jasper-recall

name	jasper-recall
description	Local RAG system for agent memory using ChromaDB and sentence-transformers. Provides semantic search over session logs, daily notes, and memory files. Use when you need persistent memory across sessions, want to search past conversations, or build agents that remember context. Commands: recall "query", index-digests, digest-sessions.

Jasper Recall

Local RAG (Retrieval-Augmented Generation) system for AI agent memory. Gives your agent the ability to remember and search past conversations.

When to Use

• Memory recall: Search past sessions for context before answering
• Continuous learning: Index daily notes and decisions for future reference
• Session continuity: Remember what happened across restarts
• Knowledge base: Build searchable documentation from your agent's experience

Quick Start

Setup

One command installs everything:

npx jasper-recall setup

This creates:

• Python venv at ~/.openclaw/rag-env
• ChromaDB database at ~/.openclaw/chroma-db
• CLI scripts in ~/.local/bin/

Basic Usage

Search your memory:

recall "what did we decide about the API design"
recall "hopeIDS patterns" --limit 10
recall "meeting notes" --json

Index your files:

index-digests  # Index memory files into ChromaDB

Create session digests:

digest-sessions          # Process new sessions
digest-sessions --dry-run  # Preview what would be processed

How It Works

Three Components

1. digest-sessions — Extracts key info from session logs (topics, tools used)
2. index-digests — Chunks and embeds markdown files into ChromaDB
3. recall — Semantic search across your indexed memory

What Gets Indexed

By default, indexes files from ~/.openclaw/workspace/memory/:

• *.md — Daily notes, MEMORY.md
• session-digests/*.md — Session summaries
• repos/*.md — Project documentation
• founder-logs/*.md — Development logs (if present)

Embedding Model

Uses sentence-transformers/all-MiniLM-L6-v2:

• 384-dimensional embeddings
• ~80MB download on first run
• Runs locally, no API needed

Agent Integration

Memory-Augmented Responses

# Before answering questions about past work
results = exec("recall 'project setup decisions' --json")
# Include relevant context in your response

Automated Indexing (Heartbeat)

Add to HEARTBEAT.md:

## Memory Maintenance
- [ ] New session logs? → `digest-sessions`
- [ ] Memory files updated? → `index-digests`

Cron Job

Schedule regular indexing:

{
  "schedule": { "kind": "cron", "expr": "0 */6 * * *" },
  "payload": {
    "kind": "agentTurn",
    "message": "Run index-digests to update the memory index"
  },
  "sessionTarget": "isolated"
}

CLI Reference

recall

recall "query" [OPTIONS]

Options:
  -n, --limit N     Number of results (default: 5)
  --json            Output as JSON
  -v, --verbose     Show similarity scores

index-digests

index-digests

Indexes markdown files from:
  ~/.openclaw/workspace/memory/*.md
  ~/.openclaw/workspace/memory/session-digests/*.md
  ~/.openclaw/workspace/memory/repos/*.md
  ~/.openclaw/workspace/memory/founder-logs/*.md

Skips files that haven't changed (content hash check).

digest-sessions

digest-sessions [OPTIONS]

Options:
  --dry-run    Preview without writing
  --all        Process all sessions (not just new)
  --recent N   Process only N most recent sessions

Configuration

Custom Paths

Set environment variables:

export RECALL_WORKSPACE=~/.openclaw/workspace
export RECALL_CHROMA_DB=~/.openclaw/chroma-db
export RECALL_SESSIONS_DIR=~/.openclaw/agents/main/sessions

Chunking

Default settings in index-digests:

• Chunk size: 500 characters
• Overlap: 100 characters

Troubleshooting

"No index found"

index-digests  # Create the index first

"Collection not found"

rm -rf ~/.openclaw/chroma-db  # Clear and rebuild
index-digests

Model download slow First run downloads ~80MB model. Subsequent runs are instant.

Links

• GitHub: https://github.com/E-x-O-Entertainment-Studios-Inc/jasper-recall
• npm: https://www.npmjs.com/package/jasper-recall
• ClawHub: https://clawhub.ai/skills/jasper-recall