feat: implement Nubenetes V2 architecture with Agentic Elite optimizer

src/v2_optimizer.py

@@ -0,0 +1,117 @@
+import os
+import re
+import json
+import asyncio
+import yaml
+from datetime import datetime
+from typing import List, Dict, Set
+from src.config import GEMINI_API_KEYS, GH_TOKEN, TARGET_REPO, MADRID_TZ
+from src.gemini_utils import call_gemini_with_retry
+from src.logger import log_event
+
+V1_DIR = "docs"
+V2_DIR = "v2-docs"
+
+class V2Optimizer:
+    def __init__(self):
+        self.elite_criteria = (
+            "You are a Principal Platform Architect in May 2026.\n"
+            "Your task is to select the ABSOLUTE BEST resources from a larger list.\n"
+            "CRITERIA for V2 (Elite Edition):\n"
+            "1. HIGH IMPACT: Only links with score > 90 or exceptional industry value.\n"
+            "2. MODERNITY: Prefer 2024-2026 content. Avoid outdated patterns unless fundational.\n"
+            "3. AWESOME LISTS: ALWAYS KEEP all links pointing to 'Awesome' repositories (GitHub/GitLab).\n"
+            "4. NO REDUNDANCY: If multiple tools do the same, pick the 1-2 most innovative or widely adopted.\n"
+            "5. AGENTIC FOCUS: Prioritize tools with AI/Agentic capabilities or eBPF/WASM innovation.\n"
+        )
+
+    async def optimize_file(self, filename: str):
+        v1_path = os.path.join(V1_DIR, filename)
+        v2_path = os.path.join(V2_DIR, filename)
+        
+        if not os.path.exists(v1_path): return
+
+        with open(v1_path, "r") as f:
+            content = f.read()
+
+        # Extract all links and their descriptions
+        links = re.findall(r'^\s*-\s*\[([^\]]+)\]\(([^\)]+)\)(.*)', content, re.MULTILINE)
+        if not links:
+            # If no links, just copy the structure/headers
+            headers = [l for l in content.splitlines() if l.startswith("#")]
+            with open(v2_path, "w") as f:
+                f.write("\n".join(headers) + "\n\n*Content coming soon as part of the 2026 Agentic Elite curation.*")
+            return
+
+        formatted_links = []
+        for title, url, desc in links:
+            formatted_links.append(f"- [{title}]({url}) {desc.strip()}")
+
+        log_event(f"[*] V2 Optimizer: Analyzing {len(formatted_links)} links in {filename}")
+
+        prompt = (
+            f"{self.elite_criteria}\n"
+            f"FILE: {filename}\n"
+            f"LINKS TO EVALUATE:\n" + "\n".join(formatted_links[:100]) + "\n\n"
+            "Respond ONLY with a JSON list of indices to KEEP. "
+            "Example: [0, 5, 22]. Remember to ALWAYS keep 'Awesome' repos."
+        )
+
+        try:
+            indices = await call_gemini_with_retry(prompt)
+            if not isinstance(indices, list): indices = []
+            
+            selected_links = [formatted_links[i] for i in indices if i < len(formatted_links)]
+            
+            # Reconstruct V2 file
+            v2_content = f"# {filename.replace('.md', '').capitalize()} (Elite Selection)\n\n"
+            v2_content += "!!! abstract \"2026 Agentic Vision\"\n"
+            v2_content += "    This page contains a curated selection of top-tier resources, strictly filtered by our Agentic AI for high impact and modern relevance.\n\n"
+            
+            if selected_links:
+                v2_content += "## Selected Resources\n"
+                v2_content += "\n".join(selected_links)
+            else:
+                v2_content += "\n*No resources met the elite criteria for this specific category yet.*"
+
+            with open(v2_path, "w") as f:
+                f.write(v2_content)
+                
+            log_event(f"  [OK] V2 file generated: {v2_path} ({len(selected_links)} links kept)")
+
+        except Exception as e:
+            log_event(f"  [!] Error optimizing {filename} for V2: {e}")
+
+    async def run_full_optimization(self):
+        log_event("STARTING V2 AGENTIC OPTIMIZATION (THE ARCHITECT'S CUT)", section_break=True)
+        files = [f for f in os.listdir(V1_DIR) if f.endswith(".md") and f != "index.md"]
+        
+        # Batch processing to avoid rate limits
+        for i in range(0, len(files), 5):
+            batch = files[i:i+5]
+            await asyncio.gather(*[self.optimize_file(f) for f in batch])
+            await asyncio.sleep(2)
+
+        # Generate Landing Page
+        await self._generate_v2_index()
+        log_event("V2 OPTIMIZATION FINISHED SUCCESSFULLY.", section_break=True)
+
+    async def _generate_v2_index(self):
+        v2_index = (
+            "# Welcome to Nubenetes V2\n\n"
+            "## The Agentic Elite Edition (2026)\n\n"
+            "This is a high-density, AI-curated view of the Cloud Native ecosystem. While our [Classic Archive](https://nubenetes.com) "
+            "serves as a comprehensive encyclopedia of thousands of tools, **Nubenetes V2** is built for the time-constrained architect.\n\n"
+            "### Core Principles of V2:\n"
+            "- **Impact First**: Only resources with exceptional value are shown.\n"
+            "- **2026 Ready**: Focus on eBPF, WASM, AI-Native Infrastructure, and Agentic Workflows.\n"
+            "- **Always Awesome**: We maintain 100% of the community's fundational 'Awesome' lists.\n\n"
+            "--- \n"
+            "Generated by Nubenetes AI Agent using Gemini 2.0/2.5 Flash."
+        )
+        with open(os.path.join(V2_DIR, "index.md"), "w") as f:
+            f.write(v2_index)
+
+if __name__ == "__main__":
+    optimizer = V2Optimizer()
+    asyncio.run(optimizer.run_full_optimization())