forked from phoenix-oss/llama-stack-mirror
41 lines
1.3 KiB
Python
41 lines
1.3 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, Optional, Protocol
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from pydantic import BaseModel
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from pyopenapi import webmethod
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from strong_typing.schema import json_schema_type
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from llama_models.llama3_1.api.datatypes import * # noqa: F403
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from llama_toolchain.reward_scoring.api.datatypes import * # noqa: F403
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from .datatypes import * # noqa: F403
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@json_schema_type
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class SyntheticDataGenerationRequest(BaseModel):
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"""Request to generate synthetic data. A small batch of prompts and a filtering function"""
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dialogs: List[Message]
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filtering_function: FilteringFunction = FilteringFunction.none
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model: Optional[RewardModel] = None
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@json_schema_type
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class SyntheticDataGenerationResponse(BaseModel):
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"""Response from the synthetic data generation. Batch of (prompt, response, score) tuples that pass the threshold."""
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synthetic_data: List[ScoredDialogGenerations]
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statistics: Optional[Dict[str, Any]] = None
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class SyntheticDataGeneration(Protocol):
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@webmethod(route="/synthetic_data_generation/generate")
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def post_generate(
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self,
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request: SyntheticDataGenerationRequest,
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) -> Union[SyntheticDataGenerationResponse]: ...
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