SelectorPlus LangGraph Project Setup
This guide will walk you through the steps to set up and run the SelectorPlus LangGraph project.

Prerequisites
Docker: Ensure Docker is installed on your system.
Python 3.8+: Make sure Python 3.8 or a later version is installed.
Git: For cloning the repository.
Setup Instructions
Clone the Repository:

git clone <your_repository_url>
cd Selector-

Create a .env File:

In the root directory of your project, create a file named .env.

Copy and paste the following environment variables into the .env file:

OPENAI_API_KEY=

WEATHER_API_KEY=

ABUSEIPDB_API_KEY=

LANGSMITH_TRACING=true

LANGSMITH_API_KEY=""

LANGSMITH_ENDPOINT="https://api.smith.langchain.com"

LANGSMITH_PROJECT="SelectorPlus"

GITHUB_TOKEN=""

GOOGLE_MAPS_API_KEY=""

SLACK_BOT_TOKEN=""

SLACK_TEAM_ID=""

SELECTOR_AI_API_KEY=

SELECTOR_URL=

Important: Keep your .env file secure, as it contains sensitive API keys. Do not commit it to version control.

Build Docker Images:

Navigate to each directory containing a Dockerfile and build the Docker images.

Bash

For the GitHub MCP

docker build -t github-mcp ./github

For the Google Maps MCP

docker build -t maps-mcp ./google_maps

For the Sequential Thinking MCP

docker build -t sequential-thinking-mcp ./sequentialthinking

For the Slack MCP

docker build -t slack-mcp ./slack

For the Selector AI MCP

docker build -t selector-mcp ./selector Run the LangGraph Application:

Navigate to the directory containing your main Python script (the one that runs the LangGraph application).

Run the Python script:

python selectorplus.py

Interact with the Application:

Follow the prompts in the terminal to interact with your LangGraph application.

The application will use the Docker containers and environment variables to execute the tools and interact with external services.

Important Notes

API Keys: Ensure that all API keys are valid and have the necessary permissions.

Docker Containers: Make sure that all Docker containers are running correctly. You can check the status of your containers using docker ps.

Error Handling: Pay close attention to the logs and error messages in the terminal to diagnose any issues.

Security: Be cautious when handling API keys and sensitive information.

This README should provide a clear and concise guide to setting up and running your LangGraph project. If you encounter any issues, refer to the logs and error messages for further debugging.