Project Sentinel Documentation
Personal AI agents swarm - self-evolving assistant system.
Document
Description
roadmap
Development phases, milestones, current status
architecture
System design, components, data flow
agents
Agent types, roles, orchestration
memory
Memory hierarchy, persistence, retrieval
interfaces
Human-AI communication channels
task_system
Task scheduling and execution
tool_calling
LLM-driven function execution
safety
Boundaries, sandboxing, self-modification rules
Path
Purpose
src/sentinel/core/
Orchestrator, config, shared types, logging
src/sentinel/agents/
Agent implementations (dialog, sleep, awareness, code)
src/sentinel/memory/
Memory hierarchy and persistence
src/sentinel/interfaces/
Telegram, CLI adapters
src/sentinel/llm/
LLM provider abstraction and intelligent routing
src/sentinel/tasks/
Task scheduling, parsing, execution
src/sentinel/tools/
Tool calling framework, registry, built-in tools
src/sentinel/workspace/
Sandboxed code execution environment
tests/
Unit tests
tests/integration/
Integration tests with live APIs
data/
SQLite DBs, workspace, file storage
Component
Technology
Runtime
Python 3.12+, uv
LLM Providers
Anthropic (Claude), OpenRouter, Local (Ollama/LM Studio)
Tool Calling
Native Anthropic tool use, OpenAI function calling
Storage
SQLite (aiosqlite) with FTS5 full-text search
Task Scheduling
SQLite-backed with async execution
Code Execution
Isolated Python venvs with sandbox validation
Interface
Telegram Bot API, CLI
Testing
pytest with integration tests
File
Purpose
Edited By
data/identity.md
Agent personality, capabilities, working style
User
data/agenda.md
Ongoing tasks, plans, preferences, notes
Agent (self-edited)
These files are loaded at agent initialization and used to build the system prompt context.