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 is an open-source LLM observability platform that helps developers monitor, debug, and improve production AI applications.
Clone the repository and install dependencies:
git clone https://github.com/juliettech13/n8n-nodes-helicone.git
cd n8n-nodes-helicone
pnpm install
pnpm buildYou can install this node as an n8n community node:
# Install via npm
npm install n8n-nodes-helicone
# Or install via pnpm
pnpm add n8n-nodes-heliconeIf you prefer to install manually, navigate to your n8n folder (usually ~/.n8n on macOS/Linux):
cd ~/.n8n
mkdir custom
cd custom
pnpm initLink your built node to the n8n custom folder:
pnpm link /path/to/your/n8n-nodes-heliconeReplace /path/to/your/n8n-nodes-helicone with the actual path to your repository.
n8n startOpen your browser and go to: http://localhost:5678
- Go to Credentials > New
- Select Helicone LLM Observability
- Enter your Helicone API key (get it from Helicone Dashboard)
- The base URL is automatically set to
https://ai-gateway.helicone.ai/
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:
- 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). - 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)
The Helicone Chat Model node uses the Helicone AI Gateway 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
This node is designed to be used as part of n8n's AI chain functionality:
- Add the Helicone Chat Model node to your workflow
- Configure the model with your desired parameters
- Connect it to other AI nodes that accept
ai_languageModelinputs - 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
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
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.
-
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
- Verify your Helicone API key is correct (starts with
-
Model Errors
- Validate your model name is correct for the chosen provider
- Check if the model is available in your Helicone account
-
Chain Integration Issues
- Ensure the node is properly connected to other AI nodes
- Verify the output type is compatible with downstream nodes
MIT