This repository contains tutorials and an implementation using a dynamic agent named LangGraph. Below are instructions for setting up a conda environment and running the provided code.

1. Setting Up the Conda Environment
2. Running the Code
3. Repository Structure Overview
4. Additional Notes

To run the code, you need to set up a conda environment named langgraph. Follow these steps:

If you don't have conda installed, download and install Miniconda or Anaconda from the official website.

Open a terminal and run the following command to create your environment:

conda create --name langgraph
conda activate langgraph

pip install -r requirements.txt

Navigate to the tutorials folder and run the specific tutorial script as follows:

• For Python Scripts: Open a terminal, navigate to the tutorials directory, and execute the Python script with Python or use an IDE that supports Python environments. For example:

  cd tutorials
  python 01-basic_langgraph.py

• requirements.txt: Lists all necessary packages for this project.
• readme.md: This file, providing instructions and information about the repository.
• tutorials/: Contains various tutorials related to LangGraph.
  • 01-basic_langgraph.py: An example Python script demonstrating a basic usage of LangGraph.
• langgraph_dynamic_agent/: Contains implementation details for LangGraph dynamic agent.
  • workflow_langgrapgh_dynamic_agent.py: The main script for running the LangGraph dynamic agent implementation.

Ensure that your terminal or command prompt is set to use the environment you created (langgraph). You can activate this environment anytime using conda activate langgraph. If you encounter any issues with dependencies, refer back to the section on setting up the conda environment for troubleshooting tips.