https://github.com/kiview/langchain-jupyter-tcc-example

Example notebook for using LangChain in a Jupyter Notebook, running on GPU-enabled Testcontainers Cloud workers
https://github.com/kiview/langchain-jupyter-tcc-example

Last synced: 28 days ago
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Example notebook for using LangChain in a Jupyter Notebook, running on GPU-enabled Testcontainers Cloud workers

• Host: GitHub
• URL: https://github.com/kiview/langchain-jupyter-tcc-example
• Owner: kiview
• License: mit
• Created: 2024-05-28T12:14:57.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-05-28T12:49:06.000Z (5 months ago)
• Last Synced: 2024-05-29T03:47:18.699Z (5 months ago)
• Language: Jupyter Notebook
• Size: 5.86 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Requirements

You need Docker and Python installed on your machine.

You also need to have Testcontainers Cloud installed and running and connected to a GPU-enabled zone.

# Setup

Create a virtual environment and install the requirements:

```bash

python3 -m venv venv

source venv/bin/activate

pip install -r requirements.txt

```

# Running the examples

Start the Juputer Lab server:

```bash

jupyter lab

```

Open the notebook `gpu.ipynb` and run the cells.

You will see an Ollama Docker container being started, including GPU access.

It will be wired up using LangChain and you can interactively explore the framework and model.