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https://github.com/helicone/n8n-nodes-helicone

n8n node for Helicone
https://github.com/helicone/n8n-nodes-helicone

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n8n node for Helicone

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# n8n-nodes-helicone

This is an n8n community node that provides a LangChain-compatible Helicone Chat Model for use in AI chains and workflows. The node routes requests to your chosen LLM provider through the Helicone AI Gateway.

[Helicone](https://helicone.ai) is an open-source LLM observability platform that helps developers monitor, debug, and improve production AI applications.

## Installation

### 1. Build the Node
Clone the repository and install dependencies:
```bash
git clone https://github.com/helicone/n8n-nodes-helicone.git
cd n8n-nodes-helicone
pnpm install
pnpm build
```

### 2. Install as n8n Community Node
You can install this node as an n8n community node:

```bash
# Install via npm
npm install n8n-nodes-helicone

# Or install via pnpm
pnpm add n8n-nodes-helicone
```

### 3. Alternative: Manual Installation
If you prefer to install manually, navigate to your n8n folder (usually `~/.n8n` on macOS/Linux):
```bash
cd ~/.n8n
mkdir custom
cd custom
pnpm init
```

Link your built node to the n8n custom folder:
```bash
pnpm link /path/to/your/n8n-nodes-helicone
```
Replace `/path/to/your/n8n-nodes-helicone` with the actual path to your repository.

### 4. Start n8n
```bash
n8n start
```

### 5. Access n8n Interface
Open your browser and go to: `http://localhost:5678`

## 6. Add Helicone API Credentials

- Go to **Credentials > New**
- Select **Helicone LLM Observability**
- Enter your Helicone API key (get it from [Helicone Dashboard](https://helicone.ai/dashboard))
- The base URL is automatically set to `https://ai-gateway.helicone.ai/`

## 7. Create a workflow and add your Helicone Chat Model node

The Helicone Chat Model node is designed to work as part of any AI chain. It outputs a LangChain-compatible model that can be used with other AI nodes.

**Node Configuration:**
1. **AI Model:** Choose any model supported by Helicone AI Gateway (find them here: https://helicone.ai/models - e.g, `gpt-4.1-mini`, `claude-3-opus-20240229`).
2. **Options:**
- **Temperature:** Sampling temperature (0-2)
- **Max Tokens:** Maximum number of tokens to generate
- **Top P:** Nucleus sampling parameter (0-1)
- **Frequency Penalty:** Control repetition (-2 to 2)
- **Presence Penalty:** Control new topics (-2 to 2)
- **Response Format:** Text or JSON
- **Timeout:** Request timeout in milliseconds
- **Max Retries:** Number of retry attempts

**Helicone Options:**
- **Custom Properties:** JSON object for metadata and filtering
- **Session Tracking:** Session ID, Path, and Name for grouping requests
- **Caching:** Enable response caching with configurable TTL (up to 365 days)

## How It Works

The Helicone Chat Model node uses the [Helicone AI Gateway](https://ai-gateway.helicone.ai) to route requests to your chosen LLM provider. The node implements the `LmChatHelicone` class and provides a LangChain-compatible ChatOpenAI interface.

This provides:
- **Unified Interface:** Single endpoint for multiple providers
- **Automatic fallbacks:** If the primary provider is down, the node will automatically use a fallback provider
- **Observability:** Track usage, performance, and costs across providers
- **Caching:** Reduce costs with intelligent response caching and reduce latency with intelligent caching
- **Session Tracking:** Group related requests with session management
- **Custom Properties:** Add metadata for filtering and analysis

## Usage in AI Chains

This node is designed to be used as part of n8n's AI chain functionality:

1. **Add the Helicone Chat Model node** to your workflow
2. **Configure the model** with your desired parameters
3. **Connect it to other AI nodes** that accept `ai_languageModel` inputs
4. **Use in chains** for complex AI workflows

The node outputs a LangChain-compatible model that can be used with:
- Chat nodes
- Chain nodes
- Other AI processing nodes

## Helicone Features

The node supports various Helicone observability features:

- **Custom Properties:** Add metadata to requests for filtering and analysis
- **Session Tracking:** Group related requests with Session ID, Path, and Name
- **Caching:** Enable response caching with configurable TTL (up to 365 days)
- **Automatic Logging:** All requests are automatically logged in your Helicone dashboard

## Response Format

The node returns a LangChain ChatOpenAI model instance that can be used with other AI nodes. The underlying responses include:

- Generated content
- Token usage information
- Model information
- Helicone-specific metadata

All requests are automatically logged in your Helicone dashboard for observability and analysis.

## Troubleshooting

### Common Issues

1. **Authentication Errors**
- Verify your Helicone API key is correct (starts with `pk-` for write access)
- Ensure your Helicone account has access to the chosen provider

2. **Model Errors**
- Validate your model name is correct for the chosen provider
- Check if the model is available in your Helicone account

3. **Chain Integration Issues**
- Ensure the node is properly connected to other AI nodes
- Verify the output type is compatible with downstream nodes

### Getting Help

- [Helicone Documentation](https://docs.helicone.ai)
- [n8n Community Forum](https://community.n8n.io)
- [Helicone Discord](https://discord.gg/helicone)

## License

MIT

## Resources

- [n8n community nodes documentation](https://docs.n8n.io/integrations/community-nodes/)
- [Helicone documentation](https://docs.helicone.ai)
- [Helicone GitHub](https://github.com/Helicone/helicone)
- [This Node's GitHub](https://github.com/juliettech13/n8n-nodes-helicone)
- [LangChain documentation](https://js.langchain.com/)