Ensuring pasting of Markdown from Wingman chat dialog (not HTML) #1514

app/src/qt/dialogs/wingman_dialog.h

@@ -142,7 +142,22 @@ class WingmanDialog : public QDialog // TODO rename to WingmanDialog
             cmdEdit->selectAll();
         }
     }
-    std::string getLastAnswer() { return this->lastAnswer; }
+    /**
+     * @brief Get the last answer as a Markdown string.
+     *
+     * The answer is typically pasted or appended to the Note editor,
+     * which uses Markdown format (not HTML), so the answer is converted
+     * to Markdown format.
+     */
+    std::string getLastAnswer() {
+        if(this->lastAnswer.find("<br/>") != std::string::npos) {
+            std::string decodedAnswer{this->lastAnswer};
+            replaceAll("<br/>", "\n", decodedAnswer);
+            return decodedAnswer;
+        }
+
+        return this->lastAnswer;
+    }
 
     QPushButton* getAppendButton() const { return appendButton; }
     QPushButton* getReplaceButton() const { return replaceButton; }

app/src/qt/main_window_presenter.cpp

@@ -2182,7 +2182,7 @@ void MainWindowPresenter::slotRunWingmanFromDialog(bool showDialog)
 
             // PUSH answer to the chat dialog
             this->wingmanDialog->appendAnswerToChat(
-                "Wingman failed to get answer from the GPT provider.<br/><br/>"+commandWingmanChat.answerHtml,
+                "Wingman failed to get answer from the GPT provider.<br/><br/>"+commandWingmanChat.answerMarkdown,
                 "",
                 this->wingmanDialog->getContextType(),
                 true
@@ -2217,7 +2217,7 @@ void MainWindowPresenter::slotRunWingmanFromDialog(bool showDialog)
         );
     } else {
         this->wingmanDialog->appendAnswerToChat(
-            commandWingmanChat.answerHtml,
+            commandWingmanChat.answerMarkdown,
             answerDescriptor,
             this->wingmanDialog->getContextType()
         );

app/src/qt/note_editor_view.cpp

@@ -209,13 +209,15 @@ void NoteEditorView::replaceSelectedText(const std::string& text)
     setTextCursor(cursor);
 }
 
-void NoteEditorView::appendAfterSelectedText(const std::string& phrase) {
+void NoteEditorView::appendAfterSelectedText(const std::string& phrase)
+{
     QTextCursor cursor = textCursor();
     cursor.movePosition(QTextCursor::EndOfBlock);
     cursor.insertText(" " + QString::fromStdString(phrase));
 }
 
-void NoteEditorView::appendAfterCursor(const std::string& phrase) {
+void NoteEditorView::appendAfterCursor(const std::string& phrase)
+{
     textCursor().insertText(QString::fromStdString(phrase));
 }
 

lib/src/mind/ai/llm/mock_wingman.cpp

@@ -41,9 +41,9 @@ void MockWingman::chat(CommandWingmanChat& command) {
     command.answerLlmModel.assign(this->llmModel);
     command.promptTokens=42;
     command.answerTokens=42198;
-    command.answerHtml.assign("chat(MOCK, '"+command.prompt+"')");
+    command.answerMarkdown.assign("chat(MOCK, '"+command.prompt+"')");
 
-    MF_DEBUG("MockWingman::chat() answer:" << command.answerHtml << endl);
+    MF_DEBUG("MockWingman::chat() answer:" << command.answerMarkdown << endl);
 }
 
 } // m8r namespace

lib/src/mind/ai/llm/openai_wingman.cpp

@@ -91,7 +91,10 @@ void OpenAiWingman::curlGet(CommandWingmanChat& command) {
         */
         nlohmann::json messageSystemJSon{};
         messageSystemJSon["role"] = "system"; // system (instruct GPT who it is), user (user prompts), assistant (GPT answers)
-        messageSystemJSon["content"] = "You are a helpful assistant.";
+        messageSystemJSon["content"] =
+            // "You are a helpful assistant that returns HTML-formatted answers to the user's prompts."
+            "You are a helpful assistant."
+            ;
         // ... more messages like above (with chat history) can be created to provide context
         nlohmann::json messageUserJSon{};
         messageUserJSon["role"] = "user";
@@ -218,7 +221,7 @@ void OpenAiWingman::curlGet(CommandWingmanChat& command) {
              "  '" << command.httpResponse << "'" << endl;
 
             command.httpResponse.clear();
-            command.answerHtml.clear();
+            command.answerMarkdown.clear();
             command.answerTokens = 0;
             command.answerLlmModel = llmModel;
 
@@ -266,7 +269,7 @@ void OpenAiWingman::curlGet(CommandWingmanChat& command) {
 
             command.status = WingmanStatusCode::WINGMAN_STATUS_CODE_ERROR;
             command.errorMessage = "Error: unable to parse OpenAI JSon response: '" + command.httpResponse + "'";
-            command.answerHtml.clear();
+            command.answerMarkdown.clear();
             command.answerTokens = 0;
             command.answerLlmModel = llmModel;
 
@@ -303,13 +306,13 @@ void OpenAiWingman::curlGet(CommandWingmanChat& command) {
             if(choice.contains("message")
                 && choice["message"].contains("content")
             ) {
-                choice["message"]["content"].get_to(command.answerHtml);
+                choice["message"]["content"].get_to(command.answerMarkdown);
                 // TODO ask GPT for HTML formatted response
                 m8r::replaceAll(
                     "\n",
                     "<br/>",
-                    command.answerHtml);
-                MF_DEBUG("  answer (HTML): " << command.answerHtml << endl);
+                    command.answerMarkdown);
+                MF_DEBUG("  answer (HTML): " << command.answerMarkdown << endl);
             }
             if(choice.contains("finish_reason")) {
                 string statusStr{};
@@ -321,15 +324,15 @@ void OpenAiWingman::curlGet(CommandWingmanChat& command) {
                     command.errorMessage.assign(
                         "OpenAI API HTTP required failed with finish_reason: "
                         + statusStr);
-                    command.answerHtml.clear();
+                    command.answerMarkdown.clear();
                     command.answerTokens = 0;
                     command.answerLlmModel = llmModel;
                 }
                 MF_DEBUG("  status: " << command.status << endl);
             }
         } else {
             command.status = m8r::WingmanStatusCode::WINGMAN_STATUS_CODE_ERROR;
-            command.answerHtml.clear();
+            command.answerMarkdown.clear();
             command.answerTokens = 0;
             command.answerLlmModel = llmModel;
             if(
@@ -357,7 +360,7 @@ void OpenAiWingman::chat(CommandWingmanChat& command) {
 
     curlGet(command);
 
-    MF_DEBUG("OpenAiWingman::chat() answer:" << endl << command.answerHtml << endl);
+    MF_DEBUG("OpenAiWingman::chat() answer:" << endl << command.answerMarkdown << endl);
 }
 
 } // m8r namespace

lib/src/mind/ai/llm/wingman.h

@@ -71,8 +71,8 @@ enum WingmanStatusCode {
 };
 
 /**
- * Wingman chat request command pattern must be used as asynchronous requests
- * cannot handle that many parameters.
+ * Wingman chat request command pattern must be used as asynchronous requests.
+ * As it annot handle that many parameters this structure is used.
  */
 struct CommandWingmanChat {
     std::string prompt;
@@ -82,7 +82,7 @@ struct CommandWingmanChat {
     std::string answerLlmModel;
     int promptTokens;
     int answerTokens;
-    std::string answerHtml;
+    std::string answerMarkdown;
 };
 
 

lib/test/src/json/json_test.cpp

@@ -74,7 +74,7 @@ TEST(JSonTestCase, ParseOpenAiResponse)
     string answerGptModel{};
     int promptTokens{};
     int answerTokens{};
-    string answerHtml{};
+    string answerMarkdown{};
 
     MF_DEBUG(
         "OpenAiWingman::curlGet() parsed response:" << endl
@@ -106,13 +106,13 @@ TEST(JSonTestCase, ParseOpenAiResponse)
         if(choice.contains("message")
             && choice["message"].contains("content")
         ) {
-            choice["message"]["content"].get_to(answerHtml);
+            choice["message"]["content"].get_to(answerMarkdown);
             // TODO ask GPT for HTML formatted response
             m8r::replaceAll(
                 "\n",
                 "<br/>",
-                answerHtml);
-            MF_DEBUG("  answer (HTML): " << answerHtml << endl);
+                answerMarkdown);
+            MF_DEBUG("  answer (HTML): " << answerMarkdown << endl);
         }
         if(choice.contains("finish_reason")) {
             string statusStr{};
@@ -142,7 +142,7 @@ TEST(JSonTestCase, ParseOpenAiResponse)
         answerGptModel);
     EXPECT_EQ(
         "LLM answer:<br/>42",
-        answerHtml);
+        answerMarkdown);
     EXPECT_EQ(
         m8r::WingmanStatusCode::WINGMAN_STATUS_CODE_OK,
         status);