feat: add GitHub Copilot model provider with OAuth device flow
Add a new 'github' model provider backed by the Copilot API (api.githubcopilot.com), with OAuth device flow for authentication. - New src/auth/github.ts: device flow login, token storage at ~/.config/flynn/auth.json with 0600 permissions - New src/models/github.ts: OpenAI-compatible client with streaming, tool calling, and Copilot-specific headers - Add 'github' to provider enum in config schema - Register provider in daemon factory and TUI client factory - Refactor TUI to use provider-agnostic client factory (was hardcoded to AnthropicClient for all tiers) - Add /login command to TUI for interactive OAuth authorization - Add Copilot model cost tracking entries
This commit is contained in:
William Valentin
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import OpenAI from 'openai';
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import type { ChatRequest, ChatResponse, ChatStreamEvent, ModelClient, MessageContentPart } from './types.js';
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import { getGitHubToken } from '../auth/index.js';
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export interface GitHubModelsClientConfig {
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apiKey?: string; // GitHub PAT or gh auth token. Falls back to GITHUB_TOKEN env var
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model: string; // e.g., 'gpt-4o' or 'claude-sonnet-4'
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maxTokens?: number;
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endpoint?: string; // Override base URL (default: https://models.github.ai/inference)
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}
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const DEFAULT_ENDPOINT = 'https://api.githubcopilot.com';
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/**
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* Convert Flynn message content to OpenAI format.
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* Reuses the same pattern as openai.ts since GitHub Models uses an OpenAI-compatible API.
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*/
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function toOpenAIContent(content: string | MessageContentPart[]): string | OpenAI.ChatCompletionContentPart[] {
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if (typeof content === 'string') {
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return content;
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}
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return content.map((part): OpenAI.ChatCompletionContentPart => {
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if (part.type === 'text') {
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return { type: 'text', text: part.text };
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}
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if (part.type === 'image') {
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const url = part.source.type === 'base64'
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? `data:${part.source.media_type};base64,${part.source.data!}`
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: part.source.url!;
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return { type: 'image_url', image_url: { url } };
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}
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// Fallback — shouldn't happen
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return { type: 'text', text: JSON.stringify(part) };
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});
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}
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export class GitHubModelsClient implements ModelClient {
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private client: OpenAI;
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private model: string;
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private defaultMaxTokens: number;
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constructor(config: GitHubModelsClientConfig) {
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const apiKey = config.apiKey ?? getGitHubToken() ?? '';
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const baseURL = config.endpoint ?? DEFAULT_ENDPOINT;
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this.client = new OpenAI({
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apiKey,
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baseURL,
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defaultHeaders: {
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'X-GitHub-Api-Version': '2022-11-28',
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'Openai-Intent': 'conversation-edits',
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},
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});
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this.model = config.model;
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this.defaultMaxTokens = config.maxTokens ?? 4096;
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}
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async chat(request: ChatRequest): Promise<ChatResponse> {
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const messages: OpenAI.ChatCompletionMessageParam[] = [];
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if (request.system) {
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messages.push({ role: 'system', content: request.system });
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}
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for (const msg of request.messages) {
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messages.push({
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role: msg.role,
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content: toOpenAIContent(msg.content),
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} as OpenAI.ChatCompletionMessageParam);
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}
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const params: OpenAI.ChatCompletionCreateParamsNonStreaming = {
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model: this.model,
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max_tokens: request.maxTokens ?? this.defaultMaxTokens,
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messages,
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};
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if (request.tools && request.tools.length > 0) {
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params.tools = request.tools.map(t => ({
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type: 'function' as const,
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function: {
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name: t.name,
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description: t.description,
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parameters: t.input_schema as OpenAI.FunctionParameters,
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},
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}));
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}
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const response = await this.client.chat.completions.create(params);
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const choice = response.choices[0];
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const content = choice?.message?.content ?? '';
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const toolCalls = choice?.message?.tool_calls?.map((tc: OpenAI.ChatCompletionMessageToolCall) => ({
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id: tc.id,
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name: tc.function.name,
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args: JSON.parse(tc.function.arguments),
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})) ?? [];
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// Map OpenAI finish reasons to Flynn's stop reasons
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let stopReason: string;
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if (toolCalls.length > 0) {
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stopReason = 'tool_use';
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} else {
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const reason = choice?.finish_reason;
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if (reason === 'stop') {
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stopReason = 'end_turn';
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} else if (reason === 'length') {
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stopReason = 'max_tokens';
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} else {
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stopReason = reason ?? 'end_turn';
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}
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}
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return {
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content,
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stopReason,
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usage: {
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inputTokens: response.usage?.prompt_tokens ?? 0,
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outputTokens: response.usage?.completion_tokens ?? 0,
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},
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...(toolCalls.length > 0 ? { toolCalls } : {}),
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};
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}
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async *chatStream(request: ChatRequest): AsyncIterable<ChatStreamEvent> {
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const messages: OpenAI.ChatCompletionMessageParam[] = [];
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if (request.system) {
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messages.push({ role: 'system', content: request.system });
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}
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for (const msg of request.messages) {
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messages.push({
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role: msg.role,
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content: toOpenAIContent(msg.content),
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} as OpenAI.ChatCompletionMessageParam);
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}
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const params: OpenAI.ChatCompletionCreateParamsStreaming = {
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model: this.model,
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max_tokens: request.maxTokens ?? this.defaultMaxTokens,
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messages,
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stream: true,
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};
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if (request.tools && request.tools.length > 0) {
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params.tools = request.tools.map(t => ({
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type: 'function' as const,
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function: {
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name: t.name,
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description: t.description,
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parameters: t.input_schema as OpenAI.FunctionParameters,
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},
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}));
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}
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try {
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const stream = await this.client.chat.completions.create(params);
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let totalInputTokens = 0;
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let totalOutputTokens = 0;
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// Accumulate tool call deltas across chunks
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const toolCallAccumulator = new Map<number, {
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id: string;
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name: string;
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arguments: string;
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}>();
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for await (const chunk of stream) {
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const delta = chunk.choices[0]?.delta;
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const finishReason = chunk.choices[0]?.finish_reason;
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// Emit text content deltas
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if (delta?.content) {
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yield { type: 'content', content: delta.content };
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}
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// Accumulate tool call deltas
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if (delta?.tool_calls) {
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for (const tc of delta.tool_calls) {
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const existing = toolCallAccumulator.get(tc.index);
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if (existing) {
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// Append argument fragments
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if (tc.function?.arguments) {
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existing.arguments += tc.function.arguments;
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}
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} else {
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toolCallAccumulator.set(tc.index, {
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id: tc.id ?? '',
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name: tc.function?.name ?? '',
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arguments: tc.function?.arguments ?? '',
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});
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}
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}
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}
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// Track usage from chunks (some providers include it in stream)
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if (chunk.usage) {
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totalInputTokens = chunk.usage.prompt_tokens ?? totalInputTokens;
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totalOutputTokens = chunk.usage.completion_tokens ?? totalOutputTokens;
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}
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// On finish, emit accumulated tool calls
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if (finishReason === 'tool_calls' || finishReason === 'stop') {
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for (const [, tc] of toolCallAccumulator) {
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yield {
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type: 'tool_use',
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toolCall: {
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id: tc.id,
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name: tc.name,
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args: JSON.parse(tc.arguments || '{}'),
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},
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};
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}
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toolCallAccumulator.clear();
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}
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}
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yield {
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type: 'done',
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usage: {
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inputTokens: totalInputTokens,
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outputTokens: totalOutputTokens,
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},
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};
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} catch (error) {
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yield {
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type: 'error',
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error: error instanceof Error ? error : new Error(String(error)),
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};
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}
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}
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}
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