langhook 0.3.12

LangHook Python SDK and Server - Make any event from anywhere instantly understandable and actionable by anyone

LangHook

Make any event from anywhere instantly understandable and actionable by anyone.

LangHook transforms chaotic webhook payloads into standardized CloudEvents with a canonical format that both humans and machines can understand. Create smart event routing with natural language - no JSON wrangling required.

🎭 Demo

Visit our interactive demo to see LangHook in action: https://demo.langhook.dev (placeholder URL)

Try sending sample webhooks and see real-time event transformation, schema discovery, and natural language subscriptions.

⚡ Quickstart: Using LangHook SDK

Install the LangHook Python SDK to integrate event processing into your applications:

pip install langhook

For SDK-specific dependencies, see the SDK documentation.

Python SDK Usage

import asyncio
from sdk.python import LangHookClient, LangHookClientConfig, AuthConfig

async def main():
    # Configure client to connect to your LangHook server
    config = LangHookClientConfig(
        endpoint="http://localhost:8000",
        auth=AuthConfig(type="token", value="your-auth-token")  # Optional
    )
    
    # Use client as context manager
    async with LangHookClient(config) as client:
        # Create a subscription using natural language
        subscription = await client.create_subscription(
            "Notify me when any pull request is merged"
        )
        
        # Set up event listener
        def event_handler(event):
            print(f"Got event: {event.publisher}/{event.action}")
        
        # Start listening for events
        stop_listening = client.listen(
            str(subscription.id), 
            event_handler, 
            {"intervalSeconds": 15}
        )
        
        # ... do other work ...
        
        # Stop listening and clean up
        stop_listening()
        await client.delete_subscription(str(subscription.id))

asyncio.run(main())

TypeScript/JavaScript SDK

npm install langhook-sdk

import { LangHookClient, LangHookClientConfig } from 'langhook-sdk';

async function main() {
  // Configure client to connect to your LangHook server
  const config: LangHookClientConfig = {
    endpoint: 'http://localhost:8000',
    auth: {
      type: 'token',
      value: 'your-auth-token'  // Optional
    }
  };
  
  // Create client
  const client = new LangHookClient(config);
  
  // Initialize connection
  await client.init();
  
  // Create a subscription using natural language
  const subscription = await client.createSubscription(
    'Notify me when any pull request is merged'
  );
  
  // Set up event listener
  const eventHandler = (event) => {
    console.log(`Got event: ${event.publisher}/${event.action}`);
  };
  
  // Start listening for events
  const stopListening = client.listen(
    subscription.id.toString(),
    eventHandler,
    { intervalSeconds: 15 }
  );
  
  // ... do other work ...
  
  // Stop listening and clean up
  stopListening();
  await client.deleteSubscription(subscription.id.toString());
}

main().catch(console.error);

🚀 Running LangHook Server

Option 1: Using Docker Compose (Recommended)

The easiest way to run LangHook with all dependencies:

# Download docker-compose.yml
curl -O https://raw.githubusercontent.com/touchaponk/langhook/main/docker-compose.yml

# Start PostgreSQL + NATS + Redis + LangHook
docker-compose --profile docker up -d

# Check status
docker-compose ps

The server will be available at http://localhost:8000.

Option 2: Running LangHook Server Only

If you already have PostgreSQL, NATS, and Redis running:

# Install the server package
pip install langhook[server]

# Configure environment (copy and edit .env.example)
curl -O https://raw.githubusercontent.com/touchaponk/langhook/main/.env.example
cp .env.example .env
# Edit .env with your database and message broker URLs

# Start the server
langhook

Required services:

• NATS JetStream (message broker) - nats://localhost:4222
• Redis (rate limiting) - redis://localhost:6379
• PostgreSQL (optional, for subscriptions) - postgresql://user:pass@localhost:5432/langhook

Option 3: Running from Source Code

For development or customization:

# Clone the repository
git clone https://github.com/touchaponk/langhook.git
cd langhook

# Start dependencies only
docker-compose up -d nats redis postgres

# Install in development mode
pip install -e .

# Copy environment configuration
cp .env.example .env
# Edit .env as needed

# Run the server
langhook

Using LangHook CLI to Start the Server

The langhook command starts the full server with all services:

# Basic usage
langhook

# View help
langhook --help

# With custom configuration
DEBUG=true LOG_LEVEL=debug langhook

Other CLI tools:

• langhook-streams - Manage NATS JetStream streams
• langhook-dlq-show - View dead letter queue messages

🎯 Try it Out

Once your server is running, visit:

• http://localhost:8000/console - Interactive web console to send test webhooks and manage subscriptions
• http://localhost:8000/docs - API documentation
• http://localhost:8000/schema - View discovered event schemas

Send your first webhook:

curl -X POST http://localhost:8000/ingest/github \
  -H "Content-Type: application/json" \
  -d '{"action": "opened", "pull_request": {"number": 123}}'

🎯 Core Features

Universal Webhook Ingestion

• Single endpoint accepts webhooks from any source (GitHub, Stripe, Slack, etc.)
• HMAC signature verification ensures payload authenticity
• Rate limiting protects against abuse
• Dead letter queue for error handling

Intelligent Event Transformation

• JSONata mapping engine converts raw payloads to canonical format
• LLM-powered fallback generates mappings for unknown events
• Enhanced fingerprinting distinguishes events with same structure but different actions
• CloudEvents 1.0 compliance for interoperability
• Schema validation ensures data quality

Natural Language Subscriptions

• Plain English queries like "Notify me when PR 1374 is approved"
• LLM-generated NATS filter patterns automatically translate intent to code
• Multiple delivery channels (Slack, email, webhooks)

Dynamic Schema Registry

• Automatic schema discovery from all processed events
• Real-time schema API exposes available event types
• Schema management with deletion capabilities
• LLM grounding ensures subscriptions use real schemas

📊 Canonical Event Format

LangHook transforms any webhook into this standardized format:

{
  "publisher": "github",
  "resource": {
    "type": "pull_request",
    "id": 1374
  },
  "action": "updated",
  "timestamp": "2025-06-03T15:45:02Z",
  "payload": { /* original webhook payload */ }
}

⚙️ Configuration

LangHook uses environment variables for configuration. Copy .env.example to .env and customize:

Essential Settings

# Message broker (required)
NATS_URL=nats://localhost:4222

# Database (optional, for subscriptions)
POSTGRES_DSN=postgresql://user:pass@localhost:5432/langhook

# Cache and rate limiting (required)
REDIS_URL=redis://localhost:6379

AI Features (Required)

# Enable LLM-powered mapping suggestions
OPENAI_API_KEY=sk-your-openai-key

# Or use local Ollama
OLLAMA_BASE_URL=http://localhost:11434

See .env.example for all available options.

🛠 Usage Examples

1. Query Available Event Schemas

curl http://localhost:8000/schema/

2. Generate a Mapping Suggestion

curl -X POST http://localhost:8000/map/suggest-map \
  -H "Content-Type: application/json" \
  -d '{
    "source": "github",
    "payload": {
      "action": "opened",
      "pull_request": {"number": 1374}
    }
  }'

3. Create a Natural Language Subscription

Visit http://localhost:8000/console and try:

"Notify me when any pull request is merged"

🏗 Architecture

graph TD
    A[Webhooks] --> B[svc-ingest]
    B --> C[NATS: raw.*]
    C --> D[svc-map]
    D --> E[NATS: langhook.events.*]
    D --> SR[Schema Registry DB]
    E --> F[Rule Engine]
    F --> G[Channels]
    H[JSONata Mappings] --> D
    I[LLM Service] -.-> D
    SR --> J[/schema API]
    SR --> K[LLM Prompt Augmentation]
    K --> L[Natural Language Subscriptions]

Services

1. svc-ingest: HTTP webhook receiver with signature verification
2. svc-map: Event transformation engine with LLM fallback and schema collection
3. Schema Registry: Dynamic database tracking all event types
4. Rule Engine: Natural language subscription matching

🧪 Testing

Unit Tests

# Install dev dependencies
pip install -e ".[dev]"

# Run tests
pytest tests/ --ignore=tests/e2e/

End-to-End Tests

# Complete E2E test suite (requires Docker)
./scripts/run-e2e-tests.sh

📚 Documentation

• Agent Documentation - For AI agents and contributors
• API Reference - Interactive OpenAPI docs
• Examples - Sample payloads and mappings
• Contributing Guide - Development setup

🤝 Contributing

We welcome contributions! Install development dependencies:

pip install -e ".[dev]"

# Run linting
ruff check langhook/
ruff format langhook/

# Run type checking
mypy langhook/

🌟 Why LangHook?

Traditional Integration	LangHook
Write custom parsers for each webhook	Single canonical format
Maintain brittle glue code	JSONata mappings + LLM fallback
Technical expertise required	Natural language subscriptions
Vendor lock-in with iPaaS	Open source, self-hostable
Complex debugging	End-to-end observability

📄 License

LangHook is licensed under the MIT License.

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Ready to simplify your event integrations? Get started with the Quickstart or try the interactive demo.

For questions or support, visit our GitHub Issues.