mirror of
https://github.com/Palm1r/QodeAssist.git
synced 2026-04-06 04:42:44 -04:00
refactor: Add external LLMCore lib (#334)
* feat: Add LLMCore submodule
This commit is contained in:
Petr Mironychev
GitHub
@ -1,4 +1,4 @@
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/*
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/*
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* Copyright (C) 2024-2025 Petr Mironychev
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*
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* This file is part of QodeAssist.
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@ -18,9 +18,9 @@
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*/
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#include "OpenAIResponsesProvider.hpp"
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#include "OpenAIResponses/ResponseObject.hpp"
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#include <LLMCore/ToolsManager.hpp>
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#include "tools/ToolsRegistration.hpp"
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#include "llmcore/ValidationUtils.hpp"
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#include "logger/Logger.hpp"
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#include "settings/ChatAssistantSettings.hpp"
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#include "settings/CodeCompletionSettings.hpp"
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@ -35,14 +35,10 @@
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namespace QodeAssist::Providers {
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OpenAIResponsesProvider::OpenAIResponsesProvider(QObject *parent)
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: LLMCore::Provider(parent)
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, m_toolsManager(new Tools::ToolsManager(this))
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: PluginLLMCore::Provider(parent)
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, m_client(new ::LLMCore::OpenAIResponsesClient(QString(), QString(), QString(), this))
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{
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connect(
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m_toolsManager,
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&Tools::ToolsManager::toolExecutionComplete,
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this,
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&OpenAIResponsesProvider::onToolExecutionComplete);
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Tools::registerQodeAssistTools(m_client->tools());
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}
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QString OpenAIResponsesProvider::name() const
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@ -50,6 +46,11 @@ QString OpenAIResponsesProvider::name() const
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return "OpenAI Responses";
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}
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QString OpenAIResponsesProvider::apiKey() const
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{
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return Settings::providerSettings().openAiApiKey();
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}
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QString OpenAIResponsesProvider::url() const
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{
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return "https://api.openai.com";
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@ -65,16 +66,11 @@ QString OpenAIResponsesProvider::chatEndpoint() const
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return "/v1/responses";
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}
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bool OpenAIResponsesProvider::supportsModelListing() const
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{
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return true;
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}
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void OpenAIResponsesProvider::prepareRequest(
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QJsonObject &request,
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LLMCore::PromptTemplate *prompt,
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LLMCore::ContextData context,
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LLMCore::RequestType type,
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PluginLLMCore::PromptTemplate *prompt,
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PluginLLMCore::ContextData context,
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PluginLLMCore::RequestType type,
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bool isToolsEnabled,
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bool isThinkingEnabled)
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{
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@ -97,7 +93,7 @@ void OpenAIResponsesProvider::prepareRequest(
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if (effortStr.isEmpty()) {
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effortStr = "medium";
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}
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QJsonObject reasoning;
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reasoning["effort"] = effortStr;
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request["reasoning"] = reasoning;
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@ -109,9 +105,9 @@ void OpenAIResponsesProvider::prepareRequest(
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request["include"] = include;
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};
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if (type == LLMCore::RequestType::CodeCompletion) {
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if (type == PluginLLMCore::RequestType::CodeCompletion) {
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applyModelParams(Settings::codeCompletionSettings());
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} else if (type == LLMCore::RequestType::QuickRefactoring) {
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} else if (type == PluginLLMCore::RequestType::QuickRefactoring) {
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const auto &qrSettings = Settings::quickRefactorSettings();
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applyModelParams(qrSettings);
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@ -128,12 +124,8 @@ void OpenAIResponsesProvider::prepareRequest(
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}
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if (isToolsEnabled) {
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const LLMCore::RunToolsFilter filter = (type == LLMCore::RequestType::QuickRefactoring)
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? LLMCore::RunToolsFilter::OnlyRead
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: LLMCore::RunToolsFilter::ALL;
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const auto toolsDefinitions
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= m_toolsManager->getToolsDefinitions(LLMCore::ToolSchemaFormat::OpenAI, filter);
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= m_client->tools()->getToolsDefinitions();
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if (!toolsDefinitions.isEmpty()) {
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QJsonArray responsesTools;
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@ -156,496 +148,40 @@ void OpenAIResponsesProvider::prepareRequest(
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request["stream"] = true;
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}
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QFuture<QList<QString>> OpenAIResponsesProvider::getInstalledModels(const QString &url)
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QFuture<QList<QString>> OpenAIResponsesProvider::getInstalledModels(const QString &baseUrl)
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{
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QNetworkRequest request(QString("%1/v1/models").arg(url));
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request.setHeader(QNetworkRequest::ContentTypeHeader, "application/json");
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if (!apiKey().isEmpty()) {
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request.setRawHeader("Authorization", QString("Bearer %1").arg(apiKey()).toUtf8());
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}
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return httpClient()->get(request).then([](const QByteArray &data) {
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QList<QString> models;
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const QJsonObject jsonObject = QJsonDocument::fromJson(data).object();
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if (jsonObject.contains("data")) {
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const QJsonArray modelArray = jsonObject["data"].toArray();
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models.reserve(modelArray.size());
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static const QStringList modelPrefixes = {"gpt-5", "o1", "o2", "o3", "o4"};
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for (const QJsonValue &value : modelArray) {
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const QJsonObject modelObject = value.toObject();
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if (!modelObject.contains("id")) {
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continue;
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}
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const QString modelId = modelObject["id"].toString();
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for (const QString &prefix : modelPrefixes) {
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if (modelId.contains(prefix)) {
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models.append(modelId);
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break;
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}
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m_client->setUrl(baseUrl);
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m_client->setApiKey(apiKey());
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return m_client->listModels().then([](const QList<QString> &models) {
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QList<QString> filtered;
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static const QStringList modelPrefixes = {"gpt-5", "o1", "o2", "o3", "o4"};
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for (const QString &modelId : models) {
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for (const QString &prefix : modelPrefixes) {
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if (modelId.contains(prefix)) {
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filtered.append(modelId);
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break;
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}
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}
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}
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return models;
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}).onFailed([](const std::exception &e) {
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LOG_MESSAGE(QString("Error fetching OpenAI models: %1").arg(e.what()));
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return QList<QString>{};
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return filtered;
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});
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}
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QList<QString> OpenAIResponsesProvider::validateRequest(
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const QJsonObject &request, LLMCore::TemplateType type)
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PluginLLMCore::ProviderID OpenAIResponsesProvider::providerID() const
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{
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Q_UNUSED(type);
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QList<QString> errors;
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if (!request.contains("input")) {
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errors.append("Missing required field: input");
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return errors;
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}
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const QJsonValue inputValue = request["input"];
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if (!inputValue.isString() && !inputValue.isArray()) {
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errors.append("Field 'input' must be either a string or an array");
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}
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if (request.contains("max_output_tokens") && !request["max_output_tokens"].isDouble()) {
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errors.append("Field 'max_output_tokens' must be a number");
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}
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if (request.contains("top_p") && !request["top_p"].isDouble()) {
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errors.append("Field 'top_p' must be a number");
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}
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if (request.contains("reasoning") && !request["reasoning"].isObject()) {
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errors.append("Field 'reasoning' must be an object");
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}
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if (request.contains("stream") && !request["stream"].isBool()) {
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errors.append("Field 'stream' must be a boolean");
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}
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if (request.contains("tools") && !request["tools"].isArray()) {
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errors.append("Field 'tools' must be an array");
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}
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return errors;
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return PluginLLMCore::ProviderID::OpenAIResponses;
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}
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QString OpenAIResponsesProvider::apiKey() const
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PluginLLMCore::ProviderCapabilities OpenAIResponsesProvider::capabilities() const
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{
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return Settings::providerSettings().openAiApiKey();
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return PluginLLMCore::ProviderCapability::Tools | PluginLLMCore::ProviderCapability::Thinking
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| PluginLLMCore::ProviderCapability::Image
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| PluginLLMCore::ProviderCapability::ModelListing;
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}
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void OpenAIResponsesProvider::prepareNetworkRequest(QNetworkRequest &networkRequest) const
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::LLMCore::BaseClient *OpenAIResponsesProvider::client() const
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{
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networkRequest.setHeader(QNetworkRequest::ContentTypeHeader, "application/json");
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if (!apiKey().isEmpty()) {
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networkRequest.setRawHeader("Authorization", QString("Bearer %1").arg(apiKey()).toUtf8());
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}
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}
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LLMCore::ProviderID OpenAIResponsesProvider::providerID() const
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{
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return LLMCore::ProviderID::OpenAIResponses;
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}
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void OpenAIResponsesProvider::sendRequest(
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const LLMCore::RequestID &requestId, const QUrl &url, const QJsonObject &payload)
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{
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if (!m_messages.contains(requestId)) {
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m_dataBuffers[requestId].clear();
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}
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m_requestUrls[requestId] = url;
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m_originalRequests[requestId] = payload;
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QNetworkRequest networkRequest(url);
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prepareNetworkRequest(networkRequest);
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httpClient()->postStreaming(requestId, networkRequest, payload);
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}
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bool OpenAIResponsesProvider::supportsTools() const
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{
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return true;
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}
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bool OpenAIResponsesProvider::supportImage() const
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{
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return true;
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}
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bool OpenAIResponsesProvider::supportThinking() const
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{
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return true;
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}
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void OpenAIResponsesProvider::cancelRequest(const LLMCore::RequestID &requestId)
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{
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LLMCore::Provider::cancelRequest(requestId);
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cleanupRequest(requestId);
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}
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void OpenAIResponsesProvider::onDataReceived(
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const QodeAssist::LLMCore::RequestID &requestId, const QByteArray &data)
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{
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LLMCore::DataBuffers &buffers = m_dataBuffers[requestId];
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const QStringList lines = buffers.rawStreamBuffer.processData(data);
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QString currentEventType;
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for (const QString &line : lines) {
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const QString trimmedLine = line.trimmed();
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if (trimmedLine.isEmpty()) {
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continue;
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}
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if (line == "data: [DONE]") {
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continue;
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}
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if (line.startsWith("event: ")) {
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currentEventType = line.mid(7).trimmed();
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continue;
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}
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QString dataLine = line;
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if (line.startsWith("data: ")) {
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dataLine = line.mid(6);
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}
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const QJsonDocument doc = QJsonDocument::fromJson(dataLine.toUtf8());
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if (doc.isObject()) {
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const QJsonObject obj = doc.object();
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processStreamEvent(requestId, currentEventType, obj);
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}
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}
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}
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void OpenAIResponsesProvider::onRequestFinished(
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const QodeAssist::LLMCore::RequestID &requestId, std::optional<QString> error)
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{
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if (error) {
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LOG_MESSAGE(QString("OpenAIResponses request %1 failed: %2").arg(requestId, *error));
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emit requestFailed(requestId, *error);
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cleanupRequest(requestId);
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return;
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}
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if (m_messages.contains(requestId)) {
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OpenAIResponsesMessage *message = m_messages[requestId];
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if (message->state() == LLMCore::MessageState::RequiresToolExecution) {
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return;
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}
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}
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if (m_dataBuffers.contains(requestId)) {
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const LLMCore::DataBuffers &buffers = m_dataBuffers[requestId];
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if (!buffers.responseContent.isEmpty()) {
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emit fullResponseReceived(requestId, buffers.responseContent);
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} else {
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LOG_MESSAGE(QString("WARNING: OpenAIResponses - Response content is empty for %1, "
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"emitting empty response")
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.arg(requestId));
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emit fullResponseReceived(requestId, "");
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}
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} else {
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LOG_MESSAGE(
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QString("WARNING: OpenAIResponses - No data buffer found for %1").arg(requestId));
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}
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cleanupRequest(requestId);
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}
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void OpenAIResponsesProvider::processStreamEvent(
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const QString &requestId, const QString &eventType, const QJsonObject &data)
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{
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OpenAIResponsesMessage *message = m_messages.value(requestId);
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if (!message) {
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message = new OpenAIResponsesMessage(this);
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m_messages[requestId] = message;
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if (m_dataBuffers.contains(requestId)) {
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emit continuationStarted(requestId);
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}
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} else if (
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m_dataBuffers.contains(requestId)
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&& message->state() == LLMCore::MessageState::RequiresToolExecution) {
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message->startNewContinuation();
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emit continuationStarted(requestId);
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}
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if (eventType == "response.content_part.added") {
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} else if (eventType == "response.output_text.delta") {
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const QString delta = data["delta"].toString();
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if (!delta.isEmpty()) {
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m_dataBuffers[requestId].responseContent += delta;
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emit partialResponseReceived(requestId, delta);
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}
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} else if (eventType == "response.output_text.done") {
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const QString fullText = data["text"].toString();
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if (!fullText.isEmpty()) {
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m_dataBuffers[requestId].responseContent = fullText;
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}
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} else if (eventType == "response.content_part.done") {
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} else if (eventType == "response.output_item.added") {
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using namespace QodeAssist::OpenAIResponses;
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const QJsonObject item = data["item"].toObject();
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OutputItem outputItem = OutputItem::fromJson(item);
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if (const auto *functionCall = outputItem.asFunctionCall()) {
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if (!functionCall->callId.isEmpty() && !functionCall->name.isEmpty()) {
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if (!m_itemIdToCallId.contains(requestId)) {
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m_itemIdToCallId[requestId] = QHash<QString, QString>();
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}
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m_itemIdToCallId[requestId][functionCall->id] = functionCall->callId;
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message->handleToolCallStart(functionCall->callId, functionCall->name);
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}
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} else if (const auto *reasoning = outputItem.asReasoning()) {
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if (!reasoning->id.isEmpty()) {
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message->handleReasoningStart(reasoning->id);
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}
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}
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} else if (eventType == "response.reasoning_content.delta") {
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const QString itemId = data["item_id"].toString();
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const QString delta = data["delta"].toString();
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if (!itemId.isEmpty() && !delta.isEmpty()) {
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message->handleReasoningDelta(itemId, delta);
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}
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} else if (eventType == "response.reasoning_content.done") {
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const QString itemId = data["item_id"].toString();
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if (!itemId.isEmpty()) {
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message->handleReasoningComplete(itemId);
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emitPendingThinkingBlocks(requestId);
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}
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} else if (eventType == "response.function_call_arguments.delta") {
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const QString itemId = data["item_id"].toString();
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const QString delta = data["delta"].toString();
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if (!itemId.isEmpty() && !delta.isEmpty()) {
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const QString callId = m_itemIdToCallId.value(requestId).value(itemId);
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if (!callId.isEmpty()) {
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message->handleToolCallDelta(callId, delta);
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} else {
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LOG_MESSAGE(QString("ERROR: No call_id mapping found for item_id: %1").arg(itemId));
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}
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}
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} else if (
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eventType == "response.function_call_arguments.done"
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|| eventType == "response.output_item.done") {
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const QString itemId = data["item_id"].toString();
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const QJsonObject item = data["item"].toObject();
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if (!item.isEmpty() && item["type"].toString() == "reasoning") {
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using namespace QodeAssist::OpenAIResponses;
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const QString finalItemId = itemId.isEmpty() ? item["id"].toString() : itemId;
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ReasoningOutput reasoningOutput = ReasoningOutput::fromJson(item);
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QString reasoningText;
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if (!reasoningOutput.summaryText.isEmpty()) {
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reasoningText = reasoningOutput.summaryText;
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} else if (!reasoningOutput.contentTexts.isEmpty()) {
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reasoningText = reasoningOutput.contentTexts.join("\n");
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}
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if (reasoningText.isEmpty()) {
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reasoningText = QString(
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"[Reasoning process completed, but detailed thinking is not available in "
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"streaming mode. The model has processed your request with extended reasoning.]");
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}
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if (!finalItemId.isEmpty()) {
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message->handleReasoningDelta(finalItemId, reasoningText);
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message->handleReasoningComplete(finalItemId);
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emitPendingThinkingBlocks(requestId);
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}
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} else if (item.isEmpty() && !itemId.isEmpty()) {
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const QString callId = m_itemIdToCallId.value(requestId).value(itemId);
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if (!callId.isEmpty()) {
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message->handleToolCallComplete(callId);
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} else {
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LOG_MESSAGE(
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QString("ERROR: OpenAIResponses - No call_id mapping found for item_id: %1")
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.arg(itemId));
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}
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} else if (!item.isEmpty() && item["type"].toString() == "function_call") {
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const QString callId = item["call_id"].toString();
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if (!callId.isEmpty()) {
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message->handleToolCallComplete(callId);
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} else {
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LOG_MESSAGE(
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QString("ERROR: OpenAIResponses - Function call done but call_id is empty"));
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}
|
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}
|
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} else if (eventType == "response.created") {
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} else if (eventType == "response.in_progress") {
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} else if (eventType == "response.completed") {
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using namespace QodeAssist::OpenAIResponses;
|
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const QJsonObject responseObj = data["response"].toObject();
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Response response = Response::fromJson(responseObj);
|
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const QString statusStr = responseObj["status"].toString();
|
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|
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if (m_dataBuffers[requestId].responseContent.isEmpty()) {
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const QString aggregatedText = response.getAggregatedText();
|
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if (!aggregatedText.isEmpty()) {
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m_dataBuffers[requestId].responseContent = aggregatedText;
|
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}
|
||||
}
|
||||
|
||||
message->handleStatus(statusStr);
|
||||
handleMessageComplete(requestId);
|
||||
} else if (eventType == "response.incomplete") {
|
||||
using namespace QodeAssist::OpenAIResponses;
|
||||
const QJsonObject responseObj = data["response"].toObject();
|
||||
|
||||
if (!responseObj.isEmpty()) {
|
||||
Response response = Response::fromJson(responseObj);
|
||||
const QString statusStr = responseObj["status"].toString();
|
||||
|
||||
if (m_dataBuffers[requestId].responseContent.isEmpty()) {
|
||||
const QString aggregatedText = response.getAggregatedText();
|
||||
if (!aggregatedText.isEmpty()) {
|
||||
m_dataBuffers[requestId].responseContent = aggregatedText;
|
||||
}
|
||||
}
|
||||
|
||||
message->handleStatus(statusStr);
|
||||
} else {
|
||||
message->handleStatus("incomplete");
|
||||
}
|
||||
|
||||
handleMessageComplete(requestId);
|
||||
} else if (!eventType.isEmpty()) {
|
||||
LOG_MESSAGE(QString("WARNING: OpenAIResponses - Unhandled event type '%1' for request %2\nData: %3")
|
||||
.arg(eventType)
|
||||
.arg(requestId)
|
||||
.arg(QString::fromUtf8(QJsonDocument(data).toJson(QJsonDocument::Compact))));
|
||||
}
|
||||
}
|
||||
|
||||
void OpenAIResponsesProvider::emitPendingThinkingBlocks(const QString &requestId)
|
||||
{
|
||||
if (!m_messages.contains(requestId)) {
|
||||
return;
|
||||
}
|
||||
|
||||
OpenAIResponsesMessage *message = m_messages[requestId];
|
||||
const auto thinkingBlocks = message->getCurrentThinkingContent();
|
||||
|
||||
if (thinkingBlocks.isEmpty()) {
|
||||
return;
|
||||
}
|
||||
|
||||
const int alreadyEmitted = m_emittedThinkingBlocksCount.value(requestId, 0);
|
||||
const int totalBlocks = thinkingBlocks.size();
|
||||
|
||||
for (int i = alreadyEmitted; i < totalBlocks; ++i) {
|
||||
const auto *thinkingContent = thinkingBlocks[i];
|
||||
|
||||
if (thinkingContent->thinking().trimmed().isEmpty()) {
|
||||
continue;
|
||||
}
|
||||
|
||||
emit thinkingBlockReceived(
|
||||
requestId, thinkingContent->thinking(), thinkingContent->signature());
|
||||
}
|
||||
|
||||
m_emittedThinkingBlocksCount[requestId] = totalBlocks;
|
||||
}
|
||||
|
||||
void OpenAIResponsesProvider::handleMessageComplete(const QString &requestId)
|
||||
{
|
||||
if (!m_messages.contains(requestId)) {
|
||||
return;
|
||||
}
|
||||
|
||||
OpenAIResponsesMessage *message = m_messages[requestId];
|
||||
|
||||
emitPendingThinkingBlocks(requestId);
|
||||
|
||||
if (message->state() == LLMCore::MessageState::RequiresToolExecution) {
|
||||
const auto toolUseContent = message->getCurrentToolUseContent();
|
||||
|
||||
if (toolUseContent.isEmpty()) {
|
||||
return;
|
||||
}
|
||||
|
||||
for (const auto *toolContent : toolUseContent) {
|
||||
const auto toolStringName = m_toolsManager->toolsFactory()->getStringName(
|
||||
toolContent->name());
|
||||
emit toolExecutionStarted(requestId, toolContent->id(), toolStringName);
|
||||
m_toolsManager->executeToolCall(
|
||||
requestId, toolContent->id(), toolContent->name(), toolContent->input());
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
void OpenAIResponsesProvider::onToolExecutionComplete(
|
||||
const QString &requestId, const QHash<QString, QString> &toolResults)
|
||||
{
|
||||
if (!m_messages.contains(requestId) || !m_requestUrls.contains(requestId)) {
|
||||
LOG_MESSAGE(QString("ERROR: OpenAIResponses - Missing data for continuation request %1")
|
||||
.arg(requestId));
|
||||
cleanupRequest(requestId);
|
||||
return;
|
||||
}
|
||||
|
||||
OpenAIResponsesMessage *message = m_messages[requestId];
|
||||
const auto toolContent = message->getCurrentToolUseContent();
|
||||
|
||||
for (auto it = toolResults.constBegin(); it != toolResults.constEnd(); ++it) {
|
||||
for (const auto *tool : toolContent) {
|
||||
if (tool->id() == it.key()) {
|
||||
const auto toolStringName = m_toolsManager->toolsFactory()->getStringName(
|
||||
tool->name());
|
||||
emit toolExecutionCompleted(
|
||||
requestId, tool->id(), toolStringName, toolResults[tool->id()]);
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
QJsonObject continuationRequest = m_originalRequests[requestId];
|
||||
QJsonArray input = continuationRequest["input"].toArray();
|
||||
|
||||
const QList<QJsonObject> assistantItems = message->toItemsFormat();
|
||||
for (const QJsonObject &item : assistantItems) {
|
||||
input.append(item);
|
||||
}
|
||||
|
||||
const QJsonArray toolResultItems = message->createToolResultItems(toolResults);
|
||||
for (const QJsonValue &item : toolResultItems) {
|
||||
input.append(item);
|
||||
}
|
||||
|
||||
continuationRequest["input"] = input;
|
||||
|
||||
m_dataBuffers[requestId].responseContent.clear();
|
||||
|
||||
sendRequest(requestId, m_requestUrls[requestId], continuationRequest);
|
||||
}
|
||||
|
||||
void OpenAIResponsesProvider::cleanupRequest(const LLMCore::RequestID &requestId)
|
||||
{
|
||||
if (m_messages.contains(requestId)) {
|
||||
OpenAIResponsesMessage *message = m_messages.take(requestId);
|
||||
message->deleteLater();
|
||||
}
|
||||
|
||||
m_dataBuffers.remove(requestId);
|
||||
m_requestUrls.remove(requestId);
|
||||
m_originalRequests.remove(requestId);
|
||||
m_itemIdToCallId.remove(requestId);
|
||||
m_emittedThinkingBlocksCount.remove(requestId);
|
||||
m_toolsManager->cleanupRequest(requestId);
|
||||
return m_client;
|
||||
}
|
||||
|
||||
} // namespace QodeAssist::Providers
|
||||
|
||||
Reference in New Issue
Block a user