This repository contains a project to provide marketing strategy using the key input of website name.
- Python 3.11 or higher (required by langmem)
- Git
It's recommended to use a virtual environment to avoid package conflicts.
# Create a virtual environment
python -m venv venv
# Activate the virtual environment
# On Windows:
venv\Scripts\activate
# On macOS/Linux:
source venv/bin/activate
# Verify Python version (should be 3.11 or higher)
python --version
Create a .env
file in the root directory of the project based on the provided example:
cp .env.sample .env
Edit the .env
file and fill in the required variables according to your needs.
You can configure either OpenAI or Anthropic API keys in your .env
file:
# Choose one of the following API configurations
# OpenAI configuration
OPENAI_API_KEY=your_openai_api_key_here
# Anthropic configuration
ANTHROPIC_API_KEY=your_anthropic_api_key_here
Install the package in development mode:
python -m pip install -e .
This will install the package and its dependencies.
To start the development server:
langgraph dev
This will start the langgraph development server, allowing you to interact with the application.
Once your LangGraph server is running, you can access the agent interface by visiting:
https://agentchat.vercel.app/
When you first visit the site, you'll need to provide:
- Deployment URL - Your LangGraph server URL (e.g.,
http://127.0.0.1:2024
) - Assistant / Graph ID - The name of your agent (typically
agent
)
No thread ID is required as the interface will handle conversation threads automatically.
- If you encounter any issues with Python version, ensure you're using Python 3.11 or higher.
- Make sure all the environment variables in the
.env
file are correctly set. - For dependency issues, try removing the virtual environment and creating a fresh one.