forked from phoenix-oss/llama-stack-mirror
314ee09ae3
llama-models should have extremely minimal cruft. Its sole purpose should be didactic -- show the simplest implementation of the llama models and document the prompt formats, etc. This PR is the complement to https://github.com/meta-llama/llama-models/pull/279 ## Test Plan Ensure all `llama` CLI `model` sub-commands work: ```bash llama model list llama model download --model-id ... llama model prompt-format -m ... ``` Ran tests: ```bash cd tests/client-sdk LLAMA_STACK_CONFIG=fireworks pytest -s -v inference/ LLAMA_STACK_CONFIG=fireworks pytest -s -v vector_io/ LLAMA_STACK_CONFIG=fireworks pytest -s -v agents/ ``` Create a fresh venv `uv venv && source .venv/bin/activate` and run `llama stack build --template fireworks --image-type venv` followed by `llama stack run together --image-type venv` <-- the server runs Also checked that the OpenAPI generator can run and there is no change in the generated files as a result. ```bash cd docs/openapi_generator sh run_openapi_generator.sh ```
66 lines
1.9 KiB
Python
66 lines
1.9 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from typing import List, Literal, Optional, Protocol, runtime_checkable
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from pydantic import BaseModel
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from llama_stack.apis.resource import Resource, ResourceType
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from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
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from llama_stack.schema_utils import json_schema_type, webmethod
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@json_schema_type
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class VectorDB(Resource):
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type: Literal[ResourceType.vector_db.value] = ResourceType.vector_db.value
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embedding_model: str
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embedding_dimension: int
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@property
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def vector_db_id(self) -> str:
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return self.identifier
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@property
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def provider_vector_db_id(self) -> str:
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return self.provider_resource_id
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class VectorDBInput(BaseModel):
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vector_db_id: str
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embedding_model: str
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embedding_dimension: int
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provider_vector_db_id: Optional[str] = None
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class ListVectorDBsResponse(BaseModel):
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data: List[VectorDB]
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@runtime_checkable
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@trace_protocol
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class VectorDBs(Protocol):
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@webmethod(route="/vector-dbs", method="GET")
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async def list_vector_dbs(self) -> ListVectorDBsResponse: ...
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@webmethod(route="/vector-dbs/{vector_db_id:path}", method="GET")
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async def get_vector_db(
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self,
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vector_db_id: str,
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) -> Optional[VectorDB]: ...
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@webmethod(route="/vector-dbs", method="POST")
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async def register_vector_db(
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self,
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vector_db_id: str,
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embedding_model: str,
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embedding_dimension: Optional[int] = 384,
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provider_id: Optional[str] = None,
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provider_vector_db_id: Optional[str] = None,
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) -> VectorDB: ...
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@webmethod(route="/vector-dbs/{vector_db_id:path}", method="DELETE")
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async def unregister_vector_db(self, vector_db_id: str) -> None: ...
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