mirror of
https://github.com/meta-llama/llama-stack.git
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formatting
This commit is contained in:
Dalton Flanagan
parent
069d877210
commit
b311dcd143
22 changed files with 82 additions and 128 deletions
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@ -63,9 +63,9 @@ class ShieldCallStep(StepCommon):
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@json_schema_type
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class MemoryRetrievalStep(StepCommon):
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step_type: Literal[
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step_type: Literal[StepType.memory_retrieval.value] = (
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StepType.memory_retrieval.value
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] = StepType.memory_retrieval.value
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)
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memory_bank_ids: List[str]
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documents: List[MemoryBankDocument]
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scores: List[float]
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@ -140,9 +140,9 @@ class AgenticSystemTurnResponseEventType(Enum):
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@json_schema_type
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class AgenticSystemTurnResponseStepStartPayload(BaseModel):
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event_type: Literal[
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event_type: Literal[AgenticSystemTurnResponseEventType.step_start.value] = (
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AgenticSystemTurnResponseEventType.step_start.value
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] = AgenticSystemTurnResponseEventType.step_start.value
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)
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step_type: StepType
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step_id: str
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metadata: Optional[Dict[str, Any]] = Field(default_factory=dict)
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@ -150,9 +150,9 @@ class AgenticSystemTurnResponseStepStartPayload(BaseModel):
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@json_schema_type
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class AgenticSystemTurnResponseStepCompletePayload(BaseModel):
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event_type: Literal[
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event_type: Literal[AgenticSystemTurnResponseEventType.step_complete.value] = (
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AgenticSystemTurnResponseEventType.step_complete.value
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] = AgenticSystemTurnResponseEventType.step_complete.value
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)
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step_type: StepType
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step_details: Step
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@ -161,9 +161,9 @@ class AgenticSystemTurnResponseStepCompletePayload(BaseModel):
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class AgenticSystemTurnResponseStepProgressPayload(BaseModel):
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model_config = ConfigDict(protected_namespaces=())
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event_type: Literal[
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event_type: Literal[AgenticSystemTurnResponseEventType.step_progress.value] = (
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AgenticSystemTurnResponseEventType.step_progress.value
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] = AgenticSystemTurnResponseEventType.step_progress.value
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)
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step_type: StepType
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step_id: str
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@ -174,17 +174,17 @@ class AgenticSystemTurnResponseStepProgressPayload(BaseModel):
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@json_schema_type
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class AgenticSystemTurnResponseTurnStartPayload(BaseModel):
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event_type: Literal[
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event_type: Literal[AgenticSystemTurnResponseEventType.turn_start.value] = (
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AgenticSystemTurnResponseEventType.turn_start.value
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] = AgenticSystemTurnResponseEventType.turn_start.value
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)
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turn_id: str
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@json_schema_type
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class AgenticSystemTurnResponseTurnCompletePayload(BaseModel):
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event_type: Literal[
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event_type: Literal[AgenticSystemTurnResponseEventType.turn_complete.value] = (
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AgenticSystemTurnResponseEventType.turn_complete.value
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] = AgenticSystemTurnResponseEventType.turn_complete.value
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)
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turn: Turn
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@ -67,36 +67,31 @@ class AgenticSystem(Protocol):
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async def create_agentic_system(
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self,
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request: AgenticSystemCreateRequest,
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) -> AgenticSystemCreateResponse:
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...
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) -> AgenticSystemCreateResponse: ...
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@webmethod(route="/agentic_system/turn/create")
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async def create_agentic_system_turn(
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self,
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request: AgenticSystemTurnCreateRequest,
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) -> AgenticSystemTurnResponseStreamChunk:
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...
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) -> AgenticSystemTurnResponseStreamChunk: ...
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@webmethod(route="/agentic_system/turn/get")
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async def get_agentic_system_turn(
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self,
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agent_id: str,
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turn_id: str,
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) -> Turn:
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...
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) -> Turn: ...
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@webmethod(route="/agentic_system/step/get")
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async def get_agentic_system_step(
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self, agent_id: str, turn_id: str, step_id: str
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) -> AgenticSystemStepResponse:
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...
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) -> AgenticSystemStepResponse: ...
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@webmethod(route="/agentic_system/session/create")
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async def create_agentic_system_session(
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self,
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request: AgenticSystemSessionCreateRequest,
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) -> AgenticSystemSessionCreateResponse:
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...
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) -> AgenticSystemSessionCreateResponse: ...
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@webmethod(route="/agentic_system/memory_bank/attach")
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async def attach_memory_bank_to_agentic_system(
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@ -104,8 +99,7 @@ class AgenticSystem(Protocol):
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agent_id: str,
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session_id: str,
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memory_bank_ids: List[str],
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) -> None:
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...
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) -> None: ...
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@webmethod(route="/agentic_system/memory_bank/detach")
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async def detach_memory_bank_from_agentic_system(
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@ -113,8 +107,7 @@ class AgenticSystem(Protocol):
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agent_id: str,
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session_id: str,
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memory_bank_ids: List[str],
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) -> None:
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...
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) -> None: ...
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@webmethod(route="/agentic_system/session/get")
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async def get_agentic_system_session(
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@ -122,18 +115,15 @@ class AgenticSystem(Protocol):
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agent_id: str,
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session_id: str,
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turn_ids: Optional[List[str]] = None,
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) -> Session:
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...
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) -> Session: ...
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@webmethod(route="/agentic_system/session/delete")
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async def delete_agentic_system_session(
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self, agent_id: str, session_id: str
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) -> None:
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...
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) -> None: ...
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@webmethod(route="/agentic_system/delete")
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async def delete_agentic_system(
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self,
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agent_id: str,
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) -> None:
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...
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) -> None: ...
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@ -10,11 +10,11 @@ import os
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import pkg_resources
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import yaml
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from termcolor import cprint
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from llama_toolchain.cli.subcommand import Subcommand
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from llama_toolchain.common.config_dirs import DISTRIBS_BASE_DIR
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from termcolor import cprint
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class DistributionInstall(Subcommand):
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"""Llama cli for configuring llama toolchain configs"""
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@ -14,10 +14,10 @@ from pathlib import Path
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import httpx
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from termcolor import cprint
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from llama_toolchain.cli.subcommand import Subcommand
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from termcolor import cprint
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class Download(Subcommand):
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"""Llama cli for downloading llama toolchain assets"""
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@ -9,12 +9,12 @@ import json
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from llama_models.sku_list import resolve_model
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from termcolor import colored
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from llama_toolchain.cli.subcommand import Subcommand
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from llama_toolchain.cli.table import print_table
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from llama_toolchain.common.serialize import EnumEncoder
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from termcolor import colored
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class ModelDescribe(Subcommand):
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"""Show details about a model"""
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@ -7,10 +7,10 @@
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import argparse
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import textwrap
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from termcolor import colored
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from llama_toolchain.cli.subcommand import Subcommand
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from termcolor import colored
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class ModelTemplate(Subcommand):
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"""Llama model cli for describe a model template (message formats)"""
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@ -1,4 +1,5 @@
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import os
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from llama_models.datatypes import Model
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from .config_dirs import DEFAULT_CHECKPOINT_DIR
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@ -26,19 +26,16 @@ class Datasets(Protocol):
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def create_dataset(
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self,
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request: CreateDatasetRequest,
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) -> None:
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...
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) -> None: ...
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@webmethod(route="/datasets/get")
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def get_dataset(
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self,
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dataset_uuid: str,
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) -> TrainEvalDataset:
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...
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) -> TrainEvalDataset: ...
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@webmethod(route="/datasets/delete")
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def delete_dataset(
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self,
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dataset_uuid: str,
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) -> None:
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...
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) -> None: ...
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@ -63,42 +63,36 @@ class Evaluations(Protocol):
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def post_evaluate_text_generation(
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self,
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request: EvaluateTextGenerationRequest,
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) -> EvaluationJob:
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...
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) -> EvaluationJob: ...
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@webmethod(route="/evaluate/question_answering/")
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def post_evaluate_question_answering(
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self,
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request: EvaluateQuestionAnsweringRequest,
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) -> EvaluationJob:
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...
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) -> EvaluationJob: ...
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@webmethod(route="/evaluate/summarization/")
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def post_evaluate_summarization(
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self,
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request: EvaluateSummarizationRequest,
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) -> EvaluationJob:
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...
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) -> EvaluationJob: ...
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@webmethod(route="/evaluate/jobs")
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def get_evaluation_jobs(self) -> List[EvaluationJob]:
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...
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def get_evaluation_jobs(self) -> List[EvaluationJob]: ...
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@webmethod(route="/evaluate/job/status")
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def get_evaluation_job_status(self, job_uuid: str) -> EvaluationJobStatusResponse:
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...
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def get_evaluation_job_status(
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self, job_uuid: str
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) -> EvaluationJobStatusResponse: ...
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# sends SSE stream of logs
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@webmethod(route="/evaluate/job/logs")
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def get_evaluation_job_logstream(self, job_uuid: str) -> EvaluationJobLogStream:
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...
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def get_evaluation_job_logstream(self, job_uuid: str) -> EvaluationJobLogStream: ...
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@webmethod(route="/evaluate/job/cancel")
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def cancel_evaluation_job(self, job_uuid: str) -> None:
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...
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def cancel_evaluation_job(self, job_uuid: str) -> None: ...
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@webmethod(route="/evaluate/job/artifacts")
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def get_evaluation_job_artifacts(
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self, job_uuid: str
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) -> EvaluationJobArtifactsResponse:
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...
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) -> EvaluationJobArtifactsResponse: ...
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@ -101,26 +101,22 @@ class Inference(Protocol):
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async def completion(
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self,
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request: CompletionRequest,
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) -> Union[CompletionResponse, CompletionResponseStreamChunk]:
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...
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) -> Union[CompletionResponse, CompletionResponseStreamChunk]: ...
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@webmethod(route="/inference/chat_completion")
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async def chat_completion(
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self,
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request: ChatCompletionRequest,
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) -> Union[ChatCompletionResponse, ChatCompletionResponseStreamChunk]:
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...
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) -> Union[ChatCompletionResponse, ChatCompletionResponseStreamChunk]: ...
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@webmethod(route="/inference/batch_completion")
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async def batch_completion(
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self,
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request: BatchCompletionRequest,
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) -> BatchCompletionResponse:
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...
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) -> BatchCompletionResponse: ...
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@webmethod(route="/inference/batch_chat_completion")
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async def batch_chat_completion(
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self,
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request: BatchChatCompletionRequest,
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) -> BatchChatCompletionResponse:
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...
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) -> BatchChatCompletionResponse: ...
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|
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@ -4,12 +4,11 @@
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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 termcolor import cprint
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from llama_toolchain.inference.api import (
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ChatCompletionResponseEventType,
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ChatCompletionResponseStreamChunk,
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)
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from termcolor import cprint
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class LogEvent:
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@ -11,10 +11,10 @@ from llama_models.datatypes import ModelFamily
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from llama_models.schema_utils import json_schema_type
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from llama_models.sku_list import all_registered_models
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from pydantic import BaseModel, Field, field_validator
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from llama_toolchain.inference.api import QuantizationConfig
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from pydantic import BaseModel, Field, field_validator
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@json_schema_type
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class MetaReferenceImplConfig(BaseModel):
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|
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@ -28,10 +28,10 @@ from llama_models.llama3_1.api.datatypes import Message
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from llama_models.llama3_1.api.tokenizer import Tokenizer
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from llama_models.llama3_1.reference_impl.model import Transformer
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from llama_models.sku_list import resolve_model
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from termcolor import cprint
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from llama_toolchain.common.model_utils import model_local_dir
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from llama_toolchain.inference.api import QuantizationType
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from termcolor import cprint
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from .config import MetaReferenceImplConfig
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@ -18,52 +18,44 @@ class MemoryBanks(Protocol):
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bank_id: str,
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bank_name: str,
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documents: List[MemoryBankDocument],
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) -> None:
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...
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) -> None: ...
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@webmethod(route="/memory_banks/list")
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def get_memory_banks(self) -> List[MemoryBank]:
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...
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def get_memory_banks(self) -> List[MemoryBank]: ...
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@webmethod(route="/memory_banks/get")
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def get_memory_bank(self, bank_id: str) -> List[MemoryBank]:
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...
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def get_memory_bank(self, bank_id: str) -> List[MemoryBank]: ...
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@webmethod(route="/memory_banks/drop")
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def delete_memory_bank(
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self,
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bank_id: str,
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) -> str:
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...
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) -> str: ...
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@webmethod(route="/memory_bank/insert")
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def post_insert_memory_documents(
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self,
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bank_id: str,
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documents: List[MemoryBankDocument],
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) -> None:
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...
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) -> None: ...
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@webmethod(route="/memory_bank/update")
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def post_update_memory_documents(
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self,
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bank_id: str,
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documents: List[MemoryBankDocument],
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) -> None:
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...
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) -> None: ...
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@webmethod(route="/memory_bank/get")
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def get_memory_documents(
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self,
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bank_id: str,
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document_uuids: List[str],
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) -> List[MemoryBankDocument]:
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...
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) -> List[MemoryBankDocument]: ...
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@webmethod(route="/memory_bank/delete")
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def delete_memory_documents(
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self,
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bank_id: str,
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document_uuids: List[str],
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) -> List[str]:
|
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...
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) -> List[str]: ...
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|
|
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|
|
@ -11,5 +11,4 @@ from llama_models.schema_utils import webmethod # noqa: F401
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from pydantic import BaseModel # noqa: F401
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class Models(Protocol):
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...
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class Models(Protocol): ...
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|
|
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@ -98,35 +98,30 @@ class PostTraining(Protocol):
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def post_supervised_fine_tune(
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self,
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request: PostTrainingSFTRequest,
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) -> PostTrainingJob:
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...
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) -> PostTrainingJob: ...
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@webmethod(route="/post_training/preference_optimize")
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def post_preference_optimize(
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self,
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request: PostTrainingRLHFRequest,
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) -> PostTrainingJob:
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...
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) -> PostTrainingJob: ...
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@webmethod(route="/post_training/jobs")
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def get_training_jobs(self) -> List[PostTrainingJob]:
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...
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def get_training_jobs(self) -> List[PostTrainingJob]: ...
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# sends SSE stream of logs
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@webmethod(route="/post_training/job/logs")
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def get_training_job_logstream(self, job_uuid: str) -> PostTrainingJobLogStream:
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...
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def get_training_job_logstream(self, job_uuid: str) -> PostTrainingJobLogStream: ...
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@webmethod(route="/post_training/job/status")
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def get_training_job_status(self, job_uuid: str) -> PostTrainingJobStatusResponse:
|
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...
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def get_training_job_status(
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self, job_uuid: str
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) -> PostTrainingJobStatusResponse: ...
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@webmethod(route="/post_training/job/cancel")
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def cancel_training_job(self, job_uuid: str) -> None:
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...
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def cancel_training_job(self, job_uuid: str) -> None: ...
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@webmethod(route="/post_training/job/artifacts")
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def get_training_job_artifacts(
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self, job_uuid: str
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) -> PostTrainingJobArtifactsResponse:
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...
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) -> PostTrainingJobArtifactsResponse: ...
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|
|
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|
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@ -30,5 +30,4 @@ class RewardScoring(Protocol):
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def post_score(
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self,
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request: RewardScoringRequest,
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) -> Union[RewardScoringResponse]:
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||||
...
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||||
) -> Union[RewardScoringResponse]: ...
|
||||
|
|
|
|||
|
|
@ -11,10 +11,10 @@ from llama_models.llama3_1.api.datatypes import ToolParamDefinition
|
|||
|
||||
from llama_models.schema_utils import json_schema_type
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
from llama_toolchain.common.deployment_types import RestAPIExecutionConfig
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
|
||||
@json_schema_type
|
||||
class BuiltinShield(Enum):
|
||||
|
|
|
|||
|
|
@ -29,5 +29,4 @@ class Safety(Protocol):
|
|||
async def run_shields(
|
||||
self,
|
||||
request: RunShieldRequest,
|
||||
) -> RunShieldResponse:
|
||||
...
|
||||
) -> RunShieldResponse: ...
|
||||
|
|
|
|||
|
|
@ -37,5 +37,4 @@ class SyntheticDataGeneration(Protocol):
|
|||
def post_generate(
|
||||
self,
|
||||
request: SyntheticDataGenerationRequest,
|
||||
) -> Union[SyntheticDataGenerationResponse]:
|
||||
...
|
||||
) -> Union[SyntheticDataGenerationResponse]: ...
|
||||
|
|
|
|||
|
|
@ -10,20 +10,16 @@ from datetime import datetime
|
|||
|
||||
from llama_models.llama3_1.api.datatypes import (
|
||||
BuiltinTool,
|
||||
UserMessage,
|
||||
StopReason,
|
||||
SystemMessage,
|
||||
ToolResponseMessage,
|
||||
UserMessage,
|
||||
)
|
||||
from llama_toolchain.inference.api.datatypes import (
|
||||
ChatCompletionResponseEventType,
|
||||
)
|
||||
from llama_toolchain.inference.meta_reference.inference import get_provider_impl
|
||||
from llama_toolchain.inference.meta_reference.config import (
|
||||
MetaReferenceImplConfig,
|
||||
)
|
||||
from llama_toolchain.inference.api.datatypes import ChatCompletionResponseEventType
|
||||
|
||||
from llama_toolchain.inference.api.endpoints import ChatCompletionRequest
|
||||
from llama_toolchain.inference.meta_reference.config import MetaReferenceImplConfig
|
||||
from llama_toolchain.inference.meta_reference.inference import get_provider_impl
|
||||
|
||||
|
||||
MODEL = "Meta-Llama3.1-8B-Instruct"
|
||||
|
|
|
|||
|
|
@ -4,16 +4,14 @@ from datetime import datetime
|
|||
|
||||
from llama_models.llama3_1.api.datatypes import (
|
||||
BuiltinTool,
|
||||
UserMessage,
|
||||
StopReason,
|
||||
SamplingParams,
|
||||
SamplingStrategy,
|
||||
StopReason,
|
||||
SystemMessage,
|
||||
ToolResponseMessage,
|
||||
UserMessage,
|
||||
)
|
||||
from llama_toolchain.inference.api.datatypes import (
|
||||
ChatCompletionResponseEventType,
|
||||
)
|
||||
from llama_toolchain.inference.api.datatypes import ChatCompletionResponseEventType
|
||||
from llama_toolchain.inference.api.endpoints import ChatCompletionRequest
|
||||
from llama_toolchain.inference.ollama.config import OllamaImplConfig
|
||||
from llama_toolchain.inference.ollama.ollama import get_provider_impl
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue