Domo is your personal AI agent on your computer

This AI agent is designed to serve as a fully private, locally running personal assistant that helps users manage and understand their digital workspace without relying on external services. Its core aim is to provide a free, secure alternative to cloud-based tools by enabling intelligent operations on local documents (such as searching for information, summarizing files or entire folders, classifying and organizing content, and ranking documents by relevance) while also augmenting its capabilities with internet-based research. By combining local data access with AI-driven reasoning, it allows users to efficiently navigate and act on their information while keeping full control over their data.

Domo is your personal assistant on your computer

Run

Start Ollama before using the assistant.

Start the app with:

./run_app.sh

Run a workflow directly with:

.venv/bin/python -m tools.<name_of_tool>.main

Run tests with:

PYTHONPATH=. pytest

Notes:

• Open the local URL shown by Streamlit, typically http://localhost:8051.
• The Streamlit assistant uses a session-scoped UI with three panes:
  • chat history
  • a derived agent-state panel
  • an activity log
• The core agent is now a deterministic plan executor with a fixed AgentState:
  • status
  • goal
  • plan
  • current_step
  • memory
  • last_error
• Domo prepares a full plan first, waits for approval, and then executes step by step.
• The planner uses a fixed capability registry. Important capability groups include:
  • read tools such as web search and local document readers
  • LLM tasks such as direct answers, summarization, evaluation, document ranking, and generated document sets
  • write tools such as single-document writes, PDF writes, JSON writes, search-result writes, and generated multi-document writes
• For requests like “create a file per result,” Domo can generate structured filename/content records and write them with write_generated_documents.
• Chat history and UI logs are stored outside the core agent state.
• This repo must be run with the local .venv, not a global Streamlit install.
• ./run_app.sh uses .venv/bin/streamlit explicitly, which avoids ModuleNotFoundError from Anaconda/global Python.
• If you prefer the raw command, use .venv/bin/streamlit run app/streamlit_app.py --server.port 8051.
• Use the streamlit CLI to run the app, not python app/streamlit_app.py.
• See CHANGELOG.md for release history.

Structure

domo/
├── README.md
├── config.yaml
├── pyproject.toml
├── requirements.txt
├── run_app.sh
├── app/
│   └── streamlit_app.py
├── assistant/
│   ├── audit.py
│   ├── controller.py
│   ├── domo_agent.py
│   ├── llm_tasks.py
│   ├── planner.py
│   ├── policy.py
│   ├── registry.py
│   ├── runtime.py
│   └── schemas.py
├── integrations/
│   └── ollama_client.py
├── tools/
├── workflows/
└── data/
    ├── inputs/
    └── outputs/
        └── logs/

License

This project is licensed under the MIT License.