| 1 | /** |
| 2 | * The `OpenAiLanguageModel` module provides the OpenAI Responses API |
| 3 | * implementation of Effect AI's `LanguageModel` service. It translates Effect |
| 4 | * AI prompts, files, tools, structured output requests, reasoning metadata, and |
| 5 | * provider options into OpenAI response requests, then converts OpenAI |
| 6 | * non-streaming or streaming response results back into Effect AI response |
| 7 | * content and metadata. |
| 8 | * |
| 9 | * @stability unstable |
| 10 | * @since 4.0.0 |
| 11 | */ |
| 12 | import * as AiError from "effect/ai/AiError" |
| 13 | import * as IdGenerator from "effect/ai/IdGenerator" |
| 14 | import * as LanguageModel from "effect/ai/LanguageModel" |
| 15 | import * as AiModel from "effect/ai/Model" |
| 16 | import { toCodecOpenAI } from "effect/ai/OpenAiStructuredOutput" |
| 17 | import type * as Prompt from "effect/ai/Prompt" |
| 18 | import type * as Response from "effect/ai/Response" |
| 19 | import * as Tool from "effect/ai/Tool" |
| 20 | import * as Context from "effect/Context" |
| 21 | import * as DateTime from "effect/DateTime" |
| 22 | import * as Effect from "effect/Effect" |
| 23 | import * as Base64 from "effect/encoding/Base64" |
| 24 | import { dual } from "effect/Function" |
| 25 | import type * as HttpClientRequest from "effect/http/HttpClientRequest" |
| 26 | import type * as HttpClientResponse from "effect/http/HttpClientResponse" |
| 27 | import * as Layer from "effect/Layer" |
| 28 | import * as Option from "effect/Option" |
| 29 | import * as Predicate from "effect/Predicate" |
| 30 | import * as Redactable from "effect/Redactable" |
| 31 | import * as Schema from "effect/Schema" |
| 32 | import * as AST from "effect/SchemaAST" |
| 33 | import * as Stream from "effect/Stream" |
| 34 | import type { Span } from "effect/Tracer" |
| 35 | import type { DeepMutable, Mutable, Simplify } from "effect/Types" |
| 36 | import * as Generated from "./Generated.ts" |
| 37 | import * as InternalUtilities from "./internal/utilities.ts" |
| 38 | import { OpenAiClient, OpenAiSocket } from "./OpenAiClient.ts" |
| 39 | import type * as OpenAiSchema from "./OpenAiSchema.ts" |
| 40 | import { addGenAIAnnotations } from "./OpenAiTelemetry.ts" |
| 41 | import type * as OpenAiTool from "./OpenAiTool.ts" |
| 42 | |
| 43 | const ResponseModelIds = Generated.ModelIdsResponses.members[1] |
| 44 | const SharedModelIds = Generated.ModelIdsShared.members[1] |
| 45 | |
| 46 | /** |
| 47 | * OpenAI model identifiers supported by the Responses API language model. |
| 48 | * |
| 49 | * @stability unstable |
| 50 | * @category models |
| 51 | * @since 4.0.0 |
| 52 | */ |
| 53 | export type Model = typeof ResponseModelIds.Encoded | typeof SharedModelIds.Encoded |
| 54 | |
| 55 | /** |
| 56 | * Image detail level for vision requests. |
| 57 | */ |
| 58 | type ImageDetail = "auto" | "low" | "high" |
| 59 | |
| 60 | type PromptCacheBreakpoint = { readonly mode: "explicit" } |
| 61 | |
| 62 | // ============================================================================= |
| 63 | // Configuration |
| 64 | // ============================================================================= |
| 65 | |
| 66 | /** |
| 67 | * Context service for OpenAI language model configuration. |
| 68 | * |
| 69 | * **When to use** |
| 70 | * |
| 71 | * Use when you need to provide OpenAI Responses API request defaults through |
| 72 | * Effect context for language model operations. |
| 73 | * |
| 74 | * **Details** |
| 75 | * |
| 76 | * Config values are merged with the config object passed to `model`, `make`, or |
| 77 | * `layer`, with scoped context values taking precedence. |
| 78 | * |
| 79 | * @see {@link withConfigOverride} for scoping language model request overrides |
| 80 | * |
| 81 | * @stability unstable |
| 82 | * @category services |
| 83 | * @since 4.0.0 |
| 84 | */ |
| 85 | export class Config extends Context.Service< |
| 86 | Config, |
| 87 | Simplify< |
| 88 | & Partial< |
| 89 | Omit< |
| 90 | typeof OpenAiSchema.CreateResponse.Encoded, |
| 91 | "input" | "tools" | "tool_choice" | "stream" | "text" |
| 92 | > |
| 93 | > |
| 94 | & { |
| 95 | /** |
| 96 | * File ID prefixes used to identify file IDs in Responses API. |
| 97 | * When undefined, all file data is treated as base64 content. |
| 98 | * |
| 99 | * Examples: |
| 100 | * - OpenAI: ['file-'] for IDs like 'file-abc123' |
| 101 | * - Azure OpenAI: ['assistant-'] for IDs like 'assistant-abc123' |
| 102 | */ |
| 103 | readonly fileIdPrefixes?: ReadonlyArray<string> | undefined |
| 104 | /** |
| 105 | * Configuration options for a text response from the model. |
| 106 | */ |
| 107 | readonly text?: { |
| 108 | /** |
| 109 | * Constrains the verbosity of the model's response. Lower values will |
| 110 | * result in more concise responses, while higher values will result in |
| 111 | * more verbose responses. |
| 112 | * |
| 113 | * Defaults to `"medium"`. |
| 114 | */ |
| 115 | readonly verbosity?: "low" | "medium" | "high" | undefined |
| 116 | } | undefined |
| 117 | /** |
| 118 | * Whether to use strict JSON schema validation. |
| 119 | * |
| 120 | * Defaults to `true`. |
| 121 | */ |
| 122 | readonly strictJsonSchema?: boolean | undefined |
| 123 | /** |
| 124 | * Whether stored response items should be sent as item references. |
| 125 | * |
| 126 | * Set to `false` for OpenAI-compatible providers that support response |
| 127 | * storage and `previous_response_id`, but require historical assistant |
| 128 | * content to be serialized inline. |
| 129 | * |
| 130 | * Defaults to `true` when `store` is `true`. |
| 131 | */ |
| 132 | readonly useItemReferences?: boolean | undefined |
| 133 | } |
| 134 | > |
| 135 | >()("@effect/ai-openai/OpenAiLanguageModel/Config") {} |
| 136 | |
| 137 | // ============================================================================= |
| 138 | // Provider Options / Metadata |
| 139 | // ============================================================================= |
| 140 | |
| 141 | declare module "effect/ai/Prompt" { |
| 142 | /** |
| 143 | * OpenAI-specific options for system messages. |
| 144 | * |
| 145 | * @stability unstable |
| 146 | * @category models |
| 147 | * @since 4.0.0 |
| 148 | */ |
| 149 | export interface SystemMessageOptions extends ProviderOptions { |
| 150 | /** |
| 151 | * Provider-specific system message options for the OpenAI Responses API. |
| 152 | */ |
| 153 | readonly openai?: { |
| 154 | /** |
| 155 | * Marks the system input text as the end of a reusable prompt prefix. |
| 156 | * |
| 157 | * Requires GPT-5.6 or later. OpenAI may reject requests that use this |
| 158 | * option with earlier models. |
| 159 | */ |
| 160 | readonly promptCacheBreakpoint?: PromptCacheBreakpoint | null |
| 161 | } | null |
| 162 | } |
| 163 | |
| 164 | /** |
| 165 | * OpenAI-specific options for file prompt parts. |
| 166 | * |
| 167 | * @stability unstable |
| 168 | * @category models |
| 169 | * @since 4.0.0 |
| 170 | */ |
| 171 | export interface FilePartOptions extends ProviderOptions { |
| 172 | /** |
| 173 | * Provider-specific file options for the OpenAI Responses API. |
| 174 | */ |
| 175 | readonly openai?: { |
| 176 | /** |
| 177 | * The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. |
| 178 | */ |
| 179 | readonly imageDetail?: ImageDetail | null |
| 180 | } | null |
| 181 | } |
| 182 | |
| 183 | /** |
| 184 | * OpenAI-specific options for reasoning prompt parts. |
| 185 | * |
| 186 | * @stability unstable |
| 187 | * @category models |
| 188 | * @since 4.0.0 |
| 189 | */ |
| 190 | export interface ReasoningPartOptions extends ProviderOptions { |
| 191 | /** |
| 192 | * Provider-specific reasoning options for the OpenAI Responses API. |
| 193 | */ |
| 194 | readonly openai?: { |
| 195 | /** |
| 196 | * The ID of the item to reference. |
| 197 | */ |
| 198 | readonly itemId?: string | null |
| 199 | /** |
| 200 | * The encrypted content of the reasoning item - populated when a response |
| 201 | * is generated with `reasoning.encrypted_content` in the `include` |
| 202 | * parameter. |
| 203 | */ |
| 204 | readonly encryptedContent?: string | null |
| 205 | } | null |
| 206 | } |
| 207 | |
| 208 | /** |
| 209 | * OpenAI-specific options for assistant tool-call prompt parts. |
| 210 | * |
| 211 | * @stability unstable |
| 212 | * @category models |
| 213 | * @since 4.0.0 |
| 214 | */ |
| 215 | export interface ToolCallPartOptions extends ProviderOptions { |
| 216 | /** |
| 217 | * Provider-specific tool-call options for the OpenAI Responses API. |
| 218 | */ |
| 219 | readonly openai?: { |
| 220 | /** |
| 221 | * The ID of the item to reference. |
| 222 | */ |
| 223 | readonly itemId?: string | null |
| 224 | /** |
| 225 | * The status of item. |
| 226 | */ |
| 227 | readonly status?: typeof OpenAiSchema.MessageStatus.Encoded | null |
| 228 | /** |
| 229 | * The ID of the approval request. |
| 230 | */ |
| 231 | readonly approvalRequestId?: string | null |
| 232 | } | null |
| 233 | } |
| 234 | |
| 235 | /** |
| 236 | * OpenAI-specific options for tool-result prompt parts. |
| 237 | * |
| 238 | * @stability unstable |
| 239 | * @category models |
| 240 | * @since 4.0.0 |
| 241 | */ |
| 242 | export interface ToolResultPartOptions extends ProviderOptions { |
| 243 | /** |
| 244 | * Provider-specific tool-result options for the OpenAI Responses API. |
| 245 | */ |
| 246 | readonly openai?: { |
| 247 | /** |
| 248 | * The ID of the item to reference. |
| 249 | */ |
| 250 | readonly itemId?: string | null |
| 251 | /** |
| 252 | * The status of item. |
| 253 | */ |
| 254 | readonly status?: typeof OpenAiSchema.MessageStatus.Encoded | null |
| 255 | /** |
| 256 | * The ID of the approval request. |
| 257 | */ |
| 258 | readonly approvalId?: string | null |
| 259 | } | null |
| 260 | } |
| 261 | |
| 262 | /** |
| 263 | * OpenAI-specific options for text prompt parts. |
| 264 | * |
| 265 | * @stability unstable |
| 266 | * @category models |
| 267 | * @since 4.0.0 |
| 268 | */ |
| 269 | export interface TextPartOptions extends ProviderOptions { |
| 270 | /** |
| 271 | * Provider-specific text options for the OpenAI Responses API. |
| 272 | */ |
| 273 | readonly openai?: { |
| 274 | /** |
| 275 | * The ID of the item to reference. |
| 276 | */ |
| 277 | readonly itemId?: string | null |
| 278 | /** |
| 279 | * The status of item. |
| 280 | */ |
| 281 | readonly status?: typeof OpenAiSchema.MessageStatus.Encoded | null |
| 282 | /** |
| 283 | * A list of annotations that apply to the output text. |
| 284 | */ |
| 285 | readonly annotations?: ReadonlyArray<typeof OpenAiSchema.Annotation.Encoded> | null |
| 286 | /** |
| 287 | * Marks the input text as the end of a reusable prompt prefix. |
| 288 | * |
| 289 | * Requires GPT-5.6 or later. OpenAI may reject requests that use this |
| 290 | * option with earlier models. |
| 291 | */ |
| 292 | readonly promptCacheBreakpoint?: PromptCacheBreakpoint | null |
| 293 | } | null |
| 294 | } |
| 295 | } |
| 296 | |
| 297 | declare module "effect/ai/Response" { |
| 298 | /** |
| 299 | * OpenAI metadata attached to a complete text response part. |
| 300 | * |
| 301 | * @stability unstable |
| 302 | * @category models |
| 303 | * @since 4.0.0 |
| 304 | */ |
| 305 | export interface TextPartMetadata extends ProviderMetadata { |
| 306 | /** |
| 307 | * Provider-specific metadata returned for the text part. |
| 308 | */ |
| 309 | readonly openai?: { |
| 310 | /** |
| 311 | * The OpenAI item ID associated with the text part. |
| 312 | */ |
| 313 | readonly itemId?: string | null |
| 314 | /** |
| 315 | * If the model emits a refusal content part, the refusal explanation |
| 316 | * from the model will be contained in the metadata of an empty text |
| 317 | * part. |
| 318 | */ |
| 319 | readonly refusal?: string | null |
| 320 | /** |
| 321 | * The status of item. |
| 322 | */ |
| 323 | readonly status?: typeof OpenAiSchema.MessageStatus.Encoded | null |
| 324 | /** |
| 325 | * The text content part annotations. |
| 326 | */ |
| 327 | readonly annotations?: ReadonlyArray<typeof OpenAiSchema.Annotation.Encoded> | null |
| 328 | } |
| 329 | } |
| 330 | |
| 331 | /** |
| 332 | * OpenAI metadata emitted when a streamed text part starts. |
| 333 | * |
| 334 | * @stability unstable |
| 335 | * @category models |
| 336 | * @since 4.0.0 |
| 337 | */ |
| 338 | export interface TextStartPartMetadata extends ProviderMetadata { |
| 339 | /** |
| 340 | * Provider-specific metadata returned for the streamed text start. |
| 341 | */ |
| 342 | readonly openai?: { |
| 343 | /** |
| 344 | * The OpenAI item ID associated with the streamed text part. |
| 345 | */ |
| 346 | readonly itemId?: string | null |
| 347 | } | null |
| 348 | } |
| 349 | |
| 350 | /** |
| 351 | * OpenAI metadata emitted when a streamed text part ends. |
| 352 | * |
| 353 | * @stability unstable |
| 354 | * @category models |
| 355 | * @since 4.0.0 |
| 356 | */ |
| 357 | export interface TextEndPartMetadata extends ProviderMetadata { |
| 358 | /** |
| 359 | * Provider-specific metadata returned for the streamed text end. |
| 360 | */ |
| 361 | readonly openai?: { |
| 362 | /** |
| 363 | * The OpenAI item ID associated with the streamed text part. |
| 364 | */ |
| 365 | readonly itemId?: string | null |
| 366 | /** |
| 367 | * The annotations collected for the completed streamed text part. |
| 368 | */ |
| 369 | readonly annotations?: ReadonlyArray<typeof OpenAiSchema.Annotation.Encoded> | null |
| 370 | } | null |
| 371 | } |
| 372 | |
| 373 | /** |
| 374 | * OpenAI metadata attached to a complete reasoning response part. |
| 375 | * |
| 376 | * @stability unstable |
| 377 | * @category models |
| 378 | * @since 4.0.0 |
| 379 | */ |
| 380 | export interface ReasoningPartMetadata extends ProviderMetadata { |
| 381 | /** |
| 382 | * Provider-specific metadata returned for the reasoning part. |
| 383 | */ |
| 384 | readonly openai?: { |
| 385 | /** |
| 386 | * The OpenAI item ID associated with the reasoning part. |
| 387 | */ |
| 388 | readonly itemId?: string | null |
| 389 | /** |
| 390 | * Encrypted reasoning content that can be sent back in later requests. |
| 391 | */ |
| 392 | readonly encryptedContent?: string | null |
| 393 | } | null |
| 394 | } |
| 395 | |
| 396 | /** |
| 397 | * OpenAI metadata emitted when a streamed reasoning part starts. |
| 398 | * |
| 399 | * @stability unstable |
| 400 | * @category models |
| 401 | * @since 4.0.0 |
| 402 | */ |
| 403 | export interface ReasoningStartPartMetadata extends ProviderMetadata { |
| 404 | /** |
| 405 | * Provider-specific metadata returned for the streamed reasoning start. |
| 406 | */ |
| 407 | readonly openai?: { |
| 408 | /** |
| 409 | * The OpenAI item ID associated with the reasoning part. |
| 410 | */ |
| 411 | readonly itemId?: string | null |
| 412 | /** |
| 413 | * Encrypted reasoning content that can be sent back in later requests. |
| 414 | */ |
| 415 | readonly encryptedContent?: string | null |
| 416 | } | null |
| 417 | } |
| 418 | |
| 419 | /** |
| 420 | * OpenAI metadata emitted for a streamed reasoning delta. |
| 421 | * |
| 422 | * @stability unstable |
| 423 | * @category models |
| 424 | * @since 4.0.0 |
| 425 | */ |
| 426 | export interface ReasoningDeltaPartMetadata extends ProviderMetadata { |
| 427 | /** |
| 428 | * Provider-specific metadata returned for the streamed reasoning delta. |
| 429 | */ |
| 430 | readonly openai?: { |
| 431 | /** |
| 432 | * The OpenAI item ID associated with the reasoning part. |
| 433 | */ |
| 434 | readonly itemId?: string | null |
| 435 | } | null |
| 436 | } |
| 437 | |
| 438 | /** |
| 439 | * OpenAI metadata emitted when a streamed reasoning part ends. |
| 440 | * |
| 441 | * @stability unstable |
| 442 | * @category models |
| 443 | * @since 4.0.0 |
| 444 | */ |
| 445 | export interface ReasoningEndPartMetadata extends ProviderMetadata { |
| 446 | /** |
| 447 | * Provider-specific metadata returned for the streamed reasoning end. |
| 448 | */ |
| 449 | readonly openai?: { |
| 450 | /** |
| 451 | * The OpenAI item ID associated with the reasoning part. |
| 452 | */ |
| 453 | readonly itemId?: string | null |
| 454 | /** |
| 455 | * Encrypted reasoning content that can be sent back in later requests. |
| 456 | */ |
| 457 | readonly encryptedContent?: string |
| 458 | } | null |
| 459 | } |
| 460 | |
| 461 | /** |
| 462 | * OpenAI metadata attached to tool-call response parts. |
| 463 | * |
| 464 | * @stability unstable |
| 465 | * @category models |
| 466 | * @since 4.0.0 |
| 467 | */ |
| 468 | export interface ToolCallPartMetadata extends ProviderMetadata { |
| 469 | /** |
| 470 | * Provider-specific metadata returned for the tool call. |
| 471 | */ |
| 472 | readonly openai?: { |
| 473 | /** |
| 474 | * The OpenAI item ID associated with the tool call. |
| 475 | */ |
| 476 | readonly itemId?: string | null |
| 477 | } | null |
| 478 | } |
| 479 | |
| 480 | /** |
| 481 | * OpenAI metadata attached to document source citations. |
| 482 | * |
| 483 | * @stability unstable |
| 484 | * @category models |
| 485 | * @since 4.0.0 |
| 486 | */ |
| 487 | export interface DocumentSourcePartMetadata extends ProviderMetadata { |
| 488 | /** |
| 489 | * Provider-specific citation metadata for the OpenAI Responses API. |
| 490 | */ |
| 491 | readonly openai?: |
| 492 | | { |
| 493 | /** |
| 494 | * Identifies a citation to an uploaded file. |
| 495 | */ |
| 496 | readonly type: "file_citation" |
| 497 | /** |
| 498 | * The index of the file in the list of files. |
| 499 | */ |
| 500 | readonly index: number |
| 501 | /** |
| 502 | * The ID of the file. |
| 503 | */ |
| 504 | readonly fileId: string |
| 505 | } |
| 506 | | { |
| 507 | /** |
| 508 | * Identifies a citation to a generated file path. |
| 509 | */ |
| 510 | readonly type: "file_path" |
| 511 | /** |
| 512 | * The index of the file in the list of files. |
| 513 | */ |
| 514 | readonly index: number |
| 515 | /** |
| 516 | * The ID of the file. |
| 517 | */ |
| 518 | readonly fileId: string |
| 519 | } |
| 520 | | { |
| 521 | /** |
| 522 | * Identifies a citation to a file inside a container. |
| 523 | */ |
| 524 | readonly type: "container_file_citation" |
| 525 | /** |
| 526 | * The ID of the file. |
| 527 | */ |
| 528 | readonly fileId: string |
| 529 | /** |
| 530 | * The ID of the container file. |
| 531 | */ |
| 532 | readonly containerId: string |
| 533 | } |
| 534 | | null |
| 535 | } |
| 536 | |
| 537 | /** |
| 538 | * OpenAI metadata attached to URL source citations. |
| 539 | * |
| 540 | * @stability unstable |
| 541 | * @category models |
| 542 | * @since 4.0.0 |
| 543 | */ |
| 544 | export interface UrlSourcePartMetadata extends ProviderMetadata { |
| 545 | /** |
| 546 | * Provider-specific URL citation metadata for the OpenAI Responses API. |
| 547 | */ |
| 548 | readonly openai?: { |
| 549 | /** |
| 550 | * Identifies a citation to a URL. |
| 551 | */ |
| 552 | readonly type: "url_citation" |
| 553 | /** |
| 554 | * The index of the first character of the URL citation in the message. |
| 555 | */ |
| 556 | readonly startIndex: number |
| 557 | /** |
| 558 | * The index of the last character of the URL citation in the message. |
| 559 | */ |
| 560 | readonly endIndex: number |
| 561 | } | null |
| 562 | } |
| 563 | |
| 564 | /** |
| 565 | * OpenAI metadata attached to finish response parts. |
| 566 | * |
| 567 | * @stability unstable |
| 568 | * @category models |
| 569 | * @since 4.0.0 |
| 570 | */ |
| 571 | export interface FinishPartMetadata extends ProviderMetadata { |
| 572 | /** |
| 573 | * Provider-specific metadata returned when generation finishes. |
| 574 | */ |
| 575 | readonly openai?: { |
| 576 | /** |
| 577 | * The service tier reported by OpenAI for the response. |
| 578 | */ |
| 579 | readonly serviceTier?: "default" | "auto" | "flex" | "scale" | "priority" | null |
| 580 | /** |
| 581 | * Prompt cache diagnostics for `prompt_cache_options.comparison_response_id`. |
| 582 | */ |
| 583 | readonly promptCacheDiagnostics?: OpenAiSchema.PromptCacheDiagnostics |
| 584 | } | null |
| 585 | } |
| 586 | } |
| 587 | |
| 588 | // ============================================================================= |
| 589 | // Language Model |
| 590 | // ============================================================================= |
| 591 | |
| 592 | /** |
| 593 | * Creates an OpenAI model descriptor that can be provided with |
| 594 | * `Effect.provide`. |
| 595 | * |
| 596 | * **When to use** |
| 597 | * |
| 598 | * Use when you want an OpenAI language model value that carries provider and |
| 599 | * model metadata and can be supplied directly to an Effect program. |
| 600 | * |
| 601 | * @see {@link layer} for creating a `LanguageModel.LanguageModel` layer directly |
| 602 | * @see {@link make} for constructing the language model service effectfully |
| 603 | * |
| 604 | * @stability unstable |
| 605 | * @category constructors |
| 606 | * @since 4.0.0 |
| 607 | */ |
| 608 | export const model = ( |
| 609 | model: (string & {}) | Model, |
| 610 | config?: Omit<typeof Config.Service, "model"> |
| 611 | ): AiModel.Model<"openai", LanguageModel.LanguageModel, OpenAiClient> => |
| 612 | AiModel.make("openai", model, layer({ model, config })) |
| 613 | |
| 614 | // TODO |
| 615 | // /** |
| 616 | // * @since 4.0.0 |
| 617 | // * @category constructors |
| 618 | // */ |
| 619 | // export const modelWithTokenizer = ( |
| 620 | // model: (string & {}) | Model, |
| 621 | // config?: Omit<typeof Config.Service, "model"> |
| 622 | // ): AiModel.Model<"openai", LanguageModel.LanguageModel | Tokenizer.Tokenizer, OpenAiClient> => |
| 623 | // AiModel.make("openai", model, layerWithTokenizer({ model, config })) |
| 624 | |
| 625 | /** |
| 626 | * Creates an OpenAI `LanguageModel` service from a model identifier and |
| 627 | * optional request defaults. |
| 628 | * |
| 629 | * **When to use** |
| 630 | * |
| 631 | * Use to construct an OpenAI Responses API language model service backed by |
| 632 | * `OpenAiClient`. |
| 633 | * |
| 634 | * **Details** |
| 635 | * |
| 636 | * The returned effect requires `OpenAiClient`. Request defaults from the |
| 637 | * `config` option are merged with any `Config` service in the context, with |
| 638 | * context values taking precedence. The service supports both `generateText` |
| 639 | * and `streamText`. |
| 640 | * |
| 641 | * @see {@link layer} for providing the service as a `Layer` |
| 642 | * @see {@link model} for creating a model descriptor for `Effect.provide` |
| 643 | * |
| 644 | * @stability unstable |
| 645 | * @category constructors |
| 646 | * @since 4.0.0 |
| 647 | */ |
| 648 | export const make = Effect.fnUntraced(function*({ model, config: providerConfig }: { |
| 649 | readonly model: (string & {}) | Model |
| 650 | readonly config?: Omit<typeof Config.Service, "model"> | undefined |
| 651 | }): Effect.fn.Return<LanguageModel.LanguageModel, never, OpenAiClient> { |
| 652 | const client = yield* OpenAiClient |
| 653 | |
| 654 | const makeConfig = Effect.gen(function*() { |
| 655 | const services = yield* Effect.context<never>() |
| 656 | return { model, ...providerConfig, ...Context.getOrUndefined(services, Config) } |
| 657 | }) |
| 658 | |
| 659 | const makeRequest = Effect.fnUntraced( |
| 660 | function*<Tools extends ReadonlyArray<Tool.Any>>({ config, options, toolNameMapper }: { |
| 661 | readonly config: typeof Config.Service |
| 662 | readonly options: LanguageModel.ProviderOptions |
| 663 | readonly toolNameMapper: Tool.NameMapper<Tools> |
| 664 | }): Effect.fn.Return<typeof OpenAiSchema.CreateResponse.Encoded, AiError.AiError> { |
| 665 | const include = new Set<typeof OpenAiSchema.IncludeEnum.Encoded>() |
| 666 | const capabilities = getModelCapabilities(config.model as string) |
| 667 | const messages = yield* prepareMessages({ |
| 668 | config, |
| 669 | options, |
| 670 | capabilities, |
| 671 | include, |
| 672 | toolNameMapper |
| 673 | }) |
| 674 | const { toolChoice, tools } = yield* prepareTools({ |
| 675 | config, |
| 676 | options, |
| 677 | toolNameMapper |
| 678 | }) |
| 679 | const responseFormat = yield* prepareResponseFormat({ |
| 680 | config, |
| 681 | options |
| 682 | }) |
| 683 | const { |
| 684 | fileIdPrefixes: _fip, |
| 685 | strictJsonSchema: _sjs, |
| 686 | useItemReferences: _uir, |
| 687 | ...apiConfig |
| 688 | } = config |
| 689 | const request: Mutable<typeof OpenAiSchema.CreateResponse.Encoded> = { |
| 690 | ...apiConfig, |
| 691 | input: messages, |
| 692 | include: include.size > 0 ? Array.from(include) : undefined, |
| 693 | text: { |
| 694 | verbosity: config.text?.verbosity ?? undefined, |
| 695 | format: responseFormat |
| 696 | } |
| 697 | } |
| 698 | if (tools) request.tools = tools |
| 699 | if (toolChoice) request.tool_choice = toolChoice |
| 700 | if (options.previousResponseId) request.previous_response_id = options.previousResponseId |
| 701 | return request |
| 702 | } |
| 703 | ) |
| 704 | |
| 705 | return yield* LanguageModel.make({ |
| 706 | codecTransformer: toCodecOpenAI, |
| 707 | generateText: Effect.fnUntraced( |
| 708 | function*(options) { |
| 709 | const config = yield* makeConfig |
| 710 | const toolNameMapper = new Tool.NameMapper(options.tools) |
| 711 | const request = yield* makeRequest({ config, options, toolNameMapper }) |
| 712 | annotateRequest(options.span, request) |
| 713 | const [rawResponse, response] = yield* client.createResponse(request) |
| 714 | annotateResponse(options.span, rawResponse) |
| 715 | return yield* makeResponse({ |
| 716 | options, |
| 717 | rawResponse, |
| 718 | response, |
| 719 | toolNameMapper |
| 720 | }) |
| 721 | } |
| 722 | ), |
| 723 | streamText: Effect.fnUntraced( |
| 724 | function*(options) { |
| 725 | const config = yield* makeConfig |
| 726 | const toolNameMapper = new Tool.NameMapper(options.tools) |
| 727 | const request = yield* makeRequest({ config, options, toolNameMapper }) |
| 728 | annotateRequest(options.span, request) |
| 729 | const [response, stream] = yield* client.createResponseStream(request) |
| 730 | return yield* makeStreamResponse({ |
| 731 | stream, |
| 732 | response, |
| 733 | config, |
| 734 | options, |
| 735 | toolNameMapper |
| 736 | }) |
| 737 | }, |
| 738 | (effect, options) => |
| 739 | effect.pipe( |
| 740 | Stream.unwrap, |
| 741 | Stream.map((response) => { |
| 742 | annotateStreamResponse(options.span, response) |
| 743 | return response |
| 744 | }) |
| 745 | ) |
| 746 | ) |
| 747 | }) |
| 748 | }) |
| 749 | |
| 750 | /** |
| 751 | * Creates a layer that provides the OpenAI `LanguageModel.LanguageModel` |
| 752 | * service. |
| 753 | * |
| 754 | * **When to use** |
| 755 | * |
| 756 | * Use when composing application layers and you want OpenAI to satisfy |
| 757 | * `LanguageModel.LanguageModel` while supplying `OpenAiClient` from another |
| 758 | * layer. |
| 759 | * |
| 760 | * **Details** |
| 761 | * |
| 762 | * The `config` option supplies request defaults for the selected model. Scoped |
| 763 | * values from `withConfigOverride` are merged when each request is built and |
| 764 | * take precedence over these defaults. |
| 765 | * |
| 766 | * @see {@link make} for constructing the language model service effectfully |
| 767 | * @see {@link model} for creating a model descriptor for `Effect.provide` |
| 768 | * @see {@link withConfigOverride} for scoped request configuration overrides |
| 769 | * |
| 770 | * @stability unstable |
| 771 | * @category layers |
| 772 | * @since 4.0.0 |
| 773 | */ |
| 774 | export const layer = (options: { |
| 775 | readonly model: (string & {}) | Model |
| 776 | readonly config?: Omit<typeof Config.Service, "model"> | undefined |
| 777 | }): Layer.Layer<LanguageModel.LanguageModel, never, OpenAiClient> => |
| 778 | Layer.effect(LanguageModel.LanguageModel, make(options)) |
| 779 | |
| 780 | /** |
| 781 | * Provides scoped config overrides for OpenAI language model operations. |
| 782 | * |
| 783 | * **When to use** |
| 784 | * |
| 785 | * Use to apply OpenAI Responses API config overrides around one or more |
| 786 | * language model operations without changing the defaults passed to `model`, |
| 787 | * `make`, or `layer`. |
| 788 | * |
| 789 | * **Details** |
| 790 | * |
| 791 | * The override is dual, so it can be used in pipe form or as |
| 792 | * `withConfigOverride(effect, overrides)`. Overrides are merged with any |
| 793 | * existing `Config` service in the current context, and the override values take |
| 794 | * precedence. |
| 795 | * |
| 796 | * @see {@link Config} for the scoped configuration service consumed by this function |
| 797 | * |
| 798 | * @stability unstable |
| 799 | * @category configuration |
| 800 | * @since 4.0.0 |
| 801 | */ |
| 802 | export const withConfigOverride: { |
| 803 | (overrides: typeof Config.Service): <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<A, E, Exclude<R, Config>> |
| 804 | <A, E, R>(self: Effect.Effect<A, E, R>, overrides: typeof Config.Service): Effect.Effect<A, E, Exclude<R, Config>> |
| 805 | } = dual< |
| 806 | ( |
| 807 | overrides: typeof Config.Service |
| 808 | ) => <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<A, E, Exclude<R, Config>>, |
| 809 | <A, E, R>(self: Effect.Effect<A, E, R>, overrides: typeof Config.Service) => Effect.Effect<A, E, Exclude<R, Config>> |
| 810 | >(2, (self, overrides) => |
| 811 | Effect.flatMap( |
| 812 | Effect.serviceOption(Config), |
| 813 | (config) => |
| 814 | Effect.provideService(self, Config, { |
| 815 | ...(config._tag === "Some" ? config.value : {}), |
| 816 | ...overrides |
| 817 | }) |
| 818 | )) |
| 819 | |
| 820 | // ============================================================================= |
| 821 | // Prompt Conversion |
| 822 | // ============================================================================= |
| 823 | |
| 824 | const getSystemMessageMode = (model: string): "system" | "developer" => |
| 825 | model.startsWith("o") || |
| 826 | model.startsWith("gpt-5") || |
| 827 | model.startsWith("codex-") || |
| 828 | model.startsWith("computer-use") |
| 829 | ? "developer" |
| 830 | : "system" |
| 831 | |
| 832 | const prepareMessages = Effect.fnUntraced( |
| 833 | function*<Tools extends ReadonlyArray<Tool.Any>>({ |
| 834 | config, |
| 835 | options, |
| 836 | capabilities, |
| 837 | include, |
| 838 | toolNameMapper |
| 839 | }: { |
| 840 | readonly config: typeof Config.Service |
| 841 | readonly options: LanguageModel.ProviderOptions |
| 842 | readonly include: Set<typeof OpenAiSchema.IncludeEnum.Encoded> |
| 843 | readonly capabilities: ModelCapabilities |
| 844 | readonly toolNameMapper: Tool.NameMapper<Tools> |
| 845 | }): Effect.fn.Return<ReadonlyArray<typeof OpenAiSchema.InputItem.Encoded>, AiError.AiError> { |
| 846 | const processedApprovalIds = new Set<string>() |
| 847 | const websocketMode = Option.isSome(yield* Effect.serviceOption(OpenAiSocket)) |
| 848 | |
| 849 | const hasConversation = Predicate.isNotNullish(config.conversation) |
| 850 | const useItemReferences = config.store === true && |
| 851 | config.useItemReferences !== false && |
| 852 | options.incrementalFallback !== true |
| 853 | |
| 854 | // Provider-Defined Tools |
| 855 | const applyPatchTool = options.tools.find((tool): tool is ReturnType<typeof OpenAiTool.ApplyPatch> => |
| 856 | Tool.isProviderDefined(tool) && tool.name === "OpenAiApplyPatch" |
| 857 | ) |
| 858 | const codeInterpreterTool = options.tools.find((tool): tool is ReturnType<typeof OpenAiTool.CodeInterpreter> => |
| 859 | Tool.isProviderDefined(tool) && tool.name === "OpenAiCodeInterpreter" |
| 860 | ) |
| 861 | const shellTool = options.tools.find((tool): tool is ReturnType<typeof OpenAiTool.Shell> => |
| 862 | Tool.isProviderDefined(tool) && tool.name === "OpenAiShell" |
| 863 | ) |
| 864 | const localShellTool = options.tools.find((tool): tool is ReturnType<typeof OpenAiTool.LocalShell> => |
| 865 | Tool.isProviderDefined(tool) && tool.name === "OpenAiLocalShell" |
| 866 | ) |
| 867 | const webSearchTool = options.tools.find((tool): tool is ReturnType<typeof OpenAiTool.WebSearch> => |
| 868 | Tool.isProviderDefined(tool) && tool.name === "OpenAiWebSearch" |
| 869 | ) |
| 870 | const webSearchPreviewTool = options.tools.find((tool): tool is ReturnType<typeof OpenAiTool.WebSearchPreview> => |
| 871 | Tool.isProviderDefined(tool) && tool.name === "OpenAiWebSearchPreview" |
| 872 | ) |
| 873 | |
| 874 | // Handle Included Features |
| 875 | if (Predicate.isNotUndefined(config.top_logprobs)) { |
| 876 | include.add("message.output_text.logprobs") |
| 877 | } |
| 878 | if ((websocketMode || !useItemReferences) && capabilities.isReasoningModel) { |
| 879 | include.add("reasoning.encrypted_content") |
| 880 | } |
| 881 | if (codeInterpreterTool) { |
| 882 | include.add("code_interpreter_call.outputs") |
| 883 | } |
| 884 | if (webSearchTool || webSearchPreviewTool) { |
| 885 | include.add("web_search_call.action.sources") |
| 886 | } |
| 887 | |
| 888 | const messages: Array<typeof OpenAiSchema.InputItem.Encoded> = [] |
| 889 | const prompt = options.incrementalPrompt ?? options.prompt |
| 890 | |
| 891 | for (const message of prompt.content) { |
| 892 | switch (message.role) { |
| 893 | case "system": { |
| 894 | messages.push({ |
| 895 | role: getSystemMessageMode(config.model as string), |
| 896 | content: [{ |
| 897 | type: "input_text", |
| 898 | text: message.content, |
| 899 | ...getPromptCacheBreakpoint(message) |
| 900 | }] |
| 901 | }) |
| 902 | break |
| 903 | } |
| 904 | |
| 905 | case "user": { |
| 906 | const content: Array<typeof OpenAiSchema.InputContent.Encoded> = [] |
| 907 | |
| 908 | for (let index = 0; index < message.content.length; index++) { |
| 909 | const part = message.content[index] |
| 910 | |
| 911 | switch (part.type) { |
| 912 | case "text": { |
| 913 | content.push({ |
| 914 | type: "input_text", |
| 915 | text: part.text, |
| 916 | ...getPromptCacheBreakpoint(part) |
| 917 | }) |
| 918 | break |
| 919 | } |
| 920 | |
| 921 | case "file": { |
| 922 | if (part.mediaType.startsWith("image/")) { |
| 923 | const detail = getImageDetail(part) |
| 924 | const mediaType = part.mediaType === "image/*" ? "image/jpeg" : part.mediaType |
| 925 | |
| 926 | if (typeof part.data === "string" && isFileId(part.data, config)) { |
| 927 | content.push({ type: "input_image", file_id: part.data, detail }) |
| 928 | } else { |
| 929 | const imageUrl = part.data instanceof URL |
| 930 | ? part.data.toString() |
| 931 | : part.data instanceof Uint8Array |
| 932 | ? `data:${mediaType};base64,${Base64.encode(part.data)}` |
| 933 | : /^(data:|https?:\/\/)/i.test(part.data) |
| 934 | ? part.data |
| 935 | : `data:${mediaType};base64,${part.data}` |
| 936 | content.push({ type: "input_image", image_url: imageUrl, detail }) |
| 937 | } |
| 938 | } else if (part.mediaType === "application/pdf") { |
| 939 | if (typeof part.data === "string" && isFileId(part.data, config)) { |
| 940 | content.push({ type: "input_file", file_id: part.data }) |
| 941 | } |
| 942 | |
| 943 | if (part.data instanceof URL) { |
| 944 | content.push({ type: "input_file", file_url: part.data.toString() }) |
| 945 | } |
| 946 | |
| 947 | if (part.data instanceof Uint8Array) { |
| 948 | const base64 = Base64.encode(part.data) |
| 949 | const fileName = part.fileName ?? `part-${index}.pdf` |
| 950 | const fileData = `data:application/pdf;base64,${base64}` |
| 951 | content.push({ type: "input_file", filename: fileName, file_data: fileData }) |
| 952 | } |
| 953 | } else { |
| 954 | return yield* AiError.make({ |
| 955 | module: "OpenAiLanguageModel", |
| 956 | method: "prepareMessages", |
| 957 | reason: new AiError.InvalidRequestError({ |
| 958 | description: `Detected unsupported media type for file: '${part.mediaType}'` |
| 959 | }) |
| 960 | }) |
| 961 | } |
| 962 | } |
| 963 | } |
| 964 | } |
| 965 | |
| 966 | messages.push({ role: "user", content }) |
| 967 | |
| 968 | break |
| 969 | } |
| 970 | |
| 971 | case "assistant": { |
| 972 | const reasoningMessages: Record<string, DeepMutable<typeof OpenAiSchema.ReasoningItem.Encoded>> = Object |
| 973 | .create(null) |
| 974 | |
| 975 | const providerExecutedParts = message.content.filter((part) => |
| 976 | (part.type === "tool-call" || part.type === "tool-result") && part.providerExecuted |
| 977 | ) |
| 978 | const unreplayableProviderItem = (name: string, id: string) => |
| 979 | AiError.make({ |
| 980 | module: "OpenAiLanguageModel", |
| 981 | method: "prepareMessages", |
| 982 | reason: new AiError.InvalidRequestError({ |
| 983 | description: `Cannot replay provider-executed tool item '${name}' ('${id}') losslessly` |
| 984 | }) |
| 985 | }) |
| 986 | |
| 987 | for (const part of message.content) { |
| 988 | switch (part.type) { |
| 989 | case "text": { |
| 990 | const id = getItemId(part) |
| 991 | |
| 992 | // When in conversation mode, skip items that already exist in the |
| 993 | // conversation context to avoid "Duplicate item found" errors |
| 994 | if (hasConversation && Predicate.isNotNull(id)) { |
| 995 | break |
| 996 | } |
| 997 | |
| 998 | if (useItemReferences && Predicate.isNotNull(id)) { |
| 999 | messages.push({ type: "item_reference", id }) |
| 1000 | break |
| 1001 | } |
| 1002 | |
| 1003 | messages.push({ |
| 1004 | id: id!, |
| 1005 | type: "message", |
| 1006 | role: "assistant", |
| 1007 | status: part.options.openai?.status ?? "completed", |
| 1008 | content: [{ |
| 1009 | type: "output_text", |
| 1010 | text: part.text, |
| 1011 | annotations: part.options.openai?.annotations ?? [], |
| 1012 | logprobs: [] |
| 1013 | }] |
| 1014 | }) |
| 1015 | |
| 1016 | break |
| 1017 | } |
| 1018 | |
| 1019 | case "reasoning": { |
| 1020 | const id = getItemId(part) |
| 1021 | const encryptedContent = getEncryptedContent(part) |
| 1022 | |
| 1023 | if (hasConversation && Predicate.isNotNull(id)) { |
| 1024 | break |
| 1025 | } |
| 1026 | |
| 1027 | if (Predicate.isNotNull(id)) { |
| 1028 | const message = reasoningMessages[id] |
| 1029 | |
| 1030 | if (useItemReferences) { |
| 1031 | // Use item references to refer to reasoning (single reference) |
| 1032 | // when the first part is encountered |
| 1033 | if (Predicate.isUndefined(message)) { |
| 1034 | messages.push({ type: "item_reference", id }) |
| 1035 | |
| 1036 | // Store unused reasoning message to mark its id as used |
| 1037 | reasoningMessages[id] = { |
| 1038 | type: "reasoning", |
| 1039 | id, |
| 1040 | summary: [] |
| 1041 | } |
| 1042 | } |
| 1043 | } else { |
| 1044 | const summaryParts: Array<typeof OpenAiSchema.SummaryTextContent.Encoded> = [] |
| 1045 | |
| 1046 | if (part.text.length > 0) { |
| 1047 | summaryParts.push({ type: "summary_text", text: part.text }) |
| 1048 | } |
| 1049 | |
| 1050 | if (Predicate.isUndefined(message)) { |
| 1051 | reasoningMessages[id] = { |
| 1052 | type: "reasoning", |
| 1053 | id, |
| 1054 | summary: summaryParts, |
| 1055 | ...(Predicate.isNotNull(encryptedContent) |
| 1056 | ? { encrypted_content: encryptedContent } |
| 1057 | : undefined) |
| 1058 | } |
| 1059 | |
| 1060 | messages.push(reasoningMessages[id]) |
| 1061 | } else { |
| 1062 | message.summary.push(...summaryParts) |
| 1063 | |
| 1064 | // Update encrypted content to enable setting it in the |
| 1065 | // last summary part |
| 1066 | if (Predicate.isNotNull(encryptedContent)) { |
| 1067 | message.encrypted_content = encryptedContent |
| 1068 | } |
| 1069 | } |
| 1070 | } |
| 1071 | } |
| 1072 | |
| 1073 | break |
| 1074 | } |
| 1075 | |
| 1076 | case "tool-call": { |
| 1077 | const id = getItemId(part) |
| 1078 | const status = getStatus(part) |
| 1079 | |
| 1080 | if (hasConversation && Predicate.isNotNull(id)) { |
| 1081 | break |
| 1082 | } |
| 1083 | |
| 1084 | if (useItemReferences && Predicate.isNotNull(id)) { |
| 1085 | messages.push({ type: "item_reference", id }) |
| 1086 | break |
| 1087 | } |
| 1088 | |
| 1089 | if (part.providerExecuted) { |
| 1090 | if ( |
| 1091 | config.store !== true && options.incrementalFallback !== true |
| 1092 | ) { |
| 1093 | break |
| 1094 | } |
| 1095 | const result = providerExecutedParts.find((candidate) => |
| 1096 | candidate.type === "tool-result" && candidate.id === part.id && candidate.name === part.name |
| 1097 | ) |
| 1098 | if (Predicate.isUndefined(result) || result.type !== "tool-result") { |
| 1099 | return yield* unreplayableProviderItem(part.name, part.id) |
| 1100 | } |
| 1101 | if ( |
| 1102 | Predicate.hasProperty(result.result, "type") && |
| 1103 | result.result.type === "execution-denied" |
| 1104 | ) { |
| 1105 | break |
| 1106 | } |
| 1107 | |
| 1108 | const itemId = getItemId(part) ?? getItemId(result) ?? part.id |
| 1109 | switch (part.name) { |
| 1110 | case "OpenAiWebSearch": |
| 1111 | case "OpenAiWebSearchPreview": { |
| 1112 | if (!Predicate.hasProperty(result.result, "status")) { |
| 1113 | return yield* unreplayableProviderItem(part.name, part.id) |
| 1114 | } |
| 1115 | messages.push({ |
| 1116 | type: "web_search_call", |
| 1117 | id: itemId, |
| 1118 | ...(Predicate.hasProperty(result.result, "action") |
| 1119 | ? { action: result.result.action } |
| 1120 | : undefined), |
| 1121 | status: result.result.status as string |
| 1122 | }) |
| 1123 | break |
| 1124 | } |
| 1125 | case "OpenAiCodeInterpreter": { |
| 1126 | if ( |
| 1127 | !Predicate.hasProperty(part.params, "code") || |
| 1128 | !Predicate.hasProperty(part.params, "container_id") || |
| 1129 | !Predicate.hasProperty(result.result, "status") || |
| 1130 | !Predicate.hasProperty(result.result, "outputs") |
| 1131 | ) { |
| 1132 | return yield* unreplayableProviderItem(part.name, part.id) |
| 1133 | } |
| 1134 | messages.push({ |
| 1135 | type: "code_interpreter_call", |
| 1136 | id: itemId, |
| 1137 | code: part.params.code as string | null, |
| 1138 | container_id: part.params.container_id as string, |
| 1139 | status: result.result.status as any, |
| 1140 | outputs: result.result.outputs as any |
| 1141 | }) |
| 1142 | break |
| 1143 | } |
| 1144 | case "OpenAiFileSearch": { |
| 1145 | if ( |
| 1146 | !Predicate.hasProperty(result.result, "status") || |
| 1147 | !Predicate.hasProperty(result.result, "queries") || |
| 1148 | !Predicate.hasProperty(result.result, "results") |
| 1149 | ) { |
| 1150 | return yield* unreplayableProviderItem(part.name, part.id) |
| 1151 | } |
| 1152 | messages.push({ |
| 1153 | type: "file_search_call", |
| 1154 | id: itemId, |
| 1155 | status: result.result.status as string, |
| 1156 | queries: result.result.queries as Array<string>, |
| 1157 | results: result.result.results |
| 1158 | }) |
| 1159 | break |
| 1160 | } |
| 1161 | case "OpenAiImageGeneration": { |
| 1162 | if (!Predicate.hasProperty(result.result, "result")) { |
| 1163 | return yield* unreplayableProviderItem(part.name, part.id) |
| 1164 | } |
| 1165 | messages.push({ |
| 1166 | type: "image_generation_call", |
| 1167 | id: itemId, |
| 1168 | result: result.result.result as string | null, |
| 1169 | status: (Predicate.hasProperty(result.result, "status") |
| 1170 | ? result.result.status |
| 1171 | : "completed") as any |
| 1172 | }) |
| 1173 | break |
| 1174 | } |
| 1175 | default: { |
| 1176 | return yield* unreplayableProviderItem(part.name, part.id) |
| 1177 | } |
| 1178 | } |
| 1179 | break |
| 1180 | } |
| 1181 | |
| 1182 | const toolName = toolNameMapper.getProviderName(part.name) |
| 1183 | |
| 1184 | if (Predicate.isNotUndefined(localShellTool) && toolName === "local_shell") { |
| 1185 | const params = yield* Schema.decodeUnknownEffect(localShellTool.parametersSchema)(part.params).pipe( |
| 1186 | Effect.mapError((error) => |
| 1187 | AiError.make({ |
| 1188 | module: "OpenAiLanguageModel", |
| 1189 | method: "prepareMessages", |
| 1190 | reason: new AiError.ToolParameterValidationError({ |
| 1191 | toolName: "local_shell", |
| 1192 | description: error.message |
| 1193 | }) |
| 1194 | }) |
| 1195 | ) |
| 1196 | ) |
| 1197 | |
| 1198 | messages.push({ |
| 1199 | id: id!, |
| 1200 | type: "local_shell_call", |
| 1201 | call_id: part.id, |
| 1202 | status: status ?? "completed", |
| 1203 | action: params.action |
| 1204 | }) |
| 1205 | |
| 1206 | break |
| 1207 | } |
| 1208 | |
| 1209 | if (Predicate.isNotUndefined(shellTool) && toolName === "shell") { |
| 1210 | const params = yield* Schema.decodeUnknownEffect(shellTool.parametersSchema)(part.params).pipe( |
| 1211 | Effect.mapError((error) => |
| 1212 | AiError.make({ |
| 1213 | module: "OpenAiLanguageModel", |
| 1214 | method: "prepareMessages", |
| 1215 | reason: new AiError.ToolParameterValidationError({ |
| 1216 | toolName: "shell", |
| 1217 | description: error.message |
| 1218 | }) |
| 1219 | }) |
| 1220 | ) |
| 1221 | ) |
| 1222 | |
| 1223 | messages.push({ |
| 1224 | id: id!, |
| 1225 | type: "shell_call", |
| 1226 | call_id: part.id, |
| 1227 | status: status ?? "completed", |
| 1228 | action: params.action |
| 1229 | }) |
| 1230 | |
| 1231 | break |
| 1232 | } |
| 1233 | |
| 1234 | messages.push({ |
| 1235 | type: "function_call", |
| 1236 | name: toolName, |
| 1237 | call_id: part.id, |
| 1238 | arguments: JSON.stringify(part.params), |
| 1239 | ...(Predicate.isNotNull(id) ? { id } : {}), |
| 1240 | ...(Predicate.isNotNull(status) ? { status } : {}) |
| 1241 | }) |
| 1242 | |
| 1243 | break |
| 1244 | } |
| 1245 | |
| 1246 | // Assistant tool-result parts are always provider executed |
| 1247 | case "tool-result": { |
| 1248 | // Skip execution denied results - these have no corresponding |
| 1249 | // item in OpenAI's store |
| 1250 | if ( |
| 1251 | Predicate.hasProperty(part.result, "type") && |
| 1252 | part.result.type === "execution-denied" |
| 1253 | ) { |
| 1254 | break |
| 1255 | } |
| 1256 | |
| 1257 | if (hasConversation) { |
| 1258 | break |
| 1259 | } |
| 1260 | |
| 1261 | if (useItemReferences) { |
| 1262 | const id = getItemId(part) ?? part.id |
| 1263 | messages.push({ type: "item_reference", id }) |
| 1264 | } else if ( |
| 1265 | part.providerExecuted && |
| 1266 | (config.store === true || options.incrementalFallback === true) |
| 1267 | ) { |
| 1268 | const call = providerExecutedParts.find((candidate) => |
| 1269 | candidate.type === "tool-call" && candidate.id === part.id && candidate.name === part.name |
| 1270 | ) |
| 1271 | if (Predicate.isUndefined(call)) { |
| 1272 | return yield* unreplayableProviderItem(part.name, part.id) |
| 1273 | } |
| 1274 | } |
| 1275 | } |
| 1276 | } |
| 1277 | } |
| 1278 | |
| 1279 | break |
| 1280 | } |
| 1281 | |
| 1282 | case "tool": { |
| 1283 | for (const part of message.content) { |
| 1284 | if (part.type === "tool-approval-response") { |
| 1285 | if (processedApprovalIds.has(part.approvalId)) { |
| 1286 | continue |
| 1287 | } |
| 1288 | |
| 1289 | processedApprovalIds.add(part.approvalId) |
| 1290 | |
| 1291 | if (useItemReferences) { |
| 1292 | messages.push({ type: "item_reference", id: part.approvalId }) |
| 1293 | } |
| 1294 | |
| 1295 | messages.push({ |
| 1296 | type: "mcp_approval_response", |
| 1297 | approval_request_id: part.approvalId, |
| 1298 | approve: part.approved |
| 1299 | } as any) |
| 1300 | |
| 1301 | continue |
| 1302 | } |
| 1303 | |
| 1304 | // Skip execution-denied results that already have an approvalId - |
| 1305 | // this indicates that the part was already handled via tool-approval-response |
| 1306 | if ( |
| 1307 | Predicate.hasProperty(part.result, "type") && |
| 1308 | part.result.type === "execution-denied" |
| 1309 | ) { |
| 1310 | if (Predicate.isNotNullish(part.options.openai?.approvalId)) { |
| 1311 | continue |
| 1312 | } |
| 1313 | } |
| 1314 | |
| 1315 | const id = getItemId(part) ?? part.id |
| 1316 | const status = getStatus(part) |
| 1317 | const toolName = toolNameMapper.getProviderName(part.name) |
| 1318 | |
| 1319 | if (Predicate.isNotUndefined(applyPatchTool) && toolName === "apply_patch") { |
| 1320 | messages.push({ |
| 1321 | id, |
| 1322 | type: "apply_patch_call_output", |
| 1323 | call_id: part.id, |
| 1324 | ...(part.result as any) |
| 1325 | }) |
| 1326 | continue |
| 1327 | } |
| 1328 | |
| 1329 | if (Predicate.isNotUndefined(shellTool) && toolName === "shell") { |
| 1330 | messages.push({ |
| 1331 | id, |
| 1332 | type: "shell_call_output", |
| 1333 | call_id: part.id, |
| 1334 | output: part.result as any, |
| 1335 | ...(Predicate.isNotNull(status) ? { status } : {}) |
| 1336 | }) |
| 1337 | continue |
| 1338 | } |
| 1339 | |
| 1340 | if (Predicate.isNotUndefined(localShellTool) && toolName === "local_shell") { |
| 1341 | messages.push({ |
| 1342 | id, |
| 1343 | type: "local_shell_call_output", |
| 1344 | call_id: part.id, |
| 1345 | output: part.result as any, |
| 1346 | ...(Predicate.isNotNull(status) ? { status } : {}) |
| 1347 | }) |
| 1348 | continue |
| 1349 | } |
| 1350 | |
| 1351 | messages.push({ |
| 1352 | type: "function_call_output", |
| 1353 | call_id: part.id, |
| 1354 | output: typeof part.result === "string" ? part.result : JSON.stringify(part.result), |
| 1355 | ...(Predicate.isNotNull(status) ? { status } : {}) |
| 1356 | }) |
| 1357 | } |
| 1358 | |
| 1359 | break |
| 1360 | } |
| 1361 | } |
| 1362 | } |
| 1363 | |
| 1364 | return messages |
| 1365 | } |
| 1366 | ) |
| 1367 | |
| 1368 | // ============================================================================= |
| 1369 | // HTTP Details |
| 1370 | // ============================================================================= |
| 1371 | |
| 1372 | const buildHttpRequestDetails = ( |
| 1373 | request: HttpClientRequest.HttpClientRequest |
| 1374 | ): typeof Response.HttpRequestDetails.Type => ({ |
| 1375 | method: request.method, |
| 1376 | url: request.url, |
| 1377 | urlParams: Array.from(request.urlParams), |
| 1378 | hash: Option.getOrUndefined(request.hash), |
| 1379 | headers: Redactable.redact(request.headers) as Record<string, string> |
| 1380 | }) |
| 1381 | |
| 1382 | const buildHttpResponseDetails = ( |
| 1383 | response: HttpClientResponse.HttpClientResponse |
| 1384 | ): typeof Response.HttpResponseDetails.Type => ({ |
| 1385 | status: response.status, |
| 1386 | headers: Redactable.redact(response.headers) as Record<string, string> |
| 1387 | }) |
| 1388 | |
| 1389 | // ============================================================================= |
| 1390 | // Response Conversion |
| 1391 | // ============================================================================= |
| 1392 | |
| 1393 | type ResponseStreamEvent = typeof OpenAiSchema.ResponseStreamEvent.Type |
| 1394 | |
| 1395 | type KnownResponseStreamEventType = |
| 1396 | | "response.created" |
| 1397 | | "response.completed" |
| 1398 | | "response.incomplete" |
| 1399 | | "response.failed" |
| 1400 | | "response.output_item.added" |
| 1401 | | "response.output_item.done" |
| 1402 | | "response.output_text.delta" |
| 1403 | | "response.output_text.annotation.added" |
| 1404 | | "response.reasoning_summary_part.added" |
| 1405 | | "response.reasoning_summary_part.done" |
| 1406 | | "response.reasoning_summary_text.delta" |
| 1407 | | "response.function_call_arguments.delta" |
| 1408 | | "response.function_call_arguments.done" |
| 1409 | | "response.code_interpreter_call_code.delta" |
| 1410 | | "response.code_interpreter_call_code.done" |
| 1411 | | "response.apply_patch_call_operation_diff.delta" |
| 1412 | | "response.apply_patch_call_operation_diff.done" |
| 1413 | | "response.image_generation_call.partial_image" |
| 1414 | | "error" |
| 1415 | |
| 1416 | type KnownResponseStreamEvent = Extract<ResponseStreamEvent, { readonly type: KnownResponseStreamEventType }> |
| 1417 | |
| 1418 | const knownResponseStreamEventTypes = new Set<KnownResponseStreamEventType>([ |
| 1419 | "response.created", |
| 1420 | "response.completed", |
| 1421 | "response.incomplete", |
| 1422 | "response.failed", |
| 1423 | "response.output_item.added", |
| 1424 | "response.output_item.done", |
| 1425 | "response.output_text.delta", |
| 1426 | "response.output_text.annotation.added", |
| 1427 | "response.reasoning_summary_part.added", |
| 1428 | "response.reasoning_summary_part.done", |
| 1429 | "response.reasoning_summary_text.delta", |
| 1430 | "response.function_call_arguments.delta", |
| 1431 | "response.function_call_arguments.done", |
| 1432 | "response.code_interpreter_call_code.delta", |
| 1433 | "response.code_interpreter_call_code.done", |
| 1434 | "response.apply_patch_call_operation_diff.delta", |
| 1435 | "response.apply_patch_call_operation_diff.done", |
| 1436 | "response.image_generation_call.partial_image", |
| 1437 | "error" |
| 1438 | ]) |
| 1439 | |
| 1440 | const isKnownResponseStreamEvent = ( |
| 1441 | event: ResponseStreamEvent |
| 1442 | ): event is KnownResponseStreamEvent => knownResponseStreamEventTypes.has(event.type as KnownResponseStreamEventType) |
| 1443 | |
| 1444 | const makeResponse = Effect.fnUntraced( |
| 1445 | function*<Tools extends ReadonlyArray<Tool.Any>>({ |
| 1446 | options, |
| 1447 | rawResponse, |
| 1448 | response, |
| 1449 | toolNameMapper |
| 1450 | }: { |
| 1451 | readonly options: LanguageModel.ProviderOptions |
| 1452 | readonly rawResponse: OpenAiSchema.Response |
| 1453 | readonly response: HttpClientResponse.HttpClientResponse |
| 1454 | readonly toolNameMapper: Tool.NameMapper<Tools> |
| 1455 | }): Effect.fn.Return< |
| 1456 | Array<Response.PartEncoded>, |
| 1457 | AiError.AiError, |
| 1458 | IdGenerator.IdGenerator |
| 1459 | > { |
| 1460 | const idGenerator = yield* IdGenerator.IdGenerator |
| 1461 | |
| 1462 | const approvalRequests = getApprovalRequestIdMapping(options.prompt) |
| 1463 | |
| 1464 | const webSearchTool = options.tools.find((tool) => |
| 1465 | Tool.isProviderDefined(tool) && |
| 1466 | (tool.name === "OpenAiWebSearch" || |
| 1467 | tool.name === "OpenAiWebSearchPreview") |
| 1468 | ) as Tool.AnyProviderDefined | undefined |
| 1469 | |
| 1470 | let hasToolCalls = false |
| 1471 | const parts: Array<Response.PartEncoded> = [] |
| 1472 | |
| 1473 | const createdAt = new Date(rawResponse.created_at * 1000) |
| 1474 | parts.push({ |
| 1475 | type: "response-metadata", |
| 1476 | id: rawResponse.id, |
| 1477 | modelId: rawResponse.model as string, |
| 1478 | timestamp: DateTime.formatIso(DateTime.fromDateUnsafe(createdAt)), |
| 1479 | request: buildHttpRequestDetails(response.request) |
| 1480 | }) |
| 1481 | |
| 1482 | for (const part of rawResponse.output) { |
| 1483 | switch (part.type) { |
| 1484 | case "apply_patch_call": { |
| 1485 | const toolName = toolNameMapper.getCustomName("apply_patch") |
| 1486 | parts.push({ |
| 1487 | type: "tool-call", |
| 1488 | id: part.call_id, |
| 1489 | name: toolName, |
| 1490 | params: { call_id: part.call_id, operation: part.operation }, |
| 1491 | metadata: { openai: makeItemIdMetadata(part.id) } |
| 1492 | }) |
| 1493 | break |
| 1494 | } |
| 1495 | |
| 1496 | case "code_interpreter_call": { |
| 1497 | const toolName = toolNameMapper.getCustomName("code_interpreter") |
| 1498 | const status = part.status ?? "completed" |
| 1499 | parts.push({ |
| 1500 | type: "tool-call", |
| 1501 | id: part.id, |
| 1502 | name: toolName, |
| 1503 | params: { code: part.code ?? null, container_id: part.container_id }, |
| 1504 | providerExecuted: true |
| 1505 | }) |
| 1506 | parts.push({ |
| 1507 | type: "tool-result", |
| 1508 | id: part.id, |
| 1509 | name: toolName, |
| 1510 | isFailure: status !== "completed", |
| 1511 | result: { status, outputs: part.outputs ?? null }, |
| 1512 | providerExecuted: true |
| 1513 | }) |
| 1514 | break |
| 1515 | } |
| 1516 | |
| 1517 | case "file_search_call": { |
| 1518 | const toolName = toolNameMapper.getCustomName("file_search") |
| 1519 | parts.push({ |
| 1520 | type: "tool-call", |
| 1521 | id: part.id, |
| 1522 | name: toolName, |
| 1523 | params: {}, |
| 1524 | providerExecuted: true |
| 1525 | }) |
| 1526 | parts.push({ |
| 1527 | type: "tool-result", |
| 1528 | id: part.id, |
| 1529 | name: toolName, |
| 1530 | isFailure: part.status !== "completed", |
| 1531 | result: { |
| 1532 | status: part.status, |
| 1533 | queries: part.queries, |
| 1534 | results: part.results ?? null |
| 1535 | }, |
| 1536 | providerExecuted: true |
| 1537 | }) |
| 1538 | break |
| 1539 | } |
| 1540 | |
| 1541 | case "function_call": { |
| 1542 | hasToolCalls = true |
| 1543 | |
| 1544 | const toolName = part.name |
| 1545 | |
| 1546 | const toolParams = yield* Effect.try({ |
| 1547 | try: () => Tool.unsafeSecureJsonParse(part.arguments), |
| 1548 | catch: (cause) => |
| 1549 | AiError.make({ |
| 1550 | module: "OpenAiLanguageModel", |
| 1551 | method: "makeResponse", |
| 1552 | reason: new AiError.ToolParameterValidationError({ |
| 1553 | toolName, |
| 1554 | description: `Faled to securely JSON parse tool parameters: ${cause}` |
| 1555 | }) |
| 1556 | }) |
| 1557 | }) |
| 1558 | |
| 1559 | const params = yield* transformToolCallParams(options.tools, part.name, toolParams) |
| 1560 | |
| 1561 | parts.push({ |
| 1562 | type: "tool-call", |
| 1563 | id: part.call_id, |
| 1564 | name: toolName, |
| 1565 | params, |
| 1566 | metadata: { openai: makeItemIdMetadata(part.id) } |
| 1567 | }) |
| 1568 | break |
| 1569 | } |
| 1570 | |
| 1571 | case "image_generation_call": { |
| 1572 | const toolName = toolNameMapper.getCustomName("image_generation") |
| 1573 | const status = part.status ?? "completed" |
| 1574 | parts.push({ |
| 1575 | type: "tool-call", |
| 1576 | id: part.id, |
| 1577 | name: toolName, |
| 1578 | params: {}, |
| 1579 | providerExecuted: true |
| 1580 | }) |
| 1581 | parts.push({ |
| 1582 | type: "tool-result", |
| 1583 | id: part.id, |
| 1584 | name: toolName, |
| 1585 | isFailure: status !== "completed", |
| 1586 | result: status === "completed" |
| 1587 | ? { result: part.result } |
| 1588 | : { status, result: part.result } |
| 1589 | }) |
| 1590 | break |
| 1591 | } |
| 1592 | |
| 1593 | case "local_shell_call": { |
| 1594 | const toolName = toolNameMapper.getCustomName("local_shell") |
| 1595 | parts.push({ |
| 1596 | type: "tool-call", |
| 1597 | id: part.call_id, |
| 1598 | name: toolName, |
| 1599 | params: { action: part.action }, |
| 1600 | metadata: { openai: makeItemIdMetadata(part.id) } |
| 1601 | }) |
| 1602 | break |
| 1603 | } |
| 1604 | |
| 1605 | case "mcp_call": { |
| 1606 | const toolId = Predicate.isNotNullish(part.approval_request_id) |
| 1607 | ? (approvalRequests.get(part.approval_request_id) ?? part.id) |
| 1608 | : part.id |
| 1609 | |
| 1610 | const { toolName, params } = yield* normalizeMcpToolCall({ |
| 1611 | toolNameMapper, |
| 1612 | toolParams: part.arguments, |
| 1613 | method: "makeResponse" |
| 1614 | }) |
| 1615 | |
| 1616 | parts.push({ |
| 1617 | type: "tool-call", |
| 1618 | id: toolId, |
| 1619 | name: toolName, |
| 1620 | params, |
| 1621 | providerExecuted: true |
| 1622 | }) |
| 1623 | |
| 1624 | parts.push({ |
| 1625 | type: "tool-result", |
| 1626 | id: toolId, |
| 1627 | name: toolName, |
| 1628 | isFailure: Predicate.isNotNullish(part.error), |
| 1629 | providerExecuted: true, |
| 1630 | result: { |
| 1631 | type: "mcp_call", |
| 1632 | name: part.name, |
| 1633 | arguments: part.arguments, |
| 1634 | server_label: part.server_label, |
| 1635 | ...(Predicate.isNotNullish(part.output) ? { output: part.output } : undefined), |
| 1636 | ...(Predicate.isNotNullish(part.error) ? { error: part.error } : undefined) |
| 1637 | }, |
| 1638 | metadata: { openai: makeItemIdMetadata(part.id) } |
| 1639 | }) |
| 1640 | |
| 1641 | break |
| 1642 | } |
| 1643 | |
| 1644 | case "mcp_list_tools": { |
| 1645 | // Skip |
| 1646 | break |
| 1647 | } |
| 1648 | |
| 1649 | case "mcp_approval_request": { |
| 1650 | const approvalRequestId = (part as any).approval_request_id ?? part.id |
| 1651 | const toolId = yield* idGenerator.generateId() |
| 1652 | |
| 1653 | const { toolName, params } = yield* normalizeMcpToolCall({ |
| 1654 | toolNameMapper, |
| 1655 | toolParams: part.arguments, |
| 1656 | method: "makeResponse" |
| 1657 | }) |
| 1658 | |
| 1659 | parts.push({ |
| 1660 | type: "tool-call", |
| 1661 | id: toolId, |
| 1662 | name: toolName, |
| 1663 | params, |
| 1664 | providerExecuted: true |
| 1665 | }) |
| 1666 | |
| 1667 | parts.push({ |
| 1668 | type: "tool-approval-request", |
| 1669 | toolCallId: toolId, |
| 1670 | approvalId: approvalRequestId |
| 1671 | }) |
| 1672 | |
| 1673 | break |
| 1674 | } |
| 1675 | |
| 1676 | case "message": { |
| 1677 | for (const contentPart of part.content) { |
| 1678 | switch (contentPart.type) { |
| 1679 | case "output_text": { |
| 1680 | const annotations = contentPart.annotations.length > 0 |
| 1681 | ? { annotations: contentPart.annotations as any } |
| 1682 | : undefined |
| 1683 | |
| 1684 | parts.push({ |
| 1685 | type: "text", |
| 1686 | text: contentPart.text, |
| 1687 | metadata: { |
| 1688 | openai: { |
| 1689 | ...makeItemIdMetadata(part.id), |
| 1690 | ...annotations |
| 1691 | } |
| 1692 | } |
| 1693 | }) |
| 1694 | for (const annotation of contentPart.annotations) { |
| 1695 | if (annotation.type === "container_file_citation") { |
| 1696 | parts.push({ |
| 1697 | type: "source", |
| 1698 | sourceType: "document", |
| 1699 | id: yield* idGenerator.generateId(), |
| 1700 | mediaType: "text/plain", |
| 1701 | title: annotation.filename, |
| 1702 | fileName: annotation.filename, |
| 1703 | metadata: { |
| 1704 | openai: { |
| 1705 | type: annotation.type, |
| 1706 | fileId: annotation.file_id, |
| 1707 | containerId: annotation.container_id |
| 1708 | } |
| 1709 | } |
| 1710 | }) |
| 1711 | } |
| 1712 | if (annotation.type === "file_citation") { |
| 1713 | parts.push({ |
| 1714 | type: "source", |
| 1715 | sourceType: "document", |
| 1716 | id: yield* idGenerator.generateId(), |
| 1717 | mediaType: "text/plain", |
| 1718 | title: annotation.filename, |
| 1719 | fileName: annotation.filename, |
| 1720 | metadata: { |
| 1721 | openai: { |
| 1722 | type: annotation.type, |
| 1723 | fileId: annotation.file_id, |
| 1724 | index: annotation.index |
| 1725 | } |
| 1726 | } |
| 1727 | }) |
| 1728 | } |
| 1729 | if (annotation.type === "file_path") { |
| 1730 | parts.push({ |
| 1731 | type: "source", |
| 1732 | sourceType: "document", |
| 1733 | id: yield* idGenerator.generateId(), |
| 1734 | mediaType: "application/octet-stream", |
| 1735 | title: annotation.file_id, |
| 1736 | fileName: annotation.file_id, |
| 1737 | metadata: { |
| 1738 | openai: { |
| 1739 | type: annotation.type, |
| 1740 | fileId: annotation.file_id, |
| 1741 | index: annotation.index |
| 1742 | } |
| 1743 | } |
| 1744 | }) |
| 1745 | } |
| 1746 | if (annotation.type === "url_citation") { |
| 1747 | parts.push({ |
| 1748 | type: "source", |
| 1749 | sourceType: "url", |
| 1750 | id: yield* idGenerator.generateId(), |
| 1751 | url: annotation.url, |
| 1752 | title: annotation.title, |
| 1753 | metadata: { |
| 1754 | openai: { |
| 1755 | type: annotation.type, |
| 1756 | startIndex: annotation.start_index, |
| 1757 | endIndex: annotation.end_index |
| 1758 | } |
| 1759 | } |
| 1760 | }) |
| 1761 | } |
| 1762 | } |
| 1763 | break |
| 1764 | } |
| 1765 | case "refusal": { |
| 1766 | parts.push({ |
| 1767 | type: "text", |
| 1768 | text: "", |
| 1769 | metadata: { openai: { refusal: contentPart.refusal } } |
| 1770 | }) |
| 1771 | break |
| 1772 | } |
| 1773 | } |
| 1774 | } |
| 1775 | break |
| 1776 | } |
| 1777 | |
| 1778 | case "reasoning": { |
| 1779 | const metadata = { |
| 1780 | openai: { |
| 1781 | ...makeItemIdMetadata(part.id), |
| 1782 | ...makeEncryptedContentMetadata(part.encrypted_content) |
| 1783 | } |
| 1784 | } |
| 1785 | // If there are no summary parts, we have to add an empty one to |
| 1786 | // propagate the part identifier and encrypted content |
| 1787 | if (part.summary.length === 0) { |
| 1788 | parts.push({ type: "reasoning", text: "", metadata }) |
| 1789 | } else { |
| 1790 | for (const summary of part.summary) { |
| 1791 | parts.push({ type: "reasoning", text: summary.text, metadata }) |
| 1792 | } |
| 1793 | } |
| 1794 | break |
| 1795 | } |
| 1796 | |
| 1797 | case "shell_call": { |
| 1798 | const toolName = toolNameMapper.getCustomName("shell") |
| 1799 | parts.push({ |
| 1800 | type: "tool-call", |
| 1801 | id: part.call_id, |
| 1802 | name: toolName, |
| 1803 | params: { action: part.action }, |
| 1804 | metadata: { openai: makeItemIdMetadata(part.id) } |
| 1805 | }) |
| 1806 | break |
| 1807 | } |
| 1808 | |
| 1809 | case "web_search_call": { |
| 1810 | const toolName = toolNameMapper.getCustomName( |
| 1811 | webSearchTool?.name ?? "web_search" |
| 1812 | ) |
| 1813 | parts.push({ |
| 1814 | type: "tool-call", |
| 1815 | id: part.id, |
| 1816 | name: toolName, |
| 1817 | params: webSearchTool?.name === "OpenAiWebSearchPreview" || Predicate.isUndefined(part.action) |
| 1818 | ? {} |
| 1819 | : { action: part.action }, |
| 1820 | providerExecuted: true |
| 1821 | }) |
| 1822 | parts.push({ |
| 1823 | type: "tool-result", |
| 1824 | id: part.id, |
| 1825 | name: toolName, |
| 1826 | isFailure: part.status !== "completed", |
| 1827 | result: { |
| 1828 | ...(Predicate.isUndefined(part.action) ? undefined : { action: part.action }), |
| 1829 | status: part.status |
| 1830 | }, |
| 1831 | providerExecuted: true |
| 1832 | }) |
| 1833 | break |
| 1834 | } |
| 1835 | } |
| 1836 | } |
| 1837 | |
| 1838 | const finishReason = InternalUtilities.resolveFinishReason( |
| 1839 | rawResponse.incomplete_details?.reason, |
| 1840 | hasToolCalls |
| 1841 | ) |
| 1842 | |
| 1843 | parts.push({ |
| 1844 | type: "finish", |
| 1845 | reason: finishReason, |
| 1846 | usage: getUsage(rawResponse.usage), |
| 1847 | response: buildHttpResponseDetails(response), |
| 1848 | ...toFinishMetadata(rawResponse) |
| 1849 | }) |
| 1850 | |
| 1851 | return parts |
| 1852 | } |
| 1853 | ) |
| 1854 | |
| 1855 | const makeStreamResponse = Effect.fnUntraced( |
| 1856 | function*<Tools extends ReadonlyArray<Tool.Any>>({ |
| 1857 | stream, |
| 1858 | response, |
| 1859 | config, |
| 1860 | options, |
| 1861 | toolNameMapper |
| 1862 | }: { |
| 1863 | readonly config: typeof Config.Service |
| 1864 | readonly stream: Stream.Stream<ResponseStreamEvent, AiError.AiError> |
| 1865 | readonly response: HttpClientResponse.HttpClientResponse |
| 1866 | readonly options: LanguageModel.ProviderOptions |
| 1867 | readonly toolNameMapper: Tool.NameMapper<Tools> |
| 1868 | }): Effect.fn.Return< |
| 1869 | Stream.Stream<Response.StreamPartEncoded, AiError.AiError>, |
| 1870 | AiError.AiError, |
| 1871 | IdGenerator.IdGenerator |
| 1872 | > { |
| 1873 | const idGenerator = yield* IdGenerator.IdGenerator |
| 1874 | const websocketMode = Option.isSome(yield* Effect.serviceOption(OpenAiSocket)) |
| 1875 | |
| 1876 | const approvalRequests = getApprovalRequestIdMapping(options.prompt) |
| 1877 | const streamApprovalRequests = new Map<string, string>() |
| 1878 | |
| 1879 | let hasToolCalls = false |
| 1880 | |
| 1881 | // Track annotations for current message to include in text-end metadata |
| 1882 | const activeAnnotations: Array<typeof OpenAiSchema.Annotation.Encoded> = [] |
| 1883 | |
| 1884 | type ReasoningSummaryPartStatus = "active" | "can-conclude" | "concluded" |
| 1885 | type ReasoningPart = { |
| 1886 | encryptedContent: string | undefined |
| 1887 | summaryParts: Record<number, ReasoningSummaryPartStatus> |
| 1888 | } |
| 1889 | |
| 1890 | // Track active reasoning items with state machine for proper concluding logic |
| 1891 | const activeReasoning: Record<string, ReasoningPart> = Object.create(null) |
| 1892 | |
| 1893 | const getOrCreateReasoningPart = ( |
| 1894 | itemId: string, |
| 1895 | encryptedContent?: string | null |
| 1896 | ): ReasoningPart => { |
| 1897 | const activePart = activeReasoning[itemId] |
| 1898 | if (Predicate.isNotUndefined(activePart)) { |
| 1899 | if (Predicate.isNotNullish(encryptedContent)) { |
| 1900 | activePart.encryptedContent = encryptedContent |
| 1901 | } |
| 1902 | return activePart |
| 1903 | } |
| 1904 | |
| 1905 | const reasoningPart: ReasoningPart = { |
| 1906 | encryptedContent: Predicate.isNotNullish(encryptedContent) ? encryptedContent : undefined, |
| 1907 | summaryParts: {} |
| 1908 | } |
| 1909 | activeReasoning[itemId] = reasoningPart |
| 1910 | return reasoningPart |
| 1911 | } |
| 1912 | |
| 1913 | // Track active tool calls with optional provider-specific state |
| 1914 | const activeToolCalls: Record<number, { |
| 1915 | readonly id: string |
| 1916 | readonly name: string |
| 1917 | readonly functionCall?: { |
| 1918 | emitted: boolean |
| 1919 | } |
| 1920 | readonly applyPatch?: { |
| 1921 | hasDiff: boolean |
| 1922 | endEmitted: boolean |
| 1923 | } |
| 1924 | readonly codeInterpreter?: { |
| 1925 | readonly containerId: string |
| 1926 | hasCode: boolean |
| 1927 | streamedCode: string |
| 1928 | } |
| 1929 | }> = {} |
| 1930 | |
| 1931 | const finishCodeInterpreterCall = ( |
| 1932 | outputIndex: number, |
| 1933 | code: string | null, |
| 1934 | parts: Array<Response.StreamPartEncoded> |
| 1935 | ) => { |
| 1936 | const toolCall = activeToolCalls[outputIndex] |
| 1937 | if (Predicate.isUndefined(toolCall?.codeInterpreter)) { |
| 1938 | return |
| 1939 | } |
| 1940 | parts.push({ |
| 1941 | type: "tool-params-delta", |
| 1942 | id: toolCall.id, |
| 1943 | delta: toolCall.codeInterpreter.hasCode ? "\"}" : `${JSON.stringify(code)}}` |
| 1944 | }) |
| 1945 | parts.push({ type: "tool-params-end", id: toolCall.id }) |
| 1946 | parts.push({ |
| 1947 | type: "tool-call", |
| 1948 | id: toolCall.id, |
| 1949 | name: toolCall.name, |
| 1950 | params: { |
| 1951 | code: toolCall.codeInterpreter.hasCode ? toolCall.codeInterpreter.streamedCode : code, |
| 1952 | container_id: toolCall.codeInterpreter.containerId |
| 1953 | }, |
| 1954 | providerExecuted: true |
| 1955 | }) |
| 1956 | delete activeToolCalls[outputIndex] |
| 1957 | } |
| 1958 | |
| 1959 | const webSearchTool = options.tools.find((tool) => |
| 1960 | Tool.isProviderDefined(tool) && |
| 1961 | (tool.name === "OpenAiWebSearch" || |
| 1962 | tool.name === "OpenAiWebSearchPreview") |
| 1963 | ) as ReturnType<typeof OpenAiTool.WebSearch> | ReturnType<typeof OpenAiTool.WebSearchPreview> | undefined |
| 1964 | |
| 1965 | return stream.pipe( |
| 1966 | Stream.mapEffect(Effect.fnUntraced(function*(event) { |
| 1967 | const parts: Array<Response.StreamPartEncoded> = [] |
| 1968 | |
| 1969 | if (!isKnownResponseStreamEvent(event)) { |
| 1970 | return parts |
| 1971 | } |
| 1972 | |
| 1973 | switch (event.type) { |
| 1974 | case "response.created": { |
| 1975 | const createdAt = new Date(event.response.created_at * 1000) |
| 1976 | parts.push({ |
| 1977 | type: "response-metadata", |
| 1978 | id: event.response.id, |
| 1979 | modelId: event.response.model, |
| 1980 | timestamp: DateTime.formatIso(DateTime.fromDateUnsafe(createdAt)), |
| 1981 | request: buildHttpRequestDetails(response.request) |
| 1982 | }) |
| 1983 | break |
| 1984 | } |
| 1985 | |
| 1986 | case "error": { |
| 1987 | parts.push({ type: "error", error: event }) |
| 1988 | break |
| 1989 | } |
| 1990 | |
| 1991 | case "response.completed": |
| 1992 | case "response.incomplete": { |
| 1993 | parts.push({ |
| 1994 | type: "finish", |
| 1995 | reason: InternalUtilities.resolveFinishReason( |
| 1996 | event.response.incomplete_details?.reason, |
| 1997 | hasToolCalls |
| 1998 | ), |
| 1999 | usage: getUsage(event.response.usage), |
| 2000 | response: buildHttpResponseDetails(response), |
| 2001 | ...toFinishMetadata(event.response) |
| 2002 | }) |
| 2003 | break |
| 2004 | } |
| 2005 | |
| 2006 | case "response.failed": { |
| 2007 | if (event.response.error) { |
| 2008 | parts.push({ type: "error", error: event.response.error }) |
| 2009 | } |
| 2010 | parts.push({ |
| 2011 | type: "finish", |
| 2012 | reason: "error", |
| 2013 | usage: getUsage(event.response.usage), |
| 2014 | response: buildHttpResponseDetails(response), |
| 2015 | ...toFinishMetadata(event.response) |
| 2016 | }) |
| 2017 | break |
| 2018 | } |
| 2019 | |
| 2020 | case "response.output_item.added": { |
| 2021 | switch (event.item.type) { |
| 2022 | case "apply_patch_call": { |
| 2023 | const toolId = event.item.call_id |
| 2024 | const toolName = toolNameMapper.getCustomName("apply_patch") |
| 2025 | const operation = event.item.operation |
| 2026 | activeToolCalls[event.output_index] = { |
| 2027 | id: toolId, |
| 2028 | name: toolName, |
| 2029 | applyPatch: { |
| 2030 | hasDiff: operation.type !== "delete_file", |
| 2031 | endEmitted: operation.type === "delete_file" |
| 2032 | } |
| 2033 | } |
| 2034 | parts.push({ |
| 2035 | type: "tool-params-start", |
| 2036 | id: toolId, |
| 2037 | name: toolName |
| 2038 | }) |
| 2039 | |
| 2040 | if (operation.type === "delete_file") { |
| 2041 | parts.push({ |
| 2042 | type: "tool-params-delta", |
| 2043 | id: toolId, |
| 2044 | delta: JSON.stringify({ |
| 2045 | call_id: toolId, |
| 2046 | operation: operation |
| 2047 | }) |
| 2048 | }) |
| 2049 | parts.push({ |
| 2050 | type: "tool-params-end", |
| 2051 | id: toolId |
| 2052 | }) |
| 2053 | } else { |
| 2054 | parts.push({ |
| 2055 | type: "tool-params-delta", |
| 2056 | id: toolId, |
| 2057 | delta: `{"call_id":"${InternalUtilities.escapeJSONDelta(toolId)}",` + |
| 2058 | `"operation":{"type":"${InternalUtilities.escapeJSONDelta(operation.type)}",` + |
| 2059 | `"path":"${InternalUtilities.escapeJSONDelta(operation.path)}","diff":"` |
| 2060 | }) |
| 2061 | } |
| 2062 | break |
| 2063 | } |
| 2064 | |
| 2065 | case "code_interpreter_call": { |
| 2066 | const toolName = toolNameMapper.getCustomName("code_interpreter") |
| 2067 | activeToolCalls[event.output_index] = { |
| 2068 | id: event.item.id, |
| 2069 | name: toolName, |
| 2070 | codeInterpreter: { containerId: event.item.container_id, hasCode: false, streamedCode: "" } |
| 2071 | } |
| 2072 | parts.push({ |
| 2073 | type: "tool-params-start", |
| 2074 | id: event.item.id, |
| 2075 | name: toolName, |
| 2076 | providerExecuted: true |
| 2077 | }) |
| 2078 | parts.push({ |
| 2079 | type: "tool-params-delta", |
| 2080 | id: event.item.id, |
| 2081 | delta: `{"container_id":${JSON.stringify(event.item.container_id)},"code":` |
| 2082 | }) |
| 2083 | break |
| 2084 | } |
| 2085 | |
| 2086 | case "computer_call": { |
| 2087 | const toolName = toolNameMapper.getCustomName("computer_use") |
| 2088 | activeToolCalls[event.output_index] = { |
| 2089 | id: event.item.id, |
| 2090 | name: toolName |
| 2091 | } |
| 2092 | parts.push({ |
| 2093 | type: "tool-params-start", |
| 2094 | id: event.item.id, |
| 2095 | name: toolName, |
| 2096 | providerExecuted: true |
| 2097 | }) |
| 2098 | break |
| 2099 | } |
| 2100 | |
| 2101 | case "file_search_call": { |
| 2102 | const toolName = toolNameMapper.getCustomName("file_search") |
| 2103 | parts.push({ |
| 2104 | type: "tool-call", |
| 2105 | id: event.item.id, |
| 2106 | name: toolName, |
| 2107 | params: {}, |
| 2108 | providerExecuted: true |
| 2109 | }) |
| 2110 | break |
| 2111 | } |
| 2112 | |
| 2113 | case "function_call": { |
| 2114 | activeToolCalls[event.output_index] = { |
| 2115 | id: event.item.call_id, |
| 2116 | name: event.item.name, |
| 2117 | functionCall: { emitted: false } |
| 2118 | } |
| 2119 | parts.push({ |
| 2120 | type: "tool-params-start", |
| 2121 | id: event.item.call_id, |
| 2122 | name: event.item.name |
| 2123 | }) |
| 2124 | break |
| 2125 | } |
| 2126 | |
| 2127 | case "image_generation_call": { |
| 2128 | const toolName = toolNameMapper.getCustomName("image_generation") |
| 2129 | parts.push({ |
| 2130 | type: "tool-call", |
| 2131 | id: event.item.id, |
| 2132 | name: toolName, |
| 2133 | params: {}, |
| 2134 | providerExecuted: true |
| 2135 | }) |
| 2136 | break |
| 2137 | } |
| 2138 | |
| 2139 | case "mcp_call": |
| 2140 | case "mcp_list_tools": |
| 2141 | case "mcp_approval_request": { |
| 2142 | // We emit MCP tool call / approvals on `output_item.done` to facilitate: |
| 2143 | // - Aliasing tool call identifiers when an approval request id exists |
| 2144 | // - Emit a proper tool-approval-request part for MCP approvals |
| 2145 | break |
| 2146 | } |
| 2147 | |
| 2148 | case "message": { |
| 2149 | // Clear annotations for new message |
| 2150 | activeAnnotations.length = 0 |
| 2151 | parts.push({ |
| 2152 | type: "text-start", |
| 2153 | id: event.item.id, |
| 2154 | metadata: { openai: makeItemIdMetadata(event.item.id) } |
| 2155 | }) |
| 2156 | break |
| 2157 | } |
| 2158 | |
| 2159 | case "reasoning": { |
| 2160 | const reasoningPart = getOrCreateReasoningPart(event.item.id, event.item.encrypted_content) |
| 2161 | if (Predicate.isUndefined(reasoningPart.summaryParts[0])) { |
| 2162 | reasoningPart.summaryParts[0] = "active" |
| 2163 | parts.push({ |
| 2164 | type: "reasoning-start", |
| 2165 | id: `${event.item.id}:0`, |
| 2166 | metadata: { |
| 2167 | openai: { |
| 2168 | ...makeItemIdMetadata(event.item.id), |
| 2169 | ...makeEncryptedContentMetadata(reasoningPart.encryptedContent) |
| 2170 | } |
| 2171 | } |
| 2172 | }) |
| 2173 | } |
| 2174 | break |
| 2175 | } |
| 2176 | |
| 2177 | case "shell_call": { |
| 2178 | const toolName = toolNameMapper.getCustomName("shell") |
| 2179 | activeToolCalls[event.output_index] = { |
| 2180 | id: event.item.id ?? event.item.call_id, |
| 2181 | name: toolName |
| 2182 | } |
| 2183 | break |
| 2184 | } |
| 2185 | |
| 2186 | case "web_search_call": { |
| 2187 | const toolName = toolNameMapper.getCustomName( |
| 2188 | webSearchTool?.providerName ?? "web_search" |
| 2189 | ) |
| 2190 | activeToolCalls[event.output_index] = { |
| 2191 | id: event.item.id, |
| 2192 | name: toolName |
| 2193 | } |
| 2194 | if (webSearchTool?.name === "OpenAiWebSearch") { |
| 2195 | break |
| 2196 | } |
| 2197 | parts.push({ |
| 2198 | type: "tool-params-start", |
| 2199 | id: event.item.id, |
| 2200 | name: webSearchTool?.name ?? "OpenAiWebSearch", |
| 2201 | providerExecuted: true |
| 2202 | }) |
| 2203 | parts.push({ |
| 2204 | type: "tool-params-end", |
| 2205 | id: event.item.id |
| 2206 | }) |
| 2207 | parts.push({ |
| 2208 | type: "tool-call", |
| 2209 | id: event.item.id, |
| 2210 | name: toolName, |
| 2211 | params: {}, |
| 2212 | providerExecuted: true |
| 2213 | }) |
| 2214 | break |
| 2215 | } |
| 2216 | } |
| 2217 | |
| 2218 | break |
| 2219 | } |
| 2220 | |
| 2221 | case "response.output_item.done": { |
| 2222 | switch (event.item.type) { |
| 2223 | case "apply_patch_call": { |
| 2224 | const toolCall = activeToolCalls[event.output_index] |
| 2225 | if ( |
| 2226 | Predicate.isNotUndefined(toolCall.applyPatch) && |
| 2227 | !toolCall.applyPatch.endEmitted && |
| 2228 | event.item.operation.type !== "delete_file" |
| 2229 | ) { |
| 2230 | if (!toolCall.applyPatch.hasDiff) { |
| 2231 | parts.push({ |
| 2232 | type: "tool-params-delta", |
| 2233 | id: toolCall.id, |
| 2234 | delta: InternalUtilities.escapeJSONDelta(event.item.operation.diff ?? "") |
| 2235 | }) |
| 2236 | } |
| 2237 | parts.push({ |
| 2238 | type: "tool-params-delta", |
| 2239 | id: toolCall.id, |
| 2240 | delta: `"}}` |
| 2241 | }) |
| 2242 | parts.push({ |
| 2243 | type: "tool-params-end", |
| 2244 | id: toolCall.id |
| 2245 | }) |
| 2246 | toolCall.applyPatch.endEmitted = true |
| 2247 | } |
| 2248 | // Emit the final tool call with the complete diff when the status is completed |
| 2249 | if (Predicate.isNotUndefined(toolCall) && event.item.status === "completed") { |
| 2250 | const toolName = toolNameMapper.getCustomName("apply_patch") |
| 2251 | parts.push({ |
| 2252 | type: "tool-call", |
| 2253 | id: toolCall.id, |
| 2254 | name: toolName, |
| 2255 | params: { call_id: event.item.call_id, operation: event.item.operation }, |
| 2256 | metadata: { openai: makeItemIdMetadata(event.item.id) } |
| 2257 | }) |
| 2258 | } |
| 2259 | delete activeToolCalls[event.output_index] |
| 2260 | break |
| 2261 | } |
| 2262 | |
| 2263 | case "code_interpreter_call": { |
| 2264 | finishCodeInterpreterCall(event.output_index, event.item.code ?? null, parts) |
| 2265 | const toolName = toolNameMapper.getCustomName("code_interpreter") |
| 2266 | const status = event.item.status ?? "completed" |
| 2267 | parts.push({ |
| 2268 | type: "tool-result", |
| 2269 | id: event.item.id, |
| 2270 | name: toolName, |
| 2271 | isFailure: status !== "completed", |
| 2272 | result: { status, outputs: event.item.outputs ?? null }, |
| 2273 | providerExecuted: true |
| 2274 | }) |
| 2275 | break |
| 2276 | } |
| 2277 | |
| 2278 | case "computer_call": { |
| 2279 | delete activeToolCalls[event.output_index] |
| 2280 | const toolName = toolNameMapper.getCustomName("computer_use") |
| 2281 | parts.push({ |
| 2282 | type: "tool-params-end", |
| 2283 | id: event.item.id |
| 2284 | }) |
| 2285 | parts.push({ |
| 2286 | type: "tool-call", |
| 2287 | id: event.item.id, |
| 2288 | name: toolName, |
| 2289 | params: {}, |
| 2290 | providerExecuted: true |
| 2291 | }) |
| 2292 | parts.push({ |
| 2293 | type: "tool-result", |
| 2294 | id: event.item.id, |
| 2295 | name: toolName, |
| 2296 | isFailure: false, |
| 2297 | result: { status: event.item.status ?? "completed" } |
| 2298 | }) |
| 2299 | break |
| 2300 | } |
| 2301 | |
| 2302 | case "file_search_call": { |
| 2303 | delete activeToolCalls[event.output_index] |
| 2304 | const toolName = toolNameMapper.getCustomName("file_search") |
| 2305 | parts.push({ |
| 2306 | type: "tool-result", |
| 2307 | id: event.item.id, |
| 2308 | name: toolName, |
| 2309 | isFailure: event.item.status !== "completed", |
| 2310 | result: { |
| 2311 | status: event.item.status, |
| 2312 | queries: event.item.queries, |
| 2313 | results: event.item.results ?? null |
| 2314 | }, |
| 2315 | providerExecuted: true |
| 2316 | }) |
| 2317 | break |
| 2318 | } |
| 2319 | |
| 2320 | case "function_call": { |
| 2321 | const toolCall = activeToolCalls[event.output_index] |
| 2322 | if (Predicate.isNotUndefined(toolCall?.functionCall?.emitted) && toolCall.functionCall.emitted) { |
| 2323 | delete activeToolCalls[event.output_index] |
| 2324 | break |
| 2325 | } |
| 2326 | delete activeToolCalls[event.output_index] |
| 2327 | |
| 2328 | hasToolCalls = true |
| 2329 | |
| 2330 | const toolName = event.item.name |
| 2331 | const toolArgs = event.item.arguments |
| 2332 | |
| 2333 | const toolParams = yield* Effect.try({ |
| 2334 | try: () => Tool.unsafeSecureJsonParse(toolArgs), |
| 2335 | catch: (cause) => |
| 2336 | AiError.make({ |
| 2337 | module: "OpenAiLanguageModel", |
| 2338 | method: "makeStreamResponse", |
| 2339 | reason: new AiError.ToolParameterValidationError({ |
| 2340 | toolName, |
| 2341 | description: `Failed securely JSON parse tool parameters: ${cause}` |
| 2342 | }) |
| 2343 | }) |
| 2344 | }) |
| 2345 | |
| 2346 | const params = yield* transformToolCallParams(options.tools, toolName, toolParams) |
| 2347 | |
| 2348 | parts.push({ |
| 2349 | type: "tool-params-end", |
| 2350 | id: event.item.call_id |
| 2351 | }) |
| 2352 | |
| 2353 | parts.push({ |
| 2354 | type: "tool-call", |
| 2355 | id: event.item.call_id, |
| 2356 | name: toolName, |
| 2357 | params, |
| 2358 | metadata: { openai: makeItemIdMetadata(event.item.id) } |
| 2359 | }) |
| 2360 | |
| 2361 | break |
| 2362 | } |
| 2363 | |
| 2364 | case "image_generation_call": { |
| 2365 | const toolName = toolNameMapper.getCustomName("image_generation") |
| 2366 | const status = event.item.status ?? "completed" |
| 2367 | parts.push({ |
| 2368 | type: "tool-result", |
| 2369 | id: event.item.id, |
| 2370 | name: toolName, |
| 2371 | isFailure: status !== "completed", |
| 2372 | result: status === "completed" |
| 2373 | ? { result: event.item.result } |
| 2374 | : { status, result: event.item.result }, |
| 2375 | providerExecuted: true |
| 2376 | }) |
| 2377 | break |
| 2378 | } |
| 2379 | |
| 2380 | case "local_shell_call": { |
| 2381 | const toolName = toolNameMapper.getCustomName("local_shell") |
| 2382 | parts.push({ |
| 2383 | type: "tool-call", |
| 2384 | id: event.item.call_id, |
| 2385 | name: toolName, |
| 2386 | params: { action: event.item.action }, |
| 2387 | metadata: { openai: makeItemIdMetadata(event.item.id) } |
| 2388 | }) |
| 2389 | break |
| 2390 | } |
| 2391 | |
| 2392 | case "mcp_call": { |
| 2393 | const approvalRequestId = event.item.approval_request_id |
| 2394 | |
| 2395 | // Track approval with our own tool call identifiers |
| 2396 | const toolId = Predicate.isNotNullish(approvalRequestId) |
| 2397 | ? (streamApprovalRequests.get(approvalRequestId) ?? approvalRequests.get(approvalRequestId) ?? |
| 2398 | event.item.id) |
| 2399 | : event.item.id |
| 2400 | |
| 2401 | const { toolName, params } = yield* normalizeMcpToolCall({ |
| 2402 | toolNameMapper, |
| 2403 | toolParams: event.item.arguments, |
| 2404 | method: "makeStreamResponse" |
| 2405 | }) |
| 2406 | |
| 2407 | parts.push({ |
| 2408 | type: "tool-call", |
| 2409 | id: toolId, |
| 2410 | name: toolName, |
| 2411 | params, |
| 2412 | providerExecuted: true |
| 2413 | }) |
| 2414 | |
| 2415 | parts.push({ |
| 2416 | type: "tool-result", |
| 2417 | id: toolId, |
| 2418 | name: toolName, |
| 2419 | isFailure: Predicate.isNotNullish(event.item.error), |
| 2420 | providerExecuted: true, |
| 2421 | result: { |
| 2422 | type: "mcp_call", |
| 2423 | name: event.item.name, |
| 2424 | arguments: event.item.arguments, |
| 2425 | server_label: event.item.server_label, |
| 2426 | ...(Predicate.isNotNullish(event.item.output) ? { output: event.item.output } : undefined), |
| 2427 | ...(Predicate.isNotNullish(event.item.error) ? { error: event.item.error } : undefined) |
| 2428 | }, |
| 2429 | metadata: { openai: makeItemIdMetadata(event.item.id) } |
| 2430 | }) |
| 2431 | |
| 2432 | break |
| 2433 | } |
| 2434 | |
| 2435 | case "mcp_list_tools": { |
| 2436 | // Skip |
| 2437 | break |
| 2438 | } |
| 2439 | |
| 2440 | case "mcp_approval_request": { |
| 2441 | const toolId = yield* idGenerator.generateId() |
| 2442 | const approvalRequestId = (event.item as any).approval_request_id ?? event.item.id |
| 2443 | streamApprovalRequests.set(approvalRequestId, toolId) |
| 2444 | const { toolName, params } = yield* normalizeMcpToolCall({ |
| 2445 | toolNameMapper, |
| 2446 | toolParams: event.item.arguments, |
| 2447 | method: "makeStreamResponse" |
| 2448 | }) |
| 2449 | parts.push({ |
| 2450 | type: "tool-call", |
| 2451 | id: toolId, |
| 2452 | name: toolName, |
| 2453 | params, |
| 2454 | providerExecuted: true |
| 2455 | }) |
| 2456 | parts.push({ |
| 2457 | type: "tool-approval-request", |
| 2458 | approvalId: approvalRequestId, |
| 2459 | toolCallId: toolId |
| 2460 | }) |
| 2461 | break |
| 2462 | } |
| 2463 | |
| 2464 | case "message": { |
| 2465 | const annotations = activeAnnotations.length > 0 |
| 2466 | ? { annotations: activeAnnotations.slice() } |
| 2467 | : undefined |
| 2468 | parts.push({ |
| 2469 | type: "text-end", |
| 2470 | id: event.item.id, |
| 2471 | metadata: { openai: { ...annotations, ...makeItemIdMetadata(event.item.id) } } |
| 2472 | }) |
| 2473 | break |
| 2474 | } |
| 2475 | |
| 2476 | case "reasoning": { |
| 2477 | const reasoningPart = getOrCreateReasoningPart(event.item.id, event.item.encrypted_content) |
| 2478 | for (const [summaryIndex, status] of Object.entries(reasoningPart.summaryParts)) { |
| 2479 | if (status === "active" || status === "can-conclude") { |
| 2480 | parts.push({ |
| 2481 | type: "reasoning-end", |
| 2482 | id: `${event.item.id}:${summaryIndex}`, |
| 2483 | metadata: { |
| 2484 | openai: { |
| 2485 | ...makeItemIdMetadata(event.item.id), |
| 2486 | ...makeEncryptedContentMetadata(reasoningPart.encryptedContent) |
| 2487 | } |
| 2488 | } |
| 2489 | }) |
| 2490 | } |
| 2491 | } |
| 2492 | delete activeReasoning[event.item.id] |
| 2493 | break |
| 2494 | } |
| 2495 | |
| 2496 | case "shell_call": { |
| 2497 | delete activeToolCalls[event.output_index] |
| 2498 | const toolName = toolNameMapper.getCustomName("shell") |
| 2499 | parts.push({ |
| 2500 | type: "tool-call", |
| 2501 | id: event.item.id ?? event.item.call_id, |
| 2502 | name: toolName, |
| 2503 | params: { action: event.item.action }, |
| 2504 | metadata: { openai: makeItemIdMetadata(event.item.id) } |
| 2505 | }) |
| 2506 | break |
| 2507 | } |
| 2508 | |
| 2509 | case "web_search_call": { |
| 2510 | delete activeToolCalls[event.output_index] |
| 2511 | const toolName = toolNameMapper.getCustomName( |
| 2512 | webSearchTool?.name ?? "web_search" |
| 2513 | ) |
| 2514 | if (webSearchTool?.name === "OpenAiWebSearch") { |
| 2515 | parts.push({ |
| 2516 | type: "tool-call", |
| 2517 | id: event.item.id, |
| 2518 | name: toolName, |
| 2519 | params: Predicate.isUndefined(event.item.action) ? {} : { action: event.item.action }, |
| 2520 | providerExecuted: true |
| 2521 | }) |
| 2522 | } |
| 2523 | parts.push({ |
| 2524 | type: "tool-result", |
| 2525 | id: event.item.id, |
| 2526 | name: toolName, |
| 2527 | isFailure: event.item.status !== "completed", |
| 2528 | result: { |
| 2529 | ...(Predicate.isUndefined(event.item.action) ? undefined : { action: event.item.action }), |
| 2530 | status: event.item.status |
| 2531 | }, |
| 2532 | providerExecuted: true |
| 2533 | }) |
| 2534 | break |
| 2535 | } |
| 2536 | } |
| 2537 | |
| 2538 | break |
| 2539 | } |
| 2540 | |
| 2541 | case "response.output_text.delta": { |
| 2542 | parts.push({ |
| 2543 | type: "text-delta", |
| 2544 | id: event.item_id, |
| 2545 | delta: event.delta |
| 2546 | }) |
| 2547 | break |
| 2548 | } |
| 2549 | |
| 2550 | case "response.output_text.annotation.added": { |
| 2551 | const annotation = event.annotation as typeof OpenAiSchema.Annotation.Encoded |
| 2552 | // Track annotation for text-end metadata |
| 2553 | activeAnnotations.push(annotation) |
| 2554 | if (annotation.type === "container_file_citation") { |
| 2555 | parts.push({ |
| 2556 | type: "source", |
| 2557 | sourceType: "document", |
| 2558 | id: yield* idGenerator.generateId(), |
| 2559 | mediaType: "text/plain", |
| 2560 | title: annotation.filename, |
| 2561 | fileName: annotation.filename, |
| 2562 | metadata: { |
| 2563 | openai: { |
| 2564 | type: annotation.type, |
| 2565 | fileId: annotation.file_id, |
| 2566 | containerId: annotation.container_id |
| 2567 | } |
| 2568 | } |
| 2569 | }) |
| 2570 | } else if (annotation.type === "file_citation") { |
| 2571 | parts.push({ |
| 2572 | type: "source", |
| 2573 | sourceType: "document", |
| 2574 | id: yield* idGenerator.generateId(), |
| 2575 | mediaType: "text/plain", |
| 2576 | title: annotation.filename, |
| 2577 | fileName: annotation.filename, |
| 2578 | metadata: { |
| 2579 | openai: { |
| 2580 | type: annotation.type, |
| 2581 | fileId: annotation.file_id, |
| 2582 | index: annotation.index |
| 2583 | } |
| 2584 | } |
| 2585 | }) |
| 2586 | } else if (annotation.type === "file_path") { |
| 2587 | parts.push({ |
| 2588 | type: "source", |
| 2589 | sourceType: "document", |
| 2590 | id: yield* idGenerator.generateId(), |
| 2591 | mediaType: "application/octet-stream", |
| 2592 | title: annotation.file_id, |
| 2593 | fileName: annotation.file_id, |
| 2594 | metadata: { |
| 2595 | openai: { |
| 2596 | type: annotation.type, |
| 2597 | fileId: annotation.file_id, |
| 2598 | index: annotation.index |
| 2599 | } |
| 2600 | } |
| 2601 | }) |
| 2602 | } else if (annotation.type === "url_citation") { |
| 2603 | parts.push({ |
| 2604 | type: "source", |
| 2605 | sourceType: "url", |
| 2606 | id: yield* idGenerator.generateId(), |
| 2607 | url: annotation.url, |
| 2608 | title: annotation.title, |
| 2609 | metadata: { |
| 2610 | openai: { |
| 2611 | type: annotation.type, |
| 2612 | startIndex: annotation.start_index, |
| 2613 | endIndex: annotation.end_index |
| 2614 | } |
| 2615 | } |
| 2616 | }) |
| 2617 | } |
| 2618 | break |
| 2619 | } |
| 2620 | |
| 2621 | case "response.function_call_arguments.delta": { |
| 2622 | const toolCallPart = activeToolCalls[event.output_index] |
| 2623 | if (Predicate.isNotUndefined(toolCallPart)) { |
| 2624 | parts.push({ |
| 2625 | type: "tool-params-delta", |
| 2626 | id: toolCallPart.id, |
| 2627 | delta: event.delta |
| 2628 | }) |
| 2629 | } |
| 2630 | break |
| 2631 | } |
| 2632 | |
| 2633 | case "response.function_call_arguments.done": { |
| 2634 | const toolCall = activeToolCalls[event.output_index] |
| 2635 | if ( |
| 2636 | Predicate.isNotUndefined(toolCall?.functionCall) && |
| 2637 | !toolCall.functionCall.emitted |
| 2638 | ) { |
| 2639 | hasToolCalls = true |
| 2640 | |
| 2641 | const toolParams = yield* Effect.try({ |
| 2642 | try: () => Tool.unsafeSecureJsonParse(event.arguments), |
| 2643 | catch: (cause) => |
| 2644 | AiError.make({ |
| 2645 | module: "OpenAiLanguageModel", |
| 2646 | method: "makeStreamResponse", |
| 2647 | reason: new AiError.ToolParameterValidationError({ |
| 2648 | toolName: toolCall.name, |
| 2649 | description: `Failed securely JSON parse tool parameters: ${cause}` |
| 2650 | }) |
| 2651 | }) |
| 2652 | }) |
| 2653 | |
| 2654 | const params = yield* transformToolCallParams(options.tools, toolCall.name, toolParams) |
| 2655 | |
| 2656 | parts.push({ |
| 2657 | type: "tool-params-end", |
| 2658 | id: toolCall.id |
| 2659 | }) |
| 2660 | |
| 2661 | parts.push({ |
| 2662 | type: "tool-call", |
| 2663 | id: toolCall.id, |
| 2664 | name: toolCall.name, |
| 2665 | params, |
| 2666 | metadata: { openai: makeItemIdMetadata(event.item_id) } |
| 2667 | }) |
| 2668 | |
| 2669 | toolCall.functionCall.emitted = true |
| 2670 | } |
| 2671 | break |
| 2672 | } |
| 2673 | |
| 2674 | case "response.apply_patch_call_operation_diff.delta": { |
| 2675 | const toolCall = activeToolCalls[event.output_index] |
| 2676 | if (Predicate.isNotUndefined(toolCall?.applyPatch)) { |
| 2677 | parts.push({ |
| 2678 | type: "tool-params-delta", |
| 2679 | id: toolCall.id, |
| 2680 | delta: InternalUtilities.escapeJSONDelta(event.delta) |
| 2681 | }) |
| 2682 | toolCall.applyPatch.hasDiff = true |
| 2683 | } |
| 2684 | break |
| 2685 | } |
| 2686 | |
| 2687 | case "response.apply_patch_call_operation_diff.done": { |
| 2688 | const toolCall = activeToolCalls[event.output_index] |
| 2689 | if (Predicate.isNotUndefined(toolCall?.applyPatch) && !toolCall.applyPatch.endEmitted) { |
| 2690 | if (!toolCall.applyPatch.hasDiff && Predicate.isNotUndefined(event.delta)) { |
| 2691 | parts.push({ |
| 2692 | type: "tool-params-delta", |
| 2693 | id: toolCall.id, |
| 2694 | delta: InternalUtilities.escapeJSONDelta(event.delta) |
| 2695 | }) |
| 2696 | toolCall.applyPatch.hasDiff = true |
| 2697 | } |
| 2698 | parts.push({ |
| 2699 | type: "tool-params-delta", |
| 2700 | id: toolCall.id, |
| 2701 | delta: `"}}` |
| 2702 | }) |
| 2703 | parts.push({ |
| 2704 | type: "tool-params-end", |
| 2705 | id: toolCall.id |
| 2706 | }) |
| 2707 | toolCall.applyPatch.endEmitted = true |
| 2708 | } |
| 2709 | break |
| 2710 | } |
| 2711 | |
| 2712 | case "response.code_interpreter_call_code.delta": { |
| 2713 | const toolCall = activeToolCalls[event.output_index] |
| 2714 | if (Predicate.isNotUndefined(toolCall?.codeInterpreter)) { |
| 2715 | parts.push({ |
| 2716 | type: "tool-params-delta", |
| 2717 | id: toolCall.id, |
| 2718 | delta: (toolCall.codeInterpreter.hasCode ? "" : "\"") + |
| 2719 | InternalUtilities.escapeJSONDelta(event.delta) |
| 2720 | }) |
| 2721 | toolCall.codeInterpreter.hasCode = true |
| 2722 | toolCall.codeInterpreter.streamedCode += event.delta |
| 2723 | } |
| 2724 | break |
| 2725 | } |
| 2726 | |
| 2727 | case "response.code_interpreter_call_code.done": { |
| 2728 | finishCodeInterpreterCall(event.output_index, event.code, parts) |
| 2729 | break |
| 2730 | } |
| 2731 | |
| 2732 | case "response.image_generation_call.partial_image": { |
| 2733 | const toolName = toolNameMapper.getCustomName("image_generation") |
| 2734 | parts.push({ |
| 2735 | type: "tool-result", |
| 2736 | id: event.item_id, |
| 2737 | name: toolName, |
| 2738 | isFailure: false, |
| 2739 | providerExecuted: false, |
| 2740 | result: { result: event.partial_image_b64 }, |
| 2741 | preliminary: true |
| 2742 | }) |
| 2743 | break |
| 2744 | } |
| 2745 | |
| 2746 | case "response.reasoning_summary_part.added": { |
| 2747 | const reasoningPart = getOrCreateReasoningPart(event.item_id) |
| 2748 | if (event.summary_index > 0) { |
| 2749 | // Conclude all can-conclude parts before starting new one |
| 2750 | for (const [summaryIndex, status] of Object.entries(reasoningPart.summaryParts)) { |
| 2751 | if (status === "can-conclude") { |
| 2752 | parts.push({ |
| 2753 | type: "reasoning-end", |
| 2754 | id: `${event.item_id}:${summaryIndex}`, |
| 2755 | metadata: { |
| 2756 | openai: { |
| 2757 | ...makeItemIdMetadata(event.item_id), |
| 2758 | ...makeEncryptedContentMetadata(reasoningPart.encryptedContent) |
| 2759 | } |
| 2760 | } |
| 2761 | }) |
| 2762 | reasoningPart.summaryParts[Number(summaryIndex)] = "concluded" |
| 2763 | } |
| 2764 | } |
| 2765 | } |
| 2766 | |
| 2767 | if (Predicate.isUndefined(reasoningPart.summaryParts[event.summary_index])) { |
| 2768 | reasoningPart.summaryParts[event.summary_index] = "active" |
| 2769 | parts.push({ |
| 2770 | type: "reasoning-start", |
| 2771 | id: `${event.item_id}:${event.summary_index}`, |
| 2772 | metadata: { |
| 2773 | openai: { |
| 2774 | ...makeItemIdMetadata(event.item_id), |
| 2775 | ...makeEncryptedContentMetadata(reasoningPart.encryptedContent) |
| 2776 | } |
| 2777 | } |
| 2778 | }) |
| 2779 | } |
| 2780 | break |
| 2781 | } |
| 2782 | |
| 2783 | case "response.reasoning_summary_text.delta": { |
| 2784 | parts.push({ |
| 2785 | type: "reasoning-delta", |
| 2786 | id: `${event.item_id}:${event.summary_index}`, |
| 2787 | delta: event.delta, |
| 2788 | metadata: { openai: makeItemIdMetadata(event.item_id) } |
| 2789 | }) |
| 2790 | break |
| 2791 | } |
| 2792 | |
| 2793 | case "response.reasoning_summary_part.done": { |
| 2794 | const reasoningPart = getOrCreateReasoningPart(event.item_id) |
| 2795 | // HTTP requests using stored item references do not need encrypted |
| 2796 | // content, so the reasoning part can be concluded immediately. |
| 2797 | if (!websocketMode && config.store === true && config.useItemReferences !== false) { |
| 2798 | parts.push({ |
| 2799 | type: "reasoning-end", |
| 2800 | id: `${event.item_id}:${event.summary_index}`, |
| 2801 | metadata: { openai: makeItemIdMetadata(event.item_id) } |
| 2802 | }) |
| 2803 | // Mark the summary part concluded |
| 2804 | reasoningPart.summaryParts[event.summary_index] = "concluded" |
| 2805 | } else { |
| 2806 | // Mark the summary part as can-conclude given we still need a |
| 2807 | // final summary part with the encrypted content |
| 2808 | reasoningPart.summaryParts[event.summary_index] = "can-conclude" |
| 2809 | } |
| 2810 | break |
| 2811 | } |
| 2812 | } |
| 2813 | |
| 2814 | return parts |
| 2815 | })), |
| 2816 | Stream.flattenIterable |
| 2817 | ) |
| 2818 | } |
| 2819 | ) |
| 2820 | |
| 2821 | // ============================================================================= |
| 2822 | // Telemetry |
| 2823 | // ============================================================================= |
| 2824 | |
| 2825 | const annotateRequest = ( |
| 2826 | span: Span, |
| 2827 | request: typeof OpenAiSchema.CreateResponse.Encoded |
| 2828 | ): void => { |
| 2829 | addGenAIAnnotations(span, { |
| 2830 | system: "openai", |
| 2831 | operation: { name: "chat" }, |
| 2832 | request: { |
| 2833 | model: request.model as string, |
| 2834 | temperature: request.temperature as number | undefined, |
| 2835 | topP: request.top_p as number | undefined, |
| 2836 | maxTokens: request.max_output_tokens as number | undefined |
| 2837 | }, |
| 2838 | openai: { |
| 2839 | request: { |
| 2840 | responseFormat: (request.text as any)?.format?.type, |
| 2841 | serviceTier: request.service_tier as string | undefined |
| 2842 | } |
| 2843 | } |
| 2844 | }) |
| 2845 | } |
| 2846 | |
| 2847 | const annotateResponse = (span: Span, response: OpenAiSchema.Response): void => { |
| 2848 | const finishReason = response.incomplete_details?.reason as string | undefined |
| 2849 | addGenAIAnnotations(span, { |
| 2850 | response: { |
| 2851 | id: response.id, |
| 2852 | model: response.model as string, |
| 2853 | finishReasons: Predicate.isNotUndefined(finishReason) ? [finishReason] : undefined |
| 2854 | }, |
| 2855 | usage: { |
| 2856 | inputTokens: response.usage?.input_tokens as number | undefined, |
| 2857 | outputTokens: response.usage?.output_tokens as number | undefined |
| 2858 | }, |
| 2859 | openai: { |
| 2860 | response: { |
| 2861 | serviceTier: response.service_tier as string | undefined |
| 2862 | } |
| 2863 | } |
| 2864 | }) |
| 2865 | } |
| 2866 | |
| 2867 | const annotateStreamResponse = (span: Span, part: Response.StreamPartEncoded) => { |
| 2868 | if (part.type === "response-metadata") { |
| 2869 | addGenAIAnnotations(span, { |
| 2870 | response: { |
| 2871 | id: part.id, |
| 2872 | model: part.modelId |
| 2873 | } |
| 2874 | }) |
| 2875 | } |
| 2876 | if (part.type === "finish") { |
| 2877 | const serviceTier = (part.metadata as any)?.openai?.serviceTier as string | undefined |
| 2878 | addGenAIAnnotations(span, { |
| 2879 | response: { |
| 2880 | finishReasons: [part.reason] |
| 2881 | }, |
| 2882 | usage: { |
| 2883 | inputTokens: part.usage.inputTokens.total, |
| 2884 | outputTokens: part.usage.outputTokens.total |
| 2885 | }, |
| 2886 | openai: { |
| 2887 | response: { serviceTier } |
| 2888 | } |
| 2889 | }) |
| 2890 | } |
| 2891 | } |
| 2892 | |
| 2893 | // ============================================================================= |
| 2894 | // Tool Conversion |
| 2895 | // ============================================================================= |
| 2896 | |
| 2897 | type OpenAiToolChoice = typeof OpenAiSchema.CreateResponse.Encoded["tool_choice"] |
| 2898 | |
| 2899 | const prepareTools = Effect.fnUntraced(function*<Tools extends ReadonlyArray<Tool.Any>>({ |
| 2900 | config, |
| 2901 | options, |
| 2902 | toolNameMapper |
| 2903 | }: { |
| 2904 | readonly config: typeof Config.Service |
| 2905 | readonly options: LanguageModel.ProviderOptions |
| 2906 | readonly toolNameMapper: Tool.NameMapper<Tools> |
| 2907 | }): Effect.fn.Return<{ |
| 2908 | readonly tools: ReadonlyArray<typeof OpenAiSchema.Tool.Encoded> | undefined |
| 2909 | readonly toolChoice: OpenAiToolChoice | undefined |
| 2910 | }, AiError.AiError> { |
| 2911 | // Return immediately if no tools are in the toolkit |
| 2912 | if (options.tools.length === 0) { |
| 2913 | return { tools: undefined, toolChoice: undefined } |
| 2914 | } |
| 2915 | |
| 2916 | const tools: Array<typeof OpenAiSchema.Tool.Encoded> = [] |
| 2917 | let toolChoice: OpenAiToolChoice | undefined = undefined |
| 2918 | |
| 2919 | // Filter the incoming tools down to the set of allowed tools as indicated by |
| 2920 | // the tool choice. This must be done here given that there is no tool name |
| 2921 | // in OpenAI's provider-defined tools, so there would be no way to perform |
| 2922 | // this filter otherwise |
| 2923 | let allowedTools = options.tools |
| 2924 | if (typeof options.toolChoice === "object" && "oneOf" in options.toolChoice) { |
| 2925 | const allowedToolNames = new Set(options.toolChoice.oneOf) |
| 2926 | allowedTools = options.tools.filter((tool) => allowedToolNames.has(tool.name)) |
| 2927 | toolChoice = options.toolChoice.mode === "required" ? "required" : "auto" |
| 2928 | } |
| 2929 | |
| 2930 | // Convert the tools in the toolkit to the provider-defined format |
| 2931 | for (const tool of allowedTools) { |
| 2932 | if (Tool.isUserDefined(tool) || Tool.isDynamic(tool)) { |
| 2933 | const strict = Tool.getStrictMode(tool) ?? config.strictJsonSchema ?? true |
| 2934 | const description = Tool.getDescription(tool) |
| 2935 | const parameters = yield* tryToolJsonSchema(tool, "prepareTools") |
| 2936 | tools.push({ |
| 2937 | type: "function", |
| 2938 | name: tool.name, |
| 2939 | parameters, |
| 2940 | strict, |
| 2941 | ...(Predicate.isNotUndefined(description) ? { description } : undefined) |
| 2942 | }) |
| 2943 | } |
| 2944 | |
| 2945 | if (Tool.isProviderDefined(tool)) { |
| 2946 | const openAiTool = tool as OpenAiTool.OpenAiTool |
| 2947 | switch (openAiTool.name) { |
| 2948 | case "OpenAiApplyPatch": { |
| 2949 | tools.push({ type: "apply_patch" }) |
| 2950 | break |
| 2951 | } |
| 2952 | case "OpenAiCodeInterpreter": { |
| 2953 | const args = yield* Schema.decodeUnknownEffect(openAiTool.argsSchema)(tool.args).pipe( |
| 2954 | Effect.mapError((error) => |
| 2955 | AiError.make({ |
| 2956 | module: "OpenAiLanguageModel", |
| 2957 | method: "prepareTools", |
| 2958 | reason: new AiError.ToolConfigurationError({ |
| 2959 | toolName: openAiTool.name, |
| 2960 | description: error.message |
| 2961 | }) |
| 2962 | }) |
| 2963 | ) |
| 2964 | ) |
| 2965 | tools.push({ |
| 2966 | ...args, |
| 2967 | type: "code_interpreter" |
| 2968 | }) |
| 2969 | break |
| 2970 | } |
| 2971 | case "OpenAiFileSearch": { |
| 2972 | const args = yield* Schema.decodeUnknownEffect(openAiTool.argsSchema)(tool.args).pipe( |
| 2973 | Effect.mapError((error) => |
| 2974 | AiError.make({ |
| 2975 | module: "OpenAiLanguageModel", |
| 2976 | method: "prepareTools", |
| 2977 | reason: new AiError.ToolConfigurationError({ |
| 2978 | toolName: openAiTool.name, |
| 2979 | description: error.message |
| 2980 | }) |
| 2981 | }) |
| 2982 | ) |
| 2983 | ) |
| 2984 | tools.push({ |
| 2985 | ...args, |
| 2986 | type: "file_search" |
| 2987 | }) |
| 2988 | break |
| 2989 | } |
| 2990 | case "OpenAiShell": { |
| 2991 | tools.push({ type: "shell" }) |
| 2992 | break |
| 2993 | } |
| 2994 | case "OpenAiImageGeneration": { |
| 2995 | const args = yield* Schema.decodeUnknownEffect(openAiTool.argsSchema)(tool.args).pipe( |
| 2996 | Effect.mapError((error) => |
| 2997 | AiError.make({ |
| 2998 | module: "OpenAiLanguageModel", |
| 2999 | method: "prepareTools", |
| 3000 | reason: new AiError.ToolConfigurationError({ |
| 3001 | toolName: openAiTool.name, |
| 3002 | description: error.message |
| 3003 | }) |
| 3004 | }) |
| 3005 | ) |
| 3006 | ) |
| 3007 | tools.push({ |
| 3008 | ...args, |
| 3009 | type: "image_generation" |
| 3010 | }) |
| 3011 | break |
| 3012 | } |
| 3013 | case "OpenAiLocalShell": { |
| 3014 | tools.push({ type: "local_shell" }) |
| 3015 | break |
| 3016 | } |
| 3017 | case "OpenAiMcp": { |
| 3018 | const args = yield* Schema.decodeUnknownEffect(openAiTool.argsSchema)(tool.args).pipe( |
| 3019 | Effect.mapError((error) => |
| 3020 | AiError.make({ |
| 3021 | module: "OpenAiLanguageModel", |
| 3022 | method: "prepareTools", |
| 3023 | reason: new AiError.ToolConfigurationError({ |
| 3024 | toolName: openAiTool.name, |
| 3025 | description: error.message |
| 3026 | }) |
| 3027 | }) |
| 3028 | ) |
| 3029 | ) |
| 3030 | tools.push({ |
| 3031 | ...args, |
| 3032 | type: "mcp" |
| 3033 | }) |
| 3034 | break |
| 3035 | } |
| 3036 | case "OpenAiWebSearch": { |
| 3037 | const args = yield* Schema.decodeUnknownEffect(openAiTool.argsSchema)(tool.args).pipe( |
| 3038 | Effect.mapError((error) => |
| 3039 | AiError.make({ |
| 3040 | module: "OpenAiLanguageModel", |
| 3041 | method: "prepareTools", |
| 3042 | reason: new AiError.ToolConfigurationError({ |
| 3043 | toolName: openAiTool.name, |
| 3044 | description: error.message |
| 3045 | }) |
| 3046 | }) |
| 3047 | ) |
| 3048 | ) |
| 3049 | tools.push({ |
| 3050 | ...args, |
| 3051 | type: "web_search" |
| 3052 | }) |
| 3053 | break |
| 3054 | } |
| 3055 | case "OpenAiWebSearchPreview": { |
| 3056 | const args = yield* Schema.decodeUnknownEffect(openAiTool.argsSchema)(tool.args).pipe( |
| 3057 | Effect.mapError((error) => |
| 3058 | AiError.make({ |
| 3059 | module: "OpenAiLanguageModel", |
| 3060 | method: "prepareTools", |
| 3061 | reason: new AiError.ToolConfigurationError({ |
| 3062 | toolName: openAiTool.name, |
| 3063 | description: error.message |
| 3064 | }) |
| 3065 | }) |
| 3066 | ) |
| 3067 | ) |
| 3068 | tools.push({ |
| 3069 | ...args, |
| 3070 | type: "web_search_preview" |
| 3071 | }) |
| 3072 | break |
| 3073 | } |
| 3074 | default: { |
| 3075 | return yield* AiError.make({ |
| 3076 | module: "OpenAiLanguageModel", |
| 3077 | method: "prepareTools", |
| 3078 | reason: new AiError.InvalidRequestError({ |
| 3079 | description: `Unknown provider-defined tool '${tool.name}'` |
| 3080 | }) |
| 3081 | }) |
| 3082 | } |
| 3083 | } |
| 3084 | } |
| 3085 | } |
| 3086 | |
| 3087 | if (options.toolChoice === "auto" || options.toolChoice === "none" || options.toolChoice === "required") { |
| 3088 | toolChoice = options.toolChoice |
| 3089 | } |
| 3090 | |
| 3091 | if (typeof options.toolChoice === "object" && "tool" in options.toolChoice) { |
| 3092 | const toolName = toolNameMapper.getProviderName(options.toolChoice.tool) |
| 3093 | const providerNames = toolNameMapper.providerNames |
| 3094 | if (providerNames.includes(toolName)) { |
| 3095 | toolChoice = { type: toolName as any } |
| 3096 | } else { |
| 3097 | toolChoice = { type: "function", name: options.toolChoice.tool } |
| 3098 | } |
| 3099 | } |
| 3100 | |
| 3101 | return { tools, toolChoice } |
| 3102 | }) |
| 3103 | |
| 3104 | // ============================================================================= |
| 3105 | // Utilities |
| 3106 | // ============================================================================= |
| 3107 | |
| 3108 | const isFileId = (data: string, config: typeof Config.Service): boolean => |
| 3109 | config.fileIdPrefixes != null && config.fileIdPrefixes.some((prefix) => data.startsWith(prefix)) |
| 3110 | |
| 3111 | const getItemId = ( |
| 3112 | part: |
| 3113 | | Prompt.TextPart |
| 3114 | | Prompt.ReasoningPart |
| 3115 | | Prompt.ToolCallPart |
| 3116 | | Prompt.ToolResultPart |
| 3117 | ): string | null => part.options.openai?.itemId ?? null |
| 3118 | const getStatus = ( |
| 3119 | part: |
| 3120 | | Prompt.TextPart |
| 3121 | | Prompt.ToolCallPart |
| 3122 | | Prompt.ToolResultPart |
| 3123 | ): typeof OpenAiSchema.MessageStatus.Encoded | null => part.options.openai?.status ?? null |
| 3124 | const getEncryptedContent = ( |
| 3125 | part: Prompt.ReasoningPart |
| 3126 | ): string | null => part.options.openai?.encryptedContent ?? null |
| 3127 | |
| 3128 | const getImageDetail = (part: Prompt.FilePart): ImageDetail => part.options.openai?.imageDetail ?? "auto" |
| 3129 | |
| 3130 | const getPromptCacheBreakpoint = ( |
| 3131 | input: Prompt.SystemMessage | Prompt.TextPart |
| 3132 | ) => { |
| 3133 | const promptCacheBreakpoint = input.options.openai?.promptCacheBreakpoint |
| 3134 | return Predicate.isNotNullish(promptCacheBreakpoint) ? { prompt_cache_breakpoint: promptCacheBreakpoint } : undefined |
| 3135 | } |
| 3136 | |
| 3137 | const makeItemIdMetadata = (itemId: string | undefined) => Predicate.isNotUndefined(itemId) ? { itemId } : {} |
| 3138 | |
| 3139 | const makeEncryptedContentMetadata = (encryptedContent: string | null | undefined) => |
| 3140 | Predicate.isNotNullish(encryptedContent) ? { encryptedContent } : undefined |
| 3141 | |
| 3142 | const unsupportedSchemaError = (error: unknown, method: string): AiError.AiError => |
| 3143 | AiError.make({ |
| 3144 | module: "OpenAiLanguageModel", |
| 3145 | method, |
| 3146 | reason: new AiError.UnsupportedSchemaError({ |
| 3147 | description: error instanceof Error ? error.message : String(error) |
| 3148 | }) |
| 3149 | }) |
| 3150 | |
| 3151 | const tryCodecTransform = <S extends Schema.Constraint>(schema: S, method: string) => |
| 3152 | Effect.try({ |
| 3153 | try: () => toCodecOpenAI(schema), |
| 3154 | catch: (error) => unsupportedSchemaError(error, method) |
| 3155 | }) |
| 3156 | |
| 3157 | const tryJsonSchema = <S extends Schema.Constraint>(schema: S, method: string) => |
| 3158 | Effect.try({ |
| 3159 | try: () => Tool.getJsonSchemaFromSchema(schema, { transformer: toCodecOpenAI }), |
| 3160 | catch: (error) => unsupportedSchemaError(error, method) |
| 3161 | }) |
| 3162 | |
| 3163 | const tryToolJsonSchema = <T extends Tool.Any>(tool: T, method: string) => |
| 3164 | Effect.try({ |
| 3165 | try: () => Tool.getJsonSchema(tool, { transformer: toCodecOpenAI }), |
| 3166 | catch: (error) => unsupportedSchemaError(error, method) |
| 3167 | }) |
| 3168 | |
| 3169 | const prepareResponseFormat = Effect.fnUntraced(function*({ config, options }: { |
| 3170 | readonly config: typeof Config.Service |
| 3171 | readonly options: LanguageModel.ProviderOptions |
| 3172 | }): Effect.fn.Return<typeof OpenAiSchema.TextResponseFormatConfiguration.Encoded, AiError.AiError> { |
| 3173 | if (options.responseFormat.type === "json") { |
| 3174 | const name = options.responseFormat.objectName |
| 3175 | const schema = options.responseFormat.schema |
| 3176 | const jsonSchema = yield* tryJsonSchema(schema, "prepareResponseFormat") |
| 3177 | return { |
| 3178 | type: "json_schema", |
| 3179 | name, |
| 3180 | description: AST.resolveDescription(schema.ast) ?? "Response with a JSON object", |
| 3181 | schema: jsonSchema, |
| 3182 | strict: config.strictJsonSchema ?? true |
| 3183 | } |
| 3184 | } |
| 3185 | return { type: "text" } |
| 3186 | }) |
| 3187 | |
| 3188 | interface ModelCapabilities { |
| 3189 | readonly isReasoningModel: boolean |
| 3190 | readonly systemMessageMode: "remove" | "system" | "developer" |
| 3191 | readonly supportsFlexProcessing: boolean |
| 3192 | readonly supportsPriorityProcessing: boolean |
| 3193 | /** |
| 3194 | * Allow temperature, topP, logProbs when reasoningEffort is none. |
| 3195 | */ |
| 3196 | readonly supportsNonReasoningParameters: boolean |
| 3197 | } |
| 3198 | |
| 3199 | const getModelCapabilities = (modelId: string): ModelCapabilities => { |
| 3200 | const supportsFlexProcessing = modelId.startsWith("o3") || |
| 3201 | modelId.startsWith("o4-mini") || |
| 3202 | (modelId.startsWith("gpt-5") && !modelId.startsWith("gpt-5-chat")) |
| 3203 | |
| 3204 | const supportsPriorityProcessing = modelId.startsWith("gpt-4") || |
| 3205 | modelId.startsWith("gpt-5-mini") || |
| 3206 | (modelId.startsWith("gpt-5") && |
| 3207 | !modelId.startsWith("gpt-5-nano") && |
| 3208 | !modelId.startsWith("gpt-5-chat")) || |
| 3209 | modelId.startsWith("o3") || |
| 3210 | modelId.startsWith("o4-mini") |
| 3211 | |
| 3212 | // Use allowlist approach: only known reasoning models should use 'developer' role |
| 3213 | // This prevents issues with fine-tuned models, third-party models, and custom models |
| 3214 | const isReasoningModel = modelId.startsWith("o1") || |
| 3215 | modelId.startsWith("o3") || |
| 3216 | modelId.startsWith("o4-mini") || |
| 3217 | modelId.startsWith("codex-mini") || |
| 3218 | modelId.startsWith("computer-use-preview") || |
| 3219 | (modelId.startsWith("gpt-5") && !modelId.startsWith("gpt-5-chat")) |
| 3220 | |
| 3221 | // https://platform.openai.com/docs/guides/latest-model#gpt-5-1-parameter-compatibility |
| 3222 | // GPT-5.1 and GPT-5.2 support temperature, topP, logProbs when reasoningEffort is none |
| 3223 | const supportsNonReasoningParameters = modelId.startsWith("gpt-5.1") || modelId.startsWith("gpt-5.2") |
| 3224 | |
| 3225 | const systemMessageMode = isReasoningModel ? "developer" : "system" |
| 3226 | |
| 3227 | return { |
| 3228 | supportsFlexProcessing, |
| 3229 | supportsPriorityProcessing, |
| 3230 | isReasoningModel, |
| 3231 | systemMessageMode, |
| 3232 | supportsNonReasoningParameters |
| 3233 | } |
| 3234 | } |
| 3235 | |
| 3236 | const getApprovalRequestIdMapping = (prompt: Prompt.Prompt): ReadonlyMap<string, string> => { |
| 3237 | const mapping = new Map<string, string>() |
| 3238 | |
| 3239 | for (const message of prompt.content) { |
| 3240 | if (message.role !== "assistant") { |
| 3241 | continue |
| 3242 | } |
| 3243 | |
| 3244 | for (const part of message.content) { |
| 3245 | if (part.type !== "tool-call") { |
| 3246 | continue |
| 3247 | } |
| 3248 | |
| 3249 | const approvalRequestId = part.options.openai?.approvalRequestId |
| 3250 | |
| 3251 | if (Predicate.isNotNullish(approvalRequestId)) { |
| 3252 | mapping.set(approvalRequestId, part.id) |
| 3253 | } |
| 3254 | } |
| 3255 | } |
| 3256 | |
| 3257 | return mapping |
| 3258 | } |
| 3259 | |
| 3260 | const normalizeMcpToolCall = Effect.fnUntraced(function*<Tools extends ReadonlyArray<Tool.Any>>({ |
| 3261 | toolNameMapper, |
| 3262 | toolParams, |
| 3263 | method |
| 3264 | }: { |
| 3265 | readonly toolNameMapper: Tool.NameMapper<Tools> |
| 3266 | readonly toolParams: unknown |
| 3267 | readonly method: string |
| 3268 | }): Effect.fn.Return<{ |
| 3269 | readonly toolName: string |
| 3270 | readonly params: unknown |
| 3271 | }, AiError.AiError> { |
| 3272 | const toolName = toolNameMapper.getCustomName("mcp") |
| 3273 | |
| 3274 | if (typeof toolParams !== "string") { |
| 3275 | return { toolName, params: toolParams } |
| 3276 | } |
| 3277 | |
| 3278 | const params = yield* Effect.try({ |
| 3279 | try: () => Tool.unsafeSecureJsonParse(toolParams), |
| 3280 | catch: (cause) => |
| 3281 | AiError.make({ |
| 3282 | module: "OpenAiLanguageModel", |
| 3283 | method, |
| 3284 | reason: new AiError.ToolParameterValidationError({ |
| 3285 | toolName, |
| 3286 | description: `Failed to securely JSON parse tool parameters: ${cause}` |
| 3287 | }) |
| 3288 | }) |
| 3289 | }) |
| 3290 | |
| 3291 | return { toolName, params } |
| 3292 | }) |
| 3293 | |
| 3294 | const getUsage = (usage: OpenAiSchema.ResponseUsage | null | undefined): Response.Usage => { |
| 3295 | if (Predicate.isNullish(usage)) { |
| 3296 | return { |
| 3297 | inputTokens: { |
| 3298 | uncached: undefined, |
| 3299 | total: undefined, |
| 3300 | cacheRead: undefined, |
| 3301 | cacheWrite: undefined |
| 3302 | }, |
| 3303 | outputTokens: { |
| 3304 | total: undefined, |
| 3305 | text: undefined, |
| 3306 | reasoning: undefined |
| 3307 | } |
| 3308 | } |
| 3309 | } |
| 3310 | |
| 3311 | const inputTokens = usage.input_tokens |
| 3312 | const outputTokens = usage.output_tokens |
| 3313 | const cachedTokens = getUsageTokenDetail(usage.input_tokens_details, "cached_tokens") ?? 0 |
| 3314 | const cacheWriteTokens = getUsageTokenDetail(usage.input_tokens_details, "cache_write_tokens") |
| 3315 | const reasoningTokens = getUsageTokenDetail(usage.output_tokens_details, "reasoning_tokens") ?? 0 |
| 3316 | |
| 3317 | return { |
| 3318 | inputTokens: { |
| 3319 | uncached: inputTokens - cachedTokens, |
| 3320 | total: inputTokens, |
| 3321 | cacheRead: cachedTokens, |
| 3322 | cacheWrite: cacheWriteTokens |
| 3323 | }, |
| 3324 | outputTokens: { |
| 3325 | total: outputTokens, |
| 3326 | text: outputTokens - reasoningTokens, |
| 3327 | reasoning: reasoningTokens |
| 3328 | } |
| 3329 | } |
| 3330 | } |
| 3331 | |
| 3332 | type ServiceTier = "default" | "auto" | "flex" | "scale" | "priority" | null |
| 3333 | |
| 3334 | const toFinishMetadata = (response: OpenAiSchema.Response): { |
| 3335 | readonly metadata: Response.FinishPartMetadata |
| 3336 | } | undefined => { |
| 3337 | let serviceTier: ServiceTier | undefined |
| 3338 | switch (response.service_tier) { |
| 3339 | case "default": |
| 3340 | case "auto": |
| 3341 | case "flex": |
| 3342 | case "scale": |
| 3343 | case "priority": |
| 3344 | serviceTier = response.service_tier |
| 3345 | break |
| 3346 | } |
| 3347 | |
| 3348 | const promptCacheDiagnostics = response.prompt_cache_diagnostics |
| 3349 | if (serviceTier === undefined && promptCacheDiagnostics === undefined) { |
| 3350 | return undefined |
| 3351 | } |
| 3352 | |
| 3353 | return { |
| 3354 | metadata: { |
| 3355 | openai: { |
| 3356 | ...(serviceTier === undefined ? undefined : { serviceTier }), |
| 3357 | ...(promptCacheDiagnostics === undefined ? undefined : { promptCacheDiagnostics }) |
| 3358 | } |
| 3359 | } |
| 3360 | } |
| 3361 | } |
| 3362 | |
| 3363 | const getUsageTokenDetail = (details: unknown, key: string): number | undefined => |
| 3364 | Predicate.hasProperty(details, key) && typeof details[key] === "number" ? details[key] : undefined |
| 3365 | |
| 3366 | const transformToolCallParams = Effect.fnUntraced(function*<Tools extends ReadonlyArray<Tool.Any>>( |
| 3367 | tools: Tools, |
| 3368 | toolName: string, |
| 3369 | toolParams: unknown |
| 3370 | ): Effect.fn.Return<unknown, AiError.AiError> { |
| 3371 | const tool = tools.find((tool) => tool.name === toolName) |
| 3372 | |
| 3373 | if (Predicate.isUndefined(tool)) { |
| 3374 | return yield* AiError.make({ |
| 3375 | module: "OpenAiLanguageModel", |
| 3376 | method: "makeResponse", |
| 3377 | reason: new AiError.ToolNotFoundError({ |
| 3378 | toolName, |
| 3379 | availableTools: tools.map((tool) => tool.name) |
| 3380 | }) |
| 3381 | }) |
| 3382 | } |
| 3383 | |
| 3384 | if (Tool.isDynamic(tool) && tool.jsonSchema !== undefined) { |
| 3385 | return toolParams |
| 3386 | } |
| 3387 | |
| 3388 | const { codec } = yield* tryCodecTransform(tool.parametersSchema, "makeResponse") |
| 3389 | |
| 3390 | // Normalize valid parameters; leave invalid ones for Toolkit. |
| 3391 | return yield* ( |
| 3392 | Schema.decodeEffect(codec)(toolParams) as Effect.Effect<unknown, Schema.SchemaError> |
| 3393 | ).pipe( |
| 3394 | Effect.flatMap((decoded) => |
| 3395 | Schema.encodeUnknownEffect(tool.parametersSchema)(decoded) as Effect.Effect<unknown, Schema.SchemaError> |
| 3396 | ), |
| 3397 | Effect.orElseSucceed(() => toolParams) |
| 3398 | ) |
| 3399 | }) |