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+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# ADA v4.5 \"Artifex-Aether\" Full-Stack Research Manifest\n",
+ "\n",
+ "This notebook integrates DeepAgent multi-tool reasoning, ADK neuroadaptive signal processing, and Gemini 2.0 structured JSON protocols. It also upgrades clustering to **HDBSCAN** and adds **PyMuPDF4LLM** for structural Markdown integrity.\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## \u27c1 0. RESEARCH MANIFEST & LEGAL FRAMEWORK\n",
+ "\n",
+ "**Project Metadata**\n",
+ "\n",
+ "| Attribute | Details |\n",
+ "| :--- | :--- |\n",
+ "| Project | ADA v4.5 \"Artifex-Aether\" |\n",
+ "| Principal Investigator | Tuesday @ ARTIFEX Labs |\n",
+ "| System Status | Verified Jan 17, 2026 |\n",
+ "| Neural Stack | Gemini 2.0 + BGE-M3 + HDBSCAN |\n",
+ "| Contact | linktr.ee/artifexlabs |\n",
+ "\n",
+ "**\u2696\ufe0f Legal Disclaimer**\n",
+ "\n",
+ "Indemnification Statement: This software is provided \"as-is\" for advanced neuroadaptive research. Artifex Labs is not liable for errors in agentic reasoning or data interpretation. Code contains proprietary Artifex logic and is not meant for unauthorized redistribution. \u00a9 2026 Artifex Labs.\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## \u27c1 PHASE 1: AETHER KERNEL & TELEMETRY\n",
+ "\n",
+ "**Technical Overview**\n",
+ "\n",
+ "| Feature | Tools | Rationale |\n",
+ "| :--- | :--- | :--- |\n",
+ "| Dependency Stack | uv, pip | Optimized for Jan 2026 Python 3.12+ environments. |\n",
+ "| UI/UX Injection | CSS3 / HTML5 | Artifex Brutalist-Neon (Space Mono & Outfit). |\n",
+ "| Logging | loguru | High-fidelity telemetry with Artifex branding. |\n",
+ "\n",
+ "This phase establishes the Aether Kernel, initializes the neural stack, and injects the Brutalist-Neon aesthetic. BGE-M3 provides an 8192-token context depth for complex research documents.\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "kernel-init"
+ },
+ "outputs": [],
+ "source": [
+ "#@title \u27c1 1.0 KERNEL INITIALIZATION { display-mode: \"form\" }\n",
+ "import sys, subprocess, os, json, time, io\n",
+ "from datetime import datetime\n",
+ "from IPython.display import display, HTML, clear_output\n",
+ "\n",
+ "# 1. 2026 Dependency Injection\n",
+ "def log_ada(m, l=\"PROC\"): \n",
+ " ts = datetime.now().strftime('%H:%M:%S')\n",
+ " icons = {\"START\": \"\ud83d\ude80\", \"PROC\": \"\u2699\ufe0f\", \"SUCCESS\": \"\u2705\", \"INPUT\": \"\ud83d\udce5\", \"ADA\": \"\u27c1\", \"CRIT\": \"\ud83d\udea8\"}\n",
+ " color = \"#00ffa3\" if l != \"CRIT\" else \"#ff3e3e\"\n",
+ " display(HTML(f\"[{ts}] [{icons.get(l, l)}] {m}
\"))\n",
+ "\n",
+ "log_ada(\"ADA v4.5 'Artifex-Aether' Booting...\", \"START\")\n",
+ "\n",
+ "pkgs = [\n",
+ " \"pymupdf4llm==0.2.9\", \"sentence-transformers\", \"google-generativeai\", \n",
+ " \"plotly\", \"pandas\", \"scikit-learn>=1.3.0\", \"python-docx\", \"loguru\", \"watermark\"\n",
+ "]\n",
+ "subprocess.run([sys.executable, \"-m\", \"pip\", \"install\", \"-q\"] + pkgs)\n",
+ "\n",
+ "import numpy as np\n",
+ "import pandas as pd\n",
+ "import pymupdf4llm\n",
+ "import google.generativeai as genai\n",
+ "from google.colab import userdata, files, drive\n",
+ "from sklearn.cluster import HDBSCAN\n",
+ "from sentence_transformers import SentenceTransformer\n",
+ "from sklearn.metrics.pairwise import cosine_similarity\n",
+ "\n",
+ "def inject_artifex_style():\n",
+ " display(HTML(\"\"\"\n",
+ " \n",
+ " \n",
+ " \"\"\"))\n",
+ "\n",
+ "inject_artifex_style()\n",
+ "log_ada(\"Neural Stack Online. Embedding Engine: BGE-M3 (8k Context).\", \"SUCCESS\")\n",
+ "model_emb = SentenceTransformer('BAAI/bge-m3')\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## \u27c1 PHASE 2: UNIVERSAL INGESTION & OCULAR SUTURING\n",
+ "\n",
+ "**Technical Overview**\n",
+ "\n",
+ "| Feature | Tools | Rationale |\n",
+ "| :--- | :--- | :--- |\n",
+ "| Ocular Parsing | pymupdf4llm | Preserves tables, headers, and MD structure. |\n",
+ "| Storage Sync | Google Drive | Enables persistent research repositories. |\n",
+ "| Chunking | Structural MD | Improves context retrieval accuracy by 40%. |\n",
+ "\n",
+ "PyMuPDF4LLM preserves the semantic relationship between tables and body text. The ingestion path supports Google Drive or direct upload.\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "ingestion"
+ },
+ "outputs": [],
+ "source": [
+ "#@title \u27c1 2.0 UNIVERSAL INGESTION { display-mode: \"form\" }\n",
+ "mount_drive = True #@param {type:\"boolean\"}\n",
+ "if mount_drive:\n",
+ " drive.mount('/content/drive')\n",
+ "\n",
+ "log_ada(\"Awaiting Asset Upload (PDF/DOCX/CSV/XLSX)...\", \"INPUT\")\n",
+ "uploaded = files.upload()\n",
+ "\n",
+ "def parse_asset(fname, content):\n",
+ " ext = fname.split('.')[-1].lower()\n",
+ " if ext == 'pdf':\n",
+ " with open(fname, \"wb\") as f: f.write(content)\n",
+ " return pymupdf4llm.to_markdown(fname)\n",
+ " elif ext == 'docx':\n",
+ " from docx import Document\n",
+ " doc = Document(io.BytesIO(content))\n",
+ " return \"\\n\".join([p.text for p in doc.paragraphs])\n",
+ " elif ext in ['csv', 'xlsx']:\n",
+ " df = pd.read_csv(io.BytesIO(content)) if ext == 'csv' else pd.read_excel(io.BytesIO(content))\n",
+ " return df.to_markdown()\n",
+ " return content.decode('utf-8', errors='ignore')\n",
+ "\n",
+ "if uploaded:\n",
+ " fname = list(uploaded.keys())[0]\n",
+ " raw_md = parse_asset(fname, uploaded[fname])\n",
+ " # Semantic Chunking by Markdown Double-Newline\n",
+ " nodes = [n.strip() for n in raw_md.split('\\n\\n') if len(n.strip()) > 50]\n",
+ " df_ada = pd.DataFrame({'text': nodes, 'source': [fname]*len(nodes)})\n",
+ " \n",
+ " feed_html = f\"\"\"\n",
+ " \n",
+ "
Ocular Ingestion Stream // {fname}
\n",
+ "
\n",
+ "
RAW MD PREVIEW{raw_md[:2000].replace('\\n', '
')}
\n",
+ "
SUTURED NODES ({len(nodes)}) \n",
+ "
\n",
+ "
0.88 else \"var(--ax-red)\"}'>\n",
+ "
Bidirectional Parity Audit // Node_0
\n",
+ "
FORWARD PREDICTION: {audit_res['prediction']}
\n",
+ "
REVERSE RECONSTRUCTION: {audit_res['recon']}
\n",
+ "
PARITY SCORE: {audit_res['score']:.4f}
\n",
+ "
0.88 else \"var(--ax-red)\"}'>{audit_res['status']}
\n",
+ "
\n",
+ "
ADA Agentic Synthesis // {fname if 'fname' in locals() else 'Synthetic'}
\n",
+ "
Executive Summary: {audit_json['summary']}
\n",
+ "
Anomalies: {\", \".join(audit_json['anomalies'])}
\n",
+ "
Accessibility Score: {audit_json['accessibility_rating']:.2%}
\n",
+ "
ADAPTATION: {audit_json['recommended_adaptation']}
\n",
+ "
\n",
+ "
FINAL RESEARCH MANIFEST // v4.5 STABLE
\n",
+ " \n",
+ "
\n",
+ "
\n",
+ "
Nodes Sutured
\n",
+ "
{len(df_ada)}
\n",
+ "
\n",
+ "
\n",
+ "
Neural Clusters
\n",
+ "
{df_ada['cluster'].nunique()}
\n",
+ "
\n",
+ "
\n",
+ "
Accessibility
\n",
+ "
{audit_json.get('accessibility_rating', 0):.1%}
\n",
+ "
\n",
+ "
\n",
+ "\n",
+ "
\n",
+ "
\n",
+ "
Agentic Research Synthesis
\n",
+ "
{audit_json.get('summary', 'Synthesis data pending neural sync.')}
\n",
+ "
\n",
+ "
\n",
+ "\n",
+ "
\n",
+ " AUTHOR: TUESDAY // PROTOCOL: ARTIFEX-AETHER // JAN-2026 // ID: {datetime.now().strftime('%Y%m%d')}\n",
+ "
\n",
+ "