A session tunnel provider routes AI Chat traffic through a secure tunnel to a model running inside an ACTIVATE compute session. This allows you to use models hosted on your own cluster hardware without exposing them to the public internet.
How Session Tunnels Work
When you start a session in ACTIVATE with an OpenAI-compatible model server running on it, you can create a tunnel that makes the model available to AI Chat. The tunnel establishes a secure connection between the ACTIVATE platform and the model endpoint inside your session.
Session tunnel providers appear in the AI Chat provider list with the type openai-tunnel. They are automatically discovered when a tunnel with the OpenAI flag enabled is active for your user account.
Prerequisites
Before using a session tunnel provider:
You have an active ACTIVATE session running on a cluster
An OpenAI-compatible model server is running inside the session (for example, vLLM, Ollama, or TGI)
A tunnel has been created from the session with the OpenAI option enabled
Setting Up a Session Tunnel
Start a session on your cluster with enough resources to run your model (GPU, memory).
Inside the session, start an OpenAI-compatible inference server on a known port.
Create a tunnel for that session and enable the OpenAI toggle.
Once the tunnel status shows as running, the provider appears automatically in your AI Chat provider list.
You do not need to manually create a provider entry. ACTIVATE detects tunnels with the OpenAI flag and includes them in your available providers.
Using a Session Tunnel Provider
Open AI Chat.
In the provider dropdown, look for your tunnel. It will show with the status of the tunnel (for example, "running" or "stopped").
Select the tunnel provider and send a message.
If the tunnel is in a "stopped" state, you must restart the session and tunnel before it can serve requests.
Use Cases
Air-gapped environments — Run models on infrastructure that has no direct internet access. The tunnel provides a secure path from ACTIVATE to the model.
Sensitive data — Keep model inference on your own hardware to ensure data does not leave your environment.
Custom fine-tuned models — Serve models you have fine-tuned on proprietary data without uploading them to a cloud provider.
Experimentation — Quickly test different models by starting sessions with different configurations.
Limitations
Session dependency — The tunnel provider is only available while the session and tunnel are active. If the session stops, the provider becomes unavailable.
No sharing — Session tunnel providers are tied to the user who created the tunnel. They cannot be shared with other users via the permissions system.
Single user — Each tunnel is associated with one user account.
