runeandClaude Sonnet 5
0af644456e
Consolidates the mac.oai.pm subdomain references (introduced in the PolyForm Noncommercial relicense) to the root oai.pm domain, across the LICENSE file, README, and all Swift source file headers. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
384 lines
16 KiB
Swift
384 lines
16 KiB
Swift
//
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// OpenAIProvider.swift
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// oAI
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//
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// OpenAI API provider with SSE streaming and tool support
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//
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// SPDX-License-Identifier: PolyForm-Noncommercial-1.0.0
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// Copyright (C) 2026 Rune Olsen
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//
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// This file is part of oAI.
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//
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// oAI is licensed under the PolyForm Noncommercial License 1.0.0.
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// You may use, study, modify, and share it for any noncommercial
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// purpose. Commercial use — including selling oAI or any part of
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// it, standalone or bundled into another product or service —
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// requires a separate commercial license from the copyright holder.
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//
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// See the LICENSE file or
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// <https://polyformproject.org/licenses/noncommercial/1.0.0> for
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// the full license text. For commercial licensing, contact Rune
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// Olsen via <https://oai.pm>.
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import Foundation
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import os
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class OpenAIProvider: AIProvider {
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let name = "OpenAI"
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let capabilities = ProviderCapabilities(
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supportsStreaming: true,
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supportsVision: true,
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supportsTools: true,
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supportsOnlineSearch: false,
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maxContextLength: nil
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)
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private let apiKey: String
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private let baseURL = "https://api.openai.com/v1"
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private let session: URLSession
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init(apiKey: String) {
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self.apiKey = apiKey
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let config = URLSessionConfiguration.default
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config.timeoutIntervalForRequest = 60
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config.timeoutIntervalForResource = 300
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self.session = URLSession(configuration: config)
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}
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// MARK: - Models
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/// Known models with pricing, used as fallback and for enrichment
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private static let knownModels: [String: (name: String, desc: String?, ctx: Int, prompt: Double, completion: Double, vision: Bool)] = [
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"gpt-4o": ("GPT-4o", "Most capable GPT-4 model", 128_000, 2.50, 10.0, true),
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"gpt-4o-mini": ("GPT-4o Mini", "Affordable and fast", 128_000, 0.15, 0.60, true),
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"gpt-4-turbo": ("GPT-4 Turbo", "GPT-4 Turbo with vision", 128_000, 10.0, 30.0, true),
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"gpt-3.5-turbo": ("GPT-3.5 Turbo", "Fast and affordable", 16_385, 0.50, 1.50, false),
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"o1": ("o1", "Advanced reasoning model", 200_000, 15.0, 60.0, true),
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"o1-mini": ("o1 Mini", "Fast reasoning model", 128_000, 3.0, 12.0, false),
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"o3-mini": ("o3 Mini", "Latest fast reasoning model", 200_000, 1.10, 4.40, false),
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]
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func listModels() async throws -> [ModelInfo] {
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Log.api.info("Fetching model list from OpenAI")
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let url = URL(string: "\(baseURL)/models")!
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var request = URLRequest(url: url)
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request.addValue("Bearer \(apiKey)", forHTTPHeaderField: "Authorization")
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do {
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let (data, response) = try await session.data(for: request)
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guard let httpResponse = response as? HTTPURLResponse, httpResponse.statusCode == 200 else {
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Log.api.warning("OpenAI models endpoint failed, using fallback models")
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return fallbackModels()
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}
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guard let json = try? JSONSerialization.jsonObject(with: data) as? [String: Any],
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let modelsArray = json["data"] as? [[String: Any]] else {
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return fallbackModels()
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}
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// Filter to chat models
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let chatModelIds = modelsArray
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.compactMap { $0["id"] as? String }
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.filter { id in
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id.contains("gpt") || id.hasPrefix("o1") || id.hasPrefix("o3")
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}
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.sorted()
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var models: [ModelInfo] = []
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for id in chatModelIds {
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if let known = Self.knownModels[id] {
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models.append(ModelInfo(
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id: id,
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name: known.name,
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description: known.desc,
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contextLength: known.ctx,
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pricing: .init(prompt: known.prompt, completion: known.completion),
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capabilities: .init(vision: known.vision, tools: true, online: false)
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))
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} else {
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models.append(ModelInfo(
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id: id,
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name: id,
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description: nil,
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contextLength: 128_000,
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pricing: .init(prompt: 0, completion: 0),
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capabilities: .init(vision: false, tools: true, online: false)
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))
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}
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}
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Log.api.info("OpenAI loaded \(models.count) models")
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return models.isEmpty ? fallbackModels() : models
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} catch {
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Log.api.warning("OpenAI models fetch failed: \(error.localizedDescription), using fallback")
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return fallbackModels()
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}
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}
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private func fallbackModels() -> [ModelInfo] {
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Self.knownModels.map { id, info in
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ModelInfo(
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id: id,
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name: info.name,
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description: info.desc,
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contextLength: info.ctx,
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pricing: .init(prompt: info.prompt, completion: info.completion),
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capabilities: .init(vision: info.vision, tools: true, online: false)
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)
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}.sorted { $0.name < $1.name }
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}
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func getModel(_ id: String) async throws -> ModelInfo? {
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let models = try await listModels()
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return models.first { $0.id == id }
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}
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// MARK: - Chat Completion
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func chat(request: ChatRequest) async throws -> ChatResponse {
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Log.api.info("OpenAI chat request: model=\(request.model), messages=\(request.messages.count)")
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let urlRequest = try buildURLRequest(from: request, stream: false)
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let (data, response) = try await session.data(for: urlRequest)
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guard let httpResponse = response as? HTTPURLResponse else {
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Log.api.error("OpenAI chat: invalid response (not HTTP)")
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throw ProviderError.invalidResponse
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}
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guard httpResponse.statusCode == 200 else {
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if let errorObj = try? JSONSerialization.jsonObject(with: data) as? [String: Any],
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let error = errorObj["error"] as? [String: Any],
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let message = error["message"] as? String {
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Log.api.error("OpenAI chat HTTP \(httpResponse.statusCode): \(message)")
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throw ProviderError.unknown(message)
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}
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Log.api.error("OpenAI chat HTTP \(httpResponse.statusCode)")
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throw ProviderError.unknown("HTTP \(httpResponse.statusCode)")
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}
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// Reuse the OpenRouter response format — OpenAI is identical
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let apiResponse = try JSONDecoder().decode(OpenRouterChatResponse.self, from: data)
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return convertToChatResponse(apiResponse)
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}
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// MARK: - Chat with raw tool messages
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func chatWithToolMessages(model: String, messages: [[String: Any]], tools: [Tool]?, maxTokens: Int?, temperature: Double?) async throws -> ChatResponse {
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Log.api.info("OpenAI tool chat: model=\(model), messages=\(messages.count)")
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let url = URL(string: "\(baseURL)/chat/completions")!
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var body: [String: Any] = [
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"model": model,
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"messages": messages,
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"stream": false
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]
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if let tools = tools {
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let toolsData = try JSONEncoder().encode(tools)
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body["tools"] = try JSONSerialization.jsonObject(with: toolsData)
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body["tool_choice"] = "auto"
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}
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if let maxTokens = maxTokens { body["max_tokens"] = maxTokens }
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// o1/o3 models don't support temperature
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if let temperature = temperature, !model.hasPrefix("o1"), !model.hasPrefix("o3") {
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body["temperature"] = temperature
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}
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var urlRequest = URLRequest(url: url)
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urlRequest.httpMethod = "POST"
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urlRequest.addValue("Bearer \(apiKey)", forHTTPHeaderField: "Authorization")
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urlRequest.addValue("application/json", forHTTPHeaderField: "Content-Type")
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urlRequest.httpBody = try JSONSerialization.data(withJSONObject: body)
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let (data, response) = try await session.data(for: urlRequest)
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guard let httpResponse = response as? HTTPURLResponse else {
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Log.api.error("OpenAI tool chat: invalid response (not HTTP)")
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throw ProviderError.invalidResponse
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}
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guard httpResponse.statusCode == 200 else {
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if let errorObj = try? JSONSerialization.jsonObject(with: data) as? [String: Any],
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let error = errorObj["error"] as? [String: Any],
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let message = error["message"] as? String {
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Log.api.error("OpenAI tool chat HTTP \(httpResponse.statusCode): \(message)")
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throw ProviderError.unknown(message)
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}
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Log.api.error("OpenAI tool chat HTTP \(httpResponse.statusCode)")
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throw ProviderError.unknown("HTTP \(httpResponse.statusCode)")
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}
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let apiResponse = try JSONDecoder().decode(OpenRouterChatResponse.self, from: data)
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return convertToChatResponse(apiResponse)
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}
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// MARK: - Streaming Chat
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func streamChat(request: ChatRequest) -> AsyncThrowingStream<StreamChunk, Error> {
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Log.api.info("OpenAI stream request: model=\(request.model), messages=\(request.messages.count)")
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return AsyncThrowingStream { continuation in
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Task {
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do {
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let urlRequest = try buildURLRequest(from: request, stream: true)
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let (bytes, response) = try await session.bytes(for: urlRequest)
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guard let httpResponse = response as? HTTPURLResponse else {
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Log.api.error("OpenAI stream: invalid response (not HTTP)")
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continuation.finish(throwing: ProviderError.invalidResponse)
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return
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}
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guard httpResponse.statusCode == 200 else {
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Log.api.error("OpenAI stream HTTP \(httpResponse.statusCode)")
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continuation.finish(throwing: ProviderError.unknown("HTTP \(httpResponse.statusCode)"))
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return
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}
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var buffer = ""
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for try await line in bytes.lines {
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guard line.hasPrefix("data: ") else { continue }
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let jsonString = String(line.dropFirst(6))
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if jsonString == "[DONE]" {
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continuation.finish()
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return
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}
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buffer += jsonString
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if let jsonData = buffer.data(using: .utf8) {
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do {
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let chunk = try JSONDecoder().decode(OpenRouterStreamChunk.self, from: jsonData)
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guard let choice = chunk.choices.first else { continue }
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continuation.yield(StreamChunk(
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id: chunk.id,
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model: chunk.model,
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delta: .init(content: choice.delta.content, role: choice.delta.role, images: nil),
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finishReason: choice.finishReason,
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usage: chunk.usage.map {
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ChatResponse.Usage(promptTokens: $0.promptTokens, completionTokens: $0.completionTokens, totalTokens: $0.totalTokens)
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}
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))
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buffer = ""
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} catch {
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continue // Partial JSON, keep buffering
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}
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}
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}
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continuation.finish()
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} catch {
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continuation.finish(throwing: error)
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}
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}
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}
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}
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// MARK: - Credits
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func getCredits() async throws -> Credits? {
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// OpenAI doesn't have a public credits API
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return nil
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}
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// MARK: - Helpers
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private func buildURLRequest(from request: ChatRequest, stream: Bool) throws -> URLRequest {
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let url = URL(string: "\(baseURL)/chat/completions")!
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var apiMessages: [[String: Any]] = []
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// Add system prompt if present
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if let systemPrompt = request.systemPrompt {
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apiMessages.append(["role": "system", "content": systemPrompt])
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}
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for msg in request.messages {
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let hasAttachments = msg.attachments?.contains(where: { $0.data != nil }) ?? false
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if hasAttachments, let attachments = msg.attachments {
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// Multi-part content (OpenAI vision format)
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var contentArray: [[String: Any]] = [
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["type": "text", "text": msg.content]
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]
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for attachment in attachments {
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guard let data = attachment.data else { continue }
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switch attachment.type {
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case .image, .pdf:
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let base64 = data.base64EncodedString()
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let dataURL = "data:\(attachment.mimeType);base64,\(base64)"
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contentArray.append([
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"type": "image_url",
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"image_url": ["url": dataURL]
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])
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case .text:
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let filename = (attachment.path as NSString).lastPathComponent
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let textContent = String(data: data, encoding: .utf8) ?? ""
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contentArray.append(["type": "text", "text": "File: \(filename)\n\n\(textContent)"])
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}
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}
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apiMessages.append(["role": msg.role.rawValue, "content": contentArray])
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} else {
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apiMessages.append(["role": msg.role.rawValue, "content": msg.content])
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}
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}
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var body: [String: Any] = [
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"model": request.model,
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"messages": apiMessages,
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"stream": stream
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]
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if let maxTokens = request.maxTokens { body["max_tokens"] = maxTokens }
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// o1/o3 reasoning models don't support temperature
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if let temperature = request.temperature, !request.model.hasPrefix("o1"), !request.model.hasPrefix("o3") {
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body["temperature"] = temperature
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}
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if let tools = request.tools {
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let toolsData = try JSONEncoder().encode(tools)
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body["tools"] = try JSONSerialization.jsonObject(with: toolsData)
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body["tool_choice"] = "auto"
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}
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if stream {
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// Request usage in streaming mode
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body["stream_options"] = ["include_usage": true]
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}
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let bodyData = try JSONSerialization.data(withJSONObject: body)
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var urlRequest = URLRequest(url: url)
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urlRequest.httpMethod = "POST"
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urlRequest.addValue("Bearer \(apiKey)", forHTTPHeaderField: "Authorization")
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urlRequest.addValue("application/json", forHTTPHeaderField: "Content-Type")
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if stream {
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urlRequest.addValue("text/event-stream", forHTTPHeaderField: "Accept")
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}
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urlRequest.httpBody = bodyData
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return urlRequest
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}
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private func convertToChatResponse(_ apiResponse: OpenRouterChatResponse) -> ChatResponse {
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guard let choice = apiResponse.choices.first else {
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return ChatResponse(id: apiResponse.id, model: apiResponse.model, content: "", role: "assistant", finishReason: nil, usage: nil, created: Date())
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}
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let toolCalls: [ToolCallInfo]? = choice.message.toolCalls?.map { tc in
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ToolCallInfo(id: tc.id, type: tc.type, functionName: tc.function.name, arguments: tc.function.arguments)
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}
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return ChatResponse(
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id: apiResponse.id,
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model: apiResponse.model,
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content: choice.message.content ?? "",
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role: choice.message.role,
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finishReason: choice.finishReason,
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usage: apiResponse.usage.map {
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ChatResponse.Usage(promptTokens: $0.promptTokens, completionTokens: $0.completionTokens, totalTokens: $0.totalTokens)
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},
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created: Date(timeIntervalSince1970: TimeInterval(apiResponse.created)),
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toolCalls: toolCalls
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)
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}
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}
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