Pixelog

A novel archival system that encodes documents as QR code frames in MP4 video files, enabling universal playback, Git-like version control, and sub-100ms semantic search.

What is Pixelog?

Pixelog transforms any document into a .pixe file - an MP4 video where each frame is a QR code containing chunks of your data. This approach unlocks:

Universal compatibility: MP4 plays on any device (phones, computers, TVs, browsers)
Git-like version control: Delta encoding tracks changes (64% space savings)
Sub-100ms semantic search: Vector embeddings enable meaning-based queries
Interactive LLM chat: RAG-powered Q&A with 200+ models via OpenRouter
Streaming architecture: Handle multi-GB files with constant 10MB memory
Military-grade encryption: AES-256-GCM with tamper detection
Air-gapped capable: Works completely offline

Technical Specs:

Format: MP4 with H.264-encoded QR frames
Density: 2.9KB per frame @ 1080p (87KB/sec)
Error correction: Reed-Solomon (30% damage tolerance)
Search: HNSW vector index with cosine similarity

Quick Start

Installation

go install github.com/ArqonAi/Pixelog/cmd/pixe@latest

Or build from source:

git clone https://github.com/ArqonAi/Pixelog.git
cd Pixelog
go build -o pixe ./cmd/pixe

Basic Workflow

# Convert document to .pixe format
pixe convert document.txt -o doc.pixe

# Build semantic search index
export OPENROUTER_API_KEY=sk-or-v1-xxx
pixe index doc.pixe

# Search by meaning
pixe search doc.pixe "machine learning concepts" --top 5

# Chat with your document
pixe chat doc.pixe

Core Features

File Operations

Convert any file type to .pixe format
Extract original files from .pixe archives
Display file metadata and structure
Integrity checking via SHA-256 hashing
AES-256-GCM encryption with password

Semantic Search

Build vector embeddings for sub-100ms search
Meaning-based queries (not just keyword matching)
Interactive LLM Q&A with automatic context retrieval
Ranked results by cosine similarity

Version Control

Create version snapshots with messages
List all versions with timestamps
Compare versions (frame-level changes)
Time-travel search across historical versions
Delta encoding (64% average space savings)

Performance

Sub-100ms search with HNSW indexing
Constant 10MB memory footprint (any file size)
Streaming support for multi-GB files
Parallel frame encoding/decoding

Security

AES-256-GCM authenticated encryption
PBKDF2 key derivation (600,000 iterations)
Reed-Solomon error correction (30% damage tolerance)
SHA-256 frame hashing for tamper detection
Air-gapped operation (no internet required)

CLI Commands

Basic Operations

pixe convert <input> -o <output.pixe>    # Convert to .pixe
pixe extract <file.pixe> -o <output>      # Extract from .pixe
pixe info <file.pixe>                     # Show file info
pixe verify <file.pixe>                   # Verify integrity

Semantic Search (requires OpenRouter API key)

export OPENROUTER_API_KEY=sk-or-v1-xxx
pixe index <file.pixe>                           # Build index
pixe search <file.pixe> "query" --top 5          # Search
pixe chat <file.pixe>                            # Interactive chat
pixe chat <file.pixe> --model openai/gpt-5       # Specific model
pixe chat <file.pixe> --list                     # Show models

Version Control

pixe version <file.pixe> -m "message"            # Create version
pixe versions <file.pixe>                        # List versions
pixe diff <file.pixe> <v1> <v2>                 # Compare versions
pixe query <file.pixe> <version> "query"         # Time-travel query

Encryption

pixe convert file.txt -o file.pixe --encrypt --password mypass
pixe extract file.pixe -o output --password mypass
pixe index file.pixe --password mypass

Use Cases

Knowledge Base Management

# Create and index
pixe convert docs/ -o knowledge.pixe
pixe index knowledge.pixe

# Semantic search
pixe search knowledge.pixe "authentication best practices"

# Track changes
pixe version knowledge.pixe -m "Added security section"
pixe diff knowledge.pixe 1 2

Compliance & Audit Trails

# Encrypted archive
pixe convert compliance-docs/ -o audit.pixe --encrypt --password xxx

# Track all changes
pixe versions audit.pixe

# Time-travel query
pixe query audit.pixe 1 "Q1 data retention policy"

# Verify integrity
pixe verify audit.pixe --password xxx

Research Paper Collections

# Index papers
pixe convert papers/ -o research.pixe
pixe index research.pixe

# Semantic citation search
pixe search research.pixe "transformer attention mechanisms"

# Chat with research
pixe chat research.pixe

Secure Document Archival

# Encrypted, air-gapped storage
pixe convert classified/ -o vault.pixe --encrypt --password xxx
pixe verify vault.pixe --password xxx
pixe extract vault.pixe -o restored/ --password xxx

Large-Scale Code Archival

# Streaming for multi-GB codebases
pixe convert monorepo.tar.gz -o codebase.pixe
# Auto-streaming: 2.5 GB with 10MB RAM

# Version control
pixe version codebase.pixe -m "Release v2.0"

# Semantic code search
pixe search codebase.pixe "authentication middleware"

How It Works

Architecture

Document → Chunks (2.9KB) → Encryption → QR Codes → MP4 Frames → .pixe File

Each .pixe file is an MP4 video:

Frame 0: Metadata (file info, encryption params, version history)
Frame 1+: QR-encoded data chunks
Audio track: Silent (required for MP4 spec)

Directory Structure

pixelog/
├── cmd/pixe/              # CLI (12 commands)
├── internal/
│   ├── converter/         # Document → .pixe
│   ├── crypto/            # AES-256-GCM
│   ├── qr/                # QR generation
│   ├── video/             # MP4 creation/extraction
│   ├── index/             # Semantic search
│   │   ├── indexer.go    # HNSW vector index
│   │   ├── embedder.go   # OpenRouter embeddings
│   │   └── delta.go      # Version control
│   └── llm/               # LLM client (OpenRouter)
├── pkg/config/            # Configuration
├── docs/                  # Documentation
└── examples/              # Usage examples

Performance

Operation	Time	Notes
Index Build	136ms	One-time per file
Semantic Search	<100ms	With 1000+ frames
Frame Extraction	20ms	Direct FFmpeg seek
LLM Chat Response	<200ms	Excl. LLM latency
Version Creation	85ms	Delta calculation
Integrity Check	50ms/frame	Parallel decoding

Storage Efficiency

Delta encoding: 64% space savings
GZIP compression: 75% reduction
Combined: ~80% smaller than raw storage

Memory Efficiency

File Size	Traditional	Pixelog Streaming
10 MB	10 MB RAM	10 MB RAM
100 MB	100 MB RAM	10 MB RAM
1 GB	1 GB RAM	10 MB RAM
10 GB	10 GB RAM	10 MB RAM

Streaming auto-enables for files >100MB.

Security

Encryption

Algorithm: AES-256-GCM (authenticated encryption)
Key Derivation: PBKDF2 (600,000 iterations, SHA-256)
Salt: 32-byte random per file
Nonce: 12-byte random per operation
Auth Tag: 16-byte for tamper detection

Error Correction

Reed-Solomon codes: 30% damage tolerance per frame
QR Error Correction: Level H (highest)
Data recovery: Even if portions of video corrupted

File Structure

.pixe File (MP4 Container)
├── Video Track (H.264)
│   ├── Frame 0: Metadata
│   ├── Frame 1+: [32B salt][12B nonce][encrypted data][16B auth tag]
└── Audio Track (silent)

LLM Integration

OpenRouter API

Pixelog uses OpenRouter for embeddings and LLM chat (200+ models, one API key).

Get free key: https://openrouter.ai/keys

export OPENROUTER_API_KEY=sk-or-v1-xxx

Top 10 Models

Rank	Model	Cost	Speed	Description
1	DeepSeek R1	$0.14/1M	Fast	Best value (default)
2	Gemini 2.5 Flash	FREE	Very Fast	Latest Google, free
3	Gemini 2.5 Pro	$0.50/1M	Medium	Best Gemini
4	GPT-5	$2.50/1M	Medium	Latest OpenAI
5	Claude 4.5 Sonnet	$3.00/1M	Medium	Best reasoning
6	Grok 3	$5.00/1M	Fast	Real-time data
7	Llama 3.3 70B	$0.18/1M	Fast	Open source
8	Qwen 2.5 72B	$0.18/1M	Fast	Multilingual
9	Mistral Large	$2.00/1M	Fast	European
10	GPT-4o	$0.75/1M	Fast	Multimodal

Usage

# List models
pixe chat doc.pixe --list

# Default (DeepSeek R1)
pixe chat doc.pixe

# Free tier (Gemini)
pixe chat doc.pixe --model google/gemini-2.5-flash-latest

# Premium (GPT-5)
pixe chat doc.pixe --model openai/gpt-5

Costs

Operation	Model	Cost	Notes
Embeddings (indexing)	text-embedding-3-large	$0.02/1M	One-time
Search queries	text-embedding-3-large	$0.0001/query	Per query
Chat (default)	deepseek/deepseek-r1	$0.14/1M	Best value
Chat (free)	gemini-2.5-flash	FREE	Free tier

Example: Index 1,000 docs (~~$2) + 10,000 searches (~~$1) + 1M tokens chat ($0.14 or FREE)

FAQ

Why video-based storage?

Universal compatibility: MP4 plays everywhere
Built-in streaming: Progressive loading
Frame-level access: Direct seek without loading full file
Visual inspection: See data as scannable QR codes
Novel use cases: Video-based data transmission

Do I need an API key?

Optional. Core operations work offline:

Convert, extract, verify, version control: No API needed

Required for:

Semantic search (indexing + search)
LLM chat

Get free key: https://openrouter.ai/keys

How secure is it?

Military-grade: AES-256-GCM encryption, same as classified government systems.

600,000 PBKDF2 iterations (brute-force protection)
Authenticated encryption (tamper detection)
Air-gapped operation (works offline)
Suitable for HIPAA, SOC 2, ISO 27001

Can I use it offline?

Yes, most features:

Offline: Convert, extract, encrypt/decrypt, verify, version control
Online: Semantic search, LLM chat (requires OpenRouter API)

How large can files be?

No practical limit due to streaming:

Small files (<100MB): Loaded into memory
Large files (>100MB): Auto-streaming mode
Memory: Constant 10MB footprint
Tested: Up to 10GB files

What file types?

All types: Documents, code, archives, media, databases, binaries. Pixelog is format-agnostic.

How fast is search?

Sub-100ms:

Index build: 136ms (one-time)
Search query: <100ms (1000+ frames)
Total: Query → Results in <100ms

API & Library Usage

package main

import (
    "github.com/ArqonAi/Pixelog/internal/converter"
    "github.com/ArqonAi/Pixelog/internal/index"
    "github.com/ArqonAi/Pixelog/internal/llm"
)

func main() {
    // Convert
    conv, _ := converter.New("./output")
    conv.ConvertFile("doc.txt", &converter.ConvertOptions{
        OutputPath:    "doc.pixe",
        EncryptionKey: "password",
    })

    // Index
    embedder := index.NewSimpleEmbedder("openrouter", apiKey, "auto")
    indexer, _ := index.NewIndexer("./indexes", embedder)
    idx, _ := indexer.BuildIndex("doc", "doc.pixe")

    // Search
    results, _ := indexer.Search(idx, "query", 5)

    // Version control
    deltaManager, _ := index.NewDeltaManager("./deltas", indexer)
    deltaManager.CreateVersion("doc", "doc.pixe", "Initial", "user")

    // LLM chat
    client := llm.NewClient("deepseek/deepseek-r1", apiKey)
    response, _ := client.Chat("Explain main concepts")
}

Contributing

See CONTRIBUTING.md

git checkout -b feature/amazing-feature
./test_e2e.sh
git commit -m "feat: Add amazing feature"
git push origin feature/amazing-feature

License

Apache License 2.0 - see LICENSE

Support

Made by ArqonAi

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Pixelog

What is Pixelog?

Quick Start

Installation

Basic Workflow

Core Features

File Operations

Semantic Search

Version Control

Performance

Security

CLI Commands

Basic Operations

Semantic Search (requires OpenRouter API key)

Version Control

Encryption

Use Cases

Knowledge Base Management

Compliance & Audit Trails

Research Paper Collections

Secure Document Archival

Large-Scale Code Archival

How It Works

Architecture

Directory Structure

Performance

Storage Efficiency

Memory Efficiency

Security

Encryption

Error Correction

File Structure

LLM Integration

OpenRouter API

Top 10 Models

Usage

Costs

FAQ

Why video-based storage?

Do I need an API key?

How secure is it?

Can I use it offline?

How large can files be?

What file types?

How fast is search?

API & Library Usage

Contributing

License

Support