AI Tool: Convert Architectural Casework Elevations (PDF) into Editable AutoCAD DWG Files with Self-Training Interface Project Description I need a custom AI tool that automatically reads architectural casework elevation drawings (PDFs) and generates complete, editable AutoCAD DWG files using my existing multiple block libraries. The tool must detect cabinets, sinks, fixtures, shelving, countertops, and miscellaneous equipment, then place the correct blocks with accurate dimensions, countertop outlines, and section views. It must also include a natural language self-training interface so a non-technical user can teach and refine the AI using plain English rules or by correcting the output drawing. This is Phase 1 (Proof of Concept) of a larger initiative. Future phases will expand to multiple elevations and additional manufacturers. Sample Files Provided Before: Architectural elevation A407 (page 26) After: Mott shop drawing 2-08 (page 30) Full block library, spec sheets, and catalogs will be supplied Key Requirements Input PDF casework elevation drawings (sometimes original DWG) My organized AutoCAD block library Project-specific catalogs and reference documents Output Clean, editable AutoCAD DWG file containing: Correctly placed blocks for all detected casework, sinks, fixtures, shelving, etc. Accurate dimensions (height, width, spacing) Countertop outlines with detailed top-view information Section views based on cabinet types Proper layers, line types, and drafting standards Visual flags / notes for any unmatched or uncertain items Core Features YOLO-based (or equivalent) object detection for cabinets, sinks, pegboards, etc. Vision LLM assistance for annotation and context understanding Block matching engine with fallback logic Natural language rule engine (“teach” the AI in plain English) Self-training interface (view, edit, enable/disable rules) Drawing-based learning (compare AI DWG vs. user-corrected DWG) Confidence warnings and visual flagging of uncertain items Technical Preferences Detection: YOLOv8 / YOLOv11 (fine-tuned on my samples) + Vision LLM (GPT-4o or Claude) DWG generation: ezdxf (preferred for standalone) or pyautocad Rule storage: Human-readable JSON/YAML Training interface: Lightweight GUI (Tkinter / PyQt) or simple web interface Deliverables Fully working Python tool (script + optional GUI) Natural language rule trainer and visual rule manager Clean DWG output meeting my drafting standards Full source code, trained model weights, training scripts, and documentation Setup guide and user manual Log/report of unmatched or low-confidence items Timeline POC Phase 1 (single cabinet and wall) with 1-2 week POC Phase 2 (single elevation A407 → 2-08) within 2–3 weeks Full Phase 1 within 6–8 weeks (flexible) Budget Please provide your fixed price for the POC 1 & POC 2 (single elevation with full DWG output + basic self-training interface). Higher budget available for excellent quality and clean code. How to Apply Please reply with: Your proposed technical approach (tools and libraries) Estimated timeline for the POC 1 & 2 Fixed price for the POC 1 & 2 Links or screenshots of any similar past projects (CAD/DXF automation, technical drawing conversion, or vision AI on drawings) I will provide all sample files immediately upon hiring. Looking forward to your proposals.