feat: initial IQAI multi-model AI dashboard

- Express backend with Replicate API proxy (chat, models, account, search)
- React + Vite + Tailwind frontend with custom Midnight Violet color scheme
- @mention autocomplete to route messages to specific models
- Parallel multi-model queries with model selection in sidebar
- DuckDuckGo web search context injection
- Model manager UI (add/edit/remove Replicate models)
- Per-model system instructions per conversation
- Replicate account info display in sidebar
- Conversation history with local persistence (Zustand)
- Full Docker deployment (backend + nginx-served frontend)
- Montserrat + Poppins fonts

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

backend/routes/chat.js

@@ -0,0 +1,129 @@
+import express from 'express';
+import { loadModels } from './models.js';
+
+const router = express.Router();
+const REPLICATE_BASE = 'https://api.replicate.com/v1';
+
+function buildInput(model, prompt, systemPrompt, extraParams) {
+  const base = { ...model.defaultInput };
+
+  // Inject system prompt if model supports it
+  if (model.systemPromptParam && systemPrompt) {
+    base[model.systemPromptParam] = systemPrompt;
+  }
+
+  // Apply extra params from user
+  if (extraParams) {
+    Object.assign(base, extraParams);
+  }
+
+  base.prompt = prompt;
+  return base;
+}
+
+async function runPrediction(model, input, token) {
+  const url = `${REPLICATE_BASE}/models/${model.owner}/${model.name}/predictions`;
+
+  const response = await fetch(url, {
+    method: 'POST',
+    headers: {
+      'Authorization': `Bearer ${token}`,
+      'Content-Type': 'application/json',
+      'Prefer': 'wait'
+    },
+    body: JSON.stringify({ input })
+  });
+
+  if (!response.ok) {
+    const err = await response.json().catch(() => ({ detail: 'Unknown error' }));
+    throw new Error(err.detail || `HTTP ${response.status}`);
+  }
+
+  return response.json();
+}
+
+function extractOutput(prediction) {
+  const { output } = prediction;
+  if (!output) return '';
+  if (typeof output === 'string') return output;
+  if (Array.isArray(output)) return output.join('');
+  if (typeof output === 'object') return JSON.stringify(output, null, 2);
+  return String(output);
+}
+
+// POST /api/chat - single model call
+router.post('/', async (req, res) => {
+  const token = process.env.REPLICATE_API_TOKEN;
+  if (!token) return res.status(400).json({ error: 'REPLICATE_API_TOKEN not configured' });
+
+  const { modelId, prompt, systemPrompt, searchContext, extraParams } = req.body;
+  if (!modelId || !prompt) return res.status(400).json({ error: 'modelId and prompt are required' });
+
+  try {
+    const models = await loadModels();
+    const model = models.find(m => m.id === modelId);
+    if (!model) return res.status(404).json({ error: `Model not found: ${modelId}` });
+
+    const finalPrompt = searchContext ? `${searchContext}\n\n${prompt}` : prompt;
+    const input = buildInput(model, finalPrompt, systemPrompt, extraParams);
+
+    const prediction = await runPrediction(model, input, token);
+    const content = extractOutput(prediction);
+
+    res.json({
+      id: prediction.id,
+      modelId: model.id,
+      modelTag: model.tag,
+      modelName: model.displayName,
+      content,
+      status: prediction.status,
+      metrics: prediction.metrics,
+      urls: prediction.urls
+    });
+  } catch (err) {
+    res.status(500).json({ error: err.message });
+  }
+});
+
+// POST /api/chat/multi - send to multiple models in parallel
+router.post('/multi', async (req, res) => {
+  const token = process.env.REPLICATE_API_TOKEN;
+  if (!token) return res.status(400).json({ error: 'REPLICATE_API_TOKEN not configured' });
+
+  const { modelIds, prompt, systemPrompt, searchContext, extraParams } = req.body;
+  if (!modelIds?.length || !prompt) return res.status(400).json({ error: 'modelIds and prompt are required' });
+
+  try {
+    const models = await loadModels();
+
+    const tasks = modelIds.map(async (modelId) => {
+      const model = models.find(m => m.id === modelId);
+      if (!model) return { modelId, error: 'Model not found' };
+
+      try {
+        const finalPrompt = searchContext ? `${searchContext}\n\n${prompt}` : prompt;
+        const input = buildInput(model, finalPrompt, systemPrompt, extraParams);
+        const prediction = await runPrediction(model, input, token);
+        const content = extractOutput(prediction);
+        return {
+          id: prediction.id,
+          modelId: model.id,
+          modelTag: model.tag,
+          modelName: model.displayName,
+          content,
+          status: prediction.status,
+          metrics: prediction.metrics
+        };
+      } catch (err) {
+        return { modelId, modelTag: model.tag, modelName: model.displayName, error: err.message };
+      }
+    });
+
+    const results = await Promise.all(tasks);
+    res.json({ results });
+  } catch (err) {
+    res.status(500).json({ error: err.message });
+  }
+});
+
+export { router as chatRouter };