8638895879 feat(gemini_oauth): full Gemini CLI OAuth integration with Cloud Code API (#1356)
* feat: integrate Gemini CLI OAuth with Cloud Code API

- Add gemini_oauth.rs: full OAuth flow with PKCE, token refresh,
  and Cloud Code project discovery (loadCodeAssist + onboardUser)
- Route preview/gemini-3 models through cloudcode-pa.googleapis.com
  with proper project ID injection in request payload
- Trigger OAuth login during onboarding wizard (not first chat message)
- Support manual redirect URL paste as fallback (tokio::select race)
- Parse 429 rate-limit errors with retry_after from Google response
- Add static model list: gemini-1.5/2.0/2.5/3.0/3.1 variants
- Add GeminiOauthConfig with default credentials path (~/.gemini/)

* feat(gemini): implement function calling, generationConfig, and update models

- Implement function calling support (functionDeclarations, functionResponse)
- Add functionCall SSE parsing and empty stream retry support
- Add generationConfig (temperature, maxOutputTokens)
- Add thinkingConfig for Gemini 3 and thinking models
- Add toolConfig (functionCallingConfig.mode)
- Fix .expect() panics with .ok_or_else()
- Restrict oauth credentials file permissions to 0600
- Update docs and FEATURE_PARITY.md
- Update wizard to current Gemini 3.1 and 2.5 models

* fix: address code review issues in gemini-cli OAuth integration

- Add cache_read_input_tokens/cache_creation_input_tokens fields (value 0)
- Implement manual Debug for OAuthCredential to redact tokens
- Fix hardcoded /tmp: use GeminiOauthConfig::default_credentials_path()
- Replace emoji output with plain text markers
- Propagate Client::builder() errors instead of silent fallback
- Use tokio::fs for all file I/O in CredentialManager (was std::fs)
- Use if let Some(ref pid) to avoid consuming credential.project_id
- Extract uses_cloud_code_api() helper; route by major version (gemini-2+)
- Concatenate multiple system messages into systemInstruction
- Include functionCall parts in assistant message conversion
- Add 401 retry loop with allow_retry flag for auth failures
- Remove biased from tokio::select! in OAuth callback handler
- Remove hardcoded context_length 1M; vary by model family
- Change GOOG_API_CLIENT from Node.js spoof to gl-rust/1.0.0
- Implement list_models() with static model list
- Move create_gemini_oauth_provider() before test module (clippy)
- Fix 9 additional clippy warnings (collapsible_if, map_or, needless_borrow)
- Run cargo fmt

* Add dedicated regression tests for Gemini OAuth fixes

* style: fix formatting in Gemini OAuth regression tests

* feat(gemini-oauth): implement code review v3 refinements

- Add force_refresh() for 401 retry (bypass timestamp check)
- Standardize Gemini model list across docs, wizard, and provider
- Restore gemini-3 check for thinkingConfig
- Redact sensitive tokens in GoogleTokenRefreshResponse Debug output
- Use dynamic version for GOOG_API_CLIENT
- Improve model_metadata() context length heuristics
- Use strip_prefix("data:") for safer SSE parsing
- Skip re-auth in wizard if keeping existing provider

* feat(gemini_oauth): full Cloud Code API integration with project discovery

- Register gemini_oauth as a dedicated backend in config/llm.rs (skip
  registry fallback, preserve backend name, suppress unknown-backend warning)
- Fix app.rs credential guard to exclude backends with dedicated configs
  (gemini_oauth, bedrock) from the provider.is_none() check
- Auto-discover Cloud Code project_id via loadCodeAssist when credentials
  lack it (e.g. created by the original Gemini CLI)
- Persist discovered project_id to credentials file for subsequent runs
- Add safety settings (BLOCK_NONE), gated behind GEMINI_SAFETY_BLOCK_NONE env
- Add thinkingConfig: budget-based for Gemini 2.5, level-based for Gemini 3.x
  (without includeThoughts to avoid empty responses from reasoning.rs stripping)
- Add thought signature injection for Gemini 3.x preview APIs
- Add history curation to filter invalid model outputs before re-sending
- Add extended generationConfig env vars (topP, topK, seed, penalties,
  responseMimeType, responseJsonSchema, cachedContent)
- Add custom headers support via GEMINI_CLI_CUSTOM_HEADERS
- Add API key auth mode (GEMINI_API_KEY + GEMINI_API_KEY_AUTH_MECHANISM)
- Add SSE metadata extraction (modelVersion, credits, promptFeedback,
  groundingMetadata, citationMetadata, cachedContentTokenCount)
- Add countTokens API support
- Add new models to wizard (gemini-3.1-pro-preview-customtools,
  gemini-3-pro-preview, gemini-3.1-flash-lite-preview)
- Update docs/LLM_PROVIDERS.md with new models and routing rules
- Rewrite regression tests with comprehensive coverage (23 unit tests pass)

* fix: CI violations — add safety comment on expect, fix fmt

- Add '// safety: hardcoded literal' to regex .expect() to satisfy
  the no-panic-in-prod CI check
- Fix cargo fmt whitespace in collapsible if-let chain

* fix: address PR review feedback from gemini-code-assist

- Fix parse_custom_headers to preserve commas in values by splitting
  only on commas followed by a header-name:colon pattern (manual scan
  instead of simple split(','))
- Use matches! macro for backend exclusion check in app.rs
- Merge SSE metadata extraction into single pass (was iterating twice)
- Replace fragile substring-based context_length with explicit match
  on known Gemini model IDs via gemini_context_length()
- Add missing models to regression test (8 models, not 5)

* fix: address Copilot PR review feedback

- Fix empty text part for assistant messages with tool calls
  (curate_contents could drop entire model turn)
- Propagate cache_read/creation_input_tokens in complete_with_tools
- Log warning on save_credential failure instead of silently ignoring
- Fix doc comment to mention underscore in header name pattern
- Handle gemini-oauth (hyphen variant) in setup wizard display
- Fix docs: thinkingConfig uses thinkingBudget/thinkingLevel, not
  includeThoughts

* fix: add missing allow_always field after staging merge

* fix(gemini_oauth): align header parser doc with implementation [skip-regression-check]

Update parse_custom_headers doc comments to include underscore in the
header-name character class, matching the actual implementation.
Also fix formatting from merge.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* fix(gemini_oauth): curate_contents per-part filtering and dead code removal

Fix curate_contents to filter invalid parts individually instead of
dropping entire model turn sequences. Previously a single empty text
part would discard all consecutive model turns including valid
functionCall parts, breaking the tool-call flow.

Also remove unused MID_STREAM_* constants.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* style(gemini_oauth): rustfmt formatting [skip-regression-check]

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* fix(llm): support smart routing cheap model for gemini_oauth backend

Add explicit gemini_oauth handling in create_cheap_provider_for_backend()
to create a GeminiOauthProvider with the cheap model swapped in. Without
this, setting LLM_CHEAP_MODEL with gemini_oauth backend would fail with
a confusing "no registry provider config available" error.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* docs: add Gemini OAuth env vars to .env.example [skip-regression-check]

Document GEMINI_MODEL, GEMINI_CREDENTIALS_PATH, GEMINI_API_KEY, and
all extended generation config env vars in the example config file.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

---------

Co-authored-by: [email protected] <[email protected]>
Co-authored-by: Claude Opus 4.6 (1M context) <[email protected]>
2026-03-21 22:41:44 -07:00
2026-02-04 22:09:52 -08:00
2026-02-11 08:31:25 +00:00
2026-03-16 21:39:47 -07:00
2026-02-22 19:08:43 +00:00
2026-02-22 19:08:43 +00:00
2026-02-21 15:14:57 -07:00
2026-03-18 11:34:19 -07:00
2026-03-18 11:34:19 -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 | 日本語

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 supports many LLM providers out of the box. Built-in providers include Anthropic, OpenAI, GitHub Copilot, Google Gemini, MiniMax, Mistral, and Ollama (local). OpenAI-compatible services like OpenRouter (300+ models), Together AI, Fireworks AI, and self-hosted servers (vLLM, LiteLLM) are also supported.

Select your provider in the wizard, or set environment variables directly:

# Example: MiniMax (built-in, 204K context)
LLM_BACKEND=minimax
MINIMAX_API_KEY=...

# Example: OpenAI-compatible endpoint
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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