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You can configure the full prompt that Sensible inputs to a large language model (LLM). You can apply configurations to multiple fields in a config, and you can override them for individual fields. When you write a prompt in a Sensible Instruct method, Sensible combines your prompt with other information to create the full prompt. The full prompt includes:
  • a prompt introduction
  • “context”, made up of chunks excerpted from the document and of page metadata. For more information about chunks, see the Notes section.
  • concatenated descriptive prompts you configure in a Sensible Instruct method, such as in the List or Query Group methods.
See the following image for an example of a full prompt that Sensible inputs to an LLM for the Query Group method: Click to enlarge The following table shows parameters that configure parts of the full prompt and that are global, or common to all Sensible Instruct methods: You can configure all of these parameters in the SenseML editor and in the Sensible Instruct editor. For example, the following screenshots show prompt settings in Sensible Instruct for a Query Group field: Click to enlarge The following screenshot shows prompt settings in Sensible Instruct for all fields in a config: Click to enlarge

Global Sensible Instruct parameters

The following table shows global parameters, or parameters that are common to all Sensible Instruct methods. You can configure these parameters for all fields in a config, or on a field-by-field basis. For parameters specific to a Sensible instruct method, see its reference topic, for example, the Query Group method reference topic. Like global parameters, method-specific parameters can be set for all fields in a config, or on a field-by-field basis.

Notes

For an overview of how Sensible Instruct methods work, see the following steps.
  1. To meet the LLM’s input token limit, Sensible splits the document into chunks.
  2. Sensible selects the most relevant chunks and combines them with page-hinting data to create a “context”.
  3. Sensible creates a full prompt for the LLM that includes the context and the descriptive prompts you configure in the method. For an example of a full prompt, see the beginning of this topic.
  4. Sensible returns the LLM’s response.
For specifics about how each Sensible instruct method works, see the Notes section for each method’s SenseML reference topic, for example, List method.