d73e35cfb0 feat: add AWS Bedrock LLM provider via native Converse API (#713)
* feat: add AWS Bedrock LLM provider via native Converse API

* fix: use JSON parsing for tool result error detection instead of brittle substring matching

* refactor: extract duplicated inference config builder into helper function

* fix: address review feedback — safe casts, input validation, and tests

- Safe u32→i32 cast for max_tokens using try_from with clamp
- Remove brittle string-based error detection fallback for tool results
- Validate BEDROCK_CROSS_REGION against allowed values (us/eu/apac/global)
- Validate message list is non-empty before Converse API call
- Log when using default us-east-1 region
- Update llm_backend doc comment to list all backends
- Add tests for build_inference_config and empty message handling

* fix: persist AWS_PROFILE for Bedrock named profile auth

The wizard collected the profile name but only printed a hint to set
it manually. Now it saves to settings and writes AWS_PROFILE to the
bootstrap .env, consistent with how BEDROCK_REGION and other Bedrock
settings are persisted.

* feat: gate AWS Bedrock behind optional `bedrock` feature flag

The AWS SDK dependencies (aws-config, aws-sdk-bedrockruntime,
aws-smithy-types) require cmake and a C compiler to build aws-lc-sys.
Gate them behind an opt-in `bedrock` feature flag so default builds
are unaffected.

Build with: cargo build --features bedrock
All config, settings, and wizard code stays unconditional (no AWS deps)
so users can configure Bedrock even without the feature compiled — they
get a clear error at startup directing them to rebuild.

* fix: address review feedback and adapt Bedrock provider to registry architecture (takeover #345)

- Resolve merge conflicts with main's registry-based provider system
- Add missing cache_creation_input_tokens/cache_read_input_tokens fields
- Add missing content_parts field in test ChatMessage
- Fix string literal type mismatches in wizard env_vars (.to_string())
- Remove non-functional bearer token auth (AWS_BEARER_TOKEN_BEDROCK) from
  wizard and documentation per reviewer feedback from @zmanian and @serrrfirat
- Remove stale BEDROCK_ACCESS_KEY proxy entry from provider table
- Update Bedrock provider to use is_bedrock string check (LlmBackend enum removed)
- Add bedrock_profile fallback from settings in config resolution

[skip-regression-check]

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

* fix: use main's Cargo.lock as base to preserve dependency versions

Regenerating Cargo.lock from scratch caused transitive dependency version
drift that broke the html_to_markdown fixture test in CI.

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

* fix: bedrock config bugs — spurious warning, alias normalization, profile fallback

- Move is_bedrock check before unknown-backend warning to prevent
  spurious "unknown backend" log for bedrock users
- Normalize backend aliases ("aws", "aws_bedrock") to "bedrock" so
  the provider factory matches correctly
- Add settings.bedrock_profile fallback for AWS_PROFILE, consistent
  with region and cross_region resolution

[skip-regression-check]

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

* fix: address Copilot review feedback — bearer token cleanup, stop_sequences, model dedup

- Remove stale bearer token refs from setup README and CHANGELOG
- Remove dead bedrock_api_key secret injection mapping
- Pass stop_sequences through to Bedrock InferenceConfiguration
- Remove "API key" from wizard menu description (bearer token removed)
- Skip duplicate LLM_MODEL write for bedrock backend in wizard
- Fix cargo fmt formatting

[skip-regression-check]

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

* fix: address review feedback — async new(), remove LiteLLM entry, wizard fixes

- Remove dead LiteLLM-based bedrock entry from providers.json (native
  Converse API intercepts before registry lookup)
- Make BedrockProvider::new() async to avoid block_in_place panic in
  current_thread runtimes; propagate async to create_llm_provider,
  build_provider_chain, and init_llm
- Document CMake build prerequisite in docs/LLM_PROVIDERS.md
- Clear bedrock_profile when user selects "default credentials" in wizard
- Fix selected_model clearing to match established pattern (conditional
  on provider switch, not unconditional)
- Add regression tests for bedrock model preservation and profile clearing

Addresses review feedback from @zmanian on PR #713.
Streaming support tracked in #741.

[skip-regression-check]

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

* fix: address remaining review comments — CLAUDE.md backends, wizard UX

- Add `bedrock` to CLAUDE.md inline backend list (#10)
- Skip full setup re-run when keeping existing Bedrock config (#11)
- Clear stale bedrock_profile on empty named-profile input (#12)
- Add regression test for empty profile clearing

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

---------

Co-authored-by: Chris Gorski <[email protected]>
Co-authored-by: cgorski <[email protected]>
Co-authored-by: Claude Opus 4.6 <[email protected]>
2026-03-09 07:10:25 +00:00
2026-03-05 17:12:49 -08:00
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

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