Python SDK 参考
Toolgroups
类型
from llama_stack_client.types import (
ListToolGroupsResponse,
ToolGroup,
ToolgroupListResponse,
)
方法
client.toolgroups.list() -> ToolgroupListResponse
client.toolgroups.unregister(toolgroup_id) -> None
工具
类型
from llama_stack_client.types import ListToolsResponse, Tool, ToolListResponse
方法
client.tools.list(**params) -> ToolListResponse
ToolRuntime
类型
from llama_stack_client.types import ToolDef, ToolInvocationResult
方法
client.tool_runtime.invoke_tool(**params) -> ToolInvocationResult
client.tool_runtime.list_tools(**params) -> JSONLDecoder[ToolDef]
RagTool
方法
client.tool_runtime.rag_tool.query(**params) -> QueryResult
Agent
类型
from llama_stack_client.types import (
InferenceStep,
MemoryRetrievalStep,
ShieldCallStep,
ToolExecutionStep,
ToolResponse,
AgentCreateResponse,
)
方法
client.agents.create(**params) -> AgentCreateResponse
client.agents.delete(agent_id) -> None
Session
类型
from llama_stack_client.types.agents import Session, SessionCreateResponse
方法
Steps
类型
from llama_stack_client.types.agents import StepRetrieveResponse
方法
client.agents.steps.retrieve(step_id, *, agent_id, session_id, turn_id) -> StepRetrieveResponse
Turn
类型
from llama_stack_client.types.agents import Turn, TurnCreateResponse
方法
client.agents.turn.create(session_id, *, agent_id, **params) -> TurnCreateResponse
client.agents.turn.retrieve(turn_id, *, agent_id, session_id) -> Turn
BatchInference
类型
from llama_stack_client.types import BatchInferenceChatCompletionResponse
方法
client.batch_inference.chat_completion(**params) -> BatchInferenceChatCompletionResponse
client.batch_inference.completion(**params) -> BatchCompletion
Datasets
类型
from llama_stack_client.types import (
ListDatasetsResponse,
DatasetRetrieveResponse,
DatasetListResponse,
)
方法
client.datasets.retrieve(dataset_id) -> Optional[DatasetRetrieveResponse]
client.datasets.list() -> DatasetListResponse
client.datasets.unregister(dataset_id) -> None
Eval
类型
from llama_stack_client.types import EvaluateResponse, Job
方法
client.eval.evaluate_rows(benchmark_id, **params) -> EvaluateResponse
Jobs
类型
from llama_stack_client.types.eval import JobStatusResponse
方法
client.eval.jobs.retrieve(job_id, *, benchmark_id) -> EvaluateResponse
client.eval.jobs.cancel(job_id, *, benchmark_id) -> None
client.eval.jobs.status(job_id, *, benchmark_id) -> Optional[JobStatusResponse]
Inspect
类型
from llama_stack_client.types import HealthInfo, ProviderInfo, RouteInfo, VersionInfo
方法
client.inspect.health() -> HealthInfo
client.inspect.version() -> VersionInfo
Inference
类型
from llama_stack_client.types import (
CompletionResponse,
EmbeddingsResponse,
TokenLogProbs,
InferenceChatCompletionResponse,
InferenceCompletionResponse,
)
方法
client.inference.chat_completion(**params) -> InferenceChatCompletionResponse
client.inference.completion(**params) -> InferenceCompletionResponse
client.inference.embeddings(**params) -> EmbeddingsResponse
VectorIo
类型
from llama_stack_client.types import QueryChunksResponse
方法
client.vector_io.query(**params) -> QueryChunksResponse
VectorDBs
类型
from llama_stack_client.types import (
ListVectorDBsResponse,
VectorDBRetrieveResponse,
VectorDBListResponse,
VectorDBRegisterResponse,
)
方法
client.vector_dbs.retrieve(vector_db_id) -> Optional[VectorDBRetrieveResponse]
client.vector_dbs.list() -> VectorDBListResponse
client.vector_dbs.register(**params) -> VectorDBRegisterResponse
client.vector_dbs.unregister(vector_db_id) -> None
Models
类型
from llama_stack_client.types import ListModelsResponse, Model, ModelListResponse
方法
client.models.retrieve(model_id) -> Optional[Model]
client.models.list() -> ModelListResponse
client.models.unregister(model_id) -> None
PostTraining
类型
from llama_stack_client.types import ListPostTrainingJobsResponse, PostTrainingJob
方法
client.post_training.preference_optimize(**params) -> PostTrainingJob
client.post_training.supervised_fine_tune(**params) -> PostTrainingJob
Job
类型
from llama_stack_client.types.post_training import (
JobListResponse,
JobArtifactsResponse,
JobStatusResponse,
)
方法
client.post_training.job.list() -> JobListResponse
client.post_training.job.artifacts(**params) -> Optional[JobArtifactsResponse]
client.post_training.job.status(**params) -> Optional[JobStatusResponse]
Providers
类型
from llama_stack_client.types import ListProvidersResponse, ProviderListResponse
方法
client.providers.list() -> ProviderListResponse
Routes
类型
from llama_stack_client.types import ListRoutesResponse, RouteListResponse
方法
client.routes.list() -> RouteListResponse
Safety
类型
from llama_stack_client.types import RunShieldResponse
方法
client.safety.run_shield(**params) -> RunShieldResponse
Shields
类型
from llama_stack_client.types import ListShieldsResponse, Shield, ShieldListResponse
方法
client.shields.retrieve(identifier) -> Optional[Shield]
client.shields.list() -> ShieldListResponse
SyntheticDataGeneration
类型
from llama_stack_client.types import SyntheticDataGenerationResponse
方法
client.synthetic_data_generation.generate(**params) -> SyntheticDataGenerationResponse
Telemetry
类型
from llama_stack_client.types import (
QuerySpansResponse,
SpanWithStatus,
Trace,
TelemetryGetSpanResponse,
TelemetryGetSpanTreeResponse,
TelemetryQuerySpansResponse,
TelemetryQueryTracesResponse,
)
方法
client.telemetry.get_span(span_id, *, trace_id) -> TelemetryGetSpanResponse
client.telemetry.get_span_tree(span_id, **params) -> TelemetryGetSpanTreeResponse
client.telemetry.query_spans(**params) -> TelemetryQuerySpansResponse
client.telemetry.query_traces(**params) -> TelemetryQueryTracesResponse
client.telemetry.save_spans_to_dataset(**params) -> None
Datasetio
类型
from llama_stack_client.types import PaginatedRowsResult
方法
client.datasetio.append_rows(**params) -> None
client.datasetio.get_rows_paginated(**params) -> PaginatedRowsResult
Scoring
类型
from llama_stack_client.types import ScoringScoreResponse, ScoringScoreBatchResponse
方法
client.scoring.score(**params) -> ScoringScoreResponse
client.scoring.score_batch(**params) -> ScoringScoreBatchResponse
ScoringFunctions
类型
from llama_stack_client.types import (
ListScoringFunctionsResponse,
ScoringFn,
ScoringFunctionListResponse,
)
方法
client.scoring_functions.retrieve(scoring_fn_id) -> Optional[ScoringFn]
client.scoring_functions.list() -> ScoringFunctionListResponse
Benchmarks
类型
from llama_stack_client.types import (
Benchmark,
ListBenchmarksResponse,
BenchmarkListResponse,
)
方法
client.benchmarks.retrieve(benchmark_id) -> Optional[Benchmark]
client.benchmarks.list() -> BenchmarkListResponse