stableagents-ai 0.2.1

A framework for self healing agents that can run locally and minimize hallucinations

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

Access

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

• Visit: stableagents.dev
• Contact: [e-mail]

Documentation

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

Implementation Examples

Basic Agent Setup

from stableagents import StableAgents

# Initialize with enterprise configuration
agent = StableAgents(
    enable_self_healing=True,
    enable_logging=True
)

# Configure AI provider
agent.set_api_key('openai', 'your-api-key')
agent.set_active_ai_provider('openai')

# Generate text with the agent
response = agent.generate_text("Analyze the performance of our product in Q1")

Custom Health Check Integration

# Register custom component for monitoring
agent.self_healing.register_component(
    "database",
    check_database_health,
    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.

© 2023-2025 StableAgents. All rights reserved.

Quick Installation

To install StableAgents globally on your system, run:

# Clone the repository
git clone https://github.com/yourusername/stableagents.git
cd stableagents

# Run the installation script
chmod +x install.sh
./install.sh

The installation script will:

1. Check for required dependencies (Python 3 and pip)
2. Install StableAgents globally
3. Add the necessary PATH entries to your shell configuration
4. Verify the installation

After installation, you can run StableAgents from anywhere using:

stableagents-ai start

Manual Installation

If you prefer to install manually:

# Clone the repository
git clone https://github.com/yourusername/stableagents.git
cd stableagents

# Install globally
pip install --user -e .

# Add to your PATH (if not already done)
echo 'export PATH="$HOME/.local/bin:$PATH"' >> ~/.bashrc  # or ~/.zshrc
source ~/.bashrc  # or source ~/.zshrc