README.md

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  <img src="https://dummyimage.com/1200x260/000/fff&text=AGENTIC+RELIABILITY+FRAMEWORK" width="100%" alt="Agentic Reliability Framework Banner" />
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<h1 align="center">⚙️ Agentic Reliability Framework</h1>

<p align="center">
  <strong>Adaptive anomaly detection + policy-driven self-healing for AI systems</strong><br>
  Minimal, fast, and production-focused.
</p>

<p align="center">
  <a href="https://www.python.org/"><img src="https://img.shields.io/badge/python-3.10+-blue" alt="Python 3.10+"></a>
  <a href="#"><img src="https://img.shields.io/badge/status-MVP-green" alt="Status: MVP"></a>
  <a href="#"><img src="https://img.shields.io/badge/license-MIT-lightgrey" alt="License: MIT"></a>
</p>

## 🧠 Agentic Reliability Framework

**Autonomous Reliability Engineering for Production AI Systems**

Transform reactive monitoring into proactive, self-healing reliability. The Agentic Reliability Framework (ARF) is a production-grade, multi-agent system that detects, diagnoses, predicts, and resolves incidents automatically in under 100ms.

## ⭐ Key Features

- **Real-time anomaly detection** across latency, errors, throughput & resources
- **Root-cause analysis** with evidence correlation
- **Predictive forecasting** (15-minute lookahead)
- **Automated healing policies** (restart, rollback, scale, circuit break)
- **Incident memory** with FAISS for semantic recall
- **Security hardened** (all CVEs patched)
- **Thread-safe, async, process-pooled architecture**
- **Sub-100ms end-to-end latency** (p50)

## 🔐 Security Hardening (v2.0)

| CVE | Severity | Component | Status |
|-----|----------|-----------|--------|
| CVE-2025-23042 | 9.1 | Gradio Path Traversal | ✅ Patched |
| CVE-2025-48889 | 7.5 | Gradio SVG DOS | ✅ Patched |
| CVE-2025-5320 | 6.5 | Gradio File Override | ✅ Patched |
| CVE-2023-32681 | 6.1 | Requests Credential Leak | ✅ Patched |
| CVE-2024-47081 | 5.3 | Requests .netrc Leak | ✅ Patched |

### Additional Hardening

- SHA-256 hashing everywhere (no MD5)
- Pydantic v2 input validation
- Rate limiting (60 req/min/user)
- Atomic operations w/ thread-safe FAISS single-writer pattern
- Lock-free reads for high throughput

## ⚡ Lock-Free Reads for High Throughput

By restructuring the internal memory stores around lock-free, single-writer / multi-reader semantics, the framework delivers deterministic concurrency without blocking. This removes tail-latency spikes and keeps event flows smooth even under burst load.

### Performance Impact

| Metric | Before | After | Δ |
|--------|--------|-------|---|
| Event Processing (p50) | ~350ms | ~100ms | ⚡ 71% faster |
| Event Processing (p99) | ~800ms | ~250ms | ⚡ 69% faster |
| Agent Orchestration | Sequential | Parallel | 3× throughput |
| Memory Behavior | Growing | Stable / Bounded | 0 leaks |

## 🧩 Architecture Overview

### System Flow

```
Your Production System
(APIs, Databases, Microservices)
           ↓
  Agentic Reliability Core
  Detect → Diagnose → Predict
           ↓
        Agents:
  🕵️ Detective Agent – Anomaly detection
  🔍 Diagnostician Agent – Root cause analysis
  🔮 Predictive Agent – Forecasting / risk estimation
           ↓
    Policy Engine (Auto-Healing)
           ↓
    Healing Actions:
    • Restart
    • Scale
    • Rollback
    • Circuit-break
```

## 🏗️ Core Framework Components

### Web Framework & UI

- **Gradio 5.50+** - High-performance async web framework serving both API layer and interactive observability dashboard (localhost:7860)
- **Python 3.10+** - Core implementation with asynchronous, thread-safe architecture

### AI/ML Stack

- **FAISS-CPU 1.13.0** - Facebook AI Similarity Search for persistent incident memory and vector operations
- **SentenceTransformers 5.1.1** - Neural embedding framework using MiniLM models from Hugging Face Hub for semantic analysis
- **NumPy 1.26.4** - Numerical computing foundation for vector operations and data processing

### Data & HTTP Layer

- **Pydantic 2.11+** - Type-safe data modeling with frozen models for immutability and runtime validation
- **Requests 2.32.5** - HTTP client library for external API communication (security patched)

### Reliability & Resilience

- **CircuitBreaker 2.0+** - Circuit breaker pattern implementation for fault tolerance and cascading failure prevention
- **AtomicWrites 1.4.1** - Atomic file operations ensuring data consistency and durability

## 🎯 Architecture Pattern

ARF implements a **Multi-Agent Orchestration Pattern** with three specialized agents:

- **Detective Agent** - Anomaly detection
- **Diagnostician Agent** - Root cause analysis
- **Predictive Agent** - Future risk forecasting

All agents run in **parallel** (not sequential) for **3× throughput improvement**.

### ⚡ Performance Features

- Native async handlers (no event loop overhead)
- Thread-safe single-writer/multi-reader pattern for FAISS
- RLock-protected policy evaluation
- Queue-based writes to prevent race conditions
- Sub-100ms p50 latency at 100+ events/second

The framework combines **Gradio** for the web/UI layer, **FAISS** for vector memory, and **SentenceTransformers** for semantic analysis, all orchestrated through a custom multi-agent Python architecture designed for production reliability.

## 🧪 The Three Agents

### 🕵️ Detective Agent — Anomaly Detection

Real-time vector embeddings + adaptive thresholds to surface deviations before they cascade.

- Adaptive multi-metric scoring
- CPU/mem resource anomaly detection
- Latency & error spike detection
- Confidence scoring (0–1)

### 🔍 Diagnostician Agent (Root Cause Analysis)

Identifies patterns such as:

- DB connection pool exhaustion
- Dependency timeouts
- Resource saturation
- App-layer regressions
- Misconfigurations

### 🔮 Predictive Agent (Forecasting)

- 15-minute risk projection
- Trend analysis
- Time-to-failure estimates
- Risk levels: low → critical

## 🚀 Quick Start

### 1. Clone

```bash
git clone https://github.com/petterjuan/agentic-reliability-framework.git
cd agentic-reliability-framework
```

### 2. Create environment

```bash
python3.10 -m venv venv
source venv/bin/activate     # Windows: venv\Scripts\activate
```

### 3. Install

```bash
pip install -r requirements.txt
```

### 4. Start

```bash
python app.py
```

**UI:** http://localhost:7860

## 🛠 Configuration

Create `.env`:

```env
HF_TOKEN=your_token
DATA_DIR=./data
INDEX_FILE=data/incident_vectors.index
LOG_LEVEL=INFO
HOST=0.0.0.0
PORT=7860
```

**Note:** `HF_TOKEN` is optional and used for downloading SentenceTransformer models from Hugging Face Hub.

## 🧩 Custom Healing Policies

```python
custom = HealingPolicy(
    name="custom_latency",
    conditions=[PolicyCondition("latency_p99", "gt", 200)],
    actions=[HealingAction.RESTART_CONTAINER, HealingAction.ALERT_TEAM],
    priority=1,
    cool_down_seconds=300,
    max_executions_per_hour=5,
)
```

## 🐳 Docker Deployment

Dockerfile and docker-compose.yml included.

```bash
docker-compose up -d
```

## 📈 Performance Benchmarks

**On Intel i7, 16GB RAM:**

| Component | p50 | p99 |
|-----------|-----|-----|
| Total End-to-End | ~100ms | ~250ms |
| Policy Engine | 19ms | 38ms |
| Vector Encoding | 15ms | 30ms |

**Stable memory:** ~250MB  
**Throughput:** 100+ events/sec

## 🧪 Testing

### Production Dependencies

```bash
pip install -r requirements.txt
```

### Development Dependencies

```bash
pip install pytest pytest-asyncio pytest-cov pytest-mock black ruff mypy
```

### Run Tests

```bash
pytest tests/ -v --cov
```

**Coverage:** 87%

Includes:
- Unit tests
- Thread-safety tests
- Stress tests
- Integration tests

### Code Quality

```bash
# Format code
black .

# Lint code
ruff check .

# Type checking
mypy app.py
```

## 🗺 Roadmap

### v2.1

- Distributed FAISS
- Prometheus / Grafana
- Slack & PagerDuty integration
- Custom alerting DSL

### v3.0

- Reinforcement learning for policy optimization
- LSTM forecasting
- Dependency graph neural networks

## 🤝 Contributing

Pull requests welcome.

Please run tests before submitting.

## 📬 Contact

**Author:** Juan Petter (LGCY Labs)

- 📧 [petter2025us@outlook.com](mailto:petter2025us@outlook.com)
- 🔗 [linkedin.com/in/petterjuan](https://linkedin.com/in/petterjuan)
- 📅 [Book a session](https://calendly.com/petter2025us/30min)

## ⭐ Support

If this project helps you:

- ⭐ Star the repo
- 🔄 Share with your network
- 🐛 Report issues
- 💡 Suggest features

<p align="center">
  <sub>Built with ❤️ for production reliability</sub>
</p>