feat: split API and provider specs into separate llama-stack-api pkg (#3895)

# What does this PR do?

Extract API definitions and provider specifications into a standalone
llama-stack-api package that can be published to PyPI independently of
the main llama-stack server.


see: https://github.com/llamastack/llama-stack/pull/2978 and
https://github.com/llamastack/llama-stack/pull/2978#issuecomment-3145115942

Motivation

External providers currently import from llama-stack, which overrides
the installed version and causes dependency conflicts. This separation
allows external providers to:

- Install only the type definitions they need without server
dependencies
- Avoid version conflicts with the installed llama-stack package
- Be versioned and released independently

This enables us to re-enable external provider module tests that were
previously blocked by these import conflicts.

Changes

- Created llama-stack-api package with minimal dependencies (pydantic,
jsonschema)
- Moved APIs, providers datatypes, strong_typing, and schema_utils
- Updated all imports from llama_stack.* to llama_stack_api.*
- Configured local editable install for development workflow
- Updated linting and type-checking configuration for both packages

Next Steps

- Publish llama-stack-api to PyPI
- Update external provider dependencies
- Re-enable external provider module tests


Pre-cursor PRs to this one:

- #4093 
- #3954 
- #4064 

These PRs moved key pieces _out_ of the Api pkg, limiting the scope of
change here.


relates to #3237 

## Test Plan

Package builds successfully and can be imported independently. All
pre-commit hooks pass with expected exclusions maintained.

---------

Signed-off-by: Charlie Doern <cdoern@redhat.com>

docs/docs/concepts/apis/external.mdx

@@ -58,7 +58,7 @@ External APIs must expose a `available_providers()` function in their module tha
 
 ```python
 # llama_stack_api_weather/api.py
-from llama_stack.providers.datatypes import Api, InlineProviderSpec, ProviderSpec
+from llama_stack_api import Api, InlineProviderSpec, ProviderSpec
 
 
 def available_providers() -> list[ProviderSpec]:
@@ -79,7 +79,7 @@ A Protocol class like so:
 # llama_stack_api_weather/api.py
 from typing import Protocol
 
-from llama_stack.schema_utils import webmethod
+from llama_stack_api import webmethod
 
 
 class WeatherAPI(Protocol):
@@ -151,13 +151,12 @@ __all__ = ["WeatherAPI", "available_providers"]
 # llama-stack-api-weather/src/llama_stack_api_weather/weather.py
 from typing import Protocol
 
-from llama_stack.providers.datatypes import (
+from llama_stack_api import (
     Api,
     ProviderSpec,
     RemoteProviderSpec,
+    webmethod,
 )
-from llama_stack.schema_utils import webmethod
-
 
 def available_providers() -> list[ProviderSpec]:
     return [

docs/docs/distributions/building_distro.mdx

@@ -65,7 +65,7 @@ external_providers_dir: /workspace/providers.d
 Inside `providers.d/custom_ollama/provider.py`, define `get_provider_spec()` so the CLI can discover dependencies:
 
 ```python
-from llama_stack.providers.datatypes import ProviderSpec
+from llama_stack_api.providers.datatypes import ProviderSpec
 
 
 def get_provider_spec() -> ProviderSpec:

docs/docs/providers/external/external-providers-guide.mdx

@@ -80,7 +80,7 @@ container_image: custom-vector-store:latest  # optional
 All providers must contain a `get_provider_spec` function in their `provider` module. This is a standardized structure that Llama Stack expects and is necessary for getting things such as the config class. The `get_provider_spec` method returns a structure identical to the `adapter`. An example function may look like:
 
 ```python
-from llama_stack.providers.datatypes import (
+from llama_stack_api.providers.datatypes import (
     ProviderSpec,
     Api,
     RemoteProviderSpec,

docs/docs/providers/vector_io/inline_sqlite-vec.mdx

@@ -153,7 +153,7 @@ description: |
   Example using RAGQueryConfig with different search modes:
 
   ```python
-  from llama_stack.apis.tools import RAGQueryConfig, RRFRanker, WeightedRanker
+  from llama_stack_api import RAGQueryConfig, RRFRanker, WeightedRanker
 
   # Vector search
   config = RAGQueryConfig(mode="vector", max_chunks=5)
@@ -358,7 +358,7 @@ Two ranker types are supported:
 Example using RAGQueryConfig with different search modes:
 
 ```python
-from llama_stack.apis.tools import RAGQueryConfig, RRFRanker, WeightedRanker
+from llama_stack_api import RAGQueryConfig, RRFRanker, WeightedRanker
 
 # Vector search
 config = RAGQueryConfig(mode="vector", max_chunks=5)