TheOgBoat 🚤

The Original AI Chatbot — powered by Groq, LangChain, and Streamlit. Fast, free, and runs the most powerful open-source LLMs in the cloud.

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What is TheOgBoat?

TheOgBoat is the original, no-nonsense AI chatbot that sails through your questions with speed and precision. Built with cutting-edge tools — Groq's blazing-fast inference, LangChain's powerful prompt chaining, and Streamlit's clean UI — TheOgBoat delivers smart answers without any cloud setup or GPU required.

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Features

• ⚡ Blazing Fast — powered by Groq's ultra-fast LLM inference
• 🧠 Multiple Models — switch between LLaMA 4, LLaMA 3.3, Qwen3, and more
• 🎛️ Full Control — adjust temperature and max tokens from the sidebar
• 💬 Chat History — full conversation memory within each session
• 🔒 Private & Secure — API keys stored safely, never exposed in code
• 📊 LangSmith Tracking — monitor and trace every prompt

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Demo

User: What is the theory of relativity?
TheOgBoat: The theory of relativity, developed by Albert Einstein...

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Getting Started

1. Prerequisites

• Python 3.10+
• A free Groq API key
• A free LangSmith API key (optional)

2. Clone the repo

git clone https://github.com/YOUR_USERNAME/TheOgBoat.git
cd TheOgBoat

3. Install dependencies

pip install -r requirements.txt

4. Set up environment variables

Create a .env file in the root directory:

GROQ_API_KEY=your_groq_api_key_here
LANGCHAIN_API_KEY=your_langsmith_api_key_here

5. Run the app

streamlit run app.py

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Project Structure

TheOgBoat/
├── app.py              # Main Streamlit app
├── requirements.txt    # Python dependencies
├── .env                # API keys (never commit this)
├── .gitignore          # Ignores .env and venv
└── README.md

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Available Models

Model	Best For
llama-3.3-70b-versatile	Best overall performance
llama-3.1-8b-instant	Fast & lightweight responses
meta-llama/llama-4-scout-17b-16e-instruct	Latest Llama 4 capabilities
qwen/qwen3-32b	Strong reasoning & logic
openai/gpt-oss-120b	Most powerful responses

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Environment Variables

Variable	Description
GROQ_API_KEY	Your Groq API key for LLM inference
LANGCHAIN_API_KEY	Your LangSmith key for prompt tracking

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Deploying on Streamlit Cloud

1. Push your code to GitHub (without .env)
2. Go to share.streamlit.io
3. Connect your GitHub repo
4. Go to Advanced settings → Secrets and add:

GROQ_API_KEY = "your_groq_api_key_here"
LANGCHAIN_API_KEY = "your_langsmith_api_key_here"

5. Click Deploy 🚀

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Tech Stack

Tool	Purpose
Groq	Ultra-fast LLM inference
LangChain	Prompt chaining & LLM abstraction
Streamlit	Web UI
LangSmith	Prompt tracking & observability
python-dotenv	Environment variable management

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Contributing

Pull requests are welcome! Feel free to open an issue for bugs or feature requests.

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License

MIT — feel free to use, modify, and share.

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Built with ❤️ by samarthx4216 — TheOgBoat ⛵