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FormatterBackend: base class for prompt-engineering backends. FormatterBackend extends the abstract [Backend](../core/backend#class-backend) with a [ChatFormatter](../formatters/chat_formatter#class-chatformatter) and a [ModelIdentifier](model_ids#class-modelidentifier), bridging mellea’s generative programming primitives to models that do not yet natively support spans or structured fine-tuning. Concrete backend implementations (e.g. Ollama, HuggingFace, OpenAI) subclass FormatterBackend and supply the model-specific generate_from_context logic.

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Classes

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CLASS FormatterBackend

FormatterBackends support legacy model types. The mellea library was designed to support generative computing with spanned attention over generative programming primitives. In the ideal world, context management is handled via span scope-relations and all generative programming primitives are baked into the model via fine-tuning. I.e., the model’s instruction tuning is done in terms of generative programming primitives, and the model is then prompted with the same set of templates that were used for that tuning. Today, most models do not yet support spans and even those that do are not properly tuned to leverage generative programming primitives. The mellea library supports these legacy models primarily through prompt engineering surfaced via FormatterBackends. A FormatterBackend is a backend that uses hand-engineered prompts for rendering generative programming primitives to a model and parsing responses from the model back into mellea. By default, a FormatterBackend uses jinja2 templates for pretty-printing, and relies on the user’s ad-hoc logic for parsing. Args:
  • model_id: The model identifier to use for generation.
  • formatter: The formatter used to convert components into prompts.
  • model_options: Default model options; if None, an empty dict is used.