LLMAgent/ ├── .env ├── pyproject.toml ├── poetry.lock ├── sample_notebook.ipynb └── README.md (optional)

1. Open a terminal and create a new directory for your project
2. Initialize a new Poetry project poetry init
3. Add Required Dependencies

• poetry add langchain
• poetry add python-dotenv
• poetry add huggingface_hub
• poetry add googlesearch-results
• poetry add tiktoken
• poetry add jupyter # Required for running .ipynb files

poetry shell

conda --version

poetry export -f requirements.txt --output requirements.txt --without-hashes

conda env list base * /opt/anaconda3 LLMAgentEnv /opt/anaconda3/envs/LLMAgentEnv conda activate LLMAgentEnv

conda env create -n LLMAgentEnv --file /Users/anjandebnath/Documents/PythonWorkspace/LLMAgent/environment.yml

anaconda-navigator

1. poetry install

2. The init.py file tells the Python interpreter to treat a directory as a package, allowing you to import modules from it. Run the ZenMl server

3. OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES poetry run zenml up

4. poetry run python run_pipeline.py

5. ETL pipeline: Dashboard URL for Pipeline Run: http://127.0.0.1:8237/projects/default/runs/8ba73d94-532a-4e79-b019-c03d64986f51

6. MongoDB connect: mongodb://localhost:27017

7. Stop docker and zenml dashboard after testing