feat: Sistema CBCFacil completo con cola secuencial
- Implementa ProcessingMonitor singleton para procesamiento secuencial de archivos - Agrega AI summary service con soporte para MiniMax API - Agrega PDF generator para resúmenes - Agrega watchers para monitoreo de carpeta remota - Mejora sistema de notificaciones Telegram - Implementa gestión de VRAM para GPU - Configuración mediante variables de entorno (sin hardcoded secrets) - .env y transcriptions/ agregados a .gitignore Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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renato97
158
services/ai_summary_service.py
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158
services/ai_summary_service.py
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"""AI Summary Service using Anthropic/Z.AI API (GLM)."""
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import logging
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import os
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from typing import Optional
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import requests
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logger = logging.getLogger(__name__)
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class AISummaryService:
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"""Service for AI-powered text summarization using Anthropic/Z.AI API."""
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def __init__(
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self,
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auth_token: Optional[str] = None,
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base_url: Optional[str] = None,
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model: Optional[str] = None,
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timeout: int = 120,
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) -> None:
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"""Initialize the AI Summary Service.
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Args:
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auth_token: API authentication token. Defaults to ANTHROPIC_AUTH_TOKEN env var.
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base_url: API base URL. Defaults to ANTHROPIC_BASE_URL env var.
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model: Model identifier. Defaults to ANTHROPIC_MODEL env var.
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timeout: Request timeout in seconds. Defaults to 120.
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"""
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self.auth_token = auth_token or os.getenv("ANTHROPIC_AUTH_TOKEN")
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# Normalize base_url: remove /anthropic suffix if present
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raw_base_url = base_url or os.getenv("ANTHROPIC_BASE_URL")
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if raw_base_url and raw_base_url.endswith("/anthropic"):
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raw_base_url = raw_base_url[:-len("/anthropic")]
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self.base_url = raw_base_url
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self.model = model or os.getenv("ANTHROPIC_MODEL", "glm-4")
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self.timeout = timeout
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self._available = bool(self.auth_token and self.base_url)
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if self._available:
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logger.info(
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"AISummaryService initialized with model=%s, base_url=%s",
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self.model,
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self.base_url,
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)
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else:
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logger.debug("AISummaryService: no configuration found, running in silent mode")
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@property
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def is_available(self) -> bool:
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"""Check if the service is properly configured."""
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return self._available
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def summarize(self, text: str, prompt_template: Optional[str] = None) -> str:
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"""Summarize the given text using the AI API.
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Args:
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text: The text to summarize.
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prompt_template: Optional custom prompt template. If None, uses default.
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Returns:
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The summarized text.
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Raises:
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RuntimeError: If the service is not configured.
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requests.RequestException: If the API call fails.
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"""
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if not self._available:
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logger.debug("AISummaryService not configured, returning original text")
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return text
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default_prompt = "Resume el siguiente texto de manera clara y concisa:"
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prompt = prompt_template.format(text=text) if prompt_template else f"{default_prompt}\n\n{text}"
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payload = {
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"model": self.model,
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"messages": [{"role": "user", "content": prompt}],
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"max_tokens": 2048,
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"temperature": 0.7,
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}
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headers = {
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"Authorization": f"Bearer {self.auth_token}",
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"Content-Type": "application/json",
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}
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try:
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logger.debug("Calling AI API for summarization (text length: %d)", len(text))
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response = requests.post(
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f"{self.base_url}/v1/chat/completions",
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json=payload,
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headers=headers,
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timeout=self.timeout,
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)
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response.raise_for_status()
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result = response.json()
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summary = result.get("choices", [{}])[0].get("message", {}).get("content", "")
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logger.info("Summarization completed successfully (output length: %d)", len(summary))
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return summary
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except requests.Timeout:
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logger.error("AI API request timed out after %d seconds", self.timeout)
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raise requests.RequestException(f"Request timed out after {self.timeout}s") from None
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except requests.RequestException as e:
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logger.error("AI API request failed: %s", str(e))
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raise
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def fix_latex(self, text: str) -> str:
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"""Fix LaTeX formatting issues in the given text.
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Args:
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text: The text containing LaTeX to fix.
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Returns:
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The text with corrected LaTeX formatting.
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"""
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if not self._available:
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logger.debug("AISummaryService not configured, returning original text")
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return text
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prompt = (
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"Corrige los errores de formato LaTeX en el siguiente texto. "
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"Mantén el contenido pero corrige la sintaxis de LaTeX:\n\n"
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f"{text}"
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)
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payload = {
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"model": self.model,
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"messages": [{"role": "user", "content": prompt}],
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"max_tokens": 4096,
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"temperature": 0.3,
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}
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headers = {
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"Authorization": f"Bearer {self.auth_token}",
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"Content-Type": "application/json",
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}
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try:
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logger.debug("Calling AI API for LaTeX fixing (text length: %d)", len(text))
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response = requests.post(
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f"{self.base_url}/v1/chat/completions",
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json=payload,
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headers=headers,
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timeout=self.timeout,
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)
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response.raise_for_status()
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result = response.json()
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fixed = result.get("choices", [{}])[0].get("message", {}).get("content", "")
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logger.info("LaTeX fixing completed successfully")
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return fixed
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except requests.RequestException as e:
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logger.error("LaTeX fixing failed: %s", str(e))
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return text
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