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Merged
Afdaan merged 2 commits into from
Mar 15, 2026
Merged

feat: add animated loading placeholder for AI response generation #43

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e858c7d
feat: Add animated loading UI and edit responses
Afdaan Mar 12, 2026
102aac8
feat: centralize loading animations in helpers
Afdaan Mar 15, 2026
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184 changes: 106 additions & 78 deletions handlers/conversation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -87,10 +87,16 @@ def _create_or_update_user(self, user) -> bool:
)
return is_admin

async def _send_error_response(self, update: Update, username: str, lang: str) -> None:
async def _send_error_response(self, update: Update, username: str, lang: str, loading_msg: Optional[Any] = None) -> None:
error_message = self.persona.get_error_message(username=username or "user", lang=lang)
formatted_error = format_error_response(error_message)
await update.message.reply_html(formatted_error)
if loading_msg:
try:
await loading_msg.edit_text(formatted_error, parse_mode="HTML")
except Exception:
await update.message.reply_html(formatted_error)
else:
await update.message.reply_html(formatted_error)

async def chat_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
user = update.effective_user
Expand Down Expand Up @@ -150,85 +156,99 @@ async def chat_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE)
self.memory.save_user_message(user.id, query)
self.context_manager.apply_sliding_window(user.id)

message_context = {}
if FEATURES.get("emotion_detection", False) and self.nlp:
message_context = self.nlp.get_message_context(query, user.id)
logger.debug(f"Message context for user {user.id}: {message_context}")

affection_delta = 0
if message_context:
affection_delta = self._calculate_affection_delta(user.id, message_context)

# === STEP 3: Get current mood and calculate new mood ===
mood_manager = MoodManager()

current_mood_data = self.db.get_user_mood(user.id)
user_info = self.db.get_user_relationship_info(user.id)

new_mood_state = mood_manager.calculate_mood(
current_mood=current_mood_data["mood"],
current_intensity=current_mood_data["intensity"],
affection_delta=affection_delta,
emotion_context=message_context,
relationship_level=user_info["relationship_level"],
last_mood_change=current_mood_data["last_change"]
)

# === STEP 4: Apply mood modifier to affection delta ===
mood_modifier = mood_manager.get_affection_modifier(
new_mood_state.mood,
affection_delta
)
modified_affection_delta = int(affection_delta * mood_modifier)

logger.info(
f"[MOOD] User {user.id}: {current_mood_data['mood']} → {new_mood_state.mood} "
f"(intensity: {new_mood_state.intensity}) | "
f"Affection: {affection_delta} → {modified_affection_delta} (×{mood_modifier:.1f})"
)

# === STEP 5: Update affection with mood-modified delta ===
if modified_affection_delta != 0:
self.db.update_affection(user.id, modified_affection_delta)

# === STEP 6: Update mood in database ===
updated_history = mood_manager.add_to_mood_history(
current_mood_data["history"],
new_mood_state
)
self.db.update_user_mood(
user.id,
new_mood_state.mood,
new_mood_state.intensity,
updated_history
)

# === STEP 7: Increment interaction count (will recalculate level) ===
self.db.increment_interaction_count(user.id)
# Send initial loading message
phrase = "Alya is thinking" if lang == "en" else "Alya lagi mikir"
loading_msg = await update.message.reply_text(f"<blockquote><b>💭 {phrase}...</b></blockquote>", parse_mode="HTML")

from utils.telegram_helpers import start_loading_animation
loading_task = start_loading_animation(loading_msg, phrase)

# Prepare context with LATEST relationship level and MOOD
user_context = await self._prepare_conversation_context(
user, query, lang, message_context, new_mood_state, mood_manager
)
response = await self.gemini.generate_response(
user_id=user.id,
username=user.first_name or "user",
message=user_context["enhanced_query"],
context=user_context["system_prompt"],
relationship_level=user_context["relationship_level"],
is_admin=user.id in ADMIN_IDS or self.db.is_admin(user.id),
lang=lang,
retry_count=3,
is_media_analysis=False,
media_context=None
)
try:
message_context = {}
if FEATURES.get("emotion_detection", False) and self.nlp:
message_context = self.nlp.get_message_context(query, user.id)
logger.debug(f"Message context for user {user.id}: {message_context}")

affection_delta = 0
if message_context:
affection_delta = self._calculate_affection_delta(user.id, message_context)

# === STEP 3: Get current mood and calculate new mood ===
mood_manager = MoodManager()

current_mood_data = self.db.get_user_mood(user.id)
user_info = self.db.get_user_relationship_info(user.id)

new_mood_state = mood_manager.calculate_mood(
current_mood=current_mood_data["mood"],
current_intensity=current_mood_data["intensity"],
affection_delta=affection_delta,
emotion_context=message_context,
relationship_level=user_info["relationship_level"],
last_mood_change=current_mood_data["last_change"]
)

# === STEP 4: Apply mood modifier to affection delta ===
mood_modifier = mood_manager.get_affection_modifier(
new_mood_state.mood,
affection_delta
)
modified_affection_delta = int(affection_delta * mood_modifier)

logger.info(
f"[MOOD] User {user.id}: {current_mood_data['mood']} → {new_mood_state.mood} "
f"(intensity: {new_mood_state.intensity}) | "
f"Affection: {affection_delta} → {modified_affection_delta} (×{mood_modifier:.1f})"
)

# === STEP 5: Update affection with mood-modified delta ===
if modified_affection_delta != 0:
self.db.update_affection(user.id, modified_affection_delta)

# === STEP 6: Update mood in database ===
updated_history = mood_manager.add_to_mood_history(
current_mood_data["history"],
new_mood_state
)
self.db.update_user_mood(
user.id,
new_mood_state.mood,
new_mood_state.intensity,
updated_history
)

# === STEP 7: Increment interaction count (will recalculate level) ===
self.db.increment_interaction_count(user.id)

# Prepare context with LATEST relationship level and MOOD
user_context = await self._prepare_conversation_context(
user, query, lang, message_context, new_mood_state, mood_manager
)
response = await self.gemini.generate_response(
user_id=user.id,
username=user.first_name or "user",
message=user_context["enhanced_query"],
context=user_context["system_prompt"],
relationship_level=user_context["relationship_level"],
is_admin=user.id in ADMIN_IDS or self.db.is_admin(user.id),
lang=lang,
retry_count=3,
is_media_analysis=False,
media_context=None
)
finally:
loading_task.cancel()
try:
await loading_task
except asyncio.CancelledError:
pass

if response:
logger.info(f"[RESPONSE_RECEIVED] Got response from Gemini, length={len(response)}")
await self._process_and_send_response(update, user, response, user_context["message_context"], lang)
await self._process_and_send_response(update, user, response, user_context["message_context"], lang, loading_msg=loading_msg)
else:
logger.warning(f"[RESPONSE_RECEIVED] Response is empty or None")
await self._send_error_response(update, user.first_name, lang)
await self._send_error_response(update, user.first_name, lang, loading_msg=loading_msg)
except Exception as e:
logger.error(f"Error in chat command: {e}", exc_info=True)
await self._send_error_response(update, user.first_name, lang)
Expand Down Expand Up @@ -489,7 +509,8 @@ async def _process_and_send_response(
user,
response: str,
message_context: Dict[str, Any],
lang: str
lang: str,
loading_msg: Optional[Any] = None
) -> None:
"""Clean, format, and send response to Telegram."""
try:
Expand All @@ -506,10 +527,17 @@ async def _process_and_send_response(
formatted_response = format_persona_response(response, use_html=True)
formatted_response = f"{formatted_response}\u200C"

await update.message.reply_html(formatted_response)
if loading_msg:
try:
await loading_msg.edit_text(formatted_response, parse_mode="HTML")
except Exception as e:
logger.error(f"Failed to edit message: {e}")
await update.message.reply_html(formatted_response)
else:
await update.message.reply_html(formatted_response)
except Exception as e:
logger.error(f"Error processing response: {e}", exc_info=True)
await self._send_error_response(update, user.first_name, lang)
await self._send_error_response(update, user.first_name, lang, loading_msg=loading_msg)

def _clean_and_append_russian_translation(self, response: str, lang: str = DEFAULT_LANGUAGE) -> str:
"""Extract and translate Russian expressions (both marked and unmarked)."""
Expand Down
62 changes: 48 additions & 14 deletions handlers/voice.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -124,6 +124,13 @@ async def handle_voice_message(self, update: Update, context: ContextTypes.DEFAU
lang_flag = {"en": "🇺🇸", "id": "🇮🇩", "jp": "🎌"}.get(detected_lang, "🌐")
await update.message.reply_html(f"🎤 <i>({lang_flag} {detected_lang.upper()}): {user_text}</i>")

import asyncio
phrase = "Alya is thinking" if db_user_dict.get('language_code', DEFAULT_LANGUAGE) == 'en' else "Alya lagi mikir"
loading_msg = await update.message.reply_text(f"<blockquote><b>💭 {phrase}...</b></blockquote>", parse_mode="HTML")

from utils.telegram_helpers import start_loading_animation
loading_task = start_loading_animation(loading_msg, phrase)

# 2. Memory & Relationship Updates
self.db_manager.save_message(user.id, "user", user_text)
if self.memory_manager:
Expand All @@ -148,36 +155,62 @@ async def handle_voice_message(self, update: Update, context: ContextTypes.DEFAU
# Clean format: [Role] Content
history_text = "\n".join([f"[{msg['role'].capitalize()}] {msg['content']}" for msg in history])

response = await self.gemini_client.generate_response(
user_id=user.id,
username=user.first_name or "user",
message=user_text,
context=self.persona_manager.get_chat_prompt(
username=user.first_name,
try:
response = await self.gemini_client.generate_response(
user_id=user.id,
username=user.first_name or "user",
message=user_text,
context=history_text,
context=self.persona_manager.get_chat_prompt(
username=user.first_name,
message=user_text,
context=history_text,
relationship_level=rel_level,
is_admin=is_admin,
lang=db_user_dict.get('language_code', DEFAULT_LANGUAGE)
),
relationship_level=rel_level,
is_admin=is_admin,
lang=db_user_dict.get('language_code', DEFAULT_LANGUAGE)
),
relationship_level=rel_level,
is_admin=is_admin,
lang=db_user_dict.get('language_code', DEFAULT_LANGUAGE)
)
)
finally:
loading_task.cancel()
try:
await loading_task
except asyncio.CancelledError:
pass

if not response:
await update.message.reply_html("❌ Gagal mendapatkan respon dari Alya...")
error_msg = "❌ Gagal mendapatkan respon dari Alya..."
try:
await loading_msg.edit_text(error_msg, parse_mode="HTML")
except Exception:
await update.message.reply_html(error_msg)
return

ui_text = format_persona_response(response, use_html=True) + "\u200C"
await update.message.reply_html(ui_text)
try:
await loading_msg.edit_text(ui_text, parse_mode="HTML")
except Exception:
await update.message.reply_html(ui_text)

voice_lang = self.db_manager.get_user_voice_language(user.id) if self.db_manager else "en"
source_lang = db_user_dict.get('language_code', DEFAULT_LANGUAGE)

# Extract dialogue and translate to voice_lang before sending to TTS
tts_text = await translate_response_for_voice(response, source_lang, voice_lang)

import asyncio
tts_phrase = "Alya is recording a voice note" if source_lang == 'en' else "Alya lagi ngerekam voice note"
tts_loading_msg = await update.message.reply_text(f"<blockquote><b>🎙️ {tts_phrase}...</b></blockquote>", parse_mode="HTML")

from utils.telegram_helpers import start_loading_animation
tts_loading_task = start_loading_animation(
tts_loading_msg,
tts_phrase,
frames=["🎙️", "🎶", "✨"],
interval=1.2
)

await dispatch_tts(
bot=context.bot,
chat_id=update.effective_chat.id,
Expand All @@ -186,6 +219,7 @@ async def handle_voice_message(self, update: Update, context: ContextTypes.DEFAU
response_text=tts_text,
voice_lang=voice_lang,
user_lang=source_lang,
loading_message_id=tts_loading_msg.message_id
)

# 5. Metadata Update
Expand Down
30 changes: 23 additions & 7 deletions utils/analyze.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,5 +1,6 @@
import io
import logging
import asyncio
from pathlib import Path
from typing import Dict, Any, Optional, Union, BinaryIO

Expand Down Expand Up @@ -241,12 +242,15 @@ async def handle_analysis_command(update: Update, context: ContextTypes.DEFAULT_
await message.reply_html(analyze_response(lang))
return

# If no query specified for media, use default
lang = get_user_lang(user.id)
if not query and media_type != "text":
lang = get_user_lang(user.id)
query = "Analyze this for me, please." if lang == 'en' else "Tolong analisis ini."

await context.bot.send_chat_action(chat_id=update.effective_chat.id, action=ChatAction.TYPING)
phrase = "Alya is analyzing" if lang == 'en' else "Alya sedang menganalisis"
loading_msg = await message.reply_text(f"<blockquote><b>🔍 {phrase}...</b></blockquote>", parse_mode="HTML")

from utils.telegram_helpers import start_loading_animation
loading_task = start_loading_animation(loading_msg, phrase, frames=["🔍", "🧐", "✨"])

try:
result = await analyzer.analyze_media(
Expand All @@ -263,14 +267,26 @@ async def handle_analysis_command(update: Update, context: ContextTypes.DEFAULT_
lang=lang,
username=user.first_name
)

finally:
loading_task.cancel()
try:
await loading_task
except asyncio.CancelledError:
pass

try:
# Handle if result is a list (long message split)
if isinstance(formatted_result, list):
for part in formatted_result:
await loading_msg.edit_text(formatted_result[0], parse_mode='HTML', disable_web_page_preview=True)
for part in formatted_result[1:]:
await message.reply_html(part, disable_web_page_preview=True)
else:
await message.reply_html(formatted_result, disable_web_page_preview=True)
await loading_msg.edit_text(formatted_result, parse_mode='HTML', disable_web_page_preview=True)
except Exception as e:
logger.error(f"Failed to handle analysis command for user {user.id}: {e}", exc_info=True)
lang = get_user_lang(user.id)
await message.reply_html(get_system_error_response(lang))
error_response = get_system_error_response(lang)
try:
await loading_msg.edit_text(error_response, parse_mode='HTML')
except Exception:
await message.reply_html(error_response)
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