Ole André Vadla Ravnås
5d0748515b
LLM agent for user-stated RE goals: propose-and-approve over the existing RPC, evidence-grounded findings, collab via the op-outbox pattern. Anthropic / OpenAI / local-OAI providers. r2ai used for explain_function when the plugin is loaded; falls back to the mission's own provider otherwise.
56 lines
1.6 KiB
Swift
56 lines
1.6 KiB
Swift
import Foundation
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import GRDB
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public struct MissionFinding: Codable, Identifiable, Sendable, FetchableRecord, PersistableRecord {
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public static let databaseTableName = "mission_finding"
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public var id: UUID
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public var missionID: UUID
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public var createdAt: Date
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public var title: String
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public var bodyMarkdown: String
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public var confidence: MissionFindingConfidence
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public var kind: String
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public var status: MissionFindingStatus
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public var sessionID: UUID?
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public var anchorJSON: String?
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public var pinnedInsightID: UUID?
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enum CodingKeys: String, CodingKey {
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case id
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case missionID = "mission_id"
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case createdAt = "created_at"
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case title
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case bodyMarkdown = "body_markdown"
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case confidence
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case kind
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case status
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case sessionID = "session_id"
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case anchorJSON = "anchor_json"
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case pinnedInsightID = "pinned_insight_id"
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}
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public init(
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id: UUID = UUID(),
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missionID: UUID,
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title: String,
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bodyMarkdown: String,
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confidence: MissionFindingConfidence,
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kind: String,
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sessionID: UUID? = nil,
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anchorJSON: String? = nil
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) {
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self.id = id
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self.missionID = missionID
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self.createdAt = Date()
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self.title = title
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self.bodyMarkdown = bodyMarkdown
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self.confidence = confidence
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self.kind = kind
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self.status = .proposed
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self.sessionID = sessionID
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self.anchorJSON = anchorJSON
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self.pinnedInsightID = nil
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}
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}
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