Codemod from llama_toolchain -> llama_stack

- added providers/registry
- cleaned up api/ subdirectories and moved impls away
- restructured api/api.py
- from llama_stack.apis.<api> import foo should work now
- update imports to do llama_stack.apis.<api>
- update many other imports
- added __init__, fixed some registry imports
- updated registry imports
- create_agentic_system -> create_agent
- AgenticSystem -> Agent
This commit is contained in:
Ashwin Bharambe 2024-09-16 17:34:07 -07:00
parent 2cf731faea
commit 76b354a081
128 changed files with 381 additions and 376 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 .reward_scoring import * # noqa: F401 F403

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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 List, Protocol, Union
from llama_models.schema_utils import json_schema_type, webmethod
from pydantic import BaseModel
from llama_models.llama3.api.datatypes import * # noqa: F403
@json_schema_type
class ScoredMessage(BaseModel):
message: Message
score: float
@json_schema_type
class DialogGenerations(BaseModel):
dialog: List[Message]
sampled_generations: List[Message]
@json_schema_type
class ScoredDialogGenerations(BaseModel):
dialog: List[Message]
scored_generations: List[ScoredMessage]
@json_schema_type
class RewardScoringRequest(BaseModel):
"""Request to score a reward function. A list of prompts and a list of responses per prompt."""
dialog_generations: List[DialogGenerations]
model: str
@json_schema_type
class RewardScoringResponse(BaseModel):
"""Response from the reward scoring. Batch of (prompt, response, score) tuples that pass the threshold."""
scored_generations: List[ScoredDialogGenerations]
class RewardScoring(Protocol):
@webmethod(route="/reward_scoring/score")
def reward_score(
self,
dialog_generations: List[DialogGenerations],
model: str,
) -> Union[RewardScoringResponse]: ...