Struct AiConversation 

pub struct AiConversation {

    pub id: Option<String>,
    pub created_at: Option<DateTime<Utc>>,
    pub updated_at: Option<DateTime<Utc>>,
    pub archived_at: Option<DateTime<Utc>>,
    pub user: Option<User>,
    pub context: Option<Value>,
    pub summary: Option<String>,
    pub slug_id: Option<String>,
    pub workflow_definition: Option<WorkflowDefinition>,
    pub initial_source: Option<AiConversationInitialSource>,
    pub status: Option<AiConversationStatus>,
    pub read_at: Option<DateTime<Utc>>,
    pub iteration_id: Option<String>,
    pub eval_log_id: Option<String>,
}

Internal A conversation between a user and the Linear AI assistant. Each conversation tracks the full thread state, context references (issues, projects, documents, etc.), and conversation parts (prompts, text responses, tool calls, widgets). Conversations can originate from direct chat, issue comments, Slack threads, Microsoft Teams, or automated workflows.

Fields

id: Option<String>

The unique identifier of the entity.

created_at: Option<DateTime<Utc>>

The time at which the entity was created.

updated_at: Option<DateTime<Utc>>

The last time at which the entity was meaningfully updated. This is the same as the creation time if the entity hasn’t been updated after creation.

archived_at: Option<DateTime<Utc>>

The time at which the entity was archived. Null if the entity has not been archived.

user: Option<User>

The user who the conversation belongs to.

context: Option<Value>

The entity contexts this conversation is related to, such as issues, projects, or documents that provide context for the AI assistant.

summary: Option<String>

A summary of the conversation.

slug_id: Option<String>

The conversation’s unique URL slug.

workflow_definition: Option<WorkflowDefinition>

Internal The workflow definition that created this conversation.

initial_source: Option<AiConversationInitialSource>

The source from which this conversation was initiated, such as direct chat, an issue comment, a Slack thread, Microsoft Teams, or a workflow automation.

status: Option<AiConversationStatus>

The current processing status of the conversation, indicating whether the AI is actively generating a response or has completed its turn.

read_at: Option<DateTime<Utc>>

The time when the user marked the conversation as read. Null if the user hasn’t read the conversation.

iteration_id: Option<String>

The iteration ID when this conversation is part of an agentic workflow. Used to track multi-step workflow executions. Null for non-workflow conversations.

eval_log_id: Option<String>

Internal The log ID of the AI response.

Trait Implementations

impl Clone for AiConversation

fn clone(&self) -> AiConversation

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for AiConversation

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for AiConversation

fn default() -> AiConversation

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for AiConversation

where AiConversation: Default,

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl GraphQLFields for AiConversation

type FullType = AiConversation

The full generated type this implementation validates against.

fn selection() -> String

Return the GraphQL field selection string for this type.

impl Serialize for AiConversation

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.