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 .`
This commit is contained in:
Ashwin Bharambe 2025-10-27 12:02:21 -07:00 committed by GitHub
parent 98a5047f9d
commit 471b1b248b
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791 changed files with 2983 additions and 456 deletions

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# 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 .vector_stores import *

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# 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 typing import Literal
from pydantic import BaseModel
from llama_stack.apis.resource import Resource, ResourceType
# Internal resource type for storing the vector store routing and other information
class VectorStore(Resource):
"""Vector database resource for storing and querying vector embeddings.
:param type: Type of resource, always 'vector_store' for vector stores
:param embedding_model: Name of the embedding model to use for vector generation
:param embedding_dimension: Dimension of the embedding vectors
"""
type: Literal[ResourceType.vector_store] = ResourceType.vector_store
embedding_model: str
embedding_dimension: int
vector_store_name: str | None = None
@property
def vector_store_id(self) -> str:
return self.identifier
@property
def provider_vector_store_id(self) -> str | None:
return self.provider_resource_id
class VectorStoreInput(BaseModel):
"""Input parameters for creating or configuring a vector database.
:param vector_store_id: Unique identifier for the vector store
:param embedding_model: Name of the embedding model to use for vector generation
:param embedding_dimension: Dimension of the embedding vectors
:param provider_vector_store_id: (Optional) Provider-specific identifier for the vector store
"""
vector_store_id: str
embedding_model: str
embedding_dimension: int
provider_id: str | None = None
provider_vector_store_id: str | None = None