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refactor(ai): share openai responses logic
This commit is contained in:
Markus Ylisiurunen
Mario Zechner
parent
085c378d34
commit
284ff81035
3 changed files with 445 additions and 888 deletions
426
packages/ai/src/providers/openai-responses-shared.ts
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426
packages/ai/src/providers/openai-responses-shared.ts
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@ -0,0 +1,426 @@
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import type OpenAI from "openai";
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import type {
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Tool as OpenAITool,
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ResponseCreateParamsStreaming,
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ResponseFunctionToolCall,
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ResponseInput,
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ResponseInputContent,
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ResponseInputImage,
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ResponseInputText,
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ResponseOutputMessage,
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ResponseReasoningItem,
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ResponseStreamEvent,
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} from "openai/resources/responses/responses.js";
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import { calculateCost } from "../models.js";
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import type {
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Api,
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AssistantMessage,
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Context,
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ImageContent,
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Model,
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StopReason,
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TextContent,
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ThinkingContent,
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Tool,
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ToolCall,
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Usage,
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} from "../types.js";
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import type { AssistantMessageEventStream } from "../utils/event-stream.js";
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import { parseStreamingJson } from "../utils/json-parse.js";
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import { sanitizeSurrogates } from "../utils/sanitize-unicode.js";
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import { transformMessages } from "./transform-messages.js";
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/** Fast deterministic hash to shorten long strings */
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function shortHash(str: string): string {
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let h1 = 0xdeadbeef;
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let h2 = 0x41c6ce57;
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for (let i = 0; i < str.length; i++) {
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const ch = str.charCodeAt(i);
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h1 = Math.imul(h1 ^ ch, 2654435761);
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h2 = Math.imul(h2 ^ ch, 1597334677);
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}
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h1 = Math.imul(h1 ^ (h1 >>> 16), 2246822507) ^ Math.imul(h2 ^ (h2 >>> 13), 3266489909);
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h2 = Math.imul(h2 ^ (h2 >>> 16), 2246822507) ^ Math.imul(h1 ^ (h1 >>> 13), 3266489909);
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return (h2 >>> 0).toString(36) + (h1 >>> 0).toString(36);
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}
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export interface OpenAIResponsesStreamOptions {
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serviceTier?: ResponseCreateParamsStreaming["service_tier"];
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applyServiceTierPricing?: (
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usage: Usage,
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serviceTier: ResponseCreateParamsStreaming["service_tier"] | undefined,
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) => void;
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}
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export function convertResponsesMessages<TApi extends Api>(
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model: Model<TApi>,
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context: Context,
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allowedToolCallProviders: ReadonlySet<string>,
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): ResponseInput {
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const messages: ResponseInput = [];
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const normalizeToolCallId = (id: string): string => {
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if (!allowedToolCallProviders.has(model.provider)) return id;
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if (!id.includes("|")) return id;
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const [callId, itemId] = id.split("|");
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const sanitizedCallId = callId.replace(/[^a-zA-Z0-9_-]/g, "_");
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let sanitizedItemId = itemId.replace(/[^a-zA-Z0-9_-]/g, "_");
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// OpenAI Responses API requires item id to start with "fc"
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if (!sanitizedItemId.startsWith("fc")) {
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sanitizedItemId = `fc_${sanitizedItemId}`;
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}
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const normalizedCallId = sanitizedCallId.length > 64 ? sanitizedCallId.slice(0, 64) : sanitizedCallId;
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const normalizedItemId = sanitizedItemId.length > 64 ? sanitizedItemId.slice(0, 64) : sanitizedItemId;
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return `${normalizedCallId}|${normalizedItemId}`;
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};
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const transformedMessages = transformMessages(context.messages, model, normalizeToolCallId);
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if (context.systemPrompt) {
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const role = model.reasoning ? "developer" : "system";
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messages.push({
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role,
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content: sanitizeSurrogates(context.systemPrompt),
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});
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}
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let msgIndex = 0;
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for (const msg of transformedMessages) {
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if (msg.role === "user") {
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if (typeof msg.content === "string") {
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messages.push({
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role: "user",
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content: [{ type: "input_text", text: sanitizeSurrogates(msg.content) }],
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});
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} else {
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const content: ResponseInputContent[] = msg.content.map((item): ResponseInputContent => {
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if (item.type === "text") {
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return {
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type: "input_text",
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text: sanitizeSurrogates(item.text),
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} satisfies ResponseInputText;
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}
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return {
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type: "input_image",
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detail: "auto",
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image_url: `data:${item.mimeType};base64,${item.data}`,
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} satisfies ResponseInputImage;
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});
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const filteredContent = !model.input.includes("image")
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? content.filter((c) => c.type !== "input_image")
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: content;
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if (filteredContent.length === 0) continue;
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messages.push({
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role: "user",
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content: filteredContent,
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});
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}
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} else if (msg.role === "assistant") {
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const output: ResponseInput = [];
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for (const block of msg.content) {
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if (block.type === "thinking") {
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if (block.thinkingSignature) {
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const reasoningItem = JSON.parse(block.thinkingSignature) as ResponseReasoningItem;
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output.push(reasoningItem);
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}
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} else if (block.type === "text") {
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const textBlock = block as TextContent;
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// OpenAI requires id to be max 64 characters
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let msgId = textBlock.textSignature;
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if (!msgId) {
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msgId = `msg_${msgIndex}`;
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} else if (msgId.length > 64) {
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msgId = `msg_${shortHash(msgId)}`;
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}
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output.push({
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type: "message",
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role: "assistant",
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content: [{ type: "output_text", text: sanitizeSurrogates(textBlock.text), annotations: [] }],
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status: "completed",
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id: msgId,
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} satisfies ResponseOutputMessage);
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} else if (block.type === "toolCall") {
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const toolCall = block as ToolCall;
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const [callId, itemId] = toolCall.id.split("|");
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output.push({
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type: "function_call",
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id: itemId,
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call_id: callId,
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name: toolCall.name,
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arguments: JSON.stringify(toolCall.arguments),
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});
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}
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}
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if (output.length === 0) continue;
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messages.push(...output);
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} else if (msg.role === "toolResult") {
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// Extract text and image content
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const textResult = msg.content
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.filter((c): c is TextContent => c.type === "text")
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.map((c) => c.text)
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.join("\n");
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const hasImages = msg.content.some((c): c is ImageContent => c.type === "image");
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// Always send function_call_output with text (or placeholder if only images)
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const hasText = textResult.length > 0;
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const [callId] = msg.toolCallId.split("|");
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messages.push({
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type: "function_call_output",
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call_id: callId,
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output: sanitizeSurrogates(hasText ? textResult : "(see attached image)"),
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});
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// If there are images and model supports them, send a follow-up user message with images
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if (hasImages && model.input.includes("image")) {
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const contentParts: ResponseInputContent[] = [];
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// Add text prefix
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contentParts.push({
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type: "input_text",
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text: "Attached image(s) from tool result:",
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} satisfies ResponseInputText);
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// Add images
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for (const block of msg.content) {
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if (block.type === "image") {
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contentParts.push({
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type: "input_image",
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detail: "auto",
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image_url: `data:${block.mimeType};base64,${block.data}`,
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} satisfies ResponseInputImage);
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}
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}
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messages.push({
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role: "user",
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content: contentParts,
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});
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}
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}
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msgIndex++;
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}
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return messages;
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}
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export function convertResponsesTools(tools: Tool[]): OpenAITool[] {
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return tools.map((tool) => ({
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type: "function",
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name: tool.name,
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description: tool.description,
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parameters: tool.parameters as any, // TypeBox already generates JSON Schema
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strict: false,
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}));
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}
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export async function processResponsesStream<TApi extends Api>(
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openaiStream: AsyncIterable<ResponseStreamEvent>,
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output: AssistantMessage,
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stream: AssistantMessageEventStream,
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model: Model<TApi>,
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options?: OpenAIResponsesStreamOptions,
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): Promise<void> {
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let currentItem: ResponseReasoningItem | ResponseOutputMessage | ResponseFunctionToolCall | null = null;
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let currentBlock: ThinkingContent | TextContent | (ToolCall & { partialJson: string }) | null = null;
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const blocks = output.content;
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const blockIndex = () => blocks.length - 1;
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for await (const event of openaiStream) {
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if (event.type === "response.output_item.added") {
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const item = event.item;
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if (item.type === "reasoning") {
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currentItem = item;
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currentBlock = { type: "thinking", thinking: "" };
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output.content.push(currentBlock);
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stream.push({ type: "thinking_start", contentIndex: blockIndex(), partial: output });
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} else if (item.type === "message") {
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currentItem = item;
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currentBlock = { type: "text", text: "" };
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output.content.push(currentBlock);
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stream.push({ type: "text_start", contentIndex: blockIndex(), partial: output });
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} else if (item.type === "function_call") {
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currentItem = item;
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currentBlock = {
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type: "toolCall",
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id: `${item.call_id}|${item.id}`,
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name: item.name,
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arguments: {},
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partialJson: item.arguments || "",
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};
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output.content.push(currentBlock);
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stream.push({ type: "toolcall_start", contentIndex: blockIndex(), partial: output });
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}
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} else if (event.type === "response.reasoning_summary_part.added") {
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if (currentItem && currentItem.type === "reasoning") {
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currentItem.summary = currentItem.summary || [];
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currentItem.summary.push(event.part);
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}
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} else if (event.type === "response.reasoning_summary_text.delta") {
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if (currentItem?.type === "reasoning" && currentBlock?.type === "thinking") {
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currentItem.summary = currentItem.summary || [];
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const lastPart = currentItem.summary[currentItem.summary.length - 1];
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if (lastPart) {
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currentBlock.thinking += event.delta;
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lastPart.text += event.delta;
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stream.push({
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type: "thinking_delta",
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contentIndex: blockIndex(),
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delta: event.delta,
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partial: output,
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});
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}
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}
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} else if (event.type === "response.reasoning_summary_part.done") {
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if (currentItem?.type === "reasoning" && currentBlock?.type === "thinking") {
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currentItem.summary = currentItem.summary || [];
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const lastPart = currentItem.summary[currentItem.summary.length - 1];
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if (lastPart) {
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currentBlock.thinking += "\n\n";
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lastPart.text += "\n\n";
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stream.push({
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type: "thinking_delta",
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contentIndex: blockIndex(),
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delta: "\n\n",
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partial: output,
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});
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}
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}
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} else if (event.type === "response.content_part.added") {
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if (currentItem?.type === "message") {
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currentItem.content = currentItem.content || [];
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// Filter out ReasoningText, only accept output_text and refusal
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if (event.part.type === "output_text" || event.part.type === "refusal") {
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currentItem.content.push(event.part);
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}
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}
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} else if (event.type === "response.output_text.delta") {
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if (currentItem?.type === "message" && currentBlock?.type === "text") {
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if (!currentItem.content || currentItem.content.length === 0) {
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continue;
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}
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const lastPart = currentItem.content[currentItem.content.length - 1];
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if (lastPart?.type === "output_text") {
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currentBlock.text += event.delta;
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lastPart.text += event.delta;
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stream.push({
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type: "text_delta",
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contentIndex: blockIndex(),
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delta: event.delta,
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partial: output,
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});
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}
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}
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} else if (event.type === "response.refusal.delta") {
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if (currentItem?.type === "message" && currentBlock?.type === "text") {
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if (!currentItem.content || currentItem.content.length === 0) {
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continue;
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}
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const lastPart = currentItem.content[currentItem.content.length - 1];
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if (lastPart?.type === "refusal") {
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currentBlock.text += event.delta;
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lastPart.refusal += event.delta;
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stream.push({
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type: "text_delta",
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contentIndex: blockIndex(),
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delta: event.delta,
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partial: output,
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});
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}
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}
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} else if (event.type === "response.function_call_arguments.delta") {
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if (currentItem?.type === "function_call" && currentBlock?.type === "toolCall") {
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currentBlock.partialJson += event.delta;
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currentBlock.arguments = parseStreamingJson(currentBlock.partialJson);
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stream.push({
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type: "toolcall_delta",
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contentIndex: blockIndex(),
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delta: event.delta,
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partial: output,
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});
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}
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} else if (event.type === "response.output_item.done") {
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const item = event.item;
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if (item.type === "reasoning" && currentBlock?.type === "thinking") {
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currentBlock.thinking = item.summary?.map((s) => s.text).join("\n\n") || "";
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currentBlock.thinkingSignature = JSON.stringify(item);
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stream.push({
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type: "thinking_end",
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contentIndex: blockIndex(),
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content: currentBlock.thinking,
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partial: output,
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});
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currentBlock = null;
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} else if (item.type === "message" && currentBlock?.type === "text") {
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currentBlock.text = item.content.map((c) => (c.type === "output_text" ? c.text : c.refusal)).join("");
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currentBlock.textSignature = item.id;
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stream.push({
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type: "text_end",
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contentIndex: blockIndex(),
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content: currentBlock.text,
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partial: output,
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});
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currentBlock = null;
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} else if (item.type === "function_call") {
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const toolCall: ToolCall = {
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type: "toolCall",
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id: `${item.call_id}|${item.id}`,
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name: item.name,
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arguments: JSON.parse(item.arguments),
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};
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stream.push({ type: "toolcall_end", contentIndex: blockIndex(), toolCall, partial: output });
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}
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} else if (event.type === "response.completed") {
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const response = event.response;
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if (response?.usage) {
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const cachedTokens = response.usage.input_tokens_details?.cached_tokens || 0;
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output.usage = {
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// OpenAI includes cached tokens in input_tokens, so subtract to get non-cached input
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input: (response.usage.input_tokens || 0) - cachedTokens,
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output: response.usage.output_tokens || 0,
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cacheRead: cachedTokens,
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cacheWrite: 0,
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totalTokens: response.usage.total_tokens || 0,
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cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
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};
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}
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calculateCost(model, output.usage);
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if (options?.applyServiceTierPricing) {
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const serviceTier = response?.service_tier ?? options.serviceTier;
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options.applyServiceTierPricing(output.usage, serviceTier);
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}
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// Map status to stop reason
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output.stopReason = mapStopReason(response?.status);
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if (output.content.some((b) => b.type === "toolCall") && output.stopReason === "stop") {
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output.stopReason = "toolUse";
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}
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} else if (event.type === "error") {
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throw new Error(`Error Code ${event.code}: ${event.message}` || "Unknown error");
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} else if (event.type === "response.failed") {
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throw new Error("Unknown error");
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}
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}
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}
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function mapStopReason(status: OpenAI.Responses.ResponseStatus | undefined): StopReason {
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if (!status) return "stop";
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switch (status) {
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case "completed":
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return "stop";
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case "incomplete":
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return "length";
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case "failed":
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case "cancelled":
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return "error";
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// These two are wonky ...
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case "in_progress":
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case "queued":
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return "stop";
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default: {
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const _exhaustive: never = status;
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throw new Error(`Unhandled stop reason: ${_exhaustive}`);
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}
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}
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}
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