feat: consolidate most distros into "starter"

* 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: #2502
Signed-off-by: Sébastien Han <seb@redhat.com>

llama_stack/providers/remote/inference/cerebras/config.py

@@ -26,8 +26,8 @@ class CerebrasImplConfig(BaseModel):
     )
 
     @classmethod
-    def sample_run_config(cls, **kwargs) -> dict[str, Any]:
+    def sample_run_config(cls, api_key: str = "${env.CEREBRAS_API_KEY}", **kwargs) -> dict[str, Any]:
         return {
             "base_url": DEFAULT_BASE_URL,
-            "api_key": "${env.CEREBRAS_API_KEY}",
+            "api_key": api_key,
         }

llama_stack/providers/remote/inference/llama_openai_compat/config.py

@@ -31,7 +31,7 @@ class LlamaCompatConfig(BaseModel):
     )
 
     @classmethod
-    def sample_run_config(cls, api_key: str = "${env.LLAMA_API_KEY}", **kwargs) -> dict[str, Any]:
+    def sample_run_config(cls, api_key: str = "${env.LLAMA_API_KEY:}", **kwargs) -> dict[str, Any]:
         return {
             "openai_compat_api_base": "https://api.llama.com/compat/v1/",
             "api_key": api_key,

llama_stack/providers/remote/inference/nvidia/config.py

@@ -53,9 +53,15 @@ class NVIDIAConfig(BaseModel):
     )
 
     @classmethod
-    def sample_run_config(cls, **kwargs) -> dict[str, Any]:
+    def sample_run_config(
+        cls,
+        url: str = "${env.NVIDIA_BASE_URL:=https://integrate.api.nvidia.com}",
+        api_key: str = "${env.NVIDIA_API_KEY:+}",
+        append_api_version: bool = "${env.NVIDIA_APPEND_API_VERSION:=True}",
+        **kwargs,
+    ) -> dict[str, Any]:
         return {
-            "url": "${env.NVIDIA_BASE_URL:=https://integrate.api.nvidia.com}",
-            "api_key": "${env.NVIDIA_API_KEY:+}",
-            "append_api_version": "${env.NVIDIA_APPEND_API_VERSION:=True}",
+            "url": url,
+            "api_key": api_key,
+            "append_api_version": append_api_version,
         }

llama_stack/providers/remote/inference/ollama/config.py

@@ -13,13 +13,9 @@ DEFAULT_OLLAMA_URL = "http://localhost:11434"
 
 class OllamaImplConfig(BaseModel):
     url: str = DEFAULT_OLLAMA_URL
-    raise_on_connect_error: bool = True
 
     @classmethod
-    def sample_run_config(
-        cls, url: str = "${env.OLLAMA_URL:=http://localhost:11434}", raise_on_connect_error: bool = True, **kwargs
-    ) -> dict[str, Any]:
+    def sample_run_config(cls, url: str = "${env.OLLAMA_URL:=http://localhost:11434}", **kwargs) -> dict[str, Any]:
         return {
             "url": url,
-            "raise_on_connect_error": raise_on_connect_error,
         }

llama_stack/providers/remote/inference/ollama/ollama.py

@@ -91,7 +91,6 @@ class OllamaInferenceAdapter(
     def __init__(self, config: OllamaImplConfig) -> None:
         self.register_helper = ModelRegistryHelper(MODEL_ENTRIES)
         self.url = config.url
-        self.raise_on_connect_error = config.raise_on_connect_error
 
     @property
     def client(self) -> AsyncClient:
@@ -105,10 +104,7 @@ class OllamaInferenceAdapter(
         logger.debug(f"checking connectivity to Ollama at `{self.url}`...")
         health_response = await self.health()
         if health_response["status"] == HealthStatus.ERROR:
-            if self.raise_on_connect_error:
-                raise RuntimeError("Ollama Server is not running, start it using `ollama serve` in a separate terminal")
-            else:
-                logger.warning("Ollama Server is not running, start it using `ollama serve` in a separate terminal")
+            raise RuntimeError("Ollama Server is not running, start it using `ollama serve` in a separate terminal")
 
     async def health(self) -> HealthResponse:
         """

llama_stack/providers/remote/inference/passthrough/config.py

@@ -24,8 +24,10 @@ class PassthroughImplConfig(BaseModel):
     )
 
     @classmethod
-    def sample_run_config(cls, **kwargs) -> dict[str, Any]:
+    def sample_run_config(
+        cls, url: str = "${env.PASSTHROUGH_URL}", api_key: str = "${env.PASSTHROUGH_API_KEY}", **kwargs
+    ) -> dict[str, Any]:
         return {
-            "url": "${env.PASSTHROUGH_URL}",
-            "api_key": "${env.PASSTHROUGH_API_KEY}",
+            "url": url,
+            "api_key": api_key,
         }

llama_stack/providers/remote/inference/tgi/config.py

@@ -17,7 +17,11 @@ class TGIImplConfig(BaseModel):
     )
 
     @classmethod
-    def sample_run_config(cls, url: str = "${env.TGI_URL}", **kwargs):
+    def sample_run_config(
+        cls,
+        url: str = "${env.TGI_URL}",
+        **kwargs,
+    ):
         return {
             "url": url,
         }

llama_stack/providers/remote/inference/tgi/tgi.py

@@ -327,7 +327,6 @@ class InferenceEndpointAdapter(_HfAdapter):
         # Get the inference endpoint details
         api = HfApi(token=config.api_token.get_secret_value())
         endpoint = api.get_inference_endpoint(config.endpoint_name)
-
         # Wait for the endpoint to be ready (if not already)
         endpoint.wait(timeout=60)