An AI-powered agent that classifies user messages to 'logical' or 'emotional' reasoning and returns responses based on that classification. If the llm ascertains the user input requires a logical response, the logical AI agent is invoked, while if an emotional response is identified then the emotional AI agent is triggered. Built with LangGraph and Anthropic.
- 📄 Two agentic chatbots are invoked
- 📄 User messages are classified into either logical or emotional responses
- ✍️ Auto-generated responses to user messages given the determined message class
- 🧠 Stateful application
- 💬 Easy prompt interface to generate applications
# Clone the repo
git clone https://github.com/ouverz/LangGraph-Tutorial.git
cd LangGraph-
# Add Anthropic API KEy to .env file
# Create venv environment (on Windows)
python -m venv <environment_name>
python <environment_name>\Scripts\activate
# Install dependencies
pip install -r requirements.txt
# Run application
python main.py
# Resource and reference
(Tech with Tim) https://github.com/techwithtim/LangGraph-Tutorial/tree/main