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rag_tool

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Sai Soundararaj 2025-07-01 16:01:37 -07:00
parent c263eca62d
commit 3634bf05b4
4 changed files with 109 additions and 29 deletions
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56
docs/_static/llama-stack-spec.html vendored
View file

@ -1973,7 +1973,7 @@
"tags": [
"ToolRuntime"
],
"description": "Index documents so they can be used by the RAG system",
"description": "Index documents so they can be used by the RAG system.",
"parameters": [],
"requestBody": {
"content": {
@ -4345,7 +4345,7 @@
"post": {
"responses": {
"200": {
"description": "OK",
"description": "RAGQueryResult containing the retrieved content and metadata",
"content": {
"application/json": {
"schema": {
@ -4370,7 +4370,7 @@
"tags": [
"ToolRuntime"
],
"description": "Query the RAG system for context; typically invoked by the agent",
"description": "Query the RAG system for context; typically invoked by the agent.",
"parameters": [],
"requestBody": {
"content": {
@ -11493,13 +11493,16 @@
"type": "array",
"items": {
"$ref": "#/components/schemas/RAGDocument"
}
},
"description": "List of documents to index in the RAG system"
},
"vector_db_id": {
"type": "string"
"type": "string",
"description": "ID of the vector database to store the document embeddings"
},
"chunk_size_in_tokens": {
"type": "integer"
"type": "integer",
"description": "(Optional) Size in tokens for document chunking during indexing"
}
},
"additionalProperties": false,
@ -14813,11 +14816,13 @@
"type": {
"type": "string",
"const": "default",
"default": "default"
"default": "default",
"description": "Type of query generator, always 'default'"
},
"separator": {
"type": "string",
"default": " "
"default": " ",
"description": "String separator used to join query terms"
}
},
"additionalProperties": false,
@ -14825,7 +14830,8 @@
"type",
"separator"
],
"title": "DefaultRAGQueryGeneratorConfig"
"title": "DefaultRAGQueryGeneratorConfig",
"description": "Configuration for the default RAG query generator."
},
"LLMRAGQueryGeneratorConfig": {
"type": "object",
@ -14833,13 +14839,16 @@
"type": {
"type": "string",
"const": "llm",
"default": "llm"
"default": "llm",
"description": "Type of query generator, always 'llm'"
},
"model": {
"type": "string"
"type": "string",
"description": "Name of the language model to use for query generation"
},
"template": {
"type": "string"
"type": "string",
"description": "Template string for formatting the query generation prompt"
}
},
"additionalProperties": false,
@ -14848,7 +14857,8 @@
"model",
"template"
],
"title": "LLMRAGQueryGeneratorConfig"
"title": "LLMRAGQueryGeneratorConfig",
"description": "Configuration for the LLM-based RAG query generator."
},
"RAGQueryConfig": {
"type": "object",
@ -14920,7 +14930,7 @@
"impact_factor": {
"type": "number",
"default": 60.0,
"description": "The impact factor for RRF scoring. Higher values give more weight to higher-ranked results. Must be greater than 0. Default of 60 is from the original RRF paper (Cormack et al., 2009)."
"description": "The impact factor for RRF scoring. Higher values give more weight to higher-ranked results. Must be greater than 0"
}
},
"additionalProperties": false,
@ -14975,16 +14985,19 @@
"type": "object",
"properties": {
"content": {
"$ref": "#/components/schemas/InterleavedContent"
"$ref": "#/components/schemas/InterleavedContent",
"description": "The query content to search for in the indexed documents"
},
"vector_db_ids": {
"type": "array",
"items": {
"type": "string"
}
},
"description": "List of vector database IDs to search within"
},
"query_config": {
"$ref": "#/components/schemas/RAGQueryConfig"
"$ref": "#/components/schemas/RAGQueryConfig",
"description": "(Optional) Configuration parameters for the query operation"
}
},
"additionalProperties": false,
@ -14998,7 +15011,8 @@
"type": "object",
"properties": {
"content": {
"$ref": "#/components/schemas/InterleavedContent"
"$ref": "#/components/schemas/InterleavedContent",
"description": "(Optional) The retrieved content from the query"
},
"metadata": {
"type": "object",
@ -15023,14 +15037,16 @@
"type": "object"
}
]
}
},
"description": "Additional metadata about the query result"
}
},
"additionalProperties": false,
"required": [
"metadata"
],
"title": "RAGQueryResult"
"title": "RAGQueryResult",
"description": "Result of a RAG query containing retrieved content and metadata."
},
"QueryChunksRequest": {
"type": "object",

41
docs/_static/llama-stack-spec.yaml vendored
View file

@ -1360,7 +1360,7 @@ paths:
tags:
- ToolRuntime
description: >-
Index documents so they can be used by the RAG system
Index documents so they can be used by the RAG system.
parameters: []
requestBody:
content:
@ -3071,7 +3071,8 @@ paths:
post:
responses:
'200':
description: OK
description: >-
RAGQueryResult containing the retrieved content and metadata
content:
application/json:
schema:
@ -3089,7 +3090,7 @@ paths:
tags:
- ToolRuntime
description: >-
Query the RAG system for context; typically invoked by the agent
Query the RAG system for context; typically invoked by the agent.
parameters: []
requestBody:
content:
@ -8202,10 +8203,16 @@ components:
type: array
items:
$ref: '#/components/schemas/RAGDocument'
description: >-
List of documents to index in the RAG system
vector_db_id:
type: string
description: >-
ID of the vector database to store the document embeddings
chunk_size_in_tokens:
type: integer
description: >-
(Optional) Size in tokens for document chunking during indexing
additionalProperties: false
required:
- documents
@ -10493,14 +10500,20 @@ components:
type: string
const: default
default: default
description: >-
Type of query generator, always 'default'
separator:
type: string
default: ' '
description: >-
String separator used to join query terms
additionalProperties: false
required:
- type
- separator
title: DefaultRAGQueryGeneratorConfig
description: >-
Configuration for the default RAG query generator.
LLMRAGQueryGeneratorConfig:
type: object
properties:
@ -10508,16 +10521,23 @@ components:
type: string
const: llm
default: llm
description: Type of query generator, always 'llm'
model:
type: string
description: >-
Name of the language model to use for query generation
template:
type: string
description: >-
Template string for formatting the query generation prompt
additionalProperties: false
required:
- type
- model
- template
title: LLMRAGQueryGeneratorConfig
description: >-
Configuration for the LLM-based RAG query generator.
RAGQueryConfig:
type: object
properties:
@ -10586,8 +10606,7 @@ components:
default: 60.0
description: >-
The impact factor for RRF scoring. Higher values give more weight to higher-ranked
results. Must be greater than 0. Default of 60 is from the original RRF
paper (Cormack et al., 2009).
results. Must be greater than 0
additionalProperties: false
required:
- type
@ -10630,12 +10649,18 @@ components:
properties:
content:
$ref: '#/components/schemas/InterleavedContent'
description: >-
The query content to search for in the indexed documents
vector_db_ids:
type: array
items:
type: string
description: >-
List of vector database IDs to search within
query_config:
$ref: '#/components/schemas/RAGQueryConfig'
description: >-
(Optional) Configuration parameters for the query operation
additionalProperties: false
required:
- content
@ -10646,6 +10671,8 @@ components:
properties:
content:
$ref: '#/components/schemas/InterleavedContent'
description: >-
(Optional) The retrieved content from the query
metadata:
type: object
additionalProperties:
@ -10656,10 +10683,14 @@ components:
- type: string
- type: array
- type: object
description: >-
Additional metadata about the query result
additionalProperties: false
required:
- metadata
title: RAGQueryResult
description: >-
Result of a RAG query containing retrieved content and metadata.
QueryChunksRequest:
type: object
properties: