From d2fd454d6e75093ae449363209eca22c6750bdd0 Mon Sep 17 00:00:00 2001 From: Anthony Stirling <77850077+Frooodle@users.noreply.github.com> Date: Sat, 27 Dec 2025 23:46:47 +0000 Subject: [PATCH] ai random --- .gitignore | 6 +- AI-Document-Generator-main/.gitignore | 45 + AI-Document-Generator-main/Dockerfile | 29 + AI-Document-Generator-main/README.md | 173 + .../backend/ai_generation.py | 165 + AI-Document-Generator-main/backend/app.py | 641 ++ AI-Document-Generator-main/backend/briefs.py | 491 ++ AI-Document-Generator-main/backend/config.py | 81 + .../backend/document_types.py | 57 + .../backend/langchain_utils.py | 22 + .../backend/latex_utils.py | 469 ++ .../backend/pdf_text_editor.py | 491 ++ .../backend/pdf_utils.py | 146 + AI-Document-Generator-main/backend/prompts.py | 129 + .../backend/requirements.txt | 6 + .../backend/scripts/check_prompts.py | 18 + AI-Document-Generator-main/backend/storage.py | 86 + AI-Document-Generator-main/backend/styles.py | 33 + AI-Document-Generator-main/backend/vision.py | 40 + .../frontend/.eslintrc.cjs | 36 + .../frontend/index.html | 13 + .../frontend/package-lock.json | 7012 +++++++++++++++++ .../frontend/package.json | 34 + .../frontend/postcss.config.js | 6 + .../frontend/public/favicon.ico | Bin 0 -> 15406 bytes .../frontend/src/App.tsx | 84 + .../src/components/landing/LandingView.tsx | 327 + .../components/modals/ImportLayoutModal.tsx | 75 + .../pdfTextEditor/PdfTextEditorFull.tsx | 2169 +++++ .../pdfTextEditor/PdfTextEditorLite.tsx | 223 + .../pdfTextEditor/PdfThumbnailViewer.tsx | 223 + .../components/pdfTextEditor/ZoomControls.tsx | 59 + .../components/pdfTextEditor/fontAnalysis.ts | 421 + .../pdfTextEditor/pdfTextEditorTypes.ts | 232 + .../pdfTextEditor/pdfTextEditorUtils.ts | 1396 ++++ .../src/components/ui/AudioWaveform.tsx | 98 + .../frontend/src/components/ui/Button.tsx | 32 + .../src/components/ui/ButtonGroup.tsx | 11 + .../src/components/workspace/ChatPanel.tsx | 255 + .../src/components/workspace/HistoryPanel.tsx | 73 + .../src/components/workspace/PreviewPanel.tsx | 137 + .../components/workspace/WorkspaceView.tsx | 113 + .../frontend/src/hooks/useDocumentWorkflow.ts | 469 ++ .../frontend/src/hooks/useSpeechCapture.ts | 367 + .../frontend/src/index.css | 27 + .../frontend/src/main.tsx | 10 + .../frontend/src/types/index.ts | 30 + .../frontend/tailwind.config.js | 11 + .../frontend/tsconfig.json | 21 + .../frontend/tsconfig.node.json | 10 + .../frontend/vite.config.ts | 17 + .../common/model/ApplicationProperties.java | 1 + .../controller/api/ai/AiProxyController.java | 141 + .../SPDF/service/ai/AiProxyService.java | 88 + .../src/main/resources/settings.yml.template | 1 + .../docker-compose-ai-stack-ollama.yml | 79 + docker/compose/docker-compose-ai-stack.yml | 60 + 57 files changed, 17488 insertions(+), 1 deletion(-) create mode 100644 AI-Document-Generator-main/.gitignore create mode 100644 AI-Document-Generator-main/Dockerfile create mode 100644 AI-Document-Generator-main/README.md create mode 100644 AI-Document-Generator-main/backend/ai_generation.py create mode 100644 AI-Document-Generator-main/backend/app.py create mode 100644 AI-Document-Generator-main/backend/briefs.py create mode 100644 AI-Document-Generator-main/backend/config.py create mode 100644 AI-Document-Generator-main/backend/document_types.py create mode 100644 AI-Document-Generator-main/backend/langchain_utils.py create mode 100644 AI-Document-Generator-main/backend/latex_utils.py create mode 100644 AI-Document-Generator-main/backend/pdf_text_editor.py create mode 100644 AI-Document-Generator-main/backend/pdf_utils.py create mode 100644 AI-Document-Generator-main/backend/prompts.py create mode 100644 AI-Document-Generator-main/backend/requirements.txt create mode 100644 AI-Document-Generator-main/backend/scripts/check_prompts.py create mode 100644 AI-Document-Generator-main/backend/storage.py create mode 100644 AI-Document-Generator-main/backend/styles.py create mode 100644 AI-Document-Generator-main/backend/vision.py create mode 100644 AI-Document-Generator-main/frontend/.eslintrc.cjs create mode 100644 AI-Document-Generator-main/frontend/index.html create mode 100644 AI-Document-Generator-main/frontend/package-lock.json create mode 100644 AI-Document-Generator-main/frontend/package.json create mode 100644 AI-Document-Generator-main/frontend/postcss.config.js create mode 100644 AI-Document-Generator-main/frontend/public/favicon.ico create mode 100644 AI-Document-Generator-main/frontend/src/App.tsx create mode 100644 AI-Document-Generator-main/frontend/src/components/landing/LandingView.tsx create mode 100644 AI-Document-Generator-main/frontend/src/components/modals/ImportLayoutModal.tsx create mode 100644 AI-Document-Generator-main/frontend/src/components/pdfTextEditor/PdfTextEditorFull.tsx create mode 100644 AI-Document-Generator-main/frontend/src/components/pdfTextEditor/PdfTextEditorLite.tsx create mode 100644 AI-Document-Generator-main/frontend/src/components/pdfTextEditor/PdfThumbnailViewer.tsx create mode 100644 AI-Document-Generator-main/frontend/src/components/pdfTextEditor/ZoomControls.tsx create mode 100644 AI-Document-Generator-main/frontend/src/components/pdfTextEditor/fontAnalysis.ts create mode 100644 AI-Document-Generator-main/frontend/src/components/pdfTextEditor/pdfTextEditorTypes.ts create mode 100644 AI-Document-Generator-main/frontend/src/components/pdfTextEditor/pdfTextEditorUtils.ts create mode 100644 AI-Document-Generator-main/frontend/src/components/ui/AudioWaveform.tsx create mode 100644 AI-Document-Generator-main/frontend/src/components/ui/Button.tsx create mode 100644 AI-Document-Generator-main/frontend/src/components/ui/ButtonGroup.tsx create mode 100644 AI-Document-Generator-main/frontend/src/components/workspace/ChatPanel.tsx create mode 100644 AI-Document-Generator-main/frontend/src/components/workspace/HistoryPanel.tsx create mode 100644 AI-Document-Generator-main/frontend/src/components/workspace/PreviewPanel.tsx create mode 100644 AI-Document-Generator-main/frontend/src/components/workspace/WorkspaceView.tsx create mode 100644 AI-Document-Generator-main/frontend/src/hooks/useDocumentWorkflow.ts create mode 100644 AI-Document-Generator-main/frontend/src/hooks/useSpeechCapture.ts create mode 100644 AI-Document-Generator-main/frontend/src/index.css create mode 100644 AI-Document-Generator-main/frontend/src/main.tsx create mode 100644 AI-Document-Generator-main/frontend/src/types/index.ts create mode 100644 AI-Document-Generator-main/frontend/tailwind.config.js create mode 100644 AI-Document-Generator-main/frontend/tsconfig.json create mode 100644 AI-Document-Generator-main/frontend/tsconfig.node.json create mode 100644 AI-Document-Generator-main/frontend/vite.config.ts create mode 100644 app/core/src/main/java/stirling/software/SPDF/controller/api/ai/AiProxyController.java create mode 100644 app/core/src/main/java/stirling/software/SPDF/service/ai/AiProxyService.java create mode 100644 docker/compose/docker-compose-ai-stack-ollama.yml create mode 100644 docker/compose/docker-compose-ai-stack.yml diff --git a/.gitignore b/.gitignore index 8b9fe5df92..fe669fe83f 100644 --- a/.gitignore +++ b/.gitignore @@ -31,6 +31,11 @@ exampleYmlFiles/stirling/ /testing/file_snapshots SwaggerDoc.json +# Docker bind-mount volumes (local data) +AI-Document-Generator-main/backend/data/ +AI-Document-Generator-main/backend/output/ +docker/compose/stirling/ + # Frontend build artifacts copied to backend static resources # These are generated by npm build and should not be committed app/core/src/main/resources/static/assets/ @@ -241,4 +246,3 @@ docs/type3/signatures/ # Type3 sample PDFs (development only) **/type3/samples/ - diff --git a/AI-Document-Generator-main/.gitignore b/AI-Document-Generator-main/.gitignore new file mode 100644 index 0000000000..94cb29e8a8 --- /dev/null +++ b/AI-Document-Generator-main/.gitignore @@ -0,0 +1,45 @@ +# Python +__pycache__/ +*.py[cod] +*$py.class +*.so +.Python +env/ +venv/ +ENV/ +build/ +dist/ +*.egg-info/ + +# Node +node_modules/ +npm-debug.log* +yarn-debug.log* +yarn-error.log* +dist/ +.vite/ + +# Environment +.env +.env.local + +# LaTeX outputs +*.aux +*.log +*.out +*.toc +*.pdf +*.tex +backend/output/ +backend/data/user_styles.json + +# IDE +.vscode/ +.idea/ +*.swp +*.swo +*~ + +# OS +.DS_Store +Thumbs.db diff --git a/AI-Document-Generator-main/Dockerfile b/AI-Document-Generator-main/Dockerfile new file mode 100644 index 0000000000..ba6e76f67f --- /dev/null +++ b/AI-Document-Generator-main/Dockerfile @@ -0,0 +1,29 @@ +FROM python:3.11-slim + +# Install full TeXLive so LLM outputs (siunitx, paracol, tikz, etc.) compile reliably. +RUN apt-get update && \ + apt-get install -y --no-install-recommends \ + texlive-full \ + latexmk \ + ghostscript \ + poppler-utils \ + ca-certificates \ + && rm -rf /var/lib/apt/lists/* + +# Set working directory +WORKDIR /app + +# Copy backend files +COPY backend/requirements.txt . +RUN pip install --no-cache-dir -r requirements.txt + +COPY backend/ . + +# Create output directories +RUN mkdir -p /app/output /app/data + +# Expose port +EXPOSE 5000 + +# Run the Flask app +CMD ["python", "app.py"] diff --git a/AI-Document-Generator-main/README.md b/AI-Document-Generator-main/README.md new file mode 100644 index 0000000000..05d79dd2a0 --- /dev/null +++ b/AI-Document-Generator-main/README.md @@ -0,0 +1,173 @@ +# LaTeX PDF Generator + +AI-powered document generator using LaTeX. Creates professional documents (invoices, resumes, contracts, etc.) from natural language prompts with conversational editing. + +## Features + +- 🎨 ChatGPT-like interface with split-screen PDF preview (main window only) +- πŸ“ Generates LaTeX documents from natural language and compiles to PDF in Docker +- πŸ”„ Conversational editing with PDF regeneration on every turn +- πŸ’Ύ Style memory + template reuse per user/team and document type +- πŸ—‚οΈ Version history with per-iteration PDFs you can reopen +- πŸ“„ Supports: Invoices, Resumes, Contracts, Letters, Reports, poems, proposals, and more + +## Quick Start + +### Option 1: Docker (Recommended) + +```bash +# Build the Docker image +docker build -t latex-generator . + +# Run the backend +docker run -p 5000:5000 latex-generator +``` + +### Option 2: Local Development + +#### Backend Setup + +```bash +cd backend + +# Install Python dependencies +pip install -r requirements.txt + +# Install LaTeX (if not already installed) +# On Ubuntu/Debian: +sudo apt-get install texlive-latex-base texlive-latex-extra + +# On Mac: +brew install --cask mactex + +# On Windows: +# Download and install MiKTeX from https://miktex.org/download + +# Run the backend +python app.py +``` + +Backend will run on `http://localhost:5000` + +#### Frontend Setup + +```bash +cd frontend + +# Install dependencies +npm install + +# Run the dev server +npm run dev +``` + +Frontend will run on `http://localhost:3000` + +## Usage + +1. Open `http://localhost:3000` in your browser +2. Type a prompt like "Create an invoice for web development services" +3. The AI generates LaTeX code and compiles it to PDF +4. Continue chatting to refine the document +5. Download the final PDF + +## Example Prompts + +- "Create a professional invoice for $1,500 in consulting services" +- "Generate a resume for a senior software engineer with 5 years experience" +- "Make a business letter to a client about project completion" +- "Create a contract for freelance web development" + +## Configuration + +### OpenAI API (Optional) + +To use real AI generation instead of mock templates: + +1. Copy `.env.example` to `.env` +2. Add your OpenAI API key: `OPENAI_API_KEY=sk-...` +3. (Optional) Choose models: + - Smart (full generation): `SMART_MODEL=gpt-5.1` (default) + - Fast (intent/pre checks): `FAST_MODEL=gpt-4.1-nano` (default) +3. (Legacy SDK) We pin `openai==0.28.1` in Docker to avoid client init issues. No code changes needed. + +## Project Structure + +``` +latex-pdf-generator/ +β”œβ”€β”€ frontend/ # React + TypeScript + Tailwind +β”‚ β”œβ”€β”€ src/ +β”‚ β”‚ β”œβ”€β”€ components/ +β”‚ β”‚ β”‚ β”œβ”€β”€ landing/ # Landing hero + CTA +β”‚ β”‚ β”‚ β”œβ”€β”€ modals/ # Reusable modal(s) +β”‚ β”‚ β”‚ β”œβ”€β”€ workspace/ # Chat panel, preview, history +β”‚ β”‚ β”‚ └── ui/ # Buttons, button groups, etc. +β”‚ β”‚ β”œβ”€β”€ hooks/ # Workflow + speech capture hooks +β”‚ β”‚ β”œβ”€β”€ types/ # Shared TypeScript interfaces +β”‚ β”‚ β”œβ”€β”€ App.tsx # Thin orchestrator +β”‚ β”‚ └── main.tsx +β”‚ β”œβ”€β”€ .eslintrc.cjs # ESLint config (React + TS) +β”‚ β”œβ”€β”€ package.json +β”‚ └── vite.config.ts +β”œβ”€β”€ backend/ # Flask + LaTeX +β”‚ β”œβ”€β”€ app.py # Routes + Flask app factory +β”‚ β”œβ”€β”€ ai_generation.py # OpenAI + mock generation helpers +β”‚ β”œβ”€β”€ briefs.py # Guided brief collection utilities +β”‚ β”œβ”€β”€ config.py # Logging + environment setup +β”‚ β”œβ”€β”€ document_types.py # Doc-type heuristics +β”‚ β”œβ”€β”€ latex_utils.py # LaTeX sanitizers + layout helpers +β”‚ β”œβ”€β”€ pdf_utils.py # PDF compilation + render helpers +β”‚ β”œβ”€β”€ storage.py # JSON persistence for users/templates +β”‚ β”œβ”€β”€ styles.py # Style preference heuristics +β”‚ β”œβ”€β”€ vision.py # Layout extraction via multimodal GPT +β”‚ β”œβ”€β”€ requirements.txt +β”‚ └── data/ # User style storage +β”œβ”€β”€ Dockerfile +└── README.md +``` + +### Linting + +The frontend now ships with ESLint + TypeScript rules that keep the new modular structure tidy: + +```bash +cd frontend +npm run lint +``` + +Backend linting can be added with your preferred tool (e.g., ruff or flake8) by pointing it at the new small modules in `backend/`. + +## Troubleshooting + +### LaTeX compilation fails + +- Ensure `pdflatex` is in your PATH +- Check logs in the backend console +- Verify LaTeX packages are installed + +### CORS errors + +- Make sure both frontend and backend are running +- Frontend proxy is configured in `vite.config.ts` + +### PDF not displaying + +- Check browser console for errors +- Ensure the backend `/output` endpoint is accessible +- Try opening the PDF URL directly + +## Development + +### Mock Mode (Current) + +The app currently uses mock LaTeX templates for quick testing. To enable real AI: + +1. Get an OpenAI API key +2. Set `OPENAI_API_KEY` and optionally override: + - `SMART_MODEL` (default `gpt-5.1`) + - `FAST_MODEL` (default `gpt-4.1-nano`) +3. Restart the backend; it auto-detects whether to call the live model or the bundled mock templates + +## License + +MIT diff --git a/AI-Document-Generator-main/backend/ai_generation.py b/AI-Document-Generator-main/backend/ai_generation.py new file mode 100644 index 0000000000..733aa9bf59 --- /dev/null +++ b/AI-Document-Generator-main/backend/ai_generation.py @@ -0,0 +1,165 @@ +from __future__ import annotations + +import json +from typing import Any, Dict, List, Optional + +from config import CLIENT_MODE, SMART_MODEL, STREAMING_ENABLED, get_chat_model, logger +from langchain_utils import to_lc_messages +from storage import save_user_style +from prompts import latex_system_prompt, latex_context_messages + + +def generate_latex_with_llm( + prompt: str, + history: List[Dict[str, str]], + style_profile: Dict[str, Any], + document_type: str, + template_hint: Optional[str] = None, + current_latex: Optional[str] = None, + structured_brief: Optional[str] = None, + edit_mode: bool = False, +) -> str: + """Call the LLM (when available) or fall back to deterministic templates.""" + if CLIENT_MODE == "langchain": + messages: List[Dict[str, Any]] = [{"role": "system", "content": latex_system_prompt(style_profile, document_type, template_hint)}] + messages.extend(history) + messages.extend(latex_context_messages(template_hint, current_latex, structured_brief)) + messages.append({"role": "user", "content": prompt}) + + try: + logger.info( + "[AI] Using live model=%s doc_type=%s template_hint=%s", + SMART_MODEL, + document_type, + "yes" if template_hint else "no", + ) + llm = get_chat_model(SMART_MODEL) + if llm: + response = llm.invoke(to_lc_messages(messages)) + return response.content + except Exception as exc: + logger.error("[AI] LangChain generation failed, falling back to mock: %s", exc) + + lower_prompt = prompt.lower() + + if "invoice" in lower_prompt: + save_user_style("default_user", {"last_doc_type": "invoice"}) + details = structured_brief or prompt or "Invoice details provided by user." + return r"""\documentclass{article} +\usepackage[utf8]{inputenc} +\usepackage{geometry} +\geometry{a4paper, margin=1in} + +\begin{document} + +\begin{center} + {\LARGE \textbf{INVOICE}}\\[0.5cm] + \#1023\\ + \today +\end{center} + +\section*{Bill To:} +Client Name \\ +123 Business Rd. + +\section*{Items} +\begin{tabular}{lr} + \textbf{Service} & \textbf{Amount} \\ + \hline + % Replace with your line items + Description & \$0.00 \\ + Description & \$0.00 \\ + \hline + \textbf{Total Due} & \textbf{\$0.00} \\ +\end{tabular} + +\section*{Notes} +""" + details + r""" + +\end{document}""" + + if "resume" in lower_prompt or "cv" in lower_prompt: + save_user_style("default_user", {"last_doc_type": "resume"}) + details = structured_brief or prompt or "Resume details provided by user." + return r"""\documentclass{article} +\usepackage[utf8]{inputenc} +\usepackage{geometry} +\geometry{a4paper, margin=0.75in} + +\begin{document} + +\section*{Details} +""" + details + r""" + +\end{document}""" + + base_doc = r"""\documentclass{article} +\usepackage[utf8]{inputenc} +\usepackage{geometry} +\geometry{a4paper, margin=1in} + +\begin{document} + +""" + content = structured_brief or prompt or "" + base_doc += r"""\section*{Document} + +""" + content + r""" + +\end{document}""" + + return base_doc + + +def generate_latex_with_llm_stream( + prompt: str, + history: List[Dict[str, str]], + style_profile: Dict[str, Any], + document_type: str, + template_hint: Optional[str] = None, + current_latex: Optional[str] = None, + structured_brief: Optional[str] = None, + edit_mode: bool = False, +): + """Stream LaTeX generation from LLM, yielding chunks as they arrive.""" + if not STREAMING_ENABLED: + full_latex = generate_latex_with_llm( + prompt, history, style_profile, document_type, template_hint, current_latex, structured_brief, edit_mode=edit_mode + ) + chunk_size = 100 + for i in range(0, len(full_latex), chunk_size): + yield full_latex[i:i + chunk_size] + return + if CLIENT_MODE == "langchain": + messages: List[Dict[str, Any]] = [{"role": "system", "content": latex_system_prompt(style_profile, document_type, template_hint)}] + messages.extend(history) + messages.extend(latex_context_messages(template_hint, current_latex, structured_brief)) + messages.append({"role": "user", "content": prompt}) + + try: + logger.info( + "[AI] Streaming from model=%s doc_type=%s template_hint=%s", + SMART_MODEL, + document_type, + "yes" if template_hint else "no", + ) + llm = get_chat_model(SMART_MODEL, streaming=True) + if llm: + for chunk in llm.stream(to_lc_messages(messages)): + if chunk.content: + yield chunk.content + return + except Exception as exc: + logger.error("[AI] LangChain streaming failed, falling back to mock: %s", exc) + + # Fallback to non-streaming for mock mode + full_latex = generate_latex_with_llm( + prompt, history, style_profile, document_type, template_hint, current_latex, structured_brief, edit_mode=edit_mode + ) + # Simulate streaming by yielding chunks + chunk_size = 100 + for i in range(0, len(full_latex), chunk_size): + yield full_latex[i:i + chunk_size] + + +__all__ = ["generate_latex_with_llm", "generate_latex_with_llm_stream"] diff --git a/AI-Document-Generator-main/backend/app.py b/AI-Document-Generator-main/backend/app.py new file mode 100644 index 0000000000..d44833212e --- /dev/null +++ b/AI-Document-Generator-main/backend/app.py @@ -0,0 +1,641 @@ +import os +import subprocess +import uuid +from datetime import datetime +from typing import Any, Dict, List, Optional, Tuple +import re +import time +import threading +import queue +from concurrent.futures import ThreadPoolExecutor + +from flask import Flask, jsonify, request, send_file, Response, stream_with_context +from flask_cors import CORS +import json + +from ai_generation import generate_latex_with_llm, generate_latex_with_llm_stream +from briefs import gather_brief, _preprocess_intent +from config import CLIENT_MODE, SMART_MODEL, OUTPUT_DIR, get_chat_model, logger +from langchain_utils import to_lc_messages +from document_types import detect_document_type +from latex_utils import clean_generated_latex +from pdf_utils import compile_latex_to_pdf, render_pdf_to_images +from pdf_text_editor import convert_pdf_to_text_editor_document +from storage import ( + load_user_style, + load_user_templates, + load_versions, + save_user_style, + save_user_template, + save_version, +) +from styles import update_style_profile_from_prompt +from vision import vision_layout_from_images +from prompts import pdf_qa_system_prompt + + +app = Flask(__name__) +CORS(app) + + +@app.before_request +def log_job_request_sequence() -> None: + job_id = request.headers.get("X-Job-Id") + if not job_id: + return + seq = request.headers.get("X-Job-Seq", "?") + total = request.headers.get("X-Job-Total", "?") + logger.info("[HTTP] job_id=%s req=%s/%s %s %s", job_id, seq, total, request.method, request.path) + + +def _json_body() -> Dict[str, Any]: + return request.get_json(silent=True) or {} + + +@app.route("/api/intent/check", methods=["POST"]) +def intent_check() -> Any: + try: + data = _json_body() + prompt: str = data.get("prompt", "") + history: List[Dict[str, str]] = data.get("conversationHistory") or [] + current_latex: Optional[str] = data.get("currentLatex") + current_pdf_url: Optional[str] = data.get("currentPdfUrl") + doc_type = detect_document_type(prompt, current_latex) + intent = _preprocess_intent(prompt, history, bool(current_pdf_url), current_latex) + intent["documentType"] = doc_type + intent["hasPdf"] = bool(current_pdf_url) + return jsonify(intent) + except Exception as exc: # noqa: BLE001 + logger.error("[INTENT] intent_check failed: %s", exc, exc_info=True) + return jsonify({"wants_pdf": True, "has_enough_info": True, "allow_makeup": False, "reason": str(exc)}), 500 + + +@app.route("/api/pdf/answer", methods=["POST"]) +def pdf_answer() -> Any: + data = _json_body() + pdf_url = data.get("pdfUrl") + question = data.get("question") + if not pdf_url or not question: + return jsonify({"error": "Missing pdfUrl or question"}), 400 + + filename = os.path.basename(pdf_url.split("?")[0]) + if not filename.lower().endswith(".pdf"): + return jsonify({"error": "Invalid pdf file"}), 400 + + pdf_path = os.path.join(OUTPUT_DIR, filename) + if not os.path.exists(pdf_path): + return jsonify({"error": "PDF not found"}), 404 + + try: + doc = convert_pdf_to_text_editor_document(pdf_path) + except Exception as exc: # noqa: BLE001 + logger.error("[PDF-ANSWER] failed to parse pdf: %s", exc, exc_info=True) + return jsonify({"error": "Failed to read PDF content"}), 500 + + pages = doc.get("document", {}).get("pages", []) if doc else [] + snippets: List[str] = [] + for page in pages: + for elem in page.get("textElements", []) or []: + text = elem.get("text") + if text: + snippets.append(str(text)) + if not snippets: + return jsonify({"error": "No readable text in PDF"}), 400 + + # Normalize and limit context + context = " ".join(snippets) + context = " ".join(context.split()) # normalize whitespace + max_context = 10000 + if len(context) > max_context: + context = context[:max_context] + + # Heuristic helpers + def _sentences(text: str) -> List[str]: + return [s.strip() for s in re.split(r"(?<=[.!?])\s+", text) if s.strip()] + + def _heuristic_summary(text: str, limit: int = 480) -> str: + sentences = _sentences(text) + hits = [s for s in sentences if re.search(r"\b(difficult|challenge|problem|issue|hard)\b", s, re.IGNORECASE)] + chosen = hits[:3] if hits else sentences[:3] + summary = " ".join(chosen).strip() + return summary[:limit] + ("…" if len(summary) > limit else "") + + def _heuristic_first_difficulty(text: str) -> str: + sentences = _sentences(text) + for s in sentences: + if re.search(r"\b(difficult|challenge|problem|issue|hard)\b", s, re.IGNORECASE): + return s + return sentences[0] if sentences else "No difficulty found in PDF text." + + if CLIENT_MODE != "langchain": + return jsonify({"error": "PDF Q&A unavailable (no AI client configured)."}), 503 + + model_name = SMART_MODEL + system_prompt = pdf_qa_system_prompt() + user_prompt = f"Question: {question}\n\nPDF text:\n{context}" + try: + llm = get_chat_model(model_name, max_tokens=220) + if not llm: + return jsonify({"error": "PDF Q&A unavailable (no AI client configured)."}), 503 + response = llm.invoke( + to_lc_messages( + [ + {"role": "system", "content": system_prompt}, + {"role": "user", "content": user_prompt}, + ] + ) + ) + answer = response.content + if not answer or not str(answer).strip(): + answer = _heuristic_summary(context) + # If model parrots title/metadata, replace with heuristic + title_like = re.match(r"^why pdfs|^minimalist|^author:", answer.strip(), re.IGNORECASE) if answer else None + normalized_answer = re.sub(r"\s+", " ", answer or "").strip().lower() + normalized_context = re.sub(r"\s+", " ", context).strip().lower() + copied_context = bool(normalized_answer) and normalized_answer in normalized_context + if title_like or copied_context: + answer = _heuristic_summary(context) + return jsonify({"answer": answer, "mode": "model"}) + except Exception as exc: # noqa: BLE001 + logger.error("[PDF-ANSWER] model failed: %s", exc, exc_info=True) + answer = _heuristic_first_difficulty(context) + return jsonify({"answer": answer, "mode": "heuristic"}) + + +@app.route("/api/generate", methods=["POST"]) +def generate() -> Any: + """Generate LaTeX + PDF in a single call.""" + data = _json_body() + user_id = data.get("userId", "default_user") + prompt: str = data.get("prompt", "") + history: List[Dict[str, str]] = data.get("conversationHistory") or [] + current_latex: str | None = data.get("currentLatex") + skip_template = bool(data.get("skipTemplate")) + force_new_document: Optional[bool] = data.get("forceNewDocument") + edit_mode = bool(current_latex) and not bool(force_new_document) + latex_source = current_latex if edit_mode else None + + style_profile = update_style_profile_from_prompt(user_id, prompt) + + doc_type = detect_document_type(prompt, latex_source or current_latex) + brief = gather_brief(doc_type, prompt, history) + if brief.get("needsInfo"): + logger.info("[REQ] brief incomplete doc_type=%s missing=%s", doc_type, brief.get("missing")) + return jsonify( + { + "needsInfo": True, + "message": brief.get("message"), + "missing": brief.get("missing", []), + "collected": brief.get("collected", {}), + "documentType": doc_type, + } + ) + + templates = load_user_templates(user_id) + template_hint = None if (skip_template or edit_mode) else templates.get(doc_type) + + logger.info( + "[REQ] user=%s doc_type=%s template=%s history_len=%s current_latex=%s skip_template=%s edit_mode=%s", + user_id, + doc_type, + "yes" if template_hint else "no", + len(history), + bool(current_latex), + skip_template, + edit_mode, + ) + + mode = "live" if CLIENT_MODE == "langchain" else "mock" + latex_code_raw = generate_latex_with_llm( + prompt, + history, + style_profile, + doc_type, + template_hint, + latex_source, + brief.get("structured_brief"), + edit_mode=edit_mode, + ) + latex_code = clean_generated_latex(latex_code_raw) + + doc_type = detect_document_type(prompt, latex_code) + save_user_style(user_id, {"last_doc_type": doc_type}) + if not skip_template and not edit_mode: + save_user_template(user_id, doc_type, latex_code) + elif skip_template: + logger.info("[TEMPLATE] skip flag set; not persisting template for %s", doc_type) + else: + logger.info("[TEMPLATE] edit mode active; not updating template for %s", doc_type) + template_used = bool(template_hint) + + job_id = str(uuid.uuid4()) + pdf_path = compile_latex_to_pdf(latex_code, job_id) + if pdf_path and os.path.exists(pdf_path): + pdf_url = f"/output/{job_id}.pdf" + version_entry = { + "id": job_id, + "prompt": prompt, + "documentType": doc_type, + "pdfUrl": pdf_url, + "latex": latex_code, + "createdAt": datetime.utcnow().isoformat() + "Z", + "styleProfile": style_profile, + "templateUsed": template_used, + "editMode": edit_mode, + } + save_version(user_id, version_entry) + + logger.info("[OK] job_id=%s doc_type=%s pdf_url=%s", job_id, doc_type, pdf_url) + return jsonify( + { + "latex": latex_code, + "pdfUrl": pdf_url, + "documentType": doc_type, + "message": f"Generated {doc_type} successfully! mode={mode}", + "version": version_entry, + "styleProfile": style_profile, + "mode": mode, + "templateUsed": template_used, + "editingExisting": edit_mode, + } + ) + + logger.error("[FAIL] job_id=%s doc_type=%s compile_failed", job_id, doc_type) + return jsonify( + { + "error": "LaTeX compilation failed. Check logs.", + "latex": latex_code, + "mode": mode, + "editingExisting": edit_mode, + } + ), 500 + + +@app.route("/api/generate_stream", methods=["POST"]) +def generate_stream() -> Any: + """Stream LaTeX generation and compile PDFs incrementally.""" + try: + data = _json_body() + user_id = data.get("userId", "default_user") + prompt: str = data.get("prompt", "") + history: List[Dict[str, str]] = data.get("conversationHistory") or [] + current_latex: str | None = data.get("currentLatex") + skip_template = bool(data.get("skipTemplate")) + force_new_document: Optional[bool] = data.get("forceNewDocument") + edit_mode = bool(current_latex) and not bool(force_new_document) + latex_source = current_latex if edit_mode else None + style_profile = update_style_profile_from_prompt(user_id, prompt) + doc_type = detect_document_type(prompt, latex_source or current_latex) + brief = gather_brief(doc_type, prompt, history, current_latex, bool(current_latex)) + logger.info( + "[STREAM] brief gate doc_type=%s needsInfo=%s missing=%s allowFabrication=%s", + doc_type, + brief.get("needsInfo"), + brief.get("missing"), + brief.get("allowFabrication"), + ) + except Exception as exc: # noqa: BLE001 + logger.error("[STREAM] Failed to prepare generation request: %s", exc, exc_info=True) + return jsonify({"error": "Failed to start generation", "detail": str(exc)}), 500 + + if brief.get("needsInfo"): + # Return a normal 200 with guidance so the assistant can ask follow-up questions + return jsonify( + { + "needsInfo": True, + "message": brief.get("message"), + "missing": brief.get("missing", []), + "collected": brief.get("collected", {}), + "documentType": doc_type, + "allowFabrication": brief.get("allowFabrication", False), + } + ) + + templates = load_user_templates(user_id) + template_hint = None if (skip_template or edit_mode) else templates.get(doc_type) + + job_id = str(uuid.uuid4()) + accumulated_latex = "" + last_compile_idx = 0 + compile_interval = 250 # Compile every ~250 characters for faster previews + compile_time_budget = 2.0 # Or every ~2 seconds, whichever comes first + last_compile_time = time.perf_counter() + last_heartbeat_time = time.perf_counter() + stream_start = time.perf_counter() + first_chunk_time: Optional[float] = None + last_chunk_time: Optional[float] = None + total_chunk_chars = 0 + total_chunks = 0 + + preview_executor = ThreadPoolExecutor(max_workers=2) + preview_tasks: Dict[str, Tuple[Any, int]] = {} + chunk_queue: "queue.Queue[Tuple[str, Optional[str]]]" = queue.Queue() + + def stream_latex(): + try: + for chunk in generate_latex_with_llm_stream( + prompt, + history, + style_profile, + doc_type, + template_hint, + latex_source, + brief.get("structured_brief"), + edit_mode=edit_mode, + ): + chunk_queue.put(("chunk", chunk)) + except Exception as exc: + logger.error("[STREAM] LLM streaming failed: %s", exc, exc_info=True) + chunk_queue.put(("error", str(exc))) + finally: + chunk_queue.put(("done", None)) + + def submit_preview(latex: str, progress: int) -> None: + preview_job_id = f"{job_id}-preview-{progress}" + + def _run_compile() -> Optional[str]: + return compile_latex_to_pdf(latex, preview_job_id, log_errors=False) + + fut = preview_executor.submit(_run_compile) + preview_tasks[preview_job_id] = (fut, progress) + + def drain_previews(): + nonlocal last_compile_idx, last_compile_time + completed = [] + for pid, (fut, progress) in list(preview_tasks.items()): + if fut.done(): + completed.append(pid) + try: + pdf_path = fut.result() + if pdf_path and os.path.exists(pdf_path): + pdf_url = f"/output/{pid}.pdf" + yield f"data: {json.dumps({'type': 'pdf_update', 'pdfUrl': pdf_url, 'progress': progress})}\n\n" + last_compile_idx = progress + last_compile_time = time.perf_counter() + except Exception as e: # noqa: BLE001 + logger.error("[STREAM] Preview compile failed (async): %s", e, exc_info=True) + for pid in completed: + preview_tasks.pop(pid, None) + + def generate(): + nonlocal accumulated_latex, last_compile_time, last_heartbeat_time + nonlocal total_chunk_chars, total_chunks, first_chunk_time, last_chunk_time + + # Send initial metadata + yield f"data: {json.dumps({'type': 'start', 'jobId': job_id, 'documentType': doc_type, 'editingExisting': edit_mode})}\n\n" + + streamer = threading.Thread(target=stream_latex, daemon=True) + streamer.start() + + try: + while True: + try: + item_type, payload = chunk_queue.get(timeout=0.5) + except queue.Empty: + now = time.perf_counter() + if now - last_heartbeat_time >= 1.0: + yield f"data: {json.dumps({'type': 'heartbeat', 'ts': now})}\n\n" + last_heartbeat_time = now + yield from drain_previews() + continue + + if item_type == "chunk": + chunk = payload or "" + accumulated_latex += chunk + total_chunks += 1 + total_chunk_chars += len(chunk) + last_chunk_time = time.perf_counter() + if first_chunk_time is None: + first_chunk_time = last_chunk_time + yield f"data: {json.dumps({'type': 'latex_chunk', 'chunk': chunk, 'accumulated': accumulated_latex})}\n\n" + + elapsed = time.perf_counter() - last_compile_time + if (len(accumulated_latex) - last_compile_idx >= compile_interval) or elapsed >= compile_time_budget: + compile_latex = accumulated_latex + if "\\begin{document}" in compile_latex and "\\end{document}" not in compile_latex: + if compile_latex.count("\\begin{") > compile_latex.count("\\end{"): + temp_latex = compile_latex + last_begin = compile_latex.rfind("\\begin{") + if last_begin != -1: + env_start = last_begin + len("\\begin{") + env_end = compile_latex.find("}", env_start) + if env_end != -1: + env_name = compile_latex[env_start:env_end] + temp_latex += f"\\end{{{env_name}}}\n" + temp_latex += "\\end{document}\n" + compile_latex = temp_latex + else: + compile_latex += "\\end{document}\n" + + if "\\begin{document}" in compile_latex and "\\end{document}" in compile_latex: + submit_preview(compile_latex, len(accumulated_latex)) + + now = time.perf_counter() + if now - last_heartbeat_time >= 1.0: + yield f"data: {json.dumps({'type': 'heartbeat', 'ts': now})}\n\n" + last_heartbeat_time = now + yield from drain_previews() + + elif item_type == "error": + message = payload or "Streaming failed" + yield f"data: {json.dumps({'type': 'error', 'message': message})}\n\n" + break + elif item_type == "done": + break + + stream_end = time.perf_counter() + if first_chunk_time is None: + logger.info( + "[STREAM] LLM finished with no chunks job_id=%s elapsed=%.2fs", + job_id, + stream_end - stream_start, + ) + else: + logger.info( + "[STREAM] LLM stats job_id=%s chunks=%s chars=%s first_chunk=%.2fs last_chunk=%.2fs elapsed=%.2fs", + job_id, + total_chunks, + total_chunk_chars, + first_chunk_time - stream_start, + (last_chunk_time or stream_end) - stream_start, + stream_end - stream_start, + ) + + # Final compilation with complete LaTeX + latex_code = clean_generated_latex(accumulated_latex) + final_doc_type = detect_document_type(prompt, latex_code) + save_user_style(user_id, {"last_doc_type": final_doc_type}) + if not skip_template and not edit_mode: + save_user_template(user_id, final_doc_type, latex_code) + elif skip_template: + logger.info("[TEMPLATE] skip flag set; not persisting template for %s", final_doc_type) + else: + logger.info("[TEMPLATE] edit mode active; not updating template for %s", final_doc_type) + template_used = bool(template_hint) + + pdf_path = compile_latex_to_pdf(latex_code, job_id) + if pdf_path and os.path.exists(pdf_path): + pdf_url = f"/output/{job_id}.pdf" + version_entry = { + "id": job_id, + "prompt": prompt, + "documentType": final_doc_type, + "pdfUrl": pdf_url, + "latex": latex_code, + "createdAt": datetime.utcnow().isoformat() + "Z", + "styleProfile": style_profile, + "templateUsed": template_used, + "editMode": edit_mode, + } + save_version(user_id, version_entry) + + yield f"data: {json.dumps({'type': 'complete', 'pdfUrl': pdf_url, 'latex': latex_code, 'version': version_entry, 'documentType': final_doc_type, 'templateUsed': template_used, 'styleProfile': style_profile, 'editingExisting': edit_mode})}\n\n" + else: + logger.error("[STREAM] Final PDF compilation failed for job_id=%s", job_id) + yield f"data: {json.dumps({'type': 'error', 'message': 'Final PDF compilation failed'})}\n\n" + + except Exception as e: # noqa: BLE001 + logger.error("[STREAM] Generation error job_id=%s: %s", job_id, e, exc_info=True) + yield f"data: {json.dumps({'type': 'error', 'message': str(e)})}\n\n" + finally: + try: + preview_executor.shutdown(wait=False, cancel_futures=True) + except Exception: + pass + + try: + return Response( + stream_with_context(generate()), + mimetype="text/event-stream", + headers={ + "Cache-Control": "no-cache", + "X-Accel-Buffering": "no", + }, + ) + except Exception as exc: # noqa: BLE001 + logger.error("[STREAM] Failed to start response: %s", exc, exc_info=True) + return jsonify({"error": "Unable to start streaming response", "detail": str(exc)}), 500 + + +@app.route("/api/progressive_render", methods=["POST"]) +def progressive_render() -> Any: + """Compile arbitrary LaTeX (partial or masked) for progressive previews.""" + data = _json_body() + latex = data.get("latex") + if not latex or not isinstance(latex, str): + return jsonify({"error": "Missing LaTeX payload"}), 400 + + job_id = data.get("jobId") or str(uuid.uuid4()) + pdf_path = compile_latex_to_pdf(latex, job_id) + if pdf_path and os.path.exists(pdf_path): + return jsonify({"pdfUrl": f"/output/{job_id}.pdf"}) + + return jsonify({"error": "Progressive compilation failed"}), 500 + + +@app.route("/output/", methods=["GET"]) +def serve_pdf(filename: str) -> Any: + """Serve generated PDF files.""" + file_path = os.path.join(OUTPUT_DIR, filename) + if os.path.exists(file_path): + return send_file(file_path, mimetype="application/pdf") + return jsonify({"error": "File not found"}), 404 + + +@app.route("/api/versions/", methods=["GET"]) +def list_versions(user_id: str) -> Any: + return jsonify({"versions": load_versions(user_id)}) + + +@app.route("/api/style/", methods=["GET"]) +def get_style(user_id: str) -> Any: + return jsonify({"style": load_user_style(user_id)}) + + +@app.route("/api/import_template", methods=["POST"]) +def import_template() -> Any: + """Accept a PDF upload, extract layout via vision model, and save as a template.""" + user_id = request.form.get("userId", "default_user") + doc_type = request.form.get("docType", "document") + file = request.files.get("file") + + if not file: + return jsonify({"error": "No file uploaded"}), 400 + + pdf_bytes = file.read() + images = render_pdf_to_images(pdf_bytes, max_pages=2, dpi=170) + if not images: + return jsonify({"error": "Failed to render PDF"}), 400 + + layout_latex = vision_layout_from_images(images, doc_type) or "" + if not layout_latex: + layout_latex = f"""\\documentclass{{article}} +\\usepackage[margin=1in]{{geometry}} +\\usepackage{{tabularx}} +\\usepackage{{multicol}} +\\begin{{document}} +% Fallback template for {doc_type} +\\section*{{Title placeholder}} +Body text goes here. +\\end{{document}} +""" + + sanitized = clean_generated_latex(layout_latex) + save_user_template(user_id, doc_type, sanitized) + return jsonify({"message": "Template imported", "docType": doc_type, "pages": len(images)}) + + +@app.route("/api/pdf-editor/document", methods=["GET"]) +def pdf_editor_document() -> Any: + """Expose a JSON snapshot of the PDF for rich text editing.""" + pdf_url = request.args.get("pdfUrl") + if not pdf_url: + return jsonify({"error": "Missing pdfUrl"}), 400 + + filename = os.path.basename(pdf_url.split("?")[0]) + if not filename: + return jsonify({"error": "Invalid pdf file"}), 400 + if not filename.lower().endswith(".pdf"): + return jsonify({"error": "Invalid pdf file"}), 400 + + pdf_path = os.path.join(OUTPUT_DIR, filename) + if not os.path.exists(pdf_path): + return jsonify({"error": "PDF not found"}), 404 + + try: + document = convert_pdf_to_text_editor_document(pdf_path) + return jsonify(document) + except FileNotFoundError: + return jsonify({"error": "Conversion failed"}), 500 + except subprocess.CalledProcessError as exc: + logger.error("[PDF-EDITOR] Conversion failed: %s", exc) + return jsonify({"error": "Conversion failed"}), 500 + except Exception as exc: # noqa: BLE001 + logger.error("[PDF-EDITOR] Unexpected conversion failure: %s", exc) + return jsonify({"error": "Conversion failed"}), 500 + + +@app.route("/api/pdf-editor/upload", methods=["POST"]) +def pdf_editor_upload() -> Any: + """Accept an edited PDF and save it so the preview can refresh.""" + file = request.files.get("file") + if not file: + return jsonify({"error": "Missing file"}), 400 + + job_id = str(uuid.uuid4()) + filename = f"{job_id}-edited.pdf" + output_path = os.path.join(OUTPUT_DIR, filename) + os.makedirs(OUTPUT_DIR, exist_ok=True) + file.save(output_path) + + logger.info("[PDF-EDITOR] uploaded edited PDF job_id=%s -> %s", job_id, filename) + return jsonify({"pdfUrl": f"/output/{filename}"}) + + +@app.route("/health", methods=["GET"]) +def health() -> Any: + return jsonify({"status": "ok", "engine": "pdflatex"}) + + +if __name__ == "__main__": + app.run(host="0.0.0.0", port=5000, debug=True) diff --git a/AI-Document-Generator-main/backend/briefs.py b/AI-Document-Generator-main/backend/briefs.py new file mode 100644 index 0000000000..758fcb34b0 --- /dev/null +++ b/AI-Document-Generator-main/backend/briefs.py @@ -0,0 +1,491 @@ +from __future__ import annotations + +import re +import json +from typing import Any, Dict, List, Optional + +from config import CLIENT_MODE, FAST_MODEL, SMART_MODEL, get_chat_model, logger +from langchain_utils import to_lc_messages +from prompts import brief_missing_info_system_prompt + + +BRIEF_SCHEMAS: Dict[str, Dict[str, Any]] = { + "resume": { + "field_order": [ + "name", + "contact", + "location", + "target_role", + "summary", + "work_history", + "education", + "skills", + "achievements", + "links", + "constraints", + ], + "labels": { + "name": ["name", "full name"], + "contact": ["contact", "contact info", "contact information", "email/phone"], + "location": ["location", "city/country"], + "target_role": ["target role", "role", "title", "headline"], + "summary": ["summary", "objective", "about"], + "work_history": ["experience", "work history", "roles"], + "education": ["education", "studies"], + "skills": ["skills", "stack"], + "achievements": ["achievements", "certifications", "awards"], + "links": ["links", "profiles", "linkedin/github"], + "constraints": ["constraints", "tone/length/style"], + }, + "questions": { + "name": "What's your name as you'd like it on the page?", + "contact": "How can someone reach you (email/phone)?", + "location": "Where are you based (or remote)?", + "target_role": "What role/title and industry are you aiming for?", + "summary": "Give me a 1–2 sentence summary about you.", + "work_history": "Recent roles: company, title, dates, location, and a few bullets with impact.", + "education": "Degree(s), school, and graduation year?", + "skills": "Key skills/stack (tech + relevant soft skills)?", + "achievements": "Awards/certifications/major achievements?", + "links": "Any LinkedIn/GitHub/portfolio links?", + "constraints": "Any tone/length constraints (ATS, one-page, etc.)?", + }, + "intro": "Hey! To build a strong resume, you can paste your old resume or just dump everything you rememberβ€”name, how to reach you, where you're based, what you're aiming for, your roles, education, skills, links. Share whatever you have and I'll work with it.", + }, + "invoice": { + "field_order": [ + "your_business", + "client", + "issue_date", + "due_date", + "line_items", + "currency", + "payment_terms", + "notes", + "constraints", + ], + "labels": { + "your_business": ["your business", "seller", "from"], + "client": ["client", "bill to"], + "issue_date": ["issue date", "invoice date"], + "due_date": ["due date"], + "line_items": ["line items", "services/items"], + "currency": ["currency"], + "payment_terms": ["payment terms"], + "notes": ["notes"], + "constraints": ["constraints", "layout/style"], + }, + "questions": { + "your_business": "Who is issuing the invoice (business name + contact)?", + "client": "Who is being billed (name + contact)?", + "issue_date": "Invoice issue date?", + "due_date": "Due date?", + "line_items": "Line items with description, qty, rate, tax (if any)?", + "currency": "Currency?", + "payment_terms": "Payment terms and payment methods?", + "notes": "Notes to include (late fees, thank you, PO #)?", + "constraints": "Branding/layout preferences?", + }, + "intro": "I'll draft an accurate invoice if I know who is billing, who is paying, and the line items. Paste an old invoice or list the details.", + }, +} + + +def classify_intent_with_llm(prompt: str, history: List[Dict[str, str]], current_latex: Optional[str], has_pdf: bool) -> Optional[Dict[str, Any]]: + """ + Use a small model to classify intent instead of brittle regex. + + Returns a dict like: + { + "documentType": "invoice|resume|contract|letter|report|form|document", + "action": "new|edit|question", + "allowFabrication": bool, + "wantsPdf": bool, + "hasEnoughInfo": bool, + "missingFields": [str], + "notes": str + } + """ + if CLIENT_MODE != "langchain": + logger.info("[INTENT] skip llm classify: client_mode=%s", CLIENT_MODE) + return None + + system = ( + "You classify user requests about documents. " + "Output strict JSON. " + "documentType must be one of: academic, agenda, brochure, business_card, case_study, checklist, " + "contract, creative, datasheet, document, flyer, invoice, letter, manual, menu, minutes, newsletter, " + "one_pager, poster, presentation, press_release, proposal, recipe, report, resume, timeline, whitepaper. " + "action: 'new' (make/generate), 'edit' (modify existing), 'question' (asking about it). " + "allowFabrication: true if the user invites making up/placeholder/dummy/random details " + "OR asks you to use your knowledge about a fictional/real character (e.g., 'use what you know about James Bond', " + "'make it for agent 007', 'create resume for Sherlock Holmes', etc.). " + "Basically, if they're NOT providing their own personal details and expect you to fill in from common knowledge or imagination, set this to true. " + "wantsPdf: true if they expect/gave permission to generate a PDF. " + "hasEnoughInfo: true if there is enough info to proceed without asking questions (or if allowFabrication is true). " + "missingFields: key details still needed (e.g., for invoice: seller, client, line items; resume: name, contact, work). " + "notes: short free-form note." + ) + + conversation = [{"role": "system", "content": system}] + # Trim history to keep request small + trimmed_history = history[-6:] if len(history) > 6 else history + for msg in trimmed_history: + if msg.get("content") and msg.get("role") in {"user", "assistant", "system"}: + conversation.append({"role": msg["role"], "content": msg["content"]}) + conversation.append({"role": "user", "content": prompt}) + + try: + llm = get_chat_model( + FAST_MODEL or SMART_MODEL, + max_tokens=800, + model_kwargs={"response_format": {"type": "json_object"}}, + ) + if not llm: + logger.info("[INTENT] skip llm classify: no LangChain client") + return None + response = llm.invoke(to_lc_messages(conversation)) + content = response.content + if not content: + logger.info("[INTENT] llm_classify empty content") + return None + data = json.loads(content) + # Normalize + doc_type = str(data.get("documentType") or "document").lower() + allowed_types = { + "academic", "agenda", "brochure", "business_card", "case_study", "checklist", + "contract", "creative", "datasheet", "document", "flyer", "invoice", "letter", + "manual", "menu", "minutes", "newsletter", "one_pager", "poster", "presentation", + "press_release", "proposal", "recipe", "report", "resume", "timeline", "whitepaper" + } + if doc_type not in allowed_types: + doc_type = "document" + action = str(data.get("action") or "new").lower() + if action not in {"new", "edit", "question"}: + action = "new" + result = { + "documentType": doc_type, + "action": action, + "allowFabrication": bool(data.get("allowFabrication")), + "wantsPdf": bool(data.get("wantsPdf", True)), + "hasEnoughInfo": bool(data.get("hasEnoughInfo", True)), + "missingFields": data.get("missingFields") or [], + "notes": data.get("notes") or "", + } + logger.info( + "[INTENT] llm_classify doc_type=%s action=%s allowFabrication=%s wantsPdf=%s hasEnoughInfo=%s missing=%s notes=%s", + result["documentType"], + result["action"], + result["allowFabrication"], + result["wantsPdf"], + result["hasEnoughInfo"], + result["missingFields"], + (result["notes"] or "")[:120], + ) + return result + except Exception as exc: # noqa: BLE001 + logger.error("[INTENT] LLM classify failed: %s", exc, exc_info=True) + return None + + +def detect_fabrication_opt_in(prompt: str, history: List[Dict[str, str]]) -> bool: + """ + Ask a small model to decide if the user has permitted invention of missing details. + + Returns True when the user says to make things up / whatever is fine / + no preference, even if they haven't provided concrete fields. + """ + if CLIENT_MODE != "langchain": + return False + + system = ( + "Decide if the user has explicitly permitted you to invent or make up missing details. " + "Reply with strict JSON: {\"allowFabrication\": true|false}. " + "Consider any user instruction like 'make it up', 'whatever you want', 'use dummy info', " + "'fabricate the rest', 'fill in anything' as permission. " + "Do not require specific keywords; infer intent from the conversation. " + "If unclear, set allowFabrication to false." + ) + + conversation = [{"role": "system", "content": system}] + trimmed_history = history[-8:] if len(history) > 8 else history + for msg in trimmed_history: + if msg.get("content") and msg.get("role") in {"user", "assistant", "system"}: + conversation.append({"role": msg["role"], "content": msg["content"]}) + conversation.append({"role": "user", "content": prompt}) + + try: + llm = get_chat_model( + FAST_MODEL or SMART_MODEL, + max_tokens=100, + model_kwargs={"response_format": {"type": "json_object"}}, + ) + if not llm: + return False + response = llm.invoke(to_lc_messages(conversation)) + content = response.content + if not content: + return False + data = json.loads(content) + return bool(data.get("allowFabrication")) + except Exception as exc: # noqa: BLE001 + logger.error("[INTENT] fabrication opt-in check failed: %s", exc) + return False + + +def _preprocess_intent( + prompt: str, + history: List[Dict[str, str]], + has_pdf: bool, + current_latex: Optional[str], +) -> Dict[str, Any]: + """ + Lightweight intent classifier used by /api/intent/check. + + It is intentionally heuristic-only to avoid extra model calls. The goal is to + decide whether we should proceed with PDF generation and whether it's OK to + fabricate placeholder content when the user explicitly asks for it. + """ + user_texts = [entry.get("content", "") for entry in history if entry.get("role") == "user"] + user_texts.append(prompt or "") + combined_text = " ".join([t for t in user_texts if t]).strip().lower() + + llm = classify_intent_with_llm(prompt, history, current_latex, has_pdf) + if llm: + return { + "wants_pdf": llm.get("wantsPdf", True), + "has_enough_info": llm.get("hasEnoughInfo", True), + "allow_makeup": llm.get("allowFabrication", False), + "document_type": llm.get("documentType"), + "missing_fields": llm.get("missingFields", []), + } + + # Fallback heuristics (only if no LLM) + avoid_pdf = bool(re.search(r"\b(no pdf|text only|markdown only|dont (make|generate) pdf)\b", combined_text)) + wants_pdf = not avoid_pdf or bool(current_latex) or has_pdf + has_meaningful_text = len(combined_text) > 20 + return { + "wants_pdf": wants_pdf, + "has_enough_info": bool(current_latex or has_pdf or has_meaningful_text), + "allow_makeup": False, + "document_type": None, + "missing_fields": [], + } + +def _extract_structured_fields(text: str, schema: Dict[str, Any]) -> Dict[str, str]: + """Naively parse user text to pull schema fields.""" + found: Dict[str, str] = {} + lower = text.lower() + + if schema.get("field_order") == BRIEF_SCHEMAS["resume"]["field_order"]: + work_matches = re.findall( + r"(?:experience|work history|role|company|position)\s*[:\-]\s*(.+?)(?=\n\n|\Z)", + text, + flags=re.IGNORECASE | re.DOTALL, + ) + if work_matches: + found["work_history"] = "\n".join(work_matches[:3]) + education_matches = re.findall( + r"(?:education|degree)\s*[:\-]\s*(.+?)(?=\n\n|\Z)", + text, + flags=re.IGNORECASE | re.DOTALL, + ) + if education_matches: + found["education"] = "\n".join(education_matches[:2]) + skills_match = re.search(r"(?:skills|stack)\s*[:\-]\s*(.+)", text, flags=re.IGNORECASE) + if skills_match: + found["skills"] = skills_match.group(1).strip() + + for field, labels in schema.get("labels", {}).items(): + for label in labels: + pattern = rf"{label}\s*[:\-]\s*(.+?)(?=\n[A-Z][a-zA-Z ]+[:\-]|\Z)" + match = re.search(pattern, text, flags=re.IGNORECASE | re.DOTALL) + if match: + found[field] = match.group(1).strip() + break + if not found.get("summary") and len(lower) < 200: + found["summary"] = text.strip() + return {k: v for k, v in found.items() if v} + + +def _format_missing_message( + doc_type: str, + schema: Dict[str, Any], + collected: Dict[str, str], + missing: List[str], + preface: Optional[str] = None, +) -> str: + """Fallback text asking the user for missing fields.""" + intro = schema.get("intro") or f"Need a few details to finish your {doc_type}." + lines = [intro] + if preface: + lines.append(preface) + if collected: + lines.append("Already have:") + for field, value in collected.items(): + label = schema.get("labels", {}).get(field, [field])[0] + lines.append(f"- {label}: {value}") + if missing: + lines.append("Still need:") + questions = schema.get("questions", {}) + for field in missing[:4]: + ask = questions.get(field) or f"{field}?" + lines.append(f"- {ask}") + lines.append("Partial info is fineβ€”share whatever you remember.") + return "\n".join(lines) + + +def _ai_missing_message( + doc_type: str, + schema: Dict[str, Any], + collected: Dict[str, str], + missing: List[str], +) -> Optional[str]: + """Let the model craft clarifying questions when available.""" + if CLIENT_MODE != "langchain" or not missing: + return None + + collected_lines = [f"- {schema.get('labels', {}).get(field, [field])[0]}: {value}" for field, value in collected.items()] + missing_labels = [schema.get("labels", {}).get(field, [field])[0] for field in missing] + user_text = "We already have:\n" + "\n".join(collected_lines) if collected_lines else "We have nothing yet." + user_text += "\nNeed to ask for: " + ", ".join(missing_labels) + if not collected_lines: + user_text += "\nInvite them to paste an old resume or dump all details if they have them." + + system_prompt = brief_missing_info_system_prompt(doc_type) + try: + llm = get_chat_model(SMART_MODEL, max_tokens=400) + if not llm: + return None + response = llm.invoke( + to_lc_messages( + [ + {"role": "system", "content": system_prompt}, + {"role": "user", "content": user_text}, + ] + ) + ) + return response.content + except Exception as exc: + logger.error("[AI] missing-questions failed: %s", exc) + return None + + +def gather_brief(doc_type: str, prompt: str, history: List[Dict[str, str]], current_latex: Optional[str] = None, has_pdf: bool = False) -> Dict[str, Any]: + """ + Determine whether we have enough structured details to generate without fabricating. + Returns needsInfo + a formatted message when details are missing, or a structured brief. + """ + classifier = classify_intent_with_llm(prompt, history, current_latex, has_pdf) + if classifier: + doc_type = classifier.get("documentType", doc_type) + logger.info( + "[BRIEF] using llm doc_type=%s allowFabrication=%s missing=%s hasEnoughInfo=%s wantsPdf=%s", + doc_type, + classifier.get("allowFabrication"), + classifier.get("missingFields"), + classifier.get("hasEnoughInfo"), + classifier.get("wantsPdf"), + ) + else: + logger.info("[BRIEF] llm classifier unavailable, using fallback schema doc_type=%s", doc_type) + + schema = BRIEF_SCHEMAS.get(doc_type) + if not schema: + return {"needsInfo": False, "structured_brief": None, "collected": {}, "missing": []} + + user_texts = [entry.get("content", "") for entry in history if entry.get("role") == "user"] + user_texts.append(prompt or "") + combined_text = "\n".join(user_texts) + collected = _extract_structured_fields(combined_text, schema) + missing = [field for field in schema.get("field_order", []) if field not in collected] + classifier_has_enough = bool(classifier.get("hasEnoughInfo")) if classifier else True + allow_makeup = bool(classifier.get("allowFabrication")) if classifier else False + if not allow_makeup: + allow_makeup = detect_fabrication_opt_in(prompt, history) + if classifier and classifier.get("missingFields"): + # If the model provided missing fields, respect that list. + missing = classifier.get("missingFields") or missing + + # If the user gave no usable content, do not allow fabrication shortcuts. + # Force the flow to ask for the required fields instead of silently proceeding. + missing_all_fields = len(missing) == len(schema.get("field_order", [])) + low_signal_request = not collected and len(combined_text.strip()) < 12 + if missing_all_fields and low_signal_request: + allow_makeup = False + + def has_minimum_resume(data: Dict[str, str]) -> bool: + has_name = bool(data.get("name")) + has_core = any(data.get(key) for key in ["work_history", "education", "skills", "contact", "target_role"]) + return has_name and has_core + + def has_minimum_invoice(data: Dict[str, str]) -> bool: + has_parties = data.get("your_business") and data.get("client") + has_items = bool(data.get("line_items")) + return bool(has_parties and has_items) + + has_minimum = True + if doc_type == "resume": + has_minimum = has_minimum_resume(collected) + elif doc_type == "invoice": + has_minimum = has_minimum_invoice(collected) + + # Decide if we must pause to ask for details. Avoid regex "ready" guesses; + # rely on the classifier's allowFabrication flag and collected data. + must_ask_first = bool(missing) and ((not allow_makeup and not has_minimum) or not classifier_has_enough) + if must_ask_first: + preface = None + if doc_type == "resume" and not has_minimum: + preface = ( + "I only have a tiny bit so far. I need at least your name plus one of: contact, " + "a role snippet, education, skills, or target role." + ) + if doc_type == "invoice" and not has_minimum: + preface = "Need who is billing, who is paying, and the line items so I don't invent details." + logger.info( + "[BRIEF] gating doc_type=%s missing=%s has_minimum=%s allowFabrication=%s", + doc_type, + missing, + has_minimum, + allow_makeup, + ) + message = _ai_missing_message(doc_type, schema, collected, missing) or _format_missing_message( + doc_type, schema, collected, missing, preface=preface + ) + message += "\nIf you'd like me to invent anything you didn't share, just say so." + return { + "needsInfo": True, + "message": message, + "collected": collected, + "missing": missing, + "allowFabrication": allow_makeup, + } + + # If fabrication is allowed but fields are missing, let downstream generation + # know which areas to fill in plausibly. + fabrication_hint = "" + if allow_makeup and missing: + fabrication_hint = "\n\nIf details are absent, invent plausible, clearly fictional details for: " + ", ".join(missing) + "." + + structured_lines = [] + for field in schema.get("field_order", []): + value = collected.get(field) + if value: + label = schema.get("labels", {}).get(field, [field])[0] + structured_lines.append(f"{label}: {value}") + structured_brief = "\n".join(structured_lines) + if fabrication_hint: + structured_brief = (structured_brief + fabrication_hint).strip() + if combined_text.strip(): + structured_brief = (structured_brief + "\n\nRaw user notes:\n" + combined_text).strip() + + return { + "needsInfo": False, + "structured_brief": structured_brief or None, + "collected": collected, + "missing": missing, + "allowFabrication": allow_makeup, + } + + +__all__ = ["gather_brief", "BRIEF_SCHEMAS", "_preprocess_intent"] diff --git a/AI-Document-Generator-main/backend/config.py b/AI-Document-Generator-main/backend/config.py new file mode 100644 index 0000000000..4ab194f19a --- /dev/null +++ b/AI-Document-Generator-main/backend/config.py @@ -0,0 +1,81 @@ +import logging +import os +from typing import Optional + + +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + +BASE_DIR = os.path.dirname(os.path.abspath(__file__)) +OUTPUT_DIR = os.path.join(BASE_DIR, "output") +DATA_DIR = os.path.join(BASE_DIR, "data") +STYLE_DB_PATH = os.path.join(DATA_DIR, "user_styles.json") +TEMPLATE_DB_PATH = os.path.join(DATA_DIR, "user_templates.json") +VERSIONS_DB_PATH = os.path.join(DATA_DIR, "versions.json") + +os.makedirs(OUTPUT_DIR, exist_ok=True) +os.makedirs(DATA_DIR, exist_ok=True) + +OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY") +OPENAI_BASE_URL = os.environ.get("OPENAI_BASE_URL") +# Default to GPT-5.1 for full document generation (smart model). +# Allow override via SMART_MODEL or legacy OPENAI_MODEL. +SMART_MODEL = os.environ.get("SMART_MODEL") or os.environ.get("OPENAI_MODEL") or "gpt-5.1" +# Default to the nano/ultra-fast tier for intent/pre checks (fast model). +# Allow override via FAST_MODEL or legacy FAST_INTENT_MODEL. +FAST_MODEL = os.environ.get("FAST_MODEL") or os.environ.get("FAST_INTENT_MODEL") or "gpt-4.1-nano" + +CLIENT_MODE: Optional[str] = None +LANGCHAIN_AVAILABLE = False +_ChatOpenAI = None +STREAMING_ENABLED = os.environ.get("AI_STREAMING", "true").lower() not in {"0", "false", "no"} +if OPENAI_BASE_URL and "ollama" in OPENAI_BASE_URL and "AI_STREAMING" not in os.environ: + STREAMING_ENABLED = False + +if OPENAI_API_KEY: + try: + from langchain_openai import ChatOpenAI # type: ignore + + _ChatOpenAI = ChatOpenAI + LANGCHAIN_AVAILABLE = True + CLIENT_MODE = "langchain" + except Exception as client_exc: # pragma: no cover - import guard + logger.warning("LangChain OpenAI init failed: %s", client_exc) + +if CLIENT_MODE == "langchain": + logger.info("AI mode: LIVE (fast_model=%s smart_model=%s)", FAST_MODEL, SMART_MODEL) +else: + logger.info("AI mode: MOCK (no OpenAI key or LangChain init failure)") + + +def get_chat_model( + model_name: str, + streaming: bool = False, + max_tokens: Optional[int] = None, + model_kwargs: Optional[dict] = None, +): + if not LANGCHAIN_AVAILABLE or not _ChatOpenAI: + return None + kwargs = {"model": model_name, "api_key": OPENAI_API_KEY, "streaming": streaming} + if max_tokens is not None: + kwargs["max_tokens"] = max_tokens + if model_kwargs: + kwargs["model_kwargs"] = model_kwargs + return _ChatOpenAI(**kwargs) + +__all__ = [ + "logger", + "OUTPUT_DIR", + "DATA_DIR", + "STYLE_DB_PATH", + "TEMPLATE_DB_PATH", + "VERSIONS_DB_PATH", + "OPENAI_API_KEY", + "OPENAI_BASE_URL", + "SMART_MODEL", + "CLIENT_MODE", + "LANGCHAIN_AVAILABLE", + "get_chat_model", + "FAST_MODEL", + "STREAMING_ENABLED", +] diff --git a/AI-Document-Generator-main/backend/document_types.py b/AI-Document-Generator-main/backend/document_types.py new file mode 100644 index 0000000000..965bfc5ad4 --- /dev/null +++ b/AI-Document-Generator-main/backend/document_types.py @@ -0,0 +1,57 @@ +from __future__ import annotations + +from typing import List, Tuple + + +KEYWORDS: List[Tuple[str, str]] = [ + ("business card", "business_card"), + ("business-card", "business_card"), + ("card", "business_card"), + ("recipe", "recipe"), + ("cookbook", "recipe"), + ("menu", "menu"), + ("flyer", "flyer"), + ("brochure", "brochure"), + ("poster", "poster"), + ("slide", "presentation"), + ("deck", "presentation"), + ("presentation", "presentation"), + ("pitch", "presentation"), + ("whitepaper", "whitepaper"), + ("datasheet", "datasheet"), + ("case study", "case_study"), + ("press release", "press_release"), + ("agenda", "agenda"), + ("minutes", "minutes"), + ("checklist", "checklist"), + ("newsletter", "newsletter"), + ("proposal", "proposal"), + ("one-pager", "one_pager"), + ("one pager", "one_pager"), + ("invoice", "invoice"), + ("resume", "resume"), + ("cv", "resume"), + ("contract", "contract"), + ("agreement", "contract"), + ("letter", "letter"), + ("report", "report"), + ("paper", "academic"), + ("research", "academic"), + ("thesis", "academic"), + ("poem", "creative"), + ("manual", "manual"), + ("timeline", "timeline"), +] + + +def detect_document_type(prompt: str, latex_code: str | None = None) -> str: + """Heuristic classifier for document types based on prompt/latex text.""" + text = (prompt or "").lower() + latex_text = (latex_code or "").lower() + for keyword, label in KEYWORDS: + if keyword in text or keyword in latex_text: + return label + return "document" + + +__all__ = ["detect_document_type"] diff --git a/AI-Document-Generator-main/backend/langchain_utils.py b/AI-Document-Generator-main/backend/langchain_utils.py new file mode 100644 index 0000000000..42a58f8ef1 --- /dev/null +++ b/AI-Document-Generator-main/backend/langchain_utils.py @@ -0,0 +1,22 @@ +from __future__ import annotations + +from typing import Any, Dict, List + +from langchain_core.messages import AIMessage, HumanMessage, SystemMessage + + +def to_lc_messages(messages: List[Dict[str, Any]]): + lc_messages = [] + for msg in messages: + role = msg.get("role") + content = msg.get("content") + if role == "system": + lc_messages.append(SystemMessage(content=content)) + elif role == "assistant": + lc_messages.append(AIMessage(content=content)) + else: + lc_messages.append(HumanMessage(content=content)) + return lc_messages + + +__all__ = ["to_lc_messages"] diff --git a/AI-Document-Generator-main/backend/latex_utils.py b/AI-Document-Generator-main/backend/latex_utils.py new file mode 100644 index 0000000000..223f596045 --- /dev/null +++ b/AI-Document-Generator-main/backend/latex_utils.py @@ -0,0 +1,469 @@ +from __future__ import annotations + +import re +from functools import lru_cache +from typing import List, Optional + +ALLOWED_LATEX_PACKAGES = { + "geometry", + "xcolor", + "tabularx", + "paracol", + "multicol", + "longtable", + "setspace", + "enumitem", + "titlesec", + "array", + "inputenc", + "fontenc", + "tikz", +} + + +def _strip_body_content(body: str) -> str: + """ + Remove user data while keeping layout/structure commands. + Keeps \begin/\end blocks, command scaffolding, and drops plain text. + """ + lines: List[str] = [] + for line in body.splitlines(): + stripped = line.strip() + if not stripped: + lines.append("") + continue + if stripped.startswith("%"): + continue + if "\\begin" in stripped or "\\end" in stripped: + lines.append(line) + continue + if stripped.startswith("\\"): + line_no_comments = line.split("%", 1)[0] + line_sections = re.sub( + r"(\\(?:section|subsection|subsubsection|paragraph|subparagraph|chapter|part)\*?)\{[^}]*\}", + r"\\1{}", + line_no_comments, + ) + line_items = re.sub(r"^\\item.*", r"\\item {}", line_sections) + line_text_cmds = re.sub( + r"\\text(?:bf|it|tt|sc|sf|normal|emph)\{[^}]*\}", + lambda match: match.group(0).split("{")[0] + "{}", + line_items, + ) + cleaned = re.sub(r"(? str: + """Keep layout-defining LaTeX while stripping user text.""" + if not latex_code: + return "" + + preamble, body = "", latex_code + split_doc = latex_code.split(r"\begin{document}", 1) + if len(split_doc) == 2: + preamble, body = split_doc + sanitized_body = _strip_body_content(body) + + hint = f"{preamble}\n% --- layout only (data stripped) ---\n{sanitized_body}" + return hint if max_chars is None else hint[:max_chars] + + +@lru_cache(maxsize=64) +def _word_to_int(word: str) -> Optional[int]: + """Convert simple English number words to int (0-100).""" + words = { + "zero": 0, + "one": 1, + "two": 2, + "three": 3, + "four": 4, + "five": 5, + "six": 6, + "seven": 7, + "eight": 8, + "nine": 9, + "ten": 10, + "twenty": 20, + "thirty": 30, + "forty": 40, + "fifty": 50, + "sixty": 60, + "seventy": 70, + "eighty": 80, + "ninety": 90, + "hundred": 100, + } + return words.get(word.strip().lower()) + + +def _sanitize_color_mix(match: re.Match[str]) -> str: + token = match.group(1) + if token.isdigit(): + val = int(token) + else: + converted = _word_to_int(token) + if converted is None: + digits = "".join(ch for ch in token if ch.isdigit()) + val = int(digits) if digits else 80 + else: + val = converted + val = max(0, min(100, val)) + return f"!{val}!" + + +def sanitize_latex(latex_code: str) -> str: + """Normalize invalid xcolor syntax like '!eighty!' to '!80!'.""" + if not latex_code: + return latex_code + return re.sub(r"!\s*([A-Za-z0-9]+)\s*!", _sanitize_color_mix, latex_code) + + +def strip_missing_packages(latex_code: str) -> str: + """Remove packages unavailable in the runtime environment.""" + if not latex_code: + return latex_code + code = latex_code + code = re.sub(r"^\\usepackage\{siunitx\}\s*$", "", code, flags=re.MULTILINE) + code = re.sub(r"\\sisetup\{[^}]*\}", "", code, flags=re.DOTALL) + code = re.sub(r"\\num\{([^}]*)\}", r"\\1", code) + code = re.sub( + r"^\\(setmainfont|setsansfont|setmonofont|newfontfamily)\b.*$", + "", + code, + flags=re.MULTILINE, + ) + + def _filter_packages(match: re.Match[str]) -> str: + options = match.group(1) or "" + packages = [pkg.strip() for pkg in match.group(2).split(",") if pkg.strip()] + allowed = [pkg for pkg in packages if pkg in ALLOWED_LATEX_PACKAGES] + if not allowed: + return "" + return f"\\usepackage{options}{{{', '.join(allowed)}}}" + + return re.sub( + r"^\\usepackage(\[[^\]]*\])?\{([^}]*)\}\s*$", + _filter_packages, + code, + flags=re.MULTILINE, + ) + + +def remove_leading_pagebreaks(latex_code: str) -> str: + """Strip explicit page breaks at the start of the document body.""" + if not latex_code: + return latex_code + parts = latex_code.split(r"\begin{document}", 1) + if len(parts) == 2: + preamble, body = parts + cleaned_body = re.sub( + r"^\s*(\\(newpage|clearpage|pagebreak|vfill)\b\s*)+", + "\n", + body, + flags=re.IGNORECASE | re.MULTILINE, + ) + return f"{preamble}\\begin{{document}}{cleaned_body}" + return re.sub( + r"^\s*(\\(newpage|clearpage|pagebreak|vfill)\b\s*)+", + "\n", + latex_code, + flags=re.IGNORECASE | re.MULTILINE, + ) + + +def strip_leading_pagebreaks(latex_code: str) -> str: + """Drop accidental leading page breaks that cause empty first pages.""" + if not latex_code: + return latex_code + parts = latex_code.split(r"\begin{document}", 1) + if len(parts) == 2: + preamble, body = parts + cleaned_body = re.sub( + r"^\s*(\\clearpage|\\newpage|\\pagebreak|\\vfill)+\s*", + "", + body, + flags=re.MULTILINE, + ) + return f"{preamble}\\begin{{document}}{cleaned_body}" + return re.sub( + r"^\s*(\\clearpage|\\newpage|\\pagebreak|\\vfill)+\s*", + "", + latex_code, + flags=re.MULTILINE, + ) + + +def fix_tabular_row_endings(latex_code: str) -> str: + """Ensure tabular environments close rows before \\end{tabular}.""" + pattern = re.compile(r"(&[^\n]*)\n\\end{tabular}", re.MULTILINE) + return pattern.sub(r"\\1 \\\\ \n\\end{tabular}", latex_code) + +def strip_placeholder_rules(latex_code: str) -> str: + """Remove placeholder boxes like \\rule/\\colorbox used as fake images.""" + code = re.sub(r"\\rule\s*\{\s*[\d\.]+[a-zA-Z]*\s*\}\s*\{\s*[\d\.]+[a-zA-Z]*\s*\}", "", latex_code) + code = re.sub(r"\\fcolorbox\{[^}]*\}\{[^}]*\}\{[^}]*\}", "", code) + code = re.sub(r"\\colorbox\{[^}]*\}\{[^}]*\}", "", code) + # Strip simple tikz pictures that are just boxes/fills + code = re.sub( + r"\\begin\{tikzpicture\}[\s\S]*?\\end\{tikzpicture\}", + "", + code, + flags=re.MULTILINE, + ) + return code + + +def strip_number_grouping_junk(latex_code: str) -> str: + """Remove stray siunitx options text that may leak into the document body.""" + if not latex_code: + return latex_code + # Drop standalone lines/paragraphs that look like siunitx option lists (common when chunks split) + return re.sub( + r"(?im)^\s*,\s*(group-minimum-digits|detect-all|table-number-alignment|round-mode|round-precision)\b.*$", + "", + latex_code, + ) + + +def rebalance_invoice_tables(latex_code: str) -> str: + """Use wrapped columns for common invoice tables to avoid overflow.""" + if not latex_code: + return latex_code + + # Legacy 4-col invoices (Item, Desc, Price, Total) + code = latex_code.replace( + r"\\begin{tabularx}{\\textwidth}{@{}l l r r@{}}", + r"\\begin{tabularx}{\\textwidth}{@{}>{\\raggedright\\arraybackslash}p{0.30\\textwidth}>{\\raggedright\\arraybackslash}X>{\\raggedleft\\arraybackslash}p{1.5cm}>{\\raggedleft\\arraybackslash}p{2.3cm}@{}}", + ) + + # Current 5-col invoices (Item, Description, Qty, Unit, Line Total) + wrapped_invoice_five = ( + r"@{}" + r">{\\raggedright\\arraybackslash}p{0.16\\textwidth}" + r">{\\raggedright\\arraybackslash}p{0.50\\textwidth}" + r">{\\raggedleft\\arraybackslash}p{0.09\\textwidth}" + r">{\\raggedleft\\arraybackslash}p{0.12\\textwidth}" + r">{\\raggedleft\\arraybackslash}p{0.13\\textwidth}" + r"@{}" + ) + + five_col_patterns = [ + ( + # tabularx with first col l/c, X desc, then three p{} numeric cols (matches default invoice template) + r"(\\begin{tabularx}\{\s*\\textwidth\s*\}\{)\s*@?\{\}?\s*[cl]\s+X\s+p\{[^}]+\}\s+p\{[^}]+\}\s+p\{[^}]+\}\s*@?\{\}?\s*(\})", + r"\1" + wrapped_invoice_five + r"\2", + ), + ( + # longtable version of the same layout (after upgrades) + r"(\\begin{longtable}\{)\s*@?\{\}?\s*[cl]\s+X\s+p\{[^}]+\}\s+p\{[^}]+\}\s+p\{[^}]+\}\s*@?\{\}?\s*(\})", + r"\1" + wrapped_invoice_five + r"\2", + ), + ] + + for pattern, replacement in five_col_patterns: + code = re.sub(pattern, replacement, code, flags=re.IGNORECASE) + + return code + + +def normalize_tabular_like_begins(latex_code: str) -> str: + """ + Fix common malformed tabular/tabularx/longtable begins where the colspec + is not passed as a braced argument (e.g. `\\begin{tabularx}\\textwidth{...}` + or `\\begin{tabularx}{\\textwidth}\\ItemsColSpec`). + """ + if not latex_code: + return latex_code + + code = latex_code + + # \begin{tabularx}\textwidth{...} -> \begin{tabularx}{\textwidth}{...} + code = re.sub( + r"\\begin{tabularx}\s*\\textwidth\s*\{([^}]*)\}", + lambda m: f"\\begin{{tabularx}}{{\\textwidth}}{{{m.group(1).strip()}}}", + code, + ) + + # \begin{tabularx}{\textwidth}\ItemsColSpec -> wrap colspec in braces + code = re.sub( + r"\\begin{tabularx}\s*\{\s*\\textwidth\s*\}\s*\\([A-Za-z@][\w@]*)", + lambda m: f"\\begin{{tabularx}}{{\\textwidth}}{{\\{m.group(1)}}}", + code, + ) + + # \begin{tabularx}{\textwidth}\colspecliteral -> wrap literal spec + code = re.sub( + r"\\begin{tabularx}\s*\{\s*\\textwidth\s*\}\s*([@A-Za-z].*)", + lambda m: f"\\begin{{tabularx}}{{\\textwidth}}{{{m.group(1).strip()}}}", + code, + ) + + # \begin{tabular}\colspecliteral OR \begin{longtable}\colspecliteral + def _wrap_simple(env: str, text: str) -> str: + return re.sub( + rf"\\begin{{{env}}}\s*([@A-Za-z].*)", + lambda m: f"\\begin{{{env}}}{{{m.group(1).strip()}}}", + text, + ) + + code = _wrap_simple("tabular", code) + code = _wrap_simple("longtable", code) + return code + + +def ensure_longtable_support(latex_code: str) -> str: + """ + Guarantee longtable availability and default centering. + + - Injects \\usepackage{longtable} if missing. + - Sets \\LTleft/\\LTright to 0pt so longtable spans the text width without manual centering. + """ + if not latex_code: + return latex_code + + code = latex_code + if r"\usepackage{longtable}" not in code: + code = re.sub( + r"(\\documentclass[^\n]*\n)", + r"\1\\usepackage{longtable}\n", + code, + count=1, + ) + if r"\setlength\LTleft" not in code: + # Use a lambda so backslashes are treated literally (avoid \L escape errors). + code = re.sub( + r"(\\usepackage\{longtable\}[^\n]*\n)", + lambda m: f"{m.group(1)}\\setlength\\LTleft{{0pt}}\n\\setlength\\LTright{{0pt}}\n", + code, + count=1, + ) + return code + + +def _normalize_alignment_to_wrapped_columns(spec: str) -> str: + """ + Convert simple l/c/r specs to wrapped p-columns that respect text width. + Keeps existing p/m/b/X columns unchanged. + """ + if re.search(r"[pmb]\{|\bX\b", spec): + return spec + + cols = [ch for ch in spec if ch in ("l", "c", "r")] + if not cols: + return spec + + width = max(0.05, min(0.98, 0.98 / len(cols))) + parts: List[str] = [] + for ch in cols: + if ch == "r": + parts.append(r">{\raggedleft\arraybackslash}p{" + f"{width:.3f}\\textwidth" + "}") + else: + parts.append(r">{\raggedright\arraybackslash}p{" + f"{width:.3f}\\textwidth" + "}") + return "@{}" + "".join(parts) + "@{}" + + +def upgrade_tabular_tables_to_longtable(latex_code: str) -> str: + """ + Replace table+tabular blocks with longtable so large tables break across pages, + stay centered, and repeat headers on each page. + """ + if not latex_code: + return latex_code + + pattern = re.compile( + r"\\begin{table}.*?\\begin{tabular}\{([^}]*)\}(.*?)\\end{tabular}.*?\\end{table}", + re.DOTALL, + ) + + def _build_longtable(match: re.Match[str]) -> str: + align_spec = match.group(1) + body = match.group(2).strip() + normalized_spec = _normalize_alignment_to_wrapped_columns(align_spec) + + header_block = "" + body_block = body + + hline_split = re.split(r"\\hline", body, maxsplit=1) + if len(hline_split) == 2: + header_block = hline_split[0].strip() + r"\\\hline" + body_block = hline_split[1].lstrip() + else: + first_row_split = re.split(r"\\\\", body, maxsplit=1) + header_block = (first_row_split[0].strip() + r"\\") if first_row_split else "" + body_block = first_row_split[1].lstrip() if len(first_row_split) == 2 else body + + header_block = header_block.strip() + body_block = body_block.strip() + + return ( + "\n\\setlength\\LTleft{0pt}\n" + "\\setlength\\LTright{0pt}\n" + f"\\begin{{longtable}}{{{normalized_spec}}}\n" + f"{header_block}\n" + "\\endfirsthead\n" + f"{header_block}\n" + "\\endhead\n" + f"{body_block}\n" + "\\end{longtable}\n" + ) + + return pattern.sub(_build_longtable, latex_code) + + +def clean_generated_latex(latex_code: str) -> str: + """Apply all sanitizers used both for compilation and template storage.""" + return rebalance_invoice_tables( + upgrade_tabular_tables_to_longtable( + ensure_longtable_support( + normalize_tabular_like_begins( + strip_placeholder_rules( + strip_number_grouping_junk( + fix_tabular_row_endings( + strip_leading_pagebreaks( + remove_leading_pagebreaks( + strip_missing_packages( + sanitize_latex( + ensure_full_latex_document(latex_code) + ) + ) + ) + ) + ) + ) + ) + ) + ) + ) + ) + + +def ensure_full_latex_document(text: str) -> str: + """Trim output to a single LaTeX document starting at \\documentclass and ending at \\end{document}.""" + if not text: + return text + start = text.find(r"\documentclass") + end = text.rfind(r"\end{document}") + if start == -1 or end == -1: + return text + end += len(r"\end{document}") + return text[start:end] + + +__all__ = [ + "extract_layout_hint", + "sanitize_latex", + "strip_missing_packages", + "remove_leading_pagebreaks", + "strip_leading_pagebreaks", + "fix_tabular_row_endings", + "rebalance_invoice_tables", + "clean_generated_latex", + "ensure_full_latex_document", +] diff --git a/AI-Document-Generator-main/backend/pdf_text_editor.py b/AI-Document-Generator-main/backend/pdf_text_editor.py new file mode 100644 index 0000000000..43a0ef56d2 --- /dev/null +++ b/AI-Document-Generator-main/backend/pdf_text_editor.py @@ -0,0 +1,491 @@ +from __future__ import annotations + +import base64 +import os +import re +import subprocess +import tempfile +import xml.etree.ElementTree as ET +from typing import Any, Dict, List, Optional + +from config import logger + + +def _safe_float(value: Optional[str], fallback: float = 0.0) -> float: + """Convert an attribute value to float while handling bad input.""" + try: + if value is None: + return fallback + return float(value) + except (TypeError, ValueError): + return fallback + + +def _read_image_as_data_url(path: str) -> Optional[str]: + """Return a data URL for the image if it exists.""" + if not os.path.exists(path): + return None + mime = "image/png" + _, ext = os.path.splitext(path) + if ext.lower() in {".jpg", ".jpeg"}: + mime = "image/jpeg" + elif ext.lower() == ".gif": + mime = "image/gif" + try: + with open(path, "rb") as img_handle: + encoded = base64.b64encode(img_handle.read()).decode("ascii") + return f"data:{mime};base64,{encoded}" + except OSError as exc: + logger.warning("[PDF-EDITOR] Failed to read image %s: %s", path, exc) + return None + + +def _parse_fonts(root: ET.Element) -> List[Dict[str, Any]]: + fonts: List[Dict[str, Any]] = [] + for spec in root.findall(".//fontspec"): + font_id = spec.attrib.get("id") + base_name = spec.attrib.get("family") + size = _safe_float(spec.attrib.get("size"), 12.0) + color = spec.attrib.get("color") + name_lower = (base_name or "").lower() + flags = 0 + if "bold" in name_lower: + flags |= 0x100 # ForceBold + if "italic" in name_lower or "oblique" in name_lower: + flags |= 0x40 # Italic + fonts.append( + { + "id": font_id, + "uid": font_id, + "baseName": base_name, + "embedded": True, + "program": None, + "programFormat": None, + "webProgram": None, + "webProgramFormat": None, + "pdfProgram": None, + "pdfProgramFormat": None, + "ascent": size, + "descent": -size * 0.25, + "unitsPerEm": max(size, 1), + "standard14Name": None, + "color": color, + "fontDescriptorFlags": flags or None, + } + ) + return fonts + + +def _parse_color_components(color: Optional[str]) -> Optional[List[float]]: + """Convert a hex/rgb color string into normalized RGB components.""" + if not color: + return None + + color = color.strip() + hex_match = re.fullmatch(r"#?([0-9a-fA-F]{6})", color) + short_hex_match = re.fullmatch(r"#?([0-9a-fA-F]{3})", color) + rgb_match = re.fullmatch(r"rgb\(\s*(\d{1,3})\s*,\s*(\d{1,3})\s*,\s*(\d{1,3})\s*\)", color, re.IGNORECASE) + + if hex_match: + hex_value = hex_match.group(1) + r = int(hex_value[0:2], 16) + g = int(hex_value[2:4], 16) + b = int(hex_value[4:6], 16) + return [r / 255.0, g / 255.0, b / 255.0] + + if short_hex_match: + hex_value = short_hex_match.group(1) + r = int(hex_value[0] * 2, 16) + g = int(hex_value[1] * 2, 16) + b = int(hex_value[2] * 2, 16) + return [r / 255.0, g / 255.0, b / 255.0] + + if rgb_match: + r = min(max(int(rgb_match.group(1)), 0), 255) + g = min(max(int(rgb_match.group(2)), 0), 255) + b = min(max(int(rgb_match.group(3)), 0), 255) + return [r / 255.0, g / 255.0, b / 255.0] + + return None + + +# -------------------- +# Table normalization +# -------------------- + +def _cluster(values: List[float], tol: float) -> List[List[float]]: + clusters: List[List[float]] = [] + for v in sorted(values): + if not clusters or abs(v - clusters[-1][-1]) > tol: + clusters.append([v]) + else: + clusters[-1].append(v) + return clusters + +def _dedupe_by_xy_text(elements: List[Dict[str, Any]], eps: float = 1.0) -> List[Dict[str, Any]]: + """ + Dedupe using quantized x,y and normalized text (ignores width/height jitter). + Keeps the better scoring text; if equal text, keeps the first. + """ + if not elements: + return elements + + def _key(el: Dict[str, Any]) -> tuple[int, int, str]: + x = el.get("x") or 0.0 + y = el.get("y") or 0.0 + t = (el.get("text") or "").strip().replace("\u00a0", " ") + return (int(round(x / eps)), int(round(y / eps)), t) + + def _score_text_global(t: str) -> tuple[int, int, int]: + stripped = t.strip() + has_currency = 1 if any(sym in stripped for sym in ("$", "€", "Β£", "Β₯")) else 0 + non_space = sum(1 for ch in stripped if not ch.isspace()) + digits = sum(1 for ch in stripped if ch.isdigit()) + return (has_currency, non_space, digits) + + deduped: Dict[tuple[int, int, str], Dict[str, Any]] = {} + for el in elements: + key = _key(el) + existing = deduped.get(key) + if existing is None: + deduped[key] = el + continue + t_new = key[2] + t_old = (existing.get("text") or "").strip().replace("\u00a0", " ") + score_new = _score_text_global(t_new) + score_old = _score_text_global(t_old) + if score_new > score_old: + deduped[key] = el + return list(deduped.values()) + + +def _detect_table_region(text_elements: List[Dict[str, Any]], page_width: float) -> Optional[Dict[str, Any]]: + """ + Header-agnostic table detection via x clustering. + Returns dict with anchors, boundaries, observed_left/right, y_min/y_max. + """ + candidates = [ + el + for el in text_elements + if el.get("text") not in (None, "") + and isinstance(el.get("x"), (int, float)) + and isinstance(el.get("y"), (int, float)) + and isinstance(el.get("height"), (int, float)) + ] + if len(candidates) < 8: + return None + + heights = [c["height"] for c in candidates if c.get("height")] + if not heights: + return None + med_h = sorted(heights)[len(heights) // 2] + short_candidates = [c for c in candidates if c["height"] <= med_h * 1.8] + if len(short_candidates) < 8: + return None + + x_centers = [c["x"] + (c.get("width") or 0) * 0.5 for c in short_candidates] + x_clusters = _cluster(x_centers, tol=12.0) + x_clusters = [c for c in x_clusters if len(c) >= 3] + if len(x_clusters) < 4: + return None + + anchors = [sum(c) / len(c) for c in x_clusters] + anchors.sort() + + y_vals = sorted(c["y"] for c in short_candidates) + y_clusters = _cluster(y_vals, tol=3.0) + if len(y_clusters) < 3: + return None + y_clusters.sort(key=lambda c: len(c), reverse=True) + y_min = min(y_clusters[0]) + y_max = max(y_clusters[0]) + + min_anchor = min(anchors) + max_anchor = max(anchors) + PAD = 12.0 + + band_elems = [] + for el in short_candidates: + cx = el["x"] + (el.get("width") or 0) * 0.5 + if y_min - PAD <= el["y"] <= y_max + PAD and (min_anchor - PAD) <= cx <= (max_anchor + PAD): + band_elems.append(el) + if not band_elems: + return None + observed_left = min(n["x"] for n in band_elems) + observed_right = max(n["x"] + (n.get("width") or 0) for n in band_elems) + + raw_bounds: List[float] = [] + for i, ax in enumerate(anchors): + if i == 0: + gap = anchors[1] - anchors[0] + raw_bounds.append(ax - gap * 0.5) + else: + raw_bounds.append((anchors[i - 1] + ax) * 0.5) + gap_last = anchors[-1] - anchors[-2] if len(anchors) > 1 else 40.0 + raw_bounds.append(anchors[-1] + gap_last * 0.5) + + # translate boundaries to align left edge; no scaling to preserve spacing + delta = observed_left - raw_bounds[0] + boundaries = [b + delta for b in raw_bounds] + + info = { + "anchors": anchors, + "boundaries": boundaries, + "observed_left": observed_left, + "observed_right": observed_right, + "y_min": y_min, + "y_max": y_max, + } + if os.getenv("PDF_EDITOR_TABLE_DEBUG"): + logger.debug( + "[PDF-EDITOR] table detected anchors=%s boundaries=%s y=(%.2f, %.2f) span=(%.2f, %.2f)", + anchors, + boundaries, + y_min, + y_max, + observed_left, + observed_right, + ) + span = boundaries[-1] - boundaries[0] + if span <= 0 or page_width <= 0: + return None + target_left = max(0.0, (page_width - span) * 0.5) + offset = target_left - boundaries[0] + info.update({"offset": offset, "page_width": page_width}) + return info + + +def _snap_table_elements(text_elements: List[Dict[str, Any]], info: Dict[str, Any]) -> List[Dict[str, Any]]: + anchors = info["anchors"] + base_boundaries = info["boundaries"] + offset = info.get("offset", 0.0) + boundaries = [b + offset for b in base_boundaries] + y_min = info["y_min"] + y_max = info["y_max"] + left = info["observed_left"] + offset + right = info["observed_right"] + offset + + def _assign_col(cx: float) -> int: + return min(range(len(anchors)), key=lambda i: abs(anchors[i] - cx)) + + EPS = 1.0 + PAD = 6.0 + + for el in text_elements: + x = el.get("x") + w = el.get("width") or 0 + y = el.get("y") + if not isinstance(x, (int, float)) or not isinstance(y, (int, float)): + continue + cx = x + w * 0.5 + offset + if not (left - PAD <= cx <= right + PAD and y_min - PAD <= y <= y_max + PAD): + continue + + col = _assign_col(cx - offset) + col_left = boundaries[col] + col_right = boundaries[col + 1] + + new_left = x + offset + new_right = x + w + offset + if new_left < col_left - EPS: + new_left = col_left + if new_right > col_right + EPS: + new_right = col_right + if new_right <= new_left: + mid = (col_left + col_right) * 0.5 + new_left = mid - 0.5 + new_right = mid + 0.5 + + el["x"] = new_left + el["width"] = max(1.0, new_right - new_left) + el["textMatrix"] = [1, 0, 0, 1, el["x"], el["y"]] + + return text_elements + + +def _parse_page(page_elem: ET.Element, base_dir: str, font_colors: Dict[str, Optional[str]]) -> Dict[str, Any]: + page_width = _safe_float(page_elem.attrib.get("width"), 612.0) + page_height = _safe_float(page_elem.attrib.get("height"), 792.0) + text_elements: List[Dict[str, Any]] = [] + image_elements: List[Dict[str, Any]] = [] + + # Cluster near-identical text draws on the same baseline and keep the best candidate. + EPS = 1.0 + best_by_pos: Dict[tuple[int, int], Dict[str, Any]] = {} + + def _q(value: float) -> int: + try: + return int(round(value / EPS)) + except Exception: + return 0 + + def _score_text(t: str) -> tuple[int, int, int]: + stripped = t.strip() + has_currency = 1 if any(sym in stripped for sym in ("$", "€", "Β£", "Β₯")) else 0 + non_space = sum(1 for ch in stripped if not ch.isspace()) + digits = sum(1 for ch in stripped if ch.isdigit()) + return (has_currency, non_space, digits) + + for index, text_elem in enumerate(page_elem.findall("text")): + raw_text = "".join(text_elem.itertext()).replace("\u00A0", " ") + text = raw_text.strip("\n") + left = _safe_float(text_elem.attrib.get("left")) + top = _safe_float(text_elem.attrib.get("top")) + width = _safe_float(text_elem.attrib.get("width")) + height = _safe_float(text_elem.attrib.get("height")) + font_id = text_elem.attrib.get("font") + font_color = font_colors.get(font_id) if font_id else None + fill_components = _parse_color_components(font_color) + + candidate = { + "id": f"t-{index}", + "text": text, + "fontId": font_id, + "fontSize": height if height > 0 else None, + "x": left, + "y": page_height - top, + "width": width, + "height": height, + "textMatrix": [1, 0, 0, 1, left, page_height - top], + "fillColor": {"colorSpace": "RGB", "components": fill_components} if fill_components else None, + } + + pos_key = (_q(left), _q(page_height - top)) + + existing = best_by_pos.get(pos_key) + if existing is None: + best_by_pos[pos_key] = candidate + else: + if _score_text(candidate["text"]) > _score_text(existing["text"]): + best_by_pos[pos_key] = candidate + + # Optional merge of adjacent runs on the same baseline (e.g., "$" + "38.00") + merged: List[Dict[str, Any]] = [] + base_elements = _dedupe_by_xy_text(sorted(best_by_pos.values(), key=lambda i: (i["y"], i["x"])), eps=1.0) + # Sort by baseline (y) then x to make merges stable and ordering deterministic + for item in sorted(base_elements, key=lambda i: (i["y"], i["x"])): + if not merged: + merged.append(item) + continue + prev = merged[-1] + same_line = _q(prev["y"]) == _q(item["y"]) + if not same_line: + merged.append(item) + continue + prev_right = prev["x"] + (prev.get("width") or 0) + gap = item["x"] - prev_right + max_h = max(prev.get("height") or 0, item.get("height") or 0) + allowed_gap = max(2.0, 0.25 * max_h) + if gap <= allowed_gap and gap >= -allowed_gap: + # Merge + needs_space = ( + prev["text"].strip() != "" + and item["text"].strip() != "" + and not prev["text"].endswith(" ") + and not item["text"].startswith(" ") + and not prev["text"].rstrip().endswith(("$", "€", "Β£", "Β₯")) + ) + merged_text = prev["text"] + (" " if needs_space else "") + item["text"] + new_left = min(prev["x"], item["x"]) + new_right = max(prev_right, item["x"] + (item.get("width") or 0)) + prev.update( + { + "text": merged_text, + "x": new_left, + "width": new_right - new_left, + "height": max_h, + # keep y and fontId from the left-most run + } + ) + else: + merged.append(item) + + # Phase A: dedupe by xy+text to remove duplicate draws + deduped = _dedupe_by_xy_text(merged, eps=1.0) + + # Phase B: table detection + snapping (header-agnostic) + table_info = _detect_table_region(deduped, page_width) + if table_info: + snapped = _snap_table_elements(deduped, table_info) + text_elements = _dedupe_by_xy_text(snapped, eps=1.0) + else: + text_elements = deduped + + for img_index, image_elem in enumerate(page_elem.findall("image")): + left = _safe_float(image_elem.attrib.get("left")) + top = _safe_float(image_elem.attrib.get("top")) + width = _safe_float(image_elem.attrib.get("width")) + height = _safe_float(image_elem.attrib.get("height")) + src = image_elem.attrib.get("src") + image_path = os.path.join(base_dir, src) if src else None + data_url = _read_image_as_data_url(image_path) if image_path else None + image_elements.append( + { + "id": src or f"image-{img_index}", + "objectName": src, + "x": left, + "y": max(page_height - top - height, 0), + "width": width, + "height": height, + "left": left, + "top": top, + "bottom": max(page_height - top, 0), + "right": left + width, + "imageData": data_url, + "imageFormat": os.path.splitext(src)[1][1:] if src else None, + } + ) + + return { + "width": page_width, + "height": page_height, + "pageNumber": _safe_float(page_elem.attrib.get("number"), 0), + "textElements": text_elements, + "imageElements": image_elements, + } + + +def convert_pdf_to_text_editor_document(pdf_path: str) -> Dict[str, Any]: + """Convert a PDF to a JSON payload usable by the PDF text editor.""" + if not os.path.exists(pdf_path): + raise FileNotFoundError(pdf_path) + + with tempfile.TemporaryDirectory() as tmpdir: + output_base = os.path.join(tmpdir, "doc") + command = [ + "pdftohtml", + "-xml", + "-enc", + "UTF-8", + "-nodrm", + "-q", + pdf_path, + output_base, + ] + try: + subprocess.run(command, check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE) + except (FileNotFoundError, subprocess.CalledProcessError) as exc: + logger.error("[PDF-EDITOR] pdftohtml failed for %s: %s", pdf_path, exc) + raise + + xml_path = f"{output_base}.xml" + if not os.path.exists(xml_path): + raise FileNotFoundError(xml_path) + + tree = ET.parse(xml_path) + root = tree.getroot() + + fonts = _parse_fonts(root) + font_colors = {font["id"]: font.get("color") for font in fonts if font.get("id")} + pages = [_parse_page(page_elem, tmpdir, font_colors) for page_elem in root.findall("page")] + + document: Dict[str, Any] = { + "metadata": {"numberOfPages": len(pages)}, + "fonts": fonts, + "pages": pages, + "lazyImages": False, + } + return {"document": document} + + +__all__ = ["convert_pdf_to_text_editor_document"] diff --git a/AI-Document-Generator-main/backend/pdf_utils.py b/AI-Document-Generator-main/backend/pdf_utils.py new file mode 100644 index 0000000000..7694c193bc --- /dev/null +++ b/AI-Document-Generator-main/backend/pdf_utils.py @@ -0,0 +1,146 @@ +from __future__ import annotations + +import base64 +import os +import subprocess +import tempfile +import time +from typing import List, Optional + +from config import OUTPUT_DIR, logger + + +_FONT_SPEC_MARKERS = ( + "\\usepackage{fontspec}", + "\\setmainfont", + "\\setsansfont", + "\\setmonofont", + "\\newfontfamily", +) + + +def _needs_unicode_engine(latex_code: str) -> bool: + return any(marker in latex_code for marker in _FONT_SPEC_MARKERS) + + +def _run_latex(engine: str, tex_filename: str) -> subprocess.CompletedProcess: + return subprocess.run( + [engine, "-interaction=nonstopmode", "-output-directory", OUTPUT_DIR, tex_filename], + stdout=subprocess.PIPE, + stderr=subprocess.PIPE, + timeout=30, + ) + + +def render_pdf_to_images(pdf_bytes: bytes, max_pages: int = 2, dpi: int = 160) -> List[str]: + """Render the first N pages of a PDF to base64-encoded PNG data URLs.""" + images: List[str] = [] + with tempfile.TemporaryDirectory() as tmpdir: + pdf_path = os.path.join(tmpdir, "upload.pdf") + with open(pdf_path, "wb") as handle: + handle.write(pdf_bytes) + + output_prefix = os.path.join(tmpdir, "page") + try: + subprocess.run( + [ + "pdftoppm", + "-png", + "-r", + str(dpi), + "-f", + "1", + "-l", + str(max_pages), + pdf_path, + output_prefix, + ], + check=True, + stdout=subprocess.PIPE, + stderr=subprocess.PIPE, + timeout=30, + ) + except Exception as exc: + logger.error("[IMPORT] pdftoppm failed: %s", exc) + return images + + for idx in range(1, max_pages + 1): + img_path = f"{output_prefix}-{idx}.png" + if os.path.exists(img_path): + with open(img_path, "rb") as img_handle: + encoded = base64.b64encode(img_handle.read()).decode("utf-8") + images.append(f"data:image/png;base64,{encoded}") + return images + + +def compile_latex_to_pdf( + latex_code: str, + job_id: str, + *, + log_errors: bool = True, + raise_on_error: bool = False, +) -> Optional[str]: + """Compile a LaTeX document and return the PDF path.""" + tex_filename = os.path.join(OUTPUT_DIR, f"{job_id}.tex") + pdf_filename = f"{job_id}.pdf" + pdf_path = os.path.join(OUTPUT_DIR, pdf_filename) + + with open(tex_filename, "w", encoding="utf-8") as handle: + handle.write(latex_code) + + try: + t_start = time.perf_counter() + engine = "xelatex" if _needs_unicode_engine(latex_code) else "pdflatex" + first = _run_latex(engine, tex_filename) + if first.returncode != 0 and engine == "pdflatex": + error_output = first.stderr.decode() or first.stdout.decode() + if "fontspec" in error_output and ("XeTeX" in error_output or "LuaTeX" in error_output): + logger.info("[PDF] pdflatex failed due to fontspec; retrying with xelatex") + engine = "xelatex" + first = _run_latex(engine, tex_filename) + t_first = time.perf_counter() + if first.returncode == 0: + _run_latex(engine, tex_filename) + t_end = time.perf_counter() + + if os.path.exists(pdf_path): + logger.info( + "[PDF] compiled job_id=%s -> %s (engine=%s first_pass=%.2fs total=%.2fs)", + job_id, + pdf_filename, + engine, + t_first - t_start, + t_end - t_start, + ) + return pdf_path + + error_output = first.stderr.decode() or first.stdout.decode() + message = error_output.strip() or f"{engine} failed without stderr output" + if log_errors: + logger.error( + "[PDF] not generated job_id=%s code=%s engine=%s after %.2fs: %s", + job_id, + first.returncode, + engine, + t_first - t_start, + message, + ) + if raise_on_error: + raise RuntimeError(message) + return None + except subprocess.TimeoutExpired: + message = f"LaTeX compilation timed out for job_id={job_id}" + if log_errors: + logger.error(message) + if raise_on_error: + raise + return None + except Exception as exc: + if log_errors: + logger.error("LaTeX compilation failed: %s", exc) + if raise_on_error: + raise + return None + + +__all__ = ["render_pdf_to_images", "compile_latex_to_pdf"] diff --git a/AI-Document-Generator-main/backend/prompts.py b/AI-Document-Generator-main/backend/prompts.py new file mode 100644 index 0000000000..5dc1bc2ae0 --- /dev/null +++ b/AI-Document-Generator-main/backend/prompts.py @@ -0,0 +1,129 @@ +from __future__ import annotations + +import json +from typing import Dict, List, Optional, Any + + +# Shared rules +ALLOWED_LATEX_PACKAGES = [ + "geometry", + "xcolor", + "tabularx", + "paracol", + "multicol", + "longtable", + "setspace", + "enumitem", + "titlesec", + "array", + "inputenc", + "fontenc", + "tikz", +] + +LATEX_RULES = [ + r"Output must start with \documentclass.", + r"Output must contain exactly one \begin{document} and one \end{document}.", + r"Do not output anything before \documentclass.", + r"Do not output anything after \end{document}.", + "Do not include commentary, apologies, or markdown fences.", + "If uncertain, prefer simpler LaTeX over complex packages.", + "Only use LaTeX packages from the allowlist in this prompt.", + "Do not use fontspec or custom font commands.", +] + + +def latex_system_prompt(style_profile: Dict[str, Any], document_type: str, template_hint: Optional[str]) -> str: + safe_style = { + "font_preference": style_profile.get("font_preference", "default"), + "tone": style_profile.get("tone", "professional"), + "color_accent": style_profile.get("color_accent", "blue"), + "layout_preference": style_profile.get("layout_preference", "clean"), + } + return ( + "You are a LaTeX document generator for PDFs.\n" + f"User Style Profile (trimmed): {json.dumps(safe_style, sort_keys=True)}\n" + f"Document Type: {document_type}\n" + f"Template Hint present: {'yes' if template_hint else 'no'}\n" + "Rules:\n" + "1) Output ONLY valid LaTeX code.\n" + f"- " + "\n- ".join(LATEX_RULES) + "\n" + "2) Use only the allowlisted packages:\n" + f"- " + "\n- ".join(ALLOWED_LATEX_PACKAGES) + "\n" + f"3) Respect preferred font ({safe_style['font_preference']}), tone ({safe_style['tone']}), and color accent ({safe_style['color_accent']}).\n" + "4) If a template hint is provided, stay close to its layout and styling.\n" + "5) Do NOT add placeholder images or black boxes; omit images entirely unless an explicit path or real image content is provided. Do not use \\rule, tikz, or colored rectangles as image stand-ins.\n" + "6) Return a full compilable document." + ) + + +def latex_context_messages( + template_hint: Optional[str], + current_latex: Optional[str], + structured_brief: Optional[str], +) -> List[Dict[str, str]]: + messages: List[Dict[str, str]] = [] + if template_hint: + messages.append( + { + "role": "user", + "content": f"REFERENCE TEMPLATE (keep style/layout, do not copy data):\n---\n{template_hint[:2000]}\n---", + } + ) + if current_latex: + messages.append( + { + "role": "user", + "content": f"CURRENT LATEX DRAFT (keep structure, apply edits):\n---\n{current_latex[:2000]}\n---", + } + ) + if structured_brief: + messages.append( + { + "role": "user", + "content": ( + "Structured details gathered from the user (authoritative; do not invent beyond this):\n" + f"---\n{structured_brief}\n---" + ), + } + ) + return messages + + +def pdf_qa_system_prompt() -> str: + return ( + "You are a helpful assistant. Read the provided PDF text and answer the user's question.\n" + "Respond with:\n" + "Answer: 2–4 sentences summarizing the answer from the text.\n" + "Evidence: 1–3 short quotes/snippets from the provided text (must be exact substrings).\n" + "If the answer is not in the text, say: 'Not found in the provided text.' and give a best-effort summary." + ) + + +def brief_missing_info_system_prompt(doc_type: str) -> str: + return ( + f"You are a brief-gathering assistant for generating a {doc_type}.\n" + "Be conversational and concise. Ask at most 3 short questions; no multi-part questions.\n" + "If the user hasn't given much, invite them to paste prior material or dump everything they remember.\n" + "Do not invent data; only ask." + ) + + +def vision_layout_system_prompt() -> str: + return ( + "You are a LaTeX layout extractor. Given page images of a PDF, return a LaTeX skeleton matching the layout and styling while blanking user content.\n" + "Do NOT copy any readable text from images. Replace all text with placeholders like TITLE HERE, LOREM, XXXX.\n" + "Infer margins, columns, header/footer, tables. Use \\rule{width}{height} placeholders sized to match blocks.\n" + "Use common packages (geometry, xcolor, tabularx, multicol, paracol, tikz). Replace text with placeholders and output a full compilable document.\n" + "Output ONLY LaTeX." + ) + + +__all__ = [ + "latex_system_prompt", + "latex_context_messages", + "pdf_qa_system_prompt", + "brief_missing_info_system_prompt", + "vision_layout_system_prompt", + "LATEX_RULES", +] diff --git a/AI-Document-Generator-main/backend/requirements.txt b/AI-Document-Generator-main/backend/requirements.txt new file mode 100644 index 0000000000..cdcbd3e00d --- /dev/null +++ b/AI-Document-Generator-main/backend/requirements.txt @@ -0,0 +1,6 @@ +Flask==3.0.0 +Flask-CORS==4.0.0 +# Use modern OpenAI SDK (v1 interface) +openai>=1.12.0 +langchain-core==1.2.5 +langchain-openai==1.1.6 diff --git a/AI-Document-Generator-main/backend/scripts/check_prompts.py b/AI-Document-Generator-main/backend/scripts/check_prompts.py new file mode 100644 index 0000000000..2135eda79e --- /dev/null +++ b/AI-Document-Generator-main/backend/scripts/check_prompts.py @@ -0,0 +1,18 @@ +from prompts import ( + pdf_qa_system_prompt, + vision_layout_system_prompt, + latex_system_prompt, +) + + +def main(): + assert pdf_qa_system_prompt(), "pdf_qa_system_prompt is empty" + assert "Do NOT copy" in vision_layout_system_prompt(), "vision prompt missing no-copy rule" + latex_prompt = latex_system_prompt({}, "document", None) + assert "\\end{document}" in latex_prompt, "latex prompt missing end document mention" + print("prompts OK") + + +if __name__ == "__main__": + main() + diff --git a/AI-Document-Generator-main/backend/storage.py b/AI-Document-Generator-main/backend/storage.py new file mode 100644 index 0000000000..b5119d667e --- /dev/null +++ b/AI-Document-Generator-main/backend/storage.py @@ -0,0 +1,86 @@ +from __future__ import annotations + +import json +import os +from typing import Any, Dict, List + +from config import STYLE_DB_PATH, TEMPLATE_DB_PATH, VERSIONS_DB_PATH +from latex_utils import clean_generated_latex, extract_layout_hint + + +def _read_json(path: str) -> Dict[str, Any]: + if not os.path.exists(path): + return {} + try: + with open(path, "r", encoding="utf-8") as handle: + return json.load(handle) + except Exception: + return {} + + +def _write_json(path: str, data: Dict[str, Any]) -> None: + with open(path, "w", encoding="utf-8") as handle: + json.dump(data, handle, indent=2) + + +def load_user_style(user_id: str) -> Dict[str, Any]: + """Load (or bootstrap) an individual user's preferred style.""" + data = _read_json(STYLE_DB_PATH) + return data.get( + user_id, + { + "layout_preference": "clean", + "font_preference": "helvet", + "tone": "professional", + "color_accent": "blue", + "last_doc_type": None, + }, + ) + + +def save_user_style(user_id: str, style_data: Dict[str, Any]) -> Dict[str, Any]: + """Persist style preferences for a user.""" + all_data = _read_json(STYLE_DB_PATH) + current = all_data.get(user_id, load_user_style(user_id)) + current.update(style_data) + all_data[user_id] = current + _write_json(STYLE_DB_PATH, all_data) + return current + + +def load_user_templates(user_id: str) -> Dict[str, str]: + templates = _read_json(TEMPLATE_DB_PATH) + return templates.get(user_id, {}) + + +def save_user_template(user_id: str, doc_type: str, latex_code: str) -> None: + """Persist sanitized layout hints per doc type.""" + templates = _read_json(TEMPLATE_DB_PATH) + user_templates = templates.get(user_id, {}) + sanitized = clean_generated_latex(latex_code) + user_templates[doc_type] = extract_layout_hint(sanitized) + templates[user_id] = user_templates + _write_json(TEMPLATE_DB_PATH, templates) + + +def load_versions(user_id: str) -> List[Dict[str, Any]]: + data = _read_json(VERSIONS_DB_PATH) + return data.get(user_id, []) + + +def save_version(user_id: str, entry: Dict[str, Any]) -> None: + data = _read_json(VERSIONS_DB_PATH) + versions = data.get(user_id, []) + versions.insert(0, entry) + data[user_id] = versions[:20] + _write_json(VERSIONS_DB_PATH, data) + + +__all__ = [ + "load_user_style", + "save_user_style", + "load_user_templates", + "save_user_template", + "load_versions", + "save_version", +] diff --git a/AI-Document-Generator-main/backend/styles.py b/AI-Document-Generator-main/backend/styles.py new file mode 100644 index 0000000000..1451b71073 --- /dev/null +++ b/AI-Document-Generator-main/backend/styles.py @@ -0,0 +1,33 @@ +from __future__ import annotations + +from typing import Any, Dict + +from storage import load_user_style, save_user_style + + +def update_style_profile_from_prompt(user_id: str, prompt: str) -> Dict[str, Any]: + """Simple heuristics to remember color/font/tone preferences from prompt text.""" + style = load_user_style(user_id) + lower = (prompt or "").lower() + + if "modern" in lower or "minimal" in lower: + style["layout_preference"] = "modern" + style["tone"] = "minimalist" + if "classic" in lower or "formal" in lower: + style["layout_preference"] = "classic" + style["tone"] = "formal" + if "serif" in lower: + style["font_preference"] = "serif" + if "sans" in lower: + style["font_preference"] = "helvet" + if "blue" in lower: + style["color_accent"] = "blue" + if "red" in lower: + style["color_accent"] = "red" + if "green" in lower: + style["color_accent"] = "green" + + return save_user_style(user_id, style) + + +__all__ = ["update_style_profile_from_prompt"] diff --git a/AI-Document-Generator-main/backend/vision.py b/AI-Document-Generator-main/backend/vision.py new file mode 100644 index 0000000000..f5d66ecaca --- /dev/null +++ b/AI-Document-Generator-main/backend/vision.py @@ -0,0 +1,40 @@ +from __future__ import annotations + +from typing import Any, List, Optional + +from config import CLIENT_MODE, SMART_MODEL, get_chat_model, logger +from langchain_utils import to_lc_messages +from prompts import vision_layout_system_prompt + + +def vision_layout_from_images(image_urls: List[str], doc_type: str) -> Optional[str]: + """Call the multimodal model to recover a LaTeX skeleton from page images.""" + if CLIENT_MODE != "langchain" or not image_urls: + return None + + system_prompt = vision_layout_system_prompt() + + user_content: List[Any] = [ + {"type": "text", "text": f"Extract layout for document type: {doc_type}. Return LaTeX skeleton only."} + ] + for url in image_urls: + user_content.append({"type": "image_url", "image_url": {"url": url}}) + + messages = [ + {"role": "system", "content": system_prompt}, + {"role": "user", "content": user_content}, + ] + + try: + logger.info("[IMPORT] vision call pages=%s doc_type=%s", len(image_urls), doc_type) + llm = get_chat_model(SMART_MODEL, max_tokens=2800) + if not llm: + return None + response = llm.invoke(to_lc_messages(messages)) + return response.content + except Exception as exc: + logger.error("[IMPORT] vision generation failed: %s", exc) + return None + + +__all__ = ["vision_layout_from_images"] diff --git a/AI-Document-Generator-main/frontend/.eslintrc.cjs b/AI-Document-Generator-main/frontend/.eslintrc.cjs new file mode 100644 index 0000000000..c11cd3a43c --- /dev/null +++ b/AI-Document-Generator-main/frontend/.eslintrc.cjs @@ -0,0 +1,36 @@ +module.exports = { + root: true, + env: { + browser: true, + es2021: true, + }, + extends: [ + 'eslint:recommended', + 'plugin:react/recommended', + 'plugin:react-hooks/recommended', + 'plugin:@typescript-eslint/recommended', + 'prettier', + ], + parser: '@typescript-eslint/parser', + parserOptions: { + ecmaVersion: 'latest', + sourceType: 'module', + ecmaFeatures: { + jsx: true, + }, + jsxPragma: null, + }, + plugins: ['react', 'react-hooks', '@typescript-eslint'], + settings: { + react: { + version: 'detect', + runtime: 'automatic', + }, + }, + ignorePatterns: ['dist', 'node_modules'], + rules: { + 'react/prop-types': 'off', + 'react/react-in-jsx-scope': 'off', + '@typescript-eslint/no-explicit-any': 'off', + }, +} diff --git a/AI-Document-Generator-main/frontend/index.html b/AI-Document-Generator-main/frontend/index.html new file mode 100644 index 0000000000..a86a29b213 --- /dev/null +++ b/AI-Document-Generator-main/frontend/index.html @@ -0,0 +1,13 @@ + + + + + + + Stirling - Intelligent Document 1.0 + + +
+ + + diff --git a/AI-Document-Generator-main/frontend/package-lock.json b/AI-Document-Generator-main/frontend/package-lock.json new file mode 100644 index 0000000000..09b787fa31 --- /dev/null +++ b/AI-Document-Generator-main/frontend/package-lock.json @@ -0,0 +1,7012 @@ +{ + "name": "latex-pdf-generator-frontend", + "version": "1.0.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "latex-pdf-generator-frontend", + "version": "1.0.0", + "dependencies": { + "@xenova/transformers": "^2.17.0", + "pdf-lib": "^1.17.1", + "pdfjs-dist": "^4.10.38", + "react": "^18.2.0", + "react-dom": "^18.2.0" + }, + "devDependencies": { + "@types/react": "^18.2.43", + "@types/react-dom": "^18.2.17", + "@typescript-eslint/eslint-plugin": "^6.14.0", + "@typescript-eslint/parser": "^6.14.0", + "@vitejs/plugin-react": "^4.2.1", + "autoprefixer": "^10.4.16", + "eslint": "^8.56.0", + "eslint-config-prettier": "^9.0.0", + "eslint-plugin-react": "^7.34.1", + 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from './components/landing/LandingView' +import { ImportLayoutModal } from './components/modals/ImportLayoutModal' +import { WorkspaceView } from './components/workspace/WorkspaceView' +import { useDocumentWorkflow } from './hooks/useDocumentWorkflow' +import { useSpeechCapture } from './hooks/useSpeechCapture' + +function App() { + const workflow = useDocumentWorkflow() + const speech = useSpeechCapture({ appendPrompt: workflow.appendPrompt }) + + const importModal = ( + workflow.setShowImportModal(false)} + onFileSelected={workflow.handleImportTemplate} + isImporting={workflow.isImporting} + status={workflow.importStatus} + /> + ) + + if (workflow.view === 'landing') { + return ( + <> + + {importModal} + + ) + } + + return ( + <> + workflow.setView('landing')} + onOpenHistory={() => workflow.setIsHistoryOpen(true)} + onOpenImport={() => workflow.setShowImportModal(true)} + isHistoryOpen={workflow.isHistoryOpen} + versions={workflow.versions} + selectedVersionId={workflow.selectedVersionId} + onSelectVersion={workflow.selectVersion} + onCloseHistory={() => workflow.setIsHistoryOpen(false)} + onRefreshHistory={workflow.fetchHistory} + onPdfUpdated={workflow.applyEditedPdf} + /> + {importModal} + + ) +} + +export default App diff --git a/AI-Document-Generator-main/frontend/src/components/landing/LandingView.tsx b/AI-Document-Generator-main/frontend/src/components/landing/LandingView.tsx new file mode 100644 index 0000000000..ce98c0fdbc --- /dev/null +++ b/AI-Document-Generator-main/frontend/src/components/landing/LandingView.tsx @@ -0,0 +1,327 @@ +import { FormEvent, KeyboardEvent, useRef, useEffect, useState, useCallback, useLayoutEffect } from 'react' +import { AudioWaveform } from '../ui/AudioWaveform' + +interface LandingViewProps { + prompt: string + onPromptChange: (value: string) => void + onSubmit: (event: FormEvent) => void + onKeyDown: (event: KeyboardEvent) => void + uploadedPdfFile: File | null + onFileSelect: (file: File | null) => void + isImporting: boolean + onToggleRecording: () => void + onCancelRecording: () => void + onAcceptRecording: () => void + isRecording: boolean + whisperStatus: string | null + waveformHistory: number[][] +} + +export function LandingView({ + prompt, + onPromptChange, + onSubmit, + onKeyDown, + uploadedPdfFile, + onFileSelect, + isImporting, + onToggleRecording, + onCancelRecording, + onAcceptRecording, + isRecording, + whisperStatus, + waveformHistory, +}: LandingViewProps) { + const textareaRef = useRef(null) + const measureRef = useRef(null) + const [isMultiline, setIsMultiline] = useState(false) + const [canScrollDown, setCanScrollDown] = useState(false) + const [textareaHeight, setTextareaHeight] = useState(24) + const prevIsMultilineRef = useRef(isMultiline) + const cursorPositionRef = useRef(null) + + // Measure the actual content height using a hidden div + const measureContent = useCallback(() => { + if (!measureRef.current) return 24 + measureRef.current.textContent = prompt || 'X' // Use 'X' as minimum to get line height + const height = measureRef.current.scrollHeight + return height + }, [prompt]) + + const updateScrollIndicator = useCallback(() => { + const textarea = textareaRef.current + if (!textarea) return + const canScroll = textarea.scrollHeight > textarea.clientHeight + 1 + const isAtBottom = textarea.scrollTop + textarea.clientHeight >= textarea.scrollHeight - 2 + setCanScrollDown(canScroll && !isAtBottom) + }, []) + + // Update layout based on content + const updateLayout = useCallback(() => { + // Save cursor position before potential layout change + if (textareaRef.current) { + cursorPositionRef.current = textareaRef.current.selectionStart + } + + const contentHeight = measureContent() + const isMulti = contentHeight > 32 // More than ~1.5 lines + setIsMultiline(isMulti) + + // Set textarea height (capped at 240px) + const newHeight = Math.min(Math.max(contentHeight, 24), 240) + setTextareaHeight(newHeight) + + // Update scroll indicator after layout settles + requestAnimationFrame(updateScrollIndicator) + }, [measureContent, updateScrollIndicator]) + + // Restore cursor position when layout mode changes + useEffect(() => { + if (prevIsMultilineRef.current !== isMultiline) { + prevIsMultilineRef.current = isMultiline + // Use requestAnimationFrame to ensure the new textarea is mounted + requestAnimationFrame(() => { + if (textareaRef.current && cursorPositionRef.current !== null) { + const pos = cursorPositionRef.current + textareaRef.current.focus() + textareaRef.current.setSelectionRange(pos, pos) + } + }) + } + }, [isMultiline]) + + // Update on every prompt change - use layoutEffect for synchronous update + useLayoutEffect(() => { + updateLayout() + }, [prompt, updateLayout]) + + // Also update after a small delay to catch any missed updates + useEffect(() => { + const timer = setTimeout(updateLayout, 10) + return () => clearTimeout(timer) + }, [prompt, updateLayout]) + + // Handle scroll to update gradient visibility + const handleScroll = useCallback(() => { + updateScrollIndicator() + }, [updateScrollIndicator]) + + // Toolbar buttons component to avoid duplication + const ToolbarButtons = () => ( +
+ + +
+ ) + + const PlusButton = () => ( + + ) + + return ( +
+
+
+
+
+ + {/* Hidden measurement div - mirrors textarea styling */} +