/* * Copyright (C) 2024 Petr Mironychev * * This file is part of QodeAssist. * * QodeAssist is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * QodeAssist is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with QodeAssist. If not, see . */ #include "OpenAICompatProvider.hpp" #include "settings/ChatAssistantSettings.hpp" #include "settings/CodeCompletionSettings.hpp" #include #include #include #include #include "llmcore/OpenAIMessage.hpp" #include "llmcore/ValidationUtils.hpp" #include "logger/Logger.hpp" namespace QodeAssist::Providers { OpenAICompatProvider::OpenAICompatProvider() {} QString OpenAICompatProvider::name() const { return "OpenAI Compatible"; } QString OpenAICompatProvider::url() const { return "http://localhost:1234"; } QString OpenAICompatProvider::completionEndpoint() const { return "/v1/chat/completions"; } QString OpenAICompatProvider::chatEndpoint() const { return "/v1/chat/completions"; } bool OpenAICompatProvider::supportsModelListing() const { return false; } void OpenAICompatProvider::prepareRequest(QJsonObject &request, LLMCore::RequestType type) { auto prepareMessages = [](QJsonObject &req) -> QJsonArray { QJsonArray messages; if (req.contains("system")) { messages.append( QJsonObject{{"role", "system"}, {"content", req.take("system").toString()}}); } if (req.contains("prompt")) { messages.append( QJsonObject{{"role", "user"}, {"content", req.take("prompt").toString()}}); } return messages; }; auto applyModelParams = [&request](const auto &settings) { request["max_tokens"] = settings.maxTokens(); request["temperature"] = settings.temperature(); if (settings.useTopP()) request["top_p"] = settings.topP(); if (settings.useTopK()) request["top_k"] = settings.topK(); if (settings.useFrequencyPenalty()) request["frequency_penalty"] = settings.frequencyPenalty(); if (settings.usePresencePenalty()) request["presence_penalty"] = settings.presencePenalty(); }; QJsonArray messages = prepareMessages(request); if (!messages.isEmpty()) { request["messages"] = std::move(messages); } if (type == LLMCore::RequestType::Fim) { applyModelParams(Settings::codeCompletionSettings()); } else { applyModelParams(Settings::chatAssistantSettings()); } } bool OpenAICompatProvider::handleResponse(QNetworkReply *reply, QString &accumulatedResponse) { QByteArray data = reply->readAll(); if (data.isEmpty()) { return false; } QByteArrayList chunks = data.split('\n'); for (const QByteArray &chunk : chunks) { if (chunk.trimmed().isEmpty() || chunk == "data: [DONE]") { continue; } QByteArray jsonData = chunk; if (chunk.startsWith("data: ")) { jsonData = chunk.mid(6); } QJsonParseError error; QJsonDocument doc = QJsonDocument::fromJson(jsonData, &error); if (doc.isNull()) { continue; } auto message = LLMCore::OpenAIMessage::fromJson(doc.object()); if (message.hasError()) { LOG_MESSAGE("Error in OpenAI response: " + message.error); continue; } accumulatedResponse += message.getContent(); return message.isDone(); } return false; } QList OpenAICompatProvider::getInstalledModels(const QString &url) { return QStringList(); } QList OpenAICompatProvider::validateRequest( const QJsonObject &request, LLMCore::TemplateType type) { const auto templateReq = QJsonObject{ {"model", {}}, {"messages", QJsonArray{{QJsonObject{{"role", {}}, {"content", {}}}}}}, {"temperature", {}}, {"max_tokens", {}}, {"top_p", {}}, {"top_k", {}}, {"frequency_penalty", {}}, {"presence_penalty", {}}, {"stop", QJsonArray{}}, {"stream", {}}}; return LLMCore::ValidationUtils::validateRequestFields(request, templateReq); } } // namespace QodeAssist::Providers