Schema for Jarvisv2 LLM Model Settings

---
$id: https://skeleton.botmd.io/jarvisv2/LLMModelSettings.schema
$schema: http://json-schema.org/draft-07/schema#
description: Defines settings for the LLM model during query flow.
properties:
  context_size:
    anyOf:
    - type: integer
    - type: 'null'
    default: null
    description: Context size aka context length
    title: Context size
  context_template:
    default: |-
      You are a friendly and warm question-answer hospital assistant, employed as an employee of the hospital.
              The only information you know is the context provided. You can use only that information as your hidden knowledge base.
              When you answer, the context provided will be known as "my training."
              If the context provided provides links, show it to the user.
    description: Template for the context
    title: Context Template
    type: string
  guardrail_identifier:
    default: arn:aws:bedrock:us-west-2:394252546268:guardrail/f83z6kx1d6hl
    description: Name of AWS guardrail if applicable. Should start with arn:aws:bedrock:us-west-2:.
    title: Guardrail Identifier
    type: string
  guardrail_version:
    default: '1'
    description: AWS Guardrail version (string) if applicable
    title: Guardrail Version
    type: string
  max_tokens:
    default: 1000
    description: Max tokens returned by LLM
    title: Max Tokens
    type: integer
  model:
    description: Name of LLM as per HuggingFace
    minLength: 1
    title: Model
    type: string
  reranker_similarity_cutoff:
    default: 0
    description: Similarity score cutoff for node postprocessing based on reranker
      score
    title: Reranker Similarity Cutoff
    type: number
  similarity_cutoff:
    default: 0.38
    description: Similarity score cutoff for node postprocessing based on embedding
      score
    title: Similarity Cutoff
    type: number
  similarity_top_k:
    default: 6
    description: Number of nodes to return after retrieval
    title: Similarity top K
    type: integer
  supported_language_codes:
    description: Restricts bot to only answer only these languages. Provide list of
      2-letter language codes, and double-check that Amazon Comprehend / Translate
      supports them.
    items:
      type: string
    title: Supported language codes
    type: array
  system_prompt:
    default: Answer the QUERY below only using the DOCUMENTs below as context, and
      not your trained knowledge.
    description: Prompt for the LLM
    title: System Prompt
    type: string
  temperature:
    default: 0
    description: Temperature
    title: Temperature
    type: number
required: [model]
title: LLM Model Settings
type: object