z zz2115

Implementation Documentation for Agentic LLM Workflow: macOS ScreenMate (SwiftUI First - Direct VLM, In-Memory Screenshot, Custom Prompts)

1. Overall Project Goal:

Develop a native macOS application ("ScreenMate") that:

Runs as a menubar accessory application (no Dock icon).
Provides advanced image understanding functionality triggered by a screenshot, capturing the image into memory (as an NSImage) and processing it using a locally loaded Vision Language Model (VLM) via MLX Swift, with an option for users to provide custom prompts. (OCR is one of its capabilities).
Features a main interface in a menubar popover panel.
Features a "Custom Prompt" floating panel allowing users to input their own VLM prompts for image processing.
Allows configuration for auto-starting at login and selecting a VLM model from a predefined list.
Uses SwiftUI for UI components where feasible, and AppKit for system integrations and panel management.

You are a highly decorated, nationally recognized AP teacher with 15+ years of experience fostering critical thinking and exam success. A student has come to you for help with the following question. Provide a comprehensive, step-by-step solution, mirroring how you would explain it to a student in class. Include: a clear restatement of the question's core task, identification of relevant concepts/historical context/formulas/theories, a detailed breakdown of the solution process (showing all work where applicable), justification for each step, potential pitfalls students often encounter, and a concluding statement summarizing the answer and offering advice for similar problems. Assume the student has a solid foundational understanding of the course material but needs guidance applying it to this specific challenge.

Retail Banking

Actions of a Great Data Scientist

Instead of simply copying notebooks, a great data scientist would:

Create original solutions tailored to specific business problems
Deeply understand and properly document methodologies
Build upon others' work while adding significant improvements
Contribute back to the community with novel approaches

Rather than training models blindly, they would:

The Cypher Style Guide

Graph technology is particularly well-suited for fraud detection because fraud often involves complex, hidden relationships between seemingly unrelated entities (people, accounts, devices, locations, transactions). Graph databases excel at modeling, traversing, and analyzing these connections in ways traditional relational databases struggle with.

Key Graph Techniques Used:

Link Analysis: This involves tracing direct and indirect connections between different entities (nodes) in the graph. It helps uncover suspicious relationships, such as an applicant sharing an address or phone number with a known fraudster, even several connections away.

Community Detection: Algorithms like Louvain identify clusters or tightly-knit groups of entities within the graph. These communities can represent organized fraud rings collaborating on activities like creating synthetic ident

https://github.com/koaning

	<!DOCTYPE html>

	<html lang="en">
	<head><meta charset="utf-8"/>
	<meta content="width=device-width, initial-scale=1.0" name="viewport"/>
	<title>Financial Fraud Detection Using Python</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script>
	<style type="text/css">
	pre { line-height: 125%; }
	td.linenos .normal { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; }

	from sqlalchemy.dialects import registry
	from sqlalchemy.dialects.postgresql.psycopg2 import PGDialect_psycopg2
	class RedshiftPostgresDialect(PGDialect_psycopg2):
	def _set_backslash_escapes(self, connection):
	self._backslash_escapes = "off"
	registry.register("redshift_custom", __name__, "RedshiftPostgresDialect")

	from sqlalchemy import create_engine
	db = create_engine("redshift_custom://user:password@redshifthost:5439/dev")

z zz2115

Implementation Documentation for Agentic LLM Workflow: macOS ScreenMate (SwiftUI First - Direct VLM, In-Memory Screenshot, Custom Prompts)

1. Overall Project Goal:

Actions of a Great Data Scientist

The Cypher Style Guide

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