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/together/together.py

@@ -0,0 +1,102 @@
+# 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 Iterable
+
+from together import AsyncTogether
+from together.constants import BASE_URL
+
+from llama_stack.apis.inference import (
+    OpenAIEmbeddingsRequestWithExtraBody,
+    OpenAIEmbeddingsResponse,
+)
+from llama_stack.apis.inference.inference import OpenAIEmbeddingUsage
+from llama_stack.apis.models import Model
+from llama_stack.core.request_headers import NeedsRequestProviderData
+from llama_stack.log import get_logger
+from llama_stack.providers.utils.inference.openai_mixin import OpenAIMixin
+
+from .config import TogetherImplConfig
+
+logger = get_logger(name=__name__, category="inference::together")
+
+
+class TogetherInferenceAdapter(OpenAIMixin, NeedsRequestProviderData):
+    config: TogetherImplConfig
+
+    embedding_model_metadata: dict[str, dict[str, int]] = {
+        "togethercomputer/m2-bert-80M-32k-retrieval": {"embedding_dimension": 768, "context_length": 32768},
+        "BAAI/bge-large-en-v1.5": {"embedding_dimension": 1024, "context_length": 512},
+        "BAAI/bge-base-en-v1.5": {"embedding_dimension": 768, "context_length": 512},
+        "Alibaba-NLP/gte-modernbert-base": {"embedding_dimension": 768, "context_length": 8192},
+        "intfloat/multilingual-e5-large-instruct": {"embedding_dimension": 1024, "context_length": 512},
+    }
+
+    _model_cache: dict[str, Model] = {}
+
+    provider_data_api_key_field: str = "together_api_key"
+
+    def get_base_url(self):
+        return BASE_URL
+
+    def _get_client(self) -> AsyncTogether:
+        together_api_key = None
+        config_api_key = self.config.auth_credential.get_secret_value() if self.config.auth_credential else None
+        if config_api_key:
+            together_api_key = config_api_key
+        else:
+            provider_data = self.get_request_provider_data()
+            if provider_data is None or not provider_data.together_api_key:
+                raise ValueError(
+                    'Pass Together API Key in the header X-LlamaStack-Provider-Data as { "together_api_key": <your api key>}'
+                )
+            together_api_key = provider_data.together_api_key
+        return AsyncTogether(api_key=together_api_key)
+
+    async def list_provider_model_ids(self) -> Iterable[str]:
+        # Together's /v1/models is not compatible with OpenAI's /v1/models. Together support ticket #13355 -> will not fix, use Together's own client
+        return [m.id for m in await self._get_client().models.list()]
+
+    async def openai_embeddings(
+        self,
+        params: OpenAIEmbeddingsRequestWithExtraBody,
+    ) -> OpenAIEmbeddingsResponse:
+        """
+        Together's OpenAI-compatible embeddings endpoint is not compatible with
+        the standard OpenAI embeddings endpoint.
+
+        The endpoint -
+         - not all models return usage information
+         - does not support user param, returns 400 Unrecognized request arguments supplied: user
+         - does not support dimensions param, returns 400 Unrecognized request arguments supplied: dimensions
+        """
+        # Together support ticket #13332 -> will not fix
+        if params.user is not None:
+            raise ValueError("Together's embeddings endpoint does not support user param.")
+        # Together support ticket #13333 -> escalated
+        if params.dimensions is not None:
+            raise ValueError("Together's embeddings endpoint does not support dimensions param.")
+
+        response = await self.client.embeddings.create(
+            model=await self._get_provider_model_id(params.model),
+            input=params.input,
+            encoding_format=params.encoding_format,
+        )
+
+        response.model = (
+            params.model
+        )  # return the user the same model id they provided, avoid exposing the provider model id
+
+        # Together support ticket #13330 -> escalated
+        #  - togethercomputer/m2-bert-80M-32k-retrieval *does not* return usage information
+        if not hasattr(response, "usage") or response.usage is None:
+            logger.warning(
+                f"Together's embedding endpoint for {params.model} did not return usage information, substituting -1s."
+            )
+            response.usage = OpenAIEmbeddingUsage(prompt_tokens=-1, total_tokens=-1)
+
+        return response  # type: ignore[no-any-return]