Home Schema Example JSON Schema

Query Engine Settings

Type: object

This contains all the settings needed for the Jarvis v2 query engine.

Enabled

Type: boolean Default: true

Whether this query engine is enabled.

Modules

Type: array

The modules to be used in the query engine.

Must contain a minimum of 1 items

No Additional Items

Each item of this array must be:


Standard IR Module Settings

Type: object

Settings for our standard IR-based module.

Answer Finder

Type: object

Configure how we retrieve, score, and rank answers.

Reranker

Type: object

Configure how we rerank answers.

Reranker Functions

Type: array

Rerankers are executed one after the other.

No Additional Items

Each item of this array must be:


Min Cutoff Reranker

Type: object

Minimum cutoff reranker function. All resulting candidates will have scores greater or equal to the cutoff.

Conditions

Type: array Default: []

Conditions for documents before we apply the reranker Documents that fail the condition will be passed through to the next reranker.

No Additional Items

Each item of this array must be:

Condition

Type: object

A condition to check before applying a reranker.

Operator

Type: enum (of string)

The comparison operator.

Must be one of:

  • "gt"
  • "gte"
  • "lt"
  • "lte"
  • "eq"
  • "ne"
  • ">"
  • "≥"
  • ">="
  • "<"
  • "≤"
  • "<="
  • "="
  • "=="
  • "!="
  • "<>"
  • "≠"

Score Key

Type: string

The key in the score vector to use for the comparison. When the key doesn't exist or is None, we return false.

Must be at least 1 characters long

Keep Original If All Discarded

Type: boolean Default: false

If all documents are discarded, keep the original candidates.

Score Key

Type: string

The key in the score vector to use for the cutoff.

Must be at least 1 characters long

Type

Type: const Default: "min-cutoff-reranker"
Specific value: "min-cutoff-reranker"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Max Cutoff Reranker

Type: object

Maximum cutoff reranker function. All resulting candidates will have scores lesser or equal to the cutoff.

Conditions

Type: array Default: []

Conditions for documents before we apply the reranker Documents that fail the condition will be passed through to the next reranker.

No Additional Items

Each item of this array must be:

Keep Original If All Discarded

Type: boolean Default: false

If all documents are discarded, keep the original candidates.

Score Key

Type: string

The key in the score vector to use for the cutoff.

Must be at least 1 characters long

Type

Type: const Default: "max-cutoff-reranker"
Specific value: "max-cutoff-reranker"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Top K Reranker

Type: object

Reranker keeps the top K candidates based on distinct score value and discards the rest.

K

Type: integer Default: 1

Keep the top K candidates.

Value must be strictly greater than 0

Keep Ties

Type: boolean Default: true

Whether to keep candidates whose score tie for top K. Defaults to true.

Score Key

Type: string

The key in the score vector to use for the cutoff.

Must be at least 1 characters long

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Load Full Document Reranker

Type: object

A pseudo-reranker that calls the load method on all candidate documents.

Type

Type: const Default: "load-full-document-reranker"
Specific value: "load-full-document-reranker"

Order By Reranker

Type: object

Reorder the candidates based on scoring keys.

Order By

Type: array of string

The scoring fields to order the candidates by. Prefix with a +/- for ascending/descending order. You can also access sv, doc, and source fields using JMESPath syntax, e.g., sv.missed_tokens_count, doc.name, source.phone, etc.

Must contain a minimum of 1 items

No Additional Items

Each item of this array must be:

Type

Type: const Default: "order-by-reranker"
Specific value: "order-by-reranker"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

First N Reranker

Type: object

Reranker keeps the first N candidates and discards the rest.

N

Type: integer Default: 16

Keep the first N candidates.

Value must be strictly greater than 0

Type

Type: const Default: "first-n-reranker"
Specific value: "first-n-reranker"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Last N Reranker

Type: object

Reranker keeps the last N candidates and discards the rest.

N

Type: integer Default: 16

Keep the last N candidates.

Value must be strictly greater than 0

Type

Type: const Default: "last-n-reranker"
Specific value: "last-n-reranker"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Answer Field Reranker

Type: object

Reranker that keeps entries containing matching answer fields.

Keep Original If All Discarded

Type: boolean Default: false

If all documents are discarded, keep the original candidates.

Match Type

Type: enum (of string) Default: "all"

Whether to match all or any of the answer fields.

Must be one of:

  • "all"
  • "any"

Type

Type: const Default: "answer-field-reranker"
Specific value: "answer-field-reranker"

Discard Or Keep Information Reranker

Type: object

Reranker that shortlists or discards entry based on the condition.

Discard Or Keep

Type: enum (of string)

The field that decides whether to discard or keep the entries.

Must be one of:

  • "discard"
  • "keep"

Type

Type: const Default: "discard-or-keep-information-reranker"
Specific value: "discard-or-keep-information-reranker"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Retriever

Type: object

Configure how we retrieve answer.

Retriever Functions

Type: array

Retrievers are executed concurrently and then concatenated after.

Must contain a minimum of 1 items

No Additional Items

Each item of this array must be:


Answer Phrase Retriever

Type: object

Settings for retrieving intent phrases.

Size

Type: integer Default: 128

The size parameter to use when retrieving documents from the KB. Note that scan is not used.

Value must be greater or equal to 0

Tiered Fuzzy Match

Default: {"fuzzy_transpositions": true, "length_thresholds": [3, 6], "prefix_length": 2, "scores": [0.8, 0.9, 1.0]}

Configure how we perform fuzzy matching when retrieving phrases.

TieredFuzzyMatchSettings

Type: object

Settings for tiered fuzzy matching.

Fuzzy Transpositions

Type: boolean Default: true

Whether to allow transpositions in fuzzy matching. See https://opensearch.org/docs/latest/query-dsl/full-text/match/#transpositions

Length Thresholds

Type: array Default: [3, 6]

A tuple [a, b] where string lengths in [0, a] do not have fuzzy matching, lengths in (a, b] allow 1 Levenshtein distance, and lengths (b, ∞) allow 2 Levenshtein distances.

Must contain a minimum of 2 items

Must contain a maximum of 2 items

No Additional Items

Tuple Validation

Item at 1 must be:
Item at 2 must be:

Prefix Length

Type: integer Default: 2

The length of the prefix to use for fuzzy matching. See https://opensearch.org/docs/latest/query-dsl/full-text/match/#prefix-length

Value must be greater or equal to 0

Type

Type: const Default: "answer-phrase-retriever"
Specific value: "answer-phrase-retriever"

Intent Phrase Retriever

Type: object

Settings for retrieving intent phrases.

Size

Type: integer Default: 128

The size parameter to use when retrieving documents from the KB. Note that scan is not used.

Value must be greater or equal to 0

Type

Type: const Default: "intent-phrase-retriever"
Specific value: "intent-phrase-retriever"

Answer Retriever

Type: object

Settings for retrieving answers.

Max Clause Count

Type: integer Default: 1000

The maximum number of answer phrase clauses to use in a query. When there are more clauses, multiple queries will be executed concurrently.

Value must be greater or equal to 0

Size

Type: integer Default: 128

The size parameter to use when retrieving documents from the KB. Note that scan is not used.

Value must be greater or equal to 0

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Retrieval Weights Settings

Type: array

The weights to use for each field in the retrieval function. By default, each field is weighted 1.

No Additional Items

Each item of this array must be:

Retrieval Weights

Type: object

Settings for retrieval weights.

Answer Type

Type: enum (of string)

The answer type where the object is used.

Must be one of:

  • "clinical-trial"
  • "dialogue"
  • "directory"
  • "document"
  • "document-snippet"
  • "monograph"
  • "roster"
  • "test"

Weight

Default: "matched_tokens_precision"

The weight to assign to the field. It can also be one of the supported phrase scoring keys or a constant weight value.

Type: enum (of string)

Must be one of:

  • "phrase_tokens_count"
  • "matched_tokens_score"
  • "missed_tokens_score"
  • "matched_tokens_count"
  • "missed_tokens_count"
  • "matched_tokens_precision"
  • "missed_tokens_precision"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Scorer

Type: object

Configure how we score answers.

Scorer Functions

Type: array

Scorer functions are executed concurrently and then merged together after.

Must contain a minimum of 1 items

No Additional Items

Each item of this array must be:


Basic Answer Scorer

Type: object

Score an answer based on standard token level P/R/F metrics.

Institution Priority Order

Type: array

The list of institution affinities.

No Additional Items

Each item of this array must be:

InstitutionAffinity

Type: object

Affinities

Type: array of string

The list of institutions starting from most to least affiniated. This field is case insensitive.

Must contain a minimum of 1 items

No Additional Items

Each item of this array must be:

Type

Type: const Default: "directory-answer-scorer"
Specific value: "directory-answer-scorer"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Answer Phrase Finders

Type: array

Configure how we retrieve, score, and rank answer phrases. This is done per answer type/field. Multiple finders for each answer type/field is supported.

No Additional Items

Each item of this array must be:

Answer Phrase Finder Settings

Type: object

Configure how we retrieve, score, and rank answer phrases in the module.

Answer Field

Type: string

The field in the answer where the object is used.

Answer Type

Type: enum (of string)

The answer type where the object is used.

Must be one of:

  • "clinical-trial"
  • "dialogue"
  • "directory"
  • "document"
  • "document-snippet"
  • "monograph"
  • "roster"
  • "test"

Reranker

Type: object

Configure how we rerank phrases.

Reranker Functions

Type: array

Rerankers are executed one after the other.

No Additional Items

Each item of this array must be:


Min Cutoff Reranker

Type: object

Minimum cutoff reranker function. All resulting candidates will have scores greater or equal to the cutoff.

Conditions

Type: array Default: []

Conditions for documents before we apply the reranker Documents that fail the condition will be passed through to the next reranker.

No Additional Items

Each item of this array must be:

Condition

Type: object

A condition to check before applying a reranker.

Operator

Type: enum (of string)

The comparison operator.

Must be one of:

  • "gt"
  • "gte"
  • "lt"
  • "lte"
  • "eq"
  • "ne"
  • ">"
  • "≥"
  • ">="
  • "<"
  • "≤"
  • "<="
  • "="
  • "=="
  • "!="
  • "<>"
  • "≠"

Score Key

Type: string

The key in the score vector to use for the comparison. When the key doesn't exist or is None, we return false.

Must be at least 1 characters long

Keep Original If All Discarded

Type: boolean Default: false

If all documents are discarded, keep the original candidates.

Score Key

Type: string

The key in the score vector to use for the cutoff.

Must be at least 1 characters long

Type

Type: const Default: "min-cutoff-reranker"
Specific value: "min-cutoff-reranker"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Max Cutoff Reranker

Type: object

Maximum cutoff reranker function. All resulting candidates will have scores lesser or equal to the cutoff.

Conditions

Type: array Default: []

Conditions for documents before we apply the reranker Documents that fail the condition will be passed through to the next reranker.

No Additional Items

Each item of this array must be:

Keep Original If All Discarded

Type: boolean Default: false

If all documents are discarded, keep the original candidates.

Score Key

Type: string

The key in the score vector to use for the cutoff.

Must be at least 1 characters long

Type

Type: const Default: "max-cutoff-reranker"
Specific value: "max-cutoff-reranker"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Top K Reranker

Type: object

Reranker keeps the top K candidates based on distinct score value and discards the rest.

K

Type: integer Default: 1

Keep the top K candidates.

Value must be strictly greater than 0

Keep Ties

Type: boolean Default: true

Whether to keep candidates whose score tie for top K. Defaults to true.

Score Key

Type: string

The key in the score vector to use for the cutoff.

Must be at least 1 characters long

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Load Full Document Reranker

Type: object

A pseudo-reranker that calls the load method on all candidate documents.

Type

Type: const Default: "load-full-document-reranker"
Specific value: "load-full-document-reranker"

Order By Reranker

Type: object

Reorder the candidates based on scoring keys.

Order By

Type: array of string

The scoring fields to order the candidates by. Prefix with a +/- for ascending/descending order. You can also access sv, doc, and source fields using JMESPath syntax, e.g., sv.missed_tokens_count, doc.name, source.phone, etc.

Must contain a minimum of 1 items

No Additional Items

Each item of this array must be:

Type

Type: const Default: "order-by-reranker"
Specific value: "order-by-reranker"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

First N Reranker

Type: object

Reranker keeps the first N candidates and discards the rest.

N

Type: integer Default: 16

Keep the first N candidates.

Value must be strictly greater than 0

Type

Type: const Default: "first-n-reranker"
Specific value: "first-n-reranker"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Last N Reranker

Type: object

Reranker keeps the last N candidates and discards the rest.

N

Type: integer Default: 16

Keep the last N candidates.

Value must be strictly greater than 0

Type

Type: const Default: "last-n-reranker"
Specific value: "last-n-reranker"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Answer Field Reranker

Type: object

Reranker that keeps entries containing matching answer fields.

Keep Original If All Discarded

Type: boolean Default: false

If all documents are discarded, keep the original candidates.

Match Type

Type: enum (of string) Default: "all"

Whether to match all or any of the answer fields.

Must be one of:

  • "all"
  • "any"

Type

Type: const Default: "answer-field-reranker"
Specific value: "answer-field-reranker"

Discard Or Keep Information Reranker

Type: object

Reranker that shortlists or discards entry based on the condition.

Discard Or Keep

Type: enum (of string)

The field that decides whether to discard or keep the entries.

Must be one of:

  • "discard"
  • "keep"

Type

Type: const Default: "discard-or-keep-information-reranker"
Specific value: "discard-or-keep-information-reranker"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Scorer

Type: object

Configure how we score phrases.

Scorer Functions

Type: array

Scorer functions are executed concurrently and then merged together after.

Must contain a minimum of 1 items

No Additional Items

Each item of this array must be:


Basic Answer Scorer

Type: object

Score an answer based on standard token level P/R/F metrics.

Institution Priority Order

Type: array

The list of institution affinities.

No Additional Items

Each item of this array must be:

InstitutionAffinity

Type: object

Affinities

Type: array of string

The list of institutions starting from most to least affiniated. This field is case insensitive.

Must contain a minimum of 1 items

No Additional Items

Each item of this array must be:

Type

Type: const Default: "directory-answer-scorer"
Specific value: "directory-answer-scorer"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Type

Type: const Default: "answer"
Specific value: "answer"

Intent Phrase Finder

Type: object

Configure how we retrieve, score, and rank intent phrases.

Reranker

Type: object

Configure how we rerank phrases.

Reranker Functions

Type: array

Rerankers are executed one after the other.

No Additional Items

Each item of this array must be:


Min Cutoff Reranker

Type: object

Minimum cutoff reranker function. All resulting candidates will have scores greater or equal to the cutoff.

Conditions

Type: array Default: []

Conditions for documents before we apply the reranker Documents that fail the condition will be passed through to the next reranker.

No Additional Items

Each item of this array must be:

Condition

Type: object

A condition to check before applying a reranker.

Operator

Type: enum (of string)

The comparison operator.

Must be one of:

  • "gt"
  • "gte"
  • "lt"
  • "lte"
  • "eq"
  • "ne"
  • ">"
  • "≥"
  • ">="
  • "<"
  • "≤"
  • "<="
  • "="
  • "=="
  • "!="
  • "<>"
  • "≠"

Score Key

Type: string

The key in the score vector to use for the comparison. When the key doesn't exist or is None, we return false.

Must be at least 1 characters long

Keep Original If All Discarded

Type: boolean Default: false

If all documents are discarded, keep the original candidates.

Score Key

Type: string

The key in the score vector to use for the cutoff.

Must be at least 1 characters long

Type

Type: const Default: "min-cutoff-reranker"
Specific value: "min-cutoff-reranker"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Max Cutoff Reranker

Type: object

Maximum cutoff reranker function. All resulting candidates will have scores lesser or equal to the cutoff.

Conditions

Type: array Default: []

Conditions for documents before we apply the reranker Documents that fail the condition will be passed through to the next reranker.

No Additional Items

Each item of this array must be:

Keep Original If All Discarded

Type: boolean Default: false

If all documents are discarded, keep the original candidates.

Score Key

Type: string

The key in the score vector to use for the cutoff.

Must be at least 1 characters long

Type

Type: const Default: "max-cutoff-reranker"
Specific value: "max-cutoff-reranker"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Top K Reranker

Type: object

Reranker keeps the top K candidates based on distinct score value and discards the rest.

K

Type: integer Default: 1

Keep the top K candidates.

Value must be strictly greater than 0

Keep Ties

Type: boolean Default: true

Whether to keep candidates whose score tie for top K. Defaults to true.

Score Key

Type: string

The key in the score vector to use for the cutoff.

Must be at least 1 characters long

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Load Full Document Reranker

Type: object

A pseudo-reranker that calls the load method on all candidate documents.

Type

Type: const Default: "load-full-document-reranker"
Specific value: "load-full-document-reranker"

Order By Reranker

Type: object

Reorder the candidates based on scoring keys.

Order By

Type: array of string

The scoring fields to order the candidates by. Prefix with a +/- for ascending/descending order. You can also access sv, doc, and source fields using JMESPath syntax, e.g., sv.missed_tokens_count, doc.name, source.phone, etc.

Must contain a minimum of 1 items

No Additional Items

Each item of this array must be:

Type

Type: const Default: "order-by-reranker"
Specific value: "order-by-reranker"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

First N Reranker

Type: object

Reranker keeps the first N candidates and discards the rest.

N

Type: integer Default: 16

Keep the first N candidates.

Value must be strictly greater than 0

Type

Type: const Default: "first-n-reranker"
Specific value: "first-n-reranker"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Last N Reranker

Type: object

Reranker keeps the last N candidates and discards the rest.

N

Type: integer Default: 16

Keep the last N candidates.

Value must be strictly greater than 0

Type

Type: const Default: "last-n-reranker"
Specific value: "last-n-reranker"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Answer Field Reranker

Type: object

Reranker that keeps entries containing matching answer fields.

Keep Original If All Discarded

Type: boolean Default: false

If all documents are discarded, keep the original candidates.

Match Type

Type: enum (of string) Default: "all"

Whether to match all or any of the answer fields.

Must be one of:

  • "all"
  • "any"

Type

Type: const Default: "answer-field-reranker"
Specific value: "answer-field-reranker"

Discard Or Keep Information Reranker

Type: object

Reranker that shortlists or discards entry based on the condition.

Discard Or Keep

Type: enum (of string)

The field that decides whether to discard or keep the entries.

Must be one of:

  • "discard"
  • "keep"

Type

Type: const Default: "discard-or-keep-information-reranker"
Specific value: "discard-or-keep-information-reranker"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Retriever Settings

Type: object

Configure how we retrieve documents.

Same definition as retriever

Scorer

Type: object

Configure how we score phrases.

Scorer Functions

Type: array

Scorer functions are executed concurrently and then merged together after.

Must contain a minimum of 1 items

No Additional Items

Each item of this array must be:


Basic Answer Scorer

Type: object

Score an answer based on standard token level P/R/F metrics.

Institution Priority Order

Type: array

The list of institution affinities.

No Additional Items

Each item of this array must be:

InstitutionAffinity

Type: object

Affinities

Type: array of string

The list of institutions starting from most to least affiniated. This field is case insensitive.

Must contain a minimum of 1 items

No Additional Items

Each item of this array must be:

Type

Type: const Default: "directory-answer-scorer"
Specific value: "directory-answer-scorer"

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Verbose

Type: boolean Default: false

Whether to log verbose debugging information.

Type

Type: const Default: "intent"
Specific value: "intent"

Intents

Type: array of string

The intents will likely trigger this module.

No Additional Items

Each item of this array must be:

Intent

Type: string

The intent phrase.

Must be at least 1 characters long

Module Responder


The responder to use for this module. Module responders evaluate all the candidate answers to form a cohesive response for a module.

Directory Module Responder Settings

Type: object

Settings for our directory module responder.

Max Answer Candidates To Load

Default: null

The maximum number of answer candidate bare answers that we will load in order to sort and display to the user. Default to None which means to load all answer candidates.

Type

Type: const Default: "directory-ir"
Specific value: "directory-ir"

Clinical Trial Module Responder Settings

Type: object

Settings for our clinical trial module responder.

Max Answer Candidates To Load

Default: null

The maximum number of answer candidate bare answers that we will load in order to sort and display to the user. Default to None which means to load all answer candidates.

Type

Type: const Default: "clinical-trial-ir"
Specific value: "clinical-trial-ir"

Module Stopwords

Type: array

Stopwords used in this module.

No Additional Items

Each item of this array must be:

Stopword Settings

Type: object

Configure stopwords on a per answer type/field level.

Answer Field

Type: string

The field in the answer where the object is used.

Answer Type

Type: enum (of string)

The answer type where the object is used.

Must be one of:

  • "clinical-trial"
  • "dialogue"
  • "directory"
  • "document"
  • "document-snippet"
  • "monograph"
  • "roster"
  • "test"

Stopwords


The stopwords for this answer type/field. It can be a list of phrases or a stopword set name.

Module Synonyms

Type: array

Synonyms used in this module.

No Additional Items

Each item of this array must be:

Synonym Settings

Type: object

Configure synonyms on a per answer type/field level.

Answer Field

Type: string

The field in the answer where the object is used.

Answer Type

Type: enum (of string)

The answer type where the object is used.

Must be one of:

  • "clinical-trial"
  • "dialogue"
  • "directory"
  • "document"
  • "document-snippet"
  • "monograph"
  • "roster"
  • "test"

Synonym Expansion Rounds

Type: integer Default: 3

The number of rounds to expand the synonyms. Each round will generate more candidate synonyms.

Value must be greater or equal to 0

Synonyms

Type: array

The synonyms for this answer type/field as a list of synonym groups.

Must contain a minimum of 1 items

No Additional Items

Each item of this array must be:

Synonym Group


Describes how synonyms are generated

One Way Synonym Group

Type: object

In a one-way synonym group, all phrases are synonyms of the first phrase but not the other way round.

Each additional property must conform to the following schema

Type: array of string

Synonyms of the first phrase.

Must contain a minimum of 1 items

No Additional Items

Each item of this array must be:

Two Way Synonym Group

Type: array of string

In a two-way synonym group, all pairs of phrases are synonyms of each other and can be used interchangeably.

Must contain a minimum of 2 items

No Additional Items

Each item of this array must be:

Synonym

Type: string

A Single synonym phrase.

Must be at least 1 characters long

Name

Type: string

The name of the module. This should be unique within the query engine.

Type

Type: const Default: "standard-ir"
Specific value: "standard-ir"

LLM Document Module Settings

Type: object

Settings for our document LLM module.

Allow early termination

Type: boolean Default: false

Defines whether to allow early termination (before LLM call). True when stock phrase functionality is requested. Default is False.

Model to use

Type: string Default: "cohere.embed-multilingual-v3"

Name of model to be used, it should correspond with one of the values in embedding_model.

Embedding

Type: array

Defines settings for the embedding model during data and query flow.

No Additional Items

Each item of this array must be:

Embedding Model Settings

Type: object

Defines settings for the embedding model during data and query flow.

Context window size of the embedding model

Type: integer Default: 512

Context size

Prompt Name

Type: enum (of string) Default: "query"

Prompt for the embedding.

Must be one of:

  • "query"
  • "text"

Dimension

Type: integer Default: 1024

Dimension of the embedding

Model Source

Type: enum (of string) Default: "bedrock"

Where is the model from?

Must be one of:

  • "huggingface"
  • "bedrock"

HNSW settings

Default: null

HNSW settings

HNSW Graph Settings

Type: object

Defines settings for HNSW graph. See
https://github.com/run-llama/llamaindex/blob/977d60a058c691957dae3eb3c66c1894faea24ac/llama-index-integrations/vectorstores/llama-index-vector-stores-postgres/llamaindex/vectorstores/postgres/base.py#L570

dist_method

Type: enum (of string) Default: "vector_cosine_ops"

Distance metric to use. Note that by default PGVectorStore.buildquery calls cosine_distance

Must be one of:

  • "vector_l2_ops"
  • "vector_ip_ops"
  • "vector_cosine_ops"
  • "vector_l1_ops"
  • "bit_hamming_ops"
  • "bit_jaccard_ops"

ef_construction

Type: integer Default: 64

Size of the dynamic candidate list for constructing the graph. Higher value provides better recall at the cost of speed

Model

Type: string Default: "cohere.embed-multilingual-v3"

Name of embedding model to use.

Must be at least 1 characters long

Query Instruction

Type: string Default: "Represent this sentence for searching relevant passages:"

Instruction for the query.

LLM Settings

Type: object

Defines settings for the LLM model during query flow.

Context Template

Type: string Default: "You are a friendly and warm question-answer hospital assistant, employed as an employee of the hospital.\n The only information you know is the context provided. You can use only that information as your hidden knowledge base.\n When you answer, the context provided will be known as \"my training.\"\n If the context provided provides links, show it to the user."

Template for the context

Guardrail Identifier

Type: string Default: "arn:aws:bedrock:us-west-2:394252546268:guardrail/f83z6kx1d6hl"

Name of AWS guardrail if applicable. Should start with arn:aws:bedrock:us-west-2:.

Guardrail Version

Type: string Default: "1"

AWS Guardrail version (string) if applicable

Max Tokens

Type: integer Default: 1000

Max tokens returned by LLM

Model

Type: string

Name of LLM as per HuggingFace

Must be at least 1 characters long

Reranker Similarity Cutoff

Type: number Default: 0

Similarity score cutoff for node postprocessing based on reranker score

Similarity Cutoff

Type: number Default: 0.38

Similarity score cutoff for node postprocessing based on embedding score

Similarity top K

Type: integer Default: 6

Number of nodes to return after retrieval

Supported language codes

Type: array of string

Restricts bot to only answer only these languages. Provide list of 2-letter language codes, and double-check that Amazon Comprehend / Translate supports them.

No Additional Items

Each item of this array must be:

System Prompt

Type: string Default: "Answer the QUERY below only using the DOCUMENTs below as context, and not your trained knowledge."

Prompt for the LLM

Temperature

Type: number Default: 0

Temperature

Name

Type: string

The name of the module. This should be unique within the query engine.

Postprocessor settings

Type: object

Configure which postprocessor functions to use

Postprocessor Functions

Type: array

Postprocessor functions to be applied one after another in the model.

No Additional Items

Each item of this array must be:


Postprocessor settings

Type: object

Configure which postprocessor functions to use

Preprocessor Functions

Type: array

Preprocessor functions to be applied one after another.

No Additional Items

Each item of this array must be:


Language Filter

Type: object

Language Filter Preprocessor function.

Supported language codes

Type: array of string

The language codes that are supported for this client. By default, if this is empty, all languages are supported. If a language is not supported, query will be nullified

No Additional Items

Each item of this array must be:

Query Feature settings

Type: object

Configure which query feature functions to use

Query Feature Functions

Type: array

Query Feature functions to be applied one after another.

No Additional Items

Each item of this array must be:

Storage Prefix

Type: const Default: "document-llm"
Specific value: "document-llm"

Type

Type: const Default: "document-llm"
Specific value: "document-llm"

Cleo Dialogue LLM Module Settings

Type: object

Settings for our Cleo dialogue LLM module.

Allow early termination

Type: boolean Default: false

Defines whether to allow early termination (before LLM call). True when stock phrase functionality is requested. Default is False.

Model to use

Type: string Default: "cohere.embed-multilingual-v3"

Name of model to be used, it should correspond with one of the values in embedding_model.

Embedding

Type: array

Defines settings for the embedding model during data and query flow.

No Additional Items

Each item of this array must be:

Embedding Model Settings

Type: object

Defines settings for the embedding model during data and query flow.

Same definition as Embedding Model Settings

LLM Settings

Type: object

Defines settings for the LLM model during query flow.

Context Template

Type: string Default: "You are a friendly and warm question-answer hospital assistant, employed as an employee of the hospital.\n The only information you know is the context provided. You can use only that information as your hidden knowledge base.\n When you answer, the context provided will be known as \"my training.\"\n If the context provided provides links, show it to the user."

Template for the context

Guardrail Identifier

Type: string Default: "arn:aws:bedrock:us-west-2:394252546268:guardrail/f83z6kx1d6hl"

Name of AWS guardrail if applicable. Should start with arn:aws:bedrock:us-west-2:.

Guardrail Version

Type: string Default: "1"

AWS Guardrail version (string) if applicable

Max Tokens

Type: integer Default: 1000

Max tokens returned by LLM

Model

Type: string

Name of LLM as per HuggingFace

Must be at least 1 characters long

Reranker Similarity Cutoff

Type: number Default: 0

Similarity score cutoff for node postprocessing based on reranker score

Similarity Cutoff

Type: number Default: 0.38

Similarity score cutoff for node postprocessing based on embedding score

Similarity top K

Type: integer Default: 6

Number of nodes to return after retrieval

Supported language codes

Type: array of string

Restricts bot to only answer only these languages. Provide list of 2-letter language codes, and double-check that Amazon Comprehend / Translate supports them.

No Additional Items

Each item of this array must be:

System Prompt

Type: string Default: "Answer the QUERY below only using the DOCUMENTs below as context, and not your trained knowledge."

Prompt for the LLM

Temperature

Type: number Default: 0

Temperature

Metadata Filter keys

Type: array of string

Configure valid keys that will be used to filter metadata. They should by default be at least any of the types of QueryFeatureSettings.

No Additional Items

Each item of this array must be:

Name

Type: string

The name of the module. This should be unique within the query engine.

Postprocessor settings

Type: object

Configure which postprocessor functions to use

Postprocessor Functions

Type: array

Postprocessor functions to be applied one after another in the model.

No Additional Items

Each item of this array must be:


Postprocessor settings

Type: object

Configure which postprocessor functions to use

Preprocessor Functions

Type: array

Preprocessor functions to be applied one after another.

No Additional Items

Each item of this array must be:


Language Filter

Type: object

Language Filter Preprocessor function.

Supported language codes

Type: array of string

The language codes that are supported for this client. By default, if this is empty, all languages are supported. If a language is not supported, query will be nullified

No Additional Items

Each item of this array must be:

Scorer Settings

Type: object

Configure how we generate query features.

Same definition as query_feature_settings

Storage Prefix

Type: const Default: "cleo-dialogue-llm"
Specific value: "cleo-dialogue-llm"

Type

Type: const Default: "dialogue-llm"
Specific value: "dialogue-llm"

Agentic Module Settings

Type: object

Defines settings for Agentic modules

# schema: jarvisv2/QueryEngineSettings.schema

name: agentic-module-query-engine
tenants: [all]
modules:
- type: agentic-module
name: agentic-module-v0
storage_prefix: agentic-module-v0-
#end agentic-module-v0

end modules

Allow early termination

Type: boolean Default: false

Defines whether to allow early termination (before LLM call). True when stock phrase functionality is requested. Default is False.

Model to use

Type: string Default: "cohere.embed-multilingual-v3"

Name of model to be used, it should correspond with one of the values in embedding_model.

Embedding

Type: array

Defines settings for the embedding model during data and query flow.

No Additional Items

Each item of this array must be:

Embedding Model Settings

Type: object

Defines settings for the embedding model during data and query flow.

Same definition as Embedding Model Settings

LLM Settings

Type: object

Defines settings for the LLM model during query flow.

Context Template

Type: string Default: "You are a friendly and warm question-answer hospital assistant, employed as an employee of the hospital.\n The only information you know is the context provided. You can use only that information as your hidden knowledge base.\n When you answer, the context provided will be known as \"my training.\"\n If the context provided provides links, show it to the user."

Template for the context

Guardrail Identifier

Type: string Default: "arn:aws:bedrock:us-west-2:394252546268:guardrail/f83z6kx1d6hl"

Name of AWS guardrail if applicable. Should start with arn:aws:bedrock:us-west-2:.

Guardrail Version

Type: string Default: "1"

AWS Guardrail version (string) if applicable

Max Tokens

Type: integer Default: 1000

Max tokens returned by LLM

Model

Type: string

Name of LLM as per HuggingFace

Must be at least 1 characters long

Reranker Similarity Cutoff

Type: number Default: 0

Similarity score cutoff for node postprocessing based on reranker score

Similarity Cutoff

Type: number Default: 0.38

Similarity score cutoff for node postprocessing based on embedding score

Similarity top K

Type: integer Default: 6

Number of nodes to return after retrieval

Supported language codes

Type: array of string

Restricts bot to only answer only these languages. Provide list of 2-letter language codes, and double-check that Amazon Comprehend / Translate supports them.

No Additional Items

Each item of this array must be:

System Prompt

Type: string Default: "Answer the QUERY below only using the DOCUMENTs below as context, and not your trained knowledge."

Prompt for the LLM

Temperature

Type: number Default: 0

Temperature

Metadata Filter keys

Type: array of string

Configure valid keys that will be used to filter metadata. They should by default be at least any of the types of QueryFeatureSettings.

No Additional Items

Each item of this array must be:

Name

Type: string

The name of the module. This should be unique within the query engine.

Postprocessor settings

Type: object

Configure which postprocessor functions to use

Postprocessor Functions

Type: array

Postprocessor functions to be applied one after another in the model.

No Additional Items

Each item of this array must be:


Postprocessor settings

Type: object

Configure which postprocessor functions to use

Preprocessor Functions

Type: array

Preprocessor functions to be applied one after another.

No Additional Items

Each item of this array must be:


Language Filter

Type: object

Language Filter Preprocessor function.

Supported language codes

Type: array of string

The language codes that are supported for this client. By default, if this is empty, all languages are supported. If a language is not supported, query will be nullified

No Additional Items

Each item of this array must be:

Scorer Settings

Type: object

Configure how we generate query features.

Same definition as query_feature_settings

Storage Prefix

Type: const Default: "agentic-module-v0-"
Specific value: "agentic-module-v0-"

Type

Type: const Default: "agentic-module"
Specific value: "agentic-module"

Noop Module Settings

Type: object

Noop module settings.

Name

Type: string Default: "noop"

The name of the module. This should be unique within the query engine.

Type

Type: const Default: "noop"
Specific value: "noop"

Name

Type: string

The name of the query engine. This should be globally unique.

Version

Type: string Default: "unknown"

Version of this query engine based on the Kondo resource version.