mirror of
https://gitea.toothfairyai.com/ToothFairyAI/tf_code.git
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feat(opencode): add copilot specific provider to properly handle copilot reasoning tokens (#8900)
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com> Co-authored-by: Aiden Cline <63023139+rekram1-node@users.noreply.github.com> Co-authored-by: Aiden Cline <aidenpcline@gmail.com>
This commit is contained in:
@@ -24,7 +24,7 @@ import { createVertexAnthropic } from "@ai-sdk/google-vertex/anthropic"
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import { createOpenAI } from "@ai-sdk/openai"
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import { createOpenAICompatible } from "@ai-sdk/openai-compatible"
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import { createOpenRouter, type LanguageModelV2 } from "@openrouter/ai-sdk-provider"
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import { createOpenaiCompatible as createGitHubCopilotOpenAICompatible } from "./sdk/openai-compatible/src"
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import { createOpenaiCompatible as createGitHubCopilotOpenAICompatible } from "./sdk/copilot"
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import { createXai } from "@ai-sdk/xai"
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import { createMistral } from "@ai-sdk/mistral"
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import { createGroq } from "@ai-sdk/groq"
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@@ -0,0 +1,177 @@
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import {
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type LanguageModelV2Prompt,
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type SharedV2ProviderMetadata,
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UnsupportedFunctionalityError,
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} from '@ai-sdk/provider';
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import type { OpenAICompatibleChatPrompt } from './openai-compatible-api-types';
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import { convertToBase64 } from '@ai-sdk/provider-utils';
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function getOpenAIMetadata(message: {
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providerOptions?: SharedV2ProviderMetadata;
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}) {
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return message?.providerOptions?.copilot ?? {};
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}
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export function convertToOpenAICompatibleChatMessages(
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prompt: LanguageModelV2Prompt,
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): OpenAICompatibleChatPrompt {
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const messages: OpenAICompatibleChatPrompt = [];
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for (const { role, content, ...message } of prompt) {
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const metadata = getOpenAIMetadata({ ...message });
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switch (role) {
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case 'system': {
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messages.push({
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role: 'system',
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content: [
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{
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type: 'text',
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text: content,
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},
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],
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...metadata,
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});
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break;
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}
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case 'user': {
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if (content.length === 1 && content[0].type === 'text') {
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messages.push({
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role: 'user',
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content: content[0].text,
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...getOpenAIMetadata(content[0]),
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});
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break;
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}
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messages.push({
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role: 'user',
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content: content.map(part => {
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const partMetadata = getOpenAIMetadata(part);
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switch (part.type) {
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case 'text': {
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return { type: 'text', text: part.text, ...partMetadata };
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}
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case 'file': {
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if (part.mediaType.startsWith('image/')) {
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const mediaType =
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part.mediaType === 'image/*'
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? 'image/jpeg'
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: part.mediaType;
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return {
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type: 'image_url',
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image_url: {
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url:
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part.data instanceof URL
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? part.data.toString()
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: `data:${mediaType};base64,${convertToBase64(part.data)}`,
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},
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...partMetadata,
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};
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} else {
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throw new UnsupportedFunctionalityError({
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functionality: `file part media type ${part.mediaType}`,
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});
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}
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}
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}
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}),
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...metadata,
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});
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break;
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}
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case 'assistant': {
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let text = '';
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let reasoningText: string | undefined;
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let reasoningOpaque: string | undefined;
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const toolCalls: Array<{
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id: string;
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type: 'function';
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function: { name: string; arguments: string };
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}> = [];
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for (const part of content) {
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const partMetadata = getOpenAIMetadata(part);
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// Check for reasoningOpaque on any part (may be attached to text/tool-call)
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const partOpaque = (
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part.providerOptions as { copilot?: { reasoningOpaque?: string } }
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)?.copilot?.reasoningOpaque;
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if (partOpaque && !reasoningOpaque) {
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reasoningOpaque = partOpaque;
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}
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switch (part.type) {
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case 'text': {
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text += part.text;
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break;
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}
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case 'reasoning': {
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reasoningText = part.text;
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break;
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}
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case 'tool-call': {
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toolCalls.push({
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id: part.toolCallId,
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type: 'function',
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function: {
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name: part.toolName,
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arguments: JSON.stringify(part.input),
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},
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...partMetadata,
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});
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break;
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}
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}
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}
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messages.push({
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role: 'assistant',
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content: text || null,
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tool_calls: toolCalls.length > 0 ? toolCalls : undefined,
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reasoning_text: reasoningText,
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reasoning_opaque: reasoningOpaque,
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...metadata,
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});
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break;
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}
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case 'tool': {
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for (const toolResponse of content) {
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const output = toolResponse.output;
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let contentValue: string;
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switch (output.type) {
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case 'text':
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case 'error-text':
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contentValue = output.value;
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break;
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case 'content':
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case 'json':
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case 'error-json':
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contentValue = JSON.stringify(output.value);
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break;
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}
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const toolResponseMetadata = getOpenAIMetadata(toolResponse);
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messages.push({
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role: 'tool',
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tool_call_id: toolResponse.toolCallId,
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content: contentValue,
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...toolResponseMetadata,
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});
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}
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break;
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}
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default: {
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const _exhaustiveCheck: never = role;
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throw new Error(`Unsupported role: ${_exhaustiveCheck}`);
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}
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}
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}
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return messages;
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}
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@@ -0,0 +1,15 @@
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export function getResponseMetadata({
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id,
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model,
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created,
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}: {
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id?: string | undefined | null;
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created?: number | undefined | null;
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model?: string | undefined | null;
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}) {
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return {
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id: id ?? undefined,
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modelId: model ?? undefined,
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timestamp: created != null ? new Date(created * 1000) : undefined,
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};
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}
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@@ -0,0 +1,19 @@
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import type { LanguageModelV2FinishReason } from '@ai-sdk/provider';
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export function mapOpenAICompatibleFinishReason(
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finishReason: string | null | undefined,
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): LanguageModelV2FinishReason {
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switch (finishReason) {
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case 'stop':
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return 'stop';
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case 'length':
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return 'length';
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case 'content_filter':
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return 'content-filter';
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case 'function_call':
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case 'tool_calls':
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return 'tool-calls';
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default:
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return 'unknown';
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}
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}
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@@ -0,0 +1,74 @@
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import type { JSONValue } from '@ai-sdk/provider';
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export type OpenAICompatibleChatPrompt = Array<OpenAICompatibleMessage>;
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export type OpenAICompatibleMessage =
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| OpenAICompatibleSystemMessage
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| OpenAICompatibleUserMessage
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| OpenAICompatibleAssistantMessage
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| OpenAICompatibleToolMessage;
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// Allow for arbitrary additional properties for general purpose
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// provider-metadata-specific extensibility.
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type JsonRecord<T = never> = Record<
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string,
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JSONValue | JSONValue[] | T | T[] | undefined
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>;
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export interface OpenAICompatibleSystemMessage
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extends JsonRecord<OpenAICompatibleSystemContentPart> {
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role: 'system';
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content: string | Array<OpenAICompatibleSystemContentPart>;
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}
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export interface OpenAICompatibleSystemContentPart
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extends JsonRecord {
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type: 'text';
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text: string;
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}
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export interface OpenAICompatibleUserMessage
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extends JsonRecord<OpenAICompatibleContentPart> {
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role: 'user';
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content: string | Array<OpenAICompatibleContentPart>;
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}
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export type OpenAICompatibleContentPart =
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| OpenAICompatibleContentPartText
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| OpenAICompatibleContentPartImage;
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export interface OpenAICompatibleContentPartImage extends JsonRecord {
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type: 'image_url';
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image_url: { url: string };
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}
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export interface OpenAICompatibleContentPartText extends JsonRecord {
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type: 'text';
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text: string;
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}
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export interface OpenAICompatibleAssistantMessage
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extends JsonRecord<OpenAICompatibleMessageToolCall> {
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role: 'assistant';
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content?: string | null;
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tool_calls?: Array<OpenAICompatibleMessageToolCall>;
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// Copilot-specific reasoning fields
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reasoning_text?: string;
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reasoning_opaque?: string;
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}
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export interface OpenAICompatibleMessageToolCall extends JsonRecord {
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type: 'function';
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id: string;
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function: {
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arguments: string;
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name: string;
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};
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}
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export interface OpenAICompatibleToolMessage
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extends JsonRecord {
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role: 'tool';
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content: string;
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tool_call_id: string;
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}
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@@ -0,0 +1,832 @@
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import {
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APICallError,
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InvalidResponseDataError,
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type LanguageModelV2,
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type LanguageModelV2CallWarning,
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type LanguageModelV2Content,
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type LanguageModelV2FinishReason,
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type LanguageModelV2StreamPart,
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type SharedV2ProviderMetadata,
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} from '@ai-sdk/provider';
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import {
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combineHeaders,
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createEventSourceResponseHandler,
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createJsonErrorResponseHandler,
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createJsonResponseHandler,
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type FetchFunction,
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generateId,
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isParsableJson,
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parseProviderOptions,
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type ParseResult,
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postJsonToApi,
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type ResponseHandler,
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} from '@ai-sdk/provider-utils';
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import { z } from 'zod/v4';
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import { convertToOpenAICompatibleChatMessages } from './convert-to-openai-compatible-chat-messages';
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import { getResponseMetadata } from './get-response-metadata';
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import { mapOpenAICompatibleFinishReason } from './map-openai-compatible-finish-reason';
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import {
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type OpenAICompatibleChatModelId,
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openaiCompatibleProviderOptions,
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} from './openai-compatible-chat-options';
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import {
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defaultOpenAICompatibleErrorStructure,
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type ProviderErrorStructure,
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} from '../openai-compatible-error';
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import type { MetadataExtractor } from './openai-compatible-metadata-extractor';
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import { prepareTools } from './openai-compatible-prepare-tools';
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export type OpenAICompatibleChatConfig = {
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provider: string;
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headers: () => Record<string, string | undefined>;
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url: (options: { modelId: string; path: string }) => string;
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fetch?: FetchFunction;
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includeUsage?: boolean;
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errorStructure?: ProviderErrorStructure<any>;
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metadataExtractor?: MetadataExtractor;
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/**
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* Whether the model supports structured outputs.
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*/
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supportsStructuredOutputs?: boolean;
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/**
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* The supported URLs for the model.
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*/
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supportedUrls?: () => LanguageModelV2['supportedUrls'];
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};
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export class OpenAICompatibleChatLanguageModel implements LanguageModelV2 {
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readonly specificationVersion = 'v2';
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readonly supportsStructuredOutputs: boolean;
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readonly modelId: OpenAICompatibleChatModelId;
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private readonly config: OpenAICompatibleChatConfig;
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private readonly failedResponseHandler: ResponseHandler<APICallError>;
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private readonly chunkSchema; // type inferred via constructor
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constructor(
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modelId: OpenAICompatibleChatModelId,
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config: OpenAICompatibleChatConfig,
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) {
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this.modelId = modelId;
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this.config = config;
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// initialize error handling:
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const errorStructure =
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config.errorStructure ?? defaultOpenAICompatibleErrorStructure;
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this.chunkSchema = createOpenAICompatibleChatChunkSchema(
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errorStructure.errorSchema,
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);
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this.failedResponseHandler = createJsonErrorResponseHandler(errorStructure);
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this.supportsStructuredOutputs = config.supportsStructuredOutputs ?? false;
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}
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get provider(): string {
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return this.config.provider;
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}
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private get providerOptionsName(): string {
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return this.config.provider.split('.')[0].trim();
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}
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get supportedUrls() {
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return this.config.supportedUrls?.() ?? {};
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}
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private async getArgs({
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prompt,
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maxOutputTokens,
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temperature,
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topP,
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topK,
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frequencyPenalty,
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presencePenalty,
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providerOptions,
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stopSequences,
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responseFormat,
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seed,
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toolChoice,
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tools,
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}: Parameters<LanguageModelV2['doGenerate']>[0]) {
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const warnings: LanguageModelV2CallWarning[] = [];
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// Parse provider options
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const compatibleOptions = Object.assign(
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(await parseProviderOptions({
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provider: 'copilot',
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providerOptions,
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schema: openaiCompatibleProviderOptions,
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})) ?? {},
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(await parseProviderOptions({
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provider: this.providerOptionsName,
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providerOptions,
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schema: openaiCompatibleProviderOptions,
|
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})) ?? {},
|
||||
);
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|
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if (topK != null) {
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warnings.push({ type: 'unsupported-setting', setting: 'topK' });
|
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}
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|
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if (
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responseFormat?.type === 'json' &&
|
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responseFormat.schema != null &&
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!this.supportsStructuredOutputs
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) {
|
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warnings.push({
|
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type: 'unsupported-setting',
|
||||
setting: 'responseFormat',
|
||||
details:
|
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'JSON response format schema is only supported with structuredOutputs',
|
||||
});
|
||||
}
|
||||
|
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const {
|
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tools: openaiTools,
|
||||
toolChoice: openaiToolChoice,
|
||||
toolWarnings,
|
||||
} = prepareTools({
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tools,
|
||||
toolChoice,
|
||||
});
|
||||
|
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return {
|
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args: {
|
||||
// model id:
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||||
model: this.modelId,
|
||||
|
||||
// model specific settings:
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||||
user: compatibleOptions.user,
|
||||
|
||||
// standardized settings:
|
||||
max_tokens: maxOutputTokens,
|
||||
temperature,
|
||||
top_p: topP,
|
||||
frequency_penalty: frequencyPenalty,
|
||||
presence_penalty: presencePenalty,
|
||||
response_format:
|
||||
responseFormat?.type === 'json'
|
||||
? this.supportsStructuredOutputs === true &&
|
||||
responseFormat.schema != null
|
||||
? {
|
||||
type: 'json_schema',
|
||||
json_schema: {
|
||||
schema: responseFormat.schema,
|
||||
name: responseFormat.name ?? 'response',
|
||||
description: responseFormat.description,
|
||||
},
|
||||
}
|
||||
: { type: 'json_object' }
|
||||
: undefined,
|
||||
|
||||
stop: stopSequences,
|
||||
seed,
|
||||
...Object.fromEntries(
|
||||
Object.entries(
|
||||
providerOptions?.[this.providerOptionsName] ?? {},
|
||||
).filter(
|
||||
([key]) =>
|
||||
!Object.keys(openaiCompatibleProviderOptions.shape).includes(key),
|
||||
),
|
||||
),
|
||||
|
||||
reasoning_effort: compatibleOptions.reasoningEffort,
|
||||
verbosity: compatibleOptions.textVerbosity,
|
||||
|
||||
// messages:
|
||||
messages: convertToOpenAICompatibleChatMessages(prompt),
|
||||
|
||||
// tools:
|
||||
tools: openaiTools,
|
||||
tool_choice: openaiToolChoice,
|
||||
|
||||
// thinking_budget
|
||||
thinking_budget: compatibleOptions.thinking_budget,
|
||||
},
|
||||
warnings: [...warnings, ...toolWarnings],
|
||||
};
|
||||
}
|
||||
|
||||
async doGenerate(
|
||||
options: Parameters<LanguageModelV2['doGenerate']>[0],
|
||||
): Promise<Awaited<ReturnType<LanguageModelV2['doGenerate']>>> {
|
||||
const { args, warnings } = await this.getArgs({ ...options });
|
||||
|
||||
const body = JSON.stringify(args);
|
||||
|
||||
const {
|
||||
responseHeaders,
|
||||
value: responseBody,
|
||||
rawValue: rawResponse,
|
||||
} = await postJsonToApi({
|
||||
url: this.config.url({
|
||||
path: '/chat/completions',
|
||||
modelId: this.modelId,
|
||||
}),
|
||||
headers: combineHeaders(this.config.headers(), options.headers),
|
||||
body: args,
|
||||
failedResponseHandler: this.failedResponseHandler,
|
||||
successfulResponseHandler: createJsonResponseHandler(
|
||||
OpenAICompatibleChatResponseSchema,
|
||||
),
|
||||
abortSignal: options.abortSignal,
|
||||
fetch: this.config.fetch,
|
||||
});
|
||||
|
||||
const choice = responseBody.choices[0];
|
||||
const content: Array<LanguageModelV2Content> = [];
|
||||
|
||||
// text content:
|
||||
const text = choice.message.content;
|
||||
if (text != null && text.length > 0) {
|
||||
content.push({ type: 'text', text });
|
||||
}
|
||||
|
||||
// reasoning content (Copilot uses reasoning_text):
|
||||
const reasoning = choice.message.reasoning_text;
|
||||
if (reasoning != null && reasoning.length > 0) {
|
||||
content.push({
|
||||
type: 'reasoning',
|
||||
text: reasoning,
|
||||
// Include reasoning_opaque for Copilot multi-turn reasoning
|
||||
providerMetadata: choice.message.reasoning_opaque
|
||||
? { copilot: { reasoningOpaque: choice.message.reasoning_opaque } }
|
||||
: undefined,
|
||||
});
|
||||
}
|
||||
|
||||
// tool calls:
|
||||
if (choice.message.tool_calls != null) {
|
||||
for (const toolCall of choice.message.tool_calls) {
|
||||
content.push({
|
||||
type: 'tool-call',
|
||||
toolCallId: toolCall.id ?? generateId(),
|
||||
toolName: toolCall.function.name,
|
||||
input: toolCall.function.arguments!,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
// provider metadata:
|
||||
const providerMetadata: SharedV2ProviderMetadata = {
|
||||
[this.providerOptionsName]: {},
|
||||
...(await this.config.metadataExtractor?.extractMetadata?.({
|
||||
parsedBody: rawResponse,
|
||||
})),
|
||||
};
|
||||
const completionTokenDetails =
|
||||
responseBody.usage?.completion_tokens_details;
|
||||
if (completionTokenDetails?.accepted_prediction_tokens != null) {
|
||||
providerMetadata[this.providerOptionsName].acceptedPredictionTokens =
|
||||
completionTokenDetails?.accepted_prediction_tokens;
|
||||
}
|
||||
if (completionTokenDetails?.rejected_prediction_tokens != null) {
|
||||
providerMetadata[this.providerOptionsName].rejectedPredictionTokens =
|
||||
completionTokenDetails?.rejected_prediction_tokens;
|
||||
}
|
||||
|
||||
return {
|
||||
content,
|
||||
finishReason: mapOpenAICompatibleFinishReason(choice.finish_reason),
|
||||
usage: {
|
||||
inputTokens: responseBody.usage?.prompt_tokens ?? undefined,
|
||||
outputTokens: responseBody.usage?.completion_tokens ?? undefined,
|
||||
totalTokens: responseBody.usage?.total_tokens ?? undefined,
|
||||
reasoningTokens:
|
||||
responseBody.usage?.completion_tokens_details?.reasoning_tokens ??
|
||||
undefined,
|
||||
cachedInputTokens:
|
||||
responseBody.usage?.prompt_tokens_details?.cached_tokens ?? undefined,
|
||||
},
|
||||
providerMetadata,
|
||||
request: { body },
|
||||
response: {
|
||||
...getResponseMetadata(responseBody),
|
||||
headers: responseHeaders,
|
||||
body: rawResponse,
|
||||
},
|
||||
warnings,
|
||||
};
|
||||
}
|
||||
|
||||
async doStream(
|
||||
options: Parameters<LanguageModelV2['doStream']>[0],
|
||||
): Promise<Awaited<ReturnType<LanguageModelV2['doStream']>>> {
|
||||
const { args, warnings } = await this.getArgs({ ...options });
|
||||
|
||||
const body = {
|
||||
...args,
|
||||
stream: true,
|
||||
|
||||
// only include stream_options when in strict compatibility mode:
|
||||
stream_options: this.config.includeUsage
|
||||
? { include_usage: true }
|
||||
: undefined,
|
||||
};
|
||||
|
||||
const metadataExtractor =
|
||||
this.config.metadataExtractor?.createStreamExtractor();
|
||||
|
||||
const { responseHeaders, value: response } = await postJsonToApi({
|
||||
url: this.config.url({
|
||||
path: '/chat/completions',
|
||||
modelId: this.modelId,
|
||||
}),
|
||||
headers: combineHeaders(this.config.headers(), options.headers),
|
||||
body,
|
||||
failedResponseHandler: this.failedResponseHandler,
|
||||
successfulResponseHandler: createEventSourceResponseHandler(
|
||||
this.chunkSchema,
|
||||
),
|
||||
abortSignal: options.abortSignal,
|
||||
fetch: this.config.fetch,
|
||||
});
|
||||
|
||||
const toolCalls: Array<{
|
||||
id: string;
|
||||
type: 'function';
|
||||
function: {
|
||||
name: string;
|
||||
arguments: string;
|
||||
};
|
||||
hasFinished: boolean;
|
||||
}> = [];
|
||||
|
||||
let finishReason: LanguageModelV2FinishReason = 'unknown';
|
||||
const usage: {
|
||||
completionTokens: number | undefined;
|
||||
completionTokensDetails: {
|
||||
reasoningTokens: number | undefined;
|
||||
acceptedPredictionTokens: number | undefined;
|
||||
rejectedPredictionTokens: number | undefined;
|
||||
};
|
||||
promptTokens: number | undefined;
|
||||
promptTokensDetails: {
|
||||
cachedTokens: number | undefined;
|
||||
};
|
||||
totalTokens: number | undefined;
|
||||
} = {
|
||||
completionTokens: undefined,
|
||||
completionTokensDetails: {
|
||||
reasoningTokens: undefined,
|
||||
acceptedPredictionTokens: undefined,
|
||||
rejectedPredictionTokens: undefined,
|
||||
},
|
||||
promptTokens: undefined,
|
||||
promptTokensDetails: {
|
||||
cachedTokens: undefined,
|
||||
},
|
||||
totalTokens: undefined,
|
||||
};
|
||||
let isFirstChunk = true;
|
||||
const providerOptionsName = this.providerOptionsName;
|
||||
let isActiveReasoning = false;
|
||||
let isActiveText = false;
|
||||
let reasoningOpaque: string | undefined;
|
||||
|
||||
return {
|
||||
stream: response.pipeThrough(
|
||||
new TransformStream<
|
||||
ParseResult<z.infer<typeof this.chunkSchema>>,
|
||||
LanguageModelV2StreamPart
|
||||
>({
|
||||
start(controller) {
|
||||
controller.enqueue({ type: 'stream-start', warnings });
|
||||
},
|
||||
|
||||
// TODO we lost type safety on Chunk, most likely due to the error schema. MUST FIX
|
||||
transform(chunk, controller) {
|
||||
// Emit raw chunk if requested (before anything else)
|
||||
if (options.includeRawChunks) {
|
||||
controller.enqueue({ type: 'raw', rawValue: chunk.rawValue });
|
||||
}
|
||||
|
||||
// handle failed chunk parsing / validation:
|
||||
if (!chunk.success) {
|
||||
finishReason = 'error';
|
||||
controller.enqueue({ type: 'error', error: chunk.error });
|
||||
return;
|
||||
}
|
||||
const value = chunk.value;
|
||||
|
||||
metadataExtractor?.processChunk(chunk.rawValue);
|
||||
|
||||
// handle error chunks:
|
||||
if ('error' in value) {
|
||||
finishReason = 'error';
|
||||
controller.enqueue({ type: 'error', error: value.error.message });
|
||||
return;
|
||||
}
|
||||
|
||||
if (isFirstChunk) {
|
||||
isFirstChunk = false;
|
||||
|
||||
controller.enqueue({
|
||||
type: 'response-metadata',
|
||||
...getResponseMetadata(value),
|
||||
});
|
||||
}
|
||||
|
||||
if (value.usage != null) {
|
||||
const {
|
||||
prompt_tokens,
|
||||
completion_tokens,
|
||||
total_tokens,
|
||||
prompt_tokens_details,
|
||||
completion_tokens_details,
|
||||
} = value.usage;
|
||||
|
||||
usage.promptTokens = prompt_tokens ?? undefined;
|
||||
usage.completionTokens = completion_tokens ?? undefined;
|
||||
usage.totalTokens = total_tokens ?? undefined;
|
||||
if (completion_tokens_details?.reasoning_tokens != null) {
|
||||
usage.completionTokensDetails.reasoningTokens =
|
||||
completion_tokens_details?.reasoning_tokens;
|
||||
}
|
||||
if (
|
||||
completion_tokens_details?.accepted_prediction_tokens != null
|
||||
) {
|
||||
usage.completionTokensDetails.acceptedPredictionTokens =
|
||||
completion_tokens_details?.accepted_prediction_tokens;
|
||||
}
|
||||
if (
|
||||
completion_tokens_details?.rejected_prediction_tokens != null
|
||||
) {
|
||||
usage.completionTokensDetails.rejectedPredictionTokens =
|
||||
completion_tokens_details?.rejected_prediction_tokens;
|
||||
}
|
||||
if (prompt_tokens_details?.cached_tokens != null) {
|
||||
usage.promptTokensDetails.cachedTokens =
|
||||
prompt_tokens_details?.cached_tokens;
|
||||
}
|
||||
}
|
||||
|
||||
const choice = value.choices[0];
|
||||
|
||||
if (choice?.finish_reason != null) {
|
||||
finishReason = mapOpenAICompatibleFinishReason(
|
||||
choice.finish_reason,
|
||||
);
|
||||
}
|
||||
|
||||
if (choice?.delta == null) {
|
||||
return;
|
||||
}
|
||||
|
||||
const delta = choice.delta;
|
||||
|
||||
// Capture reasoning_opaque for Copilot multi-turn reasoning
|
||||
if (delta.reasoning_opaque) {
|
||||
if (reasoningOpaque != null) {
|
||||
throw new InvalidResponseDataError({
|
||||
data: delta,
|
||||
message:
|
||||
'Multiple reasoning_opaque values received in a single response. Only one thinking part per response is supported.',
|
||||
});
|
||||
}
|
||||
reasoningOpaque = delta.reasoning_opaque;
|
||||
}
|
||||
|
||||
// enqueue reasoning before text deltas (Copilot uses reasoning_text):
|
||||
const reasoningContent = delta.reasoning_text;
|
||||
if (reasoningContent) {
|
||||
if (!isActiveReasoning) {
|
||||
controller.enqueue({
|
||||
type: 'reasoning-start',
|
||||
id: 'reasoning-0',
|
||||
});
|
||||
isActiveReasoning = true;
|
||||
}
|
||||
|
||||
controller.enqueue({
|
||||
type: 'reasoning-delta',
|
||||
id: 'reasoning-0',
|
||||
delta: reasoningContent,
|
||||
});
|
||||
}
|
||||
|
||||
if (delta.content) {
|
||||
// If reasoning was active and we're starting text, end reasoning first
|
||||
// This handles the case where reasoning_opaque and content come in the same chunk
|
||||
if (isActiveReasoning && !isActiveText) {
|
||||
controller.enqueue({
|
||||
type: 'reasoning-end',
|
||||
id: 'reasoning-0',
|
||||
providerMetadata: reasoningOpaque
|
||||
? { copilot: { reasoningOpaque } }
|
||||
: undefined,
|
||||
});
|
||||
isActiveReasoning = false;
|
||||
}
|
||||
|
||||
if (!isActiveText) {
|
||||
controller.enqueue({ type: 'text-start', id: 'txt-0' });
|
||||
isActiveText = true;
|
||||
}
|
||||
|
||||
controller.enqueue({
|
||||
type: 'text-delta',
|
||||
id: 'txt-0',
|
||||
delta: delta.content,
|
||||
});
|
||||
}
|
||||
|
||||
if (delta.tool_calls != null) {
|
||||
// If reasoning was active and we're starting tool calls, end reasoning first
|
||||
// This handles the case where reasoning goes directly to tool calls with no content
|
||||
if (isActiveReasoning) {
|
||||
controller.enqueue({
|
||||
type: 'reasoning-end',
|
||||
id: 'reasoning-0',
|
||||
providerMetadata: reasoningOpaque
|
||||
? { copilot: { reasoningOpaque } }
|
||||
: undefined,
|
||||
});
|
||||
isActiveReasoning = false;
|
||||
}
|
||||
for (const toolCallDelta of delta.tool_calls) {
|
||||
const index = toolCallDelta.index;
|
||||
|
||||
if (toolCalls[index] == null) {
|
||||
if (toolCallDelta.id == null) {
|
||||
throw new InvalidResponseDataError({
|
||||
data: toolCallDelta,
|
||||
message: `Expected 'id' to be a string.`,
|
||||
});
|
||||
}
|
||||
|
||||
if (toolCallDelta.function?.name == null) {
|
||||
throw new InvalidResponseDataError({
|
||||
data: toolCallDelta,
|
||||
message: `Expected 'function.name' to be a string.`,
|
||||
});
|
||||
}
|
||||
|
||||
controller.enqueue({
|
||||
type: 'tool-input-start',
|
||||
id: toolCallDelta.id,
|
||||
toolName: toolCallDelta.function.name,
|
||||
});
|
||||
|
||||
toolCalls[index] = {
|
||||
id: toolCallDelta.id,
|
||||
type: 'function',
|
||||
function: {
|
||||
name: toolCallDelta.function.name,
|
||||
arguments: toolCallDelta.function.arguments ?? '',
|
||||
},
|
||||
hasFinished: false,
|
||||
};
|
||||
|
||||
const toolCall = toolCalls[index];
|
||||
|
||||
if (
|
||||
toolCall.function?.name != null &&
|
||||
toolCall.function?.arguments != null
|
||||
) {
|
||||
// send delta if the argument text has already started:
|
||||
if (toolCall.function.arguments.length > 0) {
|
||||
controller.enqueue({
|
||||
type: 'tool-input-delta',
|
||||
id: toolCall.id,
|
||||
delta: toolCall.function.arguments,
|
||||
});
|
||||
}
|
||||
|
||||
// check if tool call is complete
|
||||
// (some providers send the full tool call in one chunk):
|
||||
if (isParsableJson(toolCall.function.arguments)) {
|
||||
controller.enqueue({
|
||||
type: 'tool-input-end',
|
||||
id: toolCall.id,
|
||||
});
|
||||
|
||||
controller.enqueue({
|
||||
type: 'tool-call',
|
||||
toolCallId: toolCall.id ?? generateId(),
|
||||
toolName: toolCall.function.name,
|
||||
input: toolCall.function.arguments,
|
||||
});
|
||||
toolCall.hasFinished = true;
|
||||
}
|
||||
}
|
||||
|
||||
continue;
|
||||
}
|
||||
|
||||
// existing tool call, merge if not finished
|
||||
const toolCall = toolCalls[index];
|
||||
|
||||
if (toolCall.hasFinished) {
|
||||
continue;
|
||||
}
|
||||
|
||||
if (toolCallDelta.function?.arguments != null) {
|
||||
toolCall.function!.arguments +=
|
||||
toolCallDelta.function?.arguments ?? '';
|
||||
}
|
||||
|
||||
// send delta
|
||||
controller.enqueue({
|
||||
type: 'tool-input-delta',
|
||||
id: toolCall.id,
|
||||
delta: toolCallDelta.function.arguments ?? '',
|
||||
});
|
||||
|
||||
// check if tool call is complete
|
||||
if (
|
||||
toolCall.function?.name != null &&
|
||||
toolCall.function?.arguments != null &&
|
||||
isParsableJson(toolCall.function.arguments)
|
||||
) {
|
||||
controller.enqueue({
|
||||
type: 'tool-input-end',
|
||||
id: toolCall.id,
|
||||
});
|
||||
|
||||
controller.enqueue({
|
||||
type: 'tool-call',
|
||||
toolCallId: toolCall.id ?? generateId(),
|
||||
toolName: toolCall.function.name,
|
||||
input: toolCall.function.arguments,
|
||||
});
|
||||
toolCall.hasFinished = true;
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
|
||||
flush(controller) {
|
||||
if (isActiveReasoning) {
|
||||
controller.enqueue({
|
||||
type: 'reasoning-end',
|
||||
id: 'reasoning-0',
|
||||
// Include reasoning_opaque for Copilot multi-turn reasoning
|
||||
providerMetadata: reasoningOpaque
|
||||
? { copilot: { reasoningOpaque } }
|
||||
: undefined,
|
||||
});
|
||||
}
|
||||
|
||||
if (isActiveText) {
|
||||
controller.enqueue({ type: 'text-end', id: 'txt-0' });
|
||||
}
|
||||
|
||||
// go through all tool calls and send the ones that are not finished
|
||||
for (const toolCall of toolCalls.filter(
|
||||
toolCall => !toolCall.hasFinished,
|
||||
)) {
|
||||
controller.enqueue({
|
||||
type: 'tool-input-end',
|
||||
id: toolCall.id,
|
||||
});
|
||||
|
||||
controller.enqueue({
|
||||
type: 'tool-call',
|
||||
toolCallId: toolCall.id ?? generateId(),
|
||||
toolName: toolCall.function.name,
|
||||
input: toolCall.function.arguments,
|
||||
});
|
||||
}
|
||||
|
||||
const providerMetadata: SharedV2ProviderMetadata = {
|
||||
[providerOptionsName]: {},
|
||||
// Include reasoning_opaque for Copilot multi-turn reasoning
|
||||
...(reasoningOpaque
|
||||
? { copilot: { reasoningOpaque } }
|
||||
: {}),
|
||||
...metadataExtractor?.buildMetadata(),
|
||||
};
|
||||
if (
|
||||
usage.completionTokensDetails.acceptedPredictionTokens != null
|
||||
) {
|
||||
providerMetadata[providerOptionsName].acceptedPredictionTokens =
|
||||
usage.completionTokensDetails.acceptedPredictionTokens;
|
||||
}
|
||||
if (
|
||||
usage.completionTokensDetails.rejectedPredictionTokens != null
|
||||
) {
|
||||
providerMetadata[providerOptionsName].rejectedPredictionTokens =
|
||||
usage.completionTokensDetails.rejectedPredictionTokens;
|
||||
}
|
||||
|
||||
controller.enqueue({
|
||||
type: 'finish',
|
||||
finishReason,
|
||||
usage: {
|
||||
inputTokens: usage.promptTokens ?? undefined,
|
||||
outputTokens: usage.completionTokens ?? undefined,
|
||||
totalTokens: usage.totalTokens ?? undefined,
|
||||
reasoningTokens:
|
||||
usage.completionTokensDetails.reasoningTokens ?? undefined,
|
||||
cachedInputTokens:
|
||||
usage.promptTokensDetails.cachedTokens ?? undefined,
|
||||
},
|
||||
providerMetadata,
|
||||
});
|
||||
},
|
||||
}),
|
||||
),
|
||||
request: { body },
|
||||
response: { headers: responseHeaders },
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
const openaiCompatibleTokenUsageSchema = z
|
||||
.object({
|
||||
prompt_tokens: z.number().nullish(),
|
||||
completion_tokens: z.number().nullish(),
|
||||
total_tokens: z.number().nullish(),
|
||||
prompt_tokens_details: z
|
||||
.object({
|
||||
cached_tokens: z.number().nullish(),
|
||||
})
|
||||
.nullish(),
|
||||
completion_tokens_details: z
|
||||
.object({
|
||||
reasoning_tokens: z.number().nullish(),
|
||||
accepted_prediction_tokens: z.number().nullish(),
|
||||
rejected_prediction_tokens: z.number().nullish(),
|
||||
})
|
||||
.nullish(),
|
||||
})
|
||||
.nullish();
|
||||
|
||||
// limited version of the schema, focussed on what is needed for the implementation
|
||||
// this approach limits breakages when the API changes and increases efficiency
|
||||
const OpenAICompatibleChatResponseSchema = z.object({
|
||||
id: z.string().nullish(),
|
||||
created: z.number().nullish(),
|
||||
model: z.string().nullish(),
|
||||
choices: z.array(
|
||||
z.object({
|
||||
message: z.object({
|
||||
role: z.literal('assistant').nullish(),
|
||||
content: z.string().nullish(),
|
||||
// Copilot-specific reasoning fields
|
||||
reasoning_text: z.string().nullish(),
|
||||
reasoning_opaque: z.string().nullish(),
|
||||
tool_calls: z
|
||||
.array(
|
||||
z.object({
|
||||
id: z.string().nullish(),
|
||||
function: z.object({
|
||||
name: z.string(),
|
||||
arguments: z.string(),
|
||||
}),
|
||||
}),
|
||||
)
|
||||
.nullish(),
|
||||
}),
|
||||
finish_reason: z.string().nullish(),
|
||||
}),
|
||||
),
|
||||
usage: openaiCompatibleTokenUsageSchema,
|
||||
});
|
||||
|
||||
// limited version of the schema, focussed on what is needed for the implementation
|
||||
// this approach limits breakages when the API changes and increases efficiency
|
||||
const createOpenAICompatibleChatChunkSchema = <
|
||||
ERROR_SCHEMA extends z.core.$ZodType,
|
||||
>(
|
||||
errorSchema: ERROR_SCHEMA,
|
||||
) =>
|
||||
z.union([
|
||||
z.object({
|
||||
id: z.string().nullish(),
|
||||
created: z.number().nullish(),
|
||||
model: z.string().nullish(),
|
||||
choices: z.array(
|
||||
z.object({
|
||||
delta: z
|
||||
.object({
|
||||
role: z.enum(['assistant']).nullish(),
|
||||
content: z.string().nullish(),
|
||||
// Copilot-specific reasoning fields
|
||||
reasoning_text: z.string().nullish(),
|
||||
reasoning_opaque: z.string().nullish(),
|
||||
tool_calls: z
|
||||
.array(
|
||||
z.object({
|
||||
index: z.number(),
|
||||
id: z.string().nullish(),
|
||||
function: z.object({
|
||||
name: z.string().nullish(),
|
||||
arguments: z.string().nullish(),
|
||||
}),
|
||||
}),
|
||||
)
|
||||
.nullish(),
|
||||
})
|
||||
.nullish(),
|
||||
finish_reason: z.string().nullish(),
|
||||
}),
|
||||
),
|
||||
usage: openaiCompatibleTokenUsageSchema,
|
||||
}),
|
||||
errorSchema,
|
||||
]);
|
||||
@@ -0,0 +1,30 @@
|
||||
import { z } from 'zod/v4';
|
||||
|
||||
export type OpenAICompatibleChatModelId = string;
|
||||
|
||||
export const openaiCompatibleProviderOptions = z.object({
|
||||
/**
|
||||
* A unique identifier representing your end-user, which can help the provider to
|
||||
* monitor and detect abuse.
|
||||
*/
|
||||
user: z.string().optional(),
|
||||
|
||||
/**
|
||||
* Reasoning effort for reasoning models. Defaults to `medium`.
|
||||
*/
|
||||
reasoningEffort: z.string().optional(),
|
||||
|
||||
/**
|
||||
* Controls the verbosity of the generated text. Defaults to `medium`.
|
||||
*/
|
||||
textVerbosity: z.string().optional(),
|
||||
|
||||
/**
|
||||
* Copilot thinking_budget used for Anthropic models.
|
||||
*/
|
||||
thinking_budget: z.number().optional(),
|
||||
});
|
||||
|
||||
export type OpenAICompatibleProviderOptions = z.infer<
|
||||
typeof openaiCompatibleProviderOptions
|
||||
>;
|
||||
@@ -0,0 +1,48 @@
|
||||
import type { SharedV2ProviderMetadata } from '@ai-sdk/provider';
|
||||
|
||||
/**
|
||||
Extracts provider-specific metadata from API responses.
|
||||
Used to standardize metadata handling across different LLM providers while allowing
|
||||
provider-specific metadata to be captured.
|
||||
*/
|
||||
export type MetadataExtractor = {
|
||||
/**
|
||||
* Extracts provider metadata from a complete, non-streaming response.
|
||||
*
|
||||
* @param parsedBody - The parsed response JSON body from the provider's API.
|
||||
*
|
||||
* @returns Provider-specific metadata or undefined if no metadata is available.
|
||||
* The metadata should be under a key indicating the provider id.
|
||||
*/
|
||||
extractMetadata: ({
|
||||
parsedBody,
|
||||
}: {
|
||||
parsedBody: unknown;
|
||||
}) => Promise<SharedV2ProviderMetadata | undefined>;
|
||||
|
||||
/**
|
||||
* Creates an extractor for handling streaming responses. The returned object provides
|
||||
* methods to process individual chunks and build the final metadata from the accumulated
|
||||
* stream data.
|
||||
*
|
||||
* @returns An object with methods to process chunks and build metadata from a stream
|
||||
*/
|
||||
createStreamExtractor: () => {
|
||||
/**
|
||||
* Process an individual chunk from the stream. Called for each chunk in the response stream
|
||||
* to accumulate metadata throughout the streaming process.
|
||||
*
|
||||
* @param parsedChunk - The parsed JSON response chunk from the provider's API
|
||||
*/
|
||||
processChunk(parsedChunk: unknown): void;
|
||||
|
||||
/**
|
||||
* Builds the metadata object after all chunks have been processed.
|
||||
* Called at the end of the stream to generate the complete provider metadata.
|
||||
*
|
||||
* @returns Provider-specific metadata or undefined if no metadata is available.
|
||||
* The metadata should be under a key indicating the provider id.
|
||||
*/
|
||||
buildMetadata(): SharedV2ProviderMetadata | undefined;
|
||||
};
|
||||
};
|
||||
@@ -0,0 +1,92 @@
|
||||
import {
|
||||
type LanguageModelV2CallOptions,
|
||||
type LanguageModelV2CallWarning,
|
||||
UnsupportedFunctionalityError,
|
||||
} from '@ai-sdk/provider';
|
||||
|
||||
export function prepareTools({
|
||||
tools,
|
||||
toolChoice,
|
||||
}: {
|
||||
tools: LanguageModelV2CallOptions['tools'];
|
||||
toolChoice?: LanguageModelV2CallOptions['toolChoice'];
|
||||
}): {
|
||||
tools:
|
||||
| undefined
|
||||
| Array<{
|
||||
type: 'function';
|
||||
function: {
|
||||
name: string;
|
||||
description: string | undefined;
|
||||
parameters: unknown;
|
||||
};
|
||||
}>;
|
||||
toolChoice:
|
||||
| { type: 'function'; function: { name: string } }
|
||||
| 'auto'
|
||||
| 'none'
|
||||
| 'required'
|
||||
| undefined;
|
||||
toolWarnings: LanguageModelV2CallWarning[];
|
||||
} {
|
||||
// when the tools array is empty, change it to undefined to prevent errors:
|
||||
tools = tools?.length ? tools : undefined;
|
||||
|
||||
const toolWarnings: LanguageModelV2CallWarning[] = [];
|
||||
|
||||
if (tools == null) {
|
||||
return { tools: undefined, toolChoice: undefined, toolWarnings };
|
||||
}
|
||||
|
||||
const openaiCompatTools: Array<{
|
||||
type: 'function';
|
||||
function: {
|
||||
name: string;
|
||||
description: string | undefined;
|
||||
parameters: unknown;
|
||||
};
|
||||
}> = [];
|
||||
|
||||
for (const tool of tools) {
|
||||
if (tool.type === 'provider-defined') {
|
||||
toolWarnings.push({ type: 'unsupported-tool', tool });
|
||||
} else {
|
||||
openaiCompatTools.push({
|
||||
type: 'function',
|
||||
function: {
|
||||
name: tool.name,
|
||||
description: tool.description,
|
||||
parameters: tool.inputSchema,
|
||||
},
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
if (toolChoice == null) {
|
||||
return { tools: openaiCompatTools, toolChoice: undefined, toolWarnings };
|
||||
}
|
||||
|
||||
const type = toolChoice.type;
|
||||
|
||||
switch (type) {
|
||||
case 'auto':
|
||||
case 'none':
|
||||
case 'required':
|
||||
return { tools: openaiCompatTools, toolChoice: type, toolWarnings };
|
||||
case 'tool':
|
||||
return {
|
||||
tools: openaiCompatTools,
|
||||
toolChoice: {
|
||||
type: 'function',
|
||||
function: { name: toolChoice.toolName },
|
||||
},
|
||||
toolWarnings,
|
||||
};
|
||||
default: {
|
||||
const _exhaustiveCheck: never = type;
|
||||
throw new UnsupportedFunctionalityError({
|
||||
functionality: `tool choice type: ${_exhaustiveCheck}`,
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -1,6 +1,6 @@
|
||||
import type { LanguageModelV2 } from "@ai-sdk/provider"
|
||||
import { OpenAICompatibleChatLanguageModel } from "@ai-sdk/openai-compatible"
|
||||
import { type FetchFunction, withoutTrailingSlash, withUserAgentSuffix } from "@ai-sdk/provider-utils"
|
||||
import { OpenAICompatibleChatLanguageModel } from "./chat/openai-compatible-chat-language-model"
|
||||
import { OpenAIResponsesLanguageModel } from "./responses/openai-responses-language-model"
|
||||
|
||||
// Import the version or define it
|
||||
2
packages/opencode/src/provider/sdk/copilot/index.ts
Normal file
2
packages/opencode/src/provider/sdk/copilot/index.ts
Normal file
@@ -0,0 +1,2 @@
|
||||
export { createOpenaiCompatible, openaiCompatible } from "./copilot-provider"
|
||||
export type { OpenaiCompatibleProvider, OpenaiCompatibleProviderSettings } from "./copilot-provider"
|
||||
@@ -0,0 +1,30 @@
|
||||
import { z, type ZodType } from 'zod/v4';
|
||||
|
||||
export const openaiCompatibleErrorDataSchema = z.object({
|
||||
error: z.object({
|
||||
message: z.string(),
|
||||
|
||||
// The additional information below is handled loosely to support
|
||||
// OpenAI-compatible providers that have slightly different error
|
||||
// responses:
|
||||
type: z.string().nullish(),
|
||||
param: z.any().nullish(),
|
||||
code: z.union([z.string(), z.number()]).nullish(),
|
||||
}),
|
||||
});
|
||||
|
||||
export type OpenAICompatibleErrorData = z.infer<
|
||||
typeof openaiCompatibleErrorDataSchema
|
||||
>;
|
||||
|
||||
export type ProviderErrorStructure<T> = {
|
||||
errorSchema: ZodType<T>;
|
||||
errorToMessage: (error: T) => string;
|
||||
isRetryable?: (response: Response, error?: T) => boolean;
|
||||
};
|
||||
|
||||
export const defaultOpenAICompatibleErrorStructure: ProviderErrorStructure<OpenAICompatibleErrorData> =
|
||||
{
|
||||
errorSchema: openaiCompatibleErrorDataSchema,
|
||||
errorToMessage: data => data.error.message,
|
||||
};
|
||||
@@ -183,7 +183,7 @@ export async function convertToOpenAIResponsesInput({
|
||||
|
||||
case "reasoning": {
|
||||
const providerOptions = await parseProviderOptions({
|
||||
provider: "openai",
|
||||
provider: "copilot",
|
||||
providerOptions: part.providerOptions,
|
||||
schema: openaiResponsesReasoningProviderOptionsSchema,
|
||||
})
|
||||
@@ -194,7 +194,7 @@ export class OpenAIResponsesLanguageModel implements LanguageModelV2 {
|
||||
}
|
||||
|
||||
const openaiOptions = await parseProviderOptions({
|
||||
provider: "openai",
|
||||
provider: "copilot",
|
||||
providerOptions,
|
||||
schema: openaiResponsesProviderOptionsSchema,
|
||||
})
|
||||
@@ -1,2 +0,0 @@
|
||||
export { createOpenaiCompatible, openaiCompatible } from "./openai-compatible-provider"
|
||||
export type { OpenaiCompatibleProvider, OpenaiCompatibleProviderSettings } from "./openai-compatible-provider"
|
||||
@@ -20,6 +20,7 @@ export namespace ProviderTransform {
|
||||
function sdkKey(npm: string): string | undefined {
|
||||
switch (npm) {
|
||||
case "@ai-sdk/github-copilot":
|
||||
return "copilot"
|
||||
case "@ai-sdk/openai":
|
||||
case "@ai-sdk/azure":
|
||||
return "openai"
|
||||
@@ -179,6 +180,9 @@ export namespace ProviderTransform {
|
||||
openaiCompatible: {
|
||||
cache_control: { type: "ephemeral" },
|
||||
},
|
||||
copilot: {
|
||||
copilot_cache_control: { type: "ephemeral" },
|
||||
},
|
||||
}
|
||||
|
||||
for (const msg of unique([...system, ...final])) {
|
||||
@@ -353,6 +357,15 @@ export namespace ProviderTransform {
|
||||
return Object.fromEntries(OPENAI_EFFORTS.map((effort) => [effort, { reasoningEffort: effort }]))
|
||||
|
||||
case "@ai-sdk/github-copilot":
|
||||
if (model.id.includes("gemini")) {
|
||||
// currently github copilot only returns thinking
|
||||
return {}
|
||||
}
|
||||
if (model.id.includes("claude")) {
|
||||
return {
|
||||
thinking: { thinking_budget: 4000 },
|
||||
}
|
||||
}
|
||||
const copilotEfforts = iife(() => {
|
||||
if (id.includes("5.1-codex-max") || id.includes("5.2")) return [...WIDELY_SUPPORTED_EFFORTS, "xhigh"]
|
||||
return WIDELY_SUPPORTED_EFFORTS
|
||||
|
||||
@@ -148,14 +148,15 @@ export namespace LLM {
|
||||
},
|
||||
)
|
||||
|
||||
const maxOutputTokens = isCodex
|
||||
? undefined
|
||||
: ProviderTransform.maxOutputTokens(
|
||||
input.model.api.npm,
|
||||
params.options,
|
||||
input.model.limit.output,
|
||||
OUTPUT_TOKEN_MAX,
|
||||
)
|
||||
const maxOutputTokens =
|
||||
isCodex || provider.id.includes("github-copilot")
|
||||
? undefined
|
||||
: ProviderTransform.maxOutputTokens(
|
||||
input.model.api.npm,
|
||||
params.options,
|
||||
input.model.limit.output,
|
||||
OUTPUT_TOKEN_MAX,
|
||||
)
|
||||
|
||||
const tools = await resolveTools(input)
|
||||
|
||||
|
||||
Reference in New Issue
Block a user