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BYK-RAG (Retrieval-Augmented Generation Module)

The BYK-RAG Module is part of the Burokratt ecosystem, designed to provide retrieval-augmented generation (RAG) capabilities for Estonian government digital services. It ensures reliable, multilingual, and compliant AI-powered responses by integrating with multiple LLM providers syncing with knowledge bases, and exposing flexible configuration and monitoring features for administrators.

Features

  • Configurable LLM Providers

    • Support for AWS Bedrock, Azure AI, Google Cloud, OpenAI, Anthropic, and self-hosted open-source LLMs.
    • Admins can create "connections" and switch providers/models without downtime.
    • Models searchable via dropdown with cache-enabled indicators.

  • Knowledge Base Integration

    • Continuous sync with central knowledge base (CKB).
    • Last sync timestamp displayed in UI.
    • LLMs restricted to answering only from CKB content.
    • “I don’t know” payload returned when confidence is low.

  • Citations & Transparency

    • All responses are accompanied with clear citations.

  • Analytics & Monitoring

    • External Langfuse dashboard for API usage, inference trends, cost analysis, and performance logs.
    • Agencies can configure cost alerts and view alerts via LLM Alerts UI.
    • Logs integrated with Grafana Loki.

Storing Langfuse Secrets

  1. Generate API keys from Langfuse UI (Settings → Project → API Keys)

  2. Copy the script to vault container:

docker cp store-langfuse-secrets.sh vault:/tmp/store-langfuse-secrets.sh
  1. Execute the script with your API keys:
docker exec -e LANGFUSE_INIT_PROJECT_PUBLIC_KEY=<your public key> \
            -e LANGFUSE_INIT_PROJECT_SECRET_KEY=<your secret key> \
            vault sh -c "chmod +x /tmp/store-langfuse-secrets.sh && /tmp/store-langfuse-secrets.sh"