ميزة: إضافة مكوني ProcedureSelection و StepProgress لأداة مخططات التدفق بصيغة PDF
- تنفيذ مكون ProcedureSelection لتمكين المستخدمين من اختيار الإجراءات من قائمة، وإدارة الاختيارات، ومعالجة الإجراءات المرفوضة. - إنشاء مكون StepProgress لعرض تقدم معالج متعدد الخطوات بشكل مرئي. - تعريف أنواع مشتركة للإجراءات، وخطوات التدفق، ورسائل الدردشة في ملف types.ts. - إضافة اختبارات وحدة لخطافات useFileUpload و useTaskPolling لضمان الأداء السليم ومعالجة الأخطاء. - تنفيذ اختبارات واجهة برمجة التطبيقات (API) للتحقق من تنسيقات نقاط النهاية وضمان اتساق ربط الواجهة الأمامية بالخلفية.
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142
backend/app/services/ai_chat_service.py
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142
backend/app/services/ai_chat_service.py
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"""AI Chat Service — OpenRouter integration for flowchart improvement."""
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import os
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import json
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import logging
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import requests
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logger = logging.getLogger(__name__)
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# Configuration
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OPENROUTER_API_KEY = os.getenv("OPENROUTER_API_KEY", "")
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OPENROUTER_MODEL = os.getenv("OPENROUTER_MODEL", "meta-llama/llama-3-8b-instruct")
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OPENROUTER_BASE_URL = os.getenv(
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"OPENROUTER_BASE_URL", "https://openrouter.ai/api/v1/chat/completions"
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)
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SYSTEM_PROMPT = """You are a flowchart improvement assistant. You help users improve their flowcharts by:
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1. Suggesting better step titles and descriptions
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2. Identifying missing steps or decision points
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3. Recommending better flow structure
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4. Simplifying complex flows
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When the user asks you to modify the flowchart, respond with your suggestion in plain text.
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Keep responses concise and actionable. Reply in the same language the user uses."""
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def chat_about_flowchart(message: str, flow_data: dict | None = None) -> dict:
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"""
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Send a message to the AI about a flowchart and get improvement suggestions.
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Args:
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message: User message
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flow_data: Current flowchart data (optional)
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Returns:
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{"reply": "...", "updated_flow": {...} | None}
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"""
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if not OPENROUTER_API_KEY:
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return {
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"reply": _fallback_response(message, flow_data),
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"updated_flow": None,
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}
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# Build context
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context = ""
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if flow_data:
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steps_summary = []
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for s in flow_data.get("steps", []):
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steps_summary.append(
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f"- [{s.get('type', 'process')}] {s.get('title', '')}"
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)
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context = (
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f"\nCurrent flowchart: {flow_data.get('title', 'Untitled')}\n"
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f"Steps:\n" + "\n".join(steps_summary)
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)
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messages = [
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{"role": "system", "content": SYSTEM_PROMPT},
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{"role": "user", "content": f"{message}{context}"},
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]
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try:
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response = requests.post(
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OPENROUTER_BASE_URL,
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headers={
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"Authorization": f"Bearer {OPENROUTER_API_KEY}",
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"Content-Type": "application/json",
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},
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json={
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"model": OPENROUTER_MODEL,
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"messages": messages,
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"max_tokens": 500,
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"temperature": 0.7,
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},
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timeout=30,
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)
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response.raise_for_status()
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data = response.json()
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reply = (
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data.get("choices", [{}])[0]
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.get("message", {})
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.get("content", "")
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.strip()
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)
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if not reply:
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reply = "I couldn't generate a response. Please try again."
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return {"reply": reply, "updated_flow": None}
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except requests.exceptions.Timeout:
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logger.warning("OpenRouter API timeout")
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return {
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"reply": "The AI service is taking too long. Please try again.",
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"updated_flow": None,
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}
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except Exception as e:
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logger.error(f"OpenRouter API error: {e}")
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return {
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"reply": _fallback_response(message, flow_data),
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"updated_flow": None,
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}
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def _fallback_response(message: str, flow_data: dict | None) -> str:
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"""Provide a helpful response when the AI API is unavailable."""
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msg_lower = message.lower()
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if flow_data:
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steps = flow_data.get("steps", [])
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title = flow_data.get("title", "your flowchart")
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step_count = len(steps)
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decision_count = sum(1 for s in steps if s.get("type") == "decision")
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if any(
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w in msg_lower for w in ["simplify", "reduce", "shorter", "بسط", "اختصر"]
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):
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return (
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f"Your flowchart '{title}' has {step_count} steps. "
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f"To simplify, consider merging consecutive process steps "
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f"that perform related actions into a single step."
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)
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if any(
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w in msg_lower for w in ["missing", "add", "more", "ناقص", "أضف"]
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):
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return (
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f"Your flowchart has {decision_count} decision points. "
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f"Consider adding error handling or validation steps "
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f"between critical process nodes."
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)
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return (
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f"Your flowchart '{title}' contains {step_count} steps "
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f"({decision_count} decisions). To get AI-powered suggestions, "
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f"please configure the OPENROUTER_API_KEY environment variable."
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)
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return (
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"AI chat requires the OPENROUTER_API_KEY to be configured. "
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"Please set up the environment variable for full AI functionality."
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)
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410
backend/app/services/flowchart_service.py
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backend/app/services/flowchart_service.py
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"""Flowchart service — Extract procedures from PDF and generate flowchart data."""
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import os
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import re
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import json
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import logging
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logger = logging.getLogger(__name__)
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class FlowchartError(Exception):
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"""Custom exception for flowchart operations."""
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pass
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# ---------------------------------------------------------------------------
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# Heuristic keywords that signal procedural content
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# ---------------------------------------------------------------------------
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_PROCEDURE_KEYWORDS = [
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"procedure", "protocol", "checklist", "sequence", "instruction",
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"steps", "process", "workflow", "troubleshoot", "maintenance",
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"startup", "shutdown", "emergency", "inspection", "replacement",
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"installation", "calibration", "operation", "safety", "guide",
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]
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_STEP_PATTERNS = re.compile(
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r"(?:^|\n)\s*(?:"
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r"(?:step\s*\d+)|" # Step 1, Step 2 …
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r"(?:\d+[\.\)]\s+)|" # 1. or 1) …
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r"(?:[a-z][\.\)]\s+)|" # a. or a) …
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r"(?:•\s)|" # bullet •
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r"(?:-\s)|" # dash -
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r"(?:✓\s)" # checkmark ✓
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r")",
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re.IGNORECASE,
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)
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_DECISION_KEYWORDS = re.compile(
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r"\b(?:if|whether|check|verify|confirm|decide|inspect|compare|ensure|"
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r"is\s+\w+\s*\?|does|should|can)\b",
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re.IGNORECASE,
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)
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def extract_text_from_pdf(input_path: str) -> list[dict]:
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"""
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Extract text from each page of a PDF.
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Returns:
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List of dicts: [{"page": 1, "text": "..."}, ...]
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"""
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try:
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from PyPDF2 import PdfReader
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if not os.path.exists(input_path):
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raise FlowchartError(f"File not found: {input_path}")
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reader = PdfReader(input_path)
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pages = []
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for i, page in enumerate(reader.pages, start=1):
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text = page.extract_text() or ""
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pages.append({"page": i, "text": text.strip()})
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return pages
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except FlowchartError:
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raise
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except Exception as e:
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raise FlowchartError(f"Failed to extract text from PDF: {str(e)}")
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def identify_procedures(pages: list[dict]) -> list[dict]:
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"""
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Analyse extracted PDF text and identify procedures/sections.
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Uses heuristic analysis:
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1. Look for headings (lines in UPPER CASE or short bold-like lines)
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2. Match procedure keywords
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3. Group consecutive pages under the same heading
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Returns:
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List of procedures: [
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{
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"id": "proc-1",
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"title": "Emergency Shutdown Protocol",
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"description": "Extracted first paragraph...",
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"pages": [8, 9],
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"step_count": 6
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},
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...
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]
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"""
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procedures = []
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current_proc = None
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proc_counter = 0
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for page_data in pages:
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text = page_data["text"]
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page_num = page_data["page"]
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if not text:
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continue
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lines = text.split("\n")
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heading_candidates = []
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for line in lines:
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stripped = line.strip()
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if not stripped:
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continue
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# Heading heuristic: short line, mostly uppercase or title-like
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is_heading = (
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len(stripped) < 80
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and (
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stripped.isupper()
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or (stripped == stripped.title() and len(stripped.split()) <= 8)
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or any(kw in stripped.lower() for kw in _PROCEDURE_KEYWORDS)
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)
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and not stripped.endswith(",")
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)
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if is_heading:
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heading_candidates.append(stripped)
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# Check if this page has procedural content
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has_steps = bool(_STEP_PATTERNS.search(text))
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has_keywords = any(kw in text.lower() for kw in _PROCEDURE_KEYWORDS)
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if heading_candidates and (has_steps or has_keywords):
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best_heading = heading_candidates[0]
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# Check if this is a continuation of the current procedure
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if current_proc and _is_continuation(current_proc["title"], best_heading, text):
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current_proc["pages"].append(page_num)
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current_proc["_text"] += "\n" + text
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else:
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# Save previous procedure
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if current_proc:
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_finalize_procedure(current_proc)
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procedures.append(current_proc)
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proc_counter += 1
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first_paragraph = _extract_first_paragraph(text, best_heading)
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current_proc = {
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"id": f"proc-{proc_counter}",
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"title": _clean_title(best_heading),
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"description": first_paragraph,
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"pages": [page_num],
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"_text": text,
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}
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elif current_proc and has_steps:
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# Continuation — same procedure on next page
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current_proc["pages"].append(page_num)
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current_proc["_text"] += "\n" + text
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# Don't forget the last one
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if current_proc:
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_finalize_procedure(current_proc)
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procedures.append(current_proc)
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# If no procedures found via headings, try splitting by page with step content
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if not procedures:
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procedures = _fallback_extraction(pages)
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return procedures
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def generate_flowchart(procedure: dict, page_texts: list[dict]) -> dict:
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"""
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Generate a flowchart (list of nodes + connections) from a procedure.
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Args:
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procedure: Procedure dict with id, title, pages
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page_texts: All page text data
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Returns:
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Flowchart dict: {
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"id": "flow-1",
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"procedureId": "proc-1",
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"title": "...",
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"steps": [ {id, type, title, description, connections}, ... ]
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}
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"""
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# Gather text for the procedure's pages
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text = ""
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for pt in page_texts:
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if pt["page"] in procedure["pages"]:
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text += pt["text"] + "\n"
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steps = _extract_steps_from_text(text, procedure["title"])
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return {
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"id": f"flow-{procedure['id']}",
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"procedureId": procedure["id"],
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"title": procedure["title"],
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"steps": steps,
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}
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def extract_and_generate(input_path: str) -> dict:
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"""
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Full pipeline: extract text → identify procedures → generate flowcharts.
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Returns:
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{
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"procedures": [...],
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"flowcharts": [...],
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"total_pages": int
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}
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"""
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pages = extract_text_from_pdf(input_path)
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procedures = identify_procedures(pages)
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flowcharts = []
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for proc in procedures:
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flow = generate_flowchart(proc, pages)
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flowcharts.append(flow)
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# Remove internal text field
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for proc in procedures:
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proc.pop("_text", None)
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return {
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"procedures": procedures,
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"flowcharts": flowcharts,
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"total_pages": len(pages),
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"pages": pages,
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}
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# ---------------------------------------------------------------------------
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# Internal helpers
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# ---------------------------------------------------------------------------
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def _is_continuation(current_title: str, new_heading: str, text: str) -> bool:
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"""Check if a page is a continuation of the current procedure."""
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continued_markers = ["(continued)", "(cont.)", "(cont'd)"]
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heading_lower = new_heading.lower()
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# Explicit continuation marker
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if any(m in heading_lower for m in continued_markers):
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return True
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# Same title repeated
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if current_title.lower().rstrip() in heading_lower:
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return True
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return False
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def _clean_title(title: str) -> str:
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"""Clean up a procedure title."""
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# Remove continuation markers
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title = re.sub(r"\s*\(continued\).*", "", title, flags=re.IGNORECASE)
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title = re.sub(r"\s*\(cont[\.\']?d?\).*", "", title, flags=re.IGNORECASE)
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# Remove leading numbers like "3.1"
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title = re.sub(r"^\d+[\.\)]\s*", "", title)
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title = re.sub(r"^\d+\.\d+\s*", "", title)
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return title.strip()
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def _extract_first_paragraph(text: str, heading: str) -> str:
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"""Extract the first meaningful paragraph after a heading."""
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idx = text.find(heading)
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if idx >= 0:
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after_heading = text[idx + len(heading):].strip()
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else:
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after_heading = text.strip()
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lines = after_heading.split("\n")
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paragraph = []
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for line in lines:
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stripped = line.strip()
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if not stripped:
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if paragraph:
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break
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continue
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if stripped.isupper() and len(stripped) > 10:
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break
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paragraph.append(stripped)
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desc = " ".join(paragraph)[:200]
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return desc if desc else "Procedural content extracted from document."
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def _finalize_procedure(proc: dict):
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"""Calculate step count from the accumulated text."""
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text = proc.get("_text", "")
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matches = _STEP_PATTERNS.findall(text)
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proc["step_count"] = max(len(matches), 2)
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def _fallback_extraction(pages: list[dict]) -> list[dict]:
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"""When no heading-based procedures found, detect pages with step-like content."""
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procedures = []
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proc_counter = 0
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||||
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for page_data in pages:
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text = page_data["text"]
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if not text:
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continue
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||||
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has_steps = bool(_STEP_PATTERNS.search(text))
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if has_steps:
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proc_counter += 1
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first_line = text.split("\n")[0].strip()[:60]
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procedures.append({
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"id": f"proc-{proc_counter}",
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"title": first_line or f"Procedure (Page {page_data['page']})",
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"description": text[:150].strip(),
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"pages": [page_data["page"]],
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"step_count": len(_STEP_PATTERNS.findall(text)),
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})
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return procedures
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||||
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def _extract_steps_from_text(text: str, procedure_title: str) -> list[dict]:
|
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"""
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Parse text into flowchart steps (nodes).
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||||
Strategy:
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1. Split text by numbered/bulleted lines
|
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2. Classify each as process or decision
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3. Add start/end nodes
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||||
4. Wire connections
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||||
"""
|
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lines = text.split("\n")
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raw_steps = []
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||||
current_step_lines = []
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||||
step_counter = 0
|
||||
|
||||
for line in lines:
|
||||
stripped = line.strip()
|
||||
if not stripped:
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||||
continue
|
||||
|
||||
# Is this the start of a new step?
|
||||
is_step_start = bool(re.match(
|
||||
r"^\s*(?:\d+[\.\)]\s+|[a-z][\.\)]\s+|•\s|-\s|✓\s|step\s*\d+)",
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||||
stripped,
|
||||
re.IGNORECASE,
|
||||
))
|
||||
|
||||
if is_step_start:
|
||||
if current_step_lines:
|
||||
raw_steps.append(" ".join(current_step_lines))
|
||||
current_step_lines = [re.sub(r"^\s*(?:\d+[\.\)]\s*|[a-z][\.\)]\s*|•\s*|-\s*|✓\s*|step\s*\d+[:\.\)]\s*)", "", stripped, flags=re.IGNORECASE)]
|
||||
elif current_step_lines:
|
||||
current_step_lines.append(stripped)
|
||||
|
||||
if current_step_lines:
|
||||
raw_steps.append(" ".join(current_step_lines))
|
||||
|
||||
# Limit to reasonable number of steps
|
||||
if len(raw_steps) > 15:
|
||||
raw_steps = raw_steps[:15]
|
||||
|
||||
# Build flowchart nodes
|
||||
nodes = []
|
||||
step_id = 0
|
||||
|
||||
# Start node
|
||||
step_id += 1
|
||||
nodes.append({
|
||||
"id": str(step_id),
|
||||
"type": "start",
|
||||
"title": f"Begin: {procedure_title[:40]}",
|
||||
"description": "Start of procedure",
|
||||
"connections": [str(step_id + 1)] if raw_steps else [],
|
||||
})
|
||||
|
||||
for i, step_text in enumerate(raw_steps):
|
||||
step_id += 1
|
||||
# Classify as decision or process
|
||||
is_decision = bool(_DECISION_KEYWORDS.search(step_text))
|
||||
|
||||
node_type = "decision" if is_decision else "process"
|
||||
title = step_text[:60]
|
||||
description = step_text[:150]
|
||||
|
||||
connections = []
|
||||
if i < len(raw_steps) - 1:
|
||||
if is_decision:
|
||||
# Decision: Yes goes to next, No could loop back or skip
|
||||
connections = [str(step_id + 1)]
|
||||
else:
|
||||
connections = [str(step_id + 1)]
|
||||
else:
|
||||
connections = [str(step_id + 1)] # Connect to end
|
||||
|
||||
nodes.append({
|
||||
"id": str(step_id),
|
||||
"type": node_type,
|
||||
"title": title,
|
||||
"description": description,
|
||||
"connections": connections,
|
||||
})
|
||||
|
||||
# End node
|
||||
step_id += 1
|
||||
nodes.append({
|
||||
"id": str(step_id),
|
||||
"type": "end",
|
||||
"title": "Procedure Complete",
|
||||
"description": "End of procedure",
|
||||
"connections": [],
|
||||
})
|
||||
|
||||
return nodes
|
||||
@@ -140,20 +140,75 @@ def split_pdf(
|
||||
|
||||
def _parse_page_range(spec: str, total: int) -> list[int]:
|
||||
"""Parse a page specification like '1,3,5-8' into 0-based indices."""
|
||||
if not spec or not spec.strip():
|
||||
raise PDFToolsError("Please specify at least one page (e.g. 1,3,5-8).")
|
||||
|
||||
indices = set()
|
||||
for part in spec.split(","):
|
||||
part = part.strip()
|
||||
invalid_tokens = []
|
||||
out_of_range_tokens = []
|
||||
|
||||
for raw_part in spec.split(","):
|
||||
part = raw_part.strip()
|
||||
|
||||
if not part:
|
||||
continue
|
||||
|
||||
if "-" in part:
|
||||
if part.count("-") != 1:
|
||||
invalid_tokens.append(part)
|
||||
continue
|
||||
|
||||
start_s, end_s = part.split("-", 1)
|
||||
start = max(1, int(start_s.strip()))
|
||||
end = min(total, int(end_s.strip()))
|
||||
start_s = start_s.strip()
|
||||
end_s = end_s.strip()
|
||||
|
||||
if not start_s.isdigit() or not end_s.isdigit():
|
||||
invalid_tokens.append(part)
|
||||
continue
|
||||
|
||||
start = int(start_s)
|
||||
end = int(end_s)
|
||||
|
||||
if start > end:
|
||||
invalid_tokens.append(part)
|
||||
continue
|
||||
|
||||
if start < 1 or end > total:
|
||||
out_of_range_tokens.append(f"{start}-{end}")
|
||||
continue
|
||||
|
||||
indices.update(range(start - 1, end))
|
||||
else:
|
||||
if not part.isdigit():
|
||||
invalid_tokens.append(part)
|
||||
continue
|
||||
|
||||
page = int(part)
|
||||
if 1 <= page <= total:
|
||||
indices.add(page - 1)
|
||||
if page < 1 or page > total:
|
||||
out_of_range_tokens.append(str(page))
|
||||
continue
|
||||
|
||||
indices.add(page - 1)
|
||||
|
||||
if invalid_tokens:
|
||||
tokens = ", ".join(invalid_tokens)
|
||||
raise PDFToolsError(
|
||||
f"Invalid page format: {tokens}. Use a format like 1,3,5-8."
|
||||
)
|
||||
|
||||
if out_of_range_tokens:
|
||||
tokens = ", ".join(out_of_range_tokens)
|
||||
page_word = "page" if total == 1 else "pages"
|
||||
raise PDFToolsError(
|
||||
f"Selected pages ({tokens}) are out of range. This PDF has only {total} {page_word}."
|
||||
)
|
||||
|
||||
if not indices:
|
||||
raise PDFToolsError("No valid pages specified.")
|
||||
page_word = "page" if total == 1 else "pages"
|
||||
raise PDFToolsError(
|
||||
f"No pages selected. This PDF has {total} {page_word}."
|
||||
)
|
||||
|
||||
return sorted(indices)
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user