Configuration Reference¶

This page documents all configuration files and environment variables used by the Curaway backend. Configuration is split between YAML files (checked into the repo) and environment variables (managed per deployment).

config/guardrails.yaml¶

The guardrails configuration controls the AI agent's input classification and output validation. It prevents the agent from soliciting or disclosing sensitive information and keeps conversations within the medical tourism intake scope.

Classifier Categories¶

The input classifier assigns each user message to one of these categories before the message reaches the LLM:

Forbidden Output Patterns¶

The output validator scans every LLM response against these 12 regex patterns. If any pattern matches, the response is blocked and a safe fallback is returned instead.

Response Templates¶

When a message is blocked, the system returns a pre-configured response template:

response_templates:
  medical_advice: >
    I understand your concern, but I'm not able to provide medical diagnoses
    or treatment recommendations. I can help connect you with qualified
    medical professionals who can properly evaluate your condition.
  emergency: >
    If you are experiencing a medical emergency, please call your local
    emergency services immediately. I can help you find appropriate care
    after your immediate needs are addressed.
  pii_solicitation: >
    For your safety, please do not share sensitive personal information
    like social security numbers or credit card details in this chat.
    Any required information will be collected securely during the
    formal intake process.
  off_topic: >
    I'm here to help with your medical travel needs. Could you tell me
    more about the medical procedure you're interested in or the
    destination you're considering?

Medical Keywords (Multilingual)¶

The classifier uses medical keyword lists in four languages to improve classification accuracy:

File Validation Limits¶

When guardrail file validation is enabled, uploaded files are checked against these limits:

config/model_registry.yaml¶

The model registry defines which LLM models are available, their capabilities, and how they are assigned to different tasks.

Model Definitions¶

models:
  gpt-4o:
    provider: openai
    context_window: 128000
    max_output_tokens: 4096
    supports_vision: true
    supports_function_calling: true
    cost_per_1k_input: 0.005
    cost_per_1k_output: 0.015

  gpt-4o-mini:
    provider: openai
    context_window: 128000
    max_output_tokens: 4096
    supports_vision: true
    supports_function_calling: true
    cost_per_1k_input: 0.00015
    cost_per_1k_output: 0.0006

  claude-3-5-sonnet:
    provider: anthropic
    context_window: 200000
    max_output_tokens: 8192
    supports_vision: true
    supports_function_calling: true
    cost_per_1k_input: 0.003
    cost_per_1k_output: 0.015

Tier Assignments¶

Models are assigned to tiers that map to specific use cases:

Fallback Chains¶

If the primary model is unavailable, the system falls back through this chain:

fallback_chains:
  default:
    - gpt-4o
    - claude-3-5-sonnet
    - gpt-4o-mini
  cost_sensitive:
    - gpt-4o-mini
    - claude-3-5-sonnet
  accuracy_critical:
    - gpt-4o
    - claude-3-5-sonnet

Environment Variables¶

All environment variables are required unless marked as optional. Never commit actual values -- use .env.example as a template.

Database¶

Authentication¶

Feature Management¶

Observability¶

Email & Notifications¶

Storage (Cloudflare R2)¶

AI / Embeddings¶

Application¶