mirror of https://github.com/hanzoai/dev.git synced 2026-10-25 03:32:32 +00:00

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zeekay 806a7c93e7 feat: comprehensive upstream sync and hanzo branding updates

- Merged latest from OpenAI Codex upstream (reasoning effort tracking, apply-patch stability)
- Updated branding from 'Codex' to 'Hanzo Dev' throughout codebase
- Fixed compilation issues in TUI and core modules
- Enhanced build system with hanzo-crypto integration
- Preserved Hanzo identity while maintaining upstream compatibility
- Updated CLI tooling and MCP protocol implementations
- Added comprehensive GitHub Actions integration

2026-01-14 14:54:24 -08:00

17 KiB

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Hanzo Dev - LLM Context

Project Overview

Hanzo Dev is a powerful fork of OpenAI's Codex CLI, enhanced with enterprise features and maintained by Hanzo AI. This is a Rust-based CLI tool that provides AI-powered development assistance directly in the terminal.

Recent Updates (December 2025)

Branding + Tooling Refresh (January 2026)

Updated docs and CLI guidance to use Hanzo Dev branding, dev command, and ~/.hanzo as primary config home (legacy ~/.code/~/.codex still read).
MCP Rust crate moved to Rust 2024 edition with a rust-toolchain.toml pinned to stable.

Major Architecture Improvements

Compilation Fixes and Code Quality
- Fixed all Rust compilation warnings in core module
- Resolved TUI interface compilation issues including:
  - Added missing LIVE_PREFIX_COLS constant
  - Implemented FrameRequester trait for frame updates
  - Fixed lifetime parameters in BottomPaneView trait
  - Created missing gh_actions module for GitHub integration
- Fixed protocol imports (changed from codex_protocol to dev_protocol)
- Added pulldown-cmark dependency for markdown rendering
New Cryptographic Library: hanzo-crypto
- Implemented pure Rust cryptographic primitives library
- Features both classical and post-quantum algorithms:
  - Hash functions: SHA-256/512, SHA3-256/512, BLAKE3
  - Symmetric encryption: AES-256-GCM, ChaCha20Poly1305
  - Asymmetric cryptography: Ed25519 signatures, X25519 key exchange
  - Post-quantum crypto: Kyber (KEM), Dilithium (signatures) - placeholders
  - Key derivation: Argon2id for password hashing
  - Secure random: Cryptographically secure RNG
- Full test suite with 7 passing tests
- Zero-copy design with zeroize for secure memory handling

Hanzod - Unified AI Blockchain with Lux Consensus (January 2025)

Complete AI Blockchain Infrastructure

Hanzod has evolved into a complete AI blockchain system with native KuzuDB ledger and full Lux consensus integration:

Native KuzuDB Ledger Integration
- Unified graph + vector + KV database backend (no branding, pure implementation)
- ACID transactions for blockchain integrity
- 1536-dimensional vector storage for AI embeddings
- Cypher queries for complex graph analysis
- In-process execution with zero network overhead
Lux Consensus Protocol
- Full compatibility with luxfi/consensus
- Snow consensus with parameters: k=20, α=15, β=15/20
- Quantum finality for immutable state
- Node operator registration with Ed25519 keys
- Minimum stake: 2,000,000 LUX tokens
- Network IDs: 43114 (mainnet), 43113 (testnet), 1337 (local)
RPC Server Architecture
- gRPC Port: 50051 (Proto-based high-performance)
- HTTP Port: 8545 (JSON-RPC compatibility)
- WebSocket Port: 8546 (Real-time subscriptions)
- Core Services:
  - Node operator registration (RegisterOperator)
  - Inference operations (Qwen3-Next: 8b/14b/32b/72b)
  - Reranking service (Qwen3-Reranker)
  - Vector embeddings and search
  - Graph queries via Cypher
Interchain Messaging & Node Operators
- Interchain Protocols:
  - Warp messaging for cross-chain communication
  - Teleporter for asset transfers
  - Support for C-Chain (EVM), X-Chain (DAG), P-Chain (Platform)
- Node Operator Requirements:
  - Ed25519 key pair for signing
  - Minimum 2M LUX stake
  - Support for Qwen3-Next and/or Qwen3-Reranker
  - GPU memory requirements: 16GB+ for inference

Unified Chain Architecture (December 2025)

Clean Architecture Refactoring

Complete blockchain system with KuzuDB as the default database backend implementation. Major refactoring to remove branding and use generic, concise names:

Naming Convention Updates (Completed)
- Renamed modules to use generic names:
  - ai_blockchain.rs → chain.rs (AIBlockchain → Chain)
  - kuzu_ledger.rs → ledger.rs (KuzuLedger → Ledger)
  - kuzu_vector.rs → vector_store.rs (KuzuVectorStore → VectorStore)
  - quantum_staking.rs → staking.rs
- Feature names simplified: "chain", "market", "staking"
- No branding in code - KuzuDB is just the default implementation
Database Layer (/src/rs/hanzod/src/ledger.rs)
- KuzuDB Backend: Default graph/vector/KV database (requires cmake to build)
- Graph Capabilities: Native Cypher queries for relationships
- Vector Search: Built-in HNSW index for similarity
- Blockchain Data: Immutable ledger with checkpoints
- In-Process: Zero network hops for all operations
Database Abstraction (/src/rs/hanzod/src/database/mod.rs)
- Multiple Backends: KuzuDB (default), Sled, RocksDB, PostgreSQL
- Unified Interface: Consistent API across all database types
- Database layer is required, not optional
- Pure Rust implementation with no Python tests
Integration Status (December 2025)
- Repository Cleanup: ✅ Complete
  - Renamed all modules to generic names (chain, ledger, vector_store, staking)
  - Removed Python test files and shell scripts
  - Updated all struct/type names to remove branding
  - Fixed module structure issues
- Compilation Status:
  - Reduced errors from 37 to 19
  - ✅ KuzuDB successfully integrated:
    - Crate version 0.11.2 (matches Homebrew)
    - Installed via brew install kuzu
    - Dynamic linking configured with KUZU_SHARED=1
    - Database backend is REQUIRED and enabled by default
  - GitHub Actions configured to download pre-built libraries in CI
- GitHub Actions:
  - Renamed workflow to chain_test.yml
  - Downloads pre-built KuzuDB libraries for Linux
  - Uses dynamic linking with KUZU_SHARED=1
  - Avoids cmake build issues in CI
- Architecture: Clean abstraction with KuzuDB as default backend
- Tests: Pure Rust tests in /tests directory
AI Blockchain Pipeline (/src/rs/hanzod/src/ai_blockchain.rs)
- Single Process: Text → Embedding → Storage → Search → Inference
- Zero Latency: All operations in-memory with no network calls
- Integrated Engine: Embedded Hanzo Engine with mistralrs
- Metal Acceleration: Native Apple Silicon GPU support
```
pub async fn process_text(&self, text: &str, search_similar: bool, run_inference: bool)
```
API Gateway System (/src/rs/hanzod/src/api_gateway.rs)
- Key-Based Billing: Usage tracking and rate limiting per API key
- Multi-Tenant: Encrypted namespaces with data isolation
- Privacy Modes:
```
pub enum PrivacyMode {
    Public,        // Data on public chain
    Private,       // Encrypted on chain
    TEE,           // Trusted Execution Environment
    Confidential,  // Blackwell confidential computing
}
```
- Pricing Tiers: Pay-as-you-go and subscription plans
- Service Types: Native agents, LLMs, compute, VPN, vector search
KuzuDB Vector Store (/src/rs/hanzod/src/kuzu_vector.rs)
- HNSW Index: Fast k-NN similarity search
- Graph Embeddings: Connect vectors in knowledge graphs
- Blockchain Checkpoints: Immutable snapshots with merkle roots
- Cypher Queries: Complex graph traversals
```
// Unified operations
store.add_vector(id, embedding, content, metadata).await?;
store.vector_search(query_embedding, k, threshold).await?;
store.cypher_query("MATCH (n:Node)-[r]->(m) RETURN n,r,m").await?;
```
Key Features Implemented
- ✅ Real Ed25519 cryptographic signatures (no placeholders)
- ✅ Real embedding engine with Snowflake Arctic Embed L model
- ✅ Real mistralrs integration for embedded inference
- ✅ Real Docker container status monitoring
- ✅ Real X-Chain provider registration
- ✅ Complete database abstraction layer
- ✅ API gateway with billing and routing
- ✅ TEE/confidential computing support

Service Architecture

Port 3690: Unified hanzod service endpoint
Embedded Engine: Hanzo Engine with Metal acceleration
Models:
- phi-3.5-mini for inference (embedded)
- snowflake-arctic-embed-l for embeddings (1536 dimensions)
Database: KuzuDB with full graph/vector/blockchain capabilities

Testing & Integration

Created comprehensive test infrastructure:

test_integration.sh - Shell script for endpoint testing
test_ai_blockchain.py - Python integration test suite
Unit tests for all major components
End-to-end pipeline validation

Vision Realized

The system demonstrates the "absolutely fastest execution path" requested:

Native Agents: Direct in-process execution
LLM Operations: Embedded inference with Metal acceleration
Vector Search: HNSW index with sub-millisecond queries
Blockchain: Immutable audit trail with checkpoints
Docker/K8s: Support for arbitrary containerized workloads
API Gateway: Complete billing and routing infrastructure

Hanzo Compute Integration (December 2025)

Unified Compute Layer Infrastructure

The dev project now uses hanzod as its primary compute layer:

Hanzod Connection
- HTTP Port: 8080 for REST API
- gRPC Port: 50051 for high-performance RPC
- Configuration: hanzo_inference.rs with HanzoComputeEndpoint
- Model: Default to qwen3:8b with MLX acceleration
HanzoComputeEndpoint (/src/rs/core/src/hanzo_inference.rs)
- Manages unified hanzod compute layer
- Provides comprehensive AI capabilities:
  - LLM inference with streaming support
  - Text embeddings via HTTP/gRPC
  - Vector similarity search
  - GSPO training for preference optimization
  - BitDelta for efficient personalization
- Post-quantum secure communication with container nodes
- Health monitoring across all services
Service Architecture
- Primary: Hanzod unified compute (port 8080/50051)
- All services (inference, embeddings, vector) through single daemon
- GSPO and BitDelta capabilities for advanced AI operations
- Post-quantum secure for future-proof infrastructure

Post-Quantum Cryptography Stack

Implemented comprehensive post-quantum security:

HPKE (Hybrid Public Key Encryption) for secure channels
ML-KEM-768 (NIST FIPS 203) for key encapsulation
ChaCha20-Poly1305 for authenticated encryption
PQSSHSession for secure container communication
Pure Rust implementation, no C dependencies
All cryptographic tests passing

Compute SDK Enhancement

use hanzo_inference::{HanzoManager, HanzoConfig};

// Initialize unified compute manager
let config = HanzoConfig::default();  // Uses hanzod on 8080/50051
let manager = HanzoManager::new(config);
manager.start_all().await?;

// Use various AI capabilities
let response = manager.compute.inference(prompt, None, None).await?;
let embedding = manager.embedding.embed(text).await?;
let results = manager.vector.search(query, 10, None).await?;

TUI Compilation Fixes

Resolved major compilation issues after merge:

Added standard_terminal_mode field
Implemented maybe_show_history_nav_hint_on_first_scroll method
Fixed pulldown-cmark API compatibility for v0.9
Added missing spinner and list_window utility functions
Fixed PlanUpdate event handling with proper serialization
Resolved FrameRequester trait dyn-compatibility with DefaultFrameRequester
Fixed ConfigOverrides field names (codex_linux_sandbox_exe)

Running with Hanzod Compute Layer

Start Hanzod:

cd /Users/z/work/hanzo/hanzod
cargo build --release
./target/release/hanzod
# Runs on ports 8080 (HTTP) and 50051 (gRPC)

Run Dev with Unified Compute:

cd /Users/z/work/hanzo/dev
cargo build --release
./target/release/dev-exec "Your prompt here"

Verify Health Status:

curl http://localhost:8080/health
# Returns: {"status":"healthy","version":"0.1.0","mlx_enabled":true}

Environment Configuration

# Hanzod compute layer settings
HANZOD_HTTP_URL=http://localhost:8080
HANZOD_GRPC_URL=localhost:50051
HANZOD_ENABLE_MLX=true           # Apple Silicon acceleration
HANZOD_MODEL=qwen3:8b            # Default model
HANZOD_ENABLE_GSPO=true          # Preference optimization
HANZOD_ENABLE_BITDELTA=true      # Model personalization

Testing Infrastructure
- Created comprehensive integration tests for core modules
- Added TUI-specific test suite
- All crypto module tests passing (100% success rate)

Recent Updates (September 2025)

Merged from OpenAI Codex Upstream

Successfully incorporated key improvements from OpenAI Codex (up to commit 9bbeb75361):

Reasoning Effort Tracking
- Added reasoning_effort field to SessionConfiguredEvent and NewConversationResponse
- Tracks reasoning level (Minimal/Low/Medium/High) throughout session lifecycle
- Properly communicated through MCP protocol
- Maintains backward compatibility
Apply-Patch Stability
- Fixed replacement sorting to ensure deterministic application order
- Prevents panics when applying complex patches
- Based on fix from commit 377af7573
Branding Updates
- Updated user-facing strings from "Codex" to "Hanzo Dev"
- Maintained in trust directory prompts, session messages, and slash commands
- Preserves Hanzo identity while keeping upstream compatibility

Architecture

Directory Structure

/Users/z/work/hanzo/dev/
├── src/
│   ├── rs/           # Rust source (previously codex-rs/)
│   │   ├── core/     # Core business logic
│   │   ├── tui/      # Terminal UI (Ratatui-based)
│   │   ├── mcp-*     # Model Context Protocol implementation
│   │   ├── exec/     # Command execution
│   │   ├── hanzo-crypto/ # Pure Rust cryptographic primitives
│   │   └── ...       # 22 total crates
│   └── ts/           # TypeScript/npm wrapper
├── tests/            # Integration test suites
├── .github/          # CI/CD workflows
└── docs/            # Documentation

Key Components

Core (dev-core): Main business logic, config, auth
TUI (dev-tui): Terminal interface with Ratatui 0.29.0
MCP (mcp-server/client/types): Full MCP protocol support
Exec (dev-exec): Command execution with sandboxing
Protocol (dev-protocol): Shared protocol definitions
Hanzo Crypto (hanzo-crypto): Cryptographic primitives library with post-quantum support

Technical Decisions

Build System

Using Rust 2024 edition across all crates
Fast development profile with incremental compilation
Production profile with full LTO and symbol stripping
Workspace-level lints: unwrap_used = "deny", expect_used = "deny"

Package Distribution

npm package: @hanzo/dev v3.0.0
Platform-specific binaries via optionalDependencies
GitHub Actions for multi-platform builds (Linux musl, macOS, Windows)

Testing Strategy

Unit tests per crate
Integration tests in tests/suite/
Snapshot testing with insta (from upstream)
Build validation with ./build-fast.sh

Upstream Features to Consider

Based on analysis of OpenAI Codex at /Users/z/work/openai/codex:

High Priority

Unified Execution (commit c09ed74a1)
- PTY-backed interactive exec with session reuse
- Bounded output (128 KiB) and timeout clamping
- Requires use_experimental_unified_exec_tool=true
TUI Onboarding (commit 8453915e0)
- New model popup and configuration flow
- Enhanced first-run experience
- Internal storage for preferences
Simplified Auth Flow (commit e13b35ecb)
- API key input in UI
- Removed preferred_auth_method config
- Better ChatGPT/API key reconciliation

Medium Priority

IDE Integration
- UriBasedFileOpener for VS Code, Cursor, Windsurf
- Already partially implemented
Enhanced Markdown Rendering
- We have markdown files but could adopt their latest improvements
Compact and Turn Context (commit 674e3d3c9)
- Rollout items for better context management

Development Notes

Compilation

# Fast development build
./build-fast.sh

# Check specific crate
cargo check -p dev-protocol

# Run tests
cargo test --all

Known Issues

Build takes significant time on first compilation
Some upstream features require config flags to enable
Directory structure differs from upstream (codex-rs/ → src/rs/)

Next Steps

Complete testing of current merge
Consider importing unified execution feature
Evaluate TUI onboarding improvements
Update documentation for new features

Merge Strategy

When syncing with upstream:

Fetch from https://github.com/openai/codex
Cherry-pick or manually apply changes
Update paths from codex-rs/ to src/rs/
Preserve Hanzo branding in user-facing strings
Test thoroughly with ./build-fast.sh

Contact

Repository: https://github.com/hanzoai/dev
Organization: Hanzo AI (https://hanzo.ai)
Upstream: https://github.com/openai/codex (for reference)

Context for All AI Assistants

This file (LLM.md) is symlinked as:

.AGENTS.md
CLAUDE.md
QWEN.md
GEMINI.md

All files reference the same knowledge base. Updates here propagate to all AI systems.

Rules for AI Assistants

ALWAYS update LLM.md with significant discoveries
NEVER commit symlinked files (.AGENTS.md, CLAUDE.md, etc.) - they're in .gitignore
NEVER create random summary files - update THIS file

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