e1691a8d42 feat: configurable hybrid search fusion strategy (#234)
* feat: configurable hybrid search fusion strategy (#169)

Add WeightedScore fusion as an alternative to the default RRF algorithm.
Users can now tune search behavior via env vars (SEARCH_FUSION_STRATEGY,
SEARCH_FTS_WEIGHT, SEARCH_VECTOR_WEIGHT, SEARCH_RRF_K) or by passing
SearchConfig with the new fields. Default behavior (RRF, k=60) is
unchanged.

- Add FusionStrategy enum (Rrf/WeightedScore) to workspace::search
- Add weighted_score_fusion() and fuse_results() dispatcher
- Add config/search.rs with WorkspaceSearchConfig from env vars
- Wire search defaults through Workspace struct
- Update both postgres and libsql backends to use fuse_results()
- Add 7 new tests (4 fusion + 3 config)

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: swap default search weights to match issue #169 spec (0.7 vector / 0.3 FTS)

The issue spec says "0.7/0.3 (vector/keyword) for weighted mode" but
our defaults had fts_weight=0.7, vector_weight=0.3 (inverted). Also
fixes the misleading docstring on weighted_score_fusion that claimed
1/rank normalizes to [0,1].

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: validate weight inputs and update stale doc comments

- Reject NaN, infinite, and negative values for SEARCH_FTS_WEIGHT and
  SEARCH_VECTOR_WEIGHT with a clear ConfigError
- Fix module-level docs that incorrectly claimed WeightedScore
  "normalizes per-method scores to [0,1]"
- Update SearchResult.score doc from "Combined RRF score" to
  strategy-agnostic "Combined fusion score"

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: validate weight setters against NaN/inf/negative values

with_fts_weight() and with_vector_weight() now silently ignore
non-finite (NaN, ±inf) and negative values, matching the env var
validation already in place for SEARCH_FTS_WEIGHT / SEARCH_VECTOR_WEIGHT.

Values > 1.0 remain valid since weights are normalized internally.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: use crate-wide ENV_MUTEX in search config tests

Replace the module-local `ENV_MUTEX` in `search.rs` with a shared
`crate::config::helpers::ENV_MUTEX` to prevent cross-module env races
when `cargo test` runs tests in parallel.

Addresses copilot review comment. Tracked in #245.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: per-strategy weight defaults to match issue #169 spec

RRF mode now defaults to 0.5/0.5 (fts/vector) and WeightedScore
defaults to 0.3/0.7, matching the acceptance criteria in #169.
Previously both modes used 0.3/0.7 uniformly.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: reject both weights=0 in weighted fusion mode

When both SEARCH_FTS_WEIGHT and SEARCH_VECTOR_WEIGHT are 0.0 under
WeightedScore strategy, all scores would be 0.0, producing arbitrary
ordering. RRF mode is unaffected since it ignores weights entirely.

Addresses Copilot review comment. The other comment (rrf_k=0 division
by zero) is a false positive — ranks are 1-based, so k=0 just gives
inverse-rank scoring with no infinity.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: clarify weight doc comments and error key

- SearchConfig field docs: clarify that Default always uses 0.5,
  per-strategy defaults only apply via WorkspaceSearchConfig::resolve()
- WorkspaceSearchConfig field docs: same clarification
- Error key for both-weights-zero now references both env vars

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: remove broken intra-doc links to pub(crate) resolve()

WorkspaceSearchConfig::resolve is pub(crate), so linking to it from
public field docs triggers rustdoc private_intra_doc_links warnings.
Switch to plain-text references.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: add document_path to weighted_score_fusion results

The weighted_score_fusion function was missing the document_path field
added in a recent main branch commit, causing a compile error after rebase.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* chore: trigger CI re-check after rebase

* fix: resolve pre-existing staging fmt and clippy issues

- Fix import ordering in cli/mod.rs (cargo fmt)
- Fix line wrapping in tools/mcp/auth.rs (cargo fmt)
- Move path_routing_tests before MemoryTreeTool to fix
  clippy::items_after_test_module

[skip-regression-check]

* fix: remove duplicate path_routing_tests module after rebase

[skip-regression-check]

---------

Co-authored-by: Claude Opus 4.6 <[email protected]>
2026-03-12 14:49:00 -07:00
2026-02-04 22:09:52 -08:00
2026-02-11 08:31:25 +00:00
2026-02-09 03:00:35 +00:00
2026-02-22 19:08:43 +00:00
2026-02-22 19:08:43 +00:00
2026-02-21 15:14:57 -07:00

IronClaw

IronClaw

Your secure personal AI assistant, always on your side

License: MIT OR Apache-2.0 Telegram: @ironclawAI Reddit: r/ironclawAI

English | 简体中文 | Русский

PhilosophyFeaturesInstallationConfigurationSecurityArchitecture


Philosophy

IronClaw is built on a simple principle: your AI assistant should work for you, not against you.

In a world where AI systems are increasingly opaque about data handling and aligned with corporate interests, IronClaw takes a different approach:

  • Your data stays yours - All information is stored locally, encrypted, and never leaves your control
  • Transparency by design - Open source, auditable, no hidden telemetry or data harvesting
  • Self-expanding capabilities - Build new tools on the fly without waiting for vendor updates
  • Defense in depth - Multiple security layers protect against prompt injection and data exfiltration

IronClaw is the AI assistant you can actually trust with your personal and professional life.

Features

Security First

  • WASM Sandbox - Untrusted tools run in isolated WebAssembly containers with capability-based permissions
  • Credential Protection - Secrets are never exposed to tools; injected at the host boundary with leak detection
  • Prompt Injection Defense - Pattern detection, content sanitization, and policy enforcement
  • Endpoint Allowlisting - HTTP requests only to explicitly approved hosts and paths

Always Available

  • Multi-channel - REPL, HTTP webhooks, WASM channels (Telegram, Slack), and web gateway
  • Docker Sandbox - Isolated container execution with per-job tokens and orchestrator/worker pattern
  • Web Gateway - Browser UI with real-time SSE/WebSocket streaming
  • Routines - Cron schedules, event triggers, webhook handlers for background automation
  • Heartbeat System - Proactive background execution for monitoring and maintenance tasks
  • Parallel Jobs - Handle multiple requests concurrently with isolated contexts
  • Self-repair - Automatic detection and recovery of stuck operations

Self-Expanding

  • Dynamic Tool Building - Describe what you need, and IronClaw builds it as a WASM tool
  • MCP Protocol - Connect to Model Context Protocol servers for additional capabilities
  • Plugin Architecture - Drop in new WASM tools and channels without restarting

Persistent Memory

  • Hybrid Search - Full-text + vector search using Reciprocal Rank Fusion
  • Workspace Filesystem - Flexible path-based storage for notes, logs, and context
  • Identity Files - Maintain consistent personality and preferences across sessions

Installation

Prerequisites

  • Rust 1.85+
  • PostgreSQL 15+ with pgvector extension
  • NEAR AI account (authentication handled via setup wizard)

Download or Build

Visit Releases page to see the latest updates.

Install via Windows Installer (Windows)

Download the Windows Installer and run it.

Install via powershell script (Windows)
irm https://github.com/nearai/ironclaw/releases/latest/download/ironclaw-installer.ps1 | iex
Install via shell script (macOS, Linux, Windows/WSL)
curl --proto '=https' --tlsv1.2 -LsSf https://github.com/nearai/ironclaw/releases/latest/download/ironclaw-installer.sh | sh
Install via Homebrew (macOS/Linux)
brew install ironclaw
Compile the source code (Cargo on Windows, Linux, macOS)

Install it with cargo, just make sure you have Rust installed on your computer.

# Clone the repository
git clone https://github.com/nearai/ironclaw.git
cd ironclaw

# Build
cargo build --release

# Run tests
cargo test

For full release (after modifying channel sources), run ./scripts/build-all.sh to rebuild channels first.

Database Setup

# Create database
createdb ironclaw

# Enable pgvector
psql ironclaw -c "CREATE EXTENSION IF NOT EXISTS vector;"

Configuration

Run the setup wizard to configure IronClaw:

ironclaw onboard

The wizard handles database connection, NEAR AI authentication (via browser OAuth), and secrets encryption (using your system keychain). Settings are persisted in the connected database; bootstrap variables (e.g. DATABASE_URL, LLM_BACKEND) are written to ~/.ironclaw/.env so they are available before the database connects.

Alternative LLM Providers

IronClaw defaults to NEAR AI but works with any OpenAI-compatible endpoint. Popular options include OpenRouter (300+ models), Together AI, Fireworks AI, Ollama (local), and self-hosted servers like vLLM or LiteLLM.

Select "OpenAI-compatible" in the wizard, or set environment variables directly:

LLM_BACKEND=openai_compatible
LLM_BASE_URL=https://openrouter.ai/api/v1
LLM_API_KEY=sk-or-...
LLM_MODEL=anthropic/claude-sonnet-4

See docs/LLM_PROVIDERS.md for a full provider guide.

Security

IronClaw implements defense in depth to protect your data and prevent misuse.

WASM Sandbox

All untrusted tools run in isolated WebAssembly containers:

  • Capability-based permissions - Explicit opt-in for HTTP, secrets, tool invocation
  • Endpoint allowlisting - HTTP requests only to approved hosts/paths
  • Credential injection - Secrets injected at host boundary, never exposed to WASM code
  • Leak detection - Scans requests and responses for secret exfiltration attempts
  • Rate limiting - Per-tool request limits to prevent abuse
  • Resource limits - Memory, CPU, and execution time constraints
WASM ──► Allowlist ──► Leak Scan ──► Credential ──► Execute ──► Leak Scan ──► WASM
         Validator     (request)     Injector       Request     (response)

Prompt Injection Defense

External content passes through multiple security layers:

  • Pattern-based detection of injection attempts
  • Content sanitization and escaping
  • Policy rules with severity levels (Block/Warn/Review/Sanitize)
  • Tool output wrapping for safe LLM context injection

Data Protection

  • All data stored locally in your PostgreSQL database
  • Secrets encrypted with AES-256-GCM
  • No telemetry, analytics, or data sharing
  • Full audit log of all tool executions

Architecture

┌────────────────────────────────────────────────────────────────┐
│                          Channels                              │
│  ┌──────┐  ┌──────┐   ┌─────────────┐  ┌─────────────┐         │
│  │ REPL │  │ HTTP │   │WASM Channels│  │ Web Gateway │         │
│  └──┬───┘  └──┬───┘   └──────┬──────┘  │ (SSE + WS)  │         │
│     │         │              │         └──────┬──────┘         │
│     └─────────┴──────────────┴────────────────┘                │
│                              │                                 │
│                    ┌─────────▼─────────┐                       │
│                    │    Agent Loop     │  Intent routing       │
│                    └────┬──────────┬───┘                       │
│                         │          │                           │
│              ┌──────────▼────┐  ┌──▼───────────────┐           │
│              │  Scheduler    │  │ Routines Engine  │           │
│              │(parallel jobs)│  │(cron, event, wh) │           │
│              └──────┬────────┘  └────────┬─────────┘           │
│                     │                    │                     │
│       ┌─────────────┼────────────────────┘                     │
│       │             │                                          │
│   ┌───▼─────┐  ┌────▼────────────────┐                         │
│   │ Local   │  │    Orchestrator     │                         │
│   │Workers  │  │  ┌───────────────┐  │                         │
│   │(in-proc)│  │  │ Docker Sandbox│  │                         │
│   └───┬─────┘  │  │   Containers  │  │                         │
│       │        │  │ ┌───────────┐ │  │                         │
│       │        │  │ │Worker / CC│ │  │                         │
│       │        │  │ └───────────┘ │  │                         │
│       │        │  └───────────────┘  │                         │
│       │        └─────────┬───────────┘                         │
│       └──────────────────┤                                     │
│                          │                                     │
│              ┌───────────▼──────────┐                          │
│              │    Tool Registry     │                          │
│              │  Built-in, MCP, WASM │                          │
│              └──────────────────────┘                          │
└────────────────────────────────────────────────────────────────┘

Core Components

Component Purpose
Agent Loop Main message handling and job coordination
Router Classifies user intent (command, query, task)
Scheduler Manages parallel job execution with priorities
Worker Executes jobs with LLM reasoning and tool calls
Orchestrator Container lifecycle, LLM proxying, per-job auth
Web Gateway Browser UI with chat, memory, jobs, logs, extensions, routines
Routines Engine Scheduled (cron) and reactive (event, webhook) background tasks
Workspace Persistent memory with hybrid search
Safety Layer Prompt injection defense and content sanitization

Usage

# First-time setup (configures database, auth, etc.)
ironclaw onboard

# Start interactive REPL
cargo run

# With debug logging
RUST_LOG=ironclaw=debug cargo run

Development

# Format code
cargo fmt

# Lint
cargo clippy --all --benches --tests --examples --all-features

# Run tests
createdb ironclaw_test
cargo test

# Run specific test
cargo test test_name
  • Telegram channel: See docs/TELEGRAM_SETUP.md for setup and DM pairing.
  • Changing channel sources: Run ./channels-src/telegram/build.sh before cargo build so the updated WASM is bundled.

OpenClaw Heritage

IronClaw is a Rust reimplementation inspired by OpenClaw. See FEATURE_PARITY.md for the complete tracking matrix.

Key differences:

  • Rust vs TypeScript - Native performance, memory safety, single binary
  • WASM sandbox vs Docker - Lightweight, capability-based security
  • PostgreSQL vs SQLite - Production-ready persistence
  • Security-first design - Multiple defense layers, credential protection

License

Licensed under either of:

at your option.

S
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IronClaw is OpenClaw inspired implementation in Rust focused on privacy and security
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