import { BaseExecutor } from "./base.js"; import { PROVIDERS } from "../config/constants.js"; import { v4 as uuidv4 } from "uuid"; import { refreshKiroToken } from "../services/tokenRefresh.js"; /** * KiroExecutor - Executor for Kiro AI (AWS CodeWhisperer) * Uses AWS CodeWhisperer streaming API with AWS EventStream binary format */ export class KiroExecutor extends BaseExecutor { constructor() { super("kiro", PROVIDERS.kiro); } buildHeaders(credentials, stream = true) { const headers = { ...this.config.headers, "Amz-Sdk-Request": "attempt=1; max=3", "Amz-Sdk-Invocation-Id": uuidv4() }; if (credentials.accessToken) { headers["Authorization"] = `Bearer ${credentials.accessToken}`; } return headers; } transformRequest(model, body, stream, credentials) { return body; } /** * Custom execute for Kiro - handles AWS EventStream binary response */ async execute({ model, body, stream, credentials, signal, log }) { const url = this.buildUrl(model, stream, 0); const headers = this.buildHeaders(credentials, stream); const transformedBody = this.transformRequest(model, body, stream, credentials); const response = await fetch(url, { method: "POST", headers, body: JSON.stringify(transformedBody), signal }); if (!response.ok) { return { response, url, headers, transformedBody }; } // For Kiro, we need to transform the binary EventStream to SSE // Create a TransformStream to convert binary to SSE text const transformedResponse = this.transformEventStreamToSSE(response, model); return { response: transformedResponse, url, headers, transformedBody }; } /** * Transform AWS EventStream binary response to SSE text stream * Using TransformStream instead of ReadableStream.pull() to avoid Workers timeout */ transformEventStreamToSSE(response, model) { let buffer = new Uint8Array(0); let chunkIndex = 0; const responseId = `chatcmpl-${Date.now()}`; const created = Math.floor(Date.now() / 1000); const state = { endDetected: false, finishEmitted: false, hasToolCalls: false, toolCallIndex: 0, seenToolIds: new Map() }; const transformStream = new TransformStream({ async transform(chunk, controller) { // Append to buffer const newBuffer = new Uint8Array(buffer.length + chunk.length); newBuffer.set(buffer); newBuffer.set(chunk, buffer.length); buffer = newBuffer; // Parse events from buffer let iterations = 0; const maxIterations = 1000; while (buffer.length >= 16 && iterations < maxIterations) { iterations++; const view = new DataView(buffer.buffer, buffer.byteOffset); const totalLength = view.getUint32(0, false); if (totalLength < 16 || totalLength > buffer.length || buffer.length < totalLength) break; const eventData = buffer.slice(0, totalLength); buffer = buffer.slice(totalLength); const event = parseEventFrame(eventData); if (!event) continue; const eventType = event.headers[":event-type"] || ""; // Track total content length for token estimation if (!state.totalContentLength) state.totalContentLength = 0; if (!state.contextUsagePercentage) state.contextUsagePercentage = 0; // Handle assistantResponseEvent if (eventType === "assistantResponseEvent" && event.payload?.content) { const content = event.payload.content; state.totalContentLength += content.length; const chunk = { id: responseId, object: "chat.completion.chunk", created, model, choices: [{ index: 0, delta: chunkIndex === 0 ? { role: "assistant", content } : { content }, finish_reason: null }] }; chunkIndex++; controller.enqueue(new TextEncoder().encode(`data: ${JSON.stringify(chunk)}\n\n`)); } // Handle codeEvent if (eventType === "codeEvent" && event.payload?.content) { const chunk = { id: responseId, object: "chat.completion.chunk", created, model, choices: [{ index: 0, delta: { content: event.payload.content }, finish_reason: null }] }; chunkIndex++; controller.enqueue(new TextEncoder().encode(`data: ${JSON.stringify(chunk)}\n\n`)); } // Handle toolUseEvent if (eventType === "toolUseEvent" && event.payload) { state.hasToolCalls = true; const toolUse = event.payload; const toolUses = Array.isArray(toolUse) ? toolUse : [toolUse]; for (const singleToolUse of toolUses) { const toolCallId = singleToolUse.toolUseId || `call_${Date.now()}`; const toolName = singleToolUse.name || ""; const toolInput = singleToolUse.input; let toolIndex; const isNewTool = !state.seenToolIds.has(toolCallId); if (isNewTool) { toolIndex = state.toolCallIndex++; state.seenToolIds.set(toolCallId, toolIndex); const startChunk = { id: responseId, object: "chat.completion.chunk", created, model, choices: [{ index: 0, delta: { ...(chunkIndex === 0 ? { role: "assistant" } : {}), tool_calls: [{ index: toolIndex, id: toolCallId, type: "function", function: { name: toolName, arguments: "" } }] }, finish_reason: null }] }; chunkIndex++; controller.enqueue(new TextEncoder().encode(`data: ${JSON.stringify(startChunk)}\n\n`)); } else { toolIndex = state.seenToolIds.get(toolCallId); } if (toolInput !== undefined) { let argumentsStr; if (typeof toolInput === 'string') { argumentsStr = toolInput; } else if (typeof toolInput === 'object') { argumentsStr = JSON.stringify(toolInput); } else { continue; } const argsChunk = { id: responseId, object: "chat.completion.chunk", created, model, choices: [{ index: 0, delta: { tool_calls: [{ index: toolIndex, function: { arguments: argumentsStr } }] }, finish_reason: null }] }; chunkIndex++; controller.enqueue(new TextEncoder().encode(`data: ${JSON.stringify(argsChunk)}\n\n`)); } } } // Handle messageStopEvent if (eventType === "messageStopEvent") { const chunk = { id: responseId, object: "chat.completion.chunk", created, model, choices: [{ index: 0, delta: {}, finish_reason: state.hasToolCalls ? "tool_calls" : "stop" }] }; state.finishEmitted = true; controller.enqueue(new TextEncoder().encode(`data: ${JSON.stringify(chunk)}\n\n`)); } // Handle contextUsageEvent to extract contextUsagePercentage if (eventType === "contextUsageEvent" && event.payload?.contextUsagePercentage) { state.contextUsagePercentage = event.payload.contextUsagePercentage; // Mark that we received context usage event state.hasContextUsage = true; } // Handle meteringEvent - mark that we received it if (eventType === "meteringEvent") { state.hasMeteringEvent = true; } // Handle metricsEvent for token usage if (eventType === "metricsEvent") { // Extract usage data from metricsEvent payload const metrics = event.payload?.metricsEvent || event.payload; if (metrics && typeof metrics === 'object') { const inputTokens = metrics.inputTokens || 0; const outputTokens = metrics.outputTokens || 0; if (inputTokens > 0 || outputTokens > 0) { state.usage = { prompt_tokens: inputTokens, completion_tokens: outputTokens, total_tokens: inputTokens + outputTokens }; } } } // Emit final chunk only after receiving BOTH meteringEvent AND contextUsageEvent if (state.hasMeteringEvent && state.hasContextUsage && !state.finishEmitted) { state.finishEmitted = true; // Estimate tokens if not available from events if (!state.usage) { // Estimate output tokens from content length const estimatedOutputTokens = state.totalContentLength > 0 ? Math.max(1, Math.floor(state.totalContentLength / 4)) : 0; // Estimate input tokens from contextUsagePercentage // Kiro models typically have 200k context window const estimatedInputTokens = state.contextUsagePercentage > 0 ? Math.floor(state.contextUsagePercentage * 200000 / 100) : 0; state.usage = { prompt_tokens: estimatedInputTokens, completion_tokens: estimatedOutputTokens, total_tokens: estimatedInputTokens + estimatedOutputTokens }; } const finishChunk = { id: responseId, object: "chat.completion.chunk", created, model, choices: [{ index: 0, delta: {}, finish_reason: state.hasToolCalls ? "tool_calls" : "stop" }] }; // Include usage in final chunk if available if (state.usage) { finishChunk.usage = state.usage; } controller.enqueue(new TextEncoder().encode(`data: ${JSON.stringify(finishChunk)}\n\n`)); } } if (iterations >= maxIterations) { console.warn("[Kiro] Max iterations reached in event parsing"); } }, flush(controller) { // Emit finish chunk if not already sent if (!state.finishEmitted) { state.finishEmitted = true; const finishChunk = { id: responseId, object: "chat.completion.chunk", created, model, choices: [{ index: 0, delta: {}, finish_reason: state.hasToolCalls ? "tool_calls" : "stop" }] }; controller.enqueue(new TextEncoder().encode(`data: ${JSON.stringify(finishChunk)}\n\n`)); } // Send final done message controller.enqueue(new TextEncoder().encode("data: [DONE]\n\n")); } }); // Pipe response body through transform stream const transformedStream = response.body.pipeThrough(transformStream); return new Response(transformedStream, { status: response.status, statusText: response.statusText, headers: { "Content-Type": "text/event-stream", "Cache-Control": "no-cache", "Connection": "keep-alive" } }); } async refreshCredentials(credentials, log) { if (!credentials.refreshToken) return null; try { // Use centralized refreshKiroToken function (handles both AWS SSO OIDC and Social Auth) const result = await refreshKiroToken( credentials.refreshToken, credentials.providerSpecificData, log ); return result; } catch (error) { log?.error?.("TOKEN", `Kiro refresh error: ${error.message}`); return null; } } } /** * Parse AWS EventStream frame */ function parseEventFrame(data) { try { const view = new DataView(data.buffer, data.byteOffset); const headersLength = view.getUint32(4, false); // Parse headers const headers = {}; let offset = 12; // After prelude const headerEnd = 12 + headersLength; while (offset < headerEnd && offset < data.length) { const nameLen = data[offset]; offset++; if (offset + nameLen > data.length) break; const name = new TextDecoder().decode(data.slice(offset, offset + nameLen)); offset += nameLen; const headerType = data[offset]; offset++; if (headerType === 7) { // String type const valueLen = (data[offset] << 8) | data[offset + 1]; offset += 2; if (offset + valueLen > data.length) break; const value = new TextDecoder().decode(data.slice(offset, offset + valueLen)); offset += valueLen; headers[name] = value; } else { break; } } // Parse payload const payloadStart = 12 + headersLength; const payloadEnd = data.length - 4; // Exclude message CRC let payload = null; if (payloadEnd > payloadStart) { const payloadStr = new TextDecoder().decode(data.slice(payloadStart, payloadEnd)); // Skip empty or whitespace-only payloads if (!payloadStr || !payloadStr.trim()) { return { headers, payload: null }; } try { payload = JSON.parse(payloadStr); } catch (parseError) { // Log parse error for debugging console.warn(`[Kiro] Failed to parse payload: ${parseError.message} | payload: ${payloadStr.substring(0, 100)}`); payload = { raw: payloadStr }; } } return { headers, payload }; } catch { return null; } } export default KiroExecutor;