ޠjb%SSKJr SSKrSSKrSSKrSSKrSSKJr SSKJr SSK J r J r J r J r JrJrJrJrJrJrJrJr SSKJr SSKJrJr SSKrSSKJr S S KJr S S K J!r!J"r"J#r#J$r$J%r%J&r&J'r'J(r(J)r) S S K*J+r+J,r,J-r-J.r.J/r/ S S K0J1r1 S SK2J3r3 S SK4J5r5 S SK6J7r7J8r8 S SK9J:r:J;r; SSKr>J?r?J@r@JArAJBrB S SKCJDrDJErE S SKFJGrGJHrH SSKIJJrJJKrKJLrLJMrMJNrNJOrO S SKPJQrQJRrR S SKSJTrT S SKUJVrVJWrW S SKXJYrY S SKZJ[r[J\r\J]r]J^r^ S SK_J`r`JaraJbrc S SKdJere S SKfJgrgJhrh S SKiJjrj S S KkJlrl S S!KmJnrnJoroJprp S S"KqJrrr S S#KsJtrt S S$KuJvrvJwrw S S%KxJyry S S&KzJ{r{ S S'K|J}r} S S(K~Jr S S)KJr S S*KJr S S+KJr S S,KJr S S-KJrJr S S.KJr S S/KJr S S0KJr S S1KJr \ (aSS2KJr SS2KJr S S3KJrJr S4S5/r\GR8"\5rS6\S7'"S8S4\75r"S9S5\85r"S:S;5r"S<S=5r"S>S?5r"S@SA5rSSSBjr"SCSD5r"SESF5r"SGSH5r"SISJ5r"SKSL5r"SMSN\5r"SOSP5r"SQSR\5rg)T) annotationsN)copy) TracebackType) TYPE_CHECKINGAnyListTypeUnionCallableIterableIteratorOptional Awaitable AsyncIteratorcast)partial)Literaloverload) BaseModel)_legacy_response) NOT_GIVENBodyOmitQueryHeadersNoneTypeNotGivenomit not_given)is_given path_templatemaybe_transformstrip_not_givenasync_maybe_transform)cached_property)normalize_httpx_url)construct_type_unchecked)SyncAPIResourceAsyncAPIResource)to_streamed_response_wrapper"async_to_streamed_response_wrapper) InputItemsAsyncInputItemsInputItemsWithRawResponseAsyncInputItemsWithRawResponseInputItemsWithStreamingResponse$AsyncInputItemsWithStreamingResponse)Stream AsyncStream)PydanticFunctionToolResponsesPydanticFunctionTool) InputTokensAsyncInputTokensInputTokensWithRawResponseAsyncInputTokensWithRawResponse InputTokensWithStreamingResponse%AsyncInputTokensWithStreamingResponse) OpenAIErrorWebSocketConnectionClosedError) SendQueue)_merge_mappingsmake_request_options)EventHandlerRegistry)response_create_paramsresponse_compact_paramsresponse_retrieve_paramsresponses_client_event_param) TextFormatTparse_responsetype_to_text_format_param)Response) ToolParamParseableToolParam) ServiceTier)Metadata)ReconnectingEventReconnectingOverridesis_recoverable_close) Reasoning)ParsedResponse)ResponseStreamManagerAsyncResponseStreamManager)CompactedResponse)WebSocketConnectionOptions)ResponseIncludable)ResponsesModel)ResponseInputParam)ResponsePromptParam)ResponseStreamEvent)ResponsesClientEvent)ResponseWsErrorResponsesServerEvent)ResponseInputItemParam)ResponseSteerInputParam)ResponseTextConfigParam)ResponsesClientEventParam)ClientConnection)OpenAI AsyncOpenAI ResponsesAsyncResponseszlogging.Loggerlogc&" \rSrSr\S,Sj5r\S-Sj5r\S.Sj5r\S/Sj5r\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ SSS\ S.#S0Sjj5r \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ SSS\ S ."S1S jj5r \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ SSS\ S ."S2S jj5r \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ SSS\ S.#S3S jjr \ \ \ \ SSS\ S .S4Sjj5r\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ SSS\ S.!S5Sjj5r\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ SSS\ S.%S6Sjjr\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ SSS\ S.%S7Sjjr\ \ \ \ \ SSS\ S.S8Sjj5r\ \ \ SSS\ S.S9Sjj5r\ \ \ SSS\ S.S:Sjj5r\ S\ \ SSS\ S.S:Sjj5r\ \ \ \ SSS\ S.S;Sjj5r\ \ \ \ SSS\ S.SS"jjrSSS\ S!.S?S#jjr\ \ \ \ \ \ \ SSS\ S$. S@S%jjr000SS&S'S(S)4SAS*jjrS+rg)Brhic,[UR5$N)r._clientselfs ^/var/www/html/gaurav/venv/lib/python3.13/site-packages/openai/resources/responses/responses.py input_itemsResponses.input_itemsjs$,,''c,[UR5$rn)r8rorps rr input_tokensResponses.input_tokensns4<<((ruc[U5$z This property can be used as a prefix for any HTTP method call to return the raw response object instead of the parsed content. For more information, see https://www.github.com/openai/openai-python#accessing-raw-response-data-eg-headers )ResponsesWithRawResponserps rrwith_raw_responseResponses.with_raw_responsers(--ruc[U5$z An alternative to `.with_raw_response` that doesn't eagerly read the response body. For more information, see https://www.github.com/openai/openai-python#with_streaming_response )ResponsesWithStreamingResponserps rrwith_streaming_response!Responses.with_streaming_response|s.d33ruN# backgroundcontext_management conversationincludeinput instructionsmax_output_tokensmax_tool_callsmetadatamodel moderationparallel_tool_callsprevious_response_idpromptprompt_cache_keyprompt_cache_optionsprompt_cache_retention reasoningsafety_identifier service_tierstorestreamstream_options temperaturetext tool_choicetools top_logprobstop_p truncationuser extra_headers extra_query extra_bodytimeoutc#ga4Creates a model response. Provide [text](https://platform.openai.com/docs/guides/text) or [image](https://platform.openai.com/docs/guides/images) inputs to generate [text](https://platform.openai.com/docs/guides/text) or [JSON](https://platform.openai.com/docs/guides/structured-outputs) outputs. Have the model call your own [custom code](https://platform.openai.com/docs/guides/function-calling) or use built-in [tools](https://platform.openai.com/docs/guides/tools) like [web search](https://platform.openai.com/docs/guides/tools-web-search) or [file search](https://platform.openai.com/docs/guides/tools-file-search) to use your own data as input for the model's response. Args: background: Whether to run the model response in the background. [Learn more](https://platform.openai.com/docs/guides/background). context_management: Context management configuration for this request. conversation: The conversation that this response belongs to. Items from this conversation are prepended to `input_items` for this response request. Input items and output items from this response are automatically added to this conversation after this response completes. include: Specify additional output data to include in the model response. Currently supported values are: - `web_search_call.action.sources`: Include the sources of the web search tool call. - `code_interpreter_call.outputs`: Includes the outputs of python code execution in code interpreter tool call items. - `computer_call_output.output.image_url`: Include image urls from the computer call output. - `file_search_call.results`: Include the search results of the file search tool call. - `message.input_image.image_url`: Include image urls from the input message. - `message.output_text.logprobs`: Include logprobs with assistant messages. - `reasoning.encrypted_content`: Includes an encrypted version of reasoning tokens in reasoning item outputs. This enables reasoning items to be used in multi-turn conversations when using the Responses API statelessly (like when the `store` parameter is set to `false`, or when an organization is enrolled in the zero data retention program). input: Text, image, or file inputs to the model, used to generate a response. Learn more: - [Text inputs and outputs](https://platform.openai.com/docs/guides/text) - [Image inputs](https://platform.openai.com/docs/guides/images) - [File inputs](https://platform.openai.com/docs/guides/pdf-files) - [Conversation state](https://platform.openai.com/docs/guides/conversation-state) - [Function calling](https://platform.openai.com/docs/guides/function-calling) instructions: A system (or developer) message inserted into the model's context. When using along with `previous_response_id`, the instructions from a previous response will not be carried over to the next response. This makes it simple to swap out system (or developer) messages in new responses. max_output_tokens: An upper bound for the number of tokens that can be generated for a response, including visible output tokens and [reasoning tokens](https://platform.openai.com/docs/guides/reasoning). max_tool_calls: The maximum number of total calls to built-in tools that can be processed in a response. This maximum number applies across all built-in tool calls, not per individual tool. Any further attempts to call a tool by the model will be ignored. 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: Model ID used to generate the response, like `gpt-6-astra`. OpenAI offers a wide range of models with different capabilities, performance characteristics, and price points. Refer to the [model guide](https://platform.openai.com/docs/models) to browse and compare available models. moderation: Configuration for running moderation on the input and output of this response. parallel_tool_calls: Whether to allow the model to run tool calls in parallel. previous_response_id: The unique ID of the previous response to the model. Use this to create multi-turn conversations. Learn more about [conversation state](https://platform.openai.com/docs/guides/conversation-state). Cannot be used in conjunction with `conversation`. prompt: Reference to a prompt template and its variables. [Learn more](https://platform.openai.com/docs/guides/text?api-mode=responses#reusable-prompts). prompt_cache_key: Used by OpenAI to cache responses for similar requests to optimize your cache hit rates. Replaces the `user` field. [Learn more](https://platform.openai.com/docs/guides/prompt-caching). prompt_cache_options: Options for prompt caching. Supported for `gpt-5.6` and later models. By default, OpenAI automatically chooses one implicit cache breakpoint. You can add explicit breakpoints to content blocks with `prompt_cache_breakpoint`. Each request can write up to four breakpoints. For cache matching, OpenAI considers up to the latest 80 breakpoints in the conversation, without a content-block lookback limit. Set `mode` to `explicit` to disable the implicit breakpoint. The `ttl` defaults to `30m`, which is currently the only supported value. See the [prompt caching guide](https://platform.openai.com/docs/guides/prompt-caching) for current details. prompt_cache_retention: Deprecated. Use `prompt_cache_options.ttl` instead. The retention policy for the prompt cache. Set to `24h` to enable extended prompt caching, which keeps cached prefixes active for longer, up to a maximum of 24 hours. [Learn more](https://platform.openai.com/docs/guides/prompt-caching#prompt-cache-retention). This field expresses a maximum retention policy, while `prompt_cache_options.ttl` expresses a minimum cache lifetime. The two fields are independent and do not interact. For `gpt-5.5`, `gpt-5.5-pro`, and future models, only `24h` is supported. For older models that support both `in_memory` and `24h`, the default depends on your organization's data retention policy: - Organizations without ZDR enabled default to `24h`. - Organizations with ZDR enabled default to `in_memory` when `prompt_cache_retention` is not specified. reasoning: Configuration options for [reasoning models](https://platform.openai.com/docs/guides/reasoning). safety_identifier: A stable identifier used to help detect users of your application that may be violating OpenAI's usage policies. The IDs should be a string that uniquely identifies each user, with a maximum length of 64 characters. We recommend hashing their username or email address, in order to avoid sending us any identifying information. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#safety-identifiers). service_tier: Specifies the processing type used for serving the request. - If set to 'auto', then the request will be processed with the service tier configured in the Project settings. Unless otherwise configured, the Project will use 'default'. - If set to 'default', then the request will be processed with the standard pricing and performance for the selected model. - If set to '[flex](https://platform.openai.com/docs/guides/flex-processing)', then the request will be processed with the Flex Processing service tier. - To opt-in to [Fast mode](/api/docs/guides/fast-mode) at the request level, include the `service_tier=fast` or `service_tier=priority` parameter for Responses or Chat Completions. The response will show `service_tier=priority` regardless of if you specify `service_tier=fast` or `priority` in your request. - If set to 'ultrafast', then the request will be processed with the access-controlled Ultrafast Processing service tier. This tier is currently available for `gpt-5.6-sol`; a response served through it will show `service_tier=ultrafast`. - When not set, the default behavior is 'auto'. When the `service_tier` parameter is set, the response body will include the `service_tier` value based on the processing mode actually used to serve the request. This response value may be different from the value set in the parameter. store: Whether to store the generated model response for later retrieval via API. Defaults to true when omitted. If set to true, response data will be stored for at least 30 days, subject to the [data retention exceptions](/api/docs/guides/your-data#v1responses). stream: If set to true, the model response data will be streamed to the client as it is generated using [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format). See the [Streaming section below](https://platform.openai.com/docs/api-reference/responses-streaming) for more information. stream_options: Options for streaming responses. Only set this when you set `stream: true`. 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. We generally recommend altering this or `top_p` but not both. text: Configuration options for a text response from the model. Can be plain text or structured JSON data. Learn more: - [Text inputs and outputs](https://platform.openai.com/docs/guides/text) - [Structured Outputs](https://platform.openai.com/docs/guides/structured-outputs) tool_choice: How the model should select which tool (or tools) to use when generating a response. See the `tools` parameter to see how to specify which tools the model can call. tools: An array of tools the model may call while generating a response. You can specify which tool to use by setting the `tool_choice` parameter. We support the following categories of tools: - **Built-in tools**: Tools that are provided by OpenAI that extend the model's capabilities, like [web search](https://platform.openai.com/docs/guides/tools-web-search) or [file search](https://platform.openai.com/docs/guides/tools-file-search). Learn more about [built-in tools](https://platform.openai.com/docs/guides/tools). - **MCP Tools**: Integrations with third-party systems via custom MCP servers or predefined connectors such as Google Drive and SharePoint. Learn more about [MCP Tools](https://platform.openai.com/docs/guides/tools-connectors-mcp). - **Function calls (custom tools)**: Functions that are defined by you, enabling the model to call your own code with strongly typed arguments and outputs. Learn more about [function calling](https://platform.openai.com/docs/guides/function-calling). You can also use custom tools to call your own code. top_logprobs: An integer between 0 and 20 specifying the maximum number of most likely tokens to return at each token position, each with an associated log probability. In some cases, the number of returned tokens may be fewer than requested. 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: The truncation strategy to use for the model response. - `auto`: If the input to this Response exceeds the model's context window size, the model will truncate the response to fit the context window by dropping items from the beginning of the conversation. - `disabled` (default): If the input size will exceed the context window size for a model, the request will fail with a 400 error. user: This field is being replaced by `safety_identifier` and `prompt_cache_key`. Use `prompt_cache_key` instead to maintain caching optimizations. A stable identifier for your end-users. Used to boost cache hit rates by better bucketing similar requests and to help OpenAI detect and prevent abuse. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#safety-identifiers). 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 N$rqrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrs$ rrcreateResponses.createx ru"rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrc#ga4Creates a model response. Provide [text](https://platform.openai.com/docs/guides/text) or [image](https://platform.openai.com/docs/guides/images) inputs to generate [text](https://platform.openai.com/docs/guides/text) or [JSON](https://platform.openai.com/docs/guides/structured-outputs) outputs. Have the model call your own [custom code](https://platform.openai.com/docs/guides/function-calling) or use built-in [tools](https://platform.openai.com/docs/guides/tools) like [web search](https://platform.openai.com/docs/guides/tools-web-search) or [file search](https://platform.openai.com/docs/guides/tools-file-search) to use your own data as input for the model's response. Args: stream: If set to true, the model response data will be streamed to the client as it is generated using [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format). See the [Streaming section below](https://platform.openai.com/docs/api-reference/responses-streaming) for more information. background: Whether to run the model response in the background. [Learn more](https://platform.openai.com/docs/guides/background). context_management: Context management configuration for this request. conversation: The conversation that this response belongs to. Items from this conversation are prepended to `input_items` for this response request. Input items and output items from this response are automatically added to this conversation after this response completes. include: Specify additional output data to include in the model response. Currently supported values are: - `web_search_call.action.sources`: Include the sources of the web search tool call. - `code_interpreter_call.outputs`: Includes the outputs of python code execution in code interpreter tool call items. - `computer_call_output.output.image_url`: Include image urls from the computer call output. - `file_search_call.results`: Include the search results of the file search tool call. - `message.input_image.image_url`: Include image urls from the input message. - `message.output_text.logprobs`: Include logprobs with assistant messages. - `reasoning.encrypted_content`: Includes an encrypted version of reasoning tokens in reasoning item outputs. This enables reasoning items to be used in multi-turn conversations when using the Responses API statelessly (like when the `store` parameter is set to `false`, or when an organization is enrolled in the zero data retention program). input: Text, image, or file inputs to the model, used to generate a response. Learn more: - [Text inputs and outputs](https://platform.openai.com/docs/guides/text) - [Image inputs](https://platform.openai.com/docs/guides/images) - [File inputs](https://platform.openai.com/docs/guides/pdf-files) - [Conversation state](https://platform.openai.com/docs/guides/conversation-state) - [Function calling](https://platform.openai.com/docs/guides/function-calling) instructions: A system (or developer) message inserted into the model's context. When using along with `previous_response_id`, the instructions from a previous response will not be carried over to the next response. This makes it simple to swap out system (or developer) messages in new responses. max_output_tokens: An upper bound for the number of tokens that can be generated for a response, including visible output tokens and [reasoning tokens](https://platform.openai.com/docs/guides/reasoning). max_tool_calls: The maximum number of total calls to built-in tools that can be processed in a response. This maximum number applies across all built-in tool calls, not per individual tool. Any further attempts to call a tool by the model will be ignored. 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: Model ID used to generate the response, like `gpt-6-astra`. OpenAI offers a wide range of models with different capabilities, performance characteristics, and price points. Refer to the [model guide](https://platform.openai.com/docs/models) to browse and compare available models. moderation: Configuration for running moderation on the input and output of this response. parallel_tool_calls: Whether to allow the model to run tool calls in parallel. previous_response_id: The unique ID of the previous response to the model. Use this to create multi-turn conversations. Learn more about [conversation state](https://platform.openai.com/docs/guides/conversation-state). Cannot be used in conjunction with `conversation`. prompt: Reference to a prompt template and its variables. [Learn more](https://platform.openai.com/docs/guides/text?api-mode=responses#reusable-prompts). prompt_cache_key: Used by OpenAI to cache responses for similar requests to optimize your cache hit rates. Replaces the `user` field. [Learn more](https://platform.openai.com/docs/guides/prompt-caching). prompt_cache_options: Options for prompt caching. Supported for `gpt-5.6` and later models. By default, OpenAI automatically chooses one implicit cache breakpoint. You can add explicit breakpoints to content blocks with `prompt_cache_breakpoint`. Each request can write up to four breakpoints. For cache matching, OpenAI considers up to the latest 80 breakpoints in the conversation, without a content-block lookback limit. Set `mode` to `explicit` to disable the implicit breakpoint. The `ttl` defaults to `30m`, which is currently the only supported value. See the [prompt caching guide](https://platform.openai.com/docs/guides/prompt-caching) for current details. prompt_cache_retention: Deprecated. Use `prompt_cache_options.ttl` instead. The retention policy for the prompt cache. Set to `24h` to enable extended prompt caching, which keeps cached prefixes active for longer, up to a maximum of 24 hours. [Learn more](https://platform.openai.com/docs/guides/prompt-caching#prompt-cache-retention). This field expresses a maximum retention policy, while `prompt_cache_options.ttl` expresses a minimum cache lifetime. The two fields are independent and do not interact. For `gpt-5.5`, `gpt-5.5-pro`, and future models, only `24h` is supported. For older models that support both `in_memory` and `24h`, the default depends on your organization's data retention policy: - Organizations without ZDR enabled default to `24h`. - Organizations with ZDR enabled default to `in_memory` when `prompt_cache_retention` is not specified. reasoning: Configuration options for [reasoning models](https://platform.openai.com/docs/guides/reasoning). safety_identifier: A stable identifier used to help detect users of your application that may be violating OpenAI's usage policies. The IDs should be a string that uniquely identifies each user, with a maximum length of 64 characters. We recommend hashing their username or email address, in order to avoid sending us any identifying information. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#safety-identifiers). service_tier: Specifies the processing type used for serving the request. - If set to 'auto', then the request will be processed with the service tier configured in the Project settings. Unless otherwise configured, the Project will use 'default'. - If set to 'default', then the request will be processed with the standard pricing and performance for the selected model. - If set to '[flex](https://platform.openai.com/docs/guides/flex-processing)', then the request will be processed with the Flex Processing service tier. - To opt-in to [Fast mode](/api/docs/guides/fast-mode) at the request level, include the `service_tier=fast` or `service_tier=priority` parameter for Responses or Chat Completions. The response will show `service_tier=priority` regardless of if you specify `service_tier=fast` or `priority` in your request. - If set to 'ultrafast', then the request will be processed with the access-controlled Ultrafast Processing service tier. This tier is currently available for `gpt-5.6-sol`; a response served through it will show `service_tier=ultrafast`. - When not set, the default behavior is 'auto'. When the `service_tier` parameter is set, the response body will include the `service_tier` value based on the processing mode actually used to serve the request. This response value may be different from the value set in the parameter. store: Whether to store the generated model response for later retrieval via API. Defaults to true when omitted. If set to true, response data will be stored for at least 30 days, subject to the [data retention exceptions](/api/docs/guides/your-data#v1responses). stream_options: Options for streaming responses. Only set this when you set `stream: true`. 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. We generally recommend altering this or `top_p` but not both. text: Configuration options for a text response from the model. Can be plain text or structured JSON data. Learn more: - [Text inputs and outputs](https://platform.openai.com/docs/guides/text) - [Structured Outputs](https://platform.openai.com/docs/guides/structured-outputs) tool_choice: How the model should select which tool (or tools) to use when generating a response. See the `tools` parameter to see how to specify which tools the model can call. tools: An array of tools the model may call while generating a response. You can specify which tool to use by setting the `tool_choice` parameter. We support the following categories of tools: - **Built-in tools**: Tools that are provided by OpenAI that extend the model's capabilities, like [web search](https://platform.openai.com/docs/guides/tools-web-search) or [file search](https://platform.openai.com/docs/guides/tools-file-search). Learn more about [built-in tools](https://platform.openai.com/docs/guides/tools). - **MCP Tools**: Integrations with third-party systems via custom MCP servers or predefined connectors such as Google Drive and SharePoint. Learn more about [MCP Tools](https://platform.openai.com/docs/guides/tools-connectors-mcp). - **Function calls (custom tools)**: Functions that are defined by you, enabling the model to call your own code with strongly typed arguments and outputs. Learn more about [function calling](https://platform.openai.com/docs/guides/function-calling). You can also use custom tools to call your own code. top_logprobs: An integer between 0 and 20 specifying the maximum number of most likely tokens to return at each token position, each with an associated log probability. In some cases, the number of returned tokens may be fewer than requested. 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: The truncation strategy to use for the model response. - `auto`: If the input to this Response exceeds the model's context window size, the model will truncate the response to fit the context window by dropping items from the beginning of the conversation. - `disabled` (default): If the input size will exceed the context window size for a model, the request will fail with a 400 error. user: This field is being replaced by `safety_identifier` and `prompt_cache_key`. Use `prompt_cache_key` instead to maintain caching optimizations. A stable identifier for your end-users. Used to boost cache hit rates by better bucketing similar requests and to help OpenAI detect and prevent abuse. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#safety-identifiers). 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 Nr$rqrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrs$ rrrrrruc#grrrs$ rrrrrruc#ZURS[0SU_SU_SU_SU_SU_SU_SU_S U_S U _S U _S U _S U _SU _SU_SU_SU_SU_UUUUUUUUUUUUUUS.EU(a[RO[R5[ U U!U"U#SS0S9[ U=(d S[[S9$N /responsesrrrrrrrrrrrrrrrrr)rrrrrrrrrrrrrr bearer_authTrrrrsecurityF)bodyoptionscast_tor stream_cls) _postr#rDResponseCreateParamsStreaming ResponseCreateParamsNonStreamingrBrKr4r]rs$ rrrrs{Rzz    * (*< #L w  U  #L (): %n  U !* *+> +,@ f '(8  +,@! "-.D# $"+):$0"$&4#. #."$0"", ? D'DD+LLI%L)+'%'. ?U12c2 2 ru text_formatstarting_afterrrrrrcgrnr rq response_idrrrrrrrs rrrResponses.stream<s.1ru!rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrc#grnr$rqrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrs$ rrrrKsR.1ru%rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrc%l^^^ ^"^#^$^%0SU_SU_SU_SU_ST _SU _SU _SU _S U _S U_S U_S U_S U_SU_SU_SU_SU_UUUUUUUUUUU US. En&U&R5V'V(s/sHun'n([U(5(dMU'PM n)n'n([T5(d[U!5(a,[U)5S:a[SSR U)5-5e[ U5n[U)5S:Ga[U5(d [S5e[U5(d [S5e[U5(a3U(d0nSU;a [ S5e[U5n[U5US'[TR40SU_SU_SU_SU_SU_ST _SU _SU _SU _S U _S U_S U_S U_S U_SU_SU_SU_SU_SU_SS_SU_S U_S!U_SU_S"U_S#U_S$U_S%U_S&U_S'U _S(U_S)T"_S*T#_S+T$_S,T%_6n*[U*UUSS-9$[T5(d [S.5e[U$U"U#U UUU%4S/jUU[U!5(aU!S-9$SS-9$s sn(n'f)0Nrrrrrrrrrrrrrrrrr rrrrrrrrrrrrrOCannot provide both response_id/starting_after can't be provided together with , 3input must be provided when creating a new response3model must be provided when creating a new responseformat1Cannot mix and match text.format with text_formatrrrrTrrrrrrrrrrrrrrr input_toolsrz7id must be provided when streaming an existing responsec J>TRTST=(d /TTT[TS9$)NT)rrrrrrrr)retriever)rrrrrrqrsrr"Responses.stream.. s/ +#Mr"/ +)#'#& ru) itemsr!len ValueErrorjoin _make_tools TypeErrorr_type_to_text_format_paramrrrU+rqrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrnew_response_argskvnew_response_args_names api_requests+`` ` ```` rrrrvsV U U  !"4  L  w  L   !2  n    *  "#6  #$8  f   0  #$8 %&2C1H1H1J"Z1JAhWXk11J"Z [ ! !Xn%=%=3G^C_bcCca))345 E" & '! +E?? !VWWE?? !VWW $$Dt##$WXXDz!;K!HX@G %A%A%A %A $6 %A * %A %A*%A#4%A .%A"%A&%A%8%A&:%A%A "2!%A"&:#%A$(>%%A&'%A( .)%A*+%A,(-%A./%A0(1%A2$3%A4#45%A6*7%A8*9%A:;%A<&=%A>?%A@&A%AB,C%AD(E%AF&G%AH I%AKN)'!#  K(( !Z[[(  (!19.1I1I~ PT U#[s H09H0%rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr verbosityrrrrc%^^[T5(a3U(d0nSU;a [S5e[U5n[T5US'[ T5mSUU4Sjjn&UR S[ 0SU_SU_SU_SU_S U_S U_S U_S U _S U _SU _SU _SU _SU_SU_SU_SU_SU_UUUUUUUUUTUUUU U!S.E[R5[U"U#U$U%U&SS0S9[[[[[5S9$)Nrrc>[TTUS9$N)rrresponserI raw_responserrs rrparserResponses.parse..parserP!!'% rurrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrTrrrr post_parserrrrrrrKreturnParsedResponse[TextFormatT]r!rrrrrr#rDResponseCreateParamsrBrr rTrHrK'rqrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrs' ` ` rrparseResponses.parsesV K 4 STT:D7 DDNE"  zz  ! *!(*<!#L!w ! U ! #L !():!%n!!U!!*!*+>!+,@!f!'(8! +,@!!"-.D#!$"+):$0"$&4#. #."$0"", !*A!D';;G$J)+'%"'. n[9:HEc2 2 rurinclude_obfuscationrrrrrrcgrnr rqrrrrrrrrrs rrrResponses.retrievesrurrrrrrcgrnr rqrrrrrrrrs rrrrs'*rucgrnrrs rrrrs25ruFrrrrrrrcga Retrieves a model response with the given ID. Args: include: Additional fields to include in the response. See the `include` parameter for Response creation above for more information. include_obfuscation: When true, stream obfuscation will be enabled. Stream obfuscation adds random characters to an `obfuscation` field on streaming delta events to normalize payload sizes as a mitigation to certain side-channel attacks. These obfuscation fields are included by default, but add a small amount of overhead to the data stream. You can set `include_obfuscation` to false to optimize for bandwidth if you trust the network links between your application and the OpenAI API. starting_after: The sequence number of the event after which to start streaming. stream: If set to true, the model response data will be streamed to the client as it is generated using [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format). See the [Streaming section below](https://platform.openai.com/docs/api-reference/responses-streaming) for more information. 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 Nrrs rrrrs\ rurrrrrrrcga Retrieves a model response with the given ID. Args: stream: If set to true, the model response data will be streamed to the client as it is generated using [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format). See the [Streaming section below](https://platform.openai.com/docs/api-reference/responses-streaming) for more information. include: Additional fields to include in the response. See the `include` parameter for Response creation above for more information. include_obfuscation: When true, stream obfuscation will be enabled. Stream obfuscation adds random characters to an `obfuscation` field on streaming delta events to normalize payload sizes as a mitigation to certain side-channel attacks. These obfuscation fields are included by default, but add a small amount of overhead to the data stream. You can set `include_obfuscation` to false to optimize for bandwidth if you trust the network links between your application and the OpenAI API. starting_after: The sequence number of the event after which to start streaming. 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 Nr rqrrrrrrrrrs rrrr^ rucgr rr s rrrrrrucU(d[SU<35eUR[SUS9[UUUU [ UUUUS.[ R 5SS0S9[U=(d S[[S 9$ N:Expected a non-empty value for `response_id` but received /responses/{response_id}r)rrrrrT)rrrrqueryrF)rrrr) r_getr"rBr#rFResponseRetrieveParamsrKr4r]rs rrrrNsYZeYhij jyy 4+ N(+'%%#*/B*8"(  -CC(. ?U12)  rurrrrc U(d[SU<35eSS0U=(d 0EnUR[SUS9[UUUUSS0S9[S 9$) ' Deletes a model response with the given ID. 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 rAccept*/*rrrTrrrr_deleter"rBrrqrrrrrs rrdeleteResponses.deletevsr.YZeYhij j!5B]-@bB || 4+ N(+'%'.   ruc U(d[SU<35eUR[SUS9[UUUUSS0S9[S9$)Cancels a model response with the given ID. Only responses created with the `background` parameter set to `true` can be cancelled. [Learn more](https://platform.openai.com/docs/guides/background). 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 r/responses/{response_id}/cancelrrTrrrrr"rBrKr s rrcancelResponses.cancels^4YZeYhij jzz ; U(+'%'.   ru rrrrrrrrrrrc URS[UUUUUUUUS.[R5[ U U U U SS0S9[ S9$)Compact a conversation. Returns a compacted response object. Learn when and how to compact long-running conversations in the [conversation state guide](https://platform.openai.com/docs/guides/conversation-state#managing-the-context-window). For ZDR-compatible compaction details, see [Compaction (advanced)](https://platform.openai.com/docs/guides/conversation-state#compaction-advanced). Args: model: Model ID used to generate the response, like `gpt-6-astra`. OpenAI offers a wide range of models with different capabilities, performance characteristics, and price points. Refer to the [model guide](https://platform.openai.com/docs/models) to browse and compare available models. input: Text, image, or file inputs to the model, used to generate a response instructions: A system (or developer) message inserted into the model's context. When used along with `previous_response_id`, the instructions from a previous response will not be carried over to the next response. This makes it simple to swap out system (or developer) messages in new responses. previous_response_id: The unique ID of the previous response to the model. Use this to create multi-turn conversations. Learn more about [conversation state](https://platform.openai.com/docs/guides/conversation-state). Cannot be used in conjunction with `conversation`. prompt_cache_key: A key to use when reading from or writing to the prompt cache. prompt_cache_options: Options for prompt caching. Supported for `gpt-5.6` and later models. By default, OpenAI automatically chooses one implicit cache breakpoint. You can add explicit breakpoints to content blocks with `prompt_cache_breakpoint`. Each request can write up to four breakpoints. For cache matching, OpenAI considers up to the latest 80 breakpoints in the conversation, without a content-block lookback limit. Set `mode` to `explicit` to disable the implicit breakpoint. The `ttl` defaults to `30m`, which is currently the only supported value. See the [prompt caching guide](https://platform.openai.com/docs/guides/prompt-caching) for current details. prompt_cache_retention: How long to retain a prompt cache entry created by this request. service_tier: Specifies the processing type used for serving the request. - If set to 'auto', then the request will be processed with the service tier configured in the Project settings. Unless otherwise configured, the Project will use 'default'. - If set to 'default', then the request will be processed with the standard pricing and performance for the selected model. - If set to '[flex](https://platform.openai.com/docs/guides/flex-processing)', then the request will be processed with the Flex Processing service tier. - To opt-in to [Fast mode](/api/docs/guides/fast-mode) at the request level, include the `service_tier=fast` or `service_tier=priority` parameter for Responses or Chat Completions. For models with a dedicated Fast tier, either value resolves to `service_tier=fast`; for other models, either value resolves to `service_tier=priority`. - When not set, the default behavior is 'auto'. When the `service_tier` parameter is set, the response body will include the `service_tier` value based on the processing mode actually used to serve the request. This response value may be different from the value set in the parameter. 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 /responses/compactrrrrrrrrrTrr)rr#rEResponseCompactParamsrBrW rqrrrrrrrrrrrrs rrcompactResponses.compactsqBzz  ""$0,@(8,@.D$0 (== )+'%'. &-  ru? @c 8[URUUUUUUUUS9 $a.Connect to a persistent Responses API WebSocket. Send `response.create` events to create responses and `response.steer` events to queue user input containing text, images, or files for a continuation. Receive response stream events and steering acceptance, pending, or failure events over the socket. ) clientrrwebsocket_connection_optionson_reconnecting max_retries initial_delay max_delaymax_queue_size)ResponsesConnectionManagerro rqrrr9r:r;r<r=r>s rrconnectResponses.connects0*<<#')E+#')  rur)rr.)rr8)rr{)rrHrOptional[bool] | OmitrCOptional[Iterable[response_create_params.ContextManagement]] | Omitr4Optional[response_create_params.Conversation] | Omitr)Optional[List[ResponseIncludable]] | Omitr%Union[str, ResponseInputParam] | OmitrOptional[str] | OmitrOptional[int] | OmitrrJrOptional[Metadata] | OmitrResponsesModel | Omitr2Optional[response_create_params.Moderation] | OmitrrDrrIr$Optional[ResponsePromptParam] | OmitrrIr0response_create_params.PromptCacheOptions | Omitr,Optional[Literal['in_memory', '24h']] | OmitrOptional[Reasoning] | OmitrrIrOptional[ServiceTier] | OmitrrDrzOptional[Literal[False]] | Omitr5Optional[response_create_params.StreamOptions] | OmitrOptional[float] | OmitrResponseTextConfigParam | Omitr(response_create_params.ToolChoice | OmitrIterable[ToolParam] | OmitrrJrrTr,Optional[Literal['auto', 'disabled']] | Omitr str | OmitrHeaders | Noner Query | Noner Body | Noner(float | httpx2.Timeout | None | NotGivenrrK)Hr Literal[True]rrDrrErrFrrGrrHrrIrrJrrJrrKrrLrrMrrDrrIrrNrrIrrOrrPrrQrrIrrRrrDrrSrrTrrUrrVrrWrrJrrTrrXrrYrrZrr[rr\rr]rStream[ResponseStreamEvent])HrboolrrDrrErrFrrGrrHrrIrrJrrJrrKrrLrrMrrDrrIrrNrrIrrOrrPrrQrrIrrRrrDrrSrrTrrUrrVrrWrrJrrTrrXrrYrrZrr[rr\rr]r&Response | Stream[ResponseStreamEvent])HrrDrrErrFrrGrrHrrIrrJrrJrrKrrLrrMrrDrrIrrNrrIrrOrrPrrQrrIrrRrrDr/Optional[Literal[False]] | Literal[True] | OmitrrSrrTrrUrrVrrWrrJrrTrrXrrYrrZrr[rr\rr]rra)rstrrtype[TextFormatT] | Omitr int | Omitr#Iterable[ParseableToolParam] | OmitrrZrr[rr\rr]r"ResponseStreamManager[TextFormatT])HrUnion[str, ResponseInputParam]rrZrrDrrErrdrrfrrFrrGrrIrrJrrJrrKrrDrrMrrIrrNrrIrrOrrPrrQrrIrrRrrDrrSrrTrrUrrVrrJrrTrrXrrYrrZrr[rr\rr]rrg)LrrYrrHrrLrrDrrErrdrrfrrFrrGrrIrrJrrJrrKrrDrrMrrIrrNrrIrrOrrPrrQrrIrrRrrDrrSrrTrrUrrVrrJrrTrrXrrYrrerrZrr[rr\rr]rrgLrrdrrDrrErrFrrGrrHrrIrrJrrJrrKrrLrrMrrDrrIrrNrrIrrOrrPrrQrrIrrRrrDrrbrrSrrTrrUrrVrrfrrJrrTrrXrrYrz1Optional[Literal['low', 'medium', 'high']] | OmitrrZrr[rr\rr]rrrrcrList[ResponseIncludable] | Omitr bool | OmitrrerzLiteral[False] | OmitrrZrr[rr\rr]rrK)rrcrr^rrkrrerrZrr[rr\rr]rr_)rrcrr`rrkrrerrZrr[rr\rr]rra)rrcrr^rrkrrlrrerrZrr[rr\rr]rr_)rrcrr`rrkrrlrrerrZrr[rr\rr]rra)rrcrrkrrlrrer%Literal[False] | Literal[True] | OmitrrZrr[rr\rr]rra rrcrrZrr[rr\rr]rNone rrcrrZrr[rr\rr]rrKraUUnion[Literal['gpt-6-astra', 'gpt-5.6-sol', 'gpt-5.6-terra', 'gpt-5.6-luna', 'gpt-5.5', 'gpt-5.5-2026-04-23', 'gpt-5.4', 'gpt-5.4-mini', 'gpt-5.4-nano', 'gpt-5.4-mini-2026-03-17', 'gpt-5.4-nano-2026-03-17', 'gpt-5.3-chat-latest', 'gpt-5.2', 'gpt-5.2-2025-12-11', 'gpt-5.2-chat-latest', 'gpt-5.2-pro', 'gpt-5.2-pro-2025-12-11', 'gpt-5.1', 'gpt-5.1-2025-11-13', 'gpt-5.1-codex', 'gpt-5.1-mini', 'gpt-5.1-chat-latest', 'gpt-5', 'gpt-5-mini', 'gpt-5-nano', 'gpt-5-2025-08-07', 'gpt-5-mini-2025-08-07', 'gpt-5-nano-2025-08-07', 'gpt-5-chat-latest', 'gpt-4.1', 'gpt-4.1-mini', 'gpt-4.1-nano', 'gpt-4.1-2025-04-14', 'gpt-4.1-mini-2025-04-14', 'gpt-4.1-nano-2025-04-14', 'o4-mini', 'o4-mini-2025-04-16', 'o3', 'o3-2025-04-16', 'o3-mini', 'o3-mini-2025-01-31', 'o1', 'o1-2024-12-17', 'o1-preview', 'o1-preview-2024-09-12', 'o1-mini', 'o1-mini-2024-09-12', 'gpt-4o', 'gpt-4o-2024-11-20', 'gpt-4o-2024-08-06', 'gpt-4o-2024-05-13', 'gpt-4o-audio-preview', 'gpt-4o-audio-preview-2024-10-01', 'gpt-4o-audio-preview-2024-12-17', 'gpt-4o-audio-preview-2025-06-03', 'gpt-4o-mini-audio-preview', 'gpt-4o-mini-audio-preview-2024-12-17', 'gpt-4o-search-preview', 'gpt-4o-mini-search-preview', 'gpt-4o-search-preview-2025-03-11', 'gpt-4o-mini-search-preview-2025-03-11', 'chatgpt-4o-latest', 'codex-mini-latest', 'gpt-4o-mini', 'gpt-4o-mini-2024-07-18', 'gpt-4-turbo', 'gpt-4-turbo-2024-04-09', 'gpt-4-0125-preview', 'gpt-4-turbo-preview', 'gpt-4-1106-preview', 'gpt-4-vision-preview', 'gpt-4', 'gpt-4-0314', 'gpt-4-0613', 'gpt-4-32k', 'gpt-4-32k-0314', 'gpt-4-32k-0613', 'gpt-3.5-turbo', 'gpt-3.5-turbo-16k', 'gpt-3.5-turbo-0301', 'gpt-3.5-turbo-0613', 'gpt-3.5-turbo-1106', 'gpt-3.5-turbo-0125', 'gpt-3.5-turbo-16k-0613', 'o1-pro', 'o1-pro-2025-03-19', 'o3-pro', 'o3-pro-2025-06-10', 'o3-deep-research', 'o3-deep-research-2025-06-26', 'o4-mini-deep-research', 'o4-mini-deep-research-2025-06-26', 'computer-use-preview', 'computer-use-preview-2025-03-11', 'gpt-5.5-pro', 'gpt-5.5-pro-2026-04-23', 'gpt-5-codex', 'gpt-5-pro', 'gpt-5-pro-2025-10-06', 'gpt-5.1-codex-max', 'gpt-daybreak-blue-latest', 'gpt-daybreak-red-latest', 'gpt-5.6-cyber'], str, None]rz9Union[str, Iterable[ResponseInputItemParam], None] | OmitrrIrrIrrIrz;Optional[response_compact_params.PromptCacheOptions] | OmitrrPrzGOptional[Literal['auto', 'default', 'fast', 'flex', 'priority']] | OmitrrZrr[rr\rr]rrW)rrrrr9rXr:BCallable[[ReconnectingEvent], ReconnectingOverrides | None] | Noner;intr<floatr=rtr>rsrr?__name__ __module__ __qualname____firstlineno__r&rsrwr|rrrr rrrrrr!r'r0rA__static_attributes__rrurrrhrhisu(())..44-1bfMQ=A7;-126/3.2'+IM59597;15QUOS042659'+26PT.2/3@D,0-1(,CG)-$("&9[ :*;[ <+=[ >&?[ @AA[ BC[ H&I[ J"K[ L M[ N:O[ P Q[ [ z -1bfMQ=A7;-126/3.2'+IM59597;15QUOS042659'+PT.2/3@D,0-1(,CG)-$("&9[ :*;[ <+=[ >&?[ @AA[ BC[ H&I[ J"K[ L M[ N:O[ P %Q[ [ z -1bfMQ=A7;-126/3.2'+IM59597;15QUOS042659'+PT.2/3@D,0-1(,CG)-$("&9[ :*;[ <+=[ >&?[ @AA[ BC[ H&I[ J"K[ L M[ N:O[ P 0Q[ [ @ -1bfMQ=A7;-126/3.2'+IM59597;15QUOS042659'+BFPT.2/3@D,0-1(,CG)-$("&9[ :*;[ <+=[ >&?[ @AA[ BC[ H&I[ J"K[ L M[ N:O[ P 0Q[ z 15%)59(,$("&;(1<+=(1>&?(1@AA(1BC(1H&I(1J"K(1L M(1N:O(1P 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S@S%jjr000SS&S'S(S)4SAS*jjrS+rg)Briic,[UR5$rn)r/rorps rrrsAsyncResponses.input_itemsst||,,ruc,[UR5$rn)r9rorps rrrwAsyncResponses.input_tokenss --ruc[U5$rz)AsyncResponsesWithRawResponserps rrr| AsyncResponses.with_raw_responses-T22ruc[U5$r)#AsyncResponsesWithStreamingResponserps rrr&AsyncResponses.with_streaming_responses3488ruNrc# # g7frrrs$ rrrAsyncResponses.create x rc# # g7frrrs$ rrrrrrc# # g7frrrs$ rrrr rrc## URS[0SU_SU_SU_SU_SU_SU_SU_S U_S U _S U _S U _S U _SU _SU_SU_SU_SU_UUUUUUUUUUUUUUS.EU(a[RO[R5IShvN [ U U!U"U#SS0S9[ U=(d S[[S9IShvN $N7N7fr) rr%rDrrrBrKr5r]rs$ rrrr0 sRZZ ,  * (*< #L w  U  #L (): %n  U !* *+> +,@ f '(8  +,@! "-.D# $"+):$0"$&4#. #."$0"", ? D'DD+LLI%%L)+'%'. ?U"#67c 2 2 2 %2 s$BCB? 2C:C;CCrcgrnrrs rrrAsyncResponses.stream s36rurc#grnrrs$ rrrr sR36rurc%0SU_SU_SU_SU_SU _SU _SU _SU _S U _S U_S U_S U_S U_SU_SU_SU_SU_UUUUUUUUUUU US. 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"    sAAAAc # U(d[SU<35eUR[SUS9[UUUUSS0S9[S9IShvN $N7f) r$rr%rrTrrNr&r s rrr'AsyncResponses.cancel sk4YZeYhij jZZ ; U(+'%'.     sAA A A r)c # URS[UUUUUUUUS.[R5IShvN [ U U U U SS0S9[ S9IShvN $N!N7f)r+r,r-NrTrr)rr%rEr.rBrWr/s rrr0AsyncResponses.compactsBZZ ,""$0,@(8,@.D$0 (==  )+'%'. &-      s!3AA AAAAr2r3r4r5c 8[URUUUUUUUUS9 $r7)AsyncResponsesConnectionManagerror@s rrrAAsyncResponses.connects0/<<#')E+#')  rur)rr/)rr9)rr)rrrC)Hrr^rrDrrErrFrrGrrHrrIrrJrrJrrKrrLrrMrrDrrIrrNrrIrrOrrPrrQrrIrrRrrDrrSrrTrrUrrVrrWrrJrrTrrXrrYrrZrr[rr\rr]r AsyncStream[ResponseStreamEvent])Hrr`rrDrrErrFrrGrrHrrIrrJrrJrrKrrLrrMrrDrrIrrNrrIrrOrrPrrQrrIrrRrrDrrSrrTrrUrrVrrWrrJrrTrrXrrYrrZrr[rr\rr]r+Response | AsyncStream[ResponseStreamEvent])HrrDrrErrFrrGrrHrrIrrJrrJrrKrrLrrMrrDrrIrrNrrIrrOrrPrrQrrIrrRrrDrrbrrSrrTrrUrrVrrWrrJrrTrrXrrYrrZrr[rr\rr]rr)rrcrrdrrerrfrrZrr[rr\rr]r'AsyncResponseStreamManager[TextFormatT])HrrhrrZrrDrrErrdrrfrrFrrGrrIrrJrrJrrKrrDrrMrrIrrNrrIrrOrrPrrQrrIrrRrrDrrSrrTrrUrrVrrJrrTrrXrrYrrZrr[rr\rr]rr)LrrYrrHrrLrrDrrErrdrrfrrFrrGrrIrrJrrJrrKrrDrrMrrIrrNrrIrrOrrPrrQrrIrrRrrDrrSrrTrrUrrVrrJrrTrrXrrYrrerrZrr[rr\rr]rrrirj)rrcrr^rrkrrerrZrr[rr\rr]rr)rrcrr`rrkrrerrZrr[rr\rr]rr)rrcrr^rrkrrlrrerrZrr[rr\rr]rr)rrcrr`rrkrrlrrerrZrr[rr\rr]rr)rrcrrkrrlrrerrmrrZrr[rr\rr]rrrnrprq)rrrrr9rXr:rrr;rsr<rtr=rtr>rsrrrurrurrririsu--..3399-1bfMQ=A7;-126/3.2'+IM59597;15QUOS042659'+26PT.2/3@D,0-1(,CG)-$("&9[ :*;[ <+=[ >&?[ @AA[ BC[ H&I[ J"K[ L M[ N:O[ P Q[ [ z -1bfMQ=A7;-126/3.2'+IM59597;15QUOS042659'+PT.2/3@D,0-1(,CG)-$("&9[ :*;[ <+=[ >&?[ @AA[ BC[ H&I[ J"K[ L M[ N:O[ P *Q[ [ z -1bfMQ=A7;-126/3.2'+IM59597;15QUOS042659'+PT.2/3@D,0-1(,CG)-$("&9[ :*;[ <+=[ >&?[ @AA[ BC[ H&I[ J"K[ L M[ N:O[ P 5Q[ [ @ -1bfMQ=A7;-126/3.2'+IM59597;15QUOS042659'+BFPT.2/3@D,0-1(,CG)-$("&9[ :*;[ <+=[ >&?[ @AA[ BC[ H&I[ J"K[ L M[ N:O[ P 5Q[ z 15%)59(,$("&;(6<+=(6>&?(6@AA(6BC(6H&I(6J"K(6L M(6N:O(6P 1Q(6(6Z#'7;'+,0bf0459MQ=A-126/3.259IM597;15QUOS042659'+PT.2/3@D-1(,CG%))-$("&=a>+?a@&AaBACaDEaF#GaL&MaN"OaP QaR:SaT 1UaL15,0bfMQ=A7;-126/3.2'+IM59597;15QUOS042659'+BFPT.2/3@D59-1(,CGGK)-$("&;o <3=o >+?o @&Ao BACo DEo FEGo L&Mo N"Oo P Qo R:So T %Uo b 48+/%)(,)-$("&>     )@@     '>>     '>>     (??     &== OO  ruc@[URR5$rn)r0rrsrps rrrs$ResponsesWithRawResponse.input_items!s()D)DEEruc@[URR5$rn)r:rrwrps rrrw%ResponsesWithRawResponse.input_tokens%s)$//*F*FGGrurr'r0rr!rrNrrhrro)rr0)rr: rvrwrxryrr&rsrwrzrrurrr{r{ s3 ,FFHHrur{cF\rSrSrSSjr\SSj5r\S Sj5rSrg) ri*cXl[R"UR5Ul[R"UR5Ul[R"UR 5Ul[R"UR 5Ul[R"UR5Ul[R"UR5Ulgrn) rrasync_to_raw_response_wrapperrrr!r'r0rrs rrr&AsyncResponsesWithRawResponse.__init__+s#&DD     )FF     'DD     'DD     (EE     &CC OO  ruc@[URR5$rn)r1rrsrps rrrs)AsyncResponsesWithRawResponse.input_itemsAs-doo.I.IJJruc@[URR5$rn)r;rrwrps rrrw*AsyncResponsesWithRawResponse.input_tokensEs.t/K/KLLrurNrrirro)rr1)rr;rrrurrrr*s3 ,KKMMrurcF\rSrSrSSjr\SSj5r\S Sj5rSrg) riJcXl[UR5Ul[UR5Ul[UR5Ul[UR 5Ul[UR 5Ulgrn)rr+rrr!r'r0rs rrr'ResponsesWithStreamingResponse.__init__Ksx#2     5     3     3     4     ruc@[URR5$rn)r2rrsrps rrrs*ResponsesWithStreamingResponse.input_items^s.t/J/JKKruc@[URR5$rn)r<rrwrps rrrw+ResponsesWithStreamingResponse.input_tokensbs/0L0LMMrurr'r0rr!rNr)rr2)rr<rrrurrrrJs3 &LLNNrurcF\rSrSrSSjr\SSj5r\S Sj5rSrg) rigcXl[UR5Ul[UR5Ul[UR5Ul[UR 5Ul[UR 5Ulgrn)rr,rrr!r'r0rs rrr,AsyncResponsesWithStreamingResponse.__init__hsx#8     ;     9     9     :     ruc@[URR5$rn)r3rrsrps rrrs/AsyncResponsesWithStreamingResponse.input_items{s3DOO4O4OPPruc@[URR5$rn)r=rrwrps rrrw0AsyncResponsesWithStreamingResponse.input_tokenss4T__5Q5QRRrurNr)rr3)rr=rrrurrrrgs3 &QQSSrurc [U5(d[$/nUHnUSS:waURU5 MSU;aURU5 M8[[U5Sn[ U[ 5(d [S5eSU;de[SUSURS5USURS5=(d SS .UR5nURUR55 M U$) NtypefunctionzcExpected Chat Completions function tool shape to be created using `openai.pydantic_function_tool()` parametersname descriptionstrictF)rrrrr) r!rappendrrrr6 Exceptionr7getr)rconverted_toolstoolrnew_tools rrrrs E?? ')O <: %  " "4 (  T !  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Canceling this method is safe. There's no risk of losing data. Ndict[str, object]rerrorr parse_event recv_bytesrrobjectdictrgetattrrcrrqevent event_types rrrAsyncResponsesConnection.recvs   t'8!89$vu-t44 $e , 0 0 8-  j# & &:*:O&'D # "9sB"B A?B"c# URRSS9IShvN n[RS[ U55 UR (ar[ R"U5n[U[5(a[SU5RS5OSn[U[5(aU(a US:waSUlU$N![[4a Us$f=f7f) Receive the next message from the connection as raw bytes. Canceling this method is safe. There's no risk of losing data. If you want to parse the message into a `ResponsesServerEvent` object like `.recv()` does, then you can call `.parse_event(data)`. FdecodeN$Received WebSocket message: %i bytesr rr rrrrjdebugrrjsonloadsrRecursionErrorrrrrrcrqmessage event_datars rrr#AsyncResponsesConnection.recv_bytess((--U-;; 8#g,G  " " %)ZZ%8 OYYceiNjNj1:>BB6JptJ*c**zjG>S*+'< /  s4C"C4C"C +AC" CC"CC"c# [U[5(aURSSSS9O+[R"[ U[ 5IShvN 5nUR(aURRU5 gURRU5IShvN gNZN![a URRU5 ef=f7fNT use_api_namesexclude_defaults exclude_unset) rrto_jsonrdumpsr%rdrrenqueuersendrrqrdatas rrr.AsyncResponsesConnection.send s%++ MMtSWM X"7?X"YYZ     $ $T *  ""''- - - Z .     $ $T *  s<A C B' 5CB+!B)"B+&C)B++'CCc# UR(aD[U[5(aUOURS5nURR U5 gUR RU5IShvN gN7fNzutf-8rrrcrrr-rr.rqr0raws rrsend_raw!AsyncResponsesConnection.send_raws[  $T3//$T[[5IC    $ $S ) ##D)))sA4A>6A<7A>codereasonc`# SUlURRXS9IShvN gN7fNTr;rrcloserqr<r=s rrrAAsyncResponsesConnection.close!s*%)"$$$$>>>s $.,.c ~[[[[R"U5[[ [5S95$z Converts a raw `str` or `bytes` message into a `ResponsesServerEvent` object. This is helpful if you're using `.recv_bytes()`. )valuetype_rr`r(rrrrqr0s rrr$AsyncResponsesConnection.parse_event%/  $4::d+;4MaCb c  ruc # SSKnURb URcgSSKJn Sn[ X5(a#UR bUR Rn[U5(dgSUl [URS-URS-5GHnXPl [URSUS- --UR5nS [ R "5S --nXg-n[#UURUUUR$UR&S 9n URU 5n U bU R+S 5(a SUl gU b S U ;a U S UlSU ;a U SUl[,R/SUURU5 UR1U5IShvN UR2(a SUl gURUR$UR&5IShvN Ul[,R/S5 SUl UR75IShvN g SUl g![(a SUl  gf=fNNcN,![(a GMf=f7f)Attempt to reconnect after a connection failure. Returns ``True`` if a new connection was established, ``False`` if the caller should re-raise the original exception. rNFrTr-??attempt max_attemptsdelay close_coderrabortrr?Reconnecting to WebSocket API (attempt %d/%d) after %.1fs delayReconnected to WebSocket API)asynciorrrrrrcvdr<rRrrangerrminrrrandomrPrrrrrjinfosleeprr_flush_send_queue) rqrr[rrWrT base_delayjitterrVrresults rrr#AsyncResponsesConnection._reconnect0sH   (DMM,A? c 1 1chh6JJ#J// $T44q8$:K:Ka:OPG&- #T00A'A+4FGYJFMMOd22F'E%!..% --"11 E ..u5 !fjj&9&9(-%! F*(.}(=D%"f,*0*AD' HHQ!!   --& & &))(-% )-t7H7H$J]J])^#^ 78(-%,,...aQh!&I (-% ( '$_/  sDI)H9+A;I)&I'I))I/I08I(I)I- I)9I I) II)II I&!I)%I&&I)c^# SU4SjjnTRRU5IShvN gN![a [R S5 gf=f7f)5Send all queued messages over the current connection.cX># TRRU5IShvN gN7frnrr.r0rqs rr_send9AsyncResponsesConnection._flush_send_queue.._sends ""''- - -s *(*N*Failed to flush send queue after reconnect)r0rcrro)r flush_asyncrrjwarning)rqrls` rrrb*AsyncResponsesConnection._flush_send_queue}sH . F""..u5 5 5 F KKD E Fs1 A313A3AAAAc^^^UbTRRTU5 T$SUU4SjjnU$)aAdds the handler to the end of the handlers list for the given event type. No checks are made to see if the handler has already been added. Multiple calls passing the same combination of event type and handler will result in the handler being added, and called, multiple times. Can be used as a method (returns ``self`` for chaining):: connection.on("response.steer.accepted", my_handler) Or as a decorator:: @connection.on("response.steer.accepted") async def my_handler(event): ... c@>TRRTU5 U$rnraddfnrrqs rr decorator.AsyncResponsesConnection.on..decorator  ( ( , ,Z <IrurwCallable[..., Any]rr|rtrqrhandlerrxs`` rronAsyncResponsesConnection.on8$    ( ( , ,Z AK  ruc<URRX5 U$z-Remove a previously registered event handler.rremoverqrr~s rroffAsyncResponsesConnection.off $$++J@ ruc\^^UbTRRTUSS9 T$SUU4SjjnU$)RRegister a one-time event handler. Automatically removed after first invocation. Toncec>>TRRTUSS9 U$NTrrtrvs rrrx0AsyncResponsesConnection.once..decorator#  ( ( , ,Z$ , GIrur{rtr}s`` rrrAsyncResponsesConnection.once=    ( ( , ,Zt , LK  ruc# SSKnUShvN nURnURRU5nURRS5nUS:Xa1U(d*U(d#[ U[ 5(a[ SU35eUH-nU"U5nURU5(dM#UIShvN M/ UH-nU"U5nURU5(dM#UIShvN M/ MNN?N g7f)aDRun the event loop, dispatching received events to registered handlers. Blocks until the connection is closed. This is the push-based alternative to iterating with ``async for event in connection``. If an ``"error"`` event arrives and no handler is registered for ``"error"`` or ``"event"``, an ``OpenAIError`` is raised. rNrr WebSocket error: )r[rr get_handlersrr_r> iscoroutine)rqr[rrspecificgenericr~res rrdispatch_events(AsyncResponsesConnection.dispatch_eventss  !%J33@@LH22??HGW$Xge_55%(9%&ABB# &&v.. LL$ # &&v.. LL# !! !# sVC;C9C3C9BC;0C;5C56)C;#C;(C7) C;3C95C;7C;9C;rrrrrrrrrrrrrr)rrrzFCallable[[Query, Headers], Awaitable[AsyncWebSocketConnection]] | Noner:rrr;rsr<rtr=rtrrrrrSendQueue | Nonerro)rz#AsyncIterator[ResponsesServerEvent]rr`rbytesrz0ResponsesClientEvent | ResponsesClientEventParamrror0z bytes | strrror<rsr=rcrror0z str | bytesrr`rrrr`rrorn)rrcr~Callable[..., Any] | NonerzSUnion[AsyncResponsesConnection, Callable[[Callable[..., Any]], Callable[..., Any]]])rrcr~r|rr)rvrwrxry__doc____annotations__rrrrr.r7rArrrbrrrrrzrrurrrrsE,,)) [_^b"!#'+=,=X = \ =  =====%= =:,$* **.R?  KZ FEI(A \8 EI(A \"!rurc\rSrSrSrSSSSSS.SS jjrSS jrSSS jjrSS jrSSS jjr SSjr \ r SSjr SSjr SSjrSrg)ria Context manager over a `AsyncResponsesConnection` that is returned by `responses.connect()` This context manager ensures that the connection will be closed when it exits. --- Note that if your application doesn't work well with the context manager approach then you can call the `.enter()` method directly to initiate a connection. **Warning**: You must remember to close the connection with `.close()`. ```py connection = await client.responses.connect(...).enter() # ... await connection.close() ``` Nr2r3r4r5r:r;r<r=r>c XlSUlX lX0lX@lXPlX`lXplXl[U S9Ul [SS9Ul g)N max_bytesFr) (_AsyncResponsesConnectionManager__client,_AsyncResponsesConnectionManager__connection-_AsyncResponsesConnectionManager__extra_query/_AsyncResponsesConnectionManager__extra_headers>_AsyncResponsesConnectionManager__websocket_connection_options1_AsyncResponsesConnectionManager__on_reconnecting-_AsyncResponsesConnectionManager__max_retries/_AsyncResponsesConnectionManager__initial_delay+_AsyncResponsesConnectionManager__max_delayr@,_AsyncResponsesConnectionManager__send_queuerC8_AsyncResponsesConnectionManager__event_handler_registry rqr8rrr9r:r;r<r=r>s rrr(AsyncResponsesConnectionManager.__init__sU =A(,.J+!0(,$%?(TRRTU5 U$rnrrurvs rrrx5AsyncResponsesConnectionManager.on..decorator  ) ) - -j" =Irur{rr}s`` rrr"AsyncResponsesConnectionManager.on8    ) ) - -j' BK  ruc<URRX5 U$r)rrrs rrr#AsyncResponsesConnectionManager.off% %%,,ZA ruc\^^UbTRRTUSS9 T$SUU4SjjnU$)GRegister a one-time event handler before the connection is established.Trc>>TRRTUSS9 U$rrrvs rrrx7AsyncResponsesConnectionManager.once..decorator2#  ) ) - -j"4 - HIrur{rr}s`` rrr$AsyncResponsesConnectionManager.once*=    ) ) - -j' - MK  ruc # URURUR5IShvN n[UURb UROSURUR UR URURURURS9 Ul URRURR5 URR5IShvN UR$NN7f)a6 If your application doesn't work well with the context manager approach then you can call this method directly to initiate a connection. **Warning**: You must remember to close the connection with `.close()`. ```py connection = await client.responses.connect(...).enter() # ... await connection.close() ``` Nr) _connect_wsrrrrrrrrrr merge_intorrbrqwss rr __aenter__*AsyncResponsesConnectionManager.__aenter__8s##D$6$68L8LM M4 (,(>(>(JD$$PT 22**..&&**..((   %%001B1B1Z1Z[11333   #N 4s"*DDCD2D3DDc# SSKJn UR 5R 0UR RREUES9n[RS5 UR(a[RS5 U"[U54UR R[0UR REU5S.URD6IShvN $![an[S5UeSnAff=fN"7f)Nr)_WebSocketConnect9You need to install `openai[realtime]` to use this methodparamsConnecting to WebSocket API,Custom WebSocket connection options provideduser_agent_headeradditional_headers)lib._websocketr ImportErrorr> _prepare_url copy_withrbase_urlrrjrrrc user_agentrA auth_headersrqrrrArurls rrr+AsyncResponsesConnectionManager._connect_wsZs d F!++--((//,  /0  . . IID E H  "mm66.mm00    11    dYZ`c c d  s4C?CCC?C=C? C:) C55C::C?cdURRb [URR5nOMURRRnUS:XaSOSnURRR US9nUR RS5S-nUR US9$Nhttprwss)scheme/s /responses)raw_path)rwebsocket_base_urlr' _base_urlrrrrstriprqrr ws_schememerge_raw_paths rrr,AsyncResponsesConnectionManager._prepare_urlv == + + 7*4==+K+KLH]],,33F && 0eI}}..88 8JH!**11$7-G!!>!::rucp# URb#URR5IShvN ggN7frn)rrArqexc_typerexc_tbs rr __aexit__)AsyncResponsesConnectionManager.__aexit__s3    (##))+ + + ) +s +646 __client __connection__event_handler_registry__extra_headers __extra_query__initial_delay __max_delay __max_retries__on_reconnecting __send_queue__websocket_connection_options)r8rgrrrrr9rXr:rrr;rsr<rtr=rtr>rsrrorrn)rrcr~rrzZUnion[AsyncResponsesConnectionManager, Callable[[Callable[..., Any]], Callable[..., Any]]])rrcr~r|rr)rr)rrrrrrrz httpx2.URLrztype[BaseException] | NonerzBaseException | NonerzTracebackType | Nonerro)rvrwrxryrrr.rrrrenterrrrrzrrurrrrs4_c"'MM M  M 'A M\MMMMM M2 (EI(A c$ EI  (A  c !@ E 8 ;,2,9M,Wk, ,rurc  \rSrSr%SrS\S'S\S'SSSS S 00SS .SS jjrSS jrS SjrS!Sjr S"Sjr S#Sjr SSS.S$Sjjr S%Sjr S&SjrS'SjrS(S)SjjrS*SjrS(S)SjjrS'SjrSrg)+ResponsesConnectionirResponsesResponseResourcerWebSocketConnectionrNr2r3r4rcXlX lX0lX@lSUlXPlX`lXplXlSUl SUl U =(d [5Ul [SS9Ul[U5Ulg)NrFTr)rrrrrrrrrrrr@rrCrrrrs rrrResponsesConnection.__init__sr& /'"#+#'+%*" %%4';T'J$1$7 ruc## SSKJnJn UR5v M!Ua gUaMnUR U5(d-UR R 5nU(a [SUS9UeeSnANWSnAff=f7frrrs rr__iter__ResponsesConnection.__iter__s T iik!& ( s++!--335F<N,2 ##, s5 A>!A>A;A>A;AA61A>6A;;A>c,URUR55n[[[U5[ 5(a[SU5R S5O [USS5n[U[5(aU(a US:waSUl U$)r r rNr rr rs rrrResponsesConnection.recvs   !23$vu-t44 $e , 0 0 8-  j# & &:*:O&'D # rucURRSS9n[RS[ U55 UR (ar[ R"U5n[U[5(a[SU5RS5OSn[U[5(aU(a US:waSUlU$![[4a Us$f=f) rFrrr rNr rrr!s rrrResponsesConnection.recv_bytess""''u'5 8#g,G  " " %)ZZ%8 OYYceiNjNj1:>BB6JptJ*c**zjG>S*+' /  s B>>CCc~[U[5(aURSSSS9O#[R"[ U[ 55nUR(aURRU5 gURRU5 g![a URRU5 ef=fr&) rrr+rr,r#rdrrr-rr.rr/s rrr.ResponsesConnection.sends%++ MMtSWM XOE3LMN     $ $T *      ! !$ '     $ $T *  s 9B'B<cUR(aD[U[5(aUOURS5nURR U5 gUR RU5 gr3r4r5s rrr7ResponsesConnection.send_rawsR  $T3//$T[[5IC    $ $S )  d#rur9r:r;cDSUlURRXS9 gr?r@rBs rrrAResponsesConnection.closes!%)" D8ruc ~[[[[R"U5[[ [5S95$rErHrIs rrrResponsesConnection.parse_eventrKruc URb URcgSSKJn Sn[ X5(a#UR bUR R n[U5(dgSUl[URS-URS-5GH~nX@l [URSUS- --UR5nS[R"5S --nXV-n[!UURUUUR"UR$S 9nURU5n U bU R)S 5(a SUl gU b S U ;a U S UlS U ;a U S Ul[*R-SUURU5 [.R0"U5 UR2(a SUl gURUR"UR$5Ul[*R-S5 SUlUR75 g SUlg![&a SUl gf=f![&a GMf=f)rMFrrNrOTr-rPrQrRrSrXrrrYrZ)rrrrrr\r<rRrr]rrr^rrr_rPrrrrrjr`timerarrrb) rqrrrWrTrcrdrVrres rrrResponsesConnection._reconnects&  (DMM,A? c 1 1chh6JJ#J// $T44q8$:K:Ka:OPG&- #T00A'A+4FGYJFMMOd22F'E%!..% --"11 E ..u5 !fjj&9&9(-%! F*(.}(=D%"f,*0*AD' HHQ!!   JJu ))(-% #'==1B1BDDWDW#X 78(-%&&(aQh!&I (-% @  s%H =AH8 H54H58 IIc^TRRU4Sj5 g![a [R S5 gf=f)rhc:>TRRU5$rnrjrks rrr7ResponsesConnection._flush_send_queue..\sT5E5E5J5J45PrurnN)r flush_syncrrjrprps`rrrb%ResponsesConnection._flush_send_queueYs< F    ' '(P Q F KKD E Fs#AAc^^^UbTRRTU5 T$SUU4SjjnU$)aAdds the handler to the end of the handlers list for the given event type. No checks are made to see if the handler has already been added. Multiple calls passing the same combination of event type and handler will result in the handler being added, and called, multiple times. Can be used as a method (returns ``self`` for chaining):: connection.on("response.steer.accepted", my_handler) Or as a decorator:: @connection.on("response.steer.accepted") def my_handler(event): ... c@>TRRTU5 U$rnrtrvs rrrx)ResponsesConnection.on..decoratorvrzrur{rtr}s`` rrrResponsesConnection.on`rruc<URRX5 U$rrrs rrrResponsesConnection.off|rruc\^^UbTRRTUSS9 T$SUU4SjjnU$)rTrc>>TRRTUSS9 U$rrtrvs rrrx+ResponsesConnection.once..decoratorrrur{rtr}s`` rrrResponsesConnection.oncerrucLUHnURnURRU5nURRS5nUS:Xa1U(d*U(d#[U[5(a[ SU35eUH nU"U5 M UH nU"U5 M M g)aQRun the event loop, dispatching received events to registered handlers. Blocks the current thread until the connection is closed. This is the push-based alternative to iterating with ``for event in connection``. If an ``"error"`` event arrives and no handler is registered for ``"error"`` or ``"event"``, an ``OpenAIError`` is raised. rr rN)rrrrr_r>)rqrrrrr~s rrr#ResponsesConnection.dispatch_eventssEJ33@@LH22??HGW$Xge_55%(9%&ABB#$##rur)rrrz6Callable[[Query, Headers], WebSocketConnection] | Noner:rrr;rsr<rtr=rtrrrrrrrro)rzIterator[ResponsesServerEvent]rrrrrrrrrn)rrcr~rrzNUnion[ResponsesConnection, Callable[[Callable[..., Any]], Callable[..., Any]]])rrcr~r|rr)rvrwrxryrrrrrrr.r7rArrrbrrrrrzrrurrrrsE''$$ KO^b"!#'+8'8H 8 \ 8  88888%8 8:,$* $$(r9  IVFEI(A W8 EI(A W"rurc\rSrSrSrSSSSSS.SS jjrSS jrSSS jjrSS jrSSS jjr SSjr \ r SSjr SSjr SSjrSrg)r?ia Context manager over a `ResponsesConnection` that is returned by `responses.connect()` This context manager ensures that the connection will be closed when it exits. --- Note that if your application doesn't work well with the context manager approach then you can call the `.enter()` method directly to initiate a connection. **Warning**: You must remember to close the connection with `.close()`. ```py connection = client.responses.connect(...).enter() # ... connection.close() ``` Nr2r3r4r5rc XlSUlX lX0lX@lXPlX`lXplXl[U S9Ul [SS9Ul g)NrTr) #_ResponsesConnectionManager__client'_ResponsesConnectionManager__connection(_ResponsesConnectionManager__extra_query*_ResponsesConnectionManager__extra_headers9_ResponsesConnectionManager__websocket_connection_options,_ResponsesConnectionManager__on_reconnecting(_ResponsesConnectionManager__max_retries*_ResponsesConnectionManager__initial_delay&_ResponsesConnectionManager__max_delayr@'_ResponsesConnectionManager__send_queuerC3_ResponsesConnectionManager__event_handler_registryrs rrr#ResponsesConnectionManager.__init__sU 8<(,.J+!0(,$%?(TRRTU5 U$rnrErurvs rrrx0ResponsesConnectionManager.on..decoratorrrur{rKr}s`` rrrResponsesConnectionManager.onrruc<URRX5 U$r)rErrs rrrResponsesConnectionManager.offrruc\^^UbTRRTUSS9 T$SUU4SjjnU$)rTrc>>TRRTUSS9 U$rrKrvs rrrx2ResponsesConnectionManager.once..decoratorrrur{rKr}s`` rrrResponsesConnectionManager.oncerruc URURUR5n[UURb UROSURUR UR URURURURS9 Ul URRURR5 URR5 UR$)a* If your application doesn't work well with the context manager approach then you can call this method directly to initiate a connection. **Warning**: You must remember to close the connection with `.close()`. ```py connection = client.responses.connect(...).enter() # ... connection.close() ``` Nr)rr=r>rr@rArBrCrDr<rErrrbrs rr __enter__$ResponsesConnectionManager.__enter__ s  d00$2F2F G/ (,(>(>(JD$$PT 22**..&&**..((   %%001B1B1Z1Z[ ++-   rucSSKJn UR 5R 0UR RREUES9n[RS5 UR(a[RS5 U"[U54UR R[0UR REU5S.URD6$![an[S5UeSnAff=f)Nr)rArrrrr)websockets.sync.clientrArr>rrr;rrrjrr?rcrrArrs rrr&ResponsesConnectionManager._connect_ws,s d 6!++--((//,  /0  . . IID E H  "mm66.mm00    11   dYZ`c c dsC C0 C++C0cdURRb [URR5nOMURRRnUS:XaSOSnURRR US9nUR RS5S-nUR US9$r)r;rr'rrrrrrs rrr'ResponsesConnectionManager._prepare_urlHrrucTURbURR5 ggrn)r<rArs rr__exit__#ResponsesConnectionManager.__exit__Ss'    (    # # % )rur)r8rfrrrrr9rXr:rrr;rsr<rtr=rtr>rsrrorrn)rrcr~rrzUUnion[ResponsesConnectionManager, Callable[[Callable[..., Any]], Callable[..., Any]]])rrcr~r|rr?)rr)rrrrrrr r)rvrwrxryrrr.rrrrUrrrr]rzrrurrr?r?s4_c"'LL L  L 'A L\LLLLL L2 (EI(A ^$ EI  (A  ^ !@ E 8 ;&2&9M&Wk& &rur?c\rSrSrSSjrSrg)BaseResponsesConnectionResourceiZcXlgrnrrqrs rrr(BaseResponsesConnectionResource.__init__[%rurbN)rrrrorvrwrxryrrzrrurrr`r`Z&rur`c!\rSrSrSSjr\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\S. SSjjrSrg) ri_c@URRSXS.5 gajQueues user input to steer a response on this WebSocket connection. Input can contain text, images, and files. Steering is supported only for single-agent responses on models and execution modes that support steering. Responses bound to a conversation or using automatic compaction do not support steering. A `response.steer.accepted` event acknowledges that the server owns the queued input, not that it has been applied. The successor's `response.created` event is the commit point. Input that cannot be committed is returned in `response.steer.failed`. Steering may cause the active response to finish at a safe output boundary with `response.incomplete` and `incomplete_details.reason` set to `steered`, followed automatically by a successor `response.created`. Normal completion can also be followed by an automatic successor. Automatic successors inherit the previous response's settings and continue from it with the queued input. If the response stops for client-owned tool output or approval, accepted steering input remains queued and `response.steer.pending` is emitted after `response.completed`. Fill the `required_input` stubs from that event with saved tool results or approval decisions, and send one explicit `response.create` per parent with the same `previous_response_id` and WebSocket lane. Do not rerun tools or resend accepted steering input. The queued input is prepended in submission order to that request's input, and the explicit request retains its own settings. This event accepts only `type`, `previous_response_id`, and `input`. Do not send `stream_id`; the target response determines the WebSocket lane. zresponse.steer)rrrNrjrqrrs rrsteerResponsesResponseResource.steer`s@ '7%vwru rrrrrrrrrrrrrrrrrrrrrr stream_idrrrrrrrrrc 2URR[[[ 0SS_SU_SU_SU_SU_SU_SU_S U_S U_S U _S U _S U _SU _SU _SU_SU_SU_0SU_SU_SU_SU_SU_SU_SU_SU_SU_SU_SU_SU_SU_S U_S!U_S"U _E555 g#$ay Client event for creating a response over a persistent WebSocket connection. This payload uses the same top-level fields as `POST /v1/responses`, plus WebSocket-only envelope metadata. Notes: - `stream` is implicit over WebSocket and should not be sent. - `background` is not supported over WebSocket. - `stream_id` is WebSocket-only and is not part of `POST /v1/responses`. rzresponse.createrrrrrrrrrrrrrrrrrrrrrrrorrrrrrrrrNrr.rrdr$!rqrrrrrrrrrrrrrrrrrrrrrrrorrrrrrrrrs! rrr ResponsesResponseResource.creates^  )" 1"$j"-.@"' " "7 "   "' ",->")."#H" "%j"./B"/0D"!&" +,)"*' +", -".!&/"0$Y1"2).3"4&{5"67"8&{9": ;"<' ="> ?"@%jA"BC"$' ) rurNrrbrrcrroBrrDrzWOptional[Iterable[responses_client_event_param.ResponseCreateContextManagement]] | OmitrzHOptional[responses_client_event_param.ResponseCreateConversation] | OmitrrGrrHrrIrrJrrJrrKrrLrzFOptional[responses_client_event_param.ResponseCreateModeration] | OmitrrDrrIrrNrrIrzDresponses_client_event_param.ResponseCreatePromptCacheOptions | OmitrrPrrQrrIrrRrrDrrDrorYrzIOptional[responses_client_event_param.ResponseCreateStreamOptions] | OmitrrTrrUrz*?X @+AX B&CX DAEX FGX H IX X rurc\rSrSrSSjrSrg)$BaseAsyncResponsesConnectionResourceicXlgrnrbrcs rrr-BaseAsyncResponsesConnectionResource.__init__rerurbN)rrrrorfrrurrryryrgruryc!\rSrSrSSjr\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\S. SSjjrSrg) ric\# URRSXS.5IShvN gN7frjrjrks rrrl$AsyncResponsesResponseResource.steers.@##% d   s ",*,rnc N# URR[[[ 0SS_SU_SU_SU_SU_SU_SU_S U_S U_S U _S U _S U _SU _SU _SU_SU_SU_0SU_SU_SU_SU_SU_SU_SU_SU_SU_SU_SU_SU_SU_S U_S!U_S"U _E555IS#hvN g#N7frqrrrss! rrr%AsyncResponsesResponseResource.creates^## )" 1"$j"-.@"' " "7 "   "' ",->")."#H" "%j"./B"/0D"!&" +,)"*' +", -".!&/"0$Y1"2).3"4&{5"67"8&{9": ;"<' ="> ?"@%jA"BC"$' ) ) ) sBB%B#B%rNrurvrwrrurrrrs" N-1ae=A7;-126/3.2'+]a59597;15eiOS042659'+(, $dh.2/3TX,0-1(,CGGX *X  X _ X ;X 5X +X 0X -X ,X %X [X 3X 3!X "5#X $/%X &c'X (!M)X *.+X ,0-X .3/X 0%1X 2&3X 45X 6b7X 8,9X :-;X <R=X >*?X @+AX B&CX DAEX FGX H IX X rur)rrfrzList[ToolParam] | Omit) __future__rrr&r_loggingrtypesrtypingrrrr r r r r rrrr functoolsrtyping_extensionsrrhttpx2pydanticrr:r_typesrrrrrrrrr _utilsr!r"r#r$r%_compatr&_httpx2r'_modelsr( _resourcer)r* _responser+r,rsr.r/r0r1r2r3 _streamingr4r5 lib._toolsr6r7rwr8r9r:r;r<r= _exceptionsr>r?rr@ _base_clientrArB_event_handlerrCtypes.responsesrDrErFrGlib._parsing._responsesrHrIrJrtypes.responses.responserKtypes.responses.tool_paramrLrMtypes.responses.service_tierrNtypes.shared_params.metadatarOtypes.websocket_reconnectionrPrQrRtypes.shared_params.reasoningrStypes.responses.parsed_responserT"lib.streaming.responses._responsesrUrV"types.responses.compacted_responserW"types.websocket_connection_optionsrX#types.responses.response_includablerY#types.shared_params.responses_modelrZ$types.responses.response_input_paramr[%types.responses.response_prompt_paramr\%types.responses.response_stream_eventr]&types.responses.responses_client_eventr^&types.responses.responses_server_eventr_r`)types.responses.response_input_item_paramra*types.responses.response_steer_input_paramrb*types.responses.response_text_config_paramrc,types.responses.responses_client_event_paramrdrXrerwebsockets.asyncio.clientrrorfrg__all__ getLoggerrvrjrrhrir{rrrrrrrr?r`rryrrrurrrs#     /  ```ff&*/:Y.MG$A2  1G74jj6=cCLEAFHHJ[OQQUNV. ( )''1^1N N b:M %M `:HH@MM@NN:SS:#Ll!l!^ l,l,^``F l&l&^&& { ?{ |&& } %I} ru