lobesync 0.1.1

Personal AI assistant for tasks, notes, memories, and checklists

Lobesync

A personal AI assistant for your terminal. Manage tasks, notes, memories, and checklists through natural conversation — powered by Claude and built on LangGraph.

Lobesync — Personal AI Assistant
Type /help for commands · exit to quit

You: Create a checklist "Launch" and add tasks for writing tests and updating docs
Lobesync: Done! Created checklist "Launch" (ID: 1) with two tasks — "Write tests" (ID: 2)
          and "Update docs" (ID: 3), both set to pending.

You: Mark write tests as in progress
Lobesync: Updated "Write tests" to in progress. ✓

Features

• Natural language interface — just talk to it, no commands to memorize
• Tasks with deadlines, statuses, and checklist grouping
• Checklists with items and pending-task guards
• Notes for storing anything
• Memories — the agent proactively remembers personal facts about you across sessions
• Session management — multiple conversations, each with its own history and incremental summary
• Streaming responses with live Markdown rendering
• Cost-efficient — single LLM call per turn (planner + executor + completion)
• Local SQLite by default — your data stays on your machine

Architecture

Lobesync uses a LangGraph graph with four nodes:

user input
    │
    ▼
┌─────────┐   direct response (streamed)   ┌────────────┐
│ Planner │ ──────────────────────────────▶ │ Commitment │ ──▶ END
└─────────┘                                 └────────────┘
    │ tool calls needed                            ▲
    ▼                                              │
┌──────────┐                              ┌────────────────┐
│ Executor │ ────────────────────────────▶ │   Completion   │
└──────────┘                              └────────────────┘

• Planner — single LLM call (Haiku). Streams a direct response for chat, or calls make_plan for data operations. Receives user memories in system prompt (cached) + session summary + last 5 messages.
• Executor — runs the plan. Atomic groups use one session (all-or-nothing). Independent steps run in separate sessions.
• Completion — generates the final natural language response with tool results as context.
• Commitment — saves user message, assistant message, and tool calls to DB. Regenerates session summary every 5 messages.

Installation

Using pipx (recommended for CLI tools)

pipx install lobesync

Using pip

pip install lobesync

From source

git clone https://github.com/panchalchetan618/lobesync
cd lobesync
pip install -e .

Setup

Run lobesync for the first time and the setup wizard will guide you through:

1. Entering your Anthropic API key
2. Choosing a local SQLite database (recommended) or providing your own database URL

Config is saved to ~/.lobesync/config.json. Local database is stored at ~/.lobesync/lobesync.db.

Usage

lobesync

CLI Commands

Command	Description
/sessions	List all chat sessions
/session new	Start a new session
/session new <name>	Start a new named session
/session <id>	Switch to an existing session
/help	Show all commands
exit	Quit

Example interactions

You: Add a task to review PRs by Friday
You: What are my pending tasks?
You: Create a note about the deployment process
You: I prefer concise responses
You: Mark the PR review task as done
You: Start a new checklist for the Q2 release

The agent remembers personal facts across sessions — tell it your preferences, goals, or anything relevant and it will factor them in automatically.

Configuration

Variable	Description
ANTHROPIC_API_KEY	Your Anthropic API key
DATABASE_URL	SQLAlchemy database URL (default: local SQLite)

Set via the setup wizard or in ~/.lobesync/config.json:

{
  "ANTHROPIC_API_KEY": "sk-ant-...",
  "DATABASE_URL": "sqlite:////home/you/.lobesync/lobesync.db"
}

You can also use a .env file in the working directory or environment variables as fallback.

Models used

Node	Model	Reason
Planner	claude-haiku-4-5	Fast, cheap, handles planning and direct chat
Completion	claude-haiku-4-5	Generates final response from tool results
Summarizer	claude-haiku-4-5	Compresses old conversation history

Tech stack

• Anthropic Python SDK
• LangGraph
• SQLModel
• Rich

Contributing

Pull requests are welcome. For major changes, open an issue first.

License

MIT