a _gA@sddlmZddlZddlmZmZmZmZddlm Z ddlm Z m Z ddl Z ddl mZdd lmZmZmZmZmZmZdd lmZmZmZmZmZdd lmZmZmZm Z dd l!m"Z"dd l#m$Z$m%Z%ddl&m'Z'm(Z(ddl)m*Z*m+Z+ddl,m-Z-m.Z.ddl/m0Z0m1Z1ddl2m3Z3m4Z4m5Z5m6Z6m7Z7m8Z8ddl9m:Z:ddl;mZ>m?Z?ddl@mAZAddlBmCZCddlDmEZEddlFmGZGddlHmIZIddlJmKZKddlLmMZMddgZNGddde$ZOGddde%ZPGd d!d!ZQGd"d#d#ZRGd$d%d%ZSGd&d'd'ZTdS)() annotationsN)ListUnionIterableOptional)partial)Literaloverload)_legacy_response)Steps AsyncStepsStepsWithRawResponseAsyncStepsWithRawResponseStepsWithStreamingResponseAsyncStepsWithStreamingResponse) NOT_GIVENBodyQueryHeadersNotGiven)is_given required_argsmaybe_transformasync_maybe_transform)cached_property)SyncAPIResourceAsyncAPIResource)to_streamed_response_wrapper"async_to_streamed_response_wrapper)Stream AsyncStream)SyncCursorPageAsyncCursorPage)AsyncPaginatormake_request_options)AssistantEventHandlerAssistantEventHandlerTAssistantStreamManagerAsyncAssistantEventHandlerAsyncAssistantEventHandlerTAsyncAssistantStreamManager) ChatModel)run_list_paramsrun_create_paramsrun_update_paramsrun_submit_tool_outputs_params)Run)Metadata)AssistantToolParam)AssistantStreamEvent)RunStepInclude)AssistantToolChoiceOptionParam)"AssistantResponseFormatOptionParamRuns AsyncRunsc@sLeZdZeddddZeddddZeddd d Zeeeeeeeeeeeeeeeeeed d d ed d d dddddddddddddddddddddd d!d"d#Z eeeeeeeeeeeeeeeeed d d ed$d d d%ddddddddddddddddddddd&d'd(d#Z eeeeeeeeeeeeeeeeed d d ed$d d d)ddddddddddddddddddddd*d'd+d#Z e d,gd,d-geeeeeeeeeeeeeeeeed d d ed d d dddddddddddd.dddddddddd*d!d/d#Z d d d ed0d d ddddd d1d2d3Z ed d d ed4d d dddddd d5d6d7Z eeeed d d ed8d d9d9d:d;dddddd?Z d d d ed0d d ddddd d1d@dAZeeeeeeeeeeeeeeeeed d d edBd ddddddddddddddddd:d ddddd dCdDdEZeedFeeeeeeeeeeeeeeed d d edGd dddddddddddddddd dddddHdIdJdKZeedFeeeeeeeeeeeeeeed d d edGd dddddddddddddddd dLdddddMdNdOdKZedFeeeeeeeeeeeeeeed d d d edPd dddddddddddddddd dQdddddRdNdSdKZd d d eefd d ddddd:d dTdUdVZeeeeeeeeeeeeeeeeed d d ed$d ddddddddddddddddd dddddHdWdXdYZeeeeeeeeeeeeeeeeed d d ed$d ddddddddddddddddd dLdddddMdZd[dYZeeeeeeeeeeeeeeeed d d d ed\d ddddddddddddddddd dQdddddRdZd]dYZeed d d ed^d d d_dddddd d` dadbZed d d ed0d d d%d_ddddd&dc dddbZed d d ed0d d d)d_ddddd*dc dedbZe dfdgggdhed d d ed^d d d_d.ddddd*d` didbZed d d edjd_d d d:ddddd dk dldmZed d d ed0d_d d dddddHdndodpZed d d ed0d_d d dLdddddMdq drdpZd d d d edsd_d d dQdddddRdq dtdpZd S)ur9r returncCs t|jSN)r _clientselfrAu/var/www/html/cobodadashboardai.evdpl.com/venv/lib/python3.9/site-packages/openai/resources/beta/threads/runs/runs.pysteps=sz Runs.stepsRunsWithRawResponsecCst|Sa This property can be used as a prefix for any HTTP method call to return the raw response object instead of the parsed content. 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For more information, see https://www.github.com/openai/openai-python#with_streaming_response )rGr?rArArBwith_streaming_responseKszRuns.with_streaming_responseNincludeadditional_instructionsadditional_messages instructionsmax_completion_tokensmax_prompt_tokensmetadatamodelparallel_tool_callsreasoning_effortresponse_formatstream temperature tool_choicetoolstop_ptruncation_strategy extra_headers extra_query extra_bodytimeoutstrList[RunStepInclude] | NotGivenOptional[str] | NotGivenBOptional[Iterable[run_create_params.AdditionalMessage]] | NotGivenOptional[int] | NotGivenOptional[Metadata] | NotGiven&Union[str, ChatModel, None] | NotGivenbool | NotGiven5Optional[Literal['low', 'medium', 'high']] | NotGiven7Optional[AssistantResponseFormatOptionParam] | NotGiven#Optional[Literal[False]] | NotGivenOptional[float] | NotGiven3Optional[AssistantToolChoiceOptionParam] | NotGiven1Optional[Iterable[AssistantToolParam]] | NotGiven9Optional[run_create_params.TruncationStrategy] | NotGivenHeaders | None Query | None Body | None'float | httpx.Timeout | None | NotGivenr2 thread_id assistant_idrKrLrMrNrOrPrQrRrSrTrUrVrWrXrYrZr[r\r]r^r_r<cCsdSa 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. include: A list of additional fields to include in the response. Currently the only supported value is `step_details.tool_calls[*].file_search.results[*].content` to fetch the file search result content. See the [file search tool documentation](https://platform.openai.com/docs/assistants/tools/file-search#customizing-file-search-settings) for more information. 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, and querying for objects via API or the dashboard. Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters. 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#configuring-parallel-function-calling) during tool use. reasoning_effort: **o1 and o3-mini models only** Constrains effort on reasoning for [reasoning models](https://platform.openai.com/docs/guides/reasoning). Currently supported values are `low`, `medium`, and `high`. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response. 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 ensures 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 ensures 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 NrAr@rtrurKrLrMrNrOrPrQrRrSrTrUrVrWrXrYrZr[r\r]r^r_rArArBcreateTsz Runs.createrKrLrMrNrOrPrQrRrSrTrUrWrXrYrZr[r\r]r^r_ Literal[True]zStream[AssistantStreamEvent]rtrurVrKrLrMrNrOrPrQrRrSrTrUrWrXrYrZr[r\r]r^r_r<cCsdSa 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. include: A list of additional fields to include in the response. Currently the only supported value is `step_details.tool_calls[*].file_search.results[*].content` to fetch the file search result content. See the [file search tool documentation](https://platform.openai.com/docs/assistants/tools/file-search#customizing-file-search-settings) for more information. 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, and querying for objects via API or the dashboard. Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters. 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#configuring-parallel-function-calling) during tool use. reasoning_effort: **o1 and o3-mini models only** Constrains effort on reasoning for [reasoning models](https://platform.openai.com/docs/guides/reasoning). Currently supported values are `low`, `medium`, and `high`. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response. 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 ensures 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 ensures 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. 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Values are strings with a maximum length of 512 characters. 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 rrrrrrrQrrrr)rrrr0RunUpdateParamsr&r2r@rrtrQr\r]r^r_rArArBupdates z Runs.updateafterbeforelimitorderr\r]r^r_str | NotGivenint | NotGiven!Literal['asc', 'desc'] | NotGivenzSyncCursorPage[Run] rtrrrrr\r]r^r_r<c Cs`|std|ddi|pi}|jd|dttt|||| t||||dtjdtdS a! 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. 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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 rrrrrr/cancelrrrrr&r2rrArArBcancelsz Runs.cancelrKrLrMrNrOrPrQrRrSrTrUrWrXrYrZr[poll_interval_msr\r]r^r_rurKrLrMrNrOrPrQrRrSrTrUrWrXrYrZr[rrtr\r]r^r_r<cCsR|j|||||||||| | | || | d|||||||d}|j|j||||||dS) A helper to create a run an poll for a terminal state. 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More information on Run lifecycles can be found here: https://platform.openai.com/docs/assistants/how-it-works/runs-and-run-steps X-Stainless-Poll-Helperr X-Stainless-Custom-Poll-Interval> incompletefailedexpired completedrequires_action cancelledrtrr\r^r]r_openai-poll-after-msN rr`rFrparsestatusheadersgetintZ_sleep r@rrtr\r]r^r_rZterminal_statesresponserZ from_headerrArArBrs*     z Runs.poll)rurKrLrMrNrOrPrQrRrSrTrUrWrXrYrZr[rtr\r]r^r_r<cCsdSrrA)r@rurKrLrMrNrOrPrQrRrSrTrUrWrXrYrZr[rtr\r]r^r_rArArBrVsz Runs.streamrurKrLrMrNrOrPrQrRrSrTrUrWrXrYrZr[rtrr\r]r^r_r<cCsdSrrAr@rurKrLrMrNrOrPrQrRrSrTrUrWrXrYrZr[rtrr\r]r^r_rArArBrV3srKrLrMrNrOrPrQrRrSrTrUrWrXrYrZr[rr\r]r^r_cCs|std|dd|rdndd|p*i}t|jd|dt|||||||| | | |d || | ||d tjt||||td |itjd td tt d }t ||pt dSrrrrrrrrrT)rurLrMrNrOrPrQrRrUrWrXrVrYrSrTr[rZrKrrrr)r@rurKrLrMrNrOrPrQrRrSrTrUrWrXrYrZr[rtrr\r]r^r_rrArArBrVTsX  $rVr\r]r^r_3Iterable[run_submit_tool_outputs_params.ToolOutput] rrt tool_outputsrVr\r]r^r_r<c CsdSam When a run has the `status: "requires_action"` and `required_action.type` is `submit_tool_outputs`, this endpoint can be used to submit the outputs from the tool calls once they're all completed. All outputs must be submitted in a single request. Args: tool_outputs: A list of tools for which the outputs are being submitted. stream: If `true`, returns a stream of events that happen during the Run as server-sent events, terminating when the Run enters a terminal state with a `data: [DONE]` message. extra_headers: Send extra headers extra_query: Add additional query parameters to the request extra_body: Add additional JSON properties to the request timeout: Override the client-level default timeout for this request, in seconds NrA r@rrtrrVr\r]r^r_rArArBsubmit_tool_outputss$zRuns.submit_tool_outputs rrtrVrr\r]r^r_r<c CsdSam When a run has the `status: "requires_action"` and `required_action.type` is `submit_tool_outputs`, this endpoint can be used to submit the outputs from the tool calls once they're all completed. All outputs must be submitted in a single request. 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