Answer Server 25.4
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# Type

The type of model to use for your passage extractor LLM or RAG system.

For a RAG system, you can use the following options:

- GenerativeLua. Use a Lua script that performs generative question answering. For this type, you must set Script to the name and path for the script to use.

- GenerativePython. Use a Python script that performs generative question answering. For this type, you must set Script to the name and path for the script to use.

For a passage extractor LLM system, you can use GenerativeLua and GenerativePython, or one of the following options:

- ExtractiveQuestionAnsweringLLM. Use an extractive question answering LLM from Hugging Face. For this type, you must set ModelName to the model to use.

- GenerativeLLM. Use an generative LLM from Hugging Face. For this type, you must set ModelName to set the model to use.

- ExtractiveQuestionAnsweringLua. Use a Lua script that performs extractive question answering. For this type, you must set Script to the name and path for the script to use.

Type: | String
Default: |
Required: | Yes
Configuration Section: | MyLLMModule
Example: | `Type=GenerativeLLM`
See Also: | ModelName Script

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Version 25.4 | Last updated October 2025

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Product: Knowledge Discovery Answer Server 25.4

Topic Title: Type