# Models used by the evaluation. Replace every <...> value that the selected methods need before running.
# base_url: null uses the client's default endpoint. api_key_env names the environment
# variable that holds the key for that endpoint (OPENAI_API_KEY by default); each key is sent only to its endpoint.

answer:              # answers every question
  model: <ANSWER_MODEL>
  base_url: null
  api_key_env: OPENAI_API_KEY
  reasoning: <true|false>   # true for a reasoning model: the methods' internal calls use max_completion_tokens
  tokenizer: <TOKENIZER>    # tiktoken encoding that counts the context budgets and chunk sizes

judge:               # grades each answer against the gold
  model: <JUDGE_MODEL>
  base_url: null
  api_key_env: OPENAI_API_KEY
  reasoning: <true|false>

embedding:           # embeddings of every method that retrieves by vector similarity
  model: <EMBEDDING_MODEL>
  base_url: null
  api_key_env: OPENAI_API_KEY
  dim: <EMBEDDING_DIM>
  batch_size: <EMBEDDING_BATCH_SIZE>   # texts per embedding request
  tokenizer: <EMBEDDING_TOKENIZER>     # tiktoken encoding of the embedding model (input truncation)

memory:              # optional: the model of every LLM call inside a method (hipporag, remem,
                     # letta and mirix also answer with it)
  model: null        # null = the answer model, at answer.base_url
  base_url: null
  api_key_env: null  # null = OPENAI_API_KEY
  reasoning: null    # null = the answer model's setting; required when memory.model is another model