🤖 AI Text Processing Assistant

Production-Style AI Automation Project for Intelligent Text Analysis, Prompt Engineering, and Structured Data Processing

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📖 Overview

A production-style AI Text Processing Assistant developed as part of the AI Automation & Workflow Engineering learning journey.

The application processes unstructured meeting notes using a Local Large Language Model (LLM) powered by Ollama, generating summaries, extracting key points, identifying action items, converting information into structured JSON, and automatically saving all generated outputs.

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🚀 Features

• AI-powered meeting summarization
• Key point extraction
• Action item extraction
• Structured JSON generation
• Automatic output saving
• Prompt template management
• Centralized logging
• Centralized validation
• Retry mechanism for AI responses
• Local LLM integration using Ollama
• Production-style project architecture

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🏗️ Project Architecture

                 User Input
                      │
                      ▼
              Input Validation
                      │
                      ▼
             Prompt Construction
                      │
                      ▼
                Ollama (LLM)
                      │
                      ▼
             AI Generated Output
          ┌────────┼────────┐
          ▼        ▼        ▼
      Summary   Key Points  Action Items
                      │
                      ▼
             Structured JSON
                      │
                      ▼
          Validation & Saving
                      │
                      ▼
             Output Files + Logs

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📁 Project Structure

AI-Text-Processing-Assistant/

│
├── app.py
├── requirements.txt
├── README.md
├── .env.example
├── .gitignore
│
├── config/
│   └── config.py
│
├── data/
│   └── meeting_notes.txt
│
├── logs/
│   └── application.log
│
├── outputs/
│
├── prompts/
│   ├── summary_prompt.txt
│   ├── key_points_prompt.txt
│   ├── action_items_prompt.txt
│   └── json_prompt.txt
│
├── services/
│   ├── ai_client.py
│   ├── summarizer.py
│   ├── key_points.py
│   ├── action_items.py
│   └── json_generator.py
│
└── utils/
    ├── file_handler.py
    ├── logger.py
    ├── prompt_loader.py
    ├── save_json.py
    ├── save_text.py
    └── validator.py

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⚙️ Technologies Used

• Python 3
• Ollama
• Llama 3.2
• OpenAI Python SDK (compatible client)
• python-dotenv
• JSON
• Logging Module
• Git
• GitHub

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📥 Installation

Clone the repository:

git clone https://github.com/<YOUR_USERNAME>/AI-Text-Processing-Assistant.git

Navigate to the project:

cd AI-Text-Processing-Assistant

Create a virtual environment:

python -m venv .venv

Activate the virtual environment.

Windows:

.venv\Scripts\activate

Install dependencies:

pip install -r requirements.txt

Install Ollama and download the model:

ollama pull llama3.2

Create your .env file using .env.example.

Run the application:

python app.py

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🔄 Application Workflow

1. Read meeting notes.

2. Validate input.

3. Load prompt templates.

4. Send prompts to the local LLM.

5. Generate:

   • Summary
   • Key Points
   • Action Items
   • Structured JSON

6. Validate generated JSON.

7. Save outputs automatically.

8. Generate application logs.

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📄 Sample Output

The application automatically generates:

outputs/

summary.txt

key_points.txt

action_items.txt

analysis.json

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📚 Learning Outcomes

This project demonstrates practical experience with:

• AI Automation
• Prompt Engineering
• Local Large Language Models
• JSON Processing
• Python Automation
• Logging
• Validation
• Modular Software Design
• AI Workflow Development
• Git & GitHub
• Production-style Project Organization

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🔮 Future Improvements

• SQLite integration
• PostgreSQL support
• REST API
• FastAPI backend
• Streamlit web interface
• Multi-document processing
• Batch processing
• PDF support
• DOCX support
• Docker containerization
• Cloud LLM support
• OpenAI API integration
• RAG (Retrieval-Augmented Generation)

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📄 License

This project is developed for educational and portfolio purposes.

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👨‍💻 Author

Abdul Qadeer

Cyber Security Undergraduate

AI Automation & Workflow Engineering Learner

GitHub: https://github.com/qaadeer55