Flowise

Flowise is a low-code visual tool for building LLM applications and AI agents using a drag-and-drop interface.

Prerequisites

• A Flowise instance (self-hosted or cloud)

• Your TensorX API key from app.tensorx.ai

Configuration

Flowise connects to TensorX through the ChatOpenAI Custom node, which allows you to specify a custom OpenAI-compatible endpoint.

Step 1: Add ChatOpenAI Custom Node

1. Open your Flowise canvas

2. In the left sidebar, navigate to Chat Models

3. Drag the ChatOpenAI Custom node onto your canvas

Step 2: Configure the Node

Configure the ChatOpenAI Custom node with these settings:

Parameter	Value
Base Path	https://api.tensorx.ai/v1
Model Name	An ID returned by GET /v1/models

Use the full model ID including the provider prefix.

Step 3: Create API Credential

1. Click the Credential field and select Create New

2. Select OpenAI API as the credential type

3. Enter your TensorX API key

4. Save the credential

Step 4: Adjust Optional Parameters

You can customize these optional settings:

Parameter	Description	Default
Temperature	Controls randomness (0-1)	0.7
Max Tokens	Maximum response length	Model default
Streaming	Enable streaming responses	true

Example Configuration

Base Path: https://api.tensorx.ai/v1
Model Name: <MODEL_ID>
Temperature: 0.7

Building a Chatflow

Here's how to create a basic chatflow with TensorX:

1. Add a ChatOpenAI Custom node and configure as shown above

2. Add a Chat Input node

3. Connect Chat Input → ChatOpenAI Custom

4. Add a Chat Output node

5. Connect ChatOpenAI Custom → Chat Output

6. Click Save Chatflow

Building an AI Agent

To create an agent with tools:

1. Add a ChatOpenAI Custom node configured for TensorX

2. Add an Agent node (e.g., OpenAI Functions Agent)

3. Connect your model to the Agent's LLM input

4. Add tool nodes (Calculator, Web Search, etc.)

5. Connect tools to the Agent

6. Add Chat Input and Chat Output nodes

For agent workflows that require tool calling, query GET /v1/model/info and select a model whose supports_function_calling value is true.

Model selection

Call GET /v1/models with your TensorX API key and use one of the returned IDs. If the integration depends on a capability or token limit, query GET /v1/model/info before selecting the model. See Models for examples.

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Troubleshooting

"Invalid API Key" Error

• Verify your API key at app.tensorx.ai

• Ensure the credential type is set to OpenAI API

• Check that the Base Path is exactly https://api.tensorx.ai/v1

"Model Not Found" Error

• Use the full model ID including the provider

• Check available models at tensorx.ai/models

Streaming Issues

If responses are slow or not streaming:

• Enable the Streaming option in the node settings

• Ensure your Flowise version supports streaming

Support

Need help? Contact us at [e-mail]