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HTM - Hierarchical Temporal Memory

Examples

Examples¶

HTM includes working example programs that demonstrate various features and integration patterns. These examples show real-world usage patterns and can serve as templates for your own applications.

Running Examples¶

All examples require the database to be configured:

export HTM_DATABASE__URL="postgresql://user@localhost:5432/htm_development"

Then run any example with:

ruby examples/<example_name>.rb

Available Examples¶

Core Usage¶

Example	Description
Basic Usage	Core HTM operations: remember, recall, forget
LLM Configuration	Configure providers, custom embeddings, and tag extractors
File Loading	Load markdown files with frontmatter and chunking

Advanced Features¶

Example	Description
Timeframes	Natural language temporal queries
Robot Groups	Multi-robot coordination with shared memory
MCP Client	Interactive AI chat with memory tools
Telemetry	Prometheus metrics and Grafana visualization

Quick Reference¶

Basic Operations¶

# Initialize HTM
htm = HTM.new(robot_name: "My Robot")

# Remember information
node_id = htm.remember("PostgreSQL supports vector search via pgvector.")

# Recall memories
results = htm.recall("database features", strategy: :hybrid, limit: 5)

# Forget a memory
htm.forget(node_id)

Configuration¶

HTM.configure do |config|
  # Use any RubyLLM-supported provider
  config.embedding.provider = :openai  # or :ollama, :anthropic, etc.
  config.embedding.model = 'text-embedding-3-small'

  config.tag.provider = :openai
  config.tag.model = 'gpt-4o-mini'
end

File Loading¶

# Load markdown files into memory
htm.load_file("docs/guide.md")
htm.load_directory("docs/", pattern: "**/*.md")

# Query nodes from a file
nodes = htm.nodes_from_file("docs/guide.md")

Prerequisites¶

Most examples require:

PostgreSQL with pgvector extension
LLM Provider - Ollama (default), OpenAI, Anthropic, etc.
Ruby 3.2+ with HTM gem installed

Ollama Setup (Default Provider)¶

# Install Ollama
curl https://ollama.ai/install.sh | sh

# Pull required models
ollama pull nomic-embed-text  # For embeddings
ollama pull gemma3:latest     # For tag extraction

Using Cloud Providers¶

# OpenAI
export OPENAI_API_KEY="your-key"

# Anthropic
export ANTHROPIC_API_KEY="your-key"

# Google Gemini
export GEMINI_API_KEY="your-key"

See Also¶