Update app.js

app.js

@@ -3,6 +3,8 @@ import cors from 'cors';
 import fs from 'fs';
 import path from 'path';
 import { createClient } from '@supabase/supabase-js';
+import { search } from "./research.js";
+
 
 const PORT = 7860;
 const SUPABASE_URL = process.env.SUPABASE_URL;
@@ -66,6 +68,45 @@ const StateManager = {
     }
 };
 
+
+async function callAIWithResearch(history, input, context, images, systemPrompt, projectContext, modelId) {
+  const firstPass = await callAI(history, input, context, images, systemPrompt, projectContext, modelId);
+
+  // Check if the AI requested any research
+  const researchMatches = [...firstPass.text.matchAll(/<deep_research>([\s\S]*?)<\/deep_research>/gi)];
+  if (researchMatches.length === 0) return firstPass;
+
+  // Resolve all research requests in parallel
+  const resolved = await Promise.all(
+    researchMatches.map(async (match) => {
+      try {
+        const payload = JSON.parse(match[1].trim());
+        const { result } = await search({
+          query:   payload.query,
+          urgent:  payload.urgent  ?? false,
+          deep:    payload.deep    ?? false,
+          supabase,
+        });
+        return `[RESEARCH: "${payload.query}"]\n${result}`;
+      } catch (e) {
+        console.error("[Research] Failed to resolve query:", e.message);
+        return null;
+      }
+    })
+  );
+
+  const researchBlock = resolved.filter(Boolean).join("\n\n────\n\n");
+  if (!researchBlock) return firstPass;
+
+  // Second pass: inject research results and let the AI continue
+  const augmentedInput =
+    `${input}\n\n` +
+    `[RESEARCH RESULTS — use these to complete your response accurately]:\n${researchBlock}`;
+
+  console.log(`[Research] Re-running AI with ${researchMatches.length} research result(s) injected.`);
+  return callAI(history, augmentedInput, context, images, systemPrompt, projectContext, modelId);
+}
+
 const callAI = async (history, input, contextData, images, systemPrompt, projectContext, modelId) => {
     let contextStr = "";
     try { contextStr = JSON.stringify(contextData, null, 2); } catch {}
@@ -108,7 +149,8 @@ function extractCommands(text) {
     
     // NEW: Extract AI queries sent to local MCPs
     parse(/<mcp_query>([\s\S]*?)<\/mcp_query>/gi, 'mcp_query');
-
+    parse(/<deep_research>([\s\S]*?)<\/deep_research>/gi, 'deep_research');
+  
     return commands;
 }
 
@@ -279,7 +321,9 @@ app.post('/init-project', async (req, res) => {
     setImmediate(async () => {
         try {
             const initInput = `PROJECT: ${name}\nDESC: ${description}\nUSER TIMEZONE OFFSET: ${timezoneOffset}\nTask: Init PRD, First Thrust, Schedule Morning Briefing.`;
-            const aiResult = await callAI([], initInput, {},[], prompts.init_system_prompt, "", SMART_MODEL_ID);
+           // const aiResult = await callAI([], initInput, {},[], prompts.init_system_prompt, "", SMART_MODEL_ID);
+            const aiResult = await callAIWithResearch([], initInput, {},[], prompts.init_system_prompt, "", SMART_MODEL_ID);
+            
             aiResult.text += `\n<notification>Project '${name}' initialized successfully!</notification>`;
             await StateManager.addHistory(lead.id, 'user', initInput);
             await StateManager.addHistory(lead.id, 'model', aiResult.text);
@@ -304,7 +348,9 @@ app.post('/process', async (req, res) => {
         const projectContext = `[PRD]: ${lead?.requirements_doc?.substring(0, 3000)}...\n[CURRENT THRUST]: ${activeThrust ? JSON.stringify(activeThrust) : "None"}\n[RECENT TIMELINE]: ${JSON.stringify(timeline ||[])}`;
         const history = await StateManager.getHistory(projectId);
         
-        let aiResult = await callAI(history, prompt, context, images, sysPrompt, projectContext, selectedModel);
+        // let aiResult = await callAI(history, prompt, context, images, sysPrompt, projectContext, selectedModel);
+       let aiResult = await callAIWithResearch(history, prompt, context, images, sysPrompt, projectContext, selectedModel);
+       
         let cmds = extractCommands(aiResult.text);
         let flags = await executeCommands(userId, projectId, cmds);
 
@@ -349,8 +395,9 @@ app.post('/automated-briefing', async (req, res) => {
         const projectContext = `[PRD]: ${lead.requirements_doc}\n[RECENT TIMELINE]: ${JSON.stringify(timeline)}`;
         const history = await StateManager.getHistory(projectId);
         
-        const aiResult = await callAI(history, prompt, {}, [], prompts.director_system_prompt, projectContext, SMART_MODEL_ID);
-        
+      //  const aiResult = await callAI(history, prompt, {}, [], prompts.director_system_prompt, projectContext, SMART_MODEL_ID);
+        const aiResult = await callAIWithResearch(history, prompt, {}, [], prompts.director_system_prompt, projectContext, SMART_MODEL_ID);
+      
         await StateManager.addHistory(projectId, 'model', aiResult.text);
         const cmds = extractCommands(aiResult.text);
         const flags = await executeCommands(lead.user_id, projectId, cmds);