Provider Reference

This page summarizes the current provider modules.

tramai-anthropic

Class:

• AnthropicProvider

Purpose:

• Anthropic Messages API integration

Auth:

• API key

Config shape:

tramai:
  providers:
    anthropic:
      api-key: ${ANTHROPIC_API_KEY}
      api-key-secret-ref: null
      base-url: https://api.anthropic.com

tramai-openai

Classes:

• OpenAiProvider
• OpenAiCompatibleProvider
• CodexAuthFileTokenSource (experimental)

Purpose:

• public OpenAI API integration
• OpenAI-compatible endpoint integration

Auth modes:

• API key
• explicit bearer token
• local Codex auth file, experimental
• Spring secret references through SecretValueResolver

Config shape:

tramai:
  providers:
    openai:
      api-key: ${OPENAI_API_KEY}
      api-key-secret-ref: null
      bearer-token: null
      bearer-token-secret-ref: null

tramai-ollama

Class:

• OllamaProvider

Purpose:

• local Ollama chat API integration

Config shape:

tramai:
  providers:
    ollama:
      base-url: http://localhost:11434

Capability Summary

Current shared baseline:

• request/response normalization
• raw string operations
• streaming support
• tool-calling support through engine-owned orchestration
• structured output via Tramai's schema-in-prompt pipeline
• explicit provider registry integration
• operation-level timeout propagation
• engine-owned retries for retryable provider failures

Not implemented across the provider layer yet:

• native provider-specific structured output modes
• externalized provider-level retry-policy configuration
• externalized provider-level timeout-policy configuration
• bundled cloud-specific secret-store resolvers

Choosing A Provider

Use:

• Anthropic when your app is centered on Claude models
• OpenAI when your app is centered on OpenAI models or compatible gateways
• Ollama for local development and self-hosted local runs
• Gemini when your app targets Google's Gemini models
• DeepSeek for cost-effective reasoning models
• Bedrock when operating within AWS infrastructure
• Azure OpenAI when your organization uses Azure

Use multiple providers when different tasks have different needs. The provider registry supports routing different models to different providers and defining fallback chains.