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chore!: BREAKING CHANGE: vector_db_id -> vector_store_id (#3923)

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# What does this PR do?


## Test Plan
CI
vector_io tests will fail until next client sync

passed with
https://github.com/llamastack/llama-stack-client-python/pull/286 checked
out locally
This commit is contained in:
ehhuang 2025-10-27 14:26:06 -07:00 • committed by GitHub
parent b6954c9882
commit b7dd3f5c56
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29 changed files with 175 additions and 175 deletions
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20
docs/docs/providers/vector_io/inline_sqlite-vec.mdx
View file

@ -72,14 +72,14 @@ description: |
Example with hybrid search:
```python
response = await vector_io.query_chunks(
vector_db_id="my_db",
vector_store_id="my_db",
query="your query here",
params={"mode": "hybrid", "max_chunks": 3, "score_threshold": 0.7},
)
# Using RRF ranker
response = await vector_io.query_chunks(
vector_db_id="my_db",
vector_store_id="my_db",
query="your query here",
params={
"mode": "hybrid",
@ -91,7 +91,7 @@ description: |
# Using weighted ranker
response = await vector_io.query_chunks(
vector_db_id="my_db",
vector_store_id="my_db",
query="your query here",
params={
"mode": "hybrid",
@ -105,7 +105,7 @@ description: |
Example with explicit vector search:
```python
response = await vector_io.query_chunks(
vector_db_id="my_db",
vector_store_id="my_db",
query="your query here",
params={"mode": "vector", "max_chunks": 3, "score_threshold": 0.7},
)
@ -114,7 +114,7 @@ description: |
Example with keyword search:
```python
response = await vector_io.query_chunks(
vector_db_id="my_db",
vector_store_id="my_db",
query="your query here",
params={"mode": "keyword", "max_chunks": 3, "score_threshold": 0.7},
)
@ -277,14 +277,14 @@ The SQLite-vec provider supports three search modes:
Example with hybrid search:
```python
response = await vector_io.query_chunks(
vector_db_id="my_db",
vector_store_id="my_db",
query="your query here",
params={"mode": "hybrid", "max_chunks": 3, "score_threshold": 0.7},
)
# Using RRF ranker
response = await vector_io.query_chunks(
vector_db_id="my_db",
vector_store_id="my_db",
query="your query here",
params={
"mode": "hybrid",
@ -296,7 +296,7 @@ response = await vector_io.query_chunks(
# Using weighted ranker
response = await vector_io.query_chunks(
vector_db_id="my_db",
vector_store_id="my_db",
query="your query here",
params={
"mode": "hybrid",
@ -310,7 +310,7 @@ response = await vector_io.query_chunks(
Example with explicit vector search:
```python
response = await vector_io.query_chunks(
vector_db_id="my_db",
vector_store_id="my_db",
query="your query here",
params={"mode": "vector", "max_chunks": 3, "score_threshold": 0.7},
)
@ -319,7 +319,7 @@ response = await vector_io.query_chunks(
Example with keyword search:
```python
response = await vector_io.query_chunks(
vector_db_id="my_db",
vector_store_id="my_db",
query="your query here",
params={"mode": "keyword", "max_chunks": 3, "score_threshold": 0.7},
)

4
docs/static/deprecated-llama-stack-spec.html vendored
View file

@ -4390,7 +4390,7 @@
"const": "memory_retrieval",
"default": "memory_retrieval"
},
"vector_db_ids": {
"vector_store_ids": {
"type": "string",
"description": "The IDs of the vector databases to retrieve context from."
},
@ -4404,7 +4404,7 @@
"turn_id",
"step_id",
"step_type",
"vector_db_ids",
"vector_store_ids",
"inserted_context"
],
"title": "MemoryRetrievalStep",

4
docs/static/deprecated-llama-stack-spec.yaml vendored
View file

@ -3252,7 +3252,7 @@ components:
description: Type of the step in an agent turn.
const: memory_retrieval
default: memory_retrieval
vector_db_ids:
vector_store_ids:
type: string
description: >-
The IDs of the vector databases to retrieve context from.
@ -3265,7 +3265,7 @@ components:
- turn_id
- step_id
- step_type
- vector_db_ids
- vector_store_ids
- inserted_context
title: MemoryRetrievalStep
description: >-

4
docs/static/experimental-llama-stack-spec.html vendored
View file

@ -2865,7 +2865,7 @@
"const": "memory_retrieval",
"default": "memory_retrieval"
},
"vector_db_ids": {
"vector_store_ids": {
"type": "string",
"description": "The IDs of the vector databases to retrieve context from."
},
@ -2879,7 +2879,7 @@
"turn_id",
"step_id",
"step_type",
"vector_db_ids",
"vector_store_ids",
"inserted_context"
],
"title": "MemoryRetrievalStep",

4
docs/static/experimental-llama-stack-spec.yaml vendored
View file

@ -2085,7 +2085,7 @@ components:
description: Type of the step in an agent turn.
const: memory_retrieval
default: memory_retrieval
vector_db_ids:
vector_store_ids:
type: string
description: >-
The IDs of the vector databases to retrieve context from.
@ -2098,7 +2098,7 @@ components:
- turn_id
- step_id
- step_type
- vector_db_ids
- vector_store_ids
- inserted_context
title: MemoryRetrievalStep
description: >-

16
docs/static/llama-stack-spec.html vendored
View file

@ -11412,7 +11412,7 @@
},
"description": "List of documents to index in the RAG system"
},
"vector_db_id": {
"vector_store_id": {
"type": "string",
"description": "ID of the vector database to store the document embeddings"
},
@ -11424,7 +11424,7 @@
"additionalProperties": false,
"required": [
"documents",
"vector_db_id",
"vector_store_id",
"chunk_size_in_tokens"
],
"title": "InsertRequest"
@ -11615,7 +11615,7 @@
"$ref": "#/components/schemas/InterleavedContent",
"description": "The query content to search for in the indexed documents"
},
"vector_db_ids": {
"vector_store_ids": {
"type": "array",
"items": {
"type": "string"
@ -11630,7 +11630,7 @@
"additionalProperties": false,
"required": [
"content",
"vector_db_ids"
"vector_store_ids"
],
"title": "QueryRequest"
},
@ -11923,7 +11923,7 @@
"InsertChunksRequest": {
"type": "object",
"properties": {
"vector_db_id": {
"vector_store_id": {
"type": "string",
"description": "The identifier of the vector database to insert the chunks into."
},
@ -11941,7 +11941,7 @@
},
"additionalProperties": false,
"required": [
"vector_db_id",
"vector_store_id",
"chunks"
],
"title": "InsertChunksRequest"
@ -11949,7 +11949,7 @@
"QueryChunksRequest": {
"type": "object",
"properties": {
"vector_db_id": {
"vector_store_id": {
"type": "string",
"description": "The identifier of the vector database to query."
},
@ -11986,7 +11986,7 @@
},
"additionalProperties": false,
"required": [
"vector_db_id",
"vector_store_id",
"query"
],
"title": "QueryChunksRequest"

16
docs/static/llama-stack-spec.yaml vendored
View file

@ -8649,7 +8649,7 @@ components:
$ref: '#/components/schemas/RAGDocument'
description: >-
List of documents to index in the RAG system
vector_db_id:
vector_store_id:
type: string
description: >-
ID of the vector database to store the document embeddings
@ -8660,7 +8660,7 @@ components:
additionalProperties: false
required:
- documents
- vector_db_id
- vector_store_id
- chunk_size_in_tokens
title: InsertRequest
DefaultRAGQueryGeneratorConfig:
@ -8831,7 +8831,7 @@ components:
$ref: '#/components/schemas/InterleavedContent'
description: >-
The query content to search for in the indexed documents
vector_db_ids:
vector_store_ids:
type: array
items:
type: string
@ -8844,7 +8844,7 @@ components:
additionalProperties: false
required:
- content
- vector_db_ids
- vector_store_ids
title: QueryRequest
RAGQueryResult:
type: object
@ -9068,7 +9068,7 @@ components:
InsertChunksRequest:
type: object
properties:
vector_db_id:
vector_store_id:
type: string
description: >-
The identifier of the vector database to insert the chunks into.
@ -9087,13 +9087,13 @@ components:
description: The time to live of the chunks.
additionalProperties: false
required:
- vector_db_id
- vector_store_id
- chunks
title: InsertChunksRequest
QueryChunksRequest:
type: object
properties:
vector_db_id:
vector_store_id:
type: string
description: >-
The identifier of the vector database to query.
@ -9113,7 +9113,7 @@ components:
description: The parameters of the query.
additionalProperties: false
required:
- vector_db_id
- vector_store_id
- query
title: QueryChunksRequest
QueryChunksResponse:

20
docs/static/stainless-llama-stack-spec.html vendored
View file

@ -13084,7 +13084,7 @@
},
"description": "List of documents to index in the RAG system"
},
"vector_db_id": {
"vector_store_id": {
"type": "string",
"description": "ID of the vector database to store the document embeddings"
},
@ -13096,7 +13096,7 @@
"additionalProperties": false,
"required": [
"documents",
"vector_db_id",
"vector_store_id",
"chunk_size_in_tokens"
],
"title": "InsertRequest"
@ -13287,7 +13287,7 @@
"$ref": "#/components/schemas/InterleavedContent",
"description": "The query content to search for in the indexed documents"
},
"vector_db_ids": {
"vector_store_ids": {
"type": "array",
"items": {
"type": "string"
@ -13302,7 +13302,7 @@
"additionalProperties": false,
"required": [
"content",
"vector_db_ids"
"vector_store_ids"
],
"title": "QueryRequest"
},
@ -13595,7 +13595,7 @@
"InsertChunksRequest": {
"type": "object",
"properties": {
"vector_db_id": {
"vector_store_id": {
"type": "string",
"description": "The identifier of the vector database to insert the chunks into."
},
@ -13613,7 +13613,7 @@
},
"additionalProperties": false,
"required": [
"vector_db_id",
"vector_store_id",
"chunks"
],
"title": "InsertChunksRequest"
@ -13621,7 +13621,7 @@
"QueryChunksRequest": {
"type": "object",
"properties": {
"vector_db_id": {
"vector_store_id": {
"type": "string",
"description": "The identifier of the vector database to query."
},
@ -13658,7 +13658,7 @@
},
"additionalProperties": false,
"required": [
"vector_db_id",
"vector_store_id",
"query"
],
"title": "QueryChunksRequest"
@ -15719,7 +15719,7 @@
"const": "memory_retrieval",
"default": "memory_retrieval"
},
"vector_db_ids": {
"vector_store_ids": {
"type": "string",
"description": "The IDs of the vector databases to retrieve context from."
},
@ -15733,7 +15733,7 @@
"turn_id",
"step_id",
"step_type",
"vector_db_ids",
"vector_store_ids",
"inserted_context"
],
"title": "MemoryRetrievalStep",

20
docs/static/stainless-llama-stack-spec.yaml vendored
View file

@ -9862,7 +9862,7 @@ components:
$ref: '#/components/schemas/RAGDocument'
description: >-
List of documents to index in the RAG system
vector_db_id:
vector_store_id:
type: string
description: >-
ID of the vector database to store the document embeddings
@ -9873,7 +9873,7 @@ components:
additionalProperties: false
required:
- documents
- vector_db_id
- vector_store_id
- chunk_size_in_tokens
title: InsertRequest
DefaultRAGQueryGeneratorConfig:
@ -10044,7 +10044,7 @@ components:
$ref: '#/components/schemas/InterleavedContent'
description: >-
The query content to search for in the indexed documents
vector_db_ids:
vector_store_ids:
type: array
items:
type: string
@ -10057,7 +10057,7 @@ components:
additionalProperties: false
required:
- content
- vector_db_ids
- vector_store_ids
title: QueryRequest
RAGQueryResult:
type: object
@ -10281,7 +10281,7 @@ components:
InsertChunksRequest:
type: object
properties:
vector_db_id:
vector_store_id:
type: string
description: >-
The identifier of the vector database to insert the chunks into.
@ -10300,13 +10300,13 @@ components:
description: The time to live of the chunks.
additionalProperties: false
required:
- vector_db_id
- vector_store_id
- chunks
title: InsertChunksRequest
QueryChunksRequest:
type: object
properties:
vector_db_id:
vector_store_id:
type: string
description: >-
The identifier of the vector database to query.
@ -10326,7 +10326,7 @@ components:
description: The parameters of the query.
additionalProperties: false
required:
- vector_db_id
- vector_store_id
- query
title: QueryChunksRequest
QueryChunksResponse:
@ -11844,7 +11844,7 @@ components:
description: Type of the step in an agent turn.
const: memory_retrieval
default: memory_retrieval
vector_db_ids:
vector_store_ids:
type: string
description: >-
The IDs of the vector databases to retrieve context from.
@ -11857,7 +11857,7 @@ components:
- turn_id
- step_id
- step_type
- vector_db_ids
- vector_store_ids
- inserted_context
title: MemoryRetrievalStep
description: >-