Use for AI SDK for Python basics. Configure a model, make messages, stream, declare tools, build a basic agent.
中文简介正在准备中。当前显示原文说明。
Use for implementing custom providers in AI SDK for Python.
中文简介正在准备中。当前显示原文说明。
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Providers emit model events. They do not run Python tools. ai.stream collects
events into a Message. ai.Agent adds tool execution, hooks, and replay.
Minimal shape:
from collections.abc import AsyncGenerator, Sequence
from typing import Any, Literal
import pydantic
import ai
class MyProtocol(ai.ProviderProtocol[Any]):
protocol_class_id: Literal["my_protocol"] = "my_protocol"
def stream(
self,
client: Any,
model: ai.Model,
messages: list[ai.messages.Message],
*,
tools: Sequence[ai.tools.Tool] | None = None,
output_type: type[pydantic.BaseModel] | None = None,
params: ai.InferenceRequestParams | None = None,
provider: str,
) -> AsyncGenerator[ai.events.Event]:
return self._stream(client, model, messages, tools=tools)
async def _stream(
self,
client: Any,
model: ai.Model,
messages: list[ai.messages.Message],
*,
tools: Sequence[ai.tools.Tool] | None,
) -> AsyncGenerator[ai.events.Event]:
yield ai.events.StreamStart()
yield ai.events.TextStart(block_id="text")
yield ai.events.TextDelta(block_id="text", chunk="Hello")
yield ai.events.TextEnd(block_id="text")
yield ai.events.StreamEnd()
class MyProvider(ai.Provider[Any]):
provider_class_id: Literal["my_provider"] = "my_provider"
name: str = "my"
default_base_url: str = "https://example.invalid"
def __init__(self, *, client: Any) -> None:
super().__init__()
self._set_client(client)
def default_protocol(self) -> ai.ProviderProtocol[Any]:
return MyProtocol()
async def list_models(self) -> list[str]:
return ["my-model"]
async def probe(self, model: ai.Model) -> None:
return None
model = ai.Model(id="my-model", provider=MyProvider(client=client))
For Python tool calls, emit ToolStart, ToolDelta, and ToolEnd:
yield ai.events.ToolStart(tool_call_id=tcid, tool_name=name)
yield ai.events.ToolDelta(tool_call_id=tcid, chunk=args_json)
yield ai.events.ToolEnd(
tool_call_id=tcid,
tool_call=ai.messages.DUMMY_TOOL_CALL,
)
The stream collector fills event.tool_call with the aggregated tool call.
Then Agent resolves and runs the tool.
If the provider runs its own built-in tool, emit BuiltinToolStart,
BuiltinToolDelta, BuiltinToolEnd, and BuiltinToolResult instead.
Do not implement a custom provider for normal app configuration. Prefer
ai.get_provider(...), ai.get_model(...), or a protocol override unless you
are adding a new upstream API adapter.
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Use for AI SDK for Python basics. Configure a model, make messages, stream, declare tools, build a basic agent.
中文简介正在准备中。当前显示原文说明。
Use when building custom agent loops. Modify tool dispatch, history management, hooks, control flow.
中文简介正在准备中。当前显示原文说明。
Use when adding durable execution to AI SDK for Python, building durable agent loops, or serializing messages across workflow steps.
中文简介正在准备中。当前显示原文说明。
Use when building serverless AI SDK for Python endpoints, handling hook approvals, deferring hooks, or resuming runs across requests.
中文简介正在准备中。当前显示原文说明。
Use for AI SDK for Python async-generator tools, streaming tool output, subagent tools, PartialToolCallResult events, and custom tool aggregation.
中文简介正在准备中。当前显示原文说明。
Use for the subagent-as-a-tool pattern.
中文简介正在准备中。当前显示原文说明。