fleet-memory/hindsight-embed/README.md
Nicolò Boschi 728ce13cea
fix: rename moltbot to openclawd (#246)
* fix: rename moltbot to openclawd

* fix

* fix

* fix: use single shared pg0 database for all banks + add default mission

This commit fixes a critical database isolation issue and adds the default
mission feature for the openclawd plugin.

## Changes:

**hindsight-embed:**
- Fixed daemon_client.py to use single shared database: pg0://hindsight-embed
- Previously, each bank_id would create a separate pg0 instance (wrong!)
- Now all banks share the same database with isolation via bank_id parameter
- Updated README to clarify database architecture

**openclawd plugin (v0.0.5):**
- Added default bank mission describing OpenClawd's multi-channel assistant role
- Added setBankMission() method to client
- Integrated mission setting during plugin initialization
- Added bankMission to plugin config schema with sensible default
- Updated docs to explain shared database architecture

## Why this matters:
Bank isolation should happen WITHIN the database (via separate tables/schemas),
not via separate database instances. Using HINDSIGHT_EMBED_BANK_ID to create
separate pg0 databases was architecturally wrong and caused confusion.

* ci: rename moltbot to openclawd in workflows and release script

- Updated build-moltbot-integration → build-openclawd-integration in test.yml
- Updated release-moltbot-integration → release-openclawd-integration in release.yml
- Updated all working directories from moltbot to openclawd
- Updated artifact names from moltbot-integration to openclawd-integration
- Added openclawd package.json to release.sh version bump script
2026-01-30 10:31:29 +01:00

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4.6 KiB
Markdown

# hindsight-embed
Hindsight embedded CLI - local memory operations with automatic daemon management.
This package provides a simple CLI for storing and recalling memories using Hindsight's memory engine. It automatically manages a background daemon for fast operations - no manual server setup required.
## How It Works
`hindsight-embed` uses a background daemon architecture for optimal performance:
1. **First command**: Automatically starts a local daemon (first run downloads dependencies and loads ML models - can take 1-3 minutes)
2. **Subsequent commands**: Near-instant responses (~1-2s) since daemon is already running
3. **Auto-shutdown**: Daemon automatically exits after 5 minutes of inactivity
The daemon runs on `localhost:8889` and uses an embedded PostgreSQL database (pg0) - everything stays local on your machine.
## Installation
```bash
pip install hindsight-embed
# or with uvx (no install needed)
uvx hindsight-embed --help
```
## Quick Start
```bash
# Interactive setup (recommended)
hindsight-embed configure
# Or set your LLM API key manually
export OPENAI_API_KEY=sk-...
# Store a memory (bank_id = "default")
hindsight-embed memory retain default "User prefers dark mode"
# Recall memories
hindsight-embed memory recall default "What are user preferences?"
```
## Commands
### configure
Interactive setup wizard:
```bash
hindsight-embed configure
```
This will:
- Let you choose an LLM provider (OpenAI, Groq, Google, Ollama)
- Configure your API key
- Set the model and memory bank ID
- Start the daemon with your configuration
### memory retain
Store a memory:
```bash
hindsight-embed memory retain default "User prefers dark mode"
hindsight-embed memory retain default "Meeting on Monday" --context work
hindsight-embed memory retain myproject "API uses JWT authentication"
```
### memory recall
Search memories:
```bash
hindsight-embed memory recall default "user preferences"
hindsight-embed memory recall default "upcoming events"
```
Use `-o json` for JSON output:
```bash
hindsight-embed memory recall default "user preferences" -o json
```
### memory reflect
Get contextual answers that synthesize multiple memories:
```bash
hindsight-embed memory reflect default "How should I set up the dev environment?"
```
### bank list
List all memory banks:
```bash
hindsight-embed bank list
```
### daemon
Manage the background daemon:
```bash
hindsight-embed daemon status # Check if daemon is running
hindsight-embed daemon start # Start the daemon
hindsight-embed daemon stop # Stop the daemon
hindsight-embed daemon logs # View last 50 lines of logs
hindsight-embed daemon logs -f # Follow logs in real-time
hindsight-embed daemon logs -n 100 # View last 100 lines
```
## Configuration
### Interactive Setup
Run `hindsight-embed configure` for a guided setup that saves to `~/.hindsight/embed`.
### Environment Variables
| Variable | Description | Default |
|----------|-------------|---------|
| `HINDSIGHT_EMBED_LLM_API_KEY` | LLM API key (or use `OPENAI_API_KEY`) | Required |
| `HINDSIGHT_EMBED_LLM_PROVIDER` | LLM provider (`openai`, `groq`, `google`, `ollama`) | `openai` |
| `HINDSIGHT_EMBED_LLM_MODEL` | LLM model | `gpt-4o-mini` |
| `HINDSIGHT_EMBED_BANK_ID` | Default memory bank ID (optional, used when not specified in CLI) | `default` |
**Note:** All banks share a single pg0 database (`pg0://hindsight-embed`). Bank isolation happens within the database via the `bank_id` parameter passed to CLI commands.
### Files
| Path | Description |
|------|-------------|
| `~/.hindsight/embed` | Configuration file |
| `~/.hindsight/config.env` | Alternative config file location |
| `~/.hindsight/daemon.log` | Daemon logs |
| `~/.hindsight/daemon.lock` | Daemon lock file (PID) |
## Use with AI Coding Assistants
This CLI is designed to work with AI coding assistants like Claude Code, Cursor, and Windsurf. Install the Hindsight skill:
```bash
curl -fsSL https://hindsight.vectorize.io/get-skill | bash
```
This will configure the LLM provider and install the skill to your assistant's skills directory.
## Troubleshooting
**Daemon won't start:**
```bash
# Check logs for errors
hindsight-embed daemon logs
# Stop any stuck daemon and restart
hindsight-embed daemon stop
hindsight-embed daemon start
```
**Slow first command:**
This is expected - the first command needs to download dependencies, start the daemon, and load ML models. First run can take 1-3 minutes depending on network speed. Subsequent commands will be fast (~1-2s).
**Change configuration:**
```bash
# Re-run configure (automatically restarts daemon)
hindsight-embed configure
```
## License
Apache 2.0