3
 
 
 metadata_store:
   namespace: null
   type: sqlite
-  db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/experimental-post-training}/registry.db
+  db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/experimental-post-training}/registry.db
 models: []
 shields: []
 vector_dbs: []

llama_stack/templates/meta-reference-gpu/meta_reference.py

@@ -46,7 +46,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="inline::meta-reference",
         config=MetaReferenceInferenceConfig.sample_run_config(
             model="${env.INFERENCE_MODEL}",
-            checkpoint_dir="${env.INFERENCE_CHECKPOINT_DIR:null}",
+            checkpoint_dir="${env.INFERENCE_CHECKPOINT_DIR:=null}",
         ),
     )
     embedding_provider = Provider(
@@ -112,7 +112,7 @@ def get_distribution_template() -> DistributionTemplate:
                             provider_type="inline::meta-reference",
                             config=MetaReferenceInferenceConfig.sample_run_config(
                                 model="${env.SAFETY_MODEL}",
-                                checkpoint_dir="${env.SAFETY_CHECKPOINT_DIR:null}",
+                                checkpoint_dir="${env.SAFETY_CHECKPOINT_DIR:=null}",
                             ),
                         ),
                     ],

llama_stack/templates/meta-reference-gpu/run-with-safety.yaml

@@ -16,7 +16,7 @@ providers:
     provider_type: inline::meta-reference
     config:
       model: ${env.INFERENCE_MODEL}
-      checkpoint_dir: ${env.INFERENCE_CHECKPOINT_DIR:null}
+      checkpoint_dir: ${env.INFERENCE_CHECKPOINT_DIR:=null}
       quantization:
         type: ${env.QUANTIZATION_TYPE:=bf16}
       model_parallel_size: ${env.MODEL_PARALLEL_SIZE:=0}
@@ -29,7 +29,7 @@ providers:
     provider_type: inline::meta-reference
     config:
       model: ${env.SAFETY_MODEL}
-      checkpoint_dir: ${env.SAFETY_CHECKPOINT_DIR:null}
+      checkpoint_dir: ${env.SAFETY_CHECKPOINT_DIR:=null}
       quantization:
         type: ${env.QUANTIZATION_TYPE:=bf16}
       model_parallel_size: ${env.MODEL_PARALLEL_SIZE:=0}

llama_stack/templates/meta-reference-gpu/run.yaml

@@ -16,7 +16,7 @@ providers:
     provider_type: inline::meta-reference
     config:
       model: ${env.INFERENCE_MODEL}
-      checkpoint_dir: ${env.INFERENCE_CHECKPOINT_DIR:null}
+      checkpoint_dir: ${env.INFERENCE_CHECKPOINT_DIR:=null}
       quantization:
         type: ${env.QUANTIZATION_TYPE:=bf16}
       model_parallel_size: ${env.MODEL_PARALLEL_SIZE:=0}

llama_stack/templates/open-benchmark/open_benchmark.py

@@ -46,7 +46,7 @@ def get_inference_providers() -> tuple[list[Provider], dict[str, list[ProviderMo
                     model_type=ModelType.llm,
                 )
             ],
-            OpenAIConfig.sample_run_config(api_key="${env.OPENAI_API_KEY:}"),
+            OpenAIConfig.sample_run_config(api_key="${env.OPENAI_API_KEY:+}"),
         ),
         (
             "anthropic",
@@ -56,7 +56,7 @@ def get_inference_providers() -> tuple[list[Provider], dict[str, list[ProviderMo
                     model_type=ModelType.llm,
                 )
             ],
-            AnthropicConfig.sample_run_config(api_key="${env.ANTHROPIC_API_KEY:}"),
+            AnthropicConfig.sample_run_config(api_key="${env.ANTHROPIC_API_KEY:+}"),
         ),
         (
             "gemini",
@@ -66,17 +66,17 @@ def get_inference_providers() -> tuple[list[Provider], dict[str, list[ProviderMo
                     model_type=ModelType.llm,
                 )
             ],
-            GeminiConfig.sample_run_config(api_key="${env.GEMINI_API_KEY:}"),
+            GeminiConfig.sample_run_config(api_key="${env.GEMINI_API_KEY:+}"),
         ),
         (
             "groq",
             [],
-            GroqConfig.sample_run_config(api_key="${env.GROQ_API_KEY:}"),
+            GroqConfig.sample_run_config(api_key="${env.GROQ_API_KEY:+}"),
         ),
         (
             "together",
             [],
-            TogetherImplConfig.sample_run_config(api_key="${env.TOGETHER_API_KEY:}"),
+            TogetherImplConfig.sample_run_config(api_key="${env.TOGETHER_API_KEY:+}"),
         ),
     ]
     inference_providers = []

llama_stack/templates/open-benchmark/run.yaml

@@ -15,20 +15,20 @@ providers:
   - provider_id: openai
     provider_type: remote::openai
     config:
-      api_key: ${env.OPENAI_API_KEY:}
+      api_key: ${env.OPENAI_API_KEY:+}
   - provider_id: anthropic
     provider_type: remote::anthropic
     config:
-      api_key: ${env.ANTHROPIC_API_KEY:}
+      api_key: ${env.ANTHROPIC_API_KEY:+}
   - provider_id: gemini
     provider_type: remote::gemini
     config:
-      api_key: ${env.GEMINI_API_KEY:}
+      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:}
+      api_key: ${env.GROQ_API_KEY:+}
   - provider_id: together
     provider_type: remote::together
     config:

llama_stack/templates/postgres-demo/postgres_demo.py

@@ -29,7 +29,7 @@ def get_distribution_template() -> DistributionTemplate:
             provider_id="vllm-inference",
             provider_type="remote::vllm",
             config=VLLMInferenceAdapterConfig.sample_run_config(
-                url="${env.VLLM_URL:http://localhost:8000/v1}",
+                url="${env.VLLM_URL:=http://localhost:8000/v1}",
             ),
         ),
     ]

llama_stack/templates/postgres-demo/run.yaml

@@ -12,7 +12,7 @@ providers:
   - provider_id: vllm-inference
     provider_type: remote::vllm
     config:
-      url: ${env.VLLM_URL:http://localhost:8000/v1}
+      url: ${env.VLLM_URL:=http://localhost:8000/v1}
       max_tokens: ${env.VLLM_MAX_TOKENS:=4096}
       api_token: ${env.VLLM_API_TOKEN:=fake}
       tls_verify: ${env.VLLM_TLS_VERIFY:=true}

llama_stack/templates/remote-vllm/run-with-safety.yaml

@@ -15,7 +15,7 @@ providers:
   - provider_id: vllm-inference
     provider_type: remote::vllm
     config:
-      url: ${env.VLLM_URL:http://localhost:8000/v1}
+      url: ${env.VLLM_URL:=http://localhost:8000/v1}
       max_tokens: ${env.VLLM_MAX_TOKENS:=4096}
       api_token: ${env.VLLM_API_TOKEN:=fake}
       tls_verify: ${env.VLLM_TLS_VERIFY:=true}

llama_stack/templates/remote-vllm/run.yaml

@@ -15,7 +15,7 @@ providers:
   - provider_id: vllm-inference
     provider_type: remote::vllm
     config:
-      url: ${env.VLLM_URL:http://localhost:8000/v1}
+      url: ${env.VLLM_URL:=http://localhost:8000/v1}
       max_tokens: ${env.VLLM_MAX_TOKENS:=4096}
       api_token: ${env.VLLM_API_TOKEN:=fake}
       tls_verify: ${env.VLLM_TLS_VERIFY:=true}

llama_stack/templates/remote-vllm/vllm.py

@@ -44,7 +44,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_id="vllm-inference",
         provider_type="remote::vllm",
         config=VLLMInferenceAdapterConfig.sample_run_config(
-            url="${env.VLLM_URL:http://localhost:8000/v1}",
+            url="${env.VLLM_URL:=http://localhost:8000/v1}",
         ),
     )
     embedding_provider = Provider(

llama_stack/templates/starter/run.yaml

@@ -68,7 +68,7 @@ providers:
         type: sqlite
         namespace: null
         db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/faiss_store.db
-  - provider_id: ${env.ENABLE_SQLITE_VEC+sqlite-vec}
+  - provider_id: ${env.ENABLE_SQLITE_VEC:+sqlite-vec}
     provider_type: inline::sqlite-vec
     config:
       db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/sqlite_vec.db

llama_stack/templates/starter/starter.py

@@ -175,7 +175,7 @@ def get_distribution_template() -> DistributionTemplate:
             config=FaissVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
         ),
         Provider(
-            provider_id="${env.ENABLE_SQLITE_VEC+sqlite-vec}",
+            provider_id="${env.ENABLE_SQLITE_VEC:+sqlite-vec}",
             provider_type="inline::sqlite-vec",
             config=SQLiteVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
         ),