- Right-docked chat panel on all workspace pages ([workspace]/layout.tsx) - Streaming SSE responses with Gemini 3.1 Pro preview via generativelanguage API - Full tool-calling loop (up to 6 rounds): deploys apps, lists projects, registers domains, fetches logs — all via existing MCP dispatcher - Persistent conversation history: fs_chat_threads + fs_chat_messages tables (Postgres) - Thread management: create, list, rename (auto-title from first message), delete - Panel collapses to a tab; open state persisted to localStorage - Read-only mode hint when no MCP token is present - Graceful content margin shift when panel is open Made-with: Cursor
219 lines
7.5 KiB
TypeScript
219 lines
7.5 KiB
TypeScript
/**
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* POST /api/chat
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*
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* Streaming chat endpoint. Accepts a thread_id + user message,
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* loads history, calls Gemini 3.1 Pro, runs the tool loop,
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* persists messages, and streams SSE back to the client.
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*
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* SSE event shapes:
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* data: {"type":"text","text":"..."}
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* data: {"type":"tool_start","name":"...","args":{}}
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* data: {"type":"tool_result","name":"...","result":"..."}
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* data: {"type":"done"}
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* data: {"type":"error","error":"..."}
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*/
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import { NextResponse } from 'next/server';
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import { authSession } from '@/lib/auth/session-server';
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import { query } from '@/lib/db-postgres';
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import { streamGeminiChat } from '@/lib/ai/gemini-chat';
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import { VIBN_TOOL_DEFINITIONS, executeMcpTool } from '@/lib/ai/vibn-tools';
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import type { ChatMessage, ToolCall } from '@/lib/ai/gemini-chat';
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const MAX_TOOL_ROUNDS = 6;
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function buildSystemPrompt(projects: any[], workspace: string): string {
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const projectsText = projects.length
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? projects
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.map(
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(p: any) =>
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`- "${p.productName || p.name}" (id: ${p.id}, status: ${p.status || 'defining'})${p.productVision ? ': ' + p.productVision.slice(0, 120) : ''}`,
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)
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.join('\n')
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: '(no projects yet)';
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return `You are Vibn AI, an expert product and infrastructure assistant embedded in the Vibn platform.
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You are talking to the owner of the "${workspace}" workspace.
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## Current workspace projects
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${projectsText}
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## Your capabilities
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You can take real actions by calling tools:
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- List/inspect projects and deployed apps
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- Deploy new applications from templates (n8n, WordPress, Twenty CRM, etc.) or Docker images
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- Register and manage custom domains
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- View application logs
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- Search available app templates
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## Guidelines
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- Be concise and action-oriented. If the user wants to deploy something, do it — don't just describe how.
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- When deploying, always confirm the app name and domain with the user first unless they've been explicit.
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- After a tool call, summarize what happened in plain language.
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- If a deployment takes time, let the user know it may take a few minutes.
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- Format code, URLs, and technical values in backticks.
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- Today's date: ${new Date().toLocaleDateString('en-US', { weekday: 'long', year: 'numeric', month: 'long', day: 'numeric' })}.`;
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}
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export async function POST(request: Request) {
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const session = await authSession();
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if (!session?.user?.email) {
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return NextResponse.json({ error: 'Unauthorized' }, { status: 401 });
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}
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let body: { thread_id: string; message: string; workspace: string; mcp_token?: string };
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try {
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body = await request.json();
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} catch {
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return NextResponse.json({ error: 'Invalid JSON' }, { status: 400 });
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}
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const { thread_id, message, workspace, mcp_token } = body;
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if (!thread_id || !message?.trim()) {
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return NextResponse.json({ error: 'thread_id and message are required' }, { status: 400 });
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}
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const email = session.user.email;
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// Verify thread belongs to user
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const threads = await query<any>(
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`SELECT id FROM fs_chat_threads WHERE id = $1 AND user_id = $2`,
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[thread_id, email],
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);
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if (!threads.length) {
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return NextResponse.json({ error: 'Thread not found' }, { status: 404 });
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}
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// Load message history (last 40 messages)
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const rows = await query<any>(
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`SELECT data FROM fs_chat_messages WHERE thread_id = $1 ORDER BY created_at DESC LIMIT 40`,
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[thread_id],
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);
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const history: ChatMessage[] = rows.reverse().map((r: any) => r.data);
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// Add user message
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const userMsg: ChatMessage = { role: 'user', content: message.trim() };
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history.push(userMsg);
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await query(
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`INSERT INTO fs_chat_messages (thread_id, user_id, data) VALUES ($1, $2, $3)`,
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[thread_id, email, JSON.stringify(userMsg)],
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);
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// Update thread updatedAt
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await query(
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`UPDATE fs_chat_threads SET updated_at = NOW(), data = data || $2 WHERE id = $1`,
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[thread_id, JSON.stringify({ updatedAt: new Date().toISOString() })],
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);
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// Load projects for system prompt context
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const projectRows = await query<any>(
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`SELECT p.data FROM fs_projects p
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JOIN fs_users u ON u.id = p.user_id
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WHERE u.data->>'email' = $1
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ORDER BY (p.data->>'updatedAt') DESC NULLS LAST LIMIT 20`,
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[email],
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);
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const projects = projectRows.map((r: any) => r.data);
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const systemPrompt = buildSystemPrompt(projects, workspace);
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// Base URL for internal MCP calls
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const host = request.headers.get('host') || 'vibnai.com';
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const proto = host.startsWith('localhost') ? 'http' : 'https';
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const baseUrl = `${proto}://${host}`;
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// Stream response
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const encoder = new TextEncoder();
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const stream = new ReadableStream({
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async start(controller) {
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function emit(chunk: object) {
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controller.enqueue(encoder.encode(`data: ${JSON.stringify(chunk)}\n\n`));
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}
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let messages = [...history];
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let round = 0;
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let assistantText = '';
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const assistantToolCalls: ToolCall[] = [];
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try {
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while (round < MAX_TOOL_ROUNDS) {
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round++;
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let pendingToolCalls: ToolCall[] = [];
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let roundText = '';
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for await (const chunk of streamGeminiChat({
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systemPrompt,
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messages,
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tools: mcp_token ? VIBN_TOOL_DEFINITIONS : [],
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temperature: 0.7,
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})) {
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if (chunk.type === 'text' && chunk.text) {
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roundText += chunk.text;
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assistantText += chunk.text;
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emit({ type: 'text', text: chunk.text });
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} else if (chunk.type === 'tool_call' && chunk.toolCall) {
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pendingToolCalls.push(chunk.toolCall);
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assistantToolCalls.push(chunk.toolCall);
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emit({ type: 'tool_start', name: chunk.toolCall.name, args: chunk.toolCall.args });
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} else if (chunk.type === 'error') {
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emit({ type: 'error', error: chunk.error });
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controller.close();
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return;
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}
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}
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// Save assistant turn
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const assistantMsg: ChatMessage = {
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role: 'assistant',
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content: roundText,
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toolCalls: pendingToolCalls.length ? pendingToolCalls : undefined,
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};
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messages.push(assistantMsg);
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if (!pendingToolCalls.length) break;
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// Execute tool calls
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for (const tc of pendingToolCalls) {
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const result = mcp_token
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? await executeMcpTool(tc.name, tc.args, mcp_token, baseUrl)
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: JSON.stringify({ error: 'No MCP token — read-only mode.' });
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emit({ type: 'tool_result', name: tc.name, result: result.slice(0, 500) });
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const toolMsg: ChatMessage = {
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role: 'tool',
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content: result,
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toolCallId: tc.id,
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toolName: tc.name,
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};
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messages.push(toolMsg);
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}
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}
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// Persist final assistant message
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const finalMsg: ChatMessage = {
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role: 'assistant',
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content: assistantText,
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toolCalls: assistantToolCalls.length ? assistantToolCalls : undefined,
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};
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await query(
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`INSERT INTO fs_chat_messages (thread_id, user_id, data) VALUES ($1, $2, $3)`,
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[thread_id, email, JSON.stringify(finalMsg)],
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);
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emit({ type: 'done' });
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controller.close();
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} catch (e) {
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emit({ type: 'error', error: e instanceof Error ? e.message : String(e) });
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controller.close();
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}
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},
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});
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return new Response(stream, {
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headers: {
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'Content-Type': 'text/event-stream',
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'Cache-Control': 'no-cache',
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Connection: 'keep-alive',
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},
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});
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}
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