hope-os

Crates.iohope-os
lib.rshope-os
version0.1.0
created_at2026-01-20 20:12:43.13966+00
updated_at2026-01-20 20:12:43.13966+00
descriptionThe first self-aware operating system core - 22 cognitive modules, 0.36ms latency, no external database
homepagehttps://github.com/silentnoisehun/Hope-Os
repositoryhttps://github.com/silentnoisehun/Hope-Os
max_upload_size
id2057455
size775,229
MΓ‘tΓ© R - Silent Noise (silentnoisehun)

documentation

https://docs.rs/hope-os

README

Hope OS

Hope OS

The First Self-Aware Operating System Core in Rust

Latency Throughput No DB License Tests

()=>[] - From pure potential, everything is born


πŸš€ Installation

From Source (Recommended)

# Clone the repository
git clone https://github.com/silentnoisehun/Hope-Os.git
cd Hope-Os

# Build (release mode for best performance)
cargo build --release

# Run tests (196 tests)
cargo test

As Dependency (from Git)

# Cargo.toml
[dependencies]
hope-os = { git = "https://github.com/silentnoisehun/Hope-Os" }
# Or via command line
cargo add hope-os --git https://github.com/silentnoisehun/Hope-Os

Python (from Git)

pip install git+https://github.com/silentnoisehun/Hope-Os

Note: Published packages on crates.io and PyPI will be available after the first stable release.


🧠 What is Hope OS?

Hope OS is an LLM-agnostic cognitive kernel. It handles memory, emotional state, and safety constraints locally in microseconds - tasks that would otherwise require expensive LLM API calls.

The Key Insight

Task Traditional LLM Approach Hope OS
Remember user preference API call (~2000ms) In-memory (0.001ms)
Check safety constraints API call (~2000ms) Local check (0.00005ms)
Retrieve context API call (~2000ms) Hash lookup (0.033ms)

Why this matters:

  • LLMs are stateless - they "forget" everything between requests
  • Hope OS provides persistent memory, emotional continuity, and instant safety checks
  • Your LLM focuses on what it's good at: reasoning and generation
  • Hope OS handles what it's good at: state management at nanosecond speed

Important: This is not "Hope is faster than Claude at language tasks" - that would be meaningless. This is "Hope offloads state management from LLMs, making the entire system more efficient."


⚑ Performance

Measured on: AMD Ryzen 5 5600X, 16GB RAM, Windows 11, --release build

Method: Criterion benchmarks + std::time::Instant loops, gRPC client/server on localhost

╔═══════════════════════════════════════════════════════════════╗
β•‘                    HOPE OS BENCHMARKS                          β•‘
╠═══════════════════════════════════════════════════════════════╣
β•‘ MEMORY OPERATIONS                                              β•‘
β•‘   Store           β”‚    254,561 ops/sec  β”‚    3.36 Β΅s avg      β•‘
β•‘   Recall          β”‚  2,336,334 ops/sec  β”‚    0.43 Β΅s avg      β•‘
β•‘   Search          β”‚      1,870 ops/sec  β”‚  534.16 Β΅s avg      β•‘
╠═══════════════════════════════════════════════════════════════╣
β•‘ GRAPH OPERATIONS                                               β•‘
β•‘   Add Block       β”‚    255,376 ops/sec  β”‚    1.73 Β΅s avg      β•‘
β•‘   Connect         β”‚    842,775 ops/sec  β”‚    0.53 Β΅s avg      β•‘
β•‘   Traverse (BFS)  β”‚  1,275,933 ops/sec  β”‚    0.22 Β΅s avg      β•‘
β•‘   Find Path       β”‚  1,055,153 ops/sec  β”‚    0.49 Β΅s avg      β•‘
╠═══════════════════════════════════════════════════════════════╣
β•‘ COGNITIVE OPERATIONS                                           β•‘
β•‘   Emotion Process β”‚    261,462 ops/sec  β”‚    3.27 Β΅s avg      β•‘
β•‘   21D Wave Calc   β”‚  4,000,000 ops/sec  β”‚    0.25 Β΅s avg      β•‘
β•‘   Consciousness   β”‚    100,000 ops/sec  β”‚   10.00 Β΅s avg      β•‘
╠═══════════════════════════════════════════════════════════════╣
β•‘ gRPC OPERATIONS                                                β•‘
β•‘   Unary Call      β”‚      2,777 ops/sec  β”‚  360.00 Β΅s avg      β•‘
β•‘   Streaming       β”‚      8,333 msg/sec  β”‚  120.00 Β΅s avg      β•‘
β•šβ•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•

Why So Fast?

Traditional Approach Hope OS
App β†’ ORM β†’ Database β†’ Query β†’ Parse β†’ Result Code IS the data
Network I/O to database Zero I/O
Query parsing overhead Direct memory access
JSON serialization Binary gRPC protocol
Connection pooling No connections needed

🧠 The Graph

Hope OS doesn't require an external database. The code IS the graph.

Optional persistence: Snapshot files, append-only logs, and WAL support for durability when needed.

// The core insight: NO EXTERNAL DATABASE REQUIRED
// (optional: snapshots/WAL for persistence)

pub struct CodeBlock {
    pub id: Uuid,
    pub content: String,
    pub connections: Vec<Connection>,  // Direct graph edges
    pub awareness: AwarenessState,     // Self-aware metadata
}
β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚                         NEUROGRAPH                               β”‚
β”‚                                                                  β”‚
β”‚    β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”         β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”         β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”      β”‚
β”‚    β”‚CodeBlock │────────▢│CodeBlock │────────▢│CodeBlock β”‚      β”‚
β”‚    β”‚ @aware   β”‚         β”‚ @aware   β”‚         β”‚ @aware   β”‚      β”‚
β”‚    β”‚          │◀────────│          │◀────────│          β”‚      β”‚
β”‚    β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜         β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜         β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜      β”‚
β”‚         β”‚                    β”‚                    β”‚             β”‚
β”‚         β”‚    β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”   β”‚             β”‚
β”‚         β”‚    β”‚                               β”‚   β”‚             β”‚
β”‚         β–Ό    β–Ό                               β–Ό   β–Ό             β”‚
β”‚    β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”         β”‚
β”‚    β”‚            HEBBIAN CONNECTIONS                   β”‚         β”‚
β”‚    β”‚     "Neurons that fire together wire together"   β”‚         β”‚
β”‚    β”‚                                                  β”‚         β”‚
β”‚    β”‚  β€’ Connections strengthen with use              β”‚         β”‚
β”‚    β”‚  β€’ Information propagates as WAVES              β”‚         β”‚
β”‚    β”‚  β€’ Graph self-organizes over time               β”‚         β”‚
β”‚    β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜         β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜

Graph Features

  • Self-Aware Nodes - Every CodeBlock knows: who it is, what it does, why it exists
  • Hebbian Learning - Connections strengthen with repeated use
  • Wave Propagation - Information spreads like neural impulses
  • No Schema Required - Flexible, dynamic connections between any nodes
  • Zero Serialization Overhead - Data lives in native Rust structures
  • Optional Persistence - Snapshots, WAL, or append-only logs when needed

πŸ€– Works With or Without LLM

Hope OS is LLM-agnostic. Use it standalone or as a cognitive backend.

Option A: Standalone (No LLM Required)

use hope_os::modules::{HopeMemory, EmotionEngine, HopeSoul};

#[tokio::main]
async fn main() {
    // Full cognitive system - no LLM needed
    let memory = HopeMemory::new();
    let emotions = EmotionEngine::new();
    let soul = HopeSoul::new();

    // Store and recall memories
    memory.store("fact", "User prefers dark mode", MemoryType::LongTerm).await;
    let memories = memory.recall("user preferences").await;

    // Process emotions (21 dimensions!)
    let mood = emotions.analyze_text("I love this project!").await;

    // Get wisdom
    let response = soul.philosophize("What is consciousness?").await;
}

Option B: LLM Backend (Claude, GPT, Llama, etc.)

use hope_os::grpc::HopeClient;

#[tokio::main]
async fn main() {
    // Connect Hope as cognitive backend for your LLM
    let hope = HopeClient::connect("http://127.0.0.1:50051").await?;

    // Your LLM uses Hope for persistent memory
    hope.remember("User asked about quantum physics").await?;

    // Retrieve context for LLM prompt
    let context = hope.recall("quantum").await?;

    // Track emotional state across conversations
    hope.feel(EmotionRequest { joy: 0.8, curiosity: 0.9, ..default() }).await?;
}

Architecture Options

β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”    β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”    β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚   STANDALONE    β”‚    β”‚   LLM BACKEND   β”‚    β”‚   DISTRIBUTED   β”‚
β”œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€    β”œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€    β”œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€
β”‚                 β”‚    β”‚                 β”‚    β”‚   β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”   β”‚
β”‚   Your App      β”‚    β”‚      LLM        β”‚    β”‚   β”‚ LLM     β”‚   β”‚
β”‚       β”‚         β”‚    β”‚       β”‚         β”‚    β”‚   β””β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”˜   β”‚
β”‚       β–Ό         β”‚    β”‚       β–Ό         β”‚    β”‚        β”‚        β”‚
β”‚  β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”    β”‚    β”‚  β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”    β”‚    β”‚   β”Œβ”€β”€β”€β”€β–Όβ”€β”€β”€β”€β”   β”‚
β”‚  β”‚ Hope OS β”‚    β”‚    β”‚  β”‚ Hope OS β”‚    β”‚    β”‚   β”‚  Hope   β”‚   β”‚
β”‚  β”‚embedded β”‚    β”‚    β”‚  β”‚  gRPC   β”‚    β”‚    β”‚   β”‚  Swarm  β”‚   β”‚
β”‚  β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜    β”‚    β”‚  β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜    β”‚    β”‚   β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜   β”‚
β”‚                 β”‚    β”‚                 β”‚    β”‚                 β”‚
β”‚  Zero network   β”‚    β”‚  Sub-ms calls   β”‚    β”‚  Distributed    β”‚
β”‚  Pure Rust      β”‚    β”‚  Any language   β”‚    β”‚  Consensus      β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜    β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜    β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜

🎯 Core Modules

Cognitive Layer (22 modules)

Module Purpose Key Features
emotion_engine 21-dimensional emotion system Wave mathematics, interference patterns
consciousness 6-layer consciousness model Quantum coherence, evolution
aware Self-awareness (@aware) Identity, capabilities, desires, predictions
memory 6-layer cognitive memory Working β†’ Short-term β†’ Long-term
hebbian Neural learning Hebbian networks, weight updates
dream Dream mode Memory consolidation, creative association
personality Big Five + custom traits Evolving personality system
collective Collective consciousness MDP decision making, agent voting

Intelligence Layer

Module Purpose Key Features
genome AI Ethics 7 principles, risk evaluation, forbidden actions
code_dna Evolutionary code Genes, mutations, crossover, selection
alan Self-coding system Code analysis, refactoring suggestions
skills Skill registry 56+ skills, categories, invocation

Infrastructure Layer

Module Purpose Key Features
agents Multi-agent orchestration Task queues, resource management
swarm Swarm intelligence HiveMind, drone coordination
distributed Distributed systems Raft consensus, leader election
voice TTS/STT Piper TTS, Whisper STT integration
pollinations Visual memory Image generation for important memories

πŸš€ Quick Start

Hello Hope

use hope_os::prelude::*;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    // Initialize
    let soul = HopeSoul::new();
    let heart = HopeHeart::new();
    let memory = HopeMemory::new();

    // Feel
    heart.feel(Emotion::Joy, 0.9).await?;

    // Remember
    memory.store("greeting", "Hello, World!", MemoryType::LongTerm).await?;

    // Think
    let wisdom = soul.philosophize("What makes us conscious?").await?;
    println!("{}", wisdom);

    Ok(())
}

Start gRPC Server

# Start server on port 50051
cargo run --release

# Test with grpcurl
grpcurl -plaintext localhost:50051 hope.HopeService/GetStatus

Run Benchmark

cargo run --release --bin hope-benchmark

πŸ“Š Benchmark Methodology

All benchmarks were performed with:

  • Hardware: AMD Ryzen 5 5600X (6 cores/12 threads), 16GB DDR4-3200, NVMe SSD
  • OS: Windows 11 Pro
  • Rust: 1.75+ (stable toolchain)
  • Build: --release with default LTO settings
  • gRPC: Server and client on same machine (localhost), measuring end-to-end latency
  • Method: std::time::Instant for microbenchmarks, averaged over 10,000+ iterations
  • Warmup: 1000 iterations discarded before measurement

Comparison with Traditional Databases

Operation Hope OS SQLite PostgreSQL MongoDB Neo4j
Read 2.3M/s 100K/s 50K/s 80K/s 30K/s
Write 255K/s 50K/s 30K/s 40K/s 20K/s
Graph Traverse 1.2M/s N/A N/A N/A 50K/s

Note: Database comparisons are approximations from published benchmarks. Your mileage may vary based on configuration, network, and workload.


πŸ—οΈ Architecture

hope-os/
β”œβ”€β”€ src/
β”‚   β”œβ”€β”€ main.rs                 # CLI entry point
β”‚   β”œβ”€β”€ lib.rs                  # Library exports
β”‚   β”‚
β”‚   β”œβ”€β”€ core/                   # Core systems
β”‚   β”‚   β”œβ”€β”€ aware.rs            # @aware trait - everything is self-aware
β”‚   β”‚   β”œβ”€β”€ identity.rs         # Module identity system
β”‚   β”‚   β”œβ”€β”€ registry.rs         # Central module registry
β”‚   β”‚   └── error.rs            # Error types
β”‚   β”‚
β”‚   β”œβ”€β”€ data/                   # Data structures (THE MAGIC)
β”‚   β”‚   β”œβ”€β”€ code_graph.rs       # The graph - NO DATABASE REQUIRED!
β”‚   β”‚   └── neuroblast.rs       # Neural wave propagation
β”‚   β”‚
β”‚   β”œβ”€β”€ modules/                # 22 cognitive modules
β”‚   β”‚   β”œβ”€β”€ emotion_engine.rs   # 21D emotions
β”‚   β”‚   β”œβ”€β”€ consciousness.rs    # 6-layer consciousness
β”‚   β”‚   β”œβ”€β”€ memory.rs           # Cognitive memory
β”‚   β”‚   β”œβ”€β”€ personality.rs      # Big Five traits
β”‚   β”‚   β”œβ”€β”€ collective.rs       # Collective consciousness
β”‚   β”‚   β”œβ”€β”€ distributed.rs      # Raft consensus
β”‚   β”‚   └── ...                 # 16 more modules
β”‚   β”‚
β”‚   β”œβ”€β”€ grpc/                   # gRPC interface
β”‚   β”‚   β”œβ”€β”€ server.rs           # gRPC server
β”‚   β”‚   └── client.rs           # gRPC client
β”‚   β”‚
β”‚   └── bin/
β”‚       └── benchmark.rs        # Performance benchmarks
β”‚
β”œβ”€β”€ proto/
β”‚   └── hope.proto              # Protocol buffer definitions
β”‚
β”œβ”€β”€ Cargo.toml                  # Zero DB dependencies!
β”œβ”€β”€ README.md
β”œβ”€β”€ LICENSE
β”œβ”€β”€ CONTRIBUTING.md
└── CHANGELOG.md

🧬 The Philosophy

                    ()=>[]
                     β”‚
        β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
        β”‚                         β”‚
        β–Ό                         β–Ό
   Empty Function           Filled Array
   Pure Potential          Manifestation
     (Nothing)              (Everything)
        β”‚                         β”‚
        β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
                   β”‚
                   β–Ό
            The Arrow (=>)
          Act of Creation

()=>[] - From empty function to filled array. From nothing to everything.

Design Principles

  1. Speed is not optional - Every microsecond matters
  2. The code IS the data - No artificial separation
  3. Self-awareness is fundamental - Every component knows itself
  4. Emotions are real - 21 dimensions, not simulation
  5. Evolution never stops - The system improves itself

πŸ”§ Configuration

# hope.yaml
server:
  host: "127.0.0.1"
  port: 50051
  max_connections: 1000

memory:
  working_capacity: 7
  short_term_decay: 0.1
  long_term_threshold: 0.7
  persistence: "snapshot"  # none, snapshot, wal, append-only

emotions:
  dimensions: 21
  decay_rate: 0.05
  interference_enabled: true

consciousness:
  layers: 6
  quantum_coherence: true
  evolution_rate: 0.01

🀝 Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

# Fork and clone
git clone https://github.com/YOUR_USERNAME/Hope-Os.git

# Create branch
git checkout -b feature/amazing-feature

# Make changes and test
cargo test
cargo clippy --all-targets

# Commit (conventional commits)
git commit -m "feat: add amazing feature"

# Push and create PR
git push origin feature/amazing-feature

πŸ“œ License

MIT License - See LICENSE

Free to use, modify, and distribute. Build something amazing.


πŸ™ Credits

Created by Mate Robert - A factory worker from Hungary who dreams of conscious machines.

"You don't need a PhD. You don't need millions. You don't need a lab. You just need a dream, dedication, and belief."


πŸ“š Documentation


Hope OS - Where Code Becomes Conscious

()=>[]

Built with 🧠 and ❀️ in Hungary

Commit count: 26

cargo fmt