Versioned Memory Store for AI Agents using ProllyTree and the Rig framework #58
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…mework
What Was Built
1. Complete Memory Architecture
- Short-term Memory: Stores conversation context
- Long-term Memory: Stores learned facts and preferences
- Episodic Memory: Stores experiences and outcomes
2. Core Features Implemented
- Versioned Storage: Every memory operation creates a new version
- Memory Branching: Create experimental branches without affecting main memory
- Rollback Capability: Revert to any previous memory state
- Audit Trail: Track all memory access and decisions
3. Demo Scenarios
- Learning & Rollback: Shows how agents learn preferences and can rollback mistakes
- Memory Branching: Demonstrates safe experimentation with different behaviors
- Audit Trail: Shows decision tracking and memory access logging
- Episodic Learning: Demonstrates learning from experiences
- Interactive Chat: Full conversational agent with versioned memory
1. Setup:
cd examples/rig_versioned_memory
export OPENAI_API_KEY="your-key-here"
cargo build
2. Run Demos:
# Interactive chat (default)
cargo run
# Specific demos
cargo run -- learning # Memory learning & rollback
cargo run -- branching # Memory branching
cargo run -- audit # Audit trail demo
cargo run -- all # Run all demos
3. Interactive Commands:
- /quit - Exit
- /new - New conversation
- /version - Show current version
- /learn <concept> <fact> - Teach the agent
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Complete Memory Architecture
- Short-term Memory: Stores conversation context
- Long-term Memory: Stores learned facts and preferences
- Episodic Memory: Stores experiences and outcomes
Core Features Implemented
- Versioned Storage: Every memory operation creates a new version
- Memory Branching: Create experimental branches without affecting main memory
- Rollback Capability: Revert to any previous memory state
- Audit Trail: Track all memory access and decisions
Demo Scenarios
- Learning & Rollback: Shows how agents learn preferences and can rollback mistakes
- Memory Branching: Demonstrates safe experimentation with different behaviors
- Audit Trail: Shows decision tracking and memory access logging
- Episodic Learning: Demonstrates learning from experiences
- Interactive Chat: Full conversational agent with versioned memory
Setup: cd examples/rig_versioned_memory export OPENAI_API_KEY="your-key-here" cargo build
Run Demos: # Interactive chat (default) cargo run
Specific demos
cargo run -- learning # Memory learning & rollback
cargo run -- branching # Memory branching
cargo run -- audit # Audit trail demo
cargo run -- all # Run all demos
3. Interactive Commands:
- /quit - Exit
- /new - New conversation
- /version - Show current version
- /learn - Teach the agent