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How to use Netra Runtime with Dify
Dify is an open-source platform for building LLM apps: chatbots, agents, and workflows with a visual editor. Any model behind an OpenAI-style endpoint can be registered as a provider, which is exactly what a Netra Runtime deployment exposes. Once registered, your Netra-served model appears in Dify's model picker like any built-in provider.
What you need
- A Dify workspace (Dify Cloud or self-hosted) with admin access to model settings.
- A Netra Runtime API key from your dashboard at app.netraruntime.com. The API base URL is
https://api.netraruntime.com/v1(self-hosted deployments use their own endpoint URL instead).
Step 1: install the OpenAI-API-compatible provider
Open the Dify Marketplace and install the OpenAI-API-compatible plugin (published by langgenius, the Dify team). This is the provider that lets you register arbitrary OpenAI-style endpoints. On some self-hosted versions it is already available under model providers without a separate install.
Step 2: add your Netra model
Go to Settings → Model Provider → OpenAI-API-compatible → Add model and fill in:
| Field | Value |
|---|---|
| Model Type | LLM |
| Model Name | The exact model id, e.g. qwen3.6-35b (/v1/models lists the current set) |
| API Key | Your Netra API key |
| API endpoint URL | https://api.netraruntime.com/v1 |
| Model context size | The context window of your deployed model |
| Max tokens limit | The output cap you want per request |
Enter the base URL only, not the full /chat/completions path; Dify appends the endpoint path itself. Enable streaming so chat apps render tokens as they arrive, and turn on function calling support if your deployed model handles tools.
Step 3: select the model in your app
In Dify Studio, open your app or workflow, click the model selector, and choose your Netra model under the OpenAI-API-compatible provider. It now serves chat apps, agent nodes, and LLM nodes in workflows. You can also set it as the workspace default in the system model settings.
Troubleshooting
- Credential validation fails. Check that the endpoint URL ends at
/v1and that the model name exactly matches an id listed at/v1/models. Validation sends a tiny real request, so a wrong model id fails here. - Self-hosted Dify can't reach the endpoint. The Dify containers need a network route to your Netra deployment. For a private VPC endpoint, run Dify inside the same network.
- Long answers get cut off. Raise the max tokens limit on the model entry, and check the per-app max tokens parameter in the model settings panel.
Frequently asked questions
Which Dify provider do I use for Netra Runtime?
Use the OpenAI-API-compatible provider plugin from the Dify Marketplace. It lets you register any model behind an OpenAI-style endpoint by entering the model name, API key, and endpoint URL.
Does this work on Dify Cloud and self-hosted Dify?
Both. Dify Cloud needs a Netra endpoint reachable from the public internet, while self-hosted Dify can also reach private endpoints inside your VPC or on-prem network.
Can I use Netra Runtime for embeddings in Dify?
If your Netra deployment serves an embeddings endpoint, add it as a separate model with the Text Embedding type. Don't route embeddings through a chat model entry.