🧠 Vision Assistant Project

This assistant helps team members navigate apps, capture screens, interpret text, and generate intelligent guidance using free AI tools. Below is the tech stack and instructions for customizing your department’s version.

🧱 Full Stack Overview

Layer	Tool/Tech	Role
Interface	Gradio / Streamlit	Launch user-friendly UI
Screen Input	Python + OpenCV	Capture screen or window
Text Recognition	Tesseract OCR	Extract readable content
Vision Model	Moondream 2 / BLIP / LLaVA	Understand UI elements
Language Model	Mistral 7B / Phi-2 / LLaMA 3	Natural-language reasoning
Orchestrator	LangChain	Connect vision, language, and actions
Local Hosting	LocalAI	Run everything without cloud
Audio Input (optional)	Whisper.cpp	Voice commands support

📦 Dependency Installation Links

• OpenCV (cv2) – PyPI
• Tesseract OCR – PyPI
• Tesseract Binary – GitHub
• Gradio – PyPI
• LangChain – PyPI
• LocalAI – Official Site
• Mistral 7B – Hugging Face
• Moondream 2 – Hugging Face
• Whisper.cpp – GitHub

📁 File Structure

vision-assistant/
├── app.py
├── capture_screen.py
├── ocr_engine.py
├── vision_model.py
├── language_model.py
├── agent_logic.py
├── config.yaml
├── requirements.txt
├── README.md
└── utils/
    ├── image_utils.py
    └── text_utils.py

🚀 Example: Main Interface (app.py)

import gradio as gr
from agent_logic import process_screen

gr.Interface(fn=process_screen, inputs=[], outputs="text", title="Vision Assistant").launch()

📂 Each Team’s Custom Version

Team members can edit agent_logic.py and config.yaml to tailor prompts and task automation logic to their department workflows (e.g., HR onboarding, Sales CRM navigation).

📣 Contribution Guidelines

Please add any improvements, utilities, or department workflows to the shared Git repo. Make sure your models are locally hosted or cloud-safe per your privacy standards.

🔐 Privacy Reminder

This assistant is built for local use. Make sure sensitive data is handled according to your organization’s internal guidelines.