fix: scope quiz logging and bot status

docker-compose.yml

@@ -37,7 +37,7 @@ services:
       - chroma_data:/app/chroma_data
     networks:
       - default
-      - speech_net
+      - danvics_speech
     depends_on:
       postgres:
         condition: service_healthy
@@ -74,7 +74,7 @@ services:
     env_file:
       - ./telegram-bot/.env
     environment:
-      - DATABASE_URL=postgresql://pedquiz:<password>@postgres:5432/pedquiz
+      - DATABASE_URL=postgresql://pedquiz:${POSTGRES_PASSWORD}@postgres:5432/pedquiz
       - PUBLIC_APP_URL=${APP_URL:-https://pedshub.com}
     depends_on:
       postgres:
@@ -147,5 +147,5 @@ volumes:
   promtail_positions:
 
 networks:
-  speech_net:
+  danvics_speech:
     external: true

promtail/promtail-config.yml

@@ -13,10 +13,14 @@ scrape_configs:
     docker_sd_configs:
       - host: unix:///var/run/docker.sock
         refresh_interval: 5s
+        filters:
+          - name: label
+            values: ["com.docker.compose.project=quiz"]
     relabel_configs:
-      # Keep only quiz-* containers
-      - source_labels: ['__meta_docker_container_name']
-        regex: '.*quiz.*'
+      # Keep only this compose project; the Docker API filter above prevents
+      # Promtail from opening non-readable log streams from other stacks.
+      - source_labels: ['__meta_docker_container_label_com_docker_compose_project']
+        regex: 'quiz'
         action: keep
       # Extract container name as label
       - source_labels: ['__meta_docker_container_name']

telegram-bot/bot.py

@@ -24,7 +24,7 @@ DATABASE_URL = os.environ["DATABASE_URL"]
 DEFAULT_QUIZ_SIZE = int(os.getenv("DEFAULT_QUIZ_SIZE", "20"))
 MAX_QUIZ_SIZE = int(os.getenv("MAX_QUIZ_SIZE", "50"))
 PUBLIC_APP_URL = os.getenv("PUBLIC_APP_URL", "https://pedshub.com").rstrip("/")
-MAX_EXPLANATION_CHARS = int(os.getenv("MAX_EXPLANATION_CHARS", "1800"))
+TELEGRAM_MESSAGE_LIMIT = 4096
 
 LETTERS = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
 NUMBER_RE = re.compile(r"^\s*(\d{1,3})\s*$")
@@ -269,15 +269,56 @@ def truncate_text(value: str, limit: int) -> str:
     return value[:limit].rsplit(" ", 1)[0].rstrip() + "..."
 
 
-def answer_feedback(question: dict[str, Any], chosen_idx: int, correct_idx: int, ok: bool) -> str:
+def answer_feedback_header(chosen_idx: int, correct_idx: int, ok: bool) -> str:
     chosen = LETTERS[chosen_idx] if chosen_idx < len(LETTERS) else "?"
     correct = LETTERS[correct_idx] if correct_idx < len(LETTERS) else "?"
-    explanation = truncate_text(question.get("explanation") or "No explanation available.", MAX_EXPLANATION_CHARS)
-    return "\n".join([
-        "Correct." if ok else f"Incorrect. You chose {chosen}; correct answer: {correct}.",
-        "",
-        f"<b>Explanation:</b> {html.escape(explanation)}",
-    ])
+    return "Correct." if ok else f"Incorrect. You chose {chosen}; correct answer: {correct}."
+
+
+def split_plain_text(text: str, limit: int) -> list[str]:
+    if len(text) <= limit:
+        return [text]
+    chunks = []
+    remaining = text
+    while remaining:
+        if len(remaining) <= limit:
+            chunks.append(remaining)
+            break
+        split_at = remaining.rfind("\n\n", 0, limit)
+        if split_at < limit // 2:
+            split_at = remaining.rfind("\n", 0, limit)
+        if split_at < limit // 2:
+            split_at = remaining.rfind(" ", 0, limit)
+        if split_at < limit // 2:
+            split_at = limit
+        chunks.append(remaining[:split_at].rstrip())
+        remaining = remaining[split_at:].lstrip()
+    return chunks
+
+
+async def send_answer_feedback(
+    context: ContextTypes.DEFAULT_TYPE,
+    chat_id: int,
+    question: dict[str, Any],
+    chosen_idx: int,
+    correct_idx: int,
+    ok: bool,
+) -> None:
+    header = answer_feedback_header(chosen_idx, correct_idx, ok)
+    explanation = (question.get("explanation") or "No explanation available.").strip()
+    first_prefix = f"{header}\n\n<b>Explanation:</b> "
+    next_prefix = "<b>Explanation continued:</b> "
+    first_limit = TELEGRAM_MESSAGE_LIMIT - len(first_prefix) - 200
+    next_limit = TELEGRAM_MESSAGE_LIMIT - len(next_prefix) - 200
+    chunks = split_plain_text(explanation, max(1000, first_limit))
+    for idx, chunk in enumerate(chunks):
+        prefix = first_prefix if idx == 0 else next_prefix
+        if idx > 0 and len(chunk) > next_limit:
+            # First chunk has a smaller budget because it includes answer feedback.
+            for subchunk in split_plain_text(chunk, next_limit):
+                await context.bot.send_message(chat_id, f"{next_prefix}{html.escape(subchunk)}", parse_mode=ParseMode.HTML)
+            continue
+        await context.bot.send_message(chat_id, f"{prefix}{html.escape(chunk)}", parse_mode=ParseMode.HTML)
 
 
 def answered_question_text(state: QuizState, question: dict[str, Any], chosen_idx: int, correct_idx: int) -> str:
@@ -527,7 +568,7 @@ async def callback_handler(update: Update, context: ContextTypes.DEFAULT_TYPE) -
                 answered_question_text(state, question, chosen_idx, correct_idx),
                 parse_mode=ParseMode.HTML,
             )
-            await context.bot.send_message(chat_id, answer_feedback(question, chosen_idx, correct_idx, ok), parse_mode=ParseMode.HTML)
+            await send_answer_feedback(context, chat_id, question, chosen_idx, correct_idx, ok)
         else:
             await query.edit_message_reply_markup(reply_markup=None)
         state.index += 1