Fix storing of response - now deque both

app/api.py

@@ -383,8 +383,8 @@ def get_voice_status():
     # 2. Вызываем метод у экземпляра voice_inst, а не у модуля
     return jsonify({
         "transcription": voice_inst.get_context_by_limit(3000, order='reversed'),
-        "response1": voice_inst.responses["regular"],
-        "response2": voice_inst.responses["commands"][:VOICE_COMMANDS_RESPONSE_TO_STORE],
+        "response1": list(voice_inst.responses["regular"]),
+        "response2": list(voice_inst.responses["commands"]),
         "is_running": voice_inst.is_running,
         "obsidian_settings_fetched": obsidian_settings_fetched
     })

app/title_generator.py

@@ -9,7 +9,7 @@ import time
 from typing import Any, Dict, Optional
 from llm_client import get_llm
 from langchain_core.messages import SystemMessage, HumanMessage
-import os
+import uuid
 
 DEFAULT_SUMMARIZATION_LLM_NAME = "gemini-2.0-flash-lite" # "mistral-small-latest" # "mistral-small-latest" #"gemini-2.0-flash-r"
 DEFAULT_VOICE_LLM_NAME = "gemini-2.0-flash-lite" # "gemini-3.0-flash-openrouter"
@@ -385,7 +385,13 @@ class TitleGenerator:
             response = self.voice_llm.invoke(llm_messages)
             
             import app.api as api
-            api.voice_inst.responses["regular"] = response # Записываем в Response 1
+            new_entry = {
+                "id": str(uuid.uuid4()),
+                "content": response
+            }
+            # Используем appendleft для автоматического управления размером deque
+            api.voice_inst.responses["regular"].appendleft(new_entry)
+
             print(f"✅🎤 Регулярный анализ голосового ввода завершен.")
         except Exception as e:
             print(f"❌🎤 Ошибка регулярного анализа: {e}")
@@ -401,14 +407,14 @@ class TitleGenerator:
             response = self.voice_llm.invoke(llm_messages)
             
             import app.api as api
-            # Форматируем для вкладки Response 2
-            formatted_res = f"<b>Команда:</b> {text}<br><b>Ответ:</b> {response}"
-            api.voice_inst.responses["commands"].insert(0, formatted_res)
-            
-            # Ограничиваем историю команд, чтобы не раздувать память
-            if len(api.voice_inst.responses["commands"]) > VOICE_COMMANDS_RESPONSE_TO_STORE:
-                api.voice_inst.responses["commands"].pop(0)
-                
+            # Форматируем как Markdown для рендеринга на фронте
+            markdown_content = f"**Команда:** {text}\n\n**Ответ:** {response}"
+            new_entry = {
+                "id": str(uuid.uuid4()),
+                "content": markdown_content
+            }
+            api.voice_inst.responses["commands"].appendleft(new_entry)
+
             print(f"✅🎤 Голосовая команда обработана.")
         except Exception as e:
-            print(f"❌🎤 Ошибка обработки команды: {e}") 
+            print(f"❌🎤 Ошибка обработки команды: {e}")

app/voice_service.py

@@ -6,9 +6,10 @@ import time
 import numpy as np
 from vosk import Model, KaldiRecognizer
 import sounddevice as sd
+import uuid
 from collections import deque
 
-VOICE_COMMANDS_RESPONSE_TO_STORE = 15
+VOICE_COMMANDS_RESPONSE_TO_STORE = 3
 
 class VoiceService:
     def __init__(self, model_path, samplerate=48000):
@@ -20,7 +21,10 @@ class VoiceService:
         self.history = []
         self.history_lock = threading.Lock()
         self.last_processed_timestamp = 0.0
-        self.responses = {"regular": "", "commands": []}
+        self.responses = {
+            "regular": deque(maxlen=VOICE_COMMANDS_RESPONSE_TO_STORE), 
+            "commands": deque(maxlen=VOICE_COMMANDS_RESPONSE_TO_STORE)
+        }
         self.lock = threading.Lock()
         self._stop_event = threading.Event()