Rename Gemini to Groq Llama 3 globally and remove pricing from mobile nav

frontend/app/chat/page.tsx

@@ -102,7 +102,7 @@ function SidebarStats() {
       <div>
         <div className="text-xs text-black/30 tracking-widest uppercase mb-3">Tech Stack</div>
         <div className="flex flex-wrap gap-2">
-          {["FastAPI", "FAISS", "LangChain", "Gemini 2.0"].map(tech => (
+          {["FastAPI", "FAISS", "LangChain", "Llama 3"].map(tech => (
             <span key={tech} className="px-2 py-1 text-xs text-black/40 bg-black/[0.03] rounded-lg border border-black/[0.06]">
               {tech}
             </span>
@@ -316,7 +316,7 @@ export default function ChatPage() {
               </button>
             </div>
             <p className="text-[10px] text-black/30 text-center mt-3">
-              Powered by FastAPI + FAISS + Gemini 2.0 — querying 15.5K+ real documents.
+              Powered by FastAPI + FAISS + Llama 3 — querying 15.5K+ real documents.
             </p>
           </form>
         </div>

frontend/app/layout.tsx

@@ -13,7 +13,7 @@ const _ibmPlexSans = IBM_Plex_Sans({ weight: ["300", "400", "500", "600"], subse
 export const metadata: Metadata = {
   title: 'SupportRAG — Dual Vector Store RAG for Customer Support',
   description: 'Production-ready RAG system with dual vector stores, async processing, and FAISS IVF optimization. 4.2x throughput improvement with 337ms average latency across 15.5k+ documents.',
-  keywords: ['RAG', 'customer support', 'vector store', 'FAISS', 'LangChain', 'Gemini', 'AI support'],
+  keywords: ['RAG', 'customer support', 'vector store', 'FAISS', 'LangChain', 'Groq', 'AI support'],
   authors: [{ name: 'Saksham Yadav' }],
   openGraph: {
     title: 'SupportRAG — Dual Vector Store RAG for Customer Support',

frontend/app/page.tsx

@@ -243,7 +243,7 @@ export default function AgenticPage() {
               <div className="w-10 h-10 rounded-xl border border-black/10 flex items-center justify-center mb-5">
                 <svg width="18" height="18" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="1.5"><path d="M12 22s8-4 8-10V5l-8-3-8 3v7c0 6 8 10 8 10z"/></svg>
               </div>
-              <h3 className="text-lg font-light mb-2">Gemini 2.0 Flash</h3>
+              <h3 className="text-lg font-light mb-2">Groq Llama 3</h3>
               <p className="text-sm text-black/45 leading-relaxed">State-of-the-art LLM for natural responses with context-aware answer generation.</p>
             </BentoCard>
           </div>
@@ -285,7 +285,7 @@ export default function AgenticPage() {
             {[
               { n: "01", title: "Ingest",  desc: "Load FAQs and support tickets into dual FAISS vector stores with IVF clustering.", delay: 0,   img: "https://hebbkx1anhila5yf.public.blob.vercel-storage.com/define-5aafAmGBrxZpOqJ3XLHY3n3qzC2I5K.png" },
               { n: "02", title: "Search", desc: "Parallel async queries across both stores. Smart fallback at 65% confidence threshold.", delay: 80,  img: "https://hebbkx1anhila5yf.public.blob.vercel-storage.com/compose-5RT5VR4f1Y3GoFmovqTKLTG4UXp3g2.png" },
-              { n: "03", title: "Generate",    desc: "Gemini 2.0 Flash generates context-aware answers with citations and metadata.", delay: 140, img: "https://hebbkx1anhila5yf.public.blob.vercel-storage.com/test-zm8guZwxJHtwWsJ7XO4B0CF7GzlNK8.png" },
+              { n: "03", title: "Generate",    desc: "Groq Llama 3 generates context-aware answers with citations and metadata.", delay: 140, img: "https://hebbkx1anhila5yf.public.blob.vercel-storage.com/test-zm8guZwxJHtwWsJ7XO4B0CF7GzlNK8.png" },
               { n: "04", title: "Respond",  desc: "Return answer with source tracking, confidence scores, and latency metrics.", delay: 200, img: "https://hebbkx1anhila5yf.public.blob.vercel-storage.com/deploy-an8fgHSLzniojkcmRyGGIFQUJF9T5J.png" },
             ].map((step) => (
               <BentoCard key={step.n} className="relative overflow-hidden flex flex-col min-h-[320px]" delay={step.delay}>
@@ -328,7 +328,7 @@ export default function AgenticPage() {
               </RevealText>
             </div>
             <p className="text-sm text-black/45 leading-relaxed max-w-xs">
-              Built with FastAPI, FAISS, LangChain, and Gemini. Full REST + WebSocket API. Python 3.10+ compatible.
+              Built with FastAPI, FAISS, LangChain, and Groq. Full REST + WebSocket API. Python 3.10+ compatible.
             </p>
           </div>
 
@@ -421,7 +421,7 @@ export default function AgenticPage() {
 
               {/* Tech badges — vertical stack */}
               <div className="pt-4 flex flex-col gap-2">
-                {["FastAPI", "FAISS IVF", "LangChain", "Gemini 2.0"].map((badge) => (
+                {["FastAPI", "FAISS IVF", "LangChain", "Llama 3"].map((badge) => (
                   <div key={badge} className="flex items-center gap-2 text-xs text-black/25">
                     <span className="w-1 h-1 rounded-full bg-black/25" />
                     {badge}

frontend/components/live-agent-feed.tsx

@@ -3,7 +3,7 @@
 import { useEffect, useState, useRef } from "react"
 
 const AGENT_NAMES = [
-  "faq-store", "ticket-store", "embedder", "gemini-llm",
+  "faq-store", "ticket-store", "embedder", "groq-llm",
   "retriever", "ranker", "generator", "validator",
   "fallback", "metrics",
 ]
@@ -90,7 +90,7 @@ function ProgressBar({ initial }: { initial: number }) {
 const SEED_ROWS: AgentRow[] = [
   { id: "A1B2C3", name: "faq-store",    task: "How do I reset my password?",       region: "faq",    status: STATUSES[0], progress: 42, elapsed: "312ms", key: 0 },
   { id: "D4E5F6", name: "ticket-store", task: "My order hasn't arrived yet",       region: "ticket", status: STATUSES[0], progress: 67, elapsed: "287ms", key: 1 },
-  { id: "G7H8I9", name: "gemini-llm",   task: "How do I get a refund?",           region: "faq",    status: STATUSES[3], progress: 18, elapsed: "156ms", key: 2 },
+  { id: "G7H8I9", name: "groq-llm",   task: "How do I get a refund?",           region: "faq",    status: STATUSES[3], progress: 18, elapsed: "156ms", key: 2 },
   { id: "J0K1L2", name: "retriever",    task: "Where is my order #54321?",        region: "ticket", status: STATUSES[0], progress: 55, elapsed: "342ms", key: 3 },
   { id: "M3N4O5", name: "embedder",     task: "Change my email address",          region: "faq",    status: STATUSES[0], progress: 80, elapsed: "198ms", key: 4 },
   { id: "P6Q7R8", name: "validator",    task: "Payment declined twice",           region: "ticket", status: STATUSES[4], progress: 99, elapsed: "401ms", key: 5 },

frontend/components/mobile-nav.tsx

@@ -7,8 +7,7 @@ const NAV_LINKS = [
   { label: "Data Sources", href: "#agents" },
   { label: "Workflow",     href: "#workflow" },
   { label: "Tech Stack",   href: "#integrations" },
-  { label: "Pricing",      href: "#pricing" },
-]
+  ]
 
 const NAV_STYLE = {
   backdropFilter: "blur(16px)",

frontend/components/stacking-agent-cards.tsx

@@ -26,7 +26,7 @@ const AGENTS = [
   },
   {
     label: "LLM ENGINE",
-    title: "Gemini 2.0 Flash",
+    title: "Groq Llama 3",
     desc: "State-of-the-art LLM for natural response generation. Context-aware answers with source tracking and confidence scoring.",
     stats: [{ v: "337ms", l: "latency" }, { v: "4.2x", l: "throughput" }],
     img: "https://hebbkx1anhila5yf.public.blob.vercel-storage.com/executor-o1q6509qMLXMtpBIGo49vcgOu34sI1.png",