feat: modo diff para /watch — notifica solo si hay novedades reales
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+39
-3
@@ -73,7 +73,8 @@ async def send_chunked(message: Message, text: str, parse_mode=None):
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async def run_scheduled_research(bot, chat_id: int, topic: str,
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session_id: int, db: ResearchDB,
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progress_message=None):
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progress_message=None,
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silent_completion: bool = False):
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if progress_message is not None:
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reporter = ProgressReporter(progress_message)
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else:
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@@ -106,6 +107,11 @@ async def run_scheduled_research(bot, chat_id: int, topic: str,
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await processor.process_session(session_id, topic, proc_progress)
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chunk_count = await db.get_chunks_count(session_id)
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if silent_completion:
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await reporter.done(
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f"🔍 Investigación completada — analizando novedades…"
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)
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else:
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await reporter.done(
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f"✅ Listo — `{scraped}` fuentes · `{chunk_count}` chunks · usa /generate <tipo>"
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)
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@@ -726,11 +732,41 @@ async def _scheduler_loop(app: Application):
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_active_sessions[chat_id] = session_id
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await db.update_watch_run(watch["id"])
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async def _task(c=chat_id, t=topic, s=session_id):
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async def _task(c=chat_id, t=topic, s=session_id, w_id=watch["id"]):
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inner_db_conn = await get_db()
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inner_db = ResearchDB(inner_db_conn)
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try:
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await run_scheduled_research(app.bot, c, t, s, inner_db)
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await run_scheduled_research(app.bot, c, t, s, inner_db,
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silent_completion=True)
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prev_session = await inner_db.get_previous_session(c, t, s)
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new_urls = await inner_db.get_session_urls(s)
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old_urls = await inner_db.get_session_urls(prev_session["id"]) \
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if prev_session else set()
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new_chunks = await inner_db.get_top_chunks(s, limit=30)
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try:
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from src.generator.generator import generate_diff_summary
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summary = await generate_diff_summary(
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t, new_urls, old_urls, new_chunks, s, inner_db
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)
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except Exception as e:
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logger.warning("Diff summary failed", error=str(e))
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summary = (
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f"📊 *Actualización disponible — {t}*\n\n"
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f"Usa /generate report para ver el análisis completo."
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)
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if summary:
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await app.bot.send_message(
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c, summary, parse_mode=ParseMode.MARKDOWN
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)
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else:
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await app.bot.send_message(
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c,
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f"🔄 *{t}* — sin novedades significativas esta vez.",
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parse_mode=ParseMode.MARKDOWN
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)
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finally:
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await inner_db_conn.close()
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@@ -159,6 +159,27 @@ class ResearchDB:
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row = await cursor.fetchone()
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return dict(row) if row else None
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async def get_session_urls(self, session_id: int) -> set:
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async with self.db.execute(
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"SELECT url FROM sources WHERE session_id = ?", (session_id,)
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) as cur:
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rows = await cur.fetchall()
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return {r[0] for r in rows}
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async def get_previous_session(self, chat_id: int, topic: str,
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exclude_session_id: int) -> Optional[dict]:
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async with self.db.execute(
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"""SELECT id, topic, status, created_at FROM research_sessions
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WHERE telegram_chat_id = ? AND topic = ? AND id != ?
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ORDER BY created_at DESC LIMIT 1""",
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(chat_id, topic, exclude_session_id)
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) as cur:
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row = await cur.fetchone()
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if not row:
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return None
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return {"id": row[0], "topic": row[1],
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"status": row[2], "created_at": row[3]}
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async def get_active_session(self, chat_id: int) -> Optional[dict]:
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cursor = await self.db.execute(
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"""SELECT * FROM research_sessions
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@@ -574,3 +574,82 @@ def generate_pdf(content: str, title: str = "ResearchOwl Output") -> bytes:
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doc.build(story)
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return buf.getvalue()
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async def generate_diff_summary(
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topic: str,
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new_urls: set,
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old_urls: set,
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new_chunks: list,
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session_id: int,
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db,
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) -> str | None:
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from src.config import settings
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import structlog
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diff_logger = structlog.get_logger()
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added_urls = new_urls - old_urls
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pct_new = len(added_urls) / max(len(new_urls), 1)
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diff_logger.info("Diff analysis", topic=topic,
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new_urls=len(new_urls), old_urls=len(old_urls),
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added=len(added_urls), pct_new=round(pct_new, 2))
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if pct_new < 0.20 and len(added_urls) < 5:
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diff_logger.info("Diff: no significant new sources", topic=topic)
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return None
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if not new_chunks:
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return None
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context = "\n\n---\n\n".join(
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f"[{c.get('source_type', 'web').upper()}] {c.get('title', '')}\n{c['content'][:400]}"
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for c in new_chunks[:20]
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)
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if not settings.anthropic_api_key:
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return (
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f"📊 *Novedades detectadas sobre {topic}*\n\n"
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f"• {len(added_urls)} fuentes nuevas encontradas\n"
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f"• {len(new_chunks)} chunks de contenido procesados\n\n"
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f"Usa /generate report para ver el análisis completo."
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)
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try:
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import anthropic
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client = anthropic.AsyncAnthropic(api_key=settings.anthropic_api_key)
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prompt = (
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f'Analiza el siguiente material de investigación sobre "{topic}" '
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f'y genera un resumen BREVE (máximo 300 palabras) de las novedades '
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f'más importantes encontradas. Escribe en español.\n\n'
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f'Si el contenido es muy similar a investigaciones anteriores o no '
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f'contiene información genuinamente nueva, responde SOLO con: '
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f'"SIN_NOVEDADES"\n\n'
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f'Material nuevo:\n{context}'
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)
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msg = await client.messages.create(
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model=settings.claude_model,
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max_tokens=500,
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messages=[{"role": "user", "content": prompt}]
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)
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summary = msg.content[0].text.strip()
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if summary == "SIN_NOVEDADES":
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diff_logger.info("Diff: Claude found no new information", topic=topic)
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return None
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try:
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await db.log_api_call(session_id, "diff", settings.claude_model,
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msg.usage.input_tokens, msg.usage.output_tokens)
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except Exception:
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pass
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return f"🔔 *Novedades — {topic}*\n\n{summary}\n\nUsa /generate para report completo."
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except Exception as e:
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diff_logger.warning("Diff summary generation failed", error=str(e))
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return (
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f"📊 *Actualización — {topic}*\n\n"
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f"• {len(added_urls)} fuentes nuevas\n"
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f"Usa /generate report para ver el análisis completo."
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)
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