llama-stack/llama_stack/apis/synthetic_data_generation/synthetic_data_generation.py
Ihar Hrachyshka 9e6561a1ec
chore: enable pyupgrade fixes (#1806)
# What does this PR do?

The goal of this PR is code base modernization.

Schema reflection code needed a minor adjustment to handle UnionTypes
and collections.abc.AsyncIterator. (Both are preferred for latest Python
releases.)

Note to reviewers: almost all changes here are automatically generated
by pyupgrade. Some additional unused imports were cleaned up. The only
change worth of note can be found under `docs/openapi_generator` and
`llama_stack/strong_typing/schema.py` where reflection code was updated
to deal with "newer" types.

Signed-off-by: Ihar Hrachyshka <ihar.hrachyshka@gmail.com>
2025-05-01 14:23:50 -07:00

51 lines
1.5 KiB
Python

# 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 enum import Enum
from typing import Any, Protocol
from pydantic import BaseModel
from llama_stack.apis.inference import Message
from llama_stack.schema_utils import json_schema_type, webmethod
class FilteringFunction(Enum):
"""The type of filtering function."""
none = "none"
random = "random"
top_k = "top_k"
top_p = "top_p"
top_k_top_p = "top_k_top_p"
sigmoid = "sigmoid"
@json_schema_type
class SyntheticDataGenerationRequest(BaseModel):
"""Request to generate synthetic data. A small batch of prompts and a filtering function"""
dialogs: list[Message]
filtering_function: FilteringFunction = FilteringFunction.none
model: str | None = None
@json_schema_type
class SyntheticDataGenerationResponse(BaseModel):
"""Response from the synthetic data generation. Batch of (prompt, response, score) tuples that pass the threshold."""
synthetic_data: list[dict[str, Any]]
statistics: dict[str, Any] | None = None
class SyntheticDataGeneration(Protocol):
@webmethod(route="/synthetic-data-generation/generate")
def synthetic_data_generate(
self,
dialogs: list[Message],
filtering_function: FilteringFunction = FilteringFunction.none,
model: str | None = None,
) -> SyntheticDataGenerationResponse: ...