Files
OSGKeyboard/OSGKeyboardShared/Models/LLMRequest.swift
T
Rocky 34be2e8dd1 feat(polish): add context safeguards, layered prompts, and output validation
Use redacted cursor neighborhood and pause-aware chunks for more natural polish,
validate protected terms with retry/local fallback, and structure bilingual prompts
for consistency and provider prefix caching.
2026-07-29 17:45:11 +08:00

142 lines
4.4 KiB
Swift

// LLMRequest.swift
// OSGKeyboard · Shared
//
// OpenAI-compatible chat completion request/response models.
// Compatible with OpenAI, DeepSeek, Qwen DashScope, and any provider that
// implements POST {baseURL}/chat/completions.
import Foundation
public struct LLMRequest: Codable, Sendable {
public let model: String
public let messages: [Message]
public let temperature: Double?
public let maxTokens: Int?
public let topP: Double?
private enum CodingKeys: String, CodingKey {
case model, messages, temperature
case maxTokens = "max_tokens"
case topP = "top_p"
}
public enum Message: Codable, Sendable {
case system(String)
case user(String)
case assistant(String)
private enum CodingKeys: String, CodingKey {
case role, content
}
public func encode(to encoder: Encoder) throws {
var c = encoder.container(keyedBy: CodingKeys.self)
switch self {
case .system(let s):
try c.encode("system", forKey: .role); try c.encode(s, forKey: .content)
case .user(let s):
try c.encode("user", forKey: .role); try c.encode(s, forKey: .content)
case .assistant(let s):
try c.encode("assistant", forKey: .role); try c.encode(s, forKey: .content)
}
}
public init(from decoder: Decoder) throws {
let c = try decoder.container(keyedBy: CodingKeys.self)
let role = try c.decode(String.self, forKey: .role)
let content = try c.decode(String.self, forKey: .content)
switch role {
case "system": self = .system(content)
case "user": self = .user(content)
case "assistant": self = .assistant(content)
default:
throw DecodingError.dataCorruptedError(forKey: .role, in: c,
debugDescription: "Unknown role \(role)")
}
}
}
public init(
model: String,
messages: [Message],
temperature: Double? = 0.1,
maxTokens: Int? = nil,
topP: Double? = 0.9
) {
self.model = model
self.messages = messages
self.temperature = temperature
self.maxTokens = maxTokens
self.topP = topP
}
/// Coarse estimate used only for a safe output ceiling.
public static func estimatedTokenCount(for text: String) -> Int {
var cjkCount = 0
var nonCJKCount = 0
for scalar in text.unicodeScalars {
switch scalar.value {
case 0x4E00...0x9FFF, 0x3400...0x4DBF, 0xF900...0xFAFF:
cjkCount += 1
default:
nonCJKCount += 1
}
}
return max(1, cjkCount + Int(ceil(Double(nonCJKCount) / 4.0)))
}
public static func outputTokenLimit(for text: String) -> Int {
min(4_096, max(256, estimatedTokenCount(for: text) * 2))
}
}
public struct LLMResponse: Codable, Sendable {
public let id: String?
public let choices: [Choice]
public let usage: Usage?
public struct Usage: Codable, Sendable {
public let promptTokens: Int?
public let promptCacheHitTokens: Int?
public let promptTokensDetails: PromptTokensDetails?
public struct PromptTokensDetails: Codable, Sendable {
public let cachedTokens: Int?
private enum CodingKeys: String, CodingKey {
case cachedTokens = "cached_tokens"
}
}
private enum CodingKeys: String, CodingKey {
case promptTokens = "prompt_tokens"
case promptCacheHitTokens = "prompt_cache_hit_tokens"
case promptTokensDetails = "prompt_tokens_details"
}
public var cachedTokens: Int? {
promptCacheHitTokens ?? promptTokensDetails?.cachedTokens
}
}
public struct Choice: Codable, Sendable {
public let index: Int
public let message: LLMRequest.Message
public let finishReason: String?
private enum CodingKeys: String, CodingKey {
case index, message
case finishReason = "finish_reason"
}
}
public var content: String {
switch choices.first?.message {
case .system(let s), .user(let s), .assistant(let s):
return s
case .none:
return ""
}
}
}