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>

src/llama_stack/core/stack.py

@@ -12,27 +12,31 @@ import tempfile
 from typing import Any
 
 import yaml
+from llama_stack_api import (
+    Agents,
+    Api,
+    Batches,
+    Benchmarks,
+    Conversations,
+    DatasetIO,
+    Datasets,
+    Eval,
+    Files,
+    Inference,
+    Inspect,
+    Models,
+    PostTraining,
+    Prompts,
+    Providers,
+    Safety,
+    Scoring,
+    ScoringFunctions,
+    Shields,
+    ToolGroups,
+    ToolRuntime,
+    VectorIO,
+)
 
-from llama_stack.apis.agents import Agents
-from llama_stack.apis.batches import Batches
-from llama_stack.apis.benchmarks import Benchmarks
-from llama_stack.apis.conversations import Conversations
-from llama_stack.apis.datasetio import DatasetIO
-from llama_stack.apis.datasets import Datasets
-from llama_stack.apis.eval import Eval
-from llama_stack.apis.files import Files
-from llama_stack.apis.inference import Inference
-from llama_stack.apis.inspect import Inspect
-from llama_stack.apis.models import Models
-from llama_stack.apis.post_training import PostTraining
-from llama_stack.apis.prompts import Prompts
-from llama_stack.apis.providers import Providers
-from llama_stack.apis.safety import Safety
-from llama_stack.apis.scoring import Scoring
-from llama_stack.apis.scoring_functions import ScoringFunctions
-from llama_stack.apis.shields import Shields
-from llama_stack.apis.tools import ToolGroups, ToolRuntime
-from llama_stack.apis.vector_io import VectorIO
 from llama_stack.core.conversations.conversations import ConversationServiceConfig, ConversationServiceImpl
 from llama_stack.core.datatypes import Provider, SafetyConfig, StackRunConfig, VectorStoresConfig
 from llama_stack.core.distribution import get_provider_registry
@@ -54,7 +58,6 @@ from llama_stack.core.storage.datatypes import (
 from llama_stack.core.store.registry import create_dist_registry
 from llama_stack.core.utils.dynamic import instantiate_class_type
 from llama_stack.log import get_logger
-from llama_stack.providers.datatypes import Api
 
 logger = get_logger(name=__name__, category="core")