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elm/ords/ARCHITECTURE.md

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+# **OrdinanceGPT: Architectural Design Document**
+
+## **1. Introduction**
+### **1.1 Purpose**
+This document describes the architectural design of the ordinance web scraping and extraction tool, focusing on its components, key classes, and their roles within the system.
+
+### **1.2 Audience**
+- **Primary:** Developers working on expanding the capabilities of ordinance extraction.
+- **Secondary:** Developers extending this functionality to other areas.
+
+### **1.3 Scope**
+Covers the backend API design, including key classes, their responsibilities, and interactions.
+
+---
+
+## **2. High-Level Architecture**
+### **2.1 System Context**
+Points of interaction for OrdinanceGPT:
+- **End Users:** Users submit model executions via command line using a configuration file. Users can select specific jurisdictions to focus on.
+- **Internet via Web Browser:** The model searches the web for relevant legal documents. The most common search technique is Google Search.
+- **LLMs:** The model relies on LLMs (typically ChatGPT) to analyze web scraping results and extract information from documents.
+- **Filesystem:** Stores output files in organized sub-directories and compiles ordinance information into a CSV.
+
+**Diagram:**
+```mermaid
+architecture-beta
+    group api(carbon:4k-filled)[OrdinanceGPT]
+
+    service db(database)[Database] in api
+    service disk1(disk)[Storage] in api
+    service disk2(disk)[Storage] in api
+    service server(server)[Server] in api
+
+    db:L -- R:server
+    disk1:T -- B:server
+    disk2:T -- B:db
+```
+
+---