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HQ uses foundation services to power different capabilities. Configure them in the Provider Configuration panel on the home screen.

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Foundation Services

Language Models

Chat, classification, structured extraction. The core AI capability.

Embeddings

Vector search, similarity matching, semantic discovery within infospaces.

Web Search

Live web results for chat - ground responses in current information.

Geocoding

Extract and map locations from your documents. Powers geographic visualizations.
App Setup Each service type supports multiple providers. Pick what fits your needs — cloud APIs, local inference, or a mix.

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API Key Storage

Two storage modes for each provider:
Background tasks require saved keys. The Celery worker that processes large analysis runs can’t access your browser. If jobs hang or fail, check that you’ve saved keys to the backend.

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Providers

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Language Models

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Ollama

Ollama is a local language model server that has many models available and is a great way to get started with local inference.
1

Select Ollama as LLM and Embedding Provider

Ollama
2

Select a model

Ollama

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Embeddings

Used for vectorizing content in your infospaces. Configure separately from language models. Enables the chat to pull in live search results.

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Geocoding

Location extraction uses Nominatim. Self-hosted deployments include it by default. No API key needed for local Nominatim.

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Verifying Setup

  1. Open Chat and send a message — confirms language model works
  2. Upload an asset and check if it is ingested properly
  3. Ask chat to search the web — confirms web search
  4. Run an analysis with location fields — confirms geocoding

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Next Steps

Infospaces

Create workspaces for your projects

Schemas

Define what to extract from documents