SonAgent

Autonomous Agent for Digital Consciousness Backup Using Large Language Models (LLM)

Overview

The Digital Consciousness Backup Agent is an autonomous system designed to safeguard your digital consciousness on the internet using Large Language Models (LLMs). As we navigate the vast landscape of the digital realm, preserving and securing our digital consciousness becomes paramount. This project employs advanced techniques to ensure the protection and backup of your digital self. Powerful code generation capability, self-editing source code

What shapes individuals is their own beliefs. by Son Nguyen Huu

Features

• Autonomous Operation: The agent operates autonomously, continuously monitoring and safeguarding your digital presence without requiring constant user intervention.

• Belief-Based Thinking with Large Language Models (LLMs): The agent engages in cognitive processes inspired by belief systems, utilizing advanced LLMs for reasoning and decision-making. This allows it to navigate the digital landscape with a level of understanding akin to human cognition.

• Automatic Belief Acquisition: The agent is designed to automatically acquire new beliefs and knowledge over time. It leverages the power of large language models to adapt and stay informed about the ever-evolving digital environment.

• Learning with Human Feedback: The agent incorporates human feedback into its learning process, enhancing its capabilities through continuous interaction with users. This dynamic learning mechanism ensures that the agent evolves and improves its performance based on real-world user experiences.

• Secure Backup: The agent employs robust encryption and secure protocols to create backups of your digital consciousness, preventing unauthorized access and ensuring the integrity of your data.

• Self-Repairing source code edits its own source code and compiles itself under human approval

• Many tools and skills: Train neural network, Search, write file, ...

Into and demo video

Getting Started

1. Install Dependencies

pip install sonagent

2. Run agent

• 2.1 create user_data folder that will save agent skill, and user database

sonagent init

• 2.2 Please fill in the API key of openai, telegram, and github if you want the agent to create a pull request in the user_data/config.json file. You can also configure the timezone for the agent (default is UTC).
• 2.3 run agent with file path param from step 2.1

Note: On first run, standard skills (TextPrinter, WeatherAPISkill, HanoiWeatherChecker, SkillBuilder) are automatically copied to user_data/skills/. You can customize or remove these as needed. See Standard Skills Documentation for more details.

sonagent run 
--config /path/to/user_data/config.json 
--agentdb sqlite:///user_data/myagentdb.sqlite 
--memory-url /path/to/user_data/memory 
--datadir /path/to/user_data/  
--user-data-dir /path/to/user_data/

for example:

sonagent run --config user_data/config.json --agentdb sqlite:///user_data/agentdb.db --memory-url user_data/memory --datadir user_data --user-data-dir user_data --log-level info

3. Configuration

The agent supports timezone configuration for datetime operations. You can configure timezone in two ways:

1. Via config.json file: Add a timezone field to your user_data/config.json:

{
    "timezone": "Asia/Saigon",
    "api_server": {
        // ... other settings
    }
}

2. Via environment variable: Set SONAGENT_TIMEZONE environment variable (overrides config file):

export SONAGENT_TIMEZONE="America/New_York"
# or when running:
SONAGENT_TIMEZONE="Europe/London" sonagent run --config user_data/config.json ...

Priority: Environment variable > Config file > Default (UTC)

Supported timezones: Any valid timezone string supported by pytz (e.g., "UTC", "Asia/Saigon", "America/New_York", "Europe/London").

4. check rpc channal

Dev

pip install --editable .

Docker

You can run SonAgent using Docker:

Using Docker Compose (recommended)

1. Clone the repository:

git clone https://github.com/sonnhfit/SonAgent.git
cd SonAgent

2. Create a .env file with your configuration (copy from example.env):

cp example.env .env
# Edit .env with your API keys and settings

3. Create user_data directory and config:

mkdir -p user_data
# Create your config.json in user_data/

4. Run with Docker Compose:

docker-compose up

Using Docker directly

docker run -d \
  --name sonagent \
  -v $(pwd)/user_data:/sonagent/user_data \
  -p 8080:8080 \
  ghcr.io/sonnhfit/sonagent/sonagent:latest \
  run \
  --config /sonagent/user_data/config.json \
  --agentdb sqlite:///user_data/tradesv3.sqlite \
  --memory-url /sonagent/user_data/memory

Building Docker image locally

docker build -t sonagent:latest .

Available Docker tags

The CI automatically builds and pushes Docker images to GitHub Container Registry:

• ghcr.io/sonnhfit/sonagent/sonagent:latest - Latest build from main branch
• ghcr.io/sonnhfit/sonagent/sonagent:dev - Latest build from dev branch
• ghcr.io/sonnhfit/sonagent/sonagent:v1.0.13 - Specific version tag
• ghcr.io/sonnhfit/sonagent/sonagent:sha-abc123 - Specific commit SHA

Contributors

A big thank you to all the contributors who helped improve this project.

• Thank you from the freqtrade community, i learned a lot during my time contributing to it
• @kkmeansnt has made major contributions to documentation as well as testing
• Another colleague i learned a lot of interesting things from him, I know about autogen through him. thank @trungtv
• And other contributors in the contribute tab
• And you who have been paying attention, users and error reporting.