Our Homegrown LLMs
How we fine-tuned specialized models for infrastructure automation and policy analysis
Choose your path based on your role and goals.
Get Terminal running with Amazon Nova Pro models and throttling resistance.
✅ AWS credentials with Bedrock access
✅ Python 3.10+ and Git installed
✅ Terminal/Command Line environment
Step 1: Install Terminal (2 minutes)
Option 1: Windows Installer (Easiest)
ona-terminal-setup.exe
from ReleasesC:\Program Files\OnaTerminal\
Option 2: Manual Installation
:: Clone the repository
git clone https://github.com/AsobaCloud/terminal.git
cd terminal
:: Create and activate virtual environment
python -m venv venv
call venv\Scripts\activate.bat
:: Install in development mode
pip install -e .
:: Verify installation
ona-terminal --version
# Clone repository
git clone https://github.com/AsobaCloud/terminal.git
cd terminal
# Install with automatic PATH setup
./install.sh
# Reload shell configuration
source ~/.bashrc # or ~/.zshrc, or restart terminal
Step 2: Configure AWS (2 minutes)
# Configure AWS credentials
aws configure
# Enter: Access Key ID, Secret Access Key, Region (us-east-1)
# Test Nova Pro model (recommended for best availability)
aws bedrock invoke-model \
--model-id amazon.nova-pro-v1:0 \
--body '{"messages":[{"role":"user","content":[{"text":"test"}]}],"inferenceConfig":{"max_new_tokens":10}}' \
--region us-east-1 \
--cli-binary-format raw-in-base64-out
# Launch interactive mode
ona-terminal
# Run validation commands
🤖 | /help
🤖 | /commands
🤖 | generate a python function that calculates fibonacci numbers
Transform reactive operations into proactive intelligence with industry-specific AI.
See how Ona Terminal transforms traditional reactive workflows into proactive intelligence
4:32Ona Terminal transforms operations into proactive intelligence:
Reactive Approach | Ona Terminal Proactive |
---|---|
🔴 Equipment fails unexpectedly | 🟢 AI predicts failures 2-4 weeks early |
🔴 Manual diagnosis (hours/days) | 🟢 Automated fault detection (minutes) |
🔴 Generic repair procedures | 🟢 Equipment-specific action plans |
🔴 Lost warranty claims | 🟢 Automated warranty validation |
🔴 High MTTR (8-24 hours) | 🟢 Reduced MTTR (2-4 hours) |
Result: 40-60% reduction in operational costs, 75% reduction in unplanned downtime.
Learn More:
How we fine-tuned specialized models for infrastructure automation and policy analysis
Military decision-making frameworks applied to energy asset management
Understanding the Observe-Orient-Decide-Act framework for systematic decision making
Domain-specific fine-tuned models deliver superior performance for specialized tasks.
For technical assistance, feature requests, or any other questions, please reach out to our dedicated support team.
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