update

Author: vasanthshanmugam

.github/workflows/hourly-ai.yml

@@ -23,7 +23,7 @@ jobs:
       - name: Install dependencies
         run: |
           npm init -y
-          npm install firebase-admin @google/generative-ai
+          npm install firebase-admin @google/generative-ai@latest
 
       - name: Execute AI Script
         env:

scripts/generate-ai-tip.js

@@ -15,116 +15,115 @@ const db = admin.firestore();
 // 2. AI SETUP
 const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY);
 
-// CATEGORY CONFIGURATION
 const categoryMap = {
     "performance": {
         name: "Performance Tools Hub",
         folder: "performance",
-        tools: ["JMeter", "NeoLoad", "LoadRunner", "k6", "Locust", "Gatling"],
-        focus: "Load testing strategies, scripting bottlenecks, and tool-specific optimizations."
+        tools: ["JMeter", "NeoLoad", "LoadRunner", "k6", "Locust"],
+        focus: "Load testing strategies and tool-specific optimizations."
     },
     "sre": {
         name: "SRE & Observability",
         folder: "sre",
-        tools: ["Kubernetes", "AKS", "Azure-Monitor", "Grafana", "Datadog", "Dynatrace", "AppDynamics"],
-        focus: "Reliability engineering, SLIs/SLOs, Error Budgets, and Infrastructure Observability."
+        tools: ["Kubernetes", "AKS", "Azure-Monitor", "Grafana", "Datadog"],
+        focus: "Reliability engineering and SLIs/SLOs."
     },
     "devops": {
         name: "DevOps & CI/CD",
         folder: "devops",
-        tools: ["GitHub-Actions", "Jenkins", "Docker", "Linux-Kernel-Tuning", "Terraform", "Ansible"],
-        focus: "Pipeline automation, container orchestration, and OS-level performance tuning."
+        tools: ["GitHub-Actions", "Jenkins", "Docker", "Terraform"],
+        focus: "Pipeline automation and container orchestration."
     },
     "performance_mastery": {
         name: "Basics to Advanced Mastery",
         folder: "performance_mastery",
-        tools: ["Fundamentals", "Workload-Design", "Queueing-Theory", "Bottleneck-Analysis", "Capacity-Planning"],
-        focus: "The professional roadmap: explaining core concepts like Little's Law from absolute basics to architectural expert level."
+        tools: ["Fundamentals", "Workload-Design", "Bottleneck-Analysis"],
+        focus: "Core performance concepts from beginner to expert level."
     },
     "trends_ai": {
         name: "Innovation & AI Trends",
         folder: "trends_ai",
-        tools: ["GenAI-in-Testing", "Predictive-Analytics", "Autonomous-Load-Testing", "LLM-Optimizations", "Tech-Trends-2025"],
-        focus: "Cutting-edge updates: How AI is transforming performance, autonomous remediation, and the future of engineering."
+        tools: ["GenAI-in-Testing", "Autonomous-Load-Testing", "Tech-Trends-2026"],
+        focus: "How AI and new trends are changing SRE and Testing."
     }
 };
 
 async function run() {
-    try {
-        // Selection Logic: Pick a random category and tool
-        const keys = Object.keys(categoryMap);
-        const selectedCatKey = keys[Math.floor(Math.random() * keys.length)];
-        const category = categoryMap[selectedCatKey];
-        const selectedTool = category.tools[Math.floor(Math.random() * category.tools.length)];
-
-        console.log(`🚀 Little's Law Team is generating content for: ${selectedTool} (${category.name})`);
-
-        // Model initialization (Using the most stable high-speed model)
-        const model = genAI.getGenerativeModel({ model: "gemini-1.5-flash" });
-
-        const prompt = `
-            ACT AS: The Senior Leadership Team at Little's Law Academy. You are world-class Architects with 30 years of history.
-            TOPIC: ${selectedTool}.
-            CATEGORY: ${category.name}.
-            THEME: ${category.focus}.
-            
-            GOAL: Write a technical briefing (Approx 350 words) for our students.
-            IMPORTANT: Do not mention AI. Speak as 'We, the Little's Law Team'.
-            
-            STRUCTURE (Use Strictly valid Markdown):
-            # ${selectedTool} Internal Team Briefing
-            
-            ## ⚡ From the Trenches (Experience)
-            Share an emotional and highly specific "war story" from our team's history. Talk about a 3 AM system collapse, a critical latency spike in production, or the stress of a failing BFCM load test. Connect this emotionally to why ${selectedTool} is vital.
-            
-            ## 🛠️ Architecture Deep-Dive
-            Break down a complex technical concept. Talk about specific metrics (P99 latency, Throughput vs Goodput, TCP handshakes, or Heap usage). Explain the internal mechanics.
-            
-            ## 💻 Technical Implementation
-            Provide one exact technical example that our team recommends. This MUST be a code block (CLI command, YAML config, JMeter Groovy snippet, or Python k6 script).
-            
-            ## 💡 Our Engineering Philosophy
-            One closing piece of mentorship/wisdom regarding the current tech landscape or the rise of AI in our field.
-            
-            TONE: High-authority, expert-level, yet inspiring and mentorship-focused.
-        `;
-
-        const result = await model.generateContent(prompt);
-        const response = await result.response;
-        const markdownContent = response.text();
-
-        if (!markdownContent) throw new Error("Empty response from Engine");
-
-        // 1. SYNC TO FIREBASE (Site-wide Banner)
-        await db.collection('admin_data').doc('hourly_tip').set({
-            content: markdownContent,
-            tool: selectedTool,
-            folder: category.folder,
-            author: "Little's Law Team",
-            lastUpdated: new Date().toISOString()
-        });
-
-        // 2. SYNC TO GITHUB (Create Folders & Save Markdown)
-        const baseDocsDir = path.join(__dirname, '../docs');
-        const targetFolder = path.join(baseDocsDir, category.folder);
-
-        // Ensure path exists
-        if (!fs.existsSync(targetFolder)) {
-            fs.mkdirSync(targetFolder, { recursive: true });
+    // Attempt these models in order of preference
+    const modelNames = ["gemini-1.5-flash", "gemini-pro"];
+    let successfulGeneration = false;
+
+    // Pick content first
+    const keys = Object.keys(categoryMap);
+    const selectedCatKey = keys[Math.floor(Math.random() * keys.length)];
+    const category = categoryMap[selectedCatKey];
+    const selectedTool = category.tools[Math.floor(Math.random() * category.tools.length)];
+
+    for (const modelName of modelNames) {
+        if (successfulGeneration) break;
+
+        try {
+            console.log(`📡 Trying generation with model: ${modelName}...`);
+            const model = genAI.getGenerativeModel({ model: modelName });
+
+            const prompt = `
+                ACT AS: The Senior Leadership Team at Little's Law Academy. You are world-class Architects.
+                TOPIC: ${selectedTool}.
+                CATEGORY: ${category.name}.
+                GOAL: Write a technical masterclass (350 words) for our students.
+                
+                STRUCTURE:
+                # ${selectedTool} Internal Team Briefing
+                ## ⚡ From the Trenches
+                Tell an emotional war story about this topic from our team's 30-year history.
+                ## 🛠️ Architecture Deep-Dive
+                Technical analysis of P99 metrics, bottlenecks, or internal mechanics.
+                ## 💻 Technical Implementation
+                Provide a code snippet or CLI command (formatted in a markdown code block).
+                ## 💡 Team Wisdom
+                A closing mentor tip.
+                
+                IMPORTANT: Do not mention AI. Only say "Little's Law Team".
+            `;
+
+            const result = await model.generateContent(prompt);
+            const response = await result.response;
+            const text = response.text();
+
+            if (text) {
+                console.log(`✅ Success using ${modelName}`);
+                await saveResult(text, selectedTool, category);
+                successfulGeneration = true;
+            }
+
+        } catch (error) {
+            console.warn(`⚠️ Model ${modelName} failed or not found. trying next...`);
         }
+    }
 
-        // Clean name for file consistency
-        const cleanName = selectedTool.toLowerCase().replace(/[^a-z0-9]/g, '_');
-        const filePath = path.join(targetFolder, `${cleanName}.md`);
-        
-        fs.writeFileSync(filePath, markdownContent);
-
-        console.log(`✅ CONTENT PUBLISHED: docs/${category.folder}/${cleanName}.md`);
-
-    } catch (error) {
-        console.error("❌ Fatal Team Content Error:", error.message);
+    if (!successfulGeneration) {
+        console.error("❌ All AI models failed. Check your API Key permissions and quota.");
         process.exit(1);
     }
 }
 
-run();
+async function saveResult(text, tool, category) {
+    // Save to Firebase
+    await db.collection('admin_data').doc('hourly_tip').set({
+        content: text,
+        tool: tool,
+        folder: category.folder,
+        author: "Little's Law Team",
+        lastUpdated: new Date().toISOString()
+    });
+
+    // Save to GitHub
+    const baseDocsDir = path.join(__dirname, '../docs');
+    const targetFolder = path.join(baseDocsDir, category.folder);
+    if (!fs.existsSync(targetFolder)) fs.mkdirSync(targetFolder, { recursive: true });
+
+    const cleanName = tool.toLowerCase().replace(/[^a-z0-9]/g, '_');
+    fs.writeFileSync(path.join(targetFolder, `${cleanName}.md`), text);
+}
+
+run().catch(console.error);