ajarbot/example_usage.py

"""Example: Using the Memory System with SOUL and User files."""

from memory_system import MemorySystem


def main() -> None:
    print("=" * 60)
    print("Memory System - SOUL + User Files Example")
    print("=" * 60)

    memory = MemorySystem()

    # 1. SOUL - Define agent personality
    print("\n[1] Updating SOUL (Agent Personality)...")
    memory.update_soul(
        """
## Additional Traits
- I remember user preferences and adapt
- I maintain context across conversations
- I learn from corrections and feedback

## Goals
- Help users be more productive
- Provide accurate, helpful information
- Build long-term relationships through memory
""",
        append=True,
    )

    # 2. Create user profiles
    print("\n[2] Creating user profiles...")

    memory.update_user(
        "alice",
        """
## Personal Info
- Name: Alice Johnson
- Role: Senior Python Developer
- Timezone: America/New_York (EST)
- Active hours: 9 AM - 6 PM EST

## Preferences
- Communication: Detailed technical explanations
- Code style: PEP 8, type hints, docstrings
- Favorite tools: VS Code, pytest, black

## Current Projects
- Building a microservices architecture
- Learning Kubernetes
- Migrating legacy Django app

## Recent Conversations
- 2026-02-12: Discussed SQLite full-text search implementation
- 2026-02-12: Asked about memory system design patterns
""",
    )

    memory.update_user(
        "bob",
        """
## Personal Info
- Name: Bob Smith
- Role: Frontend Developer
- Timezone: America/Los_Angeles (PST)
- Active hours: 11 AM - 8 PM PST

## Preferences
- Communication: Concise, bullet points
- Code style: ESLint, Prettier, React best practices
- Favorite tools: WebStorm, Vite, TailwindCSS

## Current Projects
- React dashboard redesign
- Learning TypeScript
- Performance optimization work

## Recent Conversations
- 2026-02-11: Asked about React optimization techniques
- 2026-02-12: Discussed Vite configuration
""",
    )

    # 3. Add long-term memory
    print("\n[3] Adding long-term memory...")
    memory.write_memory(
        """
# System Architecture Decisions

## Memory System Design
- **Date**: 2026-02-12
- **Decision**: Use SQLite + Markdown for memory
- **Rationale**: Simple, fast, no external dependencies
- **Files**: SOUL.md for personality, users/*.md for user context

## Search Strategy
- FTS5 for keyword search (fast, built-in)
- No vector embeddings (keep it simple)
- Per-user search capability for privacy
""",
        daily=False,
    )

    # 4. Add daily log
    print("\n[4] Adding today's notes...")
    memory.write_memory(
        """
## Conversations

### Alice (10:30 AM)
- Discussed memory system implementation
- Showed interest in SQLite FTS5 features
- Plans to integrate into her microservices project

### Bob (2:45 PM)
- Quick question about React performance
- Mentioned working late tonight on dashboard
- Prefers short, actionable answers
""",
        daily=True,
    )

    # 5. Perform searches
    print("\n[5] Searching memory...")

    print("\n  -> Global search for 'python':")
    results = memory.search("python", max_results=3)
    for r in results:
        print(f"     {r['path']}:{r['start_line']} - {r['snippet']}")

    print("\n  -> Alice's memory for 'project':")
    alice_results = memory.search_user(
        "alice", "project", max_results=2
    )
    for r in alice_results:
        print(f"     {r['path']}:{r['start_line']} - {r['snippet']}")

    print("\n  -> Bob's memory for 'React':")
    bob_results = memory.search_user("bob", "React", max_results=2)
    for r in bob_results:
        print(f"     {r['path']}:{r['start_line']} - {r['snippet']}")

    # 6. Retrieve specific content
    print("\n[6] Retrieving specific content...")

    soul = memory.get_soul()
    print(f"\n  SOUL.md ({len(soul)} chars):")
    print("  " + "\n  ".join(soul.split("\n")[:5]))
    print("  ...")

    alice_context = memory.get_user("alice")
    print(f"\n  Alice's profile ({len(alice_context)} chars):")
    print("  " + "\n  ".join(alice_context.split("\n")[:5]))
    print("  ...")

    # 7. Show system status
    print("\n[7] System Status:")
    status = memory.status()
    for key, value in status.items():
        print(f"     {key}: {value}")

    print(f"\n     Users: {', '.join(memory.list_users())}")

    # 8. Demonstrate contextual response
    print("\n" + "=" * 60)
    print("CONTEXTUAL RESPONSE EXAMPLE")
    print("=" * 60)

    def get_context_for_user(username: str) -> str:
        """Build context for an AI response."""
        user_soul = memory.get_soul()
        user_prefs = memory.get_user(username)
        recent_memory = memory.search_user(
            username, "recent", max_results=2
        )

        recent_snippet = (
            recent_memory[0]["snippet"]
            if recent_memory
            else "No recent activity"
        )

        return (
            f"\n=== SOUL ===\n{user_soul[:200]}...\n\n"
            f"=== USER: {username} ===\n{user_prefs[:200]}...\n\n"
            f"=== RECENT CONTEXT ===\n{recent_snippet}\n"
        )

    print("\nContext for Alice:")
    print(get_context_for_user("alice"))

    memory.close()
    print("\nMemory system closed")


if __name__ == "__main__":
    main()