Split LLM answer

api/audio.py

@@ -230,4 +230,8 @@ class TTSManager:
         :return: Generator yielding chunks of audio bytes.
         """
         if len(chat_history) > 0 and chat_history[-1][1]:
-            yield from self.read_text(chat_history[-1][1])
+            n = len(chat_history) - 1
+            while n >= 0 and chat_history[n][1]:
+                n -= 1
+            for i in range(n + 1, len(chat_history)):
+                yield from self.read_text(chat_history[i][1])

api/llm.py

@@ -130,12 +130,18 @@ class LLMManager:
         Send a request to the LLM and update the chat display.
         """
         chat_history = self.update_chat_history(code, previous_code, chat_history, chat_display)
-        chat_display.append([None, ""])
+        original_len = len(chat_display)
         chat_history.append({"role": "assistant", "content": ""})
         reply = self.get_text(chat_history)
         for message in reply:
-            chat_display[-1][1] = message.split("#NOTES#")[0].strip()
             chat_history[-1]["content"] = message
+            text_to_display = message.split("#NOTES#")[0].strip()
+            split_messages = text_to_display.split("\n\n")
+            chat_display = chat_display[:original_len]
+            for m in split_messages:
+                if m.strip():
+                    chat_display.append([None, m])
+
             yield chat_history, chat_display, code
 
     def end_interview_prepare_messages(

resources/prompts.py

@@ -27,6 +27,8 @@ You are an AI conducting an interview. Your role is to manage the interview effe
 - Make notes when you encounter: mistakes, bugs, incorrect statements, missed important aspects, any other observations.
 - There should be no other delimiters in your response. Only #NOTES# is a valid delimiter, everything else will be treated just like text.
 
+- If you answer is long add double '\n\n' to split it in smaller logical parts, so it will be easier to read for the candidate.
+
 - You should direct the interview strictly rather than helping the candidate solve the problem.
 - Be very concise in your responses. Allow the candidate to lead the discussion, ensuring they speak more than you do.
 - Never repeat, rephrase, or summarize candidate responses. Never provide feedback during the interview.

ui/coding.py

@@ -110,7 +110,7 @@ def get_problem_solving_ui(llm, tts, stt, default_audio_params, audio_output, na
             outputs=[solution_acc, end_btn, audio_input, send_btn],
         )
 
-        end_btn.click(
+        end_btn.click(fn=lambda x: add_candidate_message("Let's stop here.", x), inputs=[chat], outputs=[chat]).success(
             fn=add_interviewer_message(fixed_messages["end"]),
             inputs=[chat],
             outputs=[chat],