prompt-assemble 0.3.3

A lightweight prompt assembly library using sigil-based substitution with no template logic

prompt-assemble

A lightweight prompt assembly library for building dynamic prompts with sigil-based substitution. No logic in templates — templates stay dumb, logic stays in Python.

Features

• Sigil-based substitution — Simple placeholder syntax ([[VAR_NAME]] and [[PROMPT: name]])
• Format-agnostic — Works with loose XML, JSON, or plain text
• Recursive substitution — Variable values can contain sigils, resolved in a second pass
• Comments support — Single-line (#!) and multiline (<!-- -->) comments
• No template logic — Loops, conditionals, and transforms belong in Python
• Portable — Easy to use across different environments

Installation

pip install prompt-assemble

Quick Start

from prompt_assemble import assemble

template = """
<system>
You are a [[PROMPT: persona]] specializing in [[DOMAIN]].
</system>

<task>
[[PROMPT: task-instructions]]
</task>

<question>
[[QUESTION]]
</question>
"""

components = {
    "persona": "expert software architect",
    "task-instructions": "Analyze the code and provide recommendations.",
}

variables = {
    "DOMAIN": "Python development",
    "QUESTION": "How can we improve this function?",
}

result = assemble(template, components=components, variables=variables)
print(result)

Format Support

Loose XML

<system>You are a [[PROMPT: persona]]</system>
<task>[[PROMPT: task-instructions]]</task>

JSON

{
  "system": "You are a [[PROMPT: persona]]",
  "task": "[[PROMPT: task-instructions]]"
}

Plain Text

Subject: [[SUBJECT]]

Body:
[[BODY]]

Sigil Syntax

Sigil	Purpose
[[VAR_NAME]]	Simple variable substitution
[[PROMPT: name]]	Inject a named prompt component
[[PROMPT_TAG: tag1, tag2]]	Inject all prompts matching tags (AND intersection)
[[PROMPT_TAG:N: tag1, tag2]]	Inject N most recent prompts matching tags

Comments

#! Single line comment

<!-- Multi-line
     comment -->

Comments are stripped before substitution and never reach the model.

Recursive Substitution

Variable values can themselves contain sigils:

variables = {
    "TASK": "Analyze [[CODE_TYPE]] code",
    "CODE_TYPE": "Python",
}

# Second pass resolves nested sigils

CLI Usage

pambl --template prompt.prompt --components components.json --variables vars.json

Database

PostgreSQL is required. The DatabaseSource implementation uses PostgreSQL-specific features including automatic reconnection on timeout and transaction management optimized for reliability.

PostgreSQL Support

• PostgreSQL 10+ (required for production and testing)
• Automatic connection reconnection on timeout
• Multi-tenant support via table prefixes
• Version history and tagging

Quick Setup with PostgreSQL

import psycopg2
from prompt_assemble.sources import DatabaseSource

# Connect to PostgreSQL
conn = psycopg2.connect(
    host="localhost",
    database="prompts",
    user="postgres",
    password="secret"
)

# Create source with table prefix for multi-tenant support
source = DatabaseSource(conn, table_prefix="prod_")

# Use with PromptProvider
from prompt_assemble import PromptProvider

provider = PromptProvider(source)

Docker Compose with PostgreSQL

See DOCKER.md for a complete Docker Compose setup with PostgreSQL.

Bulk Import (Preloading Database)

The bulk_import() function allows you to migrate all prompts and their metadata from one source to another. This is useful for:

• Populating a database with prompts stored in the filesystem
• Migrating between storage backends
• Backing up/restoring prompts

from prompt_assemble import (
    PromptProvider,
    FileSystemSource,
    DatabaseSource,
    bulk_import
)
import psycopg2

# Load prompts from filesystem
filesystem_source = FileSystemSource('./prompts')
source_provider = PromptProvider(filesystem_source)

# Connect to PostgreSQL database
conn = psycopg2.connect(
    host="localhost",
    database="prompts",
    user="postgres",
    password="secret"
)
database_source = DatabaseSource(conn, table_prefix="prod_")
target_provider = PromptProvider(database_source)

# Bulk import with all metadata (tags, description, owner)
results = bulk_import(source_provider, target_provider, verbose=True)

print(f"✅ Imported {results['imported']} prompts")
print(f"⚠️  Skipped {results['skipped']} existing prompts")
print(f"❌ Errors: {results['errors']}")

Bulk Import Options

# Skip prompts already in target
results = bulk_import(
    source_provider,
    target_provider,
    skip_existing=True  # Don't overwrite existing prompts
)

# Verbose output for debugging
results = bulk_import(
    source_provider,
    target_provider,
    verbose=True  # Log each import operation
)

Return Value

The bulk_import() function returns a dictionary with import statistics:

{
    "imported": 42,      # Successfully imported
    "skipped": 3,        # Skipped (already exist or skip_existing=True)
    "errors": 1,         # Failed imports
    "errors_list": [     # Details of failures
        {"name": "failing_prompt", "error": "Connection timeout"}
    ]
}

What Gets Transferred

All metadata is preserved during bulk import:

• ✅ Prompt content
• ✅ Tags (AND intersection filtering supported)
• ✅ Description
• ✅ Owner
• ✅ Versioning (for database targets)

Docker Deployment

Unified Docker Image (Backend + Frontend)

A pre-built unified image is available that includes both the Python backend and the React frontend in a single container. This is the easiest way to get started with the full application.

Image Name: ghcr.io/{owner}/prompt-assemble-with-ui

Quick Start with Unified Image

Run with filesystem backend (no database required):

docker run -p 8000:8000 \
  -v ./prompts:/app/prompts \
  ghcr.io/hominemAI/prompt-assemble-with-ui:latest

Then open http://localhost:8000 in your browser.

Run with PostgreSQL database:

docker run -p 8000:8000 \
  -e DB_HOSTNAME=postgres.example.com \
  -e DB_PORT=5432 \
  -e DB_USERNAME=postgres \
  -e DB_PASSWORD=your_secure_password \
  -e DB_DATABASE=prompts \
  -e PROMPT_ASSEMBLE_TABLE_PREFIX=prod_ \
  ghcr.io/hominemAI/prompt-assemble-with-ui:latest

With Docker Compose (PostgreSQL):

version: '3.8'

services:
  postgres:
    image: postgres:15-alpine
    environment:
      POSTGRES_DB: prompts
      POSTGRES_PASSWORD: secret
    ports:
      - "5432:5432"
    volumes:
      - postgres_data:/var/lib/postgresql/data

  prompt-assemble:
    image: ghcr.io/hominemAI/prompt-assemble-with-ui:latest
    ports:
      - "8000:8000"
    environment:
      DB_HOSTNAME: postgres
      DB_PORT: 5432
      DB_USERNAME: postgres
      DB_PASSWORD: secret
      DB_DATABASE: prompts
      PROMPT_ASSEMBLE_TABLE_PREFIX: prod_
    depends_on:
      - postgres

volumes:
  postgres_data:

Building the Unified Image Locally

To build the unified image yourself:

docker build -f Dockerfile.unified -t prompt-assemble-with-ui:latest .

The Dockerfile.unified multi-stage build:

1. Frontend stage: Clones and builds the frontend from HominemAI/prompt-assemble-ui
2. Backend stage: Builds the Python prompt-assemble library
3. Runtime stage: Combines both, serving everything on port 8000

GitHub Actions Workflow

The .github/workflows/build-image-with-ui.yml workflow automatically builds and publishes the unified image:

• Triggers: Pushes to main and tags matching ui-v*.*.*
• Image: Published to GitHub Container Registry as prompt-assemble-with-ui
• Signing: Images are signed with cosign for security

To publish a release:

git tag ui-v1.0.0
git push origin ui-v1.0.0

Architecture

The unified image uses a single port for both frontend and backend:

• Port 8000: All traffic (frontend + API)
• Frontend: React UI served at /
• API: REST endpoints at /api/*
• Frontend automatically configures: API base URL set to /api (relative path)

What's Included

• Backend: Prompt Assembly library with all features (sigil substitution, versioning, variable sets)
• Frontend: React-based UI from prompt-assemble-ui
• Storage Options:
  • Filesystem: .prompt files in /app/prompts directory
  • PostgreSQL: Full database backend with versioning and multi-tenancy

Environment Variables (Unified Image)

Same as regular backend, plus frontend-specific options:

# Backend API (port 8000)
FLASK_HOST=0.0.0.0
FLASK_PORT=8000

# Database (optional - defaults to filesystem)
DB_HOSTNAME=postgres
DB_PORT=5432
DB_USERNAME=postgres
DB_PASSWORD=secret
DB_DATABASE=prompts
PROMPT_ASSEMBLE_TABLE_PREFIX=prod_

# Frontend (optional)
VITE_API_URL=/api  # Default: /api (relative path to port 8000)

Environment Variables

The prompt-assemble library and UI support the following environment variables for configuration:

Starting the UI Server

Use the provided startup script:

python start_ui_db.py

This script automatically:

• Connects to PostgreSQL using environment variables
• Initializes the database schema
• Starts the Flask UI server
• Creates tables with the configured prefix

Database Configuration (PostgreSQL)

Variable	Type	Default	Description
DB_HOSTNAME	string	localhost	PostgreSQL server hostname
DB_PORT	int	5432	PostgreSQL server port
DB_USERNAME	string	postgres	PostgreSQL username
DB_PASSWORD	string	(required)	PostgreSQL password
DB_DATABASE	string	prompts	PostgreSQL database name
DB_SSLMODE	string	require	SSL mode: require, prefer, disable
DB_PREFIX	string	pambl_	Table name prefix (e.g., tables become pambl_prompts, pambl_prompt_tags)
PORT	int	8000	Port for the Flask UI server

Example - Local PostgreSQL:

export DB_HOSTNAME=localhost
export DB_PORT=5432
export DB_USERNAME=postgres
export DB_PASSWORD=your_password
export DB_DATABASE=prompts
export DB_PREFIX=pambl_
export PORT=8000

python start_ui_db.py

Example - DigitalOcean Managed PostgreSQL:

export DB_HOSTNAME=db-postgresql-sfo2-xxxx-do-user-xxxxx-0.e.db.ondigitalocean.com
export DB_PORT=25060
export DB_USERNAME=pambl_user
export DB_PASSWORD=your_secure_password
export DB_DATABASE=pambl_db
export DB_SSLMODE=require
export DB_PREFIX=pambl_
export PORT=8000

python start_ui_db.py

Programmatic Configuration (Legacy)

Variable	Type	Default	Description
PROMPT_ASSEMBLE_UI	bool	false	Enable/disable the web UI server. Set to "true" to activate
PROMPT_ASSEMBLE_TABLE_PREFIX	string	"" (empty)	Table prefix (deprecated - use DB_PREFIX instead)

Listener & Event Configuration

Variable	Type	Default	Description
None currently	-	-	Listener callbacks are configured programmatically

Configuration Examples

Development Environment (Local PostgreSQL)

export DB_HOSTNAME=localhost
export DB_PORT=5432
export DB_USERNAME=postgres
export DB_PASSWORD=dev_password
export DB_DATABASE=prompts_dev
export DB_SSLMODE=disable
export DB_PREFIX=dev_
export PORT=8000

python start_ui_db.py

Production (DigitalOcean PostgreSQL)

export DB_HOSTNAME=db-postgresql-sfo2-xxxxx-do-user-xxxxx-0.e.db.ondigitalocean.com
export DB_PORT=25060
export DB_USERNAME=prod_user
export DB_PASSWORD=your_secure_password
export DB_DATABASE=prompts_prod
export DB_SSLMODE=require
export DB_PREFIX=prod_
export PORT=8000

python start_ui_db.py

Testing

export DB_HOSTNAME=localhost
export DB_PORT=5432
export DB_USERNAME=postgres
export DB_PASSWORD=test_password
export DB_DATABASE=prompts_test
export DB_PREFIX=test_
export PORT=8001

python start_ui_db.py

Programmatic Configuration

You can also configure these settings directly in Python:

from prompt_assemble.sources import DatabaseSource
from prompt_assemble.api import run_server
import psycopg2

# Configure PostgreSQL database with table prefix
conn = psycopg2.connect(
    host="localhost",
    database="prompts",
    user="postgres",
    password="secret"
)
source = DatabaseSource(conn, table_prefix='myapp_')

# Configure Flask server
run_server(
    source=source,
    host='0.0.0.0',
    port=8000,
    debug=False
)

Quick Reference

All Environment Variables

# UI Server (Required for web interface)
PROMPT_ASSEMBLE_UI=true

# Flask Configuration (Optional)
FLASK_HOST=0.0.0.0
FLASK_PORT=8000
FLASK_DEBUG=false

# PostgreSQL Database Connection
DB_HOSTNAME=localhost
DB_PORT=5432
DB_USERNAME=postgres
DB_PASSWORD=secret
DB_DATABASE=prompts

# Database Options
PROMPT_ASSEMBLE_TABLE_PREFIX=myapp_  # Table prefix for multi-tenancy

Database Driver

Install psycopg2 for PostgreSQL:

pip install psycopg2-binary

Connection Resilience

The DatabaseSource automatically handles connection timeouts and network interruptions:

• Automatic reconnection — Detects closed connections and reconnects transparently
• Health checks — Validates connection before each operation
• Timeout recovery — Handles PostgreSQL idle timeout gracefully

No configuration required — reconnection happens automatically on these operations:

• save_prompt() - Save/update prompts
• delete_prompt() - Delete prompts
• refresh() - Reload metadata
• get_raw() - Fetch content
• All variable set operations

Testing

Run the full test suite:

pytest tests/

Note: Database-specific tests require PostgreSQL:

# Skip database tests (for environments without PostgreSQL)
pytest tests/ -k "not test_database"

# Run only with PostgreSQL available
PGHOST=localhost PGUSER=postgres PGPASSWORD=secret PGDATABASE=test_prompts pytest tests/test_database_source.py

Test Coverage: 135 passing tests covering core library, FileSystem source, listener system, save/delete operations, and bulk import functionality. PostgreSQL-specific tests are marked as requiring PostgreSQL.

Contributing

Contributions welcome! Please open an issue or submit a pull request.

License

MIT License — see LICENSE file for details.