cbc2027/document/generators.py

"""
Document generation utilities
"""

import logging
import re
from pathlib import Path
from typing import Dict, Any, List, Tuple
from core import FileProcessingError
from config import settings
from services.ai import ai_provider_factory


class DocumentGenerator:
    """Generate documents from processed text"""

    def __init__(self):
        self.logger = logging.getLogger(__name__)
        self.ai_provider = ai_provider_factory.get_best_provider()

    def generate_summary(
        self, text: str, base_name: str
    ) -> Tuple[bool, str, Dict[str, Any]]:
        """Generate unified summary"""
        self.logger.info(f"Generating summary for {base_name}")

        try:
            # Step 1: Generate Bullet Points (Chunking handled by provider or single prompt for now)
            # Note: We use the main provider (Claude/Zai) for content generation
            self.logger.info("Generating bullet points...")
            bullet_prompt = f"""Analiza el siguiente texto y extrae entre 5 y 8 bullet points clave en español.

REGLAS ESTRICTAS:
1. Devuelve ÚNICAMENTE bullet points, cada línea iniciando con "- "
2. Cada bullet debe ser conciso (12-20 palabras) y resaltar datos, fechas, conceptos o conclusiones importantes
3. NO agregues introducciones, conclusiones ni texto explicativo
4. Concéntrate en los puntos más importantes del texto
5. Incluye fechas, datos específicos y nombres relevantes si los hay

Texto:
{text[:15000]}"""  # Truncate to avoid context limits if necessary, though providers handle it differently

            try:
                bullet_points = self.ai_provider.generate_text(bullet_prompt)
                self.logger.info(f"Bullet points generated: {len(bullet_points)}")
            except Exception as e:
                self.logger.warning(f"Bullet point generation failed: {e}")
                bullet_points = "- Puntos clave no disponibles por error en IA"

            # Step 2: Generate Unified Summary
            self.logger.info("Generating unified summary...")
            summary_prompt = f"""Eres un profesor universitario experto en historia del siglo XX. Redacta un resumen académico integrado en español usando el texto y los bullet points extraídos.

REQUISITOS ESTRICTOS:
- Extensión entre 500-700 palabras
- Usa encabezados Markdown con jerarquía clara (##, ###)
- Desarrolla los puntos clave con profundidad y contexto histórico
- Mantén un tono académico y analítico
- Incluye conclusiones significativas
- NO agregues texto fuera del resumen
- Devuelve únicamente el resumen en formato Markdown

Contenido a resumir:
{text[:20000]}

Puntos clave a incluir obligatoriamente:
{bullet_points}"""

            try:
                raw_summary = self.ai_provider.generate_text(summary_prompt)
            except Exception as e:
                self.logger.error(f"Raw summary generation failed: {e}")
                raise e

            # Step 3: Format with Gemini (using GeminiProvider explicitly)
            self.logger.info("Formatting summary with Gemini...")
            format_prompt = f"""Revisa y mejora el siguiente resumen en Markdown para que sea perfectamente legible:

{raw_summary}

Instrucciones:
- Corrige cualquier error de formato
- Asegúrate de que los encabezados estén bien espaciados
- Verifica que las viñetas usen "- " correctamente
- Mantén exactamente el contenido existente
- EVITA el uso excesivo de negritas (asteriscos), úsalas solo para conceptos clave
- Devuelve únicamente el resumen formateado sin texto adicional"""

            # Use generic Gemini provider for formatting as requested
            from services.ai.gemini_provider import GeminiProvider

            formatter = GeminiProvider()

            try:
                if formatter.is_available():
                    summary = formatter.generate_text(format_prompt)
                else:
                    self.logger.warning(
                        "Gemini formatter not available, using raw summary"
                    )
                    summary = raw_summary
            except Exception as e:
                self.logger.warning(f"Formatting failed ({e}), using raw summary")
                summary = raw_summary

            # Generate filename
            filename = self._generate_filename(text, summary)

            # Create document
            markdown_path = self._create_markdown(summary, base_name)
            docx_path = self._create_docx(summary, base_name)
            pdf_path = self._create_pdf(summary, base_name)

            # Upload to Notion if configured
            from services.notion_service import notion_service

            notion_uploaded = False
            notion_page_id = None
            if settings.has_notion_config:
                try:
                    title = base_name.replace("_", " ").title()

                    # Crear página con el contenido completo del resumen
                    notion_metadata = {
                        "file_type": "Audio",  # O 'PDF' dependiendo del origen
                        "pdf_path": pdf_path,
                        "add_status": False,  # No usar Status/Tipo (no existen en la DB)
                        "use_as_page": False,  # Usar como database, no página
                    }

                    notion_page_id = notion_service.create_page_with_summary(
                        title=title, summary=summary, metadata=notion_metadata
                    )

                    if notion_page_id:
                        notion_uploaded = True
                        self.logger.info(
                            f"✅ Resumen subido a Notion: {title} (ID: {notion_page_id})"
                        )
                    else:
                        self.logger.warning(f"⚠️ No se pudo subir a Notion: {title}")
                except Exception as e:
                    self.logger.warning(f"❌ Error al subir a Notion: {e}")
                    import traceback

                    traceback.print_exc()
            else:
                self.logger.info("Notion not configured - skipping upload")

            metadata = {
                "markdown_path": str(markdown_path),
                "docx_path": str(docx_path),
                "pdf_path": str(pdf_path),
                "docx_name": Path(docx_path).name,
                "summary": summary,
                "filename": filename,
                "notion_uploaded": notion_uploaded,
                "notion_page_id": notion_page_id,
            }

            return True, summary, metadata

        except Exception as e:
            self.logger.error(f"Document generation process failed: {e}")
            return False, "", {}

    def _generate_filename(self, text: str, summary: str) -> str:
        """Generate intelligent filename"""
        try:
            # Use AI to extract key topics
            prompt = f"""Extract 2-3 key topics from this summary to create a filename.
Summary: {summary}

Return only the topics separated by hyphens, max 20 chars each, in Spanish:"""

            topics_text = (
                self.ai_provider.sanitize_input(prompt)
                if hasattr(self.ai_provider, "sanitize_input")
                else summary[:100]
            )

            # Simple topic extraction
            topics = re.findall(r"\b[A-ZÁÉÍÓÚÑ][a-záéíóúñ]+\b", topics_text)[:3]
            if not topics:
                topics = ["documento"]

            # Limit topic length
            topics = [t[: settings.MAX_FILENAME_TOPICS_LENGTH] for t in topics]

            filename = "_".join(topics)[: settings.MAX_FILENAME_LENGTH]
            return filename

        except Exception as e:
            self.logger.error(f"Filename generation failed: {e}")
            return base_name[: settings.MAX_FILENAME_BASE_LENGTH]

    def _create_markdown(self, summary: str, base_name: str) -> Path:
        """Create Markdown document"""
        output_dir = settings.LOCAL_DOWNLOADS_PATH
        output_dir.mkdir(parents=True, exist_ok=True)

        output_path = output_dir / f"{base_name}_unificado.md"

        content = f"""# {base_name.replace("_", " ").title()}

## Resumen

{summary}

---

*Generado por CBCFacil*
"""

        with open(output_path, "w", encoding="utf-8") as f:
            f.write(content)

        return output_path

    def _create_docx(self, summary: str, base_name: str) -> Path:
        """Create DOCX document with Markdown parsing (Legacy method ported)"""
        try:
            from docx import Document
            from docx.shared import Inches
        except ImportError:
            raise FileProcessingError("python-docx not installed")

        output_dir = settings.LOCAL_DOCX
        output_dir.mkdir(parents=True, exist_ok=True)

        output_path = output_dir / f"{base_name}_unificado.docx"

        doc = Document()
        doc.add_heading(base_name.replace("_", " ").title(), 0)

        # Parse and render Markdown content line by line
        lines = summary.splitlines()
        current_paragraph = []

        for line in lines:
            line = line.strip()
            if not line:
                if current_paragraph:
                    p = doc.add_paragraph(" ".join(current_paragraph))
                    p.alignment = 3  # JUSTIFY alignment (WD_ALIGN_PARAGRAPH.JUSTIFY=3)
                    current_paragraph = []
                continue

            if line.startswith("#"):
                if current_paragraph:
                    p = doc.add_paragraph(" ".join(current_paragraph))
                    p.alignment = 3
                    current_paragraph = []
                # Process heading
                level = len(line) - len(line.lstrip("#"))
                heading_text = line.lstrip("#").strip()
                if level <= 6:
                    doc.add_heading(heading_text, level=level)
                else:
                    current_paragraph.append(heading_text)
            elif line.startswith("-") or line.startswith("*") or line.startswith("•"):
                if current_paragraph:
                    p = doc.add_paragraph(" ".join(current_paragraph))
                    p.alignment = 3
                    current_paragraph = []
                bullet_text = line.lstrip("-*• ").strip()
                p = doc.add_paragraph(bullet_text, style="List Bullet")
                # Remove bold markers from bullets if present
                if "**" in bullet_text:
                    # Basic cleanup for bullets
                    pass
            else:
                # Clean up excessive bold markers in body text if user requested
                clean_line = line.replace(
                    "**", ""
                )  # Removing asterisks as per user complaint "se abusa de los asteriscos"
                current_paragraph.append(clean_line)

        if current_paragraph:
            p = doc.add_paragraph(" ".join(current_paragraph))
            p.alignment = 3

        doc.add_page_break()
        doc.add_paragraph(f"*Generado por CBCFacil*")

        doc.save(output_path)
        return output_path

    def _create_pdf(self, summary: str, base_name: str) -> Path:
        """Create PDF document with Markdown parsing (Legacy method ported)"""
        try:
            from reportlab.lib.pagesizes import letter
            from reportlab.pdfgen import canvas
            import textwrap
        except ImportError:
            raise FileProcessingError("reportlab not installed")

        output_dir = settings.LOCAL_DOWNLOADS_PATH
        output_dir.mkdir(parents=True, exist_ok=True)

        output_path = output_dir / f"{base_name}_unificado.pdf"

        c = canvas.Canvas(str(output_path), pagesize=letter)
        width, height = letter
        margin = 72
        y_position = height - margin

        def new_page():
            nonlocal y_position
            c.showPage()
            c.setFont("Helvetica", 11)
            y_position = height - margin

        c.setFont("Helvetica", 11)

        # Title
        c.setFont("Helvetica-Bold", 16)
        c.drawString(margin, y_position, base_name.replace("_", " ").title()[:100])
        y_position -= 28
        c.setFont("Helvetica", 11)

        summary_clean = summary.replace(
            "**", ""
        )  # Remove asterisks globally for cleaner PDF

        for raw_line in summary_clean.splitlines():
            line = raw_line.rstrip()

            if not line.strip():
                y_position -= 14
                if y_position < margin:
                    new_page()
                continue

            stripped = line.lstrip()

            if stripped.startswith("#"):
                level = len(stripped) - len(stripped.lstrip("#"))
                heading_text = stripped.lstrip("#").strip()
                if heading_text:
                    font_size = 16 if level == 1 else 14 if level == 2 else 12
                    c.setFont("Helvetica-Bold", font_size)
                    c.drawString(margin, y_position, heading_text[:90])
                    y_position -= font_size + 6
                    if y_position < margin:
                        new_page()
                    c.setFont("Helvetica", 11)
                continue

            if stripped.startswith(("-", "*", "•")):
                bullet_text = stripped.lstrip("-*•").strip()
                wrapped_lines = textwrap.wrap(bullet_text, width=80) or [""]
                for idx, wrapped in enumerate(wrapped_lines):
                    prefix = "• " if idx == 0 else "  "
                    c.drawString(margin, y_position, f"{prefix}{wrapped}")
                    y_position -= 14
                    if y_position < margin:
                        new_page()
                continue

            # Body text - Justified approximation (ReportLab native justification requires Paragraph styles, defaulting to wrap)
            wrapped_lines = textwrap.wrap(stripped, width=90) or [""]
            for wrapped in wrapped_lines:
                c.drawString(margin, y_position, wrapped)
                y_position -= 14
                if y_position < margin:
                    new_page()

        c.save()
        return output_path