chore(package): migrate to src/ layout (#3920)

Migrates package structure to src/ layout following Python packaging
best practices.

All code moved from `llama_stack/` to `src/llama_stack/`. Public API
unchanged - imports remain `import llama_stack.*`.

Updated build configs, pre-commit hooks, scripts, and GitHub workflows
accordingly. All hooks pass, package builds cleanly.

**Developer note**: Reinstall after pulling: `pip install -e .`

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

@@ -0,0 +1,122 @@
+# 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 collections.abc import AsyncIterator
+from typing import Any
+
+from llama_stack_client import AsyncLlamaStackClient
+
+from llama_stack.apis.inference import (
+    Inference,
+    OpenAIChatCompletion,
+    OpenAIChatCompletionChunk,
+    OpenAIChatCompletionRequestWithExtraBody,
+    OpenAICompletion,
+    OpenAICompletionRequestWithExtraBody,
+    OpenAIEmbeddingsRequestWithExtraBody,
+    OpenAIEmbeddingsResponse,
+)
+from llama_stack.apis.models import Model
+from llama_stack.core.library_client import convert_pydantic_to_json_value
+from llama_stack.providers.utils.inference.model_registry import ModelRegistryHelper
+
+from .config import PassthroughImplConfig
+
+
+class PassthroughInferenceAdapter(Inference):
+    def __init__(self, config: PassthroughImplConfig) -> None:
+        ModelRegistryHelper.__init__(self)
+        self.config = config
+
+    async def unregister_model(self, model_id: str) -> None:
+        pass
+
+    async def register_model(self, model: Model) -> Model:
+        return model
+
+    def _get_client(self) -> AsyncLlamaStackClient:
+        passthrough_url = None
+        passthrough_api_key = None
+        provider_data = None
+
+        if self.config.url is not None:
+            passthrough_url = self.config.url
+        else:
+            provider_data = self.get_request_provider_data()
+            if provider_data is None or not provider_data.passthrough_url:
+                raise ValueError(
+                    'Pass url of the passthrough endpoint in the header X-LlamaStack-Provider-Data as { "passthrough_url": <your passthrough url>}'
+                )
+            passthrough_url = provider_data.passthrough_url
+
+        if self.config.api_key is not None:
+            passthrough_api_key = self.config.api_key.get_secret_value()
+        else:
+            provider_data = self.get_request_provider_data()
+            if provider_data is None or not provider_data.passthrough_api_key:
+                raise ValueError(
+                    'Pass API Key for the passthrough endpoint in the header X-LlamaStack-Provider-Data as { "passthrough_api_key": <your api key>}'
+                )
+            passthrough_api_key = provider_data.passthrough_api_key
+
+        return AsyncLlamaStackClient(
+            base_url=passthrough_url,
+            api_key=passthrough_api_key,
+            provider_data=provider_data,
+        )
+
+    async def openai_embeddings(
+        self,
+        params: OpenAIEmbeddingsRequestWithExtraBody,
+    ) -> OpenAIEmbeddingsResponse:
+        raise NotImplementedError()
+
+    async def openai_completion(
+        self,
+        params: OpenAICompletionRequestWithExtraBody,
+    ) -> OpenAICompletion:
+        client = self._get_client()
+        model_obj = await self.model_store.get_model(params.model)
+
+        params = params.model_copy()
+        params.model = model_obj.provider_resource_id
+
+        request_params = params.model_dump(exclude_none=True)
+
+        return await client.inference.openai_completion(**request_params)
+
+    async def openai_chat_completion(
+        self,
+        params: OpenAIChatCompletionRequestWithExtraBody,
+    ) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
+        client = self._get_client()
+        model_obj = await self.model_store.get_model(params.model)
+
+        params = params.model_copy()
+        params.model = model_obj.provider_resource_id
+
+        request_params = params.model_dump(exclude_none=True)
+
+        return await client.inference.openai_chat_completion(**request_params)
+
+    def cast_value_to_json_dict(self, request_params: dict[str, Any]) -> dict[str, Any]:
+        json_params = {}
+        for key, value in request_params.items():
+            json_input = convert_pydantic_to_json_value(value)
+            if isinstance(json_input, dict):
+                json_input = {k: v for k, v in json_input.items() if v is not None}
+            elif isinstance(json_input, list):
+                json_input = [x for x in json_input if x is not None]
+                new_input = []
+                for x in json_input:
+                    if isinstance(x, dict):
+                        x = {k: v for k, v in x.items() if v is not None}
+                    new_input.append(x)
+                json_input = new_input
+
+            json_params[key] = json_input
+
+        return json_params