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Lightspeed Core Stack

📋 Schemas for requests models

AllowedToolsFilter

Filter configuration for restricting which MCP tools can be used.

:param tool_names: (Optional) List of specific tool names that are allowed

Field	Type	Description
tool_names	array

ApprovalFilter

Filter configuration for MCP tool approval requirements.

:param always: (Optional) List of tool names that always require approval :param never: (Optional) List of tool names that never require approval

Field	Type	Description
always	array
never	array

Attachment

Model representing an attachment that can be sent from the UI as part of query.

A list of attachments can be an optional part of ‘query’ request.

Attributes: attachment_type: The attachment type, like “log”, “configuration” etc. content_type: The content type as defined in MIME standard content: The actual attachment content

Field	Type	Description
attachment_type	string	The attachment type, like ‘log’, ‘configuration’ etc.
content_type	string	The content type as defined in MIME standard
content	string	The actual attachment content

ConversationUpdateRequest

Model representing a request to update a conversation topic summary.

Attributes: topic_summary: The new topic summary for the conversation.

Field	Type	Description
topic_summary	string	The new topic summary for the conversation

FeedbackCategory

Enum representing predefined feedback categories for AI responses.

These categories help provide structured feedback about AI inference quality when users provide negative feedback (thumbs down). Multiple categories can be selected to provide comprehensive feedback about response issues.

FeedbackRequest

Model representing a feedback request.

Attributes: conversation_id: The required conversation ID (UUID). user_question: The required user question. llm_response: The required LLM response. sentiment: The optional sentiment. user_feedback: The optional user feedback. categories: The optional list of feedback categories (multi-select for negative feedback).

Field	Type	Description
conversation_id	string	The required conversation ID (UUID)
user_question	string	User question (the query string)
llm_response	string	Response from LLM
sentiment	integer	User sentiment, if provided must be -1 or 1
user_feedback	string	Feedback on the LLM response.
categories	array	List of feedback categories that describe issues with the LLM response (for negative feedback).

FeedbackStatusUpdateRequest

Model representing a feedback status update request.

Attributes: status: Value of the desired feedback enabled state.

Field	Type	Description
status	boolean	Desired state of feedback enablement, must be False or True

IncludeParameter

InputToolMCP

MCP input tool with authorization included when serializing request bodies.

Field	Type	Description
type	string
server_label	string
connector_id	string
server_url	string
headers	object
authorization	string
require_approval
allowed_tools

MCPListToolsTool

Tool definition returned by MCP list tools operation.

:param input_schema: JSON schema defining the tool’s input parameters :param name: Name of the tool :param description: (Optional) Description of what the tool does

Field	Type	Description
input_schema	object
name	string
description	string

MCPServerRegistrationRequest

Request model for dynamically registering an MCP server.

Attributes: name: Unique name for the MCP server. url: URL of the MCP server endpoint. provider_id: MCP provider identification (defaults to “model-context-protocol”). authorization_headers: Optional headers to send to the MCP server. headers: Optional list of HTTP header names to forward from incoming requests. timeout: Optional request timeout in seconds.

Field	Type	Description
name	string	Unique name for the MCP server
url	string	URL of the MCP server endpoint
provider_id	string	MCP provider identification
authorization_headers	object	Headers to send to the MCP server. Values must be one of the supported token resolution keywords: ‘client’ - forward the caller’s token provided via MCP-HEADERS, ‘kubernetes’ - use the authenticated user’s Kubernetes token, ‘oauth’ - use an OAuth token provided via MCP-HEADERS. File-path based secrets (used in static YAML config) are not supported for dynamically registered servers.
headers	array	List of HTTP header names to forward from incoming requests
timeout	integer	Request timeout in seconds for the MCP server

ModelFilter

Model representing a query parameter to select models by its type.

Attributes: model_type: Required model type, such as ‘llm’, ‘embeddings’ etc.

Field	Type	Description
model_type	string	Optional filter to return only models matching this type

OpenAIResponseAnnotationCitation

URL citation annotation for referencing external web resources.

:param type: Annotation type identifier, always “url_citation” :param end_index: End position of the citation span in the content :param start_index: Start position of the citation span in the content :param title: Title of the referenced web resource :param url: URL of the referenced web resource

Field	Type	Description
type	string
end_index	integer
start_index	integer
title	string
url	string

OpenAIResponseAnnotationContainerFileCitation

Field	Type	Description
type	string
container_id	string
end_index	integer
file_id	string
filename	string
start_index	integer

OpenAIResponseAnnotationFileCitation

File citation annotation for referencing specific files in response content.

:param type: Annotation type identifier, always “file_citation” :param file_id: Unique identifier of the referenced file :param filename: Name of the referenced file :param index: Position index of the citation within the content

Field	Type	Description
type	string
file_id	string
filename	string
index	integer

OpenAIResponseAnnotationFilePath

Field	Type	Description
type	string
file_id	string
index	integer

OpenAIResponseContentPartRefusal

Refusal content within a streamed response part.

:param type: Content part type identifier, always “refusal” :param refusal: Refusal text supplied by the model

Field	Type	Description
type	string
refusal	string

OpenAIResponseInputFunctionToolCallOutput

This represents the output of a function call that gets passed back to the model.

Field	Type	Description
call_id	string
output
type	string
id	string
status	string

OpenAIResponseInputMessageContentFile

File content for input messages in OpenAI response format.

:param type: The type of the input item. Always input_file. :param file_data: The data of the file to be sent to the model. :param file_id: (Optional) The ID of the file to be sent to the model. :param file_url: The URL of the file to be sent to the model. :param filename: The name of the file to be sent to the model.

Field	Type	Description
type	string
file_data	string
file_id	string
file_url	string
filename	string

OpenAIResponseInputMessageContentImage

Image content for input messages in OpenAI response format.

:param detail: Level of detail for image processing, can be “low”, “high”, or “auto” :param type: Content type identifier, always “input_image” :param file_id: (Optional) The ID of the file to be sent to the model. :param image_url: (Optional) URL of the image content

Field	Type	Description
detail
type	string
file_id	string
image_url	string

OpenAIResponseInputMessageContentText

Text content for input messages in OpenAI response format.

:param text: The text content of the input message :param type: Content type identifier, always “input_text”

Field	Type	Description
text	string
type	string

OpenAIResponseInputToolChoiceAllowedTools

Constrains the tools available to the model to a pre-defined set.

:param mode: Constrains the tools available to the model to a pre-defined set :param tools: A list of tool definitions that the model should be allowed to call :param type: Tool choice type identifier, always “allowed_tools”

Field	Type	Description
mode	string
tools	array
type	string

OpenAIResponseInputToolChoiceCustomTool

Forces the model to call a custom tool.

:param type: Tool choice type identifier, always “custom” :param name: The name of the custom tool to call.

Field	Type	Description
type	string
name	string

OpenAIResponseInputToolChoiceFileSearch

Indicates that the model should use file search to generate a response.

:param type: Tool choice type identifier, always “file_search”

Field	Type	Description
type	string

OpenAIResponseInputToolChoiceFunctionTool

Forces the model to call a specific function.

:param name: The name of the function to call :param type: Tool choice type identifier, always “function”

Field	Type	Description
name	string
type	string

OpenAIResponseInputToolChoiceMCPTool

Forces the model to call a specific tool on a remote MCP server

:param server_label: The label of the MCP server to use. :param type: Tool choice type identifier, always “mcp” :param name: (Optional) The name of the tool to call on the server.

Field	Type	Description
server_label	string
type	string
name	string

OpenAIResponseInputToolChoiceMode

OpenAIResponseInputToolChoiceWebSearch

Indicates that the model should use web search to generate a response

:param type: Web search tool type variant to use

Field	Type	Description
type

OpenAIResponseInputToolFileSearch

File search tool configuration for OpenAI response inputs.

:param type: Tool type identifier, always “file_search” :param vector_store_ids: List of vector store identifiers to search within :param filters: (Optional) Additional filters to apply to the search :param max_num_results: (Optional) Maximum number of search results to return (1-50) :param ranking_options: (Optional) Options for ranking and scoring search results

Field	Type	Description
type	string
vector_store_ids	array
filters	object
max_num_results	integer
ranking_options

OpenAIResponseInputToolFunction

Function tool configuration for OpenAI response inputs.

:param type: Tool type identifier, always “function” :param name: Name of the function that can be called :param description: (Optional) Description of what the function does :param parameters: (Optional) JSON schema defining the function’s parameters :param strict: (Optional) Whether to enforce strict parameter validation

Field	Type	Description
type	string
name	string
description	string
parameters	object
strict	boolean

OpenAIResponseInputToolWebSearch

Web search tool configuration for OpenAI response inputs.

:param type: Web search tool type variant to use :param search_context_size: (Optional) Size of search context, must be “low”, “medium”, or “high”

Field	Type	Description
type
search_context_size	string

OpenAIResponseMCPApprovalRequest

A request for human approval of a tool invocation.

Field	Type	Description
arguments	string
id	string
name	string
server_label	string
type	string

OpenAIResponseMCPApprovalResponse

A response to an MCP approval request.

Field	Type	Description
approval_request_id	string
approve	boolean
type	string
id	string
reason	string

OpenAIResponseMessage

Corresponds to the various Message types in the Responses API. They are all under one type because the Responses API gives them all the same “type” value, and there is no way to tell them apart in certain scenarios.

Field	Type	Description
content
role
type	string
id	string
status	string

OpenAIResponseOutputMessageContentOutputText

Field	Type	Description
text	string
type	string
annotations	array
logprobs	array

OpenAIResponseOutputMessageFileSearchToolCall

File search tool call output message for OpenAI responses.

:param id: Unique identifier for this tool call :param queries: List of search queries executed :param status: Current status of the file search operation :param type: Tool call type identifier, always “file_search_call” :param results: (Optional) Search results returned by the file search operation

Field	Type	Description
id	string
queries	array
status	string
type	string
results	array

OpenAIResponseOutputMessageFileSearchToolCallResults

Search results returned by the file search operation.

:param attributes: (Optional) Key-value attributes associated with the file :param file_id: Unique identifier of the file containing the result :param filename: Name of the file containing the result :param score: Relevance score for this search result (between 0 and 1) :param text: Text content of the search result

Field	Type	Description
attributes	object
file_id	string
filename	string
score	number
text	string

OpenAIResponseOutputMessageFunctionToolCall

Function tool call output message for OpenAI responses.

:param call_id: Unique identifier for the function call :param name: Name of the function being called :param arguments: JSON string containing the function arguments :param type: Tool call type identifier, always “function_call” :param id: (Optional) Additional identifier for the tool call :param status: (Optional) Current status of the function call execution

Field	Type	Description
call_id	string
name	string
arguments	string
type	string
id	string
status	string

OpenAIResponseOutputMessageMCPCall

Model Context Protocol (MCP) call output message for OpenAI responses.

:param id: Unique identifier for this MCP call :param type: Tool call type identifier, always “mcp_call” :param arguments: JSON string containing the MCP call arguments :param name: Name of the MCP method being called :param server_label: Label identifying the MCP server handling the call :param error: (Optional) Error message if the MCP call failed :param output: (Optional) Output result from the successful MCP call

Field	Type	Description
id	string
type	string
arguments	string
name	string
server_label	string
error	string
output	string

OpenAIResponseOutputMessageMCPListTools

MCP list tools output message containing available tools from an MCP server.

:param id: Unique identifier for this MCP list tools operation :param type: Tool call type identifier, always “mcp_list_tools” :param server_label: Label identifying the MCP server providing the tools :param tools: List of available tools provided by the MCP server

Field	Type	Description
id	string
type	string
server_label	string
tools	array

OpenAIResponseOutputMessageWebSearchToolCall

Web search tool call output message for OpenAI responses.

:param id: Unique identifier for this tool call :param status: Current status of the web search operation :param type: Tool call type identifier, always “web_search_call”

Field	Type	Description
id	string
status	string
type	string

OpenAIResponsePrompt

OpenAI compatible Prompt object that is used in OpenAI responses.

:param id: Unique identifier of the prompt template :param variables: Dictionary of variable names to OpenAIResponseInputMessageContent structure for template substitution. The substitution values can either be strings, or other Response input types like images or files. :param version: Version number of the prompt to use (defaults to latest if not specified)

Field	Type	Description
id	string
variables	object
version	string

OpenAIResponseReasoning

Configuration for reasoning effort in OpenAI responses.

Controls how much reasoning the model performs before generating a response.

:param effort: The effort level for reasoning. “low” favors speed and economical token usage, “high” favors more complete reasoning, “medium” is a balance between the two.

Field	Type	Description
effort	string

OpenAIResponseText

Text response configuration for OpenAI responses.

:param format: (Optional) Text format configuration specifying output format requirements

Field	Type	Description
format

OpenAIResponseTextFormat

Configuration for Responses API text format.

:param type: Must be “text”, “json_schema”, or “json_object” to identify the format type :param name: The name of the response format. Only used for json_schema. :param schema: The JSON schema the response should conform to. In a Python SDK, this is often a pydantic model. Only used for json_schema. :param description: (Optional) A description of the response format. Only used for json_schema. :param strict: (Optional) Whether to strictly enforce the JSON schema. If true, the response must match the schema exactly. Only used for json_schema.

Field	Type	Description
type
name	string
schema	object
description	string
strict	boolean

OpenAITokenLogProb

The log probability for a token from an OpenAI-compatible chat completion response.

Field	Type	Description
token	string	The token.
bytes	array	The bytes for the token.
logprob	number	The log probability of the token.
top_logprobs	array	The top log probabilities for the token.

OpenAITopLogProb

The top log probability for a token from an OpenAI-compatible chat completion response.

Field	Type	Description
token	string	The token.
bytes	array	The bytes for the token.
logprob	number	The log probability of the token.

PromptCreateRequest

Request body to create a stored prompt template in Llama Stack.

Attributes: prompt: Prompt text with variable placeholders. variables: Variable names allowed in the template.

Field	Type	Description
prompt	string	Prompt text with variable placeholders
variables	array	Variable names allowed in the template

PromptUpdateRequest

Request body to update a stored prompt (creates a new version).

Attributes: prompt: Updated prompt text. version: Current version being updated. set_as_default: Whether the new version becomes the default. variables: Updated allowed variable names.

Field	Type	Description
prompt	string	Updated prompt text
version	integer	Current version being updated
set_as_default	boolean	Whether the new version becomes the default
variables	array	Updated allowed variable names

QueryRequest

Model representing a request for the LLM (Language Model).

Attributes: query: The query string. conversation_id: The optional conversation ID (UUID). provider: The optional provider. model: The optional model. system_prompt: The optional system prompt. attachments: The optional attachments. no_tools: Whether to bypass all tools and MCP servers (default: False). generate_topic_summary: Whether to generate topic summary for new conversations. media_type: The optional media type for response format (application/json or text/plain). vector_store_ids: The optional list of specific vector store IDs to query for RAG. shield_ids: The optional list of safety shield IDs to apply. solr: Optional Solr inline RAG options (mode, filters) or legacy filter-only dict.

Field	Type	Description
query	string	The query string
conversation_id	string	The optional conversation ID (UUID)
provider	string	The optional provider
model	string	The optional model
system_prompt	string	The optional system prompt.
attachments	array	The optional list of attachments.
no_tools	boolean	Whether to bypass all tools and MCP servers
generate_topic_summary	boolean	Whether to generate topic summary for new conversations
media_type	string	Media type for the response format
vector_store_ids	array	Optional list of specific vector store IDs to query for RAG. If not provided, all available vector stores will be queried.
shield_ids	array	Optional list of safety shield IDs to apply. If None, all configured shields are used.
solr		Solr inline RAG config: mode (semantic, hybrid, lexical) and filters; a legacy filter-only object (e.g. fq) is still accepted.

ResponseInput

ResponseItem

ResponsesRequest

Model representing a request for the Responses API following LCORE specification.

Attributes: input: Input text or structured input items containing the query. model: Model identifier in format “provider/model”. Auto-selected if not provided. conversation: Conversation ID linking to an existing conversation. Accepts both OpenAI and LCORE formats. Mutually exclusive with previous_response_id. include: Explicitly specify output item types that are excluded by default but should be included in the response. instructions: System instructions or guidelines provided to the model (acts as the system prompt). max_infer_iters: Maximum number of inference iterations the model can perform. max_output_tokens: Maximum number of tokens allowed in the response. max_tool_calls: Maximum number of tool calls allowed in a single response. metadata: Custom metadata dictionary with key-value pairs for tracking or logging. parallel_tool_calls: Whether the model can make multiple tool calls in parallel. previous_response_id: Identifier of the previous response in a multi-turn conversation. Mutually exclusive with conversation. prompt: Prompt object containing a template with variables for dynamic substitution. reasoning: Reasoning configuration for the response. safety_identifier: Safety identifier for the response. store: Whether to store the response in conversation history. Defaults to True. stream: Whether to stream the response as it is generated. Defaults to False. temperature: Sampling temperature controlling randomness (typically 0.0–2.0). text: Text response configuration specifying output format constraints (JSON schema, JSON object, or plain text). tool_choice: Tool selection strategy (“auto”, “required”, “none”, or specific tool configuration). tools: List of tools available to the model (file search, web search, function calls, MCP tools). Defaults to all tools available to the model. generate_topic_summary: LCORE-specific flag indicating whether to generate a topic summary for new conversations. Defaults to True. shield_ids: LCORE-specific list of safety shield IDs to apply. If None, all configured shields are used. solr: Optional Solr inline RAG options (mode, filters) or legacy filter-only dict.

Field	Type	Description
input
model	string
conversation	string
include	array
instructions	string
max_infer_iters	integer
max_output_tokens	integer
max_tool_calls	integer
metadata	object
parallel_tool_calls	boolean
previous_response_id	string
prompt
reasoning
safety_identifier	string
store	boolean
stream	boolean
temperature	number
text
tool_choice
tools	array
generate_topic_summary	boolean
shield_ids	array
solr

RlsapiV1Attachment

Attachment data from rlsapi v1 context.

Attributes: contents: The textual contents of the file read on the client machine. mimetype: The MIME type of the file.

Field	Type	Description
contents	string	File contents read on client
mimetype	string	MIME type of the file

RlsapiV1CLA

Command Line Assistant information from rlsapi v1 context.

Attributes: nevra: The NEVRA (Name-Epoch-Version-Release-Architecture) of the CLA. version: The version of the command line assistant.

Field	Type	Description
nevra	string	CLA NEVRA identifier
version	string	Command line assistant version

RlsapiV1Context

Context data for rlsapi v1 /infer request.

Attributes: stdin: Redirect input read by command-line-assistant. attachments: Attachment object received by the client. terminal: Terminal object received by the client. systeminfo: System information object received by the client. cla: Command Line Assistant information.

Field	Type	Description
stdin	string	Redirect input from stdin
attachments		File attachment data
terminal		Terminal output context
systeminfo		Client system information
cla		Command line assistant metadata

RlsapiV1InferRequest

RHEL Lightspeed rlsapi v1 /infer request.

Attributes: question: User question string. context: Context with system info, terminal output, etc. (defaults provided). skip_rag: Reserved for future use. RAG retrieval is not yet implemented. include_metadata: Request extended response with debugging metadata (dev/testing only).

Example: python request = RlsapiV1InferRequest( question="How do I list files?", context=RlsapiV1Context( systeminfo=RlsapiV1SystemInfo(os="RHEL", version="9.3"), terminal=RlsapiV1Terminal(output="bash: command not found"), ), )

Field	Type	Description
question	string	User question
context		Optional context (system info, terminal output, stdin, attachments)
skip_rag	boolean	Reserved for future use. RAG retrieval is not yet implemented.
include_metadata	boolean	[Development/Testing Only] Return extended response with debugging metadata (tool_calls, rag_chunks, tokens). Only honored when allow_verbose_infer is enabled. Not available in production.

RlsapiV1SystemInfo

System information from rlsapi v1 context.

Attributes: os: The operating system of the client machine. version: The version of the operating system. arch: The architecture of the client machine. system_id: The id of the client machine.

Field	Type	Description
os	string	Operating system name
version	string	Operating system version
arch	string	System architecture
id	string	Client machine ID

RlsapiV1Terminal

Terminal output from rlsapi v1 context.

Attributes: output: The textual contents of the terminal read on the client machine.

Field	Type	Description
output	string	Terminal output from client

SearchRankingOptions

Options for ranking and filtering search results.

This class configures how search results are ranked and filtered. You can use algorithm-based rerankers (weighted, RRF) or neural rerankers. Defaults from VectorStoresConfig are used when parameters are not provided.

Examples: # Weighted ranker with custom alpha SearchRankingOptions(ranker=”weighted”, alpha=0.7)

# RRF ranker with custom impact factor
SearchRankingOptions(ranker="rrf", impact_factor=50.0)

# Use config defaults (just specify ranker type)
SearchRankingOptions(ranker="weighted")  # Uses alpha from VectorStoresConfig

# Score threshold filtering
SearchRankingOptions(ranker="weighted", score_threshold=0.5)

:param ranker: (Optional) Name of the ranking algorithm to use. Supported values: - “weighted”: Weighted combination of vector and keyword scores - “rrf”: Reciprocal Rank Fusion algorithm - “neural”: Neural reranking model (requires model parameter, Part II) Note: For OpenAI API compatibility, any string value is accepted, but only the above values are supported. :param score_threshold: (Optional) Minimum relevance score threshold for results. Default: 0.0 :param alpha: (Optional) Weight factor for weighted ranker (0-1). - 0.0 = keyword only - 0.5 = equal weight (default) - 1.0 = vector only Only used when ranker=”weighted” and weights is not provided. Falls back to VectorStoresConfig.chunk_retrieval_params.weighted_search_alpha if not provided. :param impact_factor: (Optional) Impact factor (k) for RRF algorithm. Lower values emphasize higher-ranked results. Default: 60.0 (optimal from research). Only used when ranker=”rrf”. Falls back to VectorStoresConfig.chunk_retrieval_params.rrf_impact_factor if not provided. :param weights: (Optional) Dictionary of weights for combining different signal types. Keys can be “vector”, “keyword”, “neural”. Values should sum to 1.0. Used when combining algorithm-based reranking with neural reranking (Part II). Example: {“vector”: 0.3, “keyword”: 0.3, “neural”: 0.4} :param model: (Optional) Model identifier for neural reranker (e.g., “vllm/Qwen3-Reranker-0.6B”). Required when ranker=”neural” or when weights contains “neural” (Part II).

Field	Type	Description
ranker	string
score_threshold	number
alpha	number	Weight factor for weighted ranker
impact_factor	number	Impact factor for RRF algorithm
weights	object	Weights for combining vector, keyword, and neural scores. Keys: ‘vector’, ‘keyword’, ‘neural’
model	string	Model identifier for neural reranker

SolrVectorSearchRequest

LCORE Solr inline RAG options for vector_io.query (mode and provider filters).

Attributes: mode: Solr vector_io search mode. When omitted, the server default (hybrid) is used. filters: Solr provider filter payload passed through as params[‘solr’].

Legacy clients may send a plain JSON object with filter keys only; that object is accepted as filters with mode unset (server default applies).

Field	Type	Description
mode	string	Solr vector_io search mode. When omitted, the server default (‘hybrid’) is used.
filters	object	Solr provider filter payload passed through as params[‘solr’]. Supports structured metadata filters (eq, ne, in, nin comparison operators). Legacy filter-only objects (e.g. fq) are still accepted.

StreamingInterruptRequest

Model representing a request to interrupt an active streaming query.

Attributes: request_id: Unique ID of the active streaming request to interrupt.

Field	Type	Description
request_id	string	The active streaming request ID to interrupt

VectorStoreCreateRequest

Model representing a request to create a vector store.

Attributes: name: Name of the vector store. embedding_model: Optional embedding model to use. embedding_dimension: Optional embedding dimension. chunking_strategy: Optional chunking strategy configuration. provider_id: Optional vector store provider identifier. metadata: Optional metadata dictionary for storing session information.

Field	Type	Description
name	string	Name of the vector store
embedding_model	string	Embedding model to use for the vector store
embedding_dimension	integer	Dimension of the embedding vectors
chunking_strategy	object	Chunking strategy configuration
provider_id	string	Vector store provider identifier
metadata	object	Metadata dictionary for storing session information

VectorStoreFileCreateRequest

Model representing a request to add a file to a vector store.

Attributes: file_id: ID of the file to add to the vector store. attributes: Optional metadata key-value pairs (max 16 pairs). chunking_strategy: Optional chunking strategy configuration.

Field	Type	Description
file_id	string	ID of the file to add to the vector store
attributes	object	Set of up to 16 key-value pairs for storing additional information. Keys: strings (max 64 chars). Values: strings (max 512 chars), booleans, or numbers.
chunking_strategy	object	Chunking strategy configuration for this file

VectorStoreUpdateRequest

Model representing a request to update a vector store.

Attributes: name: New name for the vector store. expires_at: Optional expiration timestamp. metadata: Optional metadata dictionary for storing session information.

Field	Type	Description
name	string	New name for the vector store
expires_at	integer	Unix timestamp when the vector store should expire
metadata	object	Metadata dictionary for storing session information