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runs.py
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# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from __future__ import annotations
import typing_extensions
from typing import Union, Iterable, Optional, overload
from functools import partial
from typing_extensions import Literal
import httpx
from ..... import _legacy_response
from .steps import (
Steps,
AsyncSteps,
StepsWithRawResponse,
AsyncStepsWithRawResponse,
StepsWithStreamingResponse,
AsyncStepsWithStreamingResponse,
)
from ....._types import NOT_GIVEN, Body, Query, Headers, NotGiven
from ....._utils import (
is_given,
required_args,
maybe_transform,
async_maybe_transform,
)
from ....._compat import cached_property
from ....._resource import SyncAPIResource, AsyncAPIResource
from ....._response import to_streamed_response_wrapper, async_to_streamed_response_wrapper
from ....._streaming import Stream, AsyncStream
from .....pagination import SyncCursorPage, AsyncCursorPage
from ....._base_client import AsyncPaginator, make_request_options
from .....lib.streaming import (
AssistantEventHandler,
AssistantEventHandlerT,
AssistantStreamManager,
AsyncAssistantEventHandler,
AsyncAssistantEventHandlerT,
AsyncAssistantStreamManager,
)
from .....types.chat_model import ChatModel
from .....types.beta.threads import (
run_list_params,
run_create_params,
run_update_params,
run_submit_tool_outputs_params,
)
from .....types.beta.threads.run import Run
from .....types.beta.assistant_tool_param import AssistantToolParam
from .....types.beta.assistant_stream_event import AssistantStreamEvent
from .....types.beta.assistant_tool_choice_option_param import AssistantToolChoiceOptionParam
from .....types.beta.assistant_response_format_option_param import AssistantResponseFormatOptionParam
__all__ = ["Runs", "AsyncRuns"]
class Runs(SyncAPIResource):
@cached_property
def steps(self) -> Steps:
return Steps(self._client)
@cached_property
def with_raw_response(self) -> RunsWithRawResponse:
return RunsWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> RunsWithStreamingResponse:
return RunsWithStreamingResponse(self)
@overload
def create(
self,
thread_id: str,
*,
assistant_id: str,
additional_instructions: Optional[str] | NotGiven = NOT_GIVEN,
additional_messages: Optional[Iterable[run_create_params.AdditionalMessage]] | NotGiven = NOT_GIVEN,
instructions: Optional[str] | NotGiven = NOT_GIVEN,
max_completion_tokens: Optional[int] | NotGiven = NOT_GIVEN,
max_prompt_tokens: Optional[int] | NotGiven = NOT_GIVEN,
metadata: Optional[object] | NotGiven = NOT_GIVEN,
model: Union[str, ChatModel, None] | NotGiven = NOT_GIVEN,
parallel_tool_calls: bool | NotGiven = NOT_GIVEN,
response_format: Optional[AssistantResponseFormatOptionParam] | NotGiven = NOT_GIVEN,
stream: Optional[Literal[False]] | NotGiven = NOT_GIVEN,
temperature: Optional[float] | NotGiven = NOT_GIVEN,
tool_choice: Optional[AssistantToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
tools: Optional[Iterable[AssistantToolParam]] | NotGiven = NOT_GIVEN,
top_p: Optional[float] | NotGiven = NOT_GIVEN,
truncation_strategy: Optional[run_create_params.TruncationStrategy] | NotGiven = NOT_GIVEN,
# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
# The extra values given here take precedence over values defined on the client or passed to this method.
extra_headers: Headers | None = None,
extra_query: Query | None = None,
extra_body: Body | None = None,
timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
) -> Run:
"""
Create a run.
Args:
assistant_id: The ID of the
[assistant](https://platform.openai.com/docs/api-reference/assistants) to use to
execute this run.
additional_instructions: Appends additional instructions at the end of the instructions for the run. This
is useful for modifying the behavior on a per-run basis without overriding other
instructions.
additional_messages: Adds additional messages to the thread before creating the run.
instructions: Overrides the
[instructions](https://platform.openai.com/docs/api-reference/assistants/createAssistant)
of the assistant. This is useful for modifying the behavior on a per-run basis.
max_completion_tokens: The maximum number of completion tokens that may be used over the course of the
run. The run will make a best effort to use only the number of completion tokens
specified, across multiple turns of the run. If the run exceeds the number of
completion tokens specified, the run will end with status `incomplete`. See
`incomplete_details` for more info.
max_prompt_tokens: The maximum number of prompt tokens that may be used over the course of the run.
The run will make a best effort to use only the number of prompt tokens
specified, across multiple turns of the run. If the run exceeds the number of
prompt tokens specified, the run will end with status `incomplete`. See
`incomplete_details` for more info.
metadata: Set of 16 key-value pairs that can be attached to an object. This can be useful
for storing additional information about the object in a structured format. Keys
can be a maximum of 64 characters long and values can be a maxium of 512
characters long.
model: The ID of the [Model](https://platform.openai.com/docs/api-reference/models) to
be used to execute this run. If a value is provided here, it will override the
model associated with the assistant. If not, the model associated with the
assistant will be used.
parallel_tool_calls: Whether to enable
[parallel function calling](https://platform.openai.com/docs/guides/function-calling/parallel-function-calling)
during tool use.
response_format: Specifies the format that the model must output. Compatible with
[GPT-4o](https://platform.openai.com/docs/models/gpt-4o),
[GPT-4 Turbo](https://platform.openai.com/docs/models/gpt-4-turbo-and-gpt-4),
and all GPT-3.5 Turbo models since `gpt-3.5-turbo-1106`.
Setting to `{ "type": "json_schema", "json_schema": {...} }` enables Structured
Outputs which guarantees the model will match your supplied JSON schema. Learn
more in the
[Structured Outputs guide](https://platform.openai.com/docs/guides/structured-outputs).
Setting to `{ "type": "json_object" }` enables JSON mode, which guarantees the
message the model generates is valid JSON.
**Important:** when using JSON mode, you **must** also instruct the model to
produce JSON yourself via a system or user message. Without this, the model may
generate an unending stream of whitespace until the generation reaches the token
limit, resulting in a long-running and seemingly "stuck" request. Also note that
the message content may be partially cut off if `finish_reason="length"`, which
indicates the generation exceeded `max_tokens` or the conversation exceeded the
max context length.
stream: If `true`, returns a stream of events that happen during the Run as server-sent
events, terminating when the Run enters a terminal state with a `data: [DONE]`
message.
temperature: What sampling temperature to use, between 0 and 2. Higher values like 0.8 will
make the output more random, while lower values like 0.2 will make it more
focused and deterministic.
tool_choice: Controls which (if any) tool is called by the model. `none` means the model will
not call any tools and instead generates a message. `auto` is the default value
and means the model can pick between generating a message or calling one or more
tools. `required` means the model must call one or more tools before responding
to the user. Specifying a particular tool like `{"type": "file_search"}` or
`{"type": "function", "function": {"name": "my_function"}}` forces the model to
call that tool.
tools: Override the tools the assistant can use for this run. This is useful for
modifying the behavior on a per-run basis.
top_p: An alternative to sampling with temperature, called nucleus sampling, where the
model considers the results of the tokens with top_p probability mass. So 0.1
means only the tokens comprising the top 10% probability mass are considered.
We generally recommend altering this or temperature but not both.
truncation_strategy: Controls for how a thread will be truncated prior to the run. Use this to
control the intial context window of the run.
extra_headers: Send extra headers
extra_query: Add additional query parameters to the request
extra_body: Add additional JSON properties to the request
timeout: Override the client-level default timeout for this request, in seconds
"""
...
@overload
def create(
self,
thread_id: str,
*,
assistant_id: str,
stream: Literal[True],
additional_instructions: Optional[str] | NotGiven = NOT_GIVEN,
additional_messages: Optional[Iterable[run_create_params.AdditionalMessage]] | NotGiven = NOT_GIVEN,
instructions: Optional[str] | NotGiven = NOT_GIVEN,
max_completion_tokens: Optional[int] | NotGiven = NOT_GIVEN,
max_prompt_tokens: Optional[int] | NotGiven = NOT_GIVEN,
metadata: Optional[object] | NotGiven = NOT_GIVEN,
model: Union[str, ChatModel, None] | NotGiven = NOT_GIVEN,
parallel_tool_calls: bool | NotGiven = NOT_GIVEN,
response_format: Optional[AssistantResponseFormatOptionParam] | NotGiven = NOT_GIVEN,
temperature: Optional[float] | NotGiven = NOT_GIVEN,
tool_choice: Optional[AssistantToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
tools: Optional[Iterable[AssistantToolParam]] | NotGiven = NOT_GIVEN,
top_p: Optional[float] | NotGiven = NOT_GIVEN,
truncation_strategy: Optional[run_create_params.TruncationStrategy] | NotGiven = NOT_GIVEN,
# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
# The extra values given here take precedence over values defined on the client or passed to this method.
extra_headers: Headers | None = None,
extra_query: Query | None = None,
extra_body: Body | None = None,
timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
) -> Stream[AssistantStreamEvent]:
"""
Create a run.
Args:
assistant_id: The ID of the
[assistant](https://platform.openai.com/docs/api-reference/assistants) to use to
execute this run.
stream: If `true`, returns a stream of events that happen during the Run as server-sent
events, terminating when the Run enters a terminal state with a `data: [DONE]`
message.
additional_instructions: Appends additional instructions at the end of the instructions for the run. This
is useful for modifying the behavior on a per-run basis without overriding other
instructions.
additional_messages: Adds additional messages to the thread before creating the run.
instructions: Overrides the
[instructions](https://platform.openai.com/docs/api-reference/assistants/createAssistant)
of the assistant. This is useful for modifying the behavior on a per-run basis.
max_completion_tokens: The maximum number of completion tokens that may be used over the course of the
run. The run will make a best effort to use only the number of completion tokens
specified, across multiple turns of the run. If the run exceeds the number of
completion tokens specified, the run will end with status `incomplete`. See
`incomplete_details` for more info.
max_prompt_tokens: The maximum number of prompt tokens that may be used over the course of the run.
The run will make a best effort to use only the number of prompt tokens
specified, across multiple turns of the run. If the run exceeds the number of
prompt tokens specified, the run will end with status `incomplete`. See
`incomplete_details` for more info.
metadata: Set of 16 key-value pairs that can be attached to an object. This can be useful
for storing additional information about the object in a structured format. Keys
can be a maximum of 64 characters long and values can be a maxium of 512
characters long.
model: The ID of the [Model](https://platform.openai.com/docs/api-reference/models) to
be used to execute this run. If a value is provided here, it will override the
model associated with the assistant. If not, the model associated with the
assistant will be used.
parallel_tool_calls: Whether to enable
[parallel function calling](https://platform.openai.com/docs/guides/function-calling/parallel-function-calling)
during tool use.
response_format: Specifies the format that the model must output. Compatible with
[GPT-4o](https://platform.openai.com/docs/models/gpt-4o),
[GPT-4 Turbo](https://platform.openai.com/docs/models/gpt-4-turbo-and-gpt-4),
and all GPT-3.5 Turbo models since `gpt-3.5-turbo-1106`.
Setting to `{ "type": "json_schema", "json_schema": {...} }` enables Structured
Outputs which guarantees the model will match your supplied JSON schema. Learn
more in the
[Structured Outputs guide](https://platform.openai.com/docs/guides/structured-outputs).
Setting to `{ "type": "json_object" }` enables JSON mode, which guarantees the
message the model generates is valid JSON.
**Important:** when using JSON mode, you **must** also instruct the model to
produce JSON yourself via a system or user message. Without this, the model may
generate an unending stream of whitespace until the generation reaches the token
limit, resulting in a long-running and seemingly "stuck" request. Also note that
the message content may be partially cut off if `finish_reason="length"`, which
indicates the generation exceeded `max_tokens` or the conversation exceeded the
max context length.
temperature: What sampling temperature to use, between 0 and 2. Higher values like 0.8 will
make the output more random, while lower values like 0.2 will make it more
focused and deterministic.
tool_choice: Controls which (if any) tool is called by the model. `none` means the model will
not call any tools and instead generates a message. `auto` is the default value
and means the model can pick between generating a message or calling one or more
tools. `required` means the model must call one or more tools before responding
to the user. Specifying a particular tool like `{"type": "file_search"}` or
`{"type": "function", "function": {"name": "my_function"}}` forces the model to
call that tool.
tools: Override the tools the assistant can use for this run. This is useful for
modifying the behavior on a per-run basis.
top_p: An alternative to sampling with temperature, called nucleus sampling, where the
model considers the results of the tokens with top_p probability mass. So 0.1
means only the tokens comprising the top 10% probability mass are considered.
We generally recommend altering this or temperature but not both.
truncation_strategy: Controls for how a thread will be truncated prior to the run. Use this to
control the intial context window of the run.
extra_headers: Send extra headers
extra_query: Add additional query parameters to the request
extra_body: Add additional JSON properties to the request
timeout: Override the client-level default timeout for this request, in seconds
"""
...
@overload
def create(
self,
thread_id: str,
*,
assistant_id: str,
stream: bool,
additional_instructions: Optional[str] | NotGiven = NOT_GIVEN,
additional_messages: Optional[Iterable[run_create_params.AdditionalMessage]] | NotGiven = NOT_GIVEN,
instructions: Optional[str] | NotGiven = NOT_GIVEN,
max_completion_tokens: Optional[int] | NotGiven = NOT_GIVEN,
max_prompt_tokens: Optional[int] | NotGiven = NOT_GIVEN,
metadata: Optional[object] | NotGiven = NOT_GIVEN,
model: Union[str, ChatModel, None] | NotGiven = NOT_GIVEN,
parallel_tool_calls: bool | NotGiven = NOT_GIVEN,
response_format: Optional[AssistantResponseFormatOptionParam] | NotGiven = NOT_GIVEN,
temperature: Optional[float] | NotGiven = NOT_GIVEN,
tool_choice: Optional[AssistantToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
tools: Optional[Iterable[AssistantToolParam]] | NotGiven = NOT_GIVEN,
top_p: Optional[float] | NotGiven = NOT_GIVEN,
truncation_strategy: Optional[run_create_params.TruncationStrategy] | NotGiven = NOT_GIVEN,
# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
# The extra values given here take precedence over values defined on the client or passed to this method.
extra_headers: Headers | None = None,
extra_query: Query | None = None,
extra_body: Body | None = None,
timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
) -> Run | Stream[AssistantStreamEvent]:
"""
Create a run.
Args:
assistant_id: The ID of the
[assistant](https://platform.openai.com/docs/api-reference/assistants) to use to
execute this run.
stream: If `true`, returns a stream of events that happen during the Run as server-sent
events, terminating when the Run enters a terminal state with a `data: [DONE]`
message.
additional_instructions: Appends additional instructions at the end of the instructions for the run. This
is useful for modifying the behavior on a per-run basis without overriding other
instructions.
additional_messages: Adds additional messages to the thread before creating the run.
instructions: Overrides the
[instructions](https://platform.openai.com/docs/api-reference/assistants/createAssistant)
of the assistant. This is useful for modifying the behavior on a per-run basis.
max_completion_tokens: The maximum number of completion tokens that may be used over the course of the
run. The run will make a best effort to use only the number of completion tokens
specified, across multiple turns of the run. If the run exceeds the number of
completion tokens specified, the run will end with status `incomplete`. See
`incomplete_details` for more info.
max_prompt_tokens: The maximum number of prompt tokens that may be used over the course of the run.
The run will make a best effort to use only the number of prompt tokens
specified, across multiple turns of the run. If the run exceeds the number of
prompt tokens specified, the run will end with status `incomplete`. See
`incomplete_details` for more info.
metadata: Set of 16 key-value pairs that can be attached to an object. This can be useful
for storing additional information about the object in a structured format. Keys
can be a maximum of 64 characters long and values can be a maxium of 512
characters long.
model: The ID of the [Model](https://platform.openai.com/docs/api-reference/models) to
be used to execute this run. If a value is provided here, it will override the
model associated with the assistant. If not, the model associated with the
assistant will be used.
parallel_tool_calls: Whether to enable
[parallel function calling](https://platform.openai.com/docs/guides/function-calling/parallel-function-calling)
during tool use.
response_format: Specifies the format that the model must output. Compatible with
[GPT-4o](https://platform.openai.com/docs/models/gpt-4o),
[GPT-4 Turbo](https://platform.openai.com/docs/models/gpt-4-turbo-and-gpt-4),
and all GPT-3.5 Turbo models since `gpt-3.5-turbo-1106`.
Setting to `{ "type": "json_schema", "json_schema": {...} }` enables Structured
Outputs which guarantees the model will match your supplied JSON schema. Learn
more in the
[Structured Outputs guide](https://platform.openai.com/docs/guides/structured-outputs).
Setting to `{ "type": "json_object" }` enables JSON mode, which guarantees the
message the model generates is valid JSON.
**Important:** when using JSON mode, you **must** also instruct the model to
produce JSON yourself via a system or user message. Without this, the model may
generate an unending stream of whitespace until the generation reaches the token
limit, resulting in a long-running and seemingly "stuck" request. Also note that
the message content may be partially cut off if `finish_reason="length"`, which
indicates the generation exceeded `max_tokens` or the conversation exceeded the
max context length.
temperature: What sampling temperature to use, between 0 and 2. Higher values like 0.8 will
make the output more random, while lower values like 0.2 will make it more
focused and deterministic.
tool_choice: Controls which (if any) tool is called by the model. `none` means the model will
not call any tools and instead generates a message. `auto` is the default value
and means the model can pick between generating a message or calling one or more
tools. `required` means the model must call one or more tools before responding
to the user. Specifying a particular tool like `{"type": "file_search"}` or
`{"type": "function", "function": {"name": "my_function"}}` forces the model to
call that tool.
tools: Override the tools the assistant can use for this run. This is useful for
modifying the behavior on a per-run basis.
top_p: An alternative to sampling with temperature, called nucleus sampling, where the
model considers the results of the tokens with top_p probability mass. So 0.1
means only the tokens comprising the top 10% probability mass are considered.
We generally recommend altering this or temperature but not both.
truncation_strategy: Controls for how a thread will be truncated prior to the run. Use this to
control the intial context window of the run.
extra_headers: Send extra headers
extra_query: Add additional query parameters to the request
extra_body: Add additional JSON properties to the request
timeout: Override the client-level default timeout for this request, in seconds
"""
...
@required_args(["assistant_id"], ["assistant_id", "stream"])
def create(
self,
thread_id: str,
*,
assistant_id: str,
additional_instructions: Optional[str] | NotGiven = NOT_GIVEN,
additional_messages: Optional[Iterable[run_create_params.AdditionalMessage]] | NotGiven = NOT_GIVEN,
instructions: Optional[str] | NotGiven = NOT_GIVEN,
max_completion_tokens: Optional[int] | NotGiven = NOT_GIVEN,
max_prompt_tokens: Optional[int] | NotGiven = NOT_GIVEN,
metadata: Optional[object] | NotGiven = NOT_GIVEN,
model: Union[str, ChatModel, None] | NotGiven = NOT_GIVEN,
parallel_tool_calls: bool | NotGiven = NOT_GIVEN,
response_format: Optional[AssistantResponseFormatOptionParam] | NotGiven = NOT_GIVEN,
stream: Optional[Literal[False]] | Literal[True] | NotGiven = NOT_GIVEN,
temperature: Optional[float] | NotGiven = NOT_GIVEN,
tool_choice: Optional[AssistantToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
tools: Optional[Iterable[AssistantToolParam]] | NotGiven = NOT_GIVEN,
top_p: Optional[float] | NotGiven = NOT_GIVEN,
truncation_strategy: Optional[run_create_params.TruncationStrategy] | NotGiven = NOT_GIVEN,
# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
# The extra values given here take precedence over values defined on the client or passed to this method.
extra_headers: Headers | None = None,
extra_query: Query | None = None,
extra_body: Body | None = None,
timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
) -> Run | Stream[AssistantStreamEvent]:
if not thread_id:
raise ValueError(f"Expected a non-empty value for `thread_id` but received {thread_id!r}")
extra_headers = {"OpenAI-Beta": "assistants=v2", **(extra_headers or {})}
return self._post(
f"/threads/{thread_id}/runs",
body=maybe_transform(
{
"assistant_id": assistant_id,
"additional_instructions": additional_instructions,
"additional_messages": additional_messages,
"instructions": instructions,
"max_completion_tokens": max_completion_tokens,
"max_prompt_tokens": max_prompt_tokens,
"metadata": metadata,
"model": model,
"parallel_tool_calls": parallel_tool_calls,
"response_format": response_format,
"stream": stream,
"temperature": temperature,
"tool_choice": tool_choice,
"tools": tools,
"top_p": top_p,
"truncation_strategy": truncation_strategy,
},
run_create_params.RunCreateParams,
),
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=Run,
stream=stream or False,
stream_cls=Stream[AssistantStreamEvent],
)
def retrieve(
self,
run_id: str,
*,
thread_id: str,
# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
# The extra values given here take precedence over values defined on the client or passed to this method.
extra_headers: Headers | None = None,
extra_query: Query | None = None,
extra_body: Body | None = None,
timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
) -> Run:
"""
Retrieves a run.
Args:
extra_headers: Send extra headers
extra_query: Add additional query parameters to the request
extra_body: Add additional JSON properties to the request
timeout: Override the client-level default timeout for this request, in seconds
"""
if not thread_id:
raise ValueError(f"Expected a non-empty value for `thread_id` but received {thread_id!r}")
if not run_id:
raise ValueError(f"Expected a non-empty value for `run_id` but received {run_id!r}")
extra_headers = {"OpenAI-Beta": "assistants=v2", **(extra_headers or {})}
return self._get(
f"/threads/{thread_id}/runs/{run_id}",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=Run,
)
def update(
self,
run_id: str,
*,
thread_id: str,
metadata: Optional[object] | NotGiven = NOT_GIVEN,
# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
# The extra values given here take precedence over values defined on the client or passed to this method.
extra_headers: Headers | None = None,
extra_query: Query | None = None,
extra_body: Body | None = None,
timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
) -> Run:
"""
Modifies a run.
Args:
metadata: Set of 16 key-value pairs that can be attached to an object. This can be useful
for storing additional information about the object in a structured format. Keys
can be a maximum of 64 characters long and values can be a maxium of 512
characters long.
extra_headers: Send extra headers
extra_query: Add additional query parameters to the request
extra_body: Add additional JSON properties to the request
timeout: Override the client-level default timeout for this request, in seconds
"""
if not thread_id:
raise ValueError(f"Expected a non-empty value for `thread_id` but received {thread_id!r}")
if not run_id:
raise ValueError(f"Expected a non-empty value for `run_id` but received {run_id!r}")
extra_headers = {"OpenAI-Beta": "assistants=v2", **(extra_headers or {})}
return self._post(
f"/threads/{thread_id}/runs/{run_id}",
body=maybe_transform({"metadata": metadata}, run_update_params.RunUpdateParams),
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=Run,
)
def list(
self,
thread_id: str,
*,
after: str | NotGiven = NOT_GIVEN,
before: str | NotGiven = NOT_GIVEN,
limit: int | NotGiven = NOT_GIVEN,
order: Literal["asc", "desc"] | NotGiven = NOT_GIVEN,
# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
# The extra values given here take precedence over values defined on the client or passed to this method.
extra_headers: Headers | None = None,
extra_query: Query | None = None,
extra_body: Body | None = None,
timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
) -> SyncCursorPage[Run]:
"""
Returns a list of runs belonging to a thread.
Args:
after: A cursor for use in pagination. `after` is an object ID that defines your place
in the list. For instance, if you make a list request and receive 100 objects,
ending with obj_foo, your subsequent call can include after=obj_foo in order to
fetch the next page of the list.
before: A cursor for use in pagination. `before` is an object ID that defines your place
in the list. For instance, if you make a list request and receive 100 objects,
ending with obj_foo, your subsequent call can include before=obj_foo in order to
fetch the previous page of the list.
limit: A limit on the number of objects to be returned. Limit can range between 1 and
100, and the default is 20.
order: Sort order by the `created_at` timestamp of the objects. `asc` for ascending
order and `desc` for descending order.
extra_headers: Send extra headers
extra_query: Add additional query parameters to the request
extra_body: Add additional JSON properties to the request
timeout: Override the client-level default timeout for this request, in seconds
"""
if not thread_id:
raise ValueError(f"Expected a non-empty value for `thread_id` but received {thread_id!r}")
extra_headers = {"OpenAI-Beta": "assistants=v2", **(extra_headers or {})}
return self._get_api_list(
f"/threads/{thread_id}/runs",
page=SyncCursorPage[Run],
options=make_request_options(
extra_headers=extra_headers,
extra_query=extra_query,
extra_body=extra_body,
timeout=timeout,
query=maybe_transform(
{
"after": after,
"before": before,
"limit": limit,
"order": order,
},
run_list_params.RunListParams,
),
),
model=Run,
)
def cancel(
self,
run_id: str,
*,
thread_id: str,
# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
# The extra values given here take precedence over values defined on the client or passed to this method.
extra_headers: Headers | None = None,
extra_query: Query | None = None,
extra_body: Body | None = None,
timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
) -> Run:
"""
Cancels a run that is `in_progress`.
Args:
extra_headers: Send extra headers
extra_query: Add additional query parameters to the request
extra_body: Add additional JSON properties to the request
timeout: Override the client-level default timeout for this request, in seconds
"""
if not thread_id:
raise ValueError(f"Expected a non-empty value for `thread_id` but received {thread_id!r}")
if not run_id:
raise ValueError(f"Expected a non-empty value for `run_id` but received {run_id!r}")
extra_headers = {"OpenAI-Beta": "assistants=v2", **(extra_headers or {})}
return self._post(
f"/threads/{thread_id}/runs/{run_id}/cancel",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=Run,
)
def create_and_poll(
self,
*,
assistant_id: str,
additional_instructions: Optional[str] | NotGiven = NOT_GIVEN,
additional_messages: Optional[Iterable[run_create_params.AdditionalMessage]] | NotGiven = NOT_GIVEN,
instructions: Optional[str] | NotGiven = NOT_GIVEN,
max_completion_tokens: Optional[int] | NotGiven = NOT_GIVEN,
max_prompt_tokens: Optional[int] | NotGiven = NOT_GIVEN,
metadata: Optional[object] | NotGiven = NOT_GIVEN,
model: Union[str, ChatModel, None] | NotGiven = NOT_GIVEN,
parallel_tool_calls: bool | NotGiven = NOT_GIVEN,
response_format: Optional[AssistantResponseFormatOptionParam] | NotGiven = NOT_GIVEN,
temperature: Optional[float] | NotGiven = NOT_GIVEN,
tool_choice: Optional[AssistantToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
tools: Optional[Iterable[AssistantToolParam]] | NotGiven = NOT_GIVEN,
top_p: Optional[float] | NotGiven = NOT_GIVEN,
truncation_strategy: Optional[run_create_params.TruncationStrategy] | NotGiven = NOT_GIVEN,
poll_interval_ms: int | NotGiven = NOT_GIVEN,
thread_id: str,
# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
# The extra values given here take precedence over values defined on the client or passed to this method.
extra_headers: Headers | None = None,
extra_query: Query | None = None,
extra_body: Body | None = None,
timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
) -> Run:
"""
A helper to create a run an poll for a terminal state. More information on Run
lifecycles can be found here:
https://platform.openai.com/docs/assistants/how-it-works/runs-and-run-steps
"""
run = self.create(
thread_id=thread_id,
assistant_id=assistant_id,
additional_instructions=additional_instructions,
additional_messages=additional_messages,
instructions=instructions,
max_completion_tokens=max_completion_tokens,
max_prompt_tokens=max_prompt_tokens,
metadata=metadata,
model=model,
response_format=response_format,
temperature=temperature,
tool_choice=tool_choice,
parallel_tool_calls=parallel_tool_calls,
# We assume we are not streaming when polling
stream=False,
tools=tools,
truncation_strategy=truncation_strategy,
top_p=top_p,
extra_headers=extra_headers,
extra_query=extra_query,
extra_body=extra_body,
timeout=timeout,
)
return self.poll(
run.id,
thread_id=thread_id,
extra_headers=extra_headers,
extra_query=extra_query,
extra_body=extra_body,
poll_interval_ms=poll_interval_ms,
timeout=timeout,
)
@overload
@typing_extensions.deprecated("use `stream` instead")
def create_and_stream(
self,
*,
assistant_id: str,
additional_instructions: Optional[str] | NotGiven = NOT_GIVEN,
additional_messages: Optional[Iterable[run_create_params.AdditionalMessage]] | NotGiven = NOT_GIVEN,
instructions: Optional[str] | NotGiven = NOT_GIVEN,
max_completion_tokens: Optional[int] | NotGiven = NOT_GIVEN,
max_prompt_tokens: Optional[int] | NotGiven = NOT_GIVEN,
metadata: Optional[object] | NotGiven = NOT_GIVEN,
model: Union[str, ChatModel, None] | NotGiven = NOT_GIVEN,
parallel_tool_calls: bool | NotGiven = NOT_GIVEN,
response_format: Optional[AssistantResponseFormatOptionParam] | NotGiven = NOT_GIVEN,
temperature: Optional[float] | NotGiven = NOT_GIVEN,
tool_choice: Optional[AssistantToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
tools: Optional[Iterable[AssistantToolParam]] | NotGiven = NOT_GIVEN,
top_p: Optional[float] | NotGiven = NOT_GIVEN,
truncation_strategy: Optional[run_create_params.TruncationStrategy] | NotGiven = NOT_GIVEN,
thread_id: str,
# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
# The extra values given here take precedence over values defined on the client or passed to this method.
extra_headers: Headers | None = None,
extra_query: Query | None = None,
extra_body: Body | None = None,
timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
) -> AssistantStreamManager[AssistantEventHandler]:
"""Create a Run stream"""
...
@overload
@typing_extensions.deprecated("use `stream` instead")
def create_and_stream(
self,
*,
assistant_id: str,
additional_instructions: Optional[str] | NotGiven = NOT_GIVEN,
additional_messages: Optional[Iterable[run_create_params.AdditionalMessage]] | NotGiven = NOT_GIVEN,
instructions: Optional[str] | NotGiven = NOT_GIVEN,
max_completion_tokens: Optional[int] | NotGiven = NOT_GIVEN,
max_prompt_tokens: Optional[int] | NotGiven = NOT_GIVEN,
metadata: Optional[object] | NotGiven = NOT_GIVEN,
model: Union[str, ChatModel, None] | NotGiven = NOT_GIVEN,
parallel_tool_calls: bool | NotGiven = NOT_GIVEN,
response_format: Optional[AssistantResponseFormatOptionParam] | NotGiven = NOT_GIVEN,
temperature: Optional[float] | NotGiven = NOT_GIVEN,
tool_choice: Optional[AssistantToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
tools: Optional[Iterable[AssistantToolParam]] | NotGiven = NOT_GIVEN,
top_p: Optional[float] | NotGiven = NOT_GIVEN,
truncation_strategy: Optional[run_create_params.TruncationStrategy] | NotGiven = NOT_GIVEN,
thread_id: str,
event_handler: AssistantEventHandlerT,
# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
# The extra values given here take precedence over values defined on the client or passed to this method.
extra_headers: Headers | None = None,
extra_query: Query | None = None,
extra_body: Body | None = None,
timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
) -> AssistantStreamManager[AssistantEventHandlerT]:
"""Create a Run stream"""
...
@typing_extensions.deprecated("use `stream` instead")
def create_and_stream(
self,
*,
assistant_id: str,
additional_instructions: Optional[str] | NotGiven = NOT_GIVEN,
additional_messages: Optional[Iterable[run_create_params.AdditionalMessage]] | NotGiven = NOT_GIVEN,
instructions: Optional[str] | NotGiven = NOT_GIVEN,
max_completion_tokens: Optional[int] | NotGiven = NOT_GIVEN,
max_prompt_tokens: Optional[int] | NotGiven = NOT_GIVEN,
metadata: Optional[object] | NotGiven = NOT_GIVEN,
model: Union[str, ChatModel, None] | NotGiven = NOT_GIVEN,
parallel_tool_calls: bool | NotGiven = NOT_GIVEN,
response_format: Optional[AssistantResponseFormatOptionParam] | NotGiven = NOT_GIVEN,
temperature: Optional[float] | NotGiven = NOT_GIVEN,
tool_choice: Optional[AssistantToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
tools: Optional[Iterable[AssistantToolParam]] | NotGiven = NOT_GIVEN,
top_p: Optional[float] | NotGiven = NOT_GIVEN,
truncation_strategy: Optional[run_create_params.TruncationStrategy] | NotGiven = NOT_GIVEN,
thread_id: str,
event_handler: AssistantEventHandlerT | None = None,
# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
# The extra values given here take precedence over values defined on the client or passed to this method.
extra_headers: Headers | None = None,
extra_query: Query | None = None,
extra_body: Body | None = None,
timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
) -> AssistantStreamManager[AssistantEventHandler] | AssistantStreamManager[AssistantEventHandlerT]:
"""Create a Run stream"""
if not thread_id:
raise ValueError(f"Expected a non-empty value for `thread_id` but received {thread_id!r}")
extra_headers = {
"OpenAI-Beta": "assistants=v2",
"X-Stainless-Stream-Helper": "threads.runs.create_and_stream",
"X-Stainless-Custom-Event-Handler": "true" if event_handler else "false",
**(extra_headers or {}),
}
make_request = partial(
self._post,
f"/threads/{thread_id}/runs",
body=maybe_transform(
{
"assistant_id": assistant_id,
"additional_instructions": additional_instructions,
"additional_messages": additional_messages,
"instructions": instructions,
"max_completion_tokens": max_completion_tokens,
"max_prompt_tokens": max_prompt_tokens,
"metadata": metadata,
"model": model,
"response_format": response_format,
"temperature": temperature,
"tool_choice": tool_choice,
"stream": True,
"tools": tools,
"truncation_strategy": truncation_strategy,
"parallel_tool_calls": parallel_tool_calls,
"top_p": top_p,
},
run_create_params.RunCreateParams,
),
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=Run,
stream=True,
stream_cls=Stream[AssistantStreamEvent],
)
return AssistantStreamManager(make_request, event_handler=event_handler or AssistantEventHandler())
def poll(
self,
run_id: str,
thread_id: str,
extra_headers: Headers | None = None,
extra_query: Query | None = None,
extra_body: Body | None = None,
timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
poll_interval_ms: int | NotGiven = NOT_GIVEN,
) -> Run:
"""
A helper to poll a run status until it reaches a terminal state. More
information on Run lifecycles can be found here:
https://platform.openai.com/docs/assistants/how-it-works/runs-and-run-steps
"""
extra_headers = {"X-Stainless-Poll-Helper": "true", **(extra_headers or {})}
if is_given(poll_interval_ms):
extra_headers["X-Stainless-Custom-Poll-Interval"] = str(poll_interval_ms)
terminal_states = {"requires_action", "cancelled", "completed", "failed", "expired", "incomplete"}
while True:
response = self.with_raw_response.retrieve(
thread_id=thread_id,
run_id=run_id,
extra_headers=extra_headers,
extra_body=extra_body,
extra_query=extra_query,
timeout=timeout,
)
run = response.parse()
# Return if we reached a terminal state
if run.status in terminal_states:
return run
if not is_given(poll_interval_ms):
from_header = response.headers.get("openai-poll-after-ms")
if from_header is not None:
poll_interval_ms = int(from_header)
else:
poll_interval_ms = 1000
self._sleep(poll_interval_ms / 1000)
@overload
def stream(
self,
*,
assistant_id: str,
additional_instructions: Optional[str] | NotGiven = NOT_GIVEN,
additional_messages: Optional[Iterable[run_create_params.AdditionalMessage]] | NotGiven = NOT_GIVEN,
instructions: Optional[str] | NotGiven = NOT_GIVEN,
max_completion_tokens: Optional[int] | NotGiven = NOT_GIVEN,
max_prompt_tokens: Optional[int] | NotGiven = NOT_GIVEN,
metadata: Optional[object] | NotGiven = NOT_GIVEN,
model: Union[str, ChatModel, None] | NotGiven = NOT_GIVEN,
parallel_tool_calls: bool | NotGiven = NOT_GIVEN,
response_format: Optional[AssistantResponseFormatOptionParam] | NotGiven = NOT_GIVEN,
temperature: Optional[float] | NotGiven = NOT_GIVEN,
tool_choice: Optional[AssistantToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
tools: Optional[Iterable[AssistantToolParam]] | NotGiven = NOT_GIVEN,
top_p: Optional[float] | NotGiven = NOT_GIVEN,
truncation_strategy: Optional[run_create_params.TruncationStrategy] | NotGiven = NOT_GIVEN,
thread_id: str,
# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
# The extra values given here take precedence over values defined on the client or passed to this method.
extra_headers: Headers | None = None,
extra_query: Query | None = None,
extra_body: Body | None = None,
timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
) -> AssistantStreamManager[AssistantEventHandler]:
"""Create a Run stream"""
...
@overload
def stream(
self,
*,
assistant_id: str,
additional_instructions: Optional[str] | NotGiven = NOT_GIVEN,
additional_messages: Optional[Iterable[run_create_params.AdditionalMessage]] | NotGiven = NOT_GIVEN,
instructions: Optional[str] | NotGiven = NOT_GIVEN,
max_completion_tokens: Optional[int] | NotGiven = NOT_GIVEN,
max_prompt_tokens: Optional[int] | NotGiven = NOT_GIVEN,
metadata: Optional[object] | NotGiven = NOT_GIVEN,
model: Union[str, ChatModel, None] | NotGiven = NOT_GIVEN,
parallel_tool_calls: bool | NotGiven = NOT_GIVEN,
response_format: Optional[AssistantResponseFormatOptionParam] | NotGiven = NOT_GIVEN,
temperature: Optional[float] | NotGiven = NOT_GIVEN,