llama-stack-mirror/llama_toolchain/telemetry/api/api.py
2024-09-07 15:23:53 -07:00

175 lines
4.1 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 datetime import datetime
from enum import Enum
from typing import Any, Dict, List, Optional, Protocol, Union
from llama_models.schema_utils import json_schema_type, webmethod
from pydantic import BaseModel
@json_schema_type
class ExperimentStatus(Enum):
NOT_STARTED = "not_started"
RUNNING = "running"
COMPLETED = "completed"
FAILED = "failed"
@json_schema_type
class Experiment(BaseModel):
id: str
name: str
status: ExperimentStatus
created_at: datetime
updated_at: datetime
metadata: Dict[str, Any]
@json_schema_type
class Run(BaseModel):
id: str
experiment_id: str
status: str
started_at: datetime
ended_at: Optional[datetime]
metadata: Dict[str, Any]
@json_schema_type
class Metric(BaseModel):
name: str
value: Union[float, int, str, bool]
timestamp: datetime
run_id: str
@json_schema_type
class Log(BaseModel):
message: str
level: str
timestamp: datetime
additional_info: Dict[str, Any]
@json_schema_type
class ArtifactType(Enum):
MODEL = "model"
DATASET = "dataset"
CHECKPOINT = "checkpoint"
PLOT = "plot"
METRIC = "metric"
CONFIG = "config"
CODE = "code"
OTHER = "other"
@json_schema_type
class Artifact(BaseModel):
id: str
name: str
type: ArtifactType
size: int
created_at: datetime
metadata: Dict[str, Any]
@json_schema_type
class CreateExperimentRequest(BaseModel):
name: str
metadata: Optional[Dict[str, Any]] = None
@json_schema_type
class UpdateExperimentRequest(BaseModel):
experiment_id: str
status: Optional[ExperimentStatus] = None
metadata: Optional[Dict[str, Any]] = None
@json_schema_type
class CreateRunRequest(BaseModel):
experiment_id: str
metadata: Optional[Dict[str, Any]] = None
@json_schema_type
class UpdateRunRequest(BaseModel):
run_id: str
status: Optional[str] = None
ended_at: Optional[datetime] = None
metadata: Optional[Dict[str, Any]] = None
@json_schema_type
class LogMetricsRequest(BaseModel):
run_id: str
metrics: List[Metric]
@json_schema_type
class LogMessagesRequest(BaseModel):
logs: List[Log]
run_id: Optional[str] = None
@json_schema_type
class UploadArtifactRequest(BaseModel):
experiment_id: str
name: str
artifact_type: str
content: bytes
metadata: Optional[Dict[str, Any]] = None
@json_schema_type
class LogSearchRequest(BaseModel):
query: str
filters: Optional[Dict[str, Any]] = None
class Telemetry(Protocol):
@webmethod(route="/experiments/create")
def create_experiment(self, request: CreateExperimentRequest) -> Experiment: ...
@webmethod(route="/experiments/list")
def list_experiments(self) -> List[Experiment]: ...
@webmethod(route="/experiments/get")
def get_experiment(self, experiment_id: str) -> Experiment: ...
@webmethod(route="/experiments/update")
def update_experiment(self, request: UpdateExperimentRequest) -> Experiment: ...
@webmethod(route="/experiments/create_run")
def create_run(self, request: CreateRunRequest) -> Run: ...
@webmethod(route="/runs/update")
def update_run(self, request: UpdateRunRequest) -> Run: ...
@webmethod(route="/runs/log_metrics")
def log_metrics(self, request: LogMetricsRequest) -> None: ...
@webmethod(route="/runs/metrics", method="GET")
def get_metrics(self, run_id: str) -> List[Metric]: ...
@webmethod(route="/logging/log_messages")
def log_messages(self, request: LogMessagesRequest) -> None: ...
@webmethod(route="/logging/get_logs")
def get_logs(self, request: LogSearchRequest) -> List[Log]: ...
@webmethod(route="/experiments/artifacts/upload")
def upload_artifact(self, request: UploadArtifactRequest) -> Artifact: ...
@webmethod(route="/experiments/artifacts/get")
def list_artifacts(self, experiment_id: str) -> List[Artifact]: ...
@webmethod(route="/artifacts/get")
def get_artifact(self, artifact_id: str) -> Artifact: ...