{"version":3,"sources":["../src/gitlab-anthropic-language-model.ts","../src/gitlab-direct-access.ts","../src/gitlab-error.ts","../src/gitlab-openai-language-model.ts","../src/model-mappings.ts","../src/gitlab-workflow-client.ts","../src/version.ts","../src/gitlab-workflow-types.ts","../src/gitlab-workflow-builtins.ts","../src/gitlab-workflow-token-client.ts","../src/gitlab-project-detector.ts","../src/gitlab-project-cache.ts","../src/gitlab-model-discovery.ts","../src/gitlab-model-cache.ts","../src/gitlab-workflow-language-model.ts","../src/gitlab-oauth-types.ts","../src/gitlab-oauth-manager.ts","../src/gitlab-provider.ts"],"sourcesContent":["import Anthropic from '@anthropic-ai/sdk';\nimport type { Tool } from '@anthropic-ai/sdk/resources/messages';\nimport { GitLabDirectAccessClient } from './gitlab-direct-access';\nimport { GitLabError } from './gitlab-error';\n\nimport type {\n LanguageModelV2,\n LanguageModelV2CallOptions,\n LanguageModelV2StreamPart,\n LanguageModelV2FinishReason,\n LanguageModelV2CallWarning,\n LanguageModelV2Content,\n LanguageModelV2Usage,\n LanguageModelV2FunctionTool,\n LanguageModelV2Message,\n LanguageModelV2ToolChoice,\n} from '@ai-sdk/provider';\n\nexport interface GitLabAnthropicConfig {\n provider: string;\n instanceUrl: string;\n getHeaders: () => Record;\n fetch?: typeof fetch;\n\n /**\n * Optional callback to refresh the API key when a 401 error occurs.\n * Should clear cached credentials and re-fetch from auth provider.\n */\n refreshApiKey?: () => Promise;\n\n /**\n * The Anthropic model to use (e.g., 'claude-sonnet-4-5-20250929')\n * @default 'claude-sonnet-4-5-20250929'\n */\n anthropicModel?: string;\n\n /**\n * Maximum tokens to generate\n * @default 8192\n */\n maxTokens?: number;\n\n /**\n * Feature flags to pass to the GitLab API\n * @default { DuoAgentPlatformNext: true }\n */\n featureFlags?: {\n DuoAgentPlatformNext: true;\n } & Record;\n\n /**\n * AI Gateway URL for the Anthropic proxy.\n * Can also be set via GITLAB_AI_GATEWAY_URL environment variable.\n * @default 'https://cloud.gitlab.com'\n */\n aiGatewayUrl?: string;\n\n /**\n * Custom headers for AI Gateway Anthropic proxy requests.\n * Merged with headers from direct_access token response.\n */\n aiGatewayHeaders?: Record;\n}\n\n/**\n * GitLab Anthropic Language Model\n *\n * This model uses GitLab's Anthropic proxy to provide native tool calling support\n * for the duo-chat model. It connects to Claude through GitLab's cloud proxy\n * at https://cloud.gitlab.com/ai/v1/proxy/anthropic/\n */\nexport class GitLabAnthropicLanguageModel implements LanguageModelV2 {\n readonly specificationVersion = 'v2' as const;\n readonly modelId: string;\n readonly supportedUrls: Record = {};\n\n private readonly config: GitLabAnthropicConfig;\n private readonly directAccessClient: GitLabDirectAccessClient;\n private anthropicClient: Anthropic | null = null;\n\n constructor(modelId: string, config: GitLabAnthropicConfig) {\n this.modelId = modelId;\n this.config = config;\n\n this.directAccessClient = new GitLabDirectAccessClient({\n instanceUrl: config.instanceUrl,\n getHeaders: config.getHeaders,\n refreshApiKey: config.refreshApiKey,\n fetch: config.fetch,\n featureFlags: config.featureFlags,\n aiGatewayUrl: config.aiGatewayUrl,\n });\n }\n\n get provider(): string {\n return this.config.provider;\n }\n\n /**\n * Get or create an Anthropic client with valid credentials\n * @param forceRefresh - If true, forces a token refresh before creating the client\n */\n private async getAnthropicClient(forceRefresh: boolean = false): Promise {\n // Get token from GitLab (will use cache unless forceRefresh is true)\n const tokenData = await this.directAccessClient.getDirectAccessToken(forceRefresh);\n\n // Create new client with the token\n // GitLab's proxy expects:\n // - authToken: sets Authorization: Bearer header (NOT apiKey which sets x-api-key)\n // - defaultHeaders: additional headers from the direct access response\n // Filter out x-api-key from headers if present - we use authToken for Bearer auth\n const { 'x-api-key': _removed, ...filteredHeaders } = tokenData.headers;\n\n // Merge: tokenData headers < custom aiGatewayHeaders\n const mergedHeaders = {\n ...filteredHeaders,\n ...this.config.aiGatewayHeaders,\n };\n\n this.anthropicClient = new Anthropic({\n apiKey: null,\n authToken: tokenData.token,\n baseURL: this.directAccessClient.getAnthropicProxyUrl(),\n defaultHeaders: mergedHeaders,\n });\n\n return this.anthropicClient;\n }\n\n /**\n * Check if an error is a token-related authentication error that can be retried\n */\n private isTokenError(error: unknown): boolean {\n if (error instanceof Anthropic.APIError) {\n // 401 Unauthorized - token expired or revoked\n if (error.status === 401) {\n return true;\n }\n // Check for token-related error messages\n const message = error.message?.toLowerCase() || '';\n if (\n message.includes('token') &&\n (message.includes('expired') || message.includes('revoked') || message.includes('invalid'))\n ) {\n return true;\n }\n }\n return false;\n }\n\n /**\n * Check if an error is a context overflow error (prompt too long)\n * These should NOT trigger token refresh and should be reported to the user.\n */\n private isContextOverflowError(error: unknown): boolean {\n if (error instanceof Anthropic.APIError) {\n // 400 Bad Request with prompt too long message\n if (error.status === 400) {\n const message = error.message?.toLowerCase() || '';\n if (\n message.includes('prompt is too long') ||\n message.includes('prompt too long') ||\n (message.includes('tokens') && message.includes('maximum'))\n ) {\n return true;\n }\n }\n }\n return false;\n }\n\n /**\n * Convert AI SDK tools to Anthropic tool format\n */\n private convertTools(tools?: LanguageModelV2CallOptions['tools']): Tool[] | undefined {\n if (!tools || tools.length === 0) {\n return undefined;\n }\n\n return tools\n .filter((tool): tool is LanguageModelV2FunctionTool => tool.type === 'function')\n .map((tool) => {\n const schema = tool.inputSchema as { properties?: object; required?: string[] } | undefined;\n return {\n name: tool.name,\n description: tool.description || '',\n input_schema: {\n type: 'object' as const,\n properties: schema?.properties || {},\n required: schema?.required || [],\n },\n };\n });\n }\n\n /**\n * Convert AI SDK tool choice to Anthropic format\n */\n private convertToolChoice(\n toolChoice?: LanguageModelV2ToolChoice\n ): Anthropic.MessageCreateParams['tool_choice'] {\n if (!toolChoice) {\n return undefined;\n }\n\n switch (toolChoice.type) {\n case 'auto':\n return { type: 'auto' };\n case 'none':\n // Anthropic doesn't have a direct 'none' - we handle this by not sending tools\n return undefined;\n case 'required':\n return { type: 'any' };\n case 'tool':\n return { type: 'tool', name: toolChoice.toolName };\n default:\n return undefined;\n }\n }\n\n /**\n * Convert AI SDK prompt to Anthropic messages format\n */\n private convertPrompt(prompt: LanguageModelV2Message[]): {\n system?: string;\n messages: Anthropic.MessageParam[];\n } {\n let systemMessage: string | undefined;\n const messages: Anthropic.MessageParam[] = [];\n\n for (const message of prompt) {\n if (message.role === 'system') {\n systemMessage = systemMessage ? `${systemMessage}\\n${message.content}` : message.content;\n continue;\n }\n\n if (message.role === 'user') {\n const content: Anthropic.ContentBlockParam[] = [];\n\n for (const part of message.content) {\n if (part.type === 'text') {\n content.push({ type: 'text', text: part.text });\n } else if (part.type === 'file') {\n // Handle file/image content if needed\n // For now, skip non-text content\n }\n }\n\n if (content.length > 0) {\n messages.push({ role: 'user', content });\n }\n } else if (message.role === 'assistant') {\n const content: Anthropic.ContentBlockParam[] = [];\n\n for (const part of message.content) {\n if (part.type === 'text') {\n content.push({ type: 'text', text: part.text });\n } else if (part.type === 'tool-call') {\n content.push({\n type: 'tool_use',\n id: part.toolCallId,\n name: part.toolName,\n input: typeof part.input === 'string' ? JSON.parse(part.input) : part.input,\n });\n }\n }\n\n if (content.length > 0) {\n messages.push({ role: 'assistant', content });\n }\n } else if (message.role === 'tool') {\n // Tool results need to be sent as user messages with tool_result content\n const content: Anthropic.ToolResultBlockParam[] = [];\n\n for (const part of message.content) {\n if (part.type === 'tool-result') {\n let resultContent: string;\n\n // Convert tool result output to string\n if (part.output.type === 'text') {\n resultContent = part.output.value;\n } else if (part.output.type === 'json') {\n resultContent = JSON.stringify(part.output.value);\n } else if (part.output.type === 'error-text') {\n resultContent = part.output.value;\n } else if (part.output.type === 'error-json') {\n resultContent = JSON.stringify(part.output.value);\n } else {\n resultContent = JSON.stringify(part.output);\n }\n\n content.push({\n type: 'tool_result',\n tool_use_id: part.toolCallId,\n content: resultContent,\n is_error: part.output.type.startsWith('error'),\n });\n }\n }\n\n if (content.length > 0) {\n messages.push({ role: 'user', content });\n }\n }\n }\n\n return { system: systemMessage, messages };\n }\n\n /**\n * Convert Anthropic finish reason to AI SDK format\n */\n private convertFinishReason(stopReason: string | null): LanguageModelV2FinishReason {\n switch (stopReason) {\n case 'end_turn':\n return 'stop';\n case 'stop_sequence':\n return 'stop';\n case 'max_tokens':\n return 'length';\n case 'tool_use':\n return 'tool-calls';\n default:\n return 'unknown';\n }\n }\n\n async doGenerate(options: LanguageModelV2CallOptions): Promise<{\n content: LanguageModelV2Content[];\n finishReason: LanguageModelV2FinishReason;\n usage: LanguageModelV2Usage;\n warnings: LanguageModelV2CallWarning[];\n }> {\n return this.doGenerateWithRetry(options, false);\n }\n\n private async doGenerateWithRetry(\n options: LanguageModelV2CallOptions,\n isRetry: boolean\n ): Promise<{\n content: LanguageModelV2Content[];\n finishReason: LanguageModelV2FinishReason;\n usage: LanguageModelV2Usage;\n warnings: LanguageModelV2CallWarning[];\n }> {\n const client = await this.getAnthropicClient(isRetry);\n const { system, messages } = this.convertPrompt(options.prompt);\n const tools = this.convertTools(options.tools);\n const toolChoice =\n options.toolChoice?.type !== 'none' ? this.convertToolChoice(options.toolChoice) : undefined;\n\n const anthropicModel = this.config.anthropicModel || 'claude-sonnet-4-5-20250929';\n const maxTokens = options.maxOutputTokens || this.config.maxTokens || 8192;\n\n try {\n const response = await client.messages.create({\n model: anthropicModel,\n max_tokens: maxTokens,\n system: system,\n messages: messages,\n tools: tools,\n tool_choice: tools ? toolChoice : undefined,\n temperature: options.temperature,\n top_p: options.topP,\n stop_sequences: options.stopSequences,\n });\n\n const content: LanguageModelV2Content[] = [];\n\n for (const block of response.content) {\n if (block.type === 'text') {\n content.push({\n type: 'text',\n text: block.text,\n });\n } else if (block.type === 'tool_use') {\n content.push({\n type: 'tool-call',\n toolCallId: block.id,\n toolName: block.name,\n input: JSON.stringify(block.input),\n });\n }\n }\n\n const usage: LanguageModelV2Usage = {\n inputTokens: response.usage.input_tokens,\n outputTokens: response.usage.output_tokens,\n totalTokens: response.usage.input_tokens + response.usage.output_tokens,\n };\n\n return {\n content,\n finishReason: this.convertFinishReason(response.stop_reason),\n usage,\n warnings: [],\n };\n } catch (error) {\n // Check for context overflow FIRST - these should NOT trigger token refresh\n if (this.isContextOverflowError(error)) {\n const apiError = error as InstanceType;\n throw new GitLabError({\n message: `Context overflow: ${apiError.message}. Please start a new session or use /compact to reduce context.`,\n statusCode: 400,\n cause: error,\n });\n }\n\n // If this is a token error and we haven't retried yet, refresh token and retry\n if (!isRetry && this.isTokenError(error)) {\n this.directAccessClient.invalidateToken();\n return this.doGenerateWithRetry(options, true);\n }\n\n if (error instanceof Anthropic.APIError) {\n throw new GitLabError({\n message: `Anthropic API error: ${error.message}`,\n statusCode: error.status,\n cause: error,\n });\n }\n throw error;\n }\n }\n\n async doStream(options: LanguageModelV2CallOptions): Promise<{\n stream: ReadableStream;\n request?: { body?: unknown };\n response?: { headers?: Record };\n }> {\n return this.doStreamWithRetry(options, false);\n }\n\n private async doStreamWithRetry(\n options: LanguageModelV2CallOptions,\n isRetry: boolean\n ): Promise<{\n stream: ReadableStream;\n request?: { body?: unknown };\n response?: { headers?: Record };\n }> {\n const client = await this.getAnthropicClient(isRetry);\n const { system, messages } = this.convertPrompt(options.prompt);\n const tools = this.convertTools(options.tools);\n const toolChoice =\n options.toolChoice?.type !== 'none' ? this.convertToolChoice(options.toolChoice) : undefined;\n\n const anthropicModel = this.config.anthropicModel || 'claude-sonnet-4-5-20250929';\n const maxTokens = options.maxOutputTokens || this.config.maxTokens || 8192;\n\n const requestBody = {\n model: anthropicModel,\n max_tokens: maxTokens,\n system: system,\n messages: messages,\n tools: tools,\n tool_choice: tools ? toolChoice : undefined,\n temperature: options.temperature,\n top_p: options.topP,\n stop_sequences: options.stopSequences,\n stream: true as const,\n };\n\n // Reference to this for use in the stream callback\n // eslint-disable-next-line @typescript-eslint/no-this-alias\n const self = this;\n\n const stream = new ReadableStream({\n start: async (controller) => {\n const contentBlocks: Record<\n number,\n | { type: 'text'; id: string }\n | { type: 'tool-call'; toolCallId: string; toolName: string; input: string }\n > = {};\n\n const usage: LanguageModelV2Usage = {\n inputTokens: 0,\n outputTokens: 0,\n totalTokens: 0,\n };\n let finishReason: LanguageModelV2FinishReason = 'unknown';\n\n try {\n const anthropicStream = client.messages.stream(requestBody, {\n signal: options.abortSignal,\n });\n\n // Stream start\n controller.enqueue({\n type: 'stream-start',\n warnings: [],\n });\n\n // Use event-based approach instead of for-await to ensure all events are received\n await new Promise((resolve, reject) => {\n anthropicStream.on('streamEvent', (event) => {\n try {\n switch (event.type) {\n case 'message_start':\n if (event.message.usage) {\n usage.inputTokens = event.message.usage.input_tokens;\n }\n controller.enqueue({\n type: 'response-metadata',\n id: event.message.id,\n modelId: event.message.model,\n });\n break;\n\n case 'content_block_start':\n if (event.content_block.type === 'text') {\n const textId = `text-${event.index}`;\n contentBlocks[event.index] = { type: 'text', id: textId };\n controller.enqueue({\n type: 'text-start',\n id: textId,\n });\n } else if (event.content_block.type === 'tool_use') {\n contentBlocks[event.index] = {\n type: 'tool-call',\n toolCallId: event.content_block.id,\n toolName: event.content_block.name,\n input: '',\n };\n controller.enqueue({\n type: 'tool-input-start',\n id: event.content_block.id,\n toolName: event.content_block.name,\n });\n }\n break;\n\n case 'content_block_delta': {\n const block = contentBlocks[event.index];\n if (event.delta.type === 'text_delta' && block?.type === 'text') {\n controller.enqueue({\n type: 'text-delta',\n id: block.id,\n delta: event.delta.text,\n });\n } else if (\n event.delta.type === 'input_json_delta' &&\n block?.type === 'tool-call'\n ) {\n block.input += event.delta.partial_json;\n controller.enqueue({\n type: 'tool-input-delta',\n id: block.toolCallId,\n delta: event.delta.partial_json,\n });\n }\n break;\n }\n\n case 'content_block_stop': {\n const block = contentBlocks[event.index];\n if (block?.type === 'text') {\n controller.enqueue({\n type: 'text-end',\n id: block.id,\n });\n } else if (block?.type === 'tool-call') {\n controller.enqueue({\n type: 'tool-input-end',\n id: block.toolCallId,\n });\n\n controller.enqueue({\n type: 'tool-call',\n toolCallId: block.toolCallId,\n toolName: block.toolName,\n input: block.input === '' ? '{}' : block.input,\n });\n }\n delete contentBlocks[event.index];\n break;\n }\n\n case 'message_delta':\n if (event.usage) {\n usage.outputTokens = event.usage.output_tokens;\n usage.totalTokens = (usage.inputTokens || 0) + event.usage.output_tokens;\n }\n if (event.delta.stop_reason) {\n finishReason = self.convertFinishReason(event.delta.stop_reason);\n }\n break;\n\n case 'message_stop': {\n controller.enqueue({\n type: 'finish',\n finishReason,\n usage,\n });\n break;\n }\n }\n } catch (error) {\n controller.enqueue({\n type: 'error',\n error: error instanceof Error ? error : new Error(String(error)),\n });\n }\n });\n\n anthropicStream.on('end', () => {\n resolve();\n });\n\n anthropicStream.on('error', (error) => {\n reject(error);\n });\n });\n\n // Emit any pending tool calls if stream ended without content_block_stop\n for (const [, block] of Object.entries(contentBlocks)) {\n if (block.type === 'tool-call') {\n controller.enqueue({\n type: 'tool-input-end',\n id: block.toolCallId,\n });\n controller.enqueue({\n type: 'tool-call',\n toolCallId: block.toolCallId,\n toolName: block.toolName,\n input: block.input === '' ? '{}' : block.input,\n });\n }\n }\n\n controller.close();\n } catch (error) {\n // Emit any pending tool calls before handling the error\n for (const [, block] of Object.entries(contentBlocks)) {\n if (block.type === 'tool-call') {\n controller.enqueue({\n type: 'tool-input-end',\n id: block.toolCallId,\n });\n controller.enqueue({\n type: 'tool-call',\n toolCallId: block.toolCallId,\n toolName: block.toolName,\n input: block.input === '' ? '{}' : block.input,\n });\n }\n }\n\n // Check for context overflow FIRST - these should NOT trigger token refresh\n if (self.isContextOverflowError(error)) {\n const apiError = error as InstanceType;\n controller.enqueue({\n type: 'error',\n error: new GitLabError({\n message: `Context overflow: ${apiError.message}. Please start a new session or use /compact to reduce context.`,\n statusCode: 400,\n cause: error,\n }),\n });\n controller.close();\n return;\n }\n\n // If this is a token error and we haven't retried yet, we need to signal retry\n // For streaming, we close this stream with an error and the caller should retry\n if (!isRetry && self.isTokenError(error)) {\n self.directAccessClient.invalidateToken();\n // Signal that a retry is needed with a special error\n controller.enqueue({\n type: 'error',\n error: new GitLabError({\n message: 'TOKEN_REFRESH_NEEDED',\n cause: error,\n }),\n });\n controller.close();\n return;\n }\n\n if (error instanceof Anthropic.APIError) {\n controller.enqueue({\n type: 'error',\n error: new GitLabError({\n message: `Anthropic API error: ${error.message}`,\n statusCode: error.status,\n cause: error,\n }),\n });\n } else {\n controller.enqueue({\n type: 'error',\n error,\n });\n }\n controller.close();\n }\n },\n });\n\n return {\n stream,\n request: { body: requestBody },\n };\n }\n}\n","import { z } from 'zod';\nimport { GitLabError } from './gitlab-error';\n\n/**\n * Response from /api/v4/ai/third_party_agents/direct_access\n */\nexport const directAccessTokenSchema = z.object({\n headers: z.record(z.string()),\n token: z.string(),\n});\n\nexport type DirectAccessToken = z.infer;\n\nexport const DEFAULT_AI_GATEWAY_URL = 'https://cloud.gitlab.com';\n\nexport interface GitLabDirectAccessConfig {\n instanceUrl: string;\n getHeaders: () => Record;\n fetch?: typeof fetch;\n /**\n * Optional callback to refresh the API key when a 401 error occurs.\n * Should clear cached credentials and re-fetch from auth provider.\n */\n refreshApiKey?: () => Promise;\n /**\n * Feature flags to pass to the GitLab API\n */\n featureFlags?: Record;\n /**\n * AI Gateway URL for the Anthropic proxy.\n * Can also be set via GITLAB_AI_GATEWAY_URL environment variable.\n * @default 'https://cloud.gitlab.com'\n */\n aiGatewayUrl?: string;\n}\n\n/**\n * Client for GitLab's third-party agents direct access API.\n * This allows routing requests through GitLab's proxy to Anthropic.\n */\nexport class GitLabDirectAccessClient {\n private readonly config: GitLabDirectAccessConfig;\n private readonly fetchFn: typeof fetch;\n private readonly aiGatewayUrl: string;\n private cachedToken: DirectAccessToken | null = null;\n private tokenExpiresAt: number = 0;\n\n constructor(config: GitLabDirectAccessConfig) {\n this.config = config;\n this.fetchFn = config.fetch ?? fetch;\n this.aiGatewayUrl =\n config.aiGatewayUrl || process.env['GITLAB_AI_GATEWAY_URL'] || DEFAULT_AI_GATEWAY_URL;\n }\n\n /**\n * Get a direct access token for the Anthropic proxy.\n * Tokens are cached for 25 minutes (they expire after 30 minutes).\n * @param forceRefresh - If true, ignores the cache and fetches a new token\n */\n async getDirectAccessToken(forceRefresh: boolean = false): Promise {\n // Check if we have a valid cached token (unless force refresh is requested)\n const now = Date.now();\n if (!forceRefresh && this.cachedToken && this.tokenExpiresAt > now) {\n return this.cachedToken;\n }\n\n // Clear cache if forcing refresh\n if (forceRefresh) {\n this.invalidateToken();\n }\n\n const url = `${this.config.instanceUrl}/api/v4/ai/third_party_agents/direct_access`;\n\n // Prepare request body with feature flags if provided\n const requestBody: Record = {};\n if (this.config.featureFlags && Object.keys(this.config.featureFlags).length > 0) {\n requestBody.feature_flags = this.config.featureFlags;\n }\n\n try {\n const response = await this.fetchFn(url, {\n method: 'POST',\n headers: {\n ...this.config.getHeaders(),\n 'Content-Type': 'application/json',\n },\n body: JSON.stringify(requestBody),\n });\n\n if (!response.ok) {\n const errorText = await response.text();\n\n // If we get a 401 and have a refresh callback, try refreshing the API key once\n if (response.status === 401 && this.config.refreshApiKey && !forceRefresh) {\n try {\n // Refresh the API key (this should clear cached credentials and re-fetch from auth)\n await this.config.refreshApiKey();\n\n // Retry the request with the refreshed credentials\n return await this.getDirectAccessToken(true);\n } catch (refreshError) {\n // If refresh fails, throw the original 401 error\n throw new GitLabError({\n message: `Failed to get direct access token: ${response.status} ${response.statusText} - ${errorText}`,\n statusCode: response.status,\n responseBody: errorText,\n });\n }\n }\n\n // Provide helpful error message for 403 errors (common with self-hosted instances)\n if (response.status === 403) {\n throw new GitLabError({\n message:\n `Access denied to GitLab AI features (${this.config.instanceUrl}). ` +\n `This may indicate that: (1) GitLab Duo is not enabled on this instance, ` +\n `(2) Your account does not have access to AI features, or ` +\n `(3) The third-party agents feature is not available. ` +\n `Original error: ${response.status} ${response.statusText} - ${errorText}`,\n statusCode: response.status,\n responseBody: errorText,\n });\n }\n\n throw new GitLabError({\n message: `Failed to get direct access token: ${response.status} ${response.statusText} - ${errorText}`,\n statusCode: response.status,\n responseBody: errorText,\n });\n }\n\n const data = await response.json();\n const token = directAccessTokenSchema.parse(data);\n\n // Cache the token for 25 minutes (tokens expire after 30 minutes)\n this.cachedToken = token;\n this.tokenExpiresAt = now + 25 * 60 * 1000;\n\n return token;\n } catch (error) {\n if (error instanceof GitLabError) {\n throw error;\n }\n throw new GitLabError({\n message: `Failed to get direct access token: ${error}`,\n cause: error,\n });\n }\n }\n\n /**\n * Get the Anthropic proxy base URL\n */\n getAnthropicProxyUrl(): string {\n const baseUrl = this.aiGatewayUrl.replace(/\\/$/, '');\n return `${baseUrl}/ai/v1/proxy/anthropic/`;\n }\n\n /**\n * Get the OpenAI proxy base URL\n * Note: The OpenAI SDK expects a base URL like https://api.openai.com/v1\n * and appends paths like /chat/completions. So we need /v1 at the end.\n */\n getOpenAIProxyUrl(): string {\n const baseUrl = this.aiGatewayUrl.replace(/\\/$/, '');\n return `${baseUrl}/ai/v1/proxy/openai/v1`;\n }\n\n /**\n * Invalidate the cached token\n */\n invalidateToken(): void {\n this.cachedToken = null;\n this.tokenExpiresAt = 0;\n }\n}\n","export interface GitLabErrorOptions {\n message: string;\n statusCode?: number;\n responseBody?: string;\n cause?: unknown;\n}\n\nexport class GitLabError extends Error {\n readonly statusCode?: number;\n readonly responseBody?: string;\n readonly cause?: unknown;\n\n constructor(options: GitLabErrorOptions) {\n super(options.message);\n this.name = 'GitLabError';\n this.statusCode = options.statusCode;\n this.responseBody = options.responseBody;\n this.cause = options.cause;\n\n // Maintain proper stack trace for where error was thrown (only available on V8)\n if (Error.captureStackTrace) {\n Error.captureStackTrace(this, GitLabError);\n }\n }\n\n static fromResponse(response: Response, body: string): GitLabError {\n return new GitLabError({\n message: `GitLab API error: ${response.status} ${response.statusText}`,\n statusCode: response.status,\n responseBody: body,\n });\n }\n\n isAuthError(): boolean {\n return this.statusCode === 401;\n }\n\n isRateLimitError(): boolean {\n return this.statusCode === 429;\n }\n\n isForbiddenError(): boolean {\n return this.statusCode === 403;\n }\n\n isServerError(): boolean {\n return this.statusCode !== undefined && this.statusCode >= 500;\n }\n\n /**\n * Check if this error is a context overflow error (prompt too long).\n * These errors occur when the conversation exceeds the model's token limit.\n */\n isContextOverflowError(): boolean {\n if (this.statusCode !== 400) {\n return false;\n }\n const message = this.message?.toLowerCase() || '';\n return (\n message.includes('context overflow') ||\n message.includes('prompt is too long') ||\n message.includes('prompt too long') ||\n (message.includes('tokens') && message.includes('maximum'))\n );\n }\n}\n","import OpenAI from 'openai';\nimport { GitLabDirectAccessClient } from './gitlab-direct-access';\nimport { GitLabError } from './gitlab-error';\nimport { isResponsesApiModel } from './model-mappings';\n\nimport type {\n LanguageModelV2,\n LanguageModelV2CallOptions,\n LanguageModelV2StreamPart,\n LanguageModelV2FinishReason,\n LanguageModelV2CallWarning,\n LanguageModelV2Content,\n LanguageModelV2Usage,\n LanguageModelV2FunctionTool,\n LanguageModelV2Message,\n LanguageModelV2ToolChoice,\n} from '@ai-sdk/provider';\n\nexport interface GitLabOpenAIConfig {\n provider: string;\n instanceUrl: string;\n getHeaders: () => Record;\n fetch?: typeof fetch;\n refreshApiKey?: () => Promise;\n openaiModel?: string;\n maxTokens?: number;\n featureFlags?: {\n DuoAgentPlatformNext: true;\n } & Record;\n aiGatewayUrl?: string;\n /** Whether to use the Responses API instead of Chat Completions API */\n useResponsesApi?: boolean;\n /**\n * Custom headers for AI Gateway OpenAI proxy requests.\n * Merged with headers from direct_access token response.\n */\n aiGatewayHeaders?: Record;\n}\n\nexport class GitLabOpenAILanguageModel implements LanguageModelV2 {\n readonly specificationVersion = 'v2' as const;\n readonly modelId: string;\n readonly supportedUrls: Record = {};\n\n private readonly config: GitLabOpenAIConfig;\n private readonly directAccessClient: GitLabDirectAccessClient;\n private readonly useResponsesApi: boolean;\n private openaiClient: OpenAI | null = null;\n\n constructor(modelId: string, config: GitLabOpenAIConfig) {\n this.modelId = modelId;\n this.config = config;\n this.useResponsesApi = config.useResponsesApi ?? isResponsesApiModel(modelId);\n\n this.directAccessClient = new GitLabDirectAccessClient({\n instanceUrl: config.instanceUrl,\n getHeaders: config.getHeaders,\n refreshApiKey: config.refreshApiKey,\n fetch: config.fetch,\n featureFlags: config.featureFlags,\n aiGatewayUrl: config.aiGatewayUrl,\n });\n }\n\n get provider(): string {\n return this.config.provider;\n }\n\n private async getOpenAIClient(forceRefresh: boolean = false): Promise {\n const tokenData = await this.directAccessClient.getDirectAccessToken(forceRefresh);\n const { 'x-api-key': _removed, ...filteredHeaders } = tokenData.headers;\n\n // Merge: tokenData headers < custom aiGatewayHeaders\n const mergedHeaders = {\n ...filteredHeaders,\n ...this.config.aiGatewayHeaders,\n };\n\n this.openaiClient = new OpenAI({\n apiKey: tokenData.token,\n baseURL: this.directAccessClient.getOpenAIProxyUrl(),\n defaultHeaders: mergedHeaders,\n });\n\n return this.openaiClient;\n }\n\n private isTokenError(error: unknown): boolean {\n if (error instanceof OpenAI.APIError) {\n if (error.status === 401) {\n return true;\n }\n const message = error.message?.toLowerCase() || '';\n if (\n message.includes('token') &&\n (message.includes('expired') || message.includes('revoked') || message.includes('invalid'))\n ) {\n return true;\n }\n }\n return false;\n }\n\n /**\n * Check if an error is a context overflow error (prompt too long)\n * These should NOT trigger token refresh and should be reported to the user.\n */\n private isContextOverflowError(error: unknown): boolean {\n if (error instanceof OpenAI.APIError) {\n // 400 Bad Request with prompt too long message\n if (error.status === 400) {\n const message = error.message?.toLowerCase() || '';\n if (\n message.includes('prompt is too long') ||\n message.includes('prompt too long') ||\n (message.includes('tokens') && message.includes('maximum'))\n ) {\n return true;\n }\n }\n }\n return false;\n }\n\n private convertTools(\n tools?: LanguageModelV2CallOptions['tools']\n ): OpenAI.ChatCompletionTool[] | undefined {\n if (!tools || tools.length === 0) {\n return undefined;\n }\n\n return tools\n .filter((tool): tool is LanguageModelV2FunctionTool => tool.type === 'function')\n .map((tool) => {\n const schema = tool.inputSchema as Record;\n return {\n type: 'function' as const,\n function: {\n name: tool.name,\n description: tool.description || '',\n // Ensure the schema has type: 'object' as OpenAI requires it\n parameters: {\n type: 'object',\n ...schema,\n },\n },\n };\n });\n }\n\n private convertToolChoice(\n toolChoice?: LanguageModelV2ToolChoice\n ): OpenAI.ChatCompletionToolChoiceOption | undefined {\n if (!toolChoice) {\n return undefined;\n }\n\n switch (toolChoice.type) {\n case 'auto':\n return 'auto';\n case 'none':\n return 'none';\n case 'required':\n return 'required';\n case 'tool':\n return { type: 'function', function: { name: toolChoice.toolName } };\n default:\n return undefined;\n }\n }\n\n private convertPrompt(prompt: LanguageModelV2Message[]): OpenAI.ChatCompletionMessageParam[] {\n const messages: OpenAI.ChatCompletionMessageParam[] = [];\n\n for (const message of prompt) {\n if (message.role === 'system') {\n messages.push({ role: 'system', content: message.content });\n continue;\n }\n\n if (message.role === 'user') {\n const textParts = message.content\n .filter((part) => part.type === 'text')\n .map((part) => part.text);\n if (textParts.length > 0) {\n messages.push({ role: 'user', content: textParts.join('\\n') });\n }\n } else if (message.role === 'assistant') {\n const textParts: string[] = [];\n const toolCalls: OpenAI.ChatCompletionMessageToolCall[] = [];\n\n for (const part of message.content) {\n if (part.type === 'text') {\n textParts.push(part.text);\n } else if (part.type === 'tool-call') {\n toolCalls.push({\n id: part.toolCallId,\n type: 'function',\n function: {\n name: part.toolName,\n arguments: typeof part.input === 'string' ? part.input : JSON.stringify(part.input),\n },\n });\n }\n }\n\n const assistantMessage: OpenAI.ChatCompletionAssistantMessageParam = {\n role: 'assistant',\n content: textParts.length > 0 ? textParts.join('\\n') : null,\n };\n if (toolCalls.length > 0) {\n assistantMessage.tool_calls = toolCalls;\n }\n messages.push(assistantMessage);\n } else if (message.role === 'tool') {\n for (const part of message.content) {\n if (part.type === 'tool-result') {\n let resultContent: string;\n if (part.output.type === 'text') {\n resultContent = part.output.value;\n } else if (part.output.type === 'json') {\n resultContent = JSON.stringify(part.output.value);\n } else if (part.output.type === 'error-text') {\n resultContent = part.output.value;\n } else if (part.output.type === 'error-json') {\n resultContent = JSON.stringify(part.output.value);\n } else {\n resultContent = JSON.stringify(part.output);\n }\n messages.push({\n role: 'tool',\n tool_call_id: part.toolCallId,\n content: resultContent,\n });\n }\n }\n }\n }\n\n return messages;\n }\n\n private convertFinishReason(\n finishReason: string | null | undefined\n ): LanguageModelV2FinishReason {\n switch (finishReason) {\n case 'stop':\n return 'stop';\n case 'length':\n return 'length';\n case 'tool_calls':\n return 'tool-calls';\n case 'content_filter':\n return 'content-filter';\n default:\n return 'unknown';\n }\n }\n\n /**\n * Convert tools to Responses API format\n */\n private convertToolsForResponses(\n tools?: LanguageModelV2CallOptions['tools']\n ): OpenAI.Responses.FunctionTool[] | undefined {\n if (!tools || tools.length === 0) {\n return undefined;\n }\n\n return tools\n .filter((tool): tool is LanguageModelV2FunctionTool => tool.type === 'function')\n .map((tool) => {\n // Clone schema and remove $schema field which can confuse the model\n // Zod 4's toJSONSchema() adds \"$schema\": \"https://json-schema.org/draft/2020-12/schema\"\n const schema = { ...(tool.inputSchema as Record) };\n delete schema['$schema'];\n\n return {\n type: 'function' as const,\n name: tool.name,\n description: tool.description || '',\n parameters: schema,\n strict: false,\n };\n });\n }\n\n /**\n * Convert prompt to Responses API input format\n */\n private convertPromptForResponses(\n prompt: LanguageModelV2Message[]\n ): OpenAI.Responses.ResponseInput {\n const items: OpenAI.Responses.ResponseInputItem[] = [];\n\n for (const message of prompt) {\n if (message.role === 'system') {\n // System messages become instructions, handled separately\n continue;\n }\n\n if (message.role === 'user') {\n const textParts = message.content\n .filter((part) => part.type === 'text')\n .map((part) => part.text);\n if (textParts.length > 0) {\n items.push({\n type: 'message',\n role: 'user',\n content: textParts.map((text) => ({ type: 'input_text' as const, text })),\n } as OpenAI.Responses.ResponseInputItem);\n }\n } else if (message.role === 'assistant') {\n // Handle text content as output message\n const textParts: string[] = [];\n for (const part of message.content) {\n if (part.type === 'text') {\n textParts.push(part.text);\n } else if (part.type === 'tool-call') {\n // Tool calls are function_call items in Responses API\n items.push({\n type: 'function_call',\n call_id: part.toolCallId,\n name: part.toolName,\n arguments: typeof part.input === 'string' ? part.input : JSON.stringify(part.input),\n } as OpenAI.Responses.ResponseInputItem);\n }\n }\n\n if (textParts.length > 0) {\n items.push({\n type: 'message',\n role: 'assistant',\n content: [{ type: 'output_text', text: textParts.join('\\n'), annotations: [] }],\n } as OpenAI.Responses.ResponseInputItem);\n }\n } else if (message.role === 'tool') {\n for (const part of message.content) {\n if (part.type === 'tool-result') {\n let resultContent: string;\n if (part.output.type === 'text') {\n resultContent = part.output.value;\n } else if (part.output.type === 'json') {\n resultContent = JSON.stringify(part.output.value);\n } else if (part.output.type === 'error-text') {\n resultContent = part.output.value;\n } else if (part.output.type === 'error-json') {\n resultContent = JSON.stringify(part.output.value);\n } else {\n resultContent = JSON.stringify(part.output);\n }\n items.push({\n type: 'function_call_output',\n call_id: part.toolCallId,\n output: resultContent,\n } as OpenAI.Responses.ResponseInputItem);\n }\n }\n }\n }\n\n return items;\n }\n\n /**\n * Extract system instructions from prompt\n */\n private extractSystemInstructions(prompt: LanguageModelV2Message[]): string | undefined {\n const systemMessages = prompt\n .filter((m) => m.role === 'system')\n .map((m) => m.content)\n .join('\\n');\n return systemMessages || undefined;\n }\n\n /**\n * Convert Responses API status to finish reason\n * Note: Responses API returns 'completed' even when making tool calls,\n * so we need to check the content for tool calls separately.\n */\n private convertResponsesStatus(\n status: string | undefined,\n hasToolCalls: boolean = false\n ): LanguageModelV2FinishReason {\n // If we have tool calls, return 'tool-calls' regardless of status\n if (hasToolCalls) {\n return 'tool-calls';\n }\n\n switch (status) {\n case 'completed':\n return 'stop';\n case 'incomplete':\n return 'length';\n case 'cancelled':\n return 'stop';\n case 'failed':\n return 'error';\n default:\n return 'unknown';\n }\n }\n\n async doGenerate(options: LanguageModelV2CallOptions): Promise<{\n content: LanguageModelV2Content[];\n finishReason: LanguageModelV2FinishReason;\n usage: LanguageModelV2Usage;\n warnings: LanguageModelV2CallWarning[];\n }> {\n if (this.useResponsesApi) {\n return this.doGenerateWithResponsesApi(options, false);\n }\n return this.doGenerateWithChatApi(options, false);\n }\n\n private async doGenerateWithChatApi(\n options: LanguageModelV2CallOptions,\n isRetry: boolean\n ): Promise<{\n content: LanguageModelV2Content[];\n finishReason: LanguageModelV2FinishReason;\n usage: LanguageModelV2Usage;\n warnings: LanguageModelV2CallWarning[];\n }> {\n const client = await this.getOpenAIClient(isRetry);\n const messages = this.convertPrompt(options.prompt);\n const tools = this.convertTools(options.tools);\n const toolChoice =\n options.toolChoice?.type !== 'none' ? this.convertToolChoice(options.toolChoice) : undefined;\n\n const openaiModel = this.config.openaiModel || 'gpt-4o';\n const maxTokens = options.maxOutputTokens || this.config.maxTokens || 8192;\n\n try {\n const response = await client.chat.completions.create({\n model: openaiModel,\n max_completion_tokens: maxTokens,\n messages: messages,\n tools: tools,\n tool_choice: tools ? toolChoice : undefined,\n temperature: options.temperature,\n top_p: options.topP,\n stop: options.stopSequences,\n });\n\n const choice = response.choices[0];\n const content: LanguageModelV2Content[] = [];\n\n if (choice?.message.content) {\n content.push({ type: 'text', text: choice.message.content });\n }\n\n if (choice?.message.tool_calls) {\n for (const toolCall of choice.message.tool_calls) {\n if (toolCall.type === 'function') {\n content.push({\n type: 'tool-call',\n toolCallId: toolCall.id,\n toolName: toolCall.function.name,\n input: toolCall.function.arguments,\n });\n }\n }\n }\n\n const usage: LanguageModelV2Usage = {\n inputTokens: response.usage?.prompt_tokens || 0,\n outputTokens: response.usage?.completion_tokens || 0,\n totalTokens: response.usage?.total_tokens || 0,\n };\n\n return {\n content,\n finishReason: this.convertFinishReason(choice?.finish_reason),\n usage,\n warnings: [],\n };\n } catch (error) {\n // Check for context overflow FIRST - these should NOT trigger token refresh\n if (this.isContextOverflowError(error)) {\n const apiError = error as InstanceType;\n throw new GitLabError({\n message: `Context overflow: ${apiError.message}. Please start a new session or use /compact to reduce context.`,\n statusCode: 400,\n cause: error,\n });\n }\n\n if (!isRetry && this.isTokenError(error)) {\n this.directAccessClient.invalidateToken();\n return this.doGenerateWithChatApi(options, true);\n }\n\n if (error instanceof OpenAI.APIError) {\n throw new GitLabError({\n message: `OpenAI API error: ${error.message}`,\n statusCode: error.status,\n cause: error,\n });\n }\n throw error;\n }\n }\n\n private async doGenerateWithResponsesApi(\n options: LanguageModelV2CallOptions,\n isRetry: boolean\n ): Promise<{\n content: LanguageModelV2Content[];\n finishReason: LanguageModelV2FinishReason;\n usage: LanguageModelV2Usage;\n warnings: LanguageModelV2CallWarning[];\n }> {\n const client = await this.getOpenAIClient(isRetry);\n const input = this.convertPromptForResponses(options.prompt);\n const tools = this.convertToolsForResponses(options.tools);\n const instructions = this.extractSystemInstructions(options.prompt);\n\n const openaiModel = this.config.openaiModel || 'gpt-5-codex';\n const maxTokens = options.maxOutputTokens || this.config.maxTokens || 8192;\n\n try {\n const response = await client.responses.create({\n model: openaiModel,\n input,\n instructions,\n tools,\n max_output_tokens: maxTokens,\n temperature: options.temperature,\n top_p: options.topP,\n store: false,\n });\n\n const content: LanguageModelV2Content[] = [];\n let hasToolCalls = false;\n\n // Process output items\n for (const item of response.output || []) {\n if (item.type === 'message' && item.role === 'assistant') {\n for (const contentItem of item.content || []) {\n if (contentItem.type === 'output_text') {\n content.push({ type: 'text', text: contentItem.text });\n }\n }\n } else if (item.type === 'function_call') {\n hasToolCalls = true;\n content.push({\n type: 'tool-call',\n toolCallId: item.call_id,\n toolName: item.name,\n input: item.arguments,\n });\n }\n }\n\n const usage: LanguageModelV2Usage = {\n inputTokens: response.usage?.input_tokens || 0,\n outputTokens: response.usage?.output_tokens || 0,\n totalTokens: response.usage?.total_tokens || 0,\n };\n\n return {\n content,\n finishReason: this.convertResponsesStatus(response.status, hasToolCalls),\n usage,\n warnings: [],\n };\n } catch (error) {\n // Check for context overflow FIRST - these should NOT trigger token refresh\n if (this.isContextOverflowError(error)) {\n const apiError = error as InstanceType;\n throw new GitLabError({\n message: `Context overflow: ${apiError.message}. Please start a new session or use /compact to reduce context.`,\n statusCode: 400,\n cause: error,\n });\n }\n\n if (!isRetry && this.isTokenError(error)) {\n this.directAccessClient.invalidateToken();\n return this.doGenerateWithResponsesApi(options, true);\n }\n\n if (error instanceof OpenAI.APIError) {\n throw new GitLabError({\n message: `OpenAI API error: ${error.message}`,\n statusCode: error.status,\n cause: error,\n });\n }\n throw error;\n }\n }\n\n async doStream(options: LanguageModelV2CallOptions): Promise<{\n stream: ReadableStream;\n request?: { body?: unknown };\n response?: { headers?: Record };\n }> {\n if (this.useResponsesApi) {\n return this.doStreamWithResponsesApi(options, false);\n }\n return this.doStreamWithChatApi(options, false);\n }\n\n private async doStreamWithChatApi(\n options: LanguageModelV2CallOptions,\n isRetry: boolean\n ): Promise<{\n stream: ReadableStream;\n request?: { body?: unknown };\n response?: { headers?: Record };\n }> {\n const client = await this.getOpenAIClient(isRetry);\n const messages = this.convertPrompt(options.prompt);\n const tools = this.convertTools(options.tools);\n const toolChoice =\n options.toolChoice?.type !== 'none' ? this.convertToolChoice(options.toolChoice) : undefined;\n\n const openaiModel = this.config.openaiModel || 'gpt-4o';\n const maxTokens = options.maxOutputTokens || this.config.maxTokens || 8192;\n\n const requestBody = {\n model: openaiModel,\n max_completion_tokens: maxTokens,\n messages: messages,\n tools: tools,\n tool_choice: tools ? toolChoice : undefined,\n temperature: options.temperature,\n top_p: options.topP,\n stop: options.stopSequences,\n stream: true as const,\n stream_options: { include_usage: true },\n };\n\n // eslint-disable-next-line @typescript-eslint/no-this-alias\n const self = this;\n\n const stream = new ReadableStream({\n start: async (controller) => {\n const toolCalls: Record = {};\n\n const usage: LanguageModelV2Usage = {\n inputTokens: 0,\n outputTokens: 0,\n totalTokens: 0,\n };\n let finishReason: LanguageModelV2FinishReason = 'unknown';\n let textStarted = false;\n const textId = 'text-0';\n\n try {\n const openaiStream = await client.chat.completions.create({\n ...requestBody,\n stream: true,\n });\n\n controller.enqueue({ type: 'stream-start', warnings: [] });\n\n for await (const chunk of openaiStream) {\n const choice = chunk.choices?.[0];\n\n if (chunk.id && !textStarted) {\n controller.enqueue({\n type: 'response-metadata',\n id: chunk.id,\n modelId: chunk.model,\n });\n }\n\n if (choice?.delta?.content) {\n if (!textStarted) {\n controller.enqueue({ type: 'text-start', id: textId });\n textStarted = true;\n }\n controller.enqueue({\n type: 'text-delta',\n id: textId,\n delta: choice.delta.content,\n });\n }\n\n if (choice?.delta?.tool_calls) {\n for (const tc of choice.delta.tool_calls) {\n const idx = tc.index;\n if (!toolCalls[idx]) {\n toolCalls[idx] = {\n id: tc.id || '',\n name: tc.function?.name || '',\n arguments: '',\n };\n controller.enqueue({\n type: 'tool-input-start',\n id: toolCalls[idx].id,\n toolName: toolCalls[idx].name,\n });\n }\n if (tc.function?.arguments) {\n toolCalls[idx].arguments += tc.function.arguments;\n controller.enqueue({\n type: 'tool-input-delta',\n id: toolCalls[idx].id,\n delta: tc.function.arguments,\n });\n }\n }\n }\n\n if (choice?.finish_reason) {\n finishReason = self.convertFinishReason(choice.finish_reason);\n }\n\n if (chunk.usage) {\n usage.inputTokens = chunk.usage.prompt_tokens || 0;\n usage.outputTokens = chunk.usage.completion_tokens || 0;\n usage.totalTokens = chunk.usage.total_tokens || 0;\n }\n }\n\n if (textStarted) {\n controller.enqueue({ type: 'text-end', id: textId });\n }\n\n for (const [, tc] of Object.entries(toolCalls)) {\n controller.enqueue({ type: 'tool-input-end', id: tc.id });\n controller.enqueue({\n type: 'tool-call',\n toolCallId: tc.id,\n toolName: tc.name,\n input: tc.arguments || '{}',\n });\n }\n\n controller.enqueue({ type: 'finish', finishReason, usage });\n controller.close();\n } catch (error) {\n // Check for context overflow FIRST - these should NOT trigger token refresh\n if (self.isContextOverflowError(error)) {\n const apiError = error as InstanceType;\n controller.enqueue({\n type: 'error',\n error: new GitLabError({\n message: `Context overflow: ${apiError.message}. Please start a new session or use /compact to reduce context.`,\n statusCode: 400,\n cause: error,\n }),\n });\n controller.close();\n return;\n }\n\n if (!isRetry && self.isTokenError(error)) {\n self.directAccessClient.invalidateToken();\n controller.enqueue({\n type: 'error',\n error: new GitLabError({ message: 'TOKEN_REFRESH_NEEDED', cause: error }),\n });\n controller.close();\n return;\n }\n\n if (error instanceof OpenAI.APIError) {\n controller.enqueue({\n type: 'error',\n error: new GitLabError({\n message: `OpenAI API error: ${error.message}`,\n statusCode: error.status,\n cause: error,\n }),\n });\n } else {\n controller.enqueue({ type: 'error', error });\n }\n controller.close();\n }\n },\n });\n\n return { stream, request: { body: requestBody } };\n }\n\n private async doStreamWithResponsesApi(\n options: LanguageModelV2CallOptions,\n isRetry: boolean\n ): Promise<{\n stream: ReadableStream;\n request?: { body?: unknown };\n response?: { headers?: Record };\n }> {\n const client = await this.getOpenAIClient(isRetry);\n const input = this.convertPromptForResponses(options.prompt);\n const tools = this.convertToolsForResponses(options.tools);\n const instructions = this.extractSystemInstructions(options.prompt);\n\n const openaiModel = this.config.openaiModel || 'gpt-5-codex';\n const maxTokens = options.maxOutputTokens || this.config.maxTokens || 8192;\n\n const requestBody = {\n model: openaiModel,\n input,\n instructions,\n tools,\n max_output_tokens: maxTokens,\n temperature: options.temperature,\n top_p: options.topP,\n store: false,\n stream: true as const,\n };\n\n // eslint-disable-next-line @typescript-eslint/no-this-alias\n const self = this;\n\n const stream = new ReadableStream({\n start: async (controller) => {\n // Use output_index as key (like OpenCode does) to track tool calls across events\n const toolCalls: Record = {};\n const usage: LanguageModelV2Usage = {\n inputTokens: 0,\n outputTokens: 0,\n totalTokens: 0,\n };\n let finishReason: LanguageModelV2FinishReason = 'unknown';\n let textStarted = false;\n const textId = 'text-0';\n\n try {\n const openaiStream = await client.responses.create({\n ...requestBody,\n stream: true,\n });\n\n controller.enqueue({ type: 'stream-start', warnings: [] });\n\n for await (const event of openaiStream) {\n // Handle different event types from Responses API streaming\n if (event.type === 'response.created') {\n controller.enqueue({\n type: 'response-metadata',\n id: event.response.id,\n modelId: event.response.model,\n });\n } else if (event.type === 'response.output_item.added') {\n // Track function calls when they start, keyed by output_index\n if (event.item.type === 'function_call') {\n const outputIndex = event.output_index;\n const callId = event.item.call_id;\n toolCalls[outputIndex] = {\n callId,\n name: event.item.name,\n arguments: '',\n };\n controller.enqueue({\n type: 'tool-input-start',\n id: callId,\n toolName: event.item.name,\n });\n }\n } else if (event.type === 'response.output_text.delta') {\n if (!textStarted) {\n controller.enqueue({ type: 'text-start', id: textId });\n textStarted = true;\n }\n controller.enqueue({\n type: 'text-delta',\n id: textId,\n delta: event.delta,\n });\n } else if (event.type === 'response.function_call_arguments.delta') {\n // Use output_index to find the tool call (like OpenCode)\n const outputIndex = event.output_index;\n const tc = toolCalls[outputIndex];\n if (tc) {\n tc.arguments += event.delta;\n controller.enqueue({\n type: 'tool-input-delta',\n id: tc.callId,\n delta: event.delta,\n });\n }\n } else if (event.type === 'response.function_call_arguments.done') {\n const outputIndex = event.output_index;\n const tc = toolCalls[outputIndex];\n if (tc) {\n tc.arguments = event.arguments;\n }\n } else if (event.type === 'response.completed') {\n // Check if there are tool calls to determine finish reason\n const hasToolCalls = Object.keys(toolCalls).length > 0;\n finishReason = self.convertResponsesStatus(event.response.status, hasToolCalls);\n if (event.response.usage) {\n usage.inputTokens = event.response.usage.input_tokens || 0;\n usage.outputTokens = event.response.usage.output_tokens || 0;\n usage.totalTokens = event.response.usage.total_tokens || 0;\n }\n }\n }\n\n if (textStarted) {\n controller.enqueue({ type: 'text-end', id: textId });\n }\n\n // Check if we have tool calls to set the correct finish reason\n const hasToolCalls = Object.keys(toolCalls).length > 0;\n if (hasToolCalls && finishReason === 'stop') {\n finishReason = 'tool-calls';\n }\n\n for (const tc of Object.values(toolCalls)) {\n controller.enqueue({ type: 'tool-input-end', id: tc.callId });\n controller.enqueue({\n type: 'tool-call',\n toolCallId: tc.callId,\n toolName: tc.name,\n input: tc.arguments || '{}',\n });\n }\n\n controller.enqueue({ type: 'finish', finishReason, usage });\n controller.close();\n } catch (error) {\n // Check for context overflow FIRST - these should NOT trigger token refresh\n if (self.isContextOverflowError(error)) {\n const apiError = error as InstanceType;\n controller.enqueue({\n type: 'error',\n error: new GitLabError({\n message: `Context overflow: ${apiError.message}. Please start a new session or use /compact to reduce context.`,\n statusCode: 400,\n cause: error,\n }),\n });\n controller.close();\n return;\n }\n\n if (!isRetry && self.isTokenError(error)) {\n self.directAccessClient.invalidateToken();\n controller.enqueue({\n type: 'error',\n error: new GitLabError({ message: 'TOKEN_REFRESH_NEEDED', cause: error }),\n });\n controller.close();\n return;\n }\n\n if (error instanceof OpenAI.APIError) {\n controller.enqueue({\n type: 'error',\n error: new GitLabError({\n message: `OpenAI API error: ${error.message}`,\n statusCode: error.status,\n cause: error,\n }),\n });\n } else {\n controller.enqueue({ type: 'error', error });\n }\n controller.close();\n }\n },\n });\n\n return { stream, request: { body: requestBody } };\n }\n}\n","export type ModelProvider = 'anthropic' | 'openai' | 'workflow';\n\nexport type OpenAIApiType = 'chat' | 'responses';\n\nexport interface ModelMapping {\n provider: ModelProvider;\n model: string;\n /** For OpenAI models, which API to use: 'chat' for /v1/chat/completions, 'responses' for /v1/responses */\n openaiApiType?: OpenAIApiType;\n}\n\nexport const MODEL_MAPPINGS: Record = {\n // Anthropic models\n 'duo-chat-opus-4-6': { provider: 'anthropic', model: 'claude-opus-4-6' },\n 'duo-chat-sonnet-4-6': { provider: 'anthropic', model: 'claude-sonnet-4-6' },\n 'duo-chat-opus-4-5': { provider: 'anthropic', model: 'claude-opus-4-5-20251101' },\n 'duo-chat-sonnet-4-5': { provider: 'anthropic', model: 'claude-sonnet-4-5-20250929' },\n 'duo-chat-haiku-4-5': { provider: 'anthropic', model: 'claude-haiku-4-5-20251001' },\n\n // OpenAI models - Chat Completions API\n 'duo-chat-gpt-5-1': { provider: 'openai', model: 'gpt-5.1-2025-11-13', openaiApiType: 'chat' },\n 'duo-chat-gpt-5-2': { provider: 'openai', model: 'gpt-5.2-2025-12-11', openaiApiType: 'chat' },\n 'duo-chat-gpt-5-mini': {\n provider: 'openai',\n model: 'gpt-5-mini-2025-08-07',\n openaiApiType: 'chat',\n },\n\n // OpenAI models - Responses API (Codex models)\n 'duo-chat-gpt-5-codex': { provider: 'openai', model: 'gpt-5-codex', openaiApiType: 'responses' },\n 'duo-chat-gpt-5-2-codex': {\n provider: 'openai',\n model: 'gpt-5.2-codex',\n openaiApiType: 'responses',\n },\n 'duo-chat-gpt-5-3-codex': {\n provider: 'openai',\n model: 'gpt-5.3-codex',\n openaiApiType: 'responses',\n },\n\n // Duo Agent Platform model (server-side agentic via DWS WebSocket).\n // This is the single user-facing model ID. The actual underlying model ref\n // is resolved dynamically at runtime via GitLabModelDiscovery.\n 'duo-workflow': { provider: 'workflow', model: 'default' },\n\n // Internal model refs — kept for backwards compatibility and direct use.\n // Not intended as user-facing model IDs.\n 'duo-workflow-default': { provider: 'workflow', model: 'default' },\n 'duo-workflow-sonnet-4-5': {\n provider: 'workflow',\n model: 'anthropic/claude-sonnet-4-5-20250929',\n },\n 'duo-workflow-sonnet-4-6': { provider: 'workflow', model: 'claude_sonnet_4_6' },\n 'duo-workflow-opus-4-5': {\n provider: 'workflow',\n model: 'anthropic/claude-opus-4-5-20251101',\n },\n 'duo-workflow-haiku-4-5': { provider: 'workflow', model: 'claude_haiku_4_5_20251001' },\n 'duo-workflow-opus-4-6': { provider: 'workflow', model: 'claude_opus_4_6_20260205' },\n};\n\nexport function getModelMapping(modelId: string): ModelMapping | undefined {\n return MODEL_MAPPINGS[modelId];\n}\n\nexport function getProviderForModelId(modelId: string): ModelProvider | undefined {\n return MODEL_MAPPINGS[modelId]?.provider;\n}\n\nexport function getValidModelsForProvider(provider: ModelProvider): string[] {\n return Object.values(MODEL_MAPPINGS)\n .filter((m) => m.provider === provider)\n .map((m) => m.model);\n}\n\nexport function getAnthropicModelForModelId(modelId: string): string | undefined {\n const mapping = MODEL_MAPPINGS[modelId];\n return mapping?.provider === 'anthropic' ? mapping.model : undefined;\n}\n\nexport function getOpenAIModelForModelId(modelId: string): string | undefined {\n const mapping = MODEL_MAPPINGS[modelId];\n return mapping?.provider === 'openai' ? mapping.model : undefined;\n}\n\nexport function getOpenAIApiType(modelId: string): OpenAIApiType {\n const mapping = MODEL_MAPPINGS[modelId];\n return mapping?.openaiApiType ?? 'chat';\n}\n\nexport function isResponsesApiModel(modelId: string): boolean {\n return getOpenAIApiType(modelId) === 'responses';\n}\n\nexport function isWorkflowModel(modelId: string): boolean {\n return MODEL_MAPPINGS[modelId]?.provider === 'workflow';\n}\n\nexport function getWorkflowModelRef(modelId: string): string | undefined {\n const mapping = MODEL_MAPPINGS[modelId];\n return mapping?.provider === 'workflow' ? mapping.model : undefined;\n}\n\nexport const MODEL_ID_TO_ANTHROPIC_MODEL: Record = Object.fromEntries(\n Object.entries(MODEL_MAPPINGS)\n .filter(([, v]) => v.provider === 'anthropic')\n .map(([k, v]) => [k, v.model])\n);\n","/**\n * WebSocket client for the GitLab Duo Agent Platform (DWS).\n *\n * Handles:\n * - WebSocket connection to `wss://{instance}/api/v4/ai/duo_workflows/ws`\n * - Sending ClientEvent messages (startRequest, actionResponse, stopWorkflow)\n * - Receiving WorkflowAction messages (newCheckpoint, runMcpTool, built-in tools)\n * - Dual heartbeat: ws.ping(45s) + JSON heartbeat(60s) — matching gitlab-lsp\n * - No reconnection on drop (matches gitlab-lsp behavior)\n */\n\nimport WebSocket from 'isomorphic-ws';\nimport { VERSION } from './version';\nimport type {\n ClientEvent,\n WorkflowAction,\n StartRequest,\n ActionResponsePayload,\n WorkflowClientEvent,\n} from './gitlab-workflow-types';\nimport {\n WS_KEEPALIVE_PING_INTERVAL_MS,\n WS_HEARTBEAT_INTERVAL_MS,\n STOP_REASON_USER,\n} from './gitlab-workflow-types';\n\nexport interface WorkflowWebSocketOptions {\n /** GitLab instance URL */\n instanceUrl: string;\n /** Model reference for DWS (e.g. 'anthropic/claude-sonnet-4-5-20250929' or 'default') */\n modelRef: string;\n /** Auth headers — must include Authorization */\n headers: Record;\n /** Optional correlation ID */\n requestId?: string;\n /** Optional project context */\n projectId?: string;\n namespaceId?: string;\n rootNamespaceId?: string;\n}\n\ntype EventCallback = (event: WorkflowClientEvent) => void;\n\nexport class GitLabWorkflowClient {\n private socket: WebSocket | null = null;\n private keepaliveInterval: ReturnType | null = null;\n private heartbeatInterval: ReturnType | null = null;\n private eventCallback: EventCallback | null = null;\n private closed = false;\n private lastSendTime = 0;\n\n /**\n * Connect to the DWS WebSocket and start listening for events.\n *\n * @param options - Connection parameters\n * @param onEvent - Callback invoked for each WorkflowClientEvent\n * @returns Promise that resolves when the connection is open\n */\n connect(options: WorkflowWebSocketOptions, onEvent: EventCallback): Promise {\n this.validateOptions(options);\n this.eventCallback = onEvent;\n this.closed = false;\n this.cleanedUp = false;\n\n return new Promise((resolve, reject) => {\n const wsUrl = this.buildWebSocketUrl(options);\n const wsHeaders = this.buildWebSocketHeaders(options);\n\n this.socket = new WebSocket(wsUrl, { headers: wsHeaders });\n let resolved = false;\n\n this.socket.onopen = () => {\n resolved = true;\n this.startKeepalive();\n this.startHeartbeat();\n resolve();\n };\n\n this.socket.onmessage = (event: WebSocket.MessageEvent) => {\n try {\n const data = typeof event.data === 'string' ? event.data : event.data.toString();\n const action = JSON.parse(data) as WorkflowAction;\n\n // Basic validation of message structure\n if (!action || typeof action !== 'object') {\n throw new Error('Invalid message structure: expected object');\n }\n\n this.handleAction(action);\n } catch (error) {\n this.emit({\n type: 'failed',\n error: error instanceof Error ? error : new Error(String(error)),\n });\n }\n };\n\n this.socket.onerror = (event: WebSocket.ErrorEvent) => {\n const error = new Error(`WebSocket error: ${event.message || 'unknown'}`);\n if (!resolved) {\n reject(error);\n } else {\n this.emit({ type: 'failed', error });\n }\n };\n\n this.socket.onclose = (event: WebSocket.CloseEvent) => {\n this.cleanup();\n if (!resolved) {\n reject(\n new Error(\n `WebSocket closed before open: code=${event.code} reason=${event.reason || ''}`\n )\n );\n return;\n }\n if (!this.closed) {\n this.emit({\n type: 'closed',\n code: event.code,\n reason: event.reason || '',\n });\n }\n };\n });\n }\n\n /**\n * Send a startRequest to begin the workflow.\n */\n sendStartRequest(request: StartRequest): void {\n this.send({ startRequest: request });\n }\n\n /**\n * Send an actionResponse (tool result) back to DWS.\n */\n sendActionResponse(requestID: string, response: string, error?: string | null): void {\n this.sendHeartbeatIfNeeded();\n const payload: ActionResponsePayload = {\n requestID,\n plainTextResponse: {\n response,\n error: error ?? null,\n },\n };\n this.send({ actionResponse: payload });\n }\n\n /**\n * Stop the workflow gracefully.\n */\n stop(): void {\n this.send({ stopWorkflow: { reason: STOP_REASON_USER } });\n this.closed = true;\n }\n\n /**\n * Close the WebSocket connection.\n */\n close(): void {\n // Set closed flag first to prevent race conditions\n if (this.closed) return;\n this.closed = true;\n\n this.cleanup();\n const sock = this.socket;\n this.socket = null;\n if (sock) {\n if (sock.readyState === WebSocket.OPEN || sock.readyState === WebSocket.CONNECTING) {\n sock.close(1000, 'Client closing');\n }\n }\n }\n\n /**\n * Check if the WebSocket is currently connected.\n */\n get isConnected(): boolean {\n return this.socket?.readyState === WebSocket.OPEN;\n }\n\n // ---------------------------------------------------------------------------\n // Private\n // ---------------------------------------------------------------------------\n\n private validateOptions(options: WorkflowWebSocketOptions): void {\n if (!options.instanceUrl || typeof options.instanceUrl !== 'string') {\n throw new Error('instanceUrl is required');\n }\n const parsed = new URL(options.instanceUrl);\n if (parsed.protocol !== 'https:' && parsed.protocol !== 'http:') {\n throw new Error(`Invalid instanceUrl protocol: ${parsed.protocol}`);\n }\n if (parsed.username || parsed.password) {\n throw new Error(\n 'instanceUrl must not contain authentication credentials (username/password)'\n );\n }\n if (!options.headers || typeof options.headers !== 'object') {\n throw new Error('headers are required');\n }\n if (options.modelRef && typeof options.modelRef !== 'string') {\n throw new Error('modelRef must be a string');\n }\n }\n\n private buildWebSocketUrl(options: WorkflowWebSocketOptions): string {\n // Match gitlab-lsp URL construction exactly:\n // - NO workflow_id in URL (it goes in startRequest.workflowID instead)\n // - Only user_selected_model_identifier as query param\n const baseUrl = new URL(options.instanceUrl.replace(/\\/?$/, '/'));\n const url = new URL('./api/v4/ai/duo_workflows/ws', baseUrl);\n url.protocol = url.protocol === 'https:' ? 'wss:' : 'ws:';\n if (options.modelRef && options.modelRef !== 'default') {\n // URL.searchParams.set() automatically encodes the value\n url.searchParams.set('user_selected_model_identifier', options.modelRef);\n }\n return url.toString();\n }\n\n private buildWebSocketHeaders(options: WorkflowWebSocketOptions): Record {\n // Normalize incoming headers to lowercase keys to avoid duplicates\n const headers: Record = {};\n for (const [key, value] of Object.entries(options.headers)) {\n headers[key.toLowerCase()] = value;\n }\n\n // Remove Content-Type — WebSocket upgrade (RFC 6455 §4.1) uses no body;\n // sending Content-Type can confuse proxies and fails some server checks.\n delete headers['content-type'];\n\n headers['x-gitlab-client-type'] = 'node-websocket';\n\n // Origin header — required by gitlab-lsp, validates WebSocket security\n // The origin is derived from the validated instanceUrl (already checked in validateOptions)\n const parsedUrl = new URL(options.instanceUrl);\n const origin = parsedUrl.origin;\n headers['origin'] = origin;\n\n if (options.requestId) {\n headers['x-request-id'] = options.requestId;\n }\n if (options.projectId) {\n headers['x-gitlab-project-id'] = options.projectId;\n }\n if (options.namespaceId) {\n headers['x-gitlab-namespace-id'] = options.namespaceId;\n }\n if (options.rootNamespaceId) {\n headers['x-gitlab-root-namespace-id'] = options.rootNamespaceId;\n }\n\n // User-Agent — set only if not already provided\n if (!headers['user-agent']) {\n headers['user-agent'] = `gitlab-ai-provider/${VERSION}`;\n }\n\n return headers;\n }\n\n private handleAction(action: WorkflowAction): void {\n // Checkpoint (text/status from LLM)\n if (action.newCheckpoint) {\n const checkpoint = action.newCheckpoint;\n\n this.emit({ type: 'checkpoint', data: checkpoint });\n\n if (checkpoint.status === 'FINISHED' || checkpoint.status === 'COMPLETED') {\n this.emit({ type: 'completed' });\n } else if (checkpoint.status === 'FAILED') {\n this.emit({\n type: 'failed',\n error: new Error(checkpoint.content || 'Workflow failed'),\n });\n } else if (checkpoint.status === 'STOPPED' || checkpoint.status === 'CANCELLED') {\n this.emit({ type: 'completed' });\n }\n return;\n }\n\n // MCP tool invocation\n if (action.runMCPTool && action.requestID) {\n this.emit({\n type: 'tool-request',\n requestID: action.requestID,\n data: action.runMCPTool,\n });\n return;\n }\n\n // Built-in tool invocations — field names match DWS protobuf wire format\n const builtinTools: Array<[string, unknown]> = [\n ['runReadFile', action.runReadFile],\n ['runReadFiles', action.runReadFiles],\n ['runWriteFile', action.runWriteFile],\n ['runShellCommand', action.runShellCommand],\n ['runEditFile', action.runEditFile],\n ['listDirectory', action.listDirectory],\n ['findFiles', action.findFiles],\n ['grep', action.grep],\n ['mkdir', action.mkdir],\n ['runCommand', action.runCommand],\n ['runGitCommand', action.runGitCommand],\n ['runHTTPRequest', action.runHTTPRequest],\n ];\n\n for (const [toolName, data] of builtinTools) {\n if (data && action.requestID) {\n this.emit({\n type: 'builtin-tool-request',\n requestID: action.requestID,\n toolName,\n data: data as Record,\n });\n return;\n }\n }\n }\n\n private send(event: ClientEvent): void {\n if (this.socket?.readyState === WebSocket.OPEN) {\n const json = JSON.stringify(event);\n this.socket.send(json);\n this.lastSendTime = Date.now();\n }\n }\n\n private sendHeartbeatIfNeeded(): void {\n const elapsed = Date.now() - this.lastSendTime;\n if (elapsed >= WS_HEARTBEAT_INTERVAL_MS / 2) {\n this.send({ heartbeat: { timestamp: Date.now() } });\n }\n }\n\n private emit(event: WorkflowClientEvent): void {\n this.eventCallback?.(event);\n }\n\n /**\n * Start ws.ping() keepalive (45s interval).\n * Keeps TCP connection alive through proxies/load balancers.\n */\n private startKeepalive(): void {\n this.keepaliveInterval = setInterval(() => {\n if (this.socket?.readyState === WebSocket.OPEN) {\n // ws-specific ping (not available in browser WebSocket, but\n // isomorphic-ws in Node.js delegates to the ws library)\n try {\n (this.socket as unknown as { ping: () => void }).ping();\n } catch {\n // Browser WebSocket doesn't have ping — silently skip\n }\n }\n }, WS_KEEPALIVE_PING_INTERVAL_MS);\n }\n\n /**\n * Start application-level heartbeat (60s interval).\n * Prevents DWS from timing out the workflow.\n */\n private startHeartbeat(): void {\n this.heartbeatInterval = setInterval(() => {\n this.send({ heartbeat: { timestamp: Date.now() } });\n }, WS_HEARTBEAT_INTERVAL_MS);\n }\n\n private cleanedUp = false;\n\n /**\n * Clean up intervals. Idempotent — safe to call multiple times.\n */\n private cleanup(): void {\n if (this.cleanedUp) return;\n this.cleanedUp = true;\n\n if (this.keepaliveInterval) {\n clearInterval(this.keepaliveInterval);\n this.keepaliveInterval = null;\n }\n if (this.heartbeatInterval) {\n clearInterval(this.heartbeatInterval);\n this.heartbeatInterval = null;\n }\n }\n}\n","// Version string of this package injected at build time.\ndeclare const __PACKAGE_VERSION__: string | undefined;\nexport const VERSION: string =\n typeof __PACKAGE_VERSION__ !== 'undefined' ? __PACKAGE_VERSION__ : '0.0.0-dev';\n","/**\n * Types for the GitLab Duo Agent Platform (DWS) protocol.\n *\n * DWS uses a WebSocket-based bidirectional protocol where:\n * - Client sends `ClientEvent` messages (startRequest, actionResponse, stopWorkflow, heartbeat)\n * - Server sends `WorkflowAction` messages (newCheckpoint, runMcpTool, built-in tools)\n *\n * Message format is JSON-serialized protobuf with camelCase field names.\n */\n\n// ---------------------------------------------------------------------------\n// Token / workflow creation responses\n// ---------------------------------------------------------------------------\n\nexport interface GenerateTokenResponse {\n gitlab_rails: {\n base_url: string;\n token: string;\n token_expires_at: string;\n };\n duo_workflow_service: {\n base_url: string;\n token: string;\n secure: boolean;\n token_expires_at: number;\n headers: Record;\n };\n duo_workflow_executor: {\n executor_binary_url: string;\n version: string;\n };\n}\n\nexport interface CreateWorkflowResponse {\n id: string;\n}\n\n// ---------------------------------------------------------------------------\n// MCP tool definitions (sent in startRequest)\n// ---------------------------------------------------------------------------\n\nexport interface McpToolDefinition {\n name: string;\n description: string;\n inputSchema: string;\n}\n\n// ---------------------------------------------------------------------------\n// Client → Server messages (ClientEvent)\n// ---------------------------------------------------------------------------\n\nexport interface AdditionalContext {\n category: string;\n id?: string;\n content?: string;\n metadata?: string;\n}\n\nexport interface StartRequest {\n workflowID: string;\n clientVersion: string;\n workflowDefinition: string;\n goal: string;\n workflowMetadata?: string;\n additional_context?: AdditionalContext[];\n clientCapabilities?: string[];\n mcpTools?: McpToolDefinition[];\n preapproved_tools?: string[];\n flowConfig?: unknown;\n flowConfigSchemaVersion?: string;\n}\n\nexport interface ActionResponsePayload {\n requestID: string;\n plainTextResponse: {\n response: string;\n error: string | null;\n };\n}\n\nexport interface StopWorkflow {\n reason: string;\n}\n\nexport interface Heartbeat {\n timestamp: number;\n}\n\n/**\n * Client → Server event union.\n * Exactly one of the fields should be set per message.\n */\nexport type ClientEvent =\n | { startRequest: StartRequest }\n | { actionResponse: ActionResponsePayload }\n | { stopWorkflow: StopWorkflow }\n | { heartbeat: Heartbeat };\n\n// ---------------------------------------------------------------------------\n// Server → Client messages (WorkflowAction)\n// ---------------------------------------------------------------------------\n\nexport type WorkflowStatus =\n | 'CREATED'\n | 'RUNNING'\n | 'FINISHED'\n | 'COMPLETED'\n | 'FAILED'\n | 'STOPPED'\n | 'CANCELLED'\n | 'PAUSED'\n | 'INPUT_REQUIRED'\n | 'PLAN_APPROVAL_REQUIRED'\n | 'TOOL_CALL_APPROVAL_REQUIRED'\n | 'UNKNOWN';\n\nexport interface NewCheckpoint {\n status: WorkflowStatus;\n goal?: string;\n /** Raw checkpoint JSON string from DWS (contains channel_values.ui_chat_log) */\n checkpoint?: string;\n /** Legacy content field (may be empty — text is in checkpoint.ui_chat_log) */\n content?: string;\n}\n\n// ---------------------------------------------------------------------------\n// Checkpoint parsing types (based on gitlab-lsp ui_chat_log.ts)\n// ---------------------------------------------------------------------------\n\nexport interface UiChatLogEntry {\n message_type: 'user' | 'agent' | 'tool' | 'request';\n message_sub_type: string | null;\n content: string;\n message_id?: string;\n timestamp: string;\n status: string | null;\n correlation_id: string | null;\n tool_info: UiChatLogToolInfo | null;\n additional_context: unknown;\n}\n\nexport interface UiChatLogToolInfo {\n name: string;\n args: Record;\n tool_response?: UiChatLogToolResponse | string;\n}\n\nexport interface UiChatLogToolResponse {\n content: string;\n type: string;\n name: string;\n id: string | null;\n tool_call_id: string;\n status: string;\n}\n\nexport interface CheckpointData {\n channel_values: {\n ui_chat_log?: UiChatLogEntry[];\n plan?: { steps: unknown[] };\n status?: string;\n [key: string]: unknown;\n };\n}\n\nexport interface RunMcpTool {\n name: string;\n args: string;\n}\n\nexport interface ReadFileAction {\n filepath: string;\n}\n\nexport interface ReadFilesAction {\n filepaths: string[];\n}\n\nexport interface WriteFileAction {\n filepath: string;\n contents: string;\n}\n\nexport interface ShellCommandAction {\n command: string;\n}\n\nexport interface EditFileAction {\n filepath: string;\n oldString: string;\n newString: string;\n}\n\nexport interface ListDirectoryAction {\n directory: string;\n}\n\nexport interface FindFilesAction {\n name_pattern: string;\n}\n\nexport interface GrepAction {\n pattern: string;\n search_directory?: string;\n case_insensitive?: boolean;\n}\n\nexport interface MkdirAction {\n directory_path: string;\n}\n\nexport interface RunCommandAction {\n program: string;\n flags?: string[];\n arguments?: string[];\n}\n\nexport interface RunGitCommandAction {\n command: string;\n arguments?: string[];\n repository_url?: string;\n}\n\nexport interface GitLabApiRequestAction {\n method: string;\n path: string;\n body?: string;\n}\n\n/**\n * Server → Client action union.\n * Field names match the DWS protobuf camelCase wire format exactly.\n * Each message has an optional `requestID` (required for tool invocations\n * that need an `actionResponse` back).\n */\nexport interface WorkflowAction {\n requestID?: string;\n\n newCheckpoint?: NewCheckpoint;\n\n runMCPTool?: RunMcpTool;\n\n runReadFile?: ReadFileAction;\n runReadFiles?: ReadFilesAction;\n runWriteFile?: WriteFileAction;\n runShellCommand?: ShellCommandAction;\n runEditFile?: EditFileAction;\n listDirectory?: ListDirectoryAction;\n findFiles?: FindFilesAction;\n grep?: GrepAction;\n mkdir?: MkdirAction;\n runCommand?: RunCommandAction;\n runGitCommand?: RunGitCommandAction;\n runHTTPRequest?: GitLabApiRequestAction;\n}\n\n// ---------------------------------------------------------------------------\n// Provider options\n// ---------------------------------------------------------------------------\n\n/**\n * Options for creating a workflow chat model via `provider.workflowChat()`.\n */\nexport interface GitLabWorkflowOptions {\n /**\n * Workflow definition type.\n * @default 'chat'\n */\n workflowDefinition?: string;\n\n /**\n * Root namespace ID for the GitLab group/project.\n * Used for token scoping and model discovery.\n */\n rootNamespaceId?: string;\n\n /**\n * GitLab project ID (numeric or path).\n * Sent as `x-gitlab-project-id` header on WebSocket.\n */\n projectId?: string;\n\n /**\n * GitLab namespace ID.\n * Sent as `x-gitlab-namespace-id` header on WebSocket.\n */\n namespaceId?: string;\n\n /**\n * MCP tool definitions to expose to the workflow.\n * These are sent in `startRequest.mcpTools`.\n */\n mcpTools?: McpToolDefinition[];\n\n /**\n * Client capabilities to advertise.\n * @default ['shell_command']\n */\n clientCapabilities?: string[];\n\n /**\n * Tool names that are pre-approved for execution without user confirmation.\n * Sent in `startRequest.preapproved_tools`.\n */\n preapprovedTools?: string[];\n\n /**\n * Additional context items to send with the first request.\n * Used for conversation history continuity.\n */\n additionalContext?: AdditionalContext[];\n\n /**\n * Feature flags to pass to the GitLab API.\n */\n featureFlags?: Record;\n\n /**\n * Working directory for auto-detecting GitLab project from git remote.\n * Used to resolve `projectId` when not explicitly set.\n * Defaults to `process.cwd()`.\n */\n workingDirectory?: string;\n\n /**\n * Flow configuration (parsed YAML object) to send to DWS.\n * Controls agent behavior, intermediate text generation, etc.\n * Sent as `startRequest.flowConfig`.\n */\n flowConfig?: unknown;\n\n /**\n * Schema version for the flow configuration.\n * Sent as `startRequest.flowConfigSchemaVersion`.\n */\n flowConfigSchemaVersion?: string;\n\n /**\n * Callback invoked when multiple workflow models are available for the\n * workspace and model switching is enabled by the instance admin.\n *\n * The provider calls this before starting the workflow so the host can\n * present a model picker to the user. Return the `ref` of the chosen\n * model, or `null`/`undefined` to fall back to the workspace default.\n *\n * If the returned ref is not in the list of selectable models it is\n * ignored and the workspace default is used instead.\n *\n * Not called when the admin has pinned a model — in that case the\n * pinned model is always used regardless of user preference.\n *\n * @param models - List of models the user can select from\n * @returns The selected model ref, or null/undefined for default\n */\n onSelectModel?: (\n models: import('./gitlab-model-discovery').AiModel[]\n ) => Promise;\n}\n\n// ---------------------------------------------------------------------------\n// WebSocket client configuration\n// ---------------------------------------------------------------------------\n\nexport interface GitLabWorkflowClientConfig {\n /** GitLab instance URL (e.g., 'https://gitlab.com') */\n instanceUrl: string;\n\n /** Function to get current auth headers */\n getHeaders: () => Record;\n\n /**\n * Optional callback to refresh the API key when a 401 error occurs.\n */\n refreshApiKey?: () => Promise;\n\n /** Custom fetch implementation */\n fetch?: typeof fetch;\n\n /** Feature flags for the token request */\n featureFlags?: Record;\n\n /**\n * AI Gateway URL.\n * Can also be set via GITLAB_AI_GATEWAY_URL environment variable.\n * @default 'https://cloud.gitlab.com'\n */\n aiGatewayUrl?: string;\n}\n\n// ---------------------------------------------------------------------------\n// WebSocket event types (emitted by GitLabWorkflowClient)\n// ---------------------------------------------------------------------------\n\nexport type WorkflowClientEvent =\n | { type: 'checkpoint'; data: NewCheckpoint }\n | { type: 'tool-request'; requestID: string; data: RunMcpTool }\n | {\n type: 'builtin-tool-request';\n requestID: string;\n toolName: string;\n data: Record;\n }\n | { type: 'completed' }\n | { type: 'failed'; error: Error }\n | { type: 'closed'; code: number; reason: string };\n\n// ---------------------------------------------------------------------------\n// Constants\n// ---------------------------------------------------------------------------\n\n/**\n * Workflow type enum — matches gitlab-lsp WorkflowType.\n *\n * - CHAT: Shared token across sessions, tokens NOT revoked on completion\n * - SOFTWARE_DEVELOPMENT: Per-workflow token, tokens revoked on completion\n */\nexport enum WorkflowType {\n CHAT = 'chat',\n SOFTWARE_DEVELOPMENT = 'software_development',\n}\n\n/** WebSocket ping interval (TCP keepalive) — 45s matching gitlab-lsp */\nexport const WS_KEEPALIVE_PING_INTERVAL_MS = 45_000;\n\n/** Application heartbeat interval — 60s matching gitlab-lsp */\nexport const WS_HEARTBEAT_INTERVAL_MS = 60_000;\n\n/** Default workflow definition — uses CHAT for agentic chat (matches gitlab-lsp) */\nexport const DEFAULT_WORKFLOW_DEFINITION = WorkflowType.CHAT;\n\n/** Default client capabilities */\nexport const DEFAULT_CLIENT_CAPABILITIES = ['shell_command'];\n\n/** Client version sent in startRequest */\nexport const CLIENT_VERSION = '1.0';\n\n/** Stop reason for user-initiated stop */\nexport const STOP_REASON_USER = 'USER_ACTION_TRIGGERED_STOP';\n\n/**\n * Agent privileges for workflow creation.\n * Matches gitlab-lsp AGENT_PRIVILEGES enum.\n */\nexport const AGENT_PRIVILEGES = {\n READ_WRITE_FILES: 1,\n READ_ONLY_GITLAB: 2,\n READ_WRITE_GITLAB: 3,\n RUN_COMMANDS: 4,\n USE_GIT: 5,\n RUN_MCP_TOOLS: 6,\n} as const;\n\n/** Default agent privileges — matches gitlab-lsp defaults */\nexport const DEFAULT_AGENT_PRIVILEGES = [\n AGENT_PRIVILEGES.READ_WRITE_FILES,\n AGENT_PRIVILEGES.READ_ONLY_GITLAB,\n AGENT_PRIVILEGES.READ_WRITE_GITLAB,\n AGENT_PRIVILEGES.RUN_COMMANDS,\n AGENT_PRIVILEGES.RUN_MCP_TOOLS,\n AGENT_PRIVILEGES.USE_GIT,\n];\n\n/** Workflow execution environment */\nexport const WORKFLOW_ENVIRONMENT = 'ide' as const;\n","/**\n * DWS built-in tool mapping and shared security utilities.\n *\n * Extracted into a standalone module so both production code\n * (gitlab-workflow-language-model.ts) and tests can reference the\n * same implementation — preventing drift between a test shim and\n * the real logic.\n *\n * @internal — not part of the public API surface.\n */\n\n/**\n * Reject strings containing shell metacharacters.\n * Used as a defence-in-depth check before shellEscape.\n */\nexport function validateNoShellMetachars(value: string, fieldName: string): void {\n const dangerousChars = /[;&|`$()<>]/;\n if (dangerousChars.test(value)) {\n throw new Error(\n `Invalid ${fieldName}: contains shell metacharacters. Use structured arguments instead.`\n );\n }\n}\n\n/**\n * Wrap a value in single quotes for safe use as a single shell argument.\n * Embedded single quotes are escaped with the '\\'' idiom.\n */\nexport function shellEscape(arg: string): string {\n return \"'\" + String(arg).replace(/'/g, \"'\\\\''\") + \"'\";\n}\n\nconst ALLOWED_URL_SCHEMES = ['http:', 'https:'];\n\n/**\n * Redact credential-like patterns from error messages before they are\n * forwarded to the stream or surfaced in UI.\n *\n * Patterns covered:\n * - Bearer / token header values\n * - GitLab PAT / CI tokens (glpat-*, glcbt-*, etc.)\n * - URL query parameters: private_token, access_token, token\n * - Basic auth in URLs: http://user:PASSWORD@host\n * - Additional GitLab token prefixes (gldt, gloas, glrt, glsoat, glffct, glsapat)\n */\nexport function sanitizeErrorMessage(message: string): string {\n if (!message) return '';\n\n return message\n .replace(/\\bBearer\\s+[A-Za-z0-9\\-_.~+/]+=*/gi, 'Bearer [REDACTED]')\n .replace(/\\bgl(?:pat|oat|cbt|dt|oas|rt|soat|ffct|sapat)-[A-Za-z0-9_-]+/g, '[REDACTED]')\n .replace(/([?&](?:private_token|access_token|token)=)[^&\\s\"']*/gi, '$1[REDACTED]')\n .replace(/:\\/\\/([^:@/\\s]+):([^@/\\s]+)@/g, '://$1:[REDACTED]@');\n}\n\n/**\n * Map DWS built-in tool names and arguments to the corresponding\n * consumer tool names and argument formats.\n *\n * DWS uses protobuf-style tool names (runReadFile, runShellCommand, etc.)\n * while consumers like OpenCode use different names (read, bash, write, etc.)\n *\n * IMPORTANT: The returned `args` are structured objects passed to the host's\n * `toolExecutor` callback — they are NOT executed as raw shell commands by\n * this library. The host (e.g., OpenCode) is responsible for safely executing\n * the mapped tool through its own permission-gated tool system.\n */\nexport function mapBuiltinTool(\n dwsToolName: string,\n data: Record\n): { toolName: string; args: Record } {\n switch (dwsToolName) {\n case 'runReadFile':\n return { toolName: 'read', args: { filePath: data.filepath } };\n case 'runReadFiles': {\n const paths = (data.filepaths as string[]) ?? [];\n if (paths.length <= 1) {\n return { toolName: 'read', args: { filePath: paths[0] ?? '' } };\n }\n return {\n toolName: 'read',\n args: { filePaths: paths },\n };\n }\n case 'runWriteFile':\n return {\n toolName: 'write',\n args: { filePath: data.filepath, content: data.contents },\n };\n case 'runEditFile':\n return {\n toolName: 'edit',\n args: {\n filePath: data.filepath,\n oldString: data.oldString ?? data.old_string,\n newString: data.newString ?? data.new_string,\n },\n };\n case 'runShellCommand': {\n const command = data.command as string;\n if (!command || typeof command !== 'string') {\n throw new Error('runShellCommand: command is required and must be a string');\n }\n if (command.length > 10000) {\n throw new Error('runShellCommand: command exceeds maximum length of 10000 characters');\n }\n return {\n toolName: 'bash',\n args: { command, description: 'DWS shell command' },\n };\n }\n case 'runCommand': {\n const program = data.program as string;\n if (!program || typeof program !== 'string') {\n throw new Error('runCommand: program is required and must be a string');\n }\n validateNoShellMetachars(program, 'program');\n\n const flags = (data.flags as string[]) ?? [];\n const cmdArgs = (data.arguments as string[]) ?? [];\n\n for (const flag of flags) {\n if (typeof flag === 'string') {\n validateNoShellMetachars(flag, 'flag');\n }\n }\n for (const arg of cmdArgs) {\n if (typeof arg === 'string') {\n validateNoShellMetachars(arg, 'argument');\n }\n }\n\n return {\n toolName: 'bash',\n args: {\n command: [program, ...flags, ...cmdArgs].map((a) => shellEscape(String(a))).join(' '),\n description: `DWS run: ${program}`,\n },\n };\n }\n case 'runGitCommand': {\n const gitCmd = data.command as string;\n if (!gitCmd || typeof gitCmd !== 'string') {\n throw new Error('runGitCommand: command is required and must be a string');\n }\n validateNoShellMetachars(gitCmd, 'git command');\n\n const gitArgs = (data.arguments as string[]) ?? [];\n for (const arg of gitArgs) {\n if (typeof arg === 'string') {\n validateNoShellMetachars(arg, 'git argument');\n }\n }\n return {\n toolName: 'bash',\n args: {\n command: ['git', gitCmd, ...gitArgs].map((a) => shellEscape(String(a))).join(' '),\n description: `DWS git: ${gitCmd}`,\n },\n };\n }\n case 'listDirectory':\n return { toolName: 'read', args: { filePath: data.directory ?? '.' } };\n case 'findFiles':\n return { toolName: 'glob', args: { pattern: data.name_pattern ?? data.namePattern } };\n case 'grep':\n return {\n toolName: 'grep',\n args: {\n pattern: data.pattern,\n path: data.search_directory ?? data.searchDirectory,\n },\n };\n case 'mkdir': {\n const dirPath = String(data.directory_path ?? data.directoryPath ?? '');\n if (!dirPath) {\n throw new Error('mkdir: directory_path is required');\n }\n if (dirPath.includes('\\0')) {\n throw new Error('mkdir: directory_path contains null bytes');\n }\n return {\n toolName: 'bash',\n args: {\n command: `mkdir -p ${shellEscape(dirPath)}`,\n description: 'DWS mkdir',\n },\n };\n }\n case 'runHTTPRequest': {\n const methodRaw = String(data.method ?? 'GET').toUpperCase();\n const allowedMethods = ['GET', 'POST', 'PUT', 'PATCH', 'DELETE', 'HEAD', 'OPTIONS'];\n if (!allowedMethods.includes(methodRaw)) {\n throw new Error(`runHTTPRequest: invalid HTTP method '${methodRaw}'`);\n }\n\n const urlPath = String(data.path ?? '');\n if (!urlPath) {\n throw new Error('runHTTPRequest: path is required');\n }\n\n try {\n const parsedUrl = new URL(urlPath);\n if (!ALLOWED_URL_SCHEMES.includes(parsedUrl.protocol)) {\n throw new Error(\n `runHTTPRequest: only http:// and https:// schemes are allowed, got '${parsedUrl.protocol}'`\n );\n }\n } catch (e) {\n if (e instanceof Error && e.message.startsWith('runHTTPRequest:')) throw e;\n // Relative path or non-URL string — allow through (curl handles these)\n }\n\n const method = shellEscape(methodRaw);\n const escapedPath = shellEscape(urlPath);\n const bodyArg = data.body ? ` -d ${shellEscape(String(data.body))}` : '';\n return {\n toolName: 'bash',\n args: {\n command: `curl -s -X ${method} -- ${escapedPath}${bodyArg}`,\n description: `DWS HTTP ${methodRaw}`,\n },\n };\n }\n default:\n return { toolName: dwsToolName, args: data };\n }\n}\n","/**\n * Token management for the GitLab Duo Agent Platform (DWS).\n *\n * Handles two API calls:\n * 1. POST /api/v4/ai/duo_workflows/direct_access → GenerateTokenResponse (workflow token)\n * 2. POST /api/v4/ai/duo_workflows/workflows → CreateWorkflowResponse (workflow ID)\n *\n * Tokens are cached for 25 minutes (they expire after ~30 minutes).\n * On 401, optionally triggers an API key refresh callback and retries once.\n * On 403, throws a clear error explaining GitLab Duo Enterprise requirements.\n */\n\nimport { GitLabError } from './gitlab-error';\nimport { sanitizeErrorMessage } from './gitlab-workflow-builtins';\nimport type {\n GenerateTokenResponse,\n CreateWorkflowResponse,\n GitLabWorkflowClientConfig,\n} from './gitlab-workflow-types';\n\nimport {\n DEFAULT_WORKFLOW_DEFINITION,\n DEFAULT_AGENT_PRIVILEGES,\n WORKFLOW_ENVIRONMENT,\n WorkflowType,\n} from './gitlab-workflow-types';\n\n/** Cache duration: 25 minutes (tokens expire at ~30 minutes) */\nconst TOKEN_CACHE_DURATION_MS = 25 * 60 * 1000;\n\nconst MAX_ERROR_TEXT_LENGTH = 500;\n\nfunction sanitizeErrorText(text: string): string {\n const truncated =\n text.length > MAX_ERROR_TEXT_LENGTH ? text.slice(0, MAX_ERROR_TEXT_LENGTH) + '...' : text;\n return sanitizeErrorMessage(truncated);\n}\n\n/**\n * Shared token cache key for CHAT workflows.\n * CHAT tokens are shared across all sessions (matching gitlab-lsp behavior).\n */\nconst CHAT_SHARED_TOKEN_KEY = '__chat_shared__';\n\ninterface CachedToken {\n token: GenerateTokenResponse;\n expiresAt: number;\n}\n\nexport class GitLabWorkflowTokenClient {\n private readonly config: GitLabWorkflowClientConfig;\n private readonly fetchFn: typeof fetch;\n\n /**\n * Token cache keyed by workflow definition type.\n *\n * - CHAT workflows use a shared key (CHAT_SHARED_TOKEN_KEY) so tokens\n * are reused across ALL chat sessions (matching gitlab-lsp behavior).\n * - SOFTWARE_DEVELOPMENT workflows would use per-workflow-id keys,\n * but since we fetch tokens before creating workflows, we key by type.\n */\n private tokenCache = new Map();\n\n constructor(config: GitLabWorkflowClientConfig) {\n this.config = config;\n this.fetchFn = config.fetch ?? fetch;\n }\n\n /**\n * Resolve the cache key for a given workflow definition.\n * CHAT workflows share a single token per namespace; other types get per-type keys.\n */\n private getCacheKey(workflowDefinition: string, rootNamespaceId?: string): string {\n const base =\n workflowDefinition === WorkflowType.CHAT ? CHAT_SHARED_TOKEN_KEY : workflowDefinition;\n return rootNamespaceId ? `${base}:${rootNamespaceId}` : base;\n }\n\n /**\n * Get a DWS token, using cached value if still valid.\n *\n * Token caching strategy (matches gitlab-lsp):\n * - CHAT workflows: shared token across all sessions\n * - Other workflows: per-type token\n *\n * @param workflowDefinition - Workflow type (default: 'chat')\n * @param rootNamespaceId - Optional root namespace for scoping\n * @param forceRefresh - Bypass cache\n */\n async getToken(\n workflowDefinition: string = DEFAULT_WORKFLOW_DEFINITION,\n rootNamespaceId?: string,\n forceRefresh: boolean = false\n ): Promise {\n const now = Date.now();\n const cacheKey = this.getCacheKey(workflowDefinition, rootNamespaceId);\n\n const cached = this.tokenCache.get(cacheKey);\n if (!forceRefresh && cached && cached.expiresAt > now) {\n return cached.token;\n }\n\n if (forceRefresh) {\n this.tokenCache.delete(cacheKey);\n }\n\n const url = `${this.config.instanceUrl}/api/v4/ai/duo_workflows/direct_access`;\n\n const body: Record = {\n workflow_definition: workflowDefinition,\n };\n if (rootNamespaceId) {\n body.root_namespace_id = rootNamespaceId;\n }\n if (this.config.featureFlags && Object.keys(this.config.featureFlags).length > 0) {\n body.feature_flags = this.config.featureFlags;\n }\n\n try {\n const response = await this.fetchFn(url, {\n method: 'POST',\n headers: {\n ...this.config.getHeaders(),\n 'Content-Type': 'application/json',\n },\n body: JSON.stringify(body),\n });\n\n if (!response.ok) {\n const errorText = await response.text();\n const safeError = sanitizeErrorText(errorText);\n\n // 401 — try refreshing the API key once\n if (response.status === 401 && this.config.refreshApiKey && !forceRefresh) {\n try {\n await this.config.refreshApiKey();\n return await this.getToken(workflowDefinition, rootNamespaceId, true);\n } catch {\n throw new GitLabError({\n message: `Failed to get workflow token: ${response.status} ${response.statusText} - ${safeError}`,\n statusCode: response.status,\n responseBody: safeError,\n });\n }\n }\n\n // 403 — fail fast with clear message about requirements\n if (response.status === 403) {\n throw new GitLabError({\n message:\n `GitLab Duo Agent Platform access denied. ` +\n `GitLab Duo Agent Platform requires GitLab Ultimate with Duo Enterprise add-on. ` +\n `Ensure: (1) Your instance has GitLab Ultimate, ` +\n `(2) Duo Enterprise add-on is enabled, ` +\n `(3) Your account has access to AI features.`,\n statusCode: response.status,\n responseBody: safeError,\n });\n }\n\n throw new GitLabError({\n message: `Failed to get workflow token: ${response.status} ${response.statusText} - ${safeError}`,\n statusCode: response.status,\n responseBody: safeError,\n });\n }\n\n const data = (await response.json()) as GenerateTokenResponse;\n\n // Cache for 25 minutes\n this.tokenCache.set(cacheKey, {\n token: data,\n expiresAt: now + TOKEN_CACHE_DURATION_MS,\n });\n\n return data;\n } catch (error) {\n if (error instanceof GitLabError) throw error;\n throw new GitLabError({\n message: `Failed to get workflow token: ${error}`,\n cause: error,\n });\n }\n }\n\n /**\n * Create a new workflow on the GitLab instance.\n *\n * @param goal - The user's message / goal for this workflow\n * @param options - Additional workflow creation options\n * @returns The created workflow's ID\n */\n async createWorkflow(\n goal: string,\n options?: {\n projectId?: string;\n namespaceId?: string;\n workflowDefinition?: string;\n agentPrivileges?: number[];\n environment?: string;\n allowAgentToRequestUser?: boolean;\n }\n ): Promise {\n // Validate goal parameter\n if (!goal || typeof goal !== 'string') {\n throw new GitLabError({ message: 'goal is required and must be a non-empty string' });\n }\n if (goal.length > 10000) {\n throw new GitLabError({ message: 'goal exceeds maximum length of 10000 characters' });\n }\n\n const url = `${this.config.instanceUrl}/api/v4/ai/duo_workflows/workflows`;\n\n const body: Record = {\n goal,\n project_id: options?.projectId,\n namespace_id: options?.namespaceId,\n workflow_definition: options?.workflowDefinition ?? DEFAULT_WORKFLOW_DEFINITION,\n agent_privileges: options?.agentPrivileges ?? DEFAULT_AGENT_PRIVILEGES,\n environment: options?.environment ?? WORKFLOW_ENVIRONMENT,\n allow_agent_to_request_user: options?.allowAgentToRequestUser ?? true,\n };\n\n try {\n const response = await this.fetchFn(url, {\n method: 'POST',\n headers: {\n ...this.config.getHeaders(),\n 'Content-Type': 'application/json',\n },\n body: JSON.stringify(body),\n });\n\n if (!response.ok) {\n const errorText = await response.text();\n const safeError = sanitizeErrorText(errorText);\n throw new GitLabError({\n message: `Failed to create workflow: ${response.status} ${response.statusText} - ${safeError}`,\n statusCode: response.status,\n responseBody: safeError,\n });\n }\n\n const data = (await response.json()) as CreateWorkflowResponse;\n return data.id.toString();\n } catch (error) {\n if (error instanceof GitLabError) throw error;\n throw new GitLabError({\n message: `Failed to create workflow: ${error}`,\n cause: error,\n });\n }\n }\n\n /**\n * Invalidate cached tokens.\n *\n * @param workflowDefinition - If provided, only invalidate for this type.\n * If omitted, clears ALL cached tokens.\n */\n invalidateToken(workflowDefinition?: string, rootNamespaceId?: string): void {\n if (workflowDefinition) {\n this.tokenCache.delete(this.getCacheKey(workflowDefinition, rootNamespaceId));\n } else {\n this.tokenCache.clear();\n }\n }\n}\n","import { spawn } from 'child_process';\nimport * as path from 'path';\nimport { GitLabProjectCache, type GitLabProject } from './gitlab-project-cache';\nimport { GitLabError } from './gitlab-error';\n\nexport interface GitLabProjectDetectorConfig {\n instanceUrl: string;\n getHeaders: () => Record;\n fetch?: typeof fetch;\n cache?: GitLabProjectCache;\n gitTimeout?: number;\n}\n\n/**\n * Detects GitLab project information from git remote URLs\n *\n * This class provides functionality to:\n * - Parse git remote URLs (SSH, HTTPS, custom domains)\n * - Execute git commands to get remote URLs\n * - Fetch project details from GitLab API\n * - Cache project information to avoid repeated API calls\n */\nexport class GitLabProjectDetector {\n private readonly config: GitLabProjectDetectorConfig;\n private readonly fetchFn: typeof fetch;\n private readonly cache: GitLabProjectCache;\n\n constructor(config: GitLabProjectDetectorConfig) {\n this.config = {\n gitTimeout: 5000, // 5 seconds default\n ...config,\n };\n this.fetchFn = config.fetch ?? fetch;\n this.cache = config.cache ?? new GitLabProjectCache();\n }\n\n /**\n * Auto-detect GitLab project from git remote in the working directory\n *\n * @param workingDirectory - The directory to check for git remote\n * @param remoteName - The git remote name to use (default: 'origin')\n * @returns The detected project or null if not a git repo / no matching remote\n * @throws GitLabError if the API call or an unexpected error occurs\n */\n async detectProject(\n workingDirectory: string,\n remoteName: string = 'origin'\n ): Promise {\n // 1. Check cache first\n const cacheKey = path.resolve(workingDirectory);\n const cached = this.cache.get(cacheKey);\n if (cached) {\n return cached;\n }\n\n try {\n // 2. Get git remote URL\n const remoteUrl = await this.getGitRemoteUrl(workingDirectory, remoteName);\n if (!remoteUrl) {\n return null; // Not a git repo or no remote\n }\n\n // 3. Parse project path from URL\n const projectPath = this.parseGitRemoteUrl(remoteUrl, this.config.instanceUrl);\n if (!projectPath) {\n return null; // Remote doesn't match instance\n }\n\n // 4. Fetch project from GitLab API\n const project = await this.getProjectByPath(projectPath);\n\n // 5. Cache the result\n this.cache.set(cacheKey, project);\n\n return project;\n } catch (error) {\n throw error instanceof GitLabError\n ? error\n : new GitLabError({\n message: `Project detection failed: ${error}`,\n cause: error,\n });\n }\n }\n\n /**\n * Parse a git remote URL to extract the project path\n *\n * Supports:\n * - SSH: git@gitlab.com:namespace/project.git\n * - HTTPS: https://gitlab.com/namespace/project.git\n * - HTTP: http://gitlab.local/namespace/project.git\n * - Custom domains and ports\n *\n * @param remoteUrl - The git remote URL\n * @param instanceUrl - The GitLab instance URL to match against\n * @returns The project path (e.g., \"namespace/project\") or null if parsing fails\n */\n parseGitRemoteUrl(remoteUrl: string, instanceUrl: string): string | null {\n try {\n // Extract hostname from instanceUrl\n const instanceHost = new URL(instanceUrl).hostname;\n\n // SSH format: git@host:path.git or git@host:port/path.git\n const sshMatch = remoteUrl.match(/^git@([^:]+):(.+?)(?:\\.git)?$/);\n if (sshMatch) {\n const [, host, pathPart] = sshMatch;\n // Handle port in SSH URLs (git@host:port/path)\n const hostWithoutPort = host.split(':')[0];\n if (hostWithoutPort === instanceHost) {\n // Remove port from path if present\n const cleanPath = pathPart.replace(/^\\d+\\//, '');\n return cleanPath.endsWith('.git') ? cleanPath.slice(0, -4) : cleanPath;\n }\n }\n\n // HTTPS/HTTP format: https://host/path.git or https://host:port/path.git\n const httpsMatch = remoteUrl.match(/^(https?):\\/\\/([^/]+)\\/(.+?)(?:\\.git)?$/);\n if (httpsMatch) {\n const [, , hostWithPort, pathPart] = httpsMatch;\n const host = hostWithPort.split(':')[0];\n if (host === instanceHost) {\n return pathPart.endsWith('.git') ? pathPart.slice(0, -4) : pathPart;\n }\n }\n\n return null;\n } catch (error) {\n // URL parsing failed\n return null;\n }\n }\n\n /**\n * Get the git remote URL from a working directory\n *\n * @param workingDirectory - The directory to check\n * @param remoteName - The git remote name (default: 'origin')\n * @returns The remote URL or null if not found\n */\n async getGitRemoteUrl(\n workingDirectory: string,\n remoteName: string = 'origin'\n ): Promise {\n return new Promise((resolve) => {\n const child = spawn('git', ['config', '--get', `remote.${remoteName}.url`], {\n cwd: workingDirectory,\n timeout: this.config.gitTimeout,\n });\n\n let stdout = '';\n let _stderr = '';\n\n child.stdout?.on('data', (data) => {\n stdout += data.toString();\n });\n\n child.stderr?.on('data', (data) => {\n _stderr += data.toString();\n });\n\n child.on('close', (exitCode) => {\n if (exitCode === 0 && stdout.trim()) {\n resolve(stdout.trim());\n } else {\n resolve(null);\n }\n });\n\n child.on('error', () => {\n // Git not available or command failed\n resolve(null);\n });\n });\n }\n\n /**\n * Fetch project details from GitLab API by project path\n *\n * @param projectPath - The project path (e.g., \"namespace/project\")\n * @returns The project details\n * @throws GitLabError if the API call fails\n */\n async getProjectByPath(projectPath: string): Promise {\n // URL-encode the project path\n const encodedPath = encodeURIComponent(projectPath);\n const url = `${this.config.instanceUrl}/api/v4/projects/${encodedPath}`;\n\n try {\n const response = await this.fetchFn(url, {\n method: 'GET',\n headers: this.config.getHeaders(),\n });\n\n if (!response.ok) {\n throw new GitLabError({\n message: `Failed to fetch project '${projectPath}': ${response.status} ${response.statusText}`,\n });\n }\n\n const data = (await response.json()) as {\n id: number;\n path: string;\n path_with_namespace: string;\n name: string;\n namespace?: { id: number };\n };\n\n return {\n id: data.id,\n path: data.path,\n pathWithNamespace: data.path_with_namespace,\n name: data.name,\n namespaceId: data.namespace?.id,\n };\n } catch (error) {\n if (error instanceof GitLabError) {\n throw error;\n }\n throw new GitLabError({\n message: `Failed to fetch project '${projectPath}': ${error}`,\n cause: error,\n });\n }\n }\n\n /**\n * Clear the project cache\n */\n clearCache(): void {\n this.cache.clear();\n }\n\n /**\n * Get the cache instance (useful for testing)\n */\n getCache(): GitLabProjectCache {\n return this.cache;\n }\n}\n","/**\n * Simple in-memory cache for GitLab project information\n * Used to avoid repeated API calls when detecting projects from git remotes\n */\n\nexport interface GitLabProject {\n id: number;\n path: string;\n pathWithNamespace: string;\n name: string;\n namespaceId?: number;\n}\n\ninterface CacheEntry {\n project: GitLabProject;\n expiresAt: number;\n}\n\n/**\n * In-memory cache for GitLab project information with TTL support\n */\nexport class GitLabProjectCache {\n private cache = new Map();\n private defaultTTL: number;\n\n /**\n * Create a new project cache\n * @param defaultTTL - Default time-to-live in milliseconds (default: 5 minutes)\n */\n constructor(defaultTTL: number = 5 * 60 * 1000) {\n this.defaultTTL = defaultTTL;\n }\n\n /**\n * Get a cached project by key\n * @param key - Cache key (typically the working directory path)\n * @returns The cached project or null if not found or expired\n */\n get(key: string): GitLabProject | null {\n const entry = this.cache.get(key);\n if (!entry) {\n return null;\n }\n\n // Check if entry has expired\n if (Date.now() > entry.expiresAt) {\n this.cache.delete(key);\n return null;\n }\n\n return entry.project;\n }\n\n /**\n * Store a project in the cache\n * @param key - Cache key (typically the working directory path)\n * @param project - The project to cache\n * @param ttl - Optional custom TTL in milliseconds\n */\n set(key: string, project: GitLabProject, ttl?: number): void {\n this.cache.set(key, {\n project,\n expiresAt: Date.now() + (ttl ?? this.defaultTTL),\n });\n }\n\n /**\n * Check if a key exists in the cache (and is not expired)\n * @param key - Cache key to check\n * @returns true if the key exists and is not expired\n */\n has(key: string): boolean {\n return this.get(key) !== null;\n }\n\n /**\n * Remove a specific entry from the cache\n * @param key - Cache key to remove\n */\n delete(key: string): void {\n this.cache.delete(key);\n }\n\n /**\n * Clear all entries from the cache\n */\n clear(): void {\n this.cache.clear();\n }\n\n /**\n * Get the number of entries in the cache (including expired ones)\n */\n get size(): number {\n return this.cache.size;\n }\n\n /**\n * Clean up expired entries from the cache\n * This is useful for long-running processes to prevent memory leaks\n */\n cleanup(): void {\n const now = Date.now();\n for (const [key, entry] of this.cache.entries()) {\n if (now > entry.expiresAt) {\n this.cache.delete(key);\n }\n }\n }\n}\n","/**\n * Dynamic model discovery via GitLab GraphQL API.\n *\n * Queries `aiChatAvailableModels` to discover which models are available\n * for a given GitLab namespace. Used to dynamically populate `duo-workflow-*`\n * model IDs at runtime.\n *\n * Requires GitLab 18.4+ (18.5+ for pinned model support).\n */\n\nimport { GitLabError } from './gitlab-error';\n\n// ---------------------------------------------------------------------------\n// Types\n// ---------------------------------------------------------------------------\n\nexport interface AiModel {\n /** Display name (e.g., 'Claude Sonnet 4.6') */\n name: string;\n /** Model reference for API use (e.g., 'claude_sonnet_4_6' or 'anthropic/claude-sonnet-4-5-20250929') */\n ref: string;\n}\n\nexport interface AiChatAvailableModels {\n defaultModel: AiModel | null;\n selectableModels: AiModel[];\n pinnedModel: AiModel | null;\n}\n\nexport interface DiscoveredModels {\n /** The effective model (pinned > user-selected > default) */\n defaultModel: AiModel | null;\n /** All models the user can select from */\n selectableModels: AiModel[];\n /** Admin-pinned model (overrides everything) */\n pinnedModel: AiModel | null;\n /** Whether the ai_user_model_switching feature flag is enabled */\n modelSwitchingEnabled: boolean;\n /** GitLab instance version */\n instanceVersion: string | null;\n}\n\nexport interface ModelDiscoveryConfig {\n /** GitLab instance URL */\n instanceUrl: string;\n /** Function returning auth headers */\n getHeaders: () => Record;\n /** Custom fetch */\n fetch?: typeof fetch;\n}\n\n// ---------------------------------------------------------------------------\n// GraphQL query (inlined — no need for graphql-request gql tag)\n// ---------------------------------------------------------------------------\n\nconst AI_CHAT_AVAILABLE_MODELS_QUERY = `\n query aiChatAvailableModels($rootNamespaceId: GroupID!) {\n metadata {\n featureFlags(names: [\"ai_user_model_switching\"]) {\n enabled\n name\n }\n version\n }\n\n aiChatAvailableModels(rootNamespaceId: $rootNamespaceId) {\n defaultModel {\n name\n ref\n }\n selectableModels {\n name\n ref\n }\n pinnedModel {\n name\n ref\n }\n }\n }\n`;\n\n// ---------------------------------------------------------------------------\n// Client\n// ---------------------------------------------------------------------------\n\nconst DISCOVERY_CACHE_TTL_MS = 10 * 60 * 1000;\n\ninterface CachedDiscovery {\n data: DiscoveredModels;\n expiresAt: number;\n}\n\nexport class GitLabModelDiscovery {\n private readonly config: ModelDiscoveryConfig;\n private readonly fetchFn: typeof fetch;\n private cache = new Map();\n\n constructor(config: ModelDiscoveryConfig) {\n this.config = config;\n this.fetchFn = config.fetch ?? fetch;\n }\n\n /**\n * Discover available models for a given root namespace.\n *\n * Results are cached per `rootNamespaceId` with a 10-minute TTL.\n * Use `invalidateCache()` to force an immediate refresh.\n *\n * @param rootNamespaceId - GitLab group ID (e.g., 'gid://gitlab/Group/12345')\n */\n async discover(rootNamespaceId: string): Promise {\n const cached = this.cache.get(rootNamespaceId);\n if (cached && cached.expiresAt > Date.now()) {\n return cached.data;\n }\n\n const url = `${this.config.instanceUrl}/api/graphql`;\n\n try {\n const response = await this.fetchFn(url, {\n method: 'POST',\n headers: {\n ...this.config.getHeaders(),\n 'Content-Type': 'application/json',\n },\n body: JSON.stringify({\n query: AI_CHAT_AVAILABLE_MODELS_QUERY,\n variables: { rootNamespaceId },\n }),\n });\n\n if (!response.ok) {\n const errorText = await response.text();\n throw new GitLabError({\n message: `Model discovery GraphQL request failed: ${response.status} ${response.statusText} - ${errorText}`,\n statusCode: response.status,\n responseBody: errorText,\n });\n }\n\n const json = (await response.json()) as {\n data?: {\n aiChatAvailableModels?: AiChatAvailableModels | null;\n metadata?: {\n featureFlags?: Array<{ name: string; enabled: boolean }>;\n version?: string;\n } | null;\n };\n errors?: Array<{ message: string }>;\n };\n\n if (json.errors && json.errors.length > 0) {\n throw new GitLabError({\n message: `Model discovery GraphQL errors: ${json.errors.map((e) => e.message).join(', ')}`,\n });\n }\n\n const models = json.data?.aiChatAvailableModels;\n const metadata = json.data?.metadata;\n\n const modelSwitchingEnabled =\n metadata?.featureFlags?.find((f) => f.name === 'ai_user_model_switching')?.enabled ?? false;\n\n const result: DiscoveredModels = {\n defaultModel: models?.defaultModel ?? null,\n selectableModels: models?.selectableModels ?? [],\n pinnedModel: models?.pinnedModel ?? null,\n modelSwitchingEnabled,\n instanceVersion: metadata?.version ?? null,\n };\n\n this.cache.set(rootNamespaceId, {\n data: result,\n expiresAt: Date.now() + DISCOVERY_CACHE_TTL_MS,\n });\n return result;\n } catch (error) {\n if (error instanceof GitLabError) throw error;\n throw new GitLabError({\n message: `Model discovery failed: ${error}`,\n cause: error,\n });\n }\n }\n\n /**\n * Get the effective model ref to use for a workflow.\n *\n * Priority: pinned > user-selected > default.\n *\n * @param rootNamespaceId - GitLab group ID\n * @param userSelectedRef - Optional user preference\n */\n async getEffectiveModelRef(\n rootNamespaceId: string,\n userSelectedRef?: string\n ): Promise {\n const discovered = await this.discover(rootNamespaceId);\n\n // Pinned model always wins\n if (discovered.pinnedModel) {\n return discovered.pinnedModel.ref;\n }\n\n // User selection (if model switching is enabled)\n if (userSelectedRef && discovered.modelSwitchingEnabled) {\n const isValid = discovered.selectableModels.some((m) => m.ref === userSelectedRef);\n if (isValid) {\n return userSelectedRef;\n }\n }\n\n // Default\n return discovered.defaultModel?.ref ?? null;\n }\n\n /**\n * Invalidate the cached discovery results.\n */\n invalidateCache(): void {\n this.cache.clear();\n }\n}\n","/**\n * File-based cache for workflow model discovery results and user selection.\n *\n * A single cache file is stored at\n * `~/.cache/opencode/gitlab-workflow-model-cache.json`\n * (or `$XDG_CACHE_HOME/opencode/...` when set).\n *\n * The file contains a JSON object keyed by a truncated SHA-256 hash of the\n * workspace directory path combined with the GitLab instance URL. This ensures\n * that switching instances for the same workspace invalidates the cache.\n * Each value holds:\n * - `discovery`: The full DiscoveredModels JSON from the last successful discovery\n * - `selectedModelRef`: The model ref the user last selected\n * - `selectedModelName`: Human-readable name of the selected model\n * - `updatedAt`: ISO timestamp of the last write\n */\n\nimport * as fs from 'fs';\nimport * as path from 'path';\nimport * as os from 'os';\nimport * as crypto from 'crypto';\nimport type { DiscoveredModels } from './gitlab-model-discovery';\n\nexport interface ModelCacheEntry {\n discovery: DiscoveredModels | null;\n selectedModelRef: string | null;\n selectedModelName: string | null;\n updatedAt: string;\n}\n\ntype CacheFile = Record;\n\nfunction getCacheFilePath(): string {\n const cacheHome = process.env.XDG_CACHE_HOME || path.join(os.homedir(), '.cache');\n return path.join(cacheHome, 'opencode', 'gitlab-workflow-model-cache.json');\n}\n\nfunction computeCacheKey(workDir: string, instanceUrl?: string): string {\n const normalizedUrl = (instanceUrl || 'https://gitlab.com').replace(/\\/$/, '');\n return crypto\n .createHash('sha256')\n .update(`${workDir}\\0${normalizedUrl}`)\n .digest('hex')\n .slice(0, 12);\n}\n\nexport class GitLabModelCache {\n private readonly filePath: string;\n private readonly key: string;\n\n constructor(workDir: string, instanceUrl?: string) {\n this.filePath = getCacheFilePath();\n this.key = computeCacheKey(workDir, instanceUrl);\n }\n\n private readAll(): CacheFile {\n try {\n if (!fs.existsSync(this.filePath)) {\n return {};\n }\n const raw = fs.readFileSync(this.filePath, 'utf-8');\n return JSON.parse(raw) as CacheFile;\n } catch {\n return {};\n }\n }\n\n private writeAll(data: CacheFile): void {\n try {\n const dir = path.dirname(this.filePath);\n fs.mkdirSync(dir, { recursive: true, mode: 0o700 });\n fs.writeFileSync(this.filePath, JSON.stringify(data, null, 2), { mode: 0o600 });\n } catch {\n // Best-effort — cache write failures are non-fatal\n }\n }\n\n /**\n * Load the cached entry for this workspace.\n * Returns null if no cache exists or is unreadable.\n */\n load(): ModelCacheEntry | null {\n return this.readAll()[this.key] ?? null;\n }\n\n /**\n * Persist the full cache entry to disk.\n */\n save(entry: ModelCacheEntry): void {\n const data = this.readAll();\n data[this.key] = entry;\n this.writeAll(data);\n }\n\n /**\n * Update only the discovery portion of the cache, preserving selection.\n */\n saveDiscovery(discovery: DiscoveredModels): void {\n const existing = this.load();\n this.save({\n discovery,\n selectedModelRef: existing?.selectedModelRef ?? null,\n selectedModelName: existing?.selectedModelName ?? null,\n updatedAt: new Date().toISOString(),\n });\n }\n\n /**\n * Update only the selected model, preserving the discovery data.\n */\n saveSelection(ref: string | null, name: string | null): void {\n const existing = this.load();\n this.save({\n discovery: existing?.discovery ?? null,\n selectedModelRef: ref,\n selectedModelName: name,\n updatedAt: new Date().toISOString(),\n });\n }\n\n /**\n * Remove the entry for this workspace from the cache file.\n */\n clear(): void {\n const data = this.readAll();\n delete data[this.key];\n if (Object.keys(data).length === 0) {\n try {\n if (fs.existsSync(this.filePath)) {\n fs.unlinkSync(this.filePath);\n }\n } catch {\n // Best-effort\n }\n } else {\n this.writeAll(data);\n }\n }\n\n /**\n * Convenience: get the cached selected model ref (or null).\n */\n getSelectedModelRef(): string | null {\n return this.load()?.selectedModelRef ?? null;\n }\n\n /**\n * Convenience: get the cached selected model name (or null).\n */\n getSelectedModelName(): string | null {\n return this.load()?.selectedModelName ?? null;\n }\n\n /**\n * Convenience: get the cached discovery result (or null).\n */\n getDiscovery(): DiscoveredModels | null {\n return this.load()?.discovery ?? null;\n }\n}\n","/**\n * LanguageModelV2 adapter for GitLab Duo Agent Platform (DWS).\n *\n * Maps DWS WebSocket events to the Vercel AI SDK streaming protocol:\n * newCheckpoint (text) → text-delta\n * runMcpTool → tool-call (emitted for UI visibility)\n * workflow COMPLETED → finish(stop)\n * workflow FAILED → error\n *\n * IMPORTANT: Tool execution architecture\n * =======================================\n * DWS drives the agentic loop server-side. When DWS requests a tool via\n * `runMcpTool`, we execute it ourselves using the AI SDK tools passed in\n * `options.tools`, send the result back to DWS via WebSocket `actionResponse`,\n * and keep streaming. The stream stays open until DWS sends COMPLETED/FAILED.\n *\n * This means the AI SDK's outer tool loop (which would call doStream() again\n * with tool results in messages) is NOT used for workflow models. The entire\n * agentic conversation happens within a single doStream() call.\n *\n * We still emit `tool-call` stream parts so the UI can show tool usage,\n * but finishReason is always 'stop' (never 'tool-calls').\n *\n * Lifecycle per doStream() call:\n * 1. Get workflow token (POST /duo_workflows/direct_access)\n * 2. Create workflow (POST /duo_workflows/workflows)\n * 3. Connect WebSocket (wss://.../duo_workflows/ws)\n * 4. Send startRequest (with goal, tools, context)\n * 5. Stream events (checkpoint → text, tool request → execute → respond)\n * 6. Close on finish (COMPLETED/FAILED/CANCELLED)\n *\n * SECURITY MODEL — Tool Execution\n * =================================\n * This library acts as a **bridge** between DWS (server) and the host's tool\n * system (e.g., OpenCode). It does NOT execute host-OS commands itself except\n * for the read-only `git` calls inside `getGitInfo()` (fixed argument lists,\n * no user-controlled data, via `execFile`).\n *\n * Built-in tool mapping (`mapBuiltinTool`)\n * -----------------------------------------\n * DWS built-in tools are mapped to structured host-tool invocations that the\n * host's `toolExecutor` callback then executes through its own permission\n * system. For tools that ultimately produce shell commands the following\n * defences are applied:\n *\n * • `shellEscape()` — wraps every argument in single quotes and escapes\n * embedded single quotes, preventing metacharacter injection for all\n * argument-based tools (runCommand, runGitCommand, mkdir, runHTTPRequest).\n *\n * • `validateNoShellMetachars()` — rejects program names and git sub-commands\n * containing `;`, `&`, `|`, `` ` ``, `$`, `(`, `)`, `<`, `>` before they\n * reach shellEscape, providing a defence-in-depth check.\n *\n * • `runShellCommand` — intentionally passes the command string through\n * **without sanitization** because it is a deliberately raw shell tool.\n * The host's `toolExecutor` / permission system is the final gate and must\n * decide whether to allow it. A length cap (10 000 chars) limits DoS via\n * oversized payloads.\n *\n * • `runHTTPRequest` — only `http://` and `https://` URL schemes are allowed\n * (allowlist); all others (file://, gopher://, ftp://, etc.) are rejected.\n * A `--` separator before the URL prevents flag injection via paths like\n * `--output /tmp/evil`.\n *\n * • `mkdir` — rejects null bytes in the directory path.\n *\n * Error sanitization\n * -------------------\n * All error messages forwarded into the stream (tool catch blocks, failed\n * events, WebSocket close reasons) are passed through `sanitizeErrorMessage()`\n * which redacts Bearer tokens, GitLab PAT/CI tokens, and URL credential query\n * parameters before they are surfaced to callers or logged.\n *\n * Trust boundary\n * ---------------\n * DWS is treated as a **trusted server** for the purpose of tool invocation —\n * it controls which tools are called and with what arguments. Consumers MUST\n * implement their own authorization layer in the `toolExecutor` callback\n * (e.g., user confirmation prompts, allow-lists) for any tool that can cause\n * side effects on the user's machine.\n */\n\nimport { GitLabWorkflowClient } from './gitlab-workflow-client';\nimport { GitLabWorkflowTokenClient } from './gitlab-workflow-token-client';\nimport { GitLabProjectDetector } from './gitlab-project-detector';\nimport { GitLabError } from './gitlab-error';\nimport { getWorkflowModelRef } from './model-mappings';\nimport { GitLabModelDiscovery } from './gitlab-model-discovery';\nimport { GitLabModelCache } from './gitlab-model-cache';\nimport { mapBuiltinTool, sanitizeErrorMessage } from './gitlab-workflow-builtins';\n\nimport type {\n LanguageModelV2,\n LanguageModelV2CallOptions,\n LanguageModelV2StreamPart,\n LanguageModelV2FinishReason,\n LanguageModelV2CallWarning,\n LanguageModelV2Content,\n LanguageModelV2Usage,\n LanguageModelV2Message,\n LanguageModelV2FunctionTool,\n} from '@ai-sdk/provider';\n\nimport type {\n GitLabWorkflowOptions,\n GitLabWorkflowClientConfig,\n McpToolDefinition,\n AdditionalContext,\n StartRequest,\n WorkflowClientEvent,\n CheckpointData,\n UiChatLogEntry,\n NewCheckpoint,\n} from './gitlab-workflow-types';\n\ninterface StreamState {\n streamClosed: boolean;\n streamedInputChars: number;\n streamedOutputChars: number;\n pendingToolCount: number;\n deferredClose: (() => void) | null;\n activeTextBlockId: string | null;\n agentMessageEmitted: Map;\n currentAgentMessageId: string;\n activeClient: GitLabWorkflowClient | null;\n}\n\nimport {\n DEFAULT_WORKFLOW_DEFINITION,\n DEFAULT_CLIENT_CAPABILITIES,\n CLIENT_VERSION,\n} from './gitlab-workflow-types';\n\nexport interface GitLabWorkflowLanguageModelConfig extends GitLabWorkflowClientConfig {\n /** Provider name (e.g., 'gitlab.workflow') */\n provider: string;\n}\n\n// ---------------------------------------------------------------------------\n// Payload size utilities\n// ---------------------------------------------------------------------------\n\nfunction simplifySchemaObj(schema: Record): Record {\n if (!schema || typeof schema !== 'object') return schema;\n\n const result: Record = {};\n for (const [key, value] of Object.entries(schema)) {\n if (key === 'description' || key === 'examples' || key === 'default') {\n continue;\n }\n if (key === 'properties' && typeof value === 'object' && value !== null) {\n const props: Record = {};\n for (const [propName, propValue] of Object.entries(value as Record)) {\n if (typeof propValue === 'object' && propValue !== null) {\n props[propName] = simplifySchemaObj(propValue as Record);\n } else {\n props[propName] = propValue;\n }\n }\n result[key] = props;\n } else if (key === 'items' && typeof value === 'object' && value !== null) {\n result[key] = simplifySchemaObj(value as Record);\n } else {\n result[key] = value;\n }\n }\n return result;\n}\n\nfunction simplifySchema(schemaStr: string): string {\n try {\n return JSON.stringify(simplifySchemaObj(JSON.parse(schemaStr)));\n } catch {\n return schemaStr;\n }\n}\n\nfunction minimalSchemaObj(schema: Record): Record {\n if (!schema || typeof schema !== 'object') return schema;\n\n const result: Record = { type: schema.type || 'object' };\n if (schema.required) {\n result.required = schema.required;\n }\n if (schema.properties && typeof schema.properties === 'object') {\n const props: Record = {};\n for (const [propName, propValue] of Object.entries(\n schema.properties as Record\n )) {\n if (typeof propValue === 'object' && propValue !== null) {\n const pv = propValue as Record;\n props[propName] = { type: pv.type || 'string' };\n } else {\n props[propName] = { type: 'string' };\n }\n }\n result.properties = props;\n }\n return result;\n}\n\nfunction minimalSchema(schemaStr: string): string {\n try {\n return JSON.stringify(minimalSchemaObj(JSON.parse(schemaStr)));\n } catch {\n return schemaStr;\n }\n}\n\n/**\n * Callback for executing a tool requested by DWS.\n * Provided by the consumer (e.g., OpenCode) to bridge DWS tool requests\n * to the host's tool execution system.\n *\n * @param toolName - Name of the tool DWS wants to execute\n * @param args - JSON-encoded arguments\n * @returns Tool execution result as a string, or throws on error\n */\nexport type WorkflowToolExecutor = (\n toolName: string,\n args: string,\n requestID: string\n) => Promise<{ result: string; error?: string | null }>;\n\n// mapBuiltinTool, sanitizeErrorMessage, shellEscape, validateNoShellMetachars\n// are imported from './gitlab-workflow-builtins' (shared module).\n\n/**\n * GitLab Duo Agent Platform Language Model.\n *\n * Implements LanguageModelV2 by bridging the DWS WebSocket protocol\n * to the Vercel AI SDK stream part format.\n */\nexport class GitLabWorkflowLanguageModel implements LanguageModelV2 {\n readonly specificationVersion = 'v2' as const;\n readonly modelId: string;\n readonly supportedUrls: Record = {};\n\n private readonly config: GitLabWorkflowLanguageModelConfig;\n private readonly workflowOptions: GitLabWorkflowOptions;\n private readonly tokenClient: GitLabWorkflowTokenClient;\n private readonly projectDetector: GitLabProjectDetector;\n private readonly modelDiscovery: GitLabModelDiscovery;\n private readonly modelCache: GitLabModelCache;\n\n // Cached detected project path\n private detectedProjectPath: string | null = null;\n\n // Workflow ID persisted across turns for multi-turn conversations.\n // When DWS sends INPUT_REQUIRED, the workflow stays alive server-side.\n // On the next doStream() call we reuse this ID (skip createWorkflow).\n private currentWorkflowId: string | null = null;\n\n // Persisted across turns so that cumulative DWS chat logs don't re-emit\n // messages that were already streamed in a previous doStream() call.\n private persistedAgentEmitted = new Map();\n\n // Track all active stream clients so stopWorkflow() can stop them all.\n private readonly activeClients = new Set();\n\n // Cache resolved values to avoid redundant GraphQL calls\n private _selectedModelRef?: string;\n private _selectedModelName?: string;\n private _rootNamespaceId?: string;\n private _discoveryPromise?: Promise;\n\n /**\n * Get the cached selected model ref.\n */\n get selectedModelRef(): string | null {\n return this._selectedModelRef ?? null;\n }\n\n /**\n * Set the selected model ref (e.g., from an eager discover call).\n * This will be used by resolveModelRef() to skip the picker.\n * Also persists to the file-based workspace cache.\n */\n set selectedModelRef(ref: string | null) {\n this._selectedModelRef = ref ?? undefined;\n this.modelCache.saveSelection(ref, this._selectedModelName ?? null);\n }\n\n /**\n * Get the cached selected model display name.\n */\n get selectedModelName(): string | null {\n return this._selectedModelName ?? null;\n }\n\n /**\n * Set the selected model display name.\n * Also persists to the file-based workspace cache.\n */\n set selectedModelName(name: string | null) {\n this._selectedModelName = name ?? undefined;\n this.modelCache.saveSelection(this._selectedModelRef ?? null, name);\n }\n\n /**\n * Optional external tool executor. When set, this is called for tool\n * requests instead of looking up tools from `options.tools`.\n * This allows the consumer (OpenCode) to wire in its permission system.\n *\n * The executor is automatically bound to the async context at the time\n * it is set, so that AsyncLocalStorage-based contexts (like Instance)\n * remain available when the executor is invoked from WebSocket callbacks.\n */\n private _toolExecutor: WorkflowToolExecutor | null = null;\n\n /**\n * Optional callback invoked with intermediate token usage estimates\n * after each tool execution completes. This allows the consumer to\n * display live token counts during long-running DWS workflows, since\n * the AI SDK only surfaces usage via finish-step at stream end.\n */\n onUsageUpdate: ((usage: { inputTokens: number; outputTokens: number }) => void) | null = null;\n\n /**\n * Optional callback invoked when multiple workflow models are available\n * and the user should pick one. Set per-stream by the host (e.g., OpenCode)\n * alongside `toolExecutor`. Takes precedence over `workflowOptions.onSelectModel`.\n */\n onSelectModel:\n | ((models: import('./gitlab-model-discovery').AiModel[]) => Promise)\n | null = null;\n\n get toolExecutor(): WorkflowToolExecutor | null {\n return this._toolExecutor;\n }\n\n set toolExecutor(executor: WorkflowToolExecutor | null) {\n if (executor) {\n try {\n // eslint-disable-next-line @typescript-eslint/no-var-requires\n const { AsyncResource } = require('node:async_hooks');\n this._toolExecutor = AsyncResource.bind(executor);\n } catch {\n this._toolExecutor = executor;\n }\n } else {\n this._toolExecutor = null;\n }\n }\n\n constructor(\n modelId: string,\n config: GitLabWorkflowLanguageModelConfig,\n workflowOptions: GitLabWorkflowOptions = {}\n ) {\n this.modelId = modelId;\n this.config = config;\n this.workflowOptions = workflowOptions;\n\n const workDir = workflowOptions.workingDirectory ?? process.cwd();\n this.modelCache = new GitLabModelCache(workDir, config.instanceUrl);\n\n const cached = this.modelCache.load();\n if (cached?.selectedModelRef) {\n this._selectedModelRef = cached.selectedModelRef;\n }\n if (cached?.selectedModelName) {\n this._selectedModelName = cached.selectedModelName;\n }\n\n this.tokenClient = new GitLabWorkflowTokenClient({\n instanceUrl: config.instanceUrl,\n getHeaders: config.getHeaders,\n refreshApiKey: config.refreshApiKey,\n fetch: config.fetch,\n featureFlags: config.featureFlags,\n });\n\n this.projectDetector = new GitLabProjectDetector({\n instanceUrl: config.instanceUrl,\n getHeaders: config.getHeaders,\n fetch: config.fetch,\n });\n\n this.modelDiscovery = new GitLabModelDiscovery({\n instanceUrl: config.instanceUrl,\n getHeaders: config.getHeaders,\n fetch: config.fetch,\n });\n }\n\n get provider(): string {\n return this.config.provider;\n }\n\n /**\n * Resolve the project ID (path) to use for workflow creation.\n * Priority: explicit option > auto-detected from git remote > undefined.\n */\n private async resolveProjectId(): Promise {\n if (this.workflowOptions.projectId) {\n return this.workflowOptions.projectId;\n }\n\n if (this.detectedProjectPath) {\n return this.detectedProjectPath;\n }\n\n const workDir = this.workflowOptions.workingDirectory ?? process.cwd();\n const project = await this.projectDetector.detectProject(workDir);\n if (project) {\n this.detectedProjectPath = project.pathWithNamespace;\n return project.pathWithNamespace;\n }\n\n return undefined;\n }\n\n /**\n * Resolve the root namespace GID to use for model discovery.\n *\n * Priority:\n * 1. Explicit `rootNamespaceId` in workflowOptions (caller-provided GID)\n * 2. Auto-detected from git remote via project detector (namespace.id → GID)\n * 3. Cached from previous call\n */\n private async resolveRootNamespaceId(): Promise {\n if (this.workflowOptions.rootNamespaceId) {\n return this.workflowOptions.rootNamespaceId;\n }\n\n // Return cached value if available\n if (this._rootNamespaceId !== undefined) {\n return this._rootNamespaceId;\n }\n\n const workDir = this.workflowOptions.workingDirectory ?? process.cwd();\n const project = await this.projectDetector.detectProject(workDir);\n if (project?.namespaceId) {\n const gid = `gid://gitlab/Group/${project.namespaceId}`;\n this._rootNamespaceId = gid;\n return gid;\n }\n\n this._rootNamespaceId = null;\n return null;\n }\n\n /**\n * Resolve the effective DWS model ref to use for this stream.\n * Deduplicates concurrent calls via a shared promise.\n *\n * Priority for the canonical `duo-workflow` model ID:\n * 1. Admin-pinned model (from GitLabModelDiscovery) — always wins\n * 2. User selection via onSelectModel callback (if model switching enabled)\n * 3. Workspace default model\n * 4. File-cached discovery/selection — used when live discovery fails\n * 5. Hard-coded 'default' (DWS decides) — fallback when discovery fails\n *\n * For all other `duo-workflow-*` model IDs the static mapping is used as-is.\n */\n private async resolveModelRef(): Promise {\n const staticRef = getWorkflowModelRef(this.modelId);\n\n if (this.modelId !== 'duo-workflow') {\n return staticRef ?? 'default';\n }\n\n if (this._selectedModelRef) {\n return this._selectedModelRef;\n }\n\n if (!this._discoveryPromise) {\n this._discoveryPromise = this.doResolveModelRef();\n this._discoveryPromise.finally(() => {\n this._discoveryPromise = undefined;\n });\n }\n return this._discoveryPromise;\n }\n\n private async doResolveModelRef(): Promise {\n const rootNamespaceId = await this.resolveRootNamespaceId();\n\n if (!rootNamespaceId) {\n this._selectedModelRef = 'default';\n return 'default';\n }\n\n try {\n const discovered = await this.modelDiscovery.discover(rootNamespaceId);\n this.modelCache.saveDiscovery(discovered);\n\n if (discovered.pinnedModel) {\n this._selectedModelRef = discovered.pinnedModel.ref;\n this._selectedModelName = discovered.pinnedModel.name;\n this.modelCache.saveSelection(discovered.pinnedModel.ref, discovered.pinnedModel.name);\n return discovered.pinnedModel.ref;\n }\n\n const selectFn = this.onSelectModel ?? this.workflowOptions.onSelectModel;\n if (discovered.selectableModels.length > 0 && selectFn) {\n const selected = await selectFn(discovered.selectableModels);\n if (selected) {\n const match = discovered.selectableModels.find((m) => m.ref === selected);\n if (match) {\n this._selectedModelRef = match.ref;\n this._selectedModelName = match.name;\n this.modelCache.saveSelection(match.ref, match.name);\n return match.ref;\n }\n }\n }\n\n if (discovered.defaultModel) {\n this._selectedModelRef = discovered.defaultModel.ref;\n this._selectedModelName = discovered.defaultModel.name;\n this.modelCache.saveSelection(discovered.defaultModel.ref, discovered.defaultModel.name);\n return discovered.defaultModel.ref;\n }\n } catch {\n const cachedEntry = this.modelCache.load();\n if (cachedEntry?.selectedModelRef) {\n this._selectedModelRef = cachedEntry.selectedModelRef;\n this._selectedModelName = cachedEntry.selectedModelName ?? undefined;\n return cachedEntry.selectedModelRef;\n }\n }\n\n this._selectedModelRef = 'default';\n return 'default';\n }\n\n /**\n * Pre-fetch available models for the workspace.\n * Call this early (e.g., on IDE startup) to avoid blocking the first stream.\n * Results are persisted to the workspace model cache.\n *\n * @param rootNamespaceId - GitLab group ID (e.g., 'gid://gitlab/Group/12345')\n * @returns Discovered models with default, selectable, and pinned models\n */\n async discoverModels(\n rootNamespaceId: string\n ): Promise {\n const result = await this.modelDiscovery.discover(rootNamespaceId);\n this.modelCache.saveDiscovery(result);\n return result;\n }\n\n /**\n * Get the file-based model cache instance for this workspace.\n * Useful for consumers that need direct cache access (e.g., the discover route).\n */\n getModelCache(): GitLabModelCache {\n return this.modelCache;\n }\n\n /**\n * Stop the active workflow.\n */\n stopWorkflow(): void {\n for (const client of this.activeClients) {\n if (client.isConnected) {\n client.stop();\n }\n }\n }\n\n /**\n * Reset the workflow state, forcing a new workflow to be created on the\n * next doStream() call. Call this when starting a new conversation.\n */\n resetWorkflow(): void {\n this.currentWorkflowId = null;\n this.persistedAgentEmitted.clear();\n }\n\n /**\n * Get the current workflow ID (if any).\n * Useful for consumers that need to track workflow state.\n */\n get workflowId(): string | null {\n return this.currentWorkflowId;\n }\n\n // ---------------------------------------------------------------------------\n // LanguageModelV2 — doGenerate (non-streaming)\n // ---------------------------------------------------------------------------\n\n async doGenerate(options: LanguageModelV2CallOptions): Promise<{\n content: LanguageModelV2Content[];\n finishReason: LanguageModelV2FinishReason;\n usage: LanguageModelV2Usage;\n warnings: LanguageModelV2CallWarning[];\n }> {\n // DWS is inherently streaming. Collect the full stream into a single result.\n const { stream } = await this.doStream(options);\n const reader = stream.getReader();\n\n const textParts: string[] = [];\n const toolCalls: LanguageModelV2Content[] = [];\n let finishReason: LanguageModelV2FinishReason = 'unknown';\n const usage: LanguageModelV2Usage = { inputTokens: 0, outputTokens: 0, totalTokens: 0 };\n\n try {\n // eslint-disable-next-line no-constant-condition\n while (true) {\n const { done, value } = await reader.read();\n if (done) break;\n\n switch (value.type) {\n case 'text-delta':\n textParts.push(value.delta);\n break;\n case 'tool-call':\n toolCalls.push({\n type: 'tool-call',\n toolCallId: value.toolCallId,\n toolName: value.toolName,\n input: value.input,\n });\n break;\n case 'finish':\n finishReason = value.finishReason;\n if (value.usage) {\n usage.inputTokens = value.usage.inputTokens ?? 0;\n usage.outputTokens = value.usage.outputTokens ?? 0;\n usage.totalTokens = value.usage.totalTokens ?? 0;\n }\n break;\n case 'error':\n throw value.error;\n }\n }\n } finally {\n reader.releaseLock();\n }\n\n const content: LanguageModelV2Content[] = [];\n const fullText = textParts.join('');\n if (fullText) {\n content.push({ type: 'text', text: fullText });\n }\n content.push(...toolCalls);\n\n return { content, finishReason, usage, warnings: [] };\n }\n\n // ---------------------------------------------------------------------------\n // LanguageModelV2 — doStream (streaming)\n // ---------------------------------------------------------------------------\n\n async doStream(options: LanguageModelV2CallOptions): Promise<{\n stream: ReadableStream;\n request?: { body?: unknown };\n }> {\n // Extract the user's goal from the prompt\n const goal = this.extractGoalFromPrompt(options.prompt);\n\n // Get the model ref for WebSocket URL — resolved dynamically for 'duo-workflow'.\n const modelRef = await this.resolveModelRef();\n\n // Extract MCP tools from options.tools (AI SDK tools → DWS mcpTools)\n const mcpTools = this.extractMcpTools(options);\n\n // Merge preapproved tools — all tool names if options provided\n const preapprovedTools = this.workflowOptions.preapprovedTools ?? mcpTools.map((t) => t.name);\n\n // Build additional context from conversation history.\n const additionalContext = this.buildAdditionalContext(options.prompt);\n\n const toolExecutor = this.toolExecutor ?? null;\n\n // Step 1: Warm the token cache — createWorkflow() below requires a valid\n // session, and getToken() caches the result for subsequent API calls.\n // The DWS token itself is used server-side; the WebSocket authenticates\n // via the GitLab PAT/OAuth token in headers.\n await this.tokenClient.getToken(\n this.workflowOptions.workflowDefinition ?? DEFAULT_WORKFLOW_DEFINITION,\n this.workflowOptions.rootNamespaceId\n );\n\n // Step 1b: Resolve project ID (auto-detect from git remote if needed)\n const projectId = await this.resolveProjectId();\n\n let workflowId: string;\n if (this.currentWorkflowId) {\n workflowId = this.currentWorkflowId;\n } else {\n workflowId = await this.tokenClient.createWorkflow(goal, {\n projectId,\n namespaceId: this.workflowOptions.namespaceId,\n workflowDefinition: this.workflowOptions.workflowDefinition,\n });\n this.currentWorkflowId = workflowId;\n }\n\n // Step 3: Create WebSocket client\n const wsClient = new GitLabWorkflowClient();\n this.activeClients.add(wsClient);\n\n let textBlockCounter = 0;\n\n // Per-stream state — isolated so parallel streams don't corrupt each other.\n // Seed agentMessageEmitted from the persisted map so that cumulative DWS\n // chat logs don't re-emit messages already streamed in a prior turn.\n const ss: StreamState = {\n streamClosed: false,\n streamedInputChars: 0,\n streamedOutputChars: 0,\n pendingToolCount: 0,\n deferredClose: null,\n activeTextBlockId: null,\n agentMessageEmitted: new Map(this.persistedAgentEmitted),\n currentAgentMessageId: '',\n activeClient: wsClient,\n };\n\n for (const msg of options.prompt) {\n if (msg.role === 'system') {\n ss.streamedInputChars += msg.content.length;\n } else if (msg.role === 'user') {\n for (const part of msg.content) {\n if (part.type === 'text') {\n ss.streamedInputChars += (part as { text: string }).text.length;\n }\n }\n }\n }\n\n const stream = new ReadableStream({\n start: async (controller) => {\n try {\n // Connect WebSocket\n await wsClient.connect(\n {\n instanceUrl: this.config.instanceUrl,\n modelRef,\n headers: this.config.getHeaders(),\n projectId: this.workflowOptions.projectId,\n namespaceId: this.workflowOptions.namespaceId,\n rootNamespaceId: this.workflowOptions.rootNamespaceId,\n },\n (event: WorkflowClientEvent) => {\n this.handleWorkflowEvent(\n ss,\n event,\n controller,\n wsClient,\n toolExecutor,\n () => `text-${textBlockCounter++}`\n );\n }\n );\n\n const workflowDef =\n this.workflowOptions.workflowDefinition ?? DEFAULT_WORKFLOW_DEFINITION;\n const capabilities =\n this.workflowOptions.clientCapabilities ?? DEFAULT_CLIENT_CAPABILITIES;\n const workflowMetadata = await this.buildWorkflowMetadata();\n const metadataStr = JSON.stringify(workflowMetadata);\n\n const basePayload = {\n workflowID: workflowId,\n clientVersion: CLIENT_VERSION,\n workflowDefinition: workflowDef,\n goal,\n workflowMetadata: metadataStr,\n clientCapabilities: capabilities,\n preapproved_tools: preapprovedTools,\n };\n const baseSize = JSON.stringify(basePayload).length + 100;\n\n const trimmed = this.trimPayload(mcpTools, additionalContext, baseSize);\n\n const trimmedPreapproved = preapprovedTools.filter((name) =>\n trimmed.mcpTools.some((t) => t.name === name)\n );\n\n const startReq: StartRequest = {\n workflowID: workflowId,\n clientVersion: CLIENT_VERSION,\n workflowDefinition: workflowDef,\n goal,\n workflowMetadata: metadataStr,\n additional_context: trimmed.additionalContext,\n clientCapabilities: capabilities,\n mcpTools: trimmed.mcpTools,\n preapproved_tools: trimmedPreapproved,\n };\n\n if (this.workflowOptions.flowConfig) {\n startReq.flowConfig = this.workflowOptions.flowConfig;\n }\n if (this.workflowOptions.flowConfigSchemaVersion) {\n startReq.flowConfigSchemaVersion = this.workflowOptions.flowConfigSchemaVersion;\n }\n\n wsClient.sendStartRequest(startReq);\n\n // Emit stream-start\n controller.enqueue({\n type: 'stream-start',\n warnings: [],\n });\n\n // Emit response metadata\n controller.enqueue({\n type: 'response-metadata',\n id: workflowId,\n modelId: modelRef,\n });\n } catch (error) {\n if (!ss.streamClosed) {\n controller.enqueue({\n type: 'error',\n error:\n error instanceof GitLabError\n ? error\n : new GitLabError({\n message: `Workflow connection failed: ${error}`,\n cause: error,\n }),\n });\n ss.streamClosed = true;\n controller.close();\n }\n }\n },\n cancel: (_reason) => {\n wsClient.stop();\n wsClient.close();\n this.activeClients.delete(wsClient);\n ss.activeClient = null;\n this.currentWorkflowId = null;\n },\n });\n\n return {\n stream,\n request: {\n body: { workflowId, modelRef, goal },\n },\n };\n }\n\n // ---------------------------------------------------------------------------\n // Event handling\n // ---------------------------------------------------------------------------\n\n private handleWorkflowEvent(\n ss: StreamState,\n event: WorkflowClientEvent,\n controller: ReadableStreamDefaultController,\n wsClient: GitLabWorkflowClient,\n toolExecutor: WorkflowToolExecutor | null,\n nextTextId: () => string\n ): void {\n if (ss.streamClosed) {\n return;\n }\n\n switch (event.type) {\n case 'checkpoint': {\n this.processCheckpoint(ss, event.data, controller, nextTextId);\n break;\n }\n\n case 'tool-request': {\n const { requestID, data } = event;\n let parsedArgs: string;\n try {\n JSON.parse(data.args);\n parsedArgs = data.args;\n } catch {\n parsedArgs = data.args || '{}';\n }\n\n if (ss.activeTextBlockId) {\n controller.enqueue({ type: 'text-end', id: ss.activeTextBlockId });\n ss.activeTextBlockId = null;\n }\n\n controller.enqueue({\n type: 'tool-input-start',\n id: requestID,\n toolName: data.name,\n providerExecuted: true,\n });\n controller.enqueue({\n type: 'tool-input-delta',\n id: requestID,\n delta: parsedArgs,\n });\n controller.enqueue({\n type: 'tool-input-end',\n id: requestID,\n });\n controller.enqueue({\n type: 'tool-call',\n toolCallId: requestID,\n toolName: data.name,\n input: parsedArgs,\n providerExecuted: true,\n });\n\n this.executeToolAndRespond(\n ss,\n wsClient,\n controller,\n requestID,\n data.name,\n parsedArgs,\n toolExecutor\n ).catch(() => {});\n break;\n }\n\n case 'builtin-tool-request': {\n const mapped = mapBuiltinTool(event.toolName, event.data);\n const mappedArgs = JSON.stringify(mapped.args);\n\n if (ss.activeTextBlockId) {\n controller.enqueue({ type: 'text-end', id: ss.activeTextBlockId });\n ss.activeTextBlockId = null;\n }\n\n controller.enqueue({\n type: 'tool-input-start',\n id: event.requestID,\n toolName: mapped.toolName,\n providerExecuted: true,\n });\n controller.enqueue({\n type: 'tool-input-delta',\n id: event.requestID,\n delta: mappedArgs,\n });\n controller.enqueue({\n type: 'tool-input-end',\n id: event.requestID,\n });\n controller.enqueue({\n type: 'tool-call',\n toolCallId: event.requestID,\n toolName: mapped.toolName,\n input: mappedArgs,\n providerExecuted: true,\n });\n\n this.executeToolAndRespond(\n ss,\n wsClient,\n controller,\n event.requestID,\n mapped.toolName,\n mappedArgs,\n toolExecutor\n ).catch(() => {});\n break;\n }\n\n case 'completed': {\n if (ss.activeTextBlockId) {\n controller.enqueue({ type: 'text-end', id: ss.activeTextBlockId });\n ss.activeTextBlockId = null;\n }\n\n const doCompleteClose = () => {\n if (ss.streamClosed) return;\n // Approximate token counts (1 token ≈ 4 chars). DWS does not expose\n // actual token usage; these are estimates for AI SDK compatibility only.\n const inputTokens = Math.ceil(ss.streamedInputChars / 4);\n const outputTokens = Math.ceil(ss.streamedOutputChars / 4);\n controller.enqueue({\n type: 'finish',\n finishReason: 'stop',\n usage: { inputTokens, outputTokens, totalTokens: inputTokens + outputTokens },\n });\n ss.streamClosed = true;\n controller.close();\n this.cleanupClient(ss);\n };\n\n if (ss.pendingToolCount > 0) {\n ss.deferredClose = doCompleteClose;\n } else {\n ss.deferredClose = null;\n doCompleteClose();\n }\n break;\n }\n\n case 'failed': {\n if (ss.activeTextBlockId) {\n controller.enqueue({ type: 'text-end', id: ss.activeTextBlockId });\n ss.activeTextBlockId = null;\n }\n controller.enqueue({\n type: 'error',\n error: new GitLabError({\n message: `Workflow failed: ${sanitizeErrorMessage(event.error.message)}`,\n cause: event.error,\n }),\n });\n ss.streamClosed = true;\n controller.close();\n this.cleanupClient(ss, true);\n break;\n }\n\n case 'closed': {\n if (ss.streamClosed) {\n break;\n }\n if (ss.activeTextBlockId) {\n controller.enqueue({ type: 'text-end', id: ss.activeTextBlockId });\n ss.activeTextBlockId = null;\n }\n\n const doClose = () => {\n if (ss.streamClosed) return;\n if (event.code !== 1000) {\n controller.enqueue({\n type: 'error',\n error: new GitLabError({\n message: `WebSocket closed unexpectedly: code=${event.code} reason=${sanitizeErrorMessage(event.reason)}`,\n statusCode: event.code,\n }),\n });\n ss.streamClosed = true;\n controller.close();\n this.cleanupClient(ss, true);\n } else {\n const inTok = Math.ceil(ss.streamedInputChars / 4);\n const outTok = Math.ceil(ss.streamedOutputChars / 4);\n controller.enqueue({\n type: 'finish',\n finishReason: 'stop',\n usage: { inputTokens: inTok, outputTokens: outTok, totalTokens: inTok + outTok },\n });\n ss.streamClosed = true;\n controller.close();\n this.cleanupClient(ss);\n }\n };\n\n if (ss.pendingToolCount > 0) {\n ss.deferredClose = doClose;\n } else {\n ss.deferredClose = null;\n doClose();\n }\n break;\n }\n }\n }\n\n // ---------------------------------------------------------------------------\n // Checkpoint content extraction\n // ---------------------------------------------------------------------------\n\n private processCheckpoint(\n ss: StreamState,\n checkpoint: NewCheckpoint,\n controller: ReadableStreamDefaultController,\n nextTextId: () => string\n ): void {\n if (!checkpoint.checkpoint) {\n if (checkpoint.content) {\n if (!ss.activeTextBlockId) {\n ss.activeTextBlockId = nextTextId();\n controller.enqueue({ type: 'text-start', id: ss.activeTextBlockId });\n }\n controller.enqueue({\n type: 'text-delta',\n id: ss.activeTextBlockId,\n delta: checkpoint.content,\n });\n ss.streamedOutputChars += checkpoint.content.length;\n }\n return;\n }\n\n let parsed: CheckpointData;\n try {\n parsed = JSON.parse(checkpoint.checkpoint);\n } catch (e) {\n return;\n }\n\n const chatLog = parsed.channel_values?.ui_chat_log;\n if (!chatLog || !Array.isArray(chatLog) || chatLog.length === 0) {\n return;\n }\n\n if (\n checkpoint.status !== 'RUNNING' &&\n checkpoint.status !== 'INPUT_REQUIRED' &&\n checkpoint.status !== 'FINISHED' &&\n checkpoint.status !== 'COMPLETED'\n ) {\n return;\n }\n\n for (let i = 0; i < chatLog.length; i++) {\n const entry = chatLog[i] as UiChatLogEntry;\n if (entry.message_type !== 'agent') continue;\n\n const content = entry.content || '';\n const msgId = entry.message_id || `idx-${i}`;\n const emittedLen = ss.agentMessageEmitted.get(msgId) ?? 0;\n\n if (content.length <= emittedLen) continue;\n\n const delta = content.slice(emittedLen);\n const isSameMsg = msgId === ss.currentAgentMessageId;\n\n if (!isSameMsg && ss.activeTextBlockId) {\n controller.enqueue({ type: 'text-end', id: ss.activeTextBlockId });\n ss.activeTextBlockId = null;\n }\n\n if (!ss.activeTextBlockId) {\n ss.activeTextBlockId = nextTextId();\n controller.enqueue({ type: 'text-start', id: ss.activeTextBlockId });\n }\n controller.enqueue({\n type: 'text-delta',\n id: ss.activeTextBlockId,\n delta,\n });\n ss.streamedOutputChars += delta.length;\n\n ss.agentMessageEmitted.set(msgId, content.length);\n this.persistedAgentEmitted.set(msgId, content.length);\n ss.currentAgentMessageId = msgId;\n }\n }\n\n private async executeToolAndRespond(\n ss: StreamState,\n wsClient: GitLabWorkflowClient,\n controller: ReadableStreamDefaultController,\n requestID: string,\n toolName: string,\n argsJson: string,\n toolExecutor: WorkflowToolExecutor | null\n ): Promise {\n ss.pendingToolCount++;\n\n const safeEnqueue = (part: LanguageModelV2StreamPart): void => {\n if (ss.streamClosed) {\n return;\n }\n try {\n controller.enqueue(part);\n } catch {\n // Stream may have been closed between the check and enqueue\n }\n };\n\n try {\n if (toolExecutor) {\n const result = await toolExecutor(toolName, argsJson, requestID);\n wsClient.sendActionResponse(requestID, result.result, result.error);\n\n // Track tool call tokens (args as input, result as output)\n ss.streamedInputChars += argsJson.length;\n ss.streamedOutputChars += result.result.length;\n\n let toolOutput = result.result;\n let toolTitle = `${toolName} result`;\n let toolMetadata: Record = { output: result.result };\n try {\n const parsed = JSON.parse(result.result);\n if (parsed && typeof parsed === 'object' && !Array.isArray(parsed)) {\n if (typeof parsed.output === 'string') {\n toolOutput = parsed.output;\n } else if (parsed.output != null) {\n toolOutput = JSON.stringify(parsed.output);\n }\n if (typeof parsed.title === 'string') toolTitle = parsed.title;\n if (parsed.metadata && typeof parsed.metadata === 'object') {\n toolMetadata = {} as Record;\n for (const [k, v] of Object.entries(parsed.metadata as Record)) {\n toolMetadata[k] = typeof v === 'string' ? v : JSON.stringify(v);\n }\n if (!('output' in toolMetadata)) {\n toolMetadata.output = toolOutput;\n }\n }\n } else if (Array.isArray(parsed)) {\n toolOutput = JSON.stringify(parsed);\n toolMetadata = { output: toolOutput };\n }\n } catch {\n // result is plain text, use as-is\n }\n\n if (result.error) {\n let errorText: string;\n if (typeof result.error === 'string') {\n errorText = result.error;\n } else if (result.error && typeof result.error === 'object') {\n errorText = JSON.stringify(result.error);\n } else {\n errorText = String(result.error);\n }\n const errorOutput = toolOutput || errorText;\n safeEnqueue({\n type: 'tool-result',\n toolCallId: requestID,\n toolName,\n result: {\n output: errorOutput,\n title: toolTitle,\n metadata: { ...toolMetadata, error: errorText },\n },\n isError: true,\n providerExecuted: true,\n });\n } else {\n safeEnqueue({\n type: 'tool-result',\n toolCallId: requestID,\n toolName,\n result: {\n output: toolOutput,\n title: toolTitle,\n metadata: toolMetadata,\n },\n isError: false,\n providerExecuted: true,\n });\n }\n } else {\n const errorMsg = `Tool executor not configured for tool: ${toolName}`;\n wsClient.sendActionResponse(requestID, '', errorMsg);\n\n safeEnqueue({\n type: 'tool-result',\n toolCallId: requestID,\n toolName,\n result: {\n output: errorMsg,\n title: `${toolName} error`,\n metadata: { output: errorMsg },\n },\n isError: true,\n providerExecuted: true,\n });\n }\n } catch (error) {\n const rawMsg = error instanceof Error ? error.message : String(error);\n const errorMsg = sanitizeErrorMessage(rawMsg);\n wsClient.sendActionResponse(requestID, '', errorMsg);\n\n safeEnqueue({\n type: 'tool-result',\n toolCallId: requestID,\n toolName,\n result: {\n output: errorMsg,\n title: `${toolName} error`,\n metadata: { output: errorMsg },\n },\n isError: true,\n providerExecuted: true,\n });\n } finally {\n ss.pendingToolCount--;\n\n if (this.onUsageUpdate) {\n try {\n this.onUsageUpdate({\n inputTokens: Math.ceil(ss.streamedInputChars / 4),\n outputTokens: Math.ceil(ss.streamedOutputChars / 4),\n });\n } catch {\n // ignore callback errors\n }\n }\n\n if (ss.pendingToolCount <= 0 && ss.deferredClose) {\n const close = ss.deferredClose;\n ss.deferredClose = null;\n close();\n }\n }\n }\n\n private cleanupClient(ss: StreamState, clearWorkflow = false): void {\n if (ss.activeClient) {\n ss.activeClient.close();\n this.activeClients.delete(ss.activeClient);\n ss.activeClient = null;\n }\n if (clearWorkflow) {\n this.currentWorkflowId = null;\n this.persistedAgentEmitted.clear();\n }\n }\n\n // ---------------------------------------------------------------------------\n // Workflow metadata\n // ---------------------------------------------------------------------------\n\n private async buildWorkflowMetadata(): Promise> {\n const metadata: Record = {\n extended_logging: false,\n };\n\n try {\n const workDir = this.workflowOptions.workingDirectory ?? process.cwd();\n const gitInfo = await this.getGitInfo(workDir);\n if (gitInfo.url) metadata.git_url = gitInfo.url;\n if (gitInfo.sha) metadata.git_sha = gitInfo.sha;\n if (gitInfo.branch) metadata.git_branch = gitInfo.branch;\n } catch {\n // Git info is best-effort\n }\n\n return metadata;\n }\n\n private async getGitInfo(\n workDir: string\n ): Promise<{ url?: string; sha?: string; branch?: string }> {\n const { execFile } = await import('child_process');\n const { promisify } = await import('util');\n const execFileAsync = promisify(execFile);\n const opts = { cwd: workDir, timeout: 3000 };\n\n const run = async (cmd: string, args: string[]): Promise => {\n try {\n const { stdout } = await execFileAsync(cmd, args, opts);\n return stdout.trim() || undefined;\n } catch {\n return undefined;\n }\n };\n\n const [url, sha, branch] = await Promise.all([\n run('git', ['remote', 'get-url', 'origin']),\n run('git', ['rev-parse', 'HEAD']),\n run('git', ['rev-parse', '--abbrev-ref', 'HEAD']),\n ]);\n\n return { url, sha, branch };\n }\n\n // ---------------------------------------------------------------------------\n // Prompt / tool extraction helpers\n // ---------------------------------------------------------------------------\n\n /**\n * Extract the user's goal (last user message) from the AI SDK prompt.\n */\n private extractGoalFromPrompt(prompt: LanguageModelV2Message[]): string {\n for (let i = prompt.length - 1; i >= 0; i--) {\n const message = prompt[i];\n if (message.role === 'user') {\n const textParts = message.content\n .filter((part) => part.type === 'text')\n .map((part) => (part as { type: 'text'; text: string }).text);\n if (textParts.length > 0) {\n return textParts.join('\\n');\n }\n }\n }\n return '';\n }\n\n /**\n * Convert AI SDK tools to DWS McpToolDefinition format.\n */\n private extractMcpTools(options: LanguageModelV2CallOptions): McpToolDefinition[] {\n if (this.workflowOptions.mcpTools && this.workflowOptions.mcpTools.length > 0) {\n return this.workflowOptions.mcpTools;\n }\n\n if (!options.tools || options.tools.length === 0) {\n return [];\n }\n\n return options.tools\n .filter((tool): tool is LanguageModelV2FunctionTool => tool.type === 'function')\n .map((tool) => ({\n name: tool.name,\n description: tool.description || '',\n inputSchema: JSON.stringify(tool.inputSchema || { type: 'object', properties: {} }),\n }));\n }\n\n // ---------------------------------------------------------------------------\n // Payload size management\n // ---------------------------------------------------------------------------\n\n private static readonly MAX_START_REQUEST_BYTES = 4 * 1024 * 1024;\n\n /**\n * Trim mcpTools and additionalContext to fit within the DWS 4MB gRPC\n * message size limit (`MAX_MESSAGE_SIZE` in duo_workflow_service/server.py).\n *\n * DWS has no per-field limits on tool descriptions, schemas, or context items.\n * The only hard constraint is the total serialized message size.\n *\n * Strategy (progressive, only if over budget):\n * 1. Send everything as-is\n * 2. Simplify tool input schemas (strip descriptions from properties)\n * 3. Strip schemas to minimal form (type + property names only)\n * 4. Drop tools from the end until it fits\n */\n private trimPayload(\n mcpTools: McpToolDefinition[],\n additionalContext: AdditionalContext[],\n basePayloadSize: number\n ): { mcpTools: McpToolDefinition[]; additionalContext: AdditionalContext[] } {\n const budget = GitLabWorkflowLanguageModel.MAX_START_REQUEST_BYTES - basePayloadSize;\n const contextJson = JSON.stringify(additionalContext);\n\n const toolsJson = JSON.stringify(mcpTools);\n const totalSize = toolsJson.length + contextJson.length;\n\n if (totalSize <= budget) {\n return { mcpTools, additionalContext };\n }\n\n const simplifiedTools = mcpTools.map((tool) => ({\n name: tool.name,\n description: tool.description,\n inputSchema: simplifySchema(tool.inputSchema),\n }));\n\n const simpSize = JSON.stringify(simplifiedTools).length + contextJson.length;\n if (simpSize <= budget) {\n return { mcpTools: simplifiedTools, additionalContext };\n }\n\n const minTools = simplifiedTools.map((tool) => ({\n name: tool.name,\n description: tool.description,\n inputSchema: minimalSchema(tool.inputSchema),\n }));\n\n const minSize = JSON.stringify(minTools).length + contextJson.length;\n if (minSize <= budget) {\n return { mcpTools: minTools, additionalContext };\n }\n\n const keptTools = [...minTools];\n while (keptTools.length > 0) {\n const currentSize = JSON.stringify(keptTools).length + contextJson.length;\n if (currentSize <= budget) break;\n keptTools.pop();\n }\n\n return { mcpTools: keptTools, additionalContext };\n }\n\n private buildAdditionalContext(prompt: LanguageModelV2Message[]): AdditionalContext[] {\n const context: AdditionalContext[] = [];\n\n if (this.workflowOptions.additionalContext) {\n context.push(...this.workflowOptions.additionalContext);\n }\n\n for (const message of prompt) {\n if (message.role === 'system') {\n context.push({\n category: 'system_prompt',\n content: message.content,\n metadata: JSON.stringify({ role: 'system' }),\n });\n } else if (message.role === 'assistant') {\n const textContent = message.content\n .filter((part) => part.type === 'text')\n .map((part) => (part as { type: 'text'; text: string }).text)\n .join('\\n');\n if (textContent) {\n context.push({\n category: 'conversation',\n content: textContent,\n metadata: JSON.stringify({ role: 'assistant' }),\n });\n }\n }\n }\n\n return context;\n }\n}\n","/**\n * OAuth types and constants for GitLab authentication\n * Based on gitlab-vscode-extension and gitlab-lsp patterns\n */\n\nexport interface GitLabOAuthTokens {\n accessToken: string;\n refreshToken: string;\n expiresAt: number; // Unix timestamp in milliseconds\n instanceUrl: string;\n}\n\nexport interface OpenCodeAuthOAuth {\n type: 'oauth';\n refresh: string;\n access: string;\n expires: number; // Unix timestamp in milliseconds\n /** @deprecated Use enterpriseUrl instead. Kept for backwards compatibility with older auth.json files. */\n instanceUrl?: string;\n /** Instance URL as written by opencode-gitlab-auth plugin (e.g. 'https://gitlab.com') */\n enterpriseUrl?: string;\n}\n\nexport interface OpenCodeAuthApi {\n type: 'api';\n key: string;\n}\n\nexport type OpenCodeAuth = OpenCodeAuthOAuth | OpenCodeAuthApi;\n\n/**\n * Default OAuth client ID for GitLab.com\n * This is the same client ID used by opencode-gitlab-auth plugin.\n * The GITLAB_OAUTH_CLIENT_ID env var takes precedence if set.\n * Note: VS Code extension uses a different client ID ('36f2a70c...') but we use the opencode plugin's ID\n * to ensure token refresh works correctly with tokens created by the auth plugin.\n */\nexport const OPENCODE_GITLAB_AUTH_CLIENT_ID =\n '1d89f9fdb23ee96d4e603201f6861dab6e143c5c3c00469a018a2d94bdc03d4e';\n\n/**\n * @deprecated Use OPENCODE_GITLAB_AUTH_CLIENT_ID instead. This is the VS Code extension's client ID\n * and will cause refresh failures if used with tokens created by opencode-gitlab-auth.\n */\nexport const BUNDLED_CLIENT_ID = '36f2a70cddeb5a0889d4fd8295c241b7e9848e89cf9e599d0eed2d8e5350fbf5';\n\n/**\n * GitLab.com URL constant\n */\nexport const GITLAB_COM_URL = 'https://gitlab.com';\n\n/**\n * Token expiry skew in milliseconds (5 minutes)\n * Refresh tokens this many milliseconds before they expire\n */\nexport const TOKEN_EXPIRY_SKEW_MS = 5 * 60 * 1000;\n\n/**\n * OAuth scopes to request\n */\nexport const OAUTH_SCOPES = ['api'];\n","/**\n * GitLab OAuth Manager\n * Handles OAuth token management, refresh, and exchange\n * Based on gitlab-vscode-extension TokenExchangeService and gitlab-lsp OAuthClientProvider\n */\n\nimport { GitLabError } from './gitlab-error';\nimport type { GitLabOAuthTokenResponse } from './gitlab-api-types';\nimport {\n type GitLabOAuthTokens,\n TOKEN_EXPIRY_SKEW_MS,\n OPENCODE_GITLAB_AUTH_CLIENT_ID,\n GITLAB_COM_URL,\n} from './gitlab-oauth-types';\n\nexport interface TokenExchangeParams {\n instanceUrl: string;\n clientId?: string;\n redirectUri?: string;\n}\n\nexport interface AuthorizationCodeParams extends TokenExchangeParams {\n code: string;\n codeVerifier: string;\n}\n\nexport interface RefreshTokenParams extends TokenExchangeParams {\n refreshToken: string;\n}\n\nexport class GitLabOAuthManager {\n private fetch: typeof fetch;\n\n constructor(fetchImpl: typeof fetch = fetch) {\n this.fetch = fetchImpl;\n }\n\n /**\n * Check if a token is expired\n */\n isTokenExpired(expiresAt: number): boolean {\n return Date.now() >= expiresAt;\n }\n\n /**\n * Check if a token needs refresh (within skew window)\n */\n needsRefresh(expiresAt: number): boolean {\n return Date.now() >= expiresAt - TOKEN_EXPIRY_SKEW_MS;\n }\n\n /**\n * Refresh tokens if needed\n * Returns the same tokens if refresh is not needed, or new tokens if refreshed\n */\n async refreshIfNeeded(tokens: GitLabOAuthTokens, clientId?: string): Promise {\n if (!this.needsRefresh(tokens.expiresAt)) {\n return tokens;\n }\n\n if (this.isTokenExpired(tokens.expiresAt)) {\n throw new GitLabError({\n message: 'OAuth token has expired and cannot be used',\n });\n }\n\n return this.exchangeRefreshToken({\n instanceUrl: tokens.instanceUrl,\n refreshToken: tokens.refreshToken,\n clientId,\n });\n }\n\n /**\n * Exchange authorization code for tokens\n * Based on gitlab-vscode-extension createOAuthAccountFromCode\n */\n async exchangeAuthorizationCode(params: AuthorizationCodeParams): Promise {\n const { instanceUrl, code, codeVerifier, clientId, redirectUri } = params;\n\n const tokenResponse = await this.exchangeToken({\n instanceUrl,\n grantType: 'authorization_code',\n code,\n codeVerifier,\n clientId: clientId || this.getClientId(instanceUrl),\n redirectUri,\n });\n\n return this.createTokensFromResponse(tokenResponse, instanceUrl);\n }\n\n /**\n * Exchange refresh token for new tokens\n * Based on gitlab-vscode-extension TokenExchangeService\n */\n async exchangeRefreshToken(params: RefreshTokenParams): Promise {\n const { instanceUrl, refreshToken, clientId } = params;\n\n const tokenResponse = await this.exchangeToken({\n instanceUrl,\n grantType: 'refresh_token',\n refreshToken,\n clientId: clientId || this.getClientId(instanceUrl),\n });\n\n return this.createTokensFromResponse(tokenResponse, instanceUrl);\n }\n\n /**\n * Get the OAuth client ID for an instance.\n * Priority: env var > opencode-gitlab-auth default (for GitLab.com).\n * Note: callers (e.g. exchangeRefreshToken) may pass an explicit clientId\n * that bypasses this method entirely.\n */\n private getClientId(instanceUrl: string): string {\n // Priority 1: Environment variable (allows overriding at runtime)\n const envClientId = process.env['GITLAB_OAUTH_CLIENT_ID'];\n if (envClientId) {\n return envClientId;\n }\n\n // Priority 2: Use opencode-gitlab-auth's client ID for GitLab.com\n // This ensures refresh works with tokens created by the auth plugin\n if (instanceUrl === GITLAB_COM_URL) {\n return OPENCODE_GITLAB_AUTH_CLIENT_ID;\n }\n\n throw new GitLabError({\n message: `No OAuth client ID configured for instance ${instanceUrl}. Please provide a clientId parameter or set GITLAB_OAUTH_CLIENT_ID environment variable.`,\n });\n }\n\n /**\n * Exchange token with GitLab OAuth endpoint\n * Based on gitlab-vscode-extension GitLabService.exchangeToken\n */\n private async exchangeToken(params: {\n instanceUrl: string;\n grantType: 'authorization_code' | 'refresh_token';\n code?: string;\n codeVerifier?: string;\n refreshToken?: string;\n clientId: string;\n redirectUri?: string;\n }): Promise {\n const { instanceUrl, grantType, code, codeVerifier, refreshToken, clientId, redirectUri } =\n params;\n\n const body: Record = {\n client_id: clientId,\n grant_type: grantType,\n };\n\n if (grantType === 'authorization_code') {\n if (!code || !codeVerifier || !redirectUri) {\n throw new GitLabError({\n message:\n 'Authorization code, code verifier, and redirect URI are required for authorization_code grant',\n });\n }\n body.code = code;\n body.code_verifier = codeVerifier;\n body.redirect_uri = redirectUri;\n } else if (grantType === 'refresh_token') {\n if (!refreshToken) {\n throw new GitLabError({\n message: 'Refresh token is required for refresh_token grant',\n });\n }\n body.refresh_token = refreshToken;\n }\n\n const url = `${instanceUrl}/oauth/token`;\n\n try {\n const response = await this.fetch(url, {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/x-www-form-urlencoded',\n },\n body: new URLSearchParams(body).toString(),\n });\n\n if (!response.ok) {\n const errorText = await response.text();\n throw new GitLabError({\n message: `OAuth token exchange failed: ${response.status} ${response.statusText}`,\n cause: new Error(errorText),\n });\n }\n\n const data = await response.json();\n return data as GitLabOAuthTokenResponse;\n } catch (error) {\n if (error instanceof GitLabError) {\n throw error;\n }\n throw new GitLabError({\n message: `Failed to exchange OAuth token: ${error instanceof Error ? error.message : String(error)}`,\n cause: error instanceof Error ? error : undefined,\n });\n }\n }\n\n /**\n * Create GitLabOAuthTokens from token response\n */\n private createTokensFromResponse(\n response: GitLabOAuthTokenResponse,\n instanceUrl: string\n ): GitLabOAuthTokens {\n const expiresAt = this.createExpiresTimestamp(response);\n\n return {\n accessToken: response.access_token,\n refreshToken: response.refresh_token || '',\n expiresAt,\n instanceUrl,\n };\n }\n\n /**\n * Create expiry timestamp from token response\n * Based on gitlab-vscode-extension createExpiresTimestamp\n */\n private createExpiresTimestamp(response: GitLabOAuthTokenResponse): number {\n // GitLab returns created_at (Unix timestamp in seconds) and expires_in (seconds)\n const createdAt = response.created_at * 1000; // Convert to milliseconds\n const expiresIn = response.expires_in * 1000; // Convert to milliseconds\n return createdAt + expiresIn;\n }\n}\n","import { GitLabAnthropicLanguageModel } from './gitlab-anthropic-language-model';\nimport { GitLabOpenAILanguageModel } from './gitlab-openai-language-model';\nimport { GitLabWorkflowLanguageModel } from './gitlab-workflow-language-model';\nimport { GitLabError } from './gitlab-error';\nimport type { LanguageModelV2 } from '@ai-sdk/provider';\nimport { GitLabOAuthManager } from './gitlab-oauth-manager';\nimport type { OpenCodeAuth } from './gitlab-oauth-types';\nimport { getModelMapping, getValidModelsForProvider, isWorkflowModel } from './model-mappings';\nimport type { GitLabWorkflowOptions } from './gitlab-workflow-types';\nimport { VERSION } from './version';\nimport * as fs from 'fs';\nimport * as path from 'path';\nimport * as os from 'os';\n\nexport interface GitLabProvider {\n (modelId: string): LanguageModelV2;\n readonly specificationVersion: 'v2';\n languageModel(modelId: string): LanguageModelV2;\n chat(modelId: string): LanguageModelV2;\n /**\n * Create an agentic chat model with tool calling support\n *\n * @param modelId - GitLab model identifier. Some IDs automatically map to specific Anthropic models.\n * @param options - Configuration options for the agentic model\n * @returns A language model with native tool calling support via Anthropic\n *\n * @example\n * // Automatic model mapping\n * const model = gitlab.agenticChat('duo-chat-opus-4-5');\n * // Uses claude-opus-4-5-20251101\n *\n * @example\n * // Explicit model override\n * const model = gitlab.agenticChat('duo-chat', {\n * anthropicModel: 'claude-sonnet-4-5-20250929'\n * });\n */\n agenticChat(modelId: string, options?: GitLabAgenticOptions): GitLabAnthropicLanguageModel;\n /**\n * Create a workflow chat model using GitLab Duo Agent Platform.\n *\n * Workflow models use a server-side agentic loop where GitLab's DWS drives\n * the LLM, requests tool executions from the client via WebSocket, and\n * streams text/status back.\n *\n * Requires GitLab Ultimate with Duo Enterprise add-on.\n *\n * @param modelId - Workflow model identifier (e.g., 'duo-workflow-sonnet-4-6')\n * @param options - Workflow-specific configuration\n * @returns A language model backed by the DWS WebSocket protocol\n *\n * @example\n * const model = gitlab.workflowChat('duo-workflow-sonnet-4-6', {\n * mcpTools: [...],\n * preapprovedTools: ['read_file', 'write_file'],\n * });\n */\n workflowChat(modelId: string, options?: GitLabWorkflowOptions): GitLabWorkflowLanguageModel;\n textEmbeddingModel(modelId: string): never;\n imageModel(modelId: string): never;\n}\n\nexport interface GitLabAgenticOptions {\n /**\n * Override the provider-specific model (optional).\n * Must be a valid model for the detected provider.\n *\n * For Anthropic models:\n * - 'claude-opus-4-6'\n * - 'claude-sonnet-4-6'\n * - 'claude-opus-4-5-20251101'\n * - 'claude-sonnet-4-5-20250929'\n * - 'claude-haiku-4-5-20251001'\n *\n * For OpenAI models:\n * - 'gpt-5.1-2025-11-13'\n * - 'gpt-5-mini-2025-08-07'\n * - 'gpt-5-codex'\n * - 'gpt-5.2-codex'\n *\n * @example\n * // Override with explicit model\n * const model = gitlab.agenticChat('duo-chat-opus-4-5', {\n * providerModel: 'claude-sonnet-4-5-20250929'\n * });\n */\n providerModel?: string;\n\n /**\n * Maximum tokens to generate\n * @default 8192\n */\n maxTokens?: number;\n\n /**\n * Feature flags to pass to the GitLab API\n */\n featureFlags?: Record;\n\n /**\n * Custom headers for AI Gateway requests (per-model override).\n * These headers are sent to the Anthropic/OpenAI proxy endpoints.\n * Merged with provider-level aiGatewayHeaders (model-level takes precedence).\n */\n aiGatewayHeaders?: Record;\n}\n\nexport interface GitLabProviderSettings {\n /**\n * GitLab instance URL (e.g., 'https://gitlab.com')\n * Can also be set via GITLAB_INSTANCE_URL environment variable.\n * @default 'https://gitlab.com'\n */\n instanceUrl?: string;\n\n /**\n * API token (Personal Access Token or OAuth access token)\n * Can also be set via GITLAB_TOKEN environment variable\n */\n apiKey?: string;\n\n /**\n * OAuth refresh token (optional, for OAuth flow)\n */\n refreshToken?: string;\n\n /**\n * OAuth client ID (required for OAuth flow)\n */\n clientId?: string;\n\n /**\n * OAuth redirect URI (required for OAuth flow)\n */\n redirectUri?: string;\n\n /**\n * Custom headers to include in requests\n */\n headers?: Record;\n\n /**\n * Custom fetch implementation\n */\n fetch?: typeof fetch;\n\n /**\n * Provider name override\n */\n name?: string;\n\n /**\n * Default feature flags to pass to the GitLab API for all agentic chat models\n */\n featureFlags?: Record;\n\n /**\n * AI Gateway URL for the Anthropic proxy.\n * Can also be set via GITLAB_AI_GATEWAY_URL environment variable.\n * @default 'https://cloud.gitlab.com'\n */\n aiGatewayUrl?: string;\n\n /**\n * Custom headers to include in AI Gateway requests (Anthropic/OpenAI proxy).\n * These headers are merged with the default headers from direct_access response.\n * Default User-Agent: gitlab-ai-provider/{version}\n */\n aiGatewayHeaders?: Record;\n}\n\n/**\n * Get OpenCode auth file path\n * Uses XDG Base Directory specification\n */\nfunction getOpenCodeAuthPath(): string {\n const homeDir = os.homedir();\n\n // Check XDG_DATA_HOME first (Linux/Mac standard)\n const xdgDataHome = process.env.XDG_DATA_HOME;\n if (xdgDataHome) {\n return path.join(xdgDataHome, 'opencode', 'auth.json');\n }\n\n // Fallback to ~/.local/share/opencode/auth.json (XDG default)\n if (process.platform !== 'win32') {\n return path.join(homeDir, '.local', 'share', 'opencode', 'auth.json');\n }\n\n // Windows fallback\n return path.join(homeDir, '.opencode', 'auth.json');\n}\n\n/**\n * Load OpenCode auth.json file\n */\nasync function loadOpenCodeAuth(instanceUrl: string): Promise {\n try {\n const authPath = getOpenCodeAuthPath();\n\n if (!fs.existsSync(authPath)) {\n return undefined;\n }\n\n const authData = JSON.parse(fs.readFileSync(authPath, 'utf-8'));\n\n // Priority 1: Check 'gitlab' key (used by opencode-gitlab-auth plugin)\n if (authData.gitlab?.type === 'oauth') {\n const gitlabAuth = authData.gitlab;\n // Verify it matches the requested instance URL\n if (\n gitlabAuth.enterpriseUrl === instanceUrl ||\n gitlabAuth.enterpriseUrl === instanceUrl.replace(/\\/$/, '')\n ) {\n return gitlabAuth as OpenCodeAuth;\n }\n }\n\n // Priority 2: Try to find auth for this instance by URL\n // Check both with and without trailing slash\n const normalizedUrl = instanceUrl.replace(/\\/$/, '');\n const auth = authData[normalizedUrl] || authData[`${normalizedUrl}/`];\n\n return auth as OpenCodeAuth | undefined;\n } catch (error) {\n throw new Error(`Failed to load auth.json: ${error instanceof Error ? error.message : error}`);\n }\n}\n\n/**\n * Load GitLab API key with OAuth support\n * Priority: explicit apiKey > OAuth token > env var\n */\nasync function loadApiKey(\n options: {\n apiKey?: string;\n environmentVariableName: string;\n description: string;\n },\n instanceUrl: string,\n clientId?: string\n): Promise {\n // Priority 1: Explicit apiKey\n if (options.apiKey) {\n return options.apiKey;\n }\n\n // Priority 2: OAuth token from OpenCode auth.json\n const auth = await loadOpenCodeAuth(instanceUrl);\n if (auth?.type === 'oauth') {\n const oauthManager = new GitLabOAuthManager();\n\n // Check if token needs refresh\n if (oauthManager.needsRefresh(auth.expires)) {\n try {\n const refreshed = await oauthManager.exchangeRefreshToken({\n instanceUrl,\n refreshToken: auth.refresh,\n clientId,\n });\n\n // Update stored token under 'gitlab' key (same format as opencode-gitlab-auth plugin)\n const authPath = getOpenCodeAuthPath();\n const authData = JSON.parse(fs.readFileSync(authPath, 'utf-8'));\n\n authData.gitlab = {\n type: 'oauth',\n refresh: refreshed.refreshToken,\n access: refreshed.accessToken,\n expires: refreshed.expiresAt,\n enterpriseUrl: instanceUrl, // Use enterpriseUrl to match auth plugin format\n };\n\n fs.writeFileSync(authPath, JSON.stringify(authData, null, 2), { mode: 0o600 });\n\n return refreshed.accessToken;\n } catch (error) {\n // If refresh fails, fall through to env var but remember the error\n const refreshErrorMsg = error instanceof Error ? error.message : String(error);\n // Silently handle refresh failure — avoid stdout output that interferes with TUI\n\n // Priority 3: Environment variable (fallback when refresh fails)\n const envApiKey = process.env[options.environmentVariableName];\n if (envApiKey) {\n return envApiKey;\n }\n\n // No env var fallback — throw with the refresh failure context\n throw new GitLabError({\n message:\n `OAuth token refresh failed and no fallback ${options.environmentVariableName} environment variable is set. ` +\n `Refresh error: ${refreshErrorMsg}. ` +\n `Re-authenticate with 'opencode auth login gitlab' or set ${options.environmentVariableName}.`,\n });\n }\n } else {\n return auth.access;\n }\n }\n\n // Priority 3: Environment variable\n const apiKey = process.env[options.environmentVariableName];\n\n if (!apiKey) {\n throw new GitLabError({\n message: `${options.description} API key is missing. Pass it as the 'apiKey' parameter, set the ${options.environmentVariableName} environment variable, or authenticate with 'opencode auth login gitlab'.`,\n });\n }\n\n return apiKey;\n}\n\nfunction withUserAgentSuffix(\n headers: Record,\n suffix: string\n): Record {\n const userAgent = headers['User-Agent'];\n return {\n ...headers,\n 'User-Agent': userAgent ? `${userAgent} ${suffix}` : suffix,\n };\n}\n\nexport function createGitLab(options: GitLabProviderSettings = {}): GitLabProvider {\n const instanceUrl =\n options.instanceUrl ?? process.env['GITLAB_INSTANCE_URL'] ?? 'https://gitlab.com';\n const providerName = options.name ?? 'gitlab';\n\n // Cache for the API key - loaded lazily on first use\n let cachedApiKey: string | undefined;\n let apiKeyPromise: Promise | undefined;\n\n const getApiKey = async (): Promise => {\n if (cachedApiKey) {\n return cachedApiKey;\n }\n\n if (apiKeyPromise) {\n return apiKeyPromise;\n }\n\n apiKeyPromise = loadApiKey(\n {\n apiKey: options.apiKey,\n environmentVariableName: 'GITLAB_TOKEN',\n description: 'GitLab',\n },\n instanceUrl,\n options.clientId\n );\n\n cachedApiKey = await apiKeyPromise;\n apiKeyPromise = undefined;\n return cachedApiKey;\n };\n\n /**\n * Refresh the API key by clearing the cache and re-fetching from auth provider.\n * This is called when a 401 error occurs to trigger OAuth token refresh.\n */\n const refreshApiKey = async (): Promise => {\n // Clear the cached API key to force a refresh\n cachedApiKey = undefined;\n apiKeyPromise = undefined;\n\n // Re-fetch the API key, but don't pass the stale options.apiKey\n // This forces loadApiKey to read from auth.json and potentially refresh the OAuth token\n cachedApiKey = await loadApiKey(\n {\n apiKey: undefined, // Bypass stale options.apiKey to force auth.json read\n environmentVariableName: 'GITLAB_TOKEN',\n description: 'GitLab',\n },\n instanceUrl,\n options.clientId\n );\n };\n\n const getHeaders = () => {\n // For synchronous access, we need to have the key already loaded\n // or fall back to env var/explicit key\n const apiKey = cachedApiKey || options.apiKey || process.env['GITLAB_TOKEN'] || '';\n\n if (!apiKey) {\n throw new GitLabError({\n message:\n \"GitLab API key is missing. Pass it as the 'apiKey' parameter, set the GITLAB_TOKEN environment variable, or authenticate with 'opencode auth login gitlab'.\",\n });\n }\n\n return withUserAgentSuffix(\n {\n Authorization: `Bearer ${apiKey}`,\n 'Content-Type': 'application/json',\n ...options.headers,\n },\n `ai-sdk-gitlab/${VERSION}`\n );\n };\n\n // Pre-load the API key asynchronously\n getApiKey().catch(() => {\n // Silently fail - will be caught when getHeaders is called\n });\n\n const createAgenticChatModel = (modelId: string, agenticOptions?: GitLabAgenticOptions) => {\n const mapping = getModelMapping(modelId);\n\n if (!mapping) {\n throw new GitLabError({\n message: `Unknown model ID: ${modelId}. Model must be registered in MODEL_MAPPINGS.`,\n });\n }\n\n if (agenticOptions?.providerModel) {\n const validModels = getValidModelsForProvider(mapping.provider);\n if (!validModels.includes(agenticOptions.providerModel)) {\n throw new GitLabError({\n message: `Invalid providerModel '${agenticOptions.providerModel}' for provider '${mapping.provider}'. 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Model ID: ${modelId}`,\n });\n };\n\n provider.imageModel = (modelId: string) => {\n throw new GitLabError({\n message: `GitLab provider does not support image models. Model ID: ${modelId}`,\n });\n };\n\n return provider;\n}\n\n/**\n * Default GitLab Duo provider instance\n *\n * @example\n * ```typescript\n * import { gitlab } from '@ai-sdk/gitlab';\n *\n * const model = gitlab('duo-chat');\n * ```\n */\nexport const gitlab = 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