📘 Project 1: AI Math Assistant (CLI)

🤖 AI Math Assistant (Gemini + LangGraph CLI Tool)

This is a command-line based AI tool powered by Google's Gemini Pro using LangGraph and LangChain. It acts as a smart math assistant that can perform arithmetic calculations interactively using natural language.

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🚀 Features

• Interactive CLI chatbot interface
• Uses Gemini via LangGraph’s ReAct agent
• Supports:
  • ✅ Sum
  • ✅ Difference
  • ✅ Product
  • ✅ Quotient (with error handling)
  • ✅ Power
  • ✅ Average (for lists)

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🧠 Built With

• LangGraph
• LangChain
• Google Gemini Pro API
• Python 3.8+

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🔧 Setup Instructions

1. Clone the repository:

git clone https://github.com/honoursbhaduria/AI_python-project.git
cd AI_python-project
cd project-1

2. Install dependencies:

pip install -r requirements.txt

3. Set up environment variables:

Create a .env file in the root directory:

GOOGLE_API_KEY=your_gemini_api_key

4. Run the app:

python app.py

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💬 Sample Interaction

You: What is the average of 10, 20, and 30?
Assistant: The result is 20.0

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📂 File Structure

.
├── app.py
├── .env
└── requirements.txt

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📄 License

This project is licensed under the MIT License.

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📄 PROJECT - 2 (AI Resume Critiquer (Streamlit + OpenAI GPT))

This project is a Streamlit web app that allows users to upload their resumes in PDF format and get real-time feedback and suggestions generated by OpenAI’s GPT models.

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🚀 Features

• Upload PDF resumes
• Analyzes:
  • Content clarity
  • Skill presentation
  • Experience descriptions
  • Tailored improvements for a specific job role
• Uses OpenAI's gpt-4o-mini or any compatible model
• Simple, elegant Streamlit interface

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🧠 Tech Stack

• Streamlit
• OpenAI Python SDK
• PyPDF2
• dotenv

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🔧 Setup Instructions

1. Clone the repository:

git clone https://github.com/honoursbhaduria/AI_python-project.git
cd AI_python-project
cd project-2

2. Install dependencies:

pip install -r requirements.txt

3. Set up your environment:

Create a .env file in the root:

OPENAI_API_KEY= your_openai_api_key 

4. Run the app:

streamlit run app.py

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📂 File Structure

.
├── app.py
├── .env
└── requirements.txt

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📄 License

MIT License