Python SDK Reference

Shared Types

from llama_stack_client.types import (
    AgentConfig,
    BatchCompletion,
    CompletionMessage,
    ContentDelta,
    Document,
    InterleavedContent,
    InterleavedContentItem,
    Message,
    ParamType,
    QueryConfig,
    QueryResult,
    ReturnType,
    SafetyViolation,
    SamplingParams,
    ScoringResult,
    SystemMessage,
    ToolCall,
    ToolParamDefinition,
    ToolResponseMessage,
    URL,
    UserMessage,
)

Toolgroups

Types:

from llama_stack_client.types import (
    ListToolGroupsResponse,
    ToolGroup,
    ToolgroupListResponse,
)

Methods:

• client.toolgroups.list() -> ToolgroupListResponse
• client.toolgroups.get(toolgroup_id) -> ToolGroup
• client.toolgroups.register(**params) -> None
• client.toolgroups.unregister(toolgroup_id) -> None

Tools

Types:

from llama_stack_client.types import ListToolsResponse, Tool, ToolListResponse

Methods:

• client.tools.list(**params) -> ToolListResponse
• client.tools.get(tool_name) -> Tool

ToolRuntime

Types:

from llama_stack_client.types import ToolDef, ToolInvocationResult

Methods:

• client.tool_runtime.invoke_tool(**params) -> ToolInvocationResult
• client.tool_runtime.list_tools(**params) -> JSONLDecoder[ToolDef]

RagTool

Methods:

• client.tool_runtime.rag_tool.insert(**params) -> None
• client.tool_runtime.rag_tool.query(**params) -> QueryResult

Agents

Types:

from llama_stack_client.types import (
    InferenceStep,
    MemoryRetrievalStep,
    ShieldCallStep,
    ToolExecutionStep,
    ToolResponse,
    AgentCreateResponse,
)

Methods:

• client.agents.create(**params) -> AgentCreateResponse
• client.agents.delete(agent_id) -> None

Session

Types:

from llama_stack_client.types.agents import Session, SessionCreateResponse

Methods:

• client.agents.session.create(agent_id, **params) -> SessionCreateResponse
• client.agents.session.retrieve(session_id, *, agent_id, **params) -> Session
• client.agents.session.delete(session_id, *, agent_id) -> None

Steps

Types:

from llama_stack_client.types.agents import StepRetrieveResponse

Methods:

• client.agents.steps.retrieve(step_id, *, agent_id, session_id, turn_id) -> StepRetrieveResponse

Turn

Types:

from llama_stack_client.types.agents import Turn, TurnCreateResponse

Methods:

• client.agents.turn.create(session_id, *, agent_id, **params) -> TurnCreateResponse
• client.agents.turn.retrieve(turn_id, *, agent_id, session_id) -> Turn

Datasets

Types:

from llama_stack_client.types import (
    ListDatasetsResponse,
    DatasetRetrieveResponse,
    DatasetListResponse,
)

Methods:

• client.datasets.retrieve(dataset_id) -> Optional[DatasetRetrieveResponse]
• client.datasets.list() -> DatasetListResponse
• client.datasets.register(**params) -> None
• client.datasets.unregister(dataset_id) -> None

Eval

Types:

from llama_stack_client.types import EvaluateResponse, Job

Methods:

• client.eval.evaluate_rows(benchmark_id, **params) -> EvaluateResponse
• client.eval.run_eval(benchmark_id, **params) -> Job

Jobs

Types:

from llama_stack_client.types.eval import JobStatusResponse

Methods:

• 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

Types:

from llama_stack_client.types import HealthInfo, ProviderInfo, RouteInfo, VersionInfo

Methods:

• client.inspect.health() -> HealthInfo
• client.inspect.version() -> VersionInfo

Inference

Types:

from llama_stack_client.types import (
    CompletionResponse,
    EmbeddingsResponse,
    TokenLogProbs,
    InferenceChatCompletionResponse,
    InferenceCompletionResponse,
)

Methods:

• client.inference.embeddings(**params) -> EmbeddingsResponse

VectorIo

DEPRECATED API

This API is deprecated and will be removed in a future version.

Use the OpenAI-compatible Vector Stores API instead:

• Instead of client.vector_io.insert(), use client.vector_stores.files.create() and client.vector_stores.files.chunks.create()
• Instead of client.vector_io.query(), use client.vector_stores.search()

See the RAG documentation for migration examples.

Related: Issue #2981

Types:

from llama_stack_client.types import QueryChunksResponse

Methods:

• client.vector_io.insert(**params) -> None
• client.vector_io.query(**params) -> QueryChunksResponse

VectorDBs

DEPRECATED API

This API is deprecated and will be removed in a future version.

Use the OpenAI-compatible Vector Stores API instead:

• Instead of client.vector_dbs.register(), use client.vector_stores.create()
• Instead of client.vector_dbs.list(), use client.vector_stores.list()
• Instead of client.vector_dbs.retrieve(), use client.vector_stores.retrieve()
• Instead of client.vector_dbs.unregister(), use client.vector_stores.delete()

See the RAG documentation for migration examples.

Related: Issue #2981

Types:

from llama_stack_client.types import (
    ListVectorDBsResponse,
    VectorDBRetrieveResponse,
    VectorDBListResponse,
    VectorDBRegisterResponse,
)

Methods:

• 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

Types:

from llama_stack_client.types import ListModelsResponse, Model, ModelListResponse

Methods:

• client.models.retrieve(model_id) -> Optional[Model]
• client.models.list() -> ModelListResponse
• client.models.register(**params) -> Model
• client.models.unregister(model_id) -> None

PostTraining

Types:

from llama_stack_client.types import ListPostTrainingJobsResponse, PostTrainingJob

Methods:

• client.post_training.preference_optimize(**params) -> PostTrainingJob
• client.post_training.supervised_fine_tune(**params) -> PostTrainingJob

Job

Types:

from llama_stack_client.types.post_training import (
    JobListResponse,
    JobArtifactsResponse,
    JobStatusResponse,
)

Methods:

• client.post_training.job.list() -> JobListResponse
• client.post_training.job.artifacts(**params) -> Optional[JobArtifactsResponse]
• client.post_training.job.cancel(**params) -> None
• client.post_training.job.status(**params) -> Optional[JobStatusResponse]

Providers

Types:

from llama_stack_client.types import ListProvidersResponse, ProviderListResponse

Methods:

• client.providers.list() -> ProviderListResponse

Routes

Types:

from llama_stack_client.types import ListRoutesResponse, RouteListResponse

Methods:

• client.routes.list() -> RouteListResponse

Safety

Types:

from llama_stack_client.types import RunShieldResponse

Methods:

• client.safety.run_shield(**params) -> RunShieldResponse

Shields

Types:

from llama_stack_client.types import ListShieldsResponse, Shield, ShieldListResponse

Methods:

• client.shields.retrieve(identifier) -> Optional[Shield]
• client.shields.list() -> ShieldListResponse
• client.shields.register(**params) -> Shield

SyntheticDataGeneration

Types:

from llama_stack_client.types import SyntheticDataGenerationResponse

Methods:

• client.synthetic_data_generation.generate(**params) -> SyntheticDataGenerationResponse

Datasetio

Types:

from llama_stack_client.types import PaginatedRowsResult

Methods:

• client.datasetio.append_rows(**params) -> None
• client.datasetio.get_rows_paginated(**params) -> PaginatedRowsResult

Scoring

Types:

from llama_stack_client.types import ScoringScoreResponse, ScoringScoreBatchResponse

Methods:

• client.scoring.score(**params) -> ScoringScoreResponse
• client.scoring.score_batch(**params) -> ScoringScoreBatchResponse

ScoringFunctions

Types:

from llama_stack_client.types import (
    ListScoringFunctionsResponse,
    ScoringFn,
    ScoringFunctionListResponse,
)

Methods:

• client.scoring_functions.retrieve(scoring_fn_id) -> Optional[ScoringFn]
• client.scoring_functions.list() -> ScoringFunctionListResponse
• client.scoring_functions.register(**params) -> None

Benchmarks

Types:

from llama_stack_client.types import (
    Benchmark,
    ListBenchmarksResponse,
    BenchmarkListResponse,
)

Methods:

• client.benchmarks.retrieve(benchmark_id) -> Optional[Benchmark]
• client.benchmarks.list() -> BenchmarkListResponse
• client.benchmarks.register(**params) -> None