mirror of
https://github.com/meta-llama/llama-stack.git
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8de8eb03c8
## What does this PR do?
This is a long-pending change and particularly important to get done
now.
Specifically:
- we cannot "localize" (aka download) any URLs from media attachments
anywhere near our modeling code. it must be done within llama-stack.
- `PIL.Image` is infesting all our APIs via `ImageMedia ->
InterleavedTextMedia` and that cannot be right at all. Anything in the
API surface must be "naturally serializable". We need a standard `{
type: "image", image_url: "<...>" }` which is more extensible
- `UserMessage`, `SystemMessage`, etc. are moved completely to
llama-stack from the llama-models repository.
See https://github.com/meta-llama/llama-models/pull/244 for the
corresponding PR in llama-models.
## Test Plan
```bash
cd llama_stack/providers/tests
pytest -s -v -k "fireworks or ollama or together" inference/test_vision_inference.py
pytest -s -v -k "(fireworks or ollama or together) and llama_3b" inference/test_text_inference.py
pytest -s -v -k chroma memory/test_memory.py \
--env EMBEDDING_DIMENSION=384 --env CHROMA_DB_PATH=/tmp/foobar
pytest -s -v -k fireworks agents/test_agents.py \
--safety-shield=meta-llama/Llama-Guard-3-8B \
--inference-model=meta-llama/Llama-3.1-8B-Instruct
```
Updated the client sdk (see PR ...), installed the SDK in the same
environment and then ran the SDK tests:
```bash
cd tests/client-sdk
LLAMA_STACK_CONFIG=together pytest -s -v agents/test_agents.py
LLAMA_STACK_CONFIG=ollama pytest -s -v memory/test_memory.py
# this one needed a bit of hacking in the run.yaml to ensure I could register the vision model correctly
INFERENCE_MODEL=llama3.2-vision:latest LLAMA_STACK_CONFIG=ollama pytest -s -v inference/test_inference.py
```
72 lines
2 KiB
Python
72 lines
2 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 Any, Dict, List, Literal, Optional, Protocol
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from llama_models.schema_utils import json_schema_type, webmethod
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from pydantic import BaseModel, Field
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from llama_stack.apis.common.content_types import URL
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from llama_stack.apis.common.type_system import ParamType
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from llama_stack.apis.resource import Resource, ResourceType
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class CommonDatasetFields(BaseModel):
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dataset_schema: Dict[str, ParamType]
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url: URL
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metadata: Dict[str, Any] = Field(
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default_factory=dict,
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description="Any additional metadata for this dataset",
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)
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@json_schema_type
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class Dataset(CommonDatasetFields, Resource):
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type: Literal[ResourceType.dataset.value] = ResourceType.dataset.value
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@property
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def dataset_id(self) -> str:
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return self.identifier
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@property
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def provider_dataset_id(self) -> str:
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return self.provider_resource_id
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class DatasetInput(CommonDatasetFields, BaseModel):
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dataset_id: str
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provider_id: Optional[str] = None
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provider_dataset_id: Optional[str] = None
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class Datasets(Protocol):
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@webmethod(route="/datasets/register", method="POST")
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async def register_dataset(
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self,
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dataset_id: str,
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dataset_schema: Dict[str, ParamType],
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url: URL,
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provider_dataset_id: Optional[str] = None,
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provider_id: Optional[str] = None,
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metadata: Optional[Dict[str, Any]] = None,
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) -> None: ...
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@webmethod(route="/datasets/get", method="GET")
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async def get_dataset(
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self,
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dataset_id: str,
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) -> Optional[Dataset]: ...
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@webmethod(route="/datasets/list", method="GET")
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async def list_datasets(self) -> List[Dataset]: ...
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@webmethod(route="/datasets/unregister", method="POST")
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async def unregister_dataset(
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self,
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dataset_id: str,
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) -> None: ...
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