archastro.platform.types.ai
1# Copyright (c) 2026 ArchAstro Inc. Licensed under the MIT License. 2# This file is auto-generated by @archastro/sdk-generator. Do not edit. 3# Content hash: 9ba45d20ba35 4 5from typing import Any 6 7from pydantic import BaseModel, Field 8 9 10class AIChatStreamDone(BaseModel): 11 """ 12 Terminal event marking the end of a streaming chat completion (SSE `done` event). 13 """ 14 15 finish_reason: str | None = Field( 16 default=None, description="The overall finish reason for the completion." 17 ) 18 run_count: int | None = Field( 19 default=None, 20 description="Number of model runs executed, including continuations triggered by tool calls.", 21 ) 22 total_usage: dict[str, Any] | None = Field( 23 default=None, 24 description="Aggregate token usage across every run in the completion (including tool-call continuations), keyed by model ID.", 25 ) 26 usage: dict[str, Any] | None = Field( 27 default=None, description="Token usage for the final run, keyed by model ID." 28 ) 29 30 31class AIChatStreamError(BaseModel): 32 """ 33 Terminal error event for a streaming chat completion (SSE `error` event). 34 """ 35 36 message: str = Field( 37 ..., description="Human-readable description of the error that terminated the stream." 38 ) 39 40 41class AIToolCall(BaseModel): 42 """ 43 A tool (function) call emitted by the assistant within an AI message. Mirrors the OpenAI tool-call object format. 44 """ 45 46 arguments: dict[str, Any] = Field( 47 ..., 48 description="Arguments the model wants to pass to the tool, as a key-value map. Deserialize and validate these against the tool's input schema before executing.", 49 ) 50 id: str = Field( 51 ..., 52 description="Unique identifier for this tool call, assigned by the model. Use this value as `id` when submitting the corresponding tool result.", 53 ) 54 name: str = Field( 55 ..., 56 description='Name of the tool or function the model wants to invoke, e.g. `"web_search"` or `"run_code"`.', 57 ) 58 thought_signature: str | None = Field( 59 default=None, 60 description="Opaque signature representing the model's internal reasoning that led to this tool call. `null` when the provider does not expose chain-of-thought data.", 61 ) 62 63 64class AIToolResult(BaseModel): 65 """ 66 The result of executing a tool call, submitted back to the model as a tool-role message. Mirrors the OpenAI tool-result object format. 67 """ 68 69 content: str | None = Field( 70 default=None, 71 description="Plain-text output produced by the tool execution. `null` when the result is expressed entirely through `resolution`.", 72 ) 73 id: str = Field( 74 ..., 75 description="ID of the tool call this result satisfies. Must match the `id` from the corresponding `AIToolCall`.", 76 ) 77 name: str = Field( 78 ..., 79 description='Name of the tool or function that was executed, e.g. `"web_search"`. Must match the `name` from the corresponding `AIToolCall`.', 80 ) 81 resolution: Any | None = Field( 82 default=None, 83 description="Structured result data from the tool execution. Shape varies by tool. `null` when the result is expressed as plain text in `content`.", 84 ) 85 86 87class AIMessage(BaseModel): 88 """ 89 A single message in an AI conversation, following the OpenAI-compatible chat format. Used in both request inputs and completion responses. 90 """ 91 92 content: str | None = Field( 93 default=None, 94 description="Plain-text content of the message. Present for `system`, `user`, and `assistant` messages. `null` when the message body is expressed through `content_parts` or `tool_calls`.", 95 ) 96 content_parts: list[dict[str, Any]] | None = Field( 97 default=None, 98 description='Multimodal content parts for the message, used when the body includes images or mixed media. Each part is a map with a `type` key (`"text"`, `"image_url"`, or `"image_data"`). `null` when `content` is set.', 99 ) 100 resume_token: str | None = Field( 101 default=None, 102 description="Opaque token that can be passed on a subsequent request to resume this conversation from the current state. `null` when the provider does not support conversation resumption.", 103 ) 104 role: str = Field( 105 ..., 106 description='The speaker role for this message. One of `"system"`, `"user"`, `"assistant"`, or `"tool"`.', 107 ) 108 structured_output: Any | None = Field( 109 default=None, 110 description="Parsed structured data returned by the model when a JSON schema or structured-output mode was requested. Shape varies by the schema supplied at call time. `null` when structured output was not requested.", 111 ) 112 tool_calls: list[AIToolCall] | None = Field( 113 default=None, 114 description="Tool calls requested by the model in an `assistant` message. Present only on assistant messages that invoke one or more tools. `null` on all other message roles.", 115 ) 116 tool_results: list[AIToolResult] | None = Field( 117 default=None, 118 description="Tool execution results provided in a `tool` message. Each entry corresponds to a prior tool call by its `id`. `null` on all other message roles.", 119 ) 120 121 122class AIChatStreamMessageComplete(BaseModel): 123 """ 124 The fully assembled assistant message for one run of a streaming chat completion (SSE `message_complete` event). 125 """ 126 127 finish_reason: str | None = Field( 128 default=None, 129 description='Why the model stopped generating this message, e.g. `"stop"`, `"length"`, or `"tool_calls"`.', 130 ) 131 message: AIMessage = Field( 132 ..., 133 description="The complete assistant message for this run, assembled from the preceding deltas.", 134 ) 135 usage: dict[str, Any] | None = Field( 136 default=None, 137 description="Token consumption for this run, keyed by model ID. `null` when usage data is unavailable.", 138 ) 139 140 141class AIChatStreamMessageDelta(BaseModel): 142 """ 143 Incremental assistant text emitted during a streaming chat completion (SSE `message_delta` event). 144 """ 145 146 delta: str = Field( 147 ..., 148 description="The chunk of assistant text produced since the previous `message_delta` event. Concatenate deltas in order to reconstruct the message.", 149 ) 150 151 152class AIChatStreamThinkingDelta(BaseModel): 153 """ 154 Incremental model reasoning emitted during a streaming chat completion (SSE `thinking_delta` event). 155 """ 156 157 delta: str = Field( 158 ..., 159 description="The chunk of model reasoning produced since the previous `thinking_delta` event.", 160 ) 161 162 163class AIChatStreamToolCallDelta(BaseModel): 164 """ 165 Incremental tool-call data emitted as the model assembles a tool invocation (SSE `tool_call_delta` event). 166 """ 167 168 delta: str | None = Field( 169 default=None, 170 description="A chunk of the tool call's serialized arguments. Concatenate deltas to reconstruct the arguments JSON.", 171 ) 172 id: str | None = Field( 173 default=None, 174 description="Identifier of the tool call this delta belongs to, once the model has assigned one.", 175 ) 176 name: str | None = Field(default=None, description="Name of the tool being called, once known.") 177 178 179class AIChatStreamToolResult(BaseModel): 180 """ 181 The result of a server-executed tool, streamed back into the run (SSE `tool_result` event). 182 """ 183 184 content: str | None = Field( 185 default=None, description="The tool's output, serialized as a string." 186 ) 187 id: str | None = Field(default=None, description="ID of the tool call this result satisfies.") 188 name: str | None = Field( 189 default=None, description="Name of the tool that produced this result." 190 ) 191 resolution: str | None = Field( 192 default=None, description='How the tool call resolved, e.g. `"ok"` or `"error"`.' 193 ) 194 195 196class AICompletionResult(BaseModel): 197 """ 198 The result of an AI chat completion request. Returned by chat completion endpoints after the model finishes generating. 199 """ 200 201 finish_reason: str = Field( 202 ..., 203 description='The reason the model stopped generating. Common values include `"stop"` (natural end), `"length"` (token limit reached), and `"tool_calls"` (the model invoked a tool).', 204 ) 205 message: AIMessage = Field( 206 ..., description="The final assistant message produced by the completion." 207 ) 208 messages: list[AIMessage] = Field( 209 ..., 210 description="The complete message history for the conversation, including all user, assistant, and tool messages in order.", 211 ) 212 token_usage: dict[str, Any] | None = Field( 213 default=None, 214 description='Token consumption breakdown keyed by model ID. Each value is a map with `"input_tokens"` and `"output_tokens"` counts. `null` when usage data is unavailable.', 215 ) 216 217 218class AIImageResult(BaseModel): 219 """ 220 The result returned by an AI image generation or editing operation. Contains the generated image (as inline data or a URL) along with dimension, size, and usage metadata. 221 """ 222 223 aspect_ratio: str | None = Field( 224 default=None, 225 description='Aspect ratio of the generated image, e.g. `"16:9"` or `"1:1"`. `null` when not reported by the provider.', 226 ) 227 height: int | None = Field( 228 default=None, 229 description="Height of the generated image in pixels. `null` when the provider does not report dimensions.", 230 ) 231 image_data: str | None = Field( 232 default=None, 233 description="The generated image encoded as a base64 string. Present when the provider returns inline image data. `null` when `image_url` is set instead.", 234 ) 235 image_size: str | None = Field( 236 default=None, 237 description='Resolution tier label for the image, e.g. `"1K"` or `"2K"`. `null` when the provider does not include a tier label.', 238 ) 239 image_type: str | None = Field( 240 default=None, 241 description='MIME type of the generated image, e.g. `"image/png"` or `"image/jpeg"`. `null` when the provider does not report a content type.', 242 ) 243 image_url: str | None = Field( 244 default=None, 245 description="Temporary URL pointing to the generated image hosted by the provider. Present when the provider returns a URL rather than inline data. `null` when `image_data` is set instead.", 246 ) 247 model: str = Field( 248 ..., 249 description='Identifier of the model that produced the image, e.g. `"dall-e-3"` or `"imagen-3"`.', 250 ) 251 revised_prompt: str | None = Field( 252 default=None, 253 description="The prompt as rewritten by the provider before generation. Some providers (e.g. DALL-E 3) automatically expand or safety-check the original prompt. `null` when the provider does not revise prompts.", 254 ) 255 size: str | None = Field( 256 default=None, 257 description='Canonical size string as returned by the provider, e.g. `"1024x1024"`. `null` when not reported.', 258 ) 259 usage: dict[str, Any] | None = Field( 260 default=None, 261 description="Provider-reported token and compute usage for the request. Structure varies by provider. `null` when usage data is unavailable.", 262 ) 263 width: int | None = Field( 264 default=None, 265 description="Width of the generated image in pixels. `null` when the provider does not report dimensions.", 266 )
class
AIChatStreamDone(pydantic.main.BaseModel):
11class AIChatStreamDone(BaseModel): 12 """ 13 Terminal event marking the end of a streaming chat completion (SSE `done` event). 14 """ 15 16 finish_reason: str | None = Field( 17 default=None, description="The overall finish reason for the completion." 18 ) 19 run_count: int | None = Field( 20 default=None, 21 description="Number of model runs executed, including continuations triggered by tool calls.", 22 ) 23 total_usage: dict[str, Any] | None = Field( 24 default=None, 25 description="Aggregate token usage across every run in the completion (including tool-call continuations), keyed by model ID.", 26 ) 27 usage: dict[str, Any] | None = Field( 28 default=None, description="Token usage for the final run, keyed by model ID." 29 )
Terminal event marking the end of a streaming chat completion (SSE done event).
run_count: int | None =
None
Number of model runs executed, including continuations triggered by tool calls.
class
AIChatStreamError(pydantic.main.BaseModel):
32class AIChatStreamError(BaseModel): 33 """ 34 Terminal error event for a streaming chat completion (SSE `error` event). 35 """ 36 37 message: str = Field( 38 ..., description="Human-readable description of the error that terminated the stream." 39 )
Terminal error event for a streaming chat completion (SSE error event).
class
AIToolCall(pydantic.main.BaseModel):
42class AIToolCall(BaseModel): 43 """ 44 A tool (function) call emitted by the assistant within an AI message. Mirrors the OpenAI tool-call object format. 45 """ 46 47 arguments: dict[str, Any] = Field( 48 ..., 49 description="Arguments the model wants to pass to the tool, as a key-value map. Deserialize and validate these against the tool's input schema before executing.", 50 ) 51 id: str = Field( 52 ..., 53 description="Unique identifier for this tool call, assigned by the model. Use this value as `id` when submitting the corresponding tool result.", 54 ) 55 name: str = Field( 56 ..., 57 description='Name of the tool or function the model wants to invoke, e.g. `"web_search"` or `"run_code"`.', 58 ) 59 thought_signature: str | None = Field( 60 default=None, 61 description="Opaque signature representing the model's internal reasoning that led to this tool call. `null` when the provider does not expose chain-of-thought data.", 62 )
A tool (function) call emitted by the assistant within an AI message. Mirrors the OpenAI tool-call object format.
arguments: dict[str, typing.Any] =
PydanticUndefined
Arguments the model wants to pass to the tool, as a key-value map. Deserialize and validate these against the tool's input schema before executing.
id: str =
PydanticUndefined
Unique identifier for this tool call, assigned by the model. Use this value as id when submitting the corresponding tool result.
class
AIToolResult(pydantic.main.BaseModel):
65class AIToolResult(BaseModel): 66 """ 67 The result of executing a tool call, submitted back to the model as a tool-role message. Mirrors the OpenAI tool-result object format. 68 """ 69 70 content: str | None = Field( 71 default=None, 72 description="Plain-text output produced by the tool execution. `null` when the result is expressed entirely through `resolution`.", 73 ) 74 id: str = Field( 75 ..., 76 description="ID of the tool call this result satisfies. Must match the `id` from the corresponding `AIToolCall`.", 77 ) 78 name: str = Field( 79 ..., 80 description='Name of the tool or function that was executed, e.g. `"web_search"`. Must match the `name` from the corresponding `AIToolCall`.', 81 ) 82 resolution: Any | None = Field( 83 default=None, 84 description="Structured result data from the tool execution. Shape varies by tool. `null` when the result is expressed as plain text in `content`.", 85 )
The result of executing a tool call, submitted back to the model as a tool-role message. Mirrors the OpenAI tool-result object format.
content: str | None =
None
Plain-text output produced by the tool execution. null when the result is expressed entirely through resolution.
id: str =
PydanticUndefined
ID of the tool call this result satisfies. Must match the id from the corresponding AIToolCall.
name: str =
PydanticUndefined
Name of the tool or function that was executed, e.g. "web_search". Must match the name from the corresponding AIToolCall.
resolution: typing.Any | None =
None
Structured result data from the tool execution. Shape varies by tool. null when the result is expressed as plain text in content.
class
AIMessage(pydantic.main.BaseModel):
88class AIMessage(BaseModel): 89 """ 90 A single message in an AI conversation, following the OpenAI-compatible chat format. Used in both request inputs and completion responses. 91 """ 92 93 content: str | None = Field( 94 default=None, 95 description="Plain-text content of the message. Present for `system`, `user`, and `assistant` messages. `null` when the message body is expressed through `content_parts` or `tool_calls`.", 96 ) 97 content_parts: list[dict[str, Any]] | None = Field( 98 default=None, 99 description='Multimodal content parts for the message, used when the body includes images or mixed media. Each part is a map with a `type` key (`"text"`, `"image_url"`, or `"image_data"`). `null` when `content` is set.', 100 ) 101 resume_token: str | None = Field( 102 default=None, 103 description="Opaque token that can be passed on a subsequent request to resume this conversation from the current state. `null` when the provider does not support conversation resumption.", 104 ) 105 role: str = Field( 106 ..., 107 description='The speaker role for this message. One of `"system"`, `"user"`, `"assistant"`, or `"tool"`.', 108 ) 109 structured_output: Any | None = Field( 110 default=None, 111 description="Parsed structured data returned by the model when a JSON schema or structured-output mode was requested. Shape varies by the schema supplied at call time. `null` when structured output was not requested.", 112 ) 113 tool_calls: list[AIToolCall] | None = Field( 114 default=None, 115 description="Tool calls requested by the model in an `assistant` message. Present only on assistant messages that invoke one or more tools. `null` on all other message roles.", 116 ) 117 tool_results: list[AIToolResult] | None = Field( 118 default=None, 119 description="Tool execution results provided in a `tool` message. Each entry corresponds to a prior tool call by its `id`. `null` on all other message roles.", 120 )
A single message in an AI conversation, following the OpenAI-compatible chat format. Used in both request inputs and completion responses.
content: str | None =
None
Plain-text content of the message. Present for system, user, and assistant messages. null when the message body is expressed through content_parts or tool_calls.
content_parts: list[dict[str, typing.Any]] | None =
None
Multimodal content parts for the message, used when the body includes images or mixed media. Each part is a map with a type key ("text", "image_url", or "image_data"). null when content is set.
resume_token: str | None =
None
Opaque token that can be passed on a subsequent request to resume this conversation from the current state. null when the provider does not support conversation resumption.
role: str =
PydanticUndefined
The speaker role for this message. One of "system", "user", "assistant", or "tool".
structured_output: typing.Any | None =
None
Parsed structured data returned by the model when a JSON schema or structured-output mode was requested. Shape varies by the schema supplied at call time. null when structured output was not requested.
Tool calls requested by the model in an assistant message. Present only on assistant messages that invoke one or more tools. null on all other message roles.
class
AIChatStreamMessageComplete(pydantic.main.BaseModel):
123class AIChatStreamMessageComplete(BaseModel): 124 """ 125 The fully assembled assistant message for one run of a streaming chat completion (SSE `message_complete` event). 126 """ 127 128 finish_reason: str | None = Field( 129 default=None, 130 description='Why the model stopped generating this message, e.g. `"stop"`, `"length"`, or `"tool_calls"`.', 131 ) 132 message: AIMessage = Field( 133 ..., 134 description="The complete assistant message for this run, assembled from the preceding deltas.", 135 ) 136 usage: dict[str, Any] | None = Field( 137 default=None, 138 description="Token consumption for this run, keyed by model ID. `null` when usage data is unavailable.", 139 )
The fully assembled assistant message for one run of a streaming chat completion (SSE message_complete event).
finish_reason: str | None =
None
Why the model stopped generating this message, e.g. "stop", "length", or "tool_calls".
class
AIChatStreamMessageDelta(pydantic.main.BaseModel):
142class AIChatStreamMessageDelta(BaseModel): 143 """ 144 Incremental assistant text emitted during a streaming chat completion (SSE `message_delta` event). 145 """ 146 147 delta: str = Field( 148 ..., 149 description="The chunk of assistant text produced since the previous `message_delta` event. Concatenate deltas in order to reconstruct the message.", 150 )
Incremental assistant text emitted during a streaming chat completion (SSE message_delta event).
class
AIChatStreamThinkingDelta(pydantic.main.BaseModel):
153class AIChatStreamThinkingDelta(BaseModel): 154 """ 155 Incremental model reasoning emitted during a streaming chat completion (SSE `thinking_delta` event). 156 """ 157 158 delta: str = Field( 159 ..., 160 description="The chunk of model reasoning produced since the previous `thinking_delta` event.", 161 )
Incremental model reasoning emitted during a streaming chat completion (SSE thinking_delta event).
class
AIChatStreamToolCallDelta(pydantic.main.BaseModel):
164class AIChatStreamToolCallDelta(BaseModel): 165 """ 166 Incremental tool-call data emitted as the model assembles a tool invocation (SSE `tool_call_delta` event). 167 """ 168 169 delta: str | None = Field( 170 default=None, 171 description="A chunk of the tool call's serialized arguments. Concatenate deltas to reconstruct the arguments JSON.", 172 ) 173 id: str | None = Field( 174 default=None, 175 description="Identifier of the tool call this delta belongs to, once the model has assigned one.", 176 ) 177 name: str | None = Field(default=None, description="Name of the tool being called, once known.")
Incremental tool-call data emitted as the model assembles a tool invocation (SSE tool_call_delta event).
delta: str | None =
None
A chunk of the tool call's serialized arguments. Concatenate deltas to reconstruct the arguments JSON.
class
AIChatStreamToolResult(pydantic.main.BaseModel):
180class AIChatStreamToolResult(BaseModel): 181 """ 182 The result of a server-executed tool, streamed back into the run (SSE `tool_result` event). 183 """ 184 185 content: str | None = Field( 186 default=None, description="The tool's output, serialized as a string." 187 ) 188 id: str | None = Field(default=None, description="ID of the tool call this result satisfies.") 189 name: str | None = Field( 190 default=None, description="Name of the tool that produced this result." 191 ) 192 resolution: str | None = Field( 193 default=None, description='How the tool call resolved, e.g. `"ok"` or `"error"`.' 194 )
The result of a server-executed tool, streamed back into the run (SSE tool_result event).
class
AICompletionResult(pydantic.main.BaseModel):
197class AICompletionResult(BaseModel): 198 """ 199 The result of an AI chat completion request. Returned by chat completion endpoints after the model finishes generating. 200 """ 201 202 finish_reason: str = Field( 203 ..., 204 description='The reason the model stopped generating. Common values include `"stop"` (natural end), `"length"` (token limit reached), and `"tool_calls"` (the model invoked a tool).', 205 ) 206 message: AIMessage = Field( 207 ..., description="The final assistant message produced by the completion." 208 ) 209 messages: list[AIMessage] = Field( 210 ..., 211 description="The complete message history for the conversation, including all user, assistant, and tool messages in order.", 212 ) 213 token_usage: dict[str, Any] | None = Field( 214 default=None, 215 description='Token consumption breakdown keyed by model ID. Each value is a map with `"input_tokens"` and `"output_tokens"` counts. `null` when usage data is unavailable.', 216 )
The result of an AI chat completion request. Returned by chat completion endpoints after the model finishes generating.
finish_reason: str =
PydanticUndefined
The reason the model stopped generating. Common values include "stop" (natural end), "length" (token limit reached), and "tool_calls" (the model invoked a tool).
class
AIImageResult(pydantic.main.BaseModel):
219class AIImageResult(BaseModel): 220 """ 221 The result returned by an AI image generation or editing operation. Contains the generated image (as inline data or a URL) along with dimension, size, and usage metadata. 222 """ 223 224 aspect_ratio: str | None = Field( 225 default=None, 226 description='Aspect ratio of the generated image, e.g. `"16:9"` or `"1:1"`. `null` when not reported by the provider.', 227 ) 228 height: int | None = Field( 229 default=None, 230 description="Height of the generated image in pixels. `null` when the provider does not report dimensions.", 231 ) 232 image_data: str | None = Field( 233 default=None, 234 description="The generated image encoded as a base64 string. Present when the provider returns inline image data. `null` when `image_url` is set instead.", 235 ) 236 image_size: str | None = Field( 237 default=None, 238 description='Resolution tier label for the image, e.g. `"1K"` or `"2K"`. `null` when the provider does not include a tier label.', 239 ) 240 image_type: str | None = Field( 241 default=None, 242 description='MIME type of the generated image, e.g. `"image/png"` or `"image/jpeg"`. `null` when the provider does not report a content type.', 243 ) 244 image_url: str | None = Field( 245 default=None, 246 description="Temporary URL pointing to the generated image hosted by the provider. Present when the provider returns a URL rather than inline data. `null` when `image_data` is set instead.", 247 ) 248 model: str = Field( 249 ..., 250 description='Identifier of the model that produced the image, e.g. `"dall-e-3"` or `"imagen-3"`.', 251 ) 252 revised_prompt: str | None = Field( 253 default=None, 254 description="The prompt as rewritten by the provider before generation. Some providers (e.g. DALL-E 3) automatically expand or safety-check the original prompt. `null` when the provider does not revise prompts.", 255 ) 256 size: str | None = Field( 257 default=None, 258 description='Canonical size string as returned by the provider, e.g. `"1024x1024"`. `null` when not reported.', 259 ) 260 usage: dict[str, Any] | None = Field( 261 default=None, 262 description="Provider-reported token and compute usage for the request. Structure varies by provider. `null` when usage data is unavailable.", 263 ) 264 width: int | None = Field( 265 default=None, 266 description="Width of the generated image in pixels. `null` when the provider does not report dimensions.", 267 )
The result returned by an AI image generation or editing operation. Contains the generated image (as inline data or a URL) along with dimension, size, and usage metadata.
aspect_ratio: str | None =
None
Aspect ratio of the generated image, e.g. "16:9" or "1:1". null when not reported by the provider.
height: int | None =
None
Height of the generated image in pixels. null when the provider does not report dimensions.
image_data: str | None =
None
The generated image encoded as a base64 string. Present when the provider returns inline image data. null when image_url is set instead.
image_size: str | None =
None
Resolution tier label for the image, e.g. "1K" or "2K". null when the provider does not include a tier label.
image_type: str | None =
None
MIME type of the generated image, e.g. "image/png" or "image/jpeg". null when the provider does not report a content type.
image_url: str | None =
None
Temporary URL pointing to the generated image hosted by the provider. Present when the provider returns a URL rather than inline data. null when image_data is set instead.
model: str =
PydanticUndefined
Identifier of the model that produced the image, e.g. "dall-e-3" or "imagen-3".
revised_prompt: str | None =
None
The prompt as rewritten by the provider before generation. Some providers (e.g. DALL-E 3) automatically expand or safety-check the original prompt. null when the provider does not revise prompts.
size: str | None =
None
Canonical size string as returned by the provider, e.g. "1024x1024". null when not reported.