AI Model Providers
The model is yours, not ours#
Abrq DIP ships no AI model and calls no vendor by default. AI-assisted features — today, the DW Generator — only work after an admin registers a provider under Settings → AI Models, pointing the platform at an endpoint the customer controls: a commercial API account you own, or an in-network model server.
Only schema metadata is ever sent to a provider by the DW Generator — table and column structure, never row data and never stored secrets. Privacy is under your control: point the provider at an in-network endpoint and nothing leaves your network.
Supported provider types#
| Provider type | Notes |
|---|---|
| OpenAI | Hosted API |
| Anthropic (Claude) | Hosted API |
| Google Gemini | Hosted API |
| Azure OpenAI | Requires an endpoint URL and a deployment name |
| Amazon Bedrock (preview) | Hosted API |
| OpenAI-compatible | Ollama, vLLM, LM Studio, and similar servers; requires a base URL |
| Custom external endpoint | Requires a base URL |
| Custom on-prem endpoint | Requires a base URL |
| Internal on-prem (OpenAI-compatible) | Requires a base URL |
Registering a provider#
- Open Settings → AI Models and add a provider.
- Fill in:
- Display name.
- Provider — one of the types above.
- Base URL / endpoint — required for the Azure, OpenAI-compatible, custom, and on-prem types; optional for the hosted vendors (their default endpoints are used).
- API key — optional: leave it empty for endpoints that don't enforce authentication (common for in-network model servers). When set, it is encrypted into the platform's secrets store and never returned by the API — the UI only shows whether a key is stored. Clearing or replacing it is an explicit action on edit.
- Default model, and optionally an allowed models list to restrict which models may be used.
- Organization / Project / Tenant ID and deployment name — only where the provider type calls for them (deployment name is required for Azure OpenAI).
- Enabled and default flags — the default provider is the one the DW Generator uses.
- Use Test to probe reachability and authentication; the outcome (status, message, time) is stored on the provider row so the last-known state is always visible. A models refresh action lists the models the endpoint exposes.
Tip. For a fully offline deployment, run an OpenAI-compatible server (Ollama, vLLM, or similar) inside your network and register it with the Internal on-prem type and no API key.
Configuration knobs#
The provider registry lives in the database, encrypted where needed — there are no per-provider environment variables. The only environment variable in the AI subsystem is the request timeout:
| Variable | Default | Effect |
|---|---|---|
ABRQ_AI_REQUEST_TIMEOUT_SECONDS |
120 |
Timeout applied to every outbound request to a provider |
Network and trust considerations#
Requests to a provider originate from the backend and go directly to the configured base URL with the timeout above. The base URL is admin-supplied deployment configuration — point it only at endpoints you trust, and prefer in-network endpoints when data-governance rules require it. The deployment's outbound-traffic policy is described in Transport and egress.
Audit trail#
Provider creation, updates, deletion, and connection tests are audited; the audit records carry the provider's non-secret fields only — never the API key. See Audit.