kairos-ark 0.1.8
KAIROS-ARK: A deterministic multi-threaded scheduler for agentic AI workflows
License: MIT
Requires Python: <3.14,>=3.8

# KAIROS-ARK

<div align="center">

![KAIROS-ARK Logo](assets/logo.jpg)

**The Operating System for Agentic AI**

[![Rust](https://img.shields.io/badge/rust-1.70+-orange.svg)](https://www.rust-lang.org/)
[![Python](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/)
[![License](https://img.shields.io/badge/license-MIT-green.svg)](LICENSE)

</div>



## Overview

**KAIROS-ARK** is a high-performance, deterministic execution kernel designed for mission-critical agentic AI workflows. Unlike traditional frameworks that prioritize prompt engineering, KAIROS-ARK prioritizes **system integrity**, **reproducibility**, and **industrial-grade governance**.

It provides a specialized "Operating System" for agents, handling:
- **Scheduling**: Deterministic, multi-threaded task execution.
- **Memory**: Zero-copy shared memory for large datasets.
- **Security**: Kernel-level policy enforcement and sandboxing.
- **Time**: Logical clocks for bit-for-bit identical replay debugging.
- **Governance**: Human-in-the-Loop (HITL) approvals and cryptographic audit logs.

<br/>

<div align="center">
  <img src="assets/architecture_diagram.png" alt="KAIROS-ARK Architecture" width="100%">
</div>

<br/>

---

## Key Features

| Feature | Description |
|---------|-------------|
| **⚡ High Throughput** | Process **720,000+ nodes/second** with Rust-native execution. |
| **🔒 Policy Engine** | Restrict agent capabilities (Network, FS, Exec) at the kernel level. |
| **⏱️ Time-Travel** | Replay any execution from a ledger with 100% determinism. |
| **🚀 Zero-Copy** | Pass GB-sized payloads between tasks in microseconds. |
| **🤝 Interoperability** | Native adapters for LangGraph, CrewAI, and MCP tools. |
| **🛡️ Governance** | Cryptographically signed audit logs and enforced HITL protocols. |

---

## Installation

```bash
pip install kairos-ark
```

Or build from source for maximum performance:

```bash
git clone https://github.com/YASSERRMD/KAIROS-ARK.git
cd KAIROS-ARK
pip install maturin
maturin develop
```

---

## Quick Start

### 1. Hello World Agent

```python
from kairos_ark import Agent

# Create a deterministic agent
agent = Agent(seed=42)

# Add tasks (nodes)
agent.add_node("fetch", lambda: {"data": "raw data"})
agent.add_node("process", lambda: {"status": "processed"})

# Connect workflow
agent.connect("fetch", "process")

# Execute
results = agent.execute("fetch")
print(f"Executed {len(results)} nodes")
```

### 2. Parallel Execution

KAIROS-ARK uses a Rayon-backed thread pool for true parallelism:

```python
# Fork execution into parallel branches
agent.add_fork("start_parallel", ["scrape_web", "query_db", "check_cache"])

# Join results
agent.add_join("sync_results", ["scrape_web", "query_db", "check_cache"])

agent.execute("start_parallel")
```

---

## Core Capabilities

### 🛡️ Security & Policy Engine

Prevent "excessive agency" by sandboxing tools at the kernel level.

```python
from kairos_ark import Agent, Policy, Cap

# Define a restrictive policy
policy = Policy(
    allowed_capabilities=[Cap.LLM_CALL],       # Only allow LLM calls
    max_tool_calls={"web_search": 5},          # Rate limit specific tools
    forbidden_content=["password", "api_key"]  # Automatic redaction
)

# Run agent with policy
agent.run("start", policy=policy)
```

### 💾 Persistence & Time-Travel Debugging

Debug "Heisenbugs" by replaying execution logs exactly as they happened.

```python
# 1. Save execution ledger
agent.save_ledger("run_001.jsonl")

# 2. Replay later (reconstructs state without re-running side effects)
state = agent.replay("run_001.jsonl")
print(f"Final State: {state['node_outputs']}")

# 3. Create Snapshots for fast recovery
agent.create_snapshot("checkpoint.json", "run_001")
```

### 🚀 Zero-Copy Shared Memory

Pass large objects (images, embeddings, codebases) between Python/Rust without serialization overhead.

```python
# Write 1GB data once (~5µs latency)
handle = agent.kernel.write_shared(large_data_list)

# Pass unique handle to other nodes
result = agent.kernel.read_shared(handle)
```

### 🤝 Interoperability & Ecosystem

KAIROS-ARK acts as a native backend for other frameworks, with built-in adapters.

```python
# 1. LangGraph Adapter (Native Checkpointer)
from kairos_ark.integrations.langgraph import ArkNativeCheckpointer
checkpointer = ArkNativeCheckpointer(agent)

# 2. Universal Connectors
from kairos_ark.connectors import (
    ArkGeminiConnector,
    ArkOpenAIConnector,
    ArkClaudeConnector,
    ArkOllamaConnector,
    ArkCohereConnector
)

# Gemini (Google)
llm = ArkGeminiConnector(model_name="gemini-2.0-flash-lite")

# Cohere (Enterprise)
cohere = ArkCohereConnector(model="command-r-plus")

# OpenAI / Groq / DeepSeek
groq = ArkOpenAIConnector(
    base_url="https://api.groq.com/openai/v1",
    api_key="gsk_...",
    model="llama3-70b-8192"
)

# Local (Ollama)
local_llm = ArkOllamaConnector(model="llama3")

# 3. Native Tools (Zero-Copy Ready)
from kairos_ark.tools import ArkTools
results = ArkTools.tavily_search("KAIROS-ARK Architecture")
```

#### Kernel-Level Support

```python
# State Store (~4µs access)
agent.kernel.state_set("messages", json.dumps(history))

# MCP Tool Registry
agent.kernel.mcp_register_tool("search", "Search tool")
```

### ⚖️ Governance & HITL

Industrial-grade compliance features built-in.

```python
# 1. Human-in-the-Loop (HITL) Interrupts
req_id = agent.kernel.request_approval("run_1", "deploy", "Deploy to prod?")
# Execution suspends until approved
agent.kernel.approve(req_id, "admin_user")

# 2. Cryptographic Verification
ledger = agent.get_audit_log_json()
signed = agent.kernel.sign_ledger(ledger, "run_1")
is_valid = agent.kernel.verify_ledger(signed)
```

---

## Documentation

- **[Getting Started Guide](docs/getting-started.md)**: Build your first agent in 5 minutes.
- **[The Scheduler](docs/core-concepts/scheduler.md)**: Deep dive into logical clocks and determinism.
- **[Policy Engine](docs/core-concepts/policy-engine.md)**: Configuring capabilities and sandboxes.
- **[Zero-Copy Memory](docs/advanced/zero-copy.md)**: Optimizing for large-scale data.
- **[Time-Travel Debugging](docs/advanced/time-travel.md)**: Mastering the Replay Engine.

---

## Benchmarks

KAIROS-ARK is built for speed.
> [!NOTE]
> All benchmarks were executed with native execution only. Python was not present in the hot path.

| Category | Metric | Performance | Verdict |
|----------|--------|-------------|---------|
| **Core** | **Kernel Overhead** | **8.37 µs / node** | 🚀 10x Faster than Frameworks |
| **Core** | **Tool Chaining** | **0.45 ms (Total)** | ⚡ Instant |
| **Core** | **Determinism** | **Byte-for-Byte Match** | ✅ Exact Replay |
| **Core** | **Parallelism** | **206ms (4x 200ms)** | 🧵 True Parallel Fan-out |
| **Throughput** | **Node Throughput** | **720,000+ nodes/sec** | High Frequency |
| **Latency** | **Task Dispatch** | ~1.4 µs | Real-time |
| **Latency** | **Policy Check** | ~3.0 µs | Zero-Cost Security |
| **Latency** | **State Store** | ~4.0 µs | Fast IPC |

---

## License

MIT License - see [LICENSE](LICENSE) for details.

## Author

**YASSERRMD**