StableAgents Framework

A production-ready framework for building enterprise-grade AI agents - providing robust infrastructure and system-level capabilities that enable reliable, secure, and efficient AI agent operations at scale.

Official site: stableagents.dev

Overview

StableAgents is designed to be the foundation for large-scale AI agent deployments with a focus on:

• Reliability: Built-in self-healing mechanisms ensure consistent operation even under adverse conditions
• Scalability: Architecture supports everything from single-agent deployments to complex multi-agent systems
• Security: Enterprise-grade authentication, access controls, and data protection mechanisms
• Extensibility: Modular design allows for customization and extension of core capabilities

Key Features

• Multi-Provider Support: Seamlessly integrate with OpenAI, Anthropic, and other AI providers
• Local Model Integration: Run models offline with local inference capabilities
• Self-Healing System: Automatic issue detection, diagnosis, and recovery
• Memory Management: Efficient handling of context and persistent storage
• Computer Control: Safe system interaction capabilities
• Comprehensive Logging: Detailed activity tracking and monitoring

Quick Installation

Option 1: Install from GitHub (Recommended)

bash pip install git+https://github.com/jordanplows/stableagents.git

Option 2: Install with Local Models Support

bash pip install git+https://github.com/jordanplows/stableagents.git[local]

Option 3: Development Installation

bash git clone https://github.com/jordanplows/stableagents.git cd stableagents pip install -e .

Quick Start

After installation, start StableAgents:

bash stableagents-ai --start

The CLI will guide you through: 1. API Key Setup: Choose between managed keys ($20) or bring your own 2. Provider Selection: Configure OpenAI, Anthropic, Google, or local models 3. Security Setup: Set up encrypted storage for your credentials

Basic Usage

Python API

```python from stableagents import StableAgents

Initialize the agent

agent = StableAgents()

Generate text

response = agent.generate_text("Hello, how can you help me today?") print(response) ```

Command Line Interface

```bash

Start interactive mode

stableagents-ai

Run with specific model

stableagents-ai --model openai --api-key your-key

Use local models

stableagents-ai --local --model-path ~/models/llama-2-7b.gguf ```

Access

StableAgents is a private framework available to authorized partners and enterprise customers. For access inquiries:

• Visit: stableagents.dev
• Contact: support@stableagents.dev

Documentation

Comprehensive documentation is available to authorized users at docs.stableagents.dev

Implementation Examples

Basic Agent Setup

```python from stableagents import StableAgents

Initialize with enterprise configuration

agent = StableAgents( enableselfhealing=True, enable_logging=True )

Configure AI provider

agent.setapikey('openai', 'your-api-key') agent.setactiveai_provider('openai')

Generate text with the agent

response = agent.generate_text("Analyze the performance of our product in Q1") ```

Custom Health Check Integration

```python

Register custom component for monitoring

agent.selfhealing.registercomponent( "database", checkdatabasehealth, thresholds={ "connection_status": {"min": True, "severity": "high"} } ) ```

Use Cases

• Customer Service: Deploy conversational agents that can understand, respond, and solve customer issues
• Enterprise Assistants: Create specialized assistants for internal business processes
• Data Analysis: Build agents that can process, analyze, and report on complex business data
• Content Generation: Develop agents for content creation, curation, and management
• Research Automation: Automate literature reviews, data collection, and preliminary analysis

License

Proprietary software licensed exclusively to authorized partners and customers.

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