> For the complete documentation index, see [llms.txt](https://docs.tensorx.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.tensorx.ai/automation-platforms/dify.md).

# Dify

Dify is an open-source LLMOps platform for building AI applications, chatbots, and agents with a visual workflow interface.

## Prerequisites

* A Dify instance (self-hosted or [Dify Cloud](https://cloud.dify.ai))
* Your TensorX API key from [app.tensorx.ai](https://app.tensorx.ai)

## Configuration

Dify connects to TensorX through the **OpenAI API Compatible** plugin, which supports custom OpenAI-compatible endpoints.

### Step 1: Install the Plugin

1. Go to your Dify workspace
2. Navigate to **Plugins** in the left sidebar
3. Search for **OpenAI API Compatible**
4. Click **Install** to add the plugin

{% hint style="info" %}
The OpenAI API Compatible plugin is an official Dify plugin that supports LLMs, text embedding, speech-to-text, and text-to-speech from OpenAI-compatible providers.
{% endhint %}

### Step 2: Add Model Provider

1. Go to **Settings** → **Model Providers**
2. Find **OpenAI API Compatible** in the list
3. Click **Add Model**

### Step 3: Configure the Model

Fill in the configuration form:

| Field                | Value                         |
| -------------------- | ----------------------------- |
| **Model Type**       | `LLM`                         |
| **Model Name**       | `deepseek/deepseek-chat-v3.1` |
| **API Key**          | Your TensorX API key          |
| **API Endpoint URL** | `https://api.tensorx.ai/v1`   |

Click **Save** to add the model.

### Step 4: Add More Models (Optional)

Repeat Step 3 to add additional TensorX models:

| Model Name             | Best For                      |
| ---------------------- | ----------------------------- |
| `z-ai/glm-5.1`         | Tool calling, code generation |
| `minimax/minimax-m2.5` | Reasoning, functions          |
| `moonshotai/kimi-k2.5` | Vision, long context          |

## Using TensorX Models

### In Chat Applications

1. Create a new **Chatbot** or **Agent** application
2. In the orchestration panel, click the model selector
3. Select your configured TensorX model
4. Adjust parameters (temperature, max tokens) as needed

### In Workflows

1. Create a new **Workflow** application
2. Add an **LLM** node to your workflow
3. Select your TensorX model from the dropdown
4. Configure the prompt and parameters

## Recommended Models

{% hint style="info" %}
**For Coding Tasks:**

* `z-ai/glm-5.1` - Best for tool calling and structured outputs
* `minimax/minimax-m2.5` - Best for complex reasoning tasks
  {% endhint %}

| Model ID                      | Use Case                             |
| ----------------------------- | ------------------------------------ |
| `deepseek/deepseek-chat-v3.1` | General chat, balanced performance   |
| `z-ai/glm-5.1`                | Tool calling, function calling, code |
| `minimax/minimax-m2.5`        | Reasoning, analysis, complex tasks   |
| `moonshotai/kimi-k2.5`        | Vision tasks, long context           |

## Advanced Configuration

### Adding Embedding Models

To use TensorX for text embeddings:

1. Go to **Settings** → **Model Providers**
2. Click **Add Model** under OpenAI API Compatible
3. Set **Model Type** to `Text Embedding`
4. Enter the embedding model name
5. Configure API key and endpoint URL

### Adding Speech Models

For text-to-speech or speech-to-text:

1. Add a new model with type `TTS` or `Speech2Text`
2. Use the appropriate TensorX audio model
3. Configure API key and endpoint URL

## Agent Configuration

When building agents that use tools:

1. Select `z-ai/glm-5.1` as your model (best tool calling support)
2. Enable **Function Calling** in the agent settings
3. Add your desired tools from the Dify tool library
4. Configure tool permissions and parameters

## Example: Building a Code Assistant

1. Create a new **Agent** application
2. Select `z-ai/glm-5.1` as the model
3. Add a system prompt:

   ```
   You are an expert programming assistant. Help users write, debug, and explain code.
   ```
4. Enable tools like **Code Interpreter** if available
5. Set temperature to `0.3` for more deterministic outputs
6. Publish your application

## Troubleshooting

### "Model Not Found" Error

* Ensure you're using the full model ID (e.g., `deepseek/deepseek-chat-v3.1`)
* Verify the API Endpoint URL is exactly `https://api.tensorx.ai/v1`

### "Authentication Failed" Error

* Check that your API key is correct
* Verify the key at [app.tensorx.ai](https://app.tensorx.ai)
* Ensure there are no extra spaces in the API key field

### Model Not Appearing in Selector

* Confirm the plugin is installed and enabled
* Check that the model was saved successfully in Model Providers
* Refresh the page or restart the application

### Slow Responses

* Check your Dify instance's network connection
* Consider using a model with faster response times
* Enable streaming in the application settings

## Support

Need help? Contact us at <support@tensorx.ai>


---

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