datadm 0.3.6

DataDM is your private data assistant. Slide into your data's DMs

dataDM 💬📊

DataDM is your private data assistant. A conversational interface for your data where you can load, clean, transform, and visualize without a single line of code. DataDM is open source and can be run entirely locally, keeping your juicy data secrets fully private.

Demo

https://github.com/approximatelabs/datadm/assets/916073/f15e6ab5-8108-40ea-a6de-c69a1389af84

Note: Demo above is GPT-4, which sends the conversation to OpenAI's API. To use in full local mode, be sure to select starchat-alpha-cuda or starchat-beta-cuda as the model. This will use the StarChat model, which is a bit less capable but runs entirely locally.

⚠️ LLMs are known to hallucinate and generate fake results. So, double-check before trusting their results blindly!

⇒ Try it now! Hosted public environment is live! (Click Here) ⇐

Don't put any sensitive data in the public environment, use the docker image or colab notebook for your private conversations.

Join our discord to join the community and share your thoughts!

Features

• Persistent Juptyer kernel backend for data manipulation during conversation
• Run entirely locally, keeping your data private
• Natural language chat, visualizations/plots, and direct download of data assets
• Easy to use docker-images for one-line deployment
• Load multiple tables directly into the chat
• Search for data and load CSVs directly from github
• Option to use OpenAI's GPT-3.5 or GPT-4 (requires API key)
• WIP: GGML based mode (CPU only, no GPU required)
• WIP: Rollback kernel state when undo using criu (re-execute all cells)
• TODO: Support for more data sources (e.g. SQL, S3, PySpark etc.)
• TODO: Export a conversation as a notebook or html

Things you can ask DataDM

• Load data from a URL
• Clean data by removing duplicates, nulls, outliers, etc.
• Join data from multiple tables into a single output table
• Visualize data with plots and charts
• Ask whatever you want to your very own private code-interpreter

Quickstart

You can use docker, colab, or install locally.

1. Docker to run locally

docker run -e OPENAI_API_KEY={{YOUR_API_KEY_HERE}} -p 7860:7860 -it ghcr.io/approximatelabs/datadm:latest

For local-mode using StarChat model (requiring a CUDA device with at least 24GB of RAM)

docker run --gpus all -p 7860:7860 -it ghcr.io/approximatelabs/datadm:latest-cuda

2. Colab to run in the cloud

3. Use as a python package

⚠️ datadm used this way runs LLM generated code in your userspace

For local-data, cloud-model mode (no GPU required) - requires an OpenAI API key

$ pip install datadm
$ datadm

For local-mode using StarChat model (requiring a CUDA device with at least 24GB of RAM)

$ pip install "datadm[cuda]"
$ datadm

Special Thanks

• starchat-beta (starcoder with databricks-dolly and OpenAssistant/oasst1)
• Guidance
• HuggingFace
• OpenAI

Contributions

Contributions are welcome! Feel free to submit a PR or open an issue.

Community

Join the Discord to chat with the team

Check out our other projects: sketch and approximatelabs