| Name | datadm JSON |
| Version |
0.3.6
JSON |
| download |
| home_page | |
| Summary | DataDM is your private data assistant. Slide into your data's DMs |
| upload_time | 2023-08-23 22:38:49 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.8 |
| license | MIT License Copyright (c) 2023 Approximate Labs Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
nlp
ai
data
chatbot
database
csv
analytics
datachat
datadm
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# [dataDM](https://github.com/approximatelabs/datadm) 💬📊
[](https://pypi.org/project/datadm/)
[](https://github.com/approximatelabs/datadm/actions/workflows/test-build-publish.yml)
[](https://colab.research.google.com/github/approximatelabs/datadm/blob/main/datadm.ipynb)
[](https://discord.gg/kW9nBQErGe)
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)](https://datadm.approx.dev/new)* ⇐
Don't put any sensitive data in the public environment, use the docker image or colab notebook for your private conversations.
### Join our [discord](https://discord.gg/kW9nBQErGe) to join the community and share your thoughts!
## Features
- [x] Persistent Juptyer kernel backend for data manipulation during conversation
- [x] Run entirely locally, keeping your data private
- [x] Natural language chat, visualizations/plots, and direct download of data assets
- [x] Easy to use docker-images for one-line deployment
- [x] Load multiple tables directly into the chat
- [x] Search for data and load CSVs directly from github
- [x] 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
- [x] Load data from a URL
- [x] Clean data by removing duplicates, nulls, outliers, etc.
- [x] Join data from multiple tables into a single output table
- [x] Visualize data with plots and charts
- [x] 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
```bash
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)
```bash
docker run --gpus all -p 7860:7860 -it ghcr.io/approximatelabs/datadm:latest-cuda
```
### 2. Colab to run in the cloud
[](https://colab.research.google.com/github/approximatelabs/datadm/blob/main/datadm.ipynb)
### 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
```bash
$ pip install datadm
$ datadm
```
For local-mode using StarChat model (requiring a CUDA device with at least 24GB of RAM)
```bash
$ pip install "datadm[cuda]"
$ datadm
```
## Special Thanks
* [starchat-beta](https://huggingface.co/HuggingFaceH4/starchat-beta) ([starcoder](https://github.com/bigcode-project/starcoder) with [databricks-dolly](https://huggingface.co/datasets/databricks/databricks-dolly-15k) and [OpenAssistant/oasst1](https://huggingface.co/datasets/OpenAssistant/oasst1))
* [Guidance](https://github.com/microsoft/guidance)
* [HuggingFace](https://huggingface.co/)
* [OpenAI](https://openai.com/)
## Contributions
Contributions are welcome! Feel free to submit a PR or open an issue.
## Community
Join the [Discord](https://discord.gg/kW9nBQErGe) to chat with the team
Check out our other projects: [sketch](https://github.com/approximatelabs/sketch) and [approximatelabs](https://approximatelabs.com)
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"description": "# [dataDM](https://github.com/approximatelabs/datadm) \ud83d\udcac\ud83d\udcca\n\n[](https://pypi.org/project/datadm/)\n[](https://github.com/approximatelabs/datadm/actions/workflows/test-build-publish.yml)\n[](https://colab.research.google.com/github/approximatelabs/datadm/blob/main/datadm.ipynb)\n[](https://discord.gg/kW9nBQErGe)\n\n\n\nDataDM 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.\n\n## Demo\n\nhttps://github.com/approximatelabs/datadm/assets/916073/f15e6ab5-8108-40ea-a6de-c69a1389af84\n\nNote: 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.\n\n\u26a0\ufe0f LLMs are known to hallucinate and generate fake results. So, double-check before trusting their results blindly!\n\n### \u21d2 *[Try it now! Hosted public environment is live! (Click Here)](https://datadm.approx.dev/new)* \u21d0\nDon't put any sensitive data in the public environment, use the docker image or colab notebook for your private conversations.\n\n### Join our [discord](https://discord.gg/kW9nBQErGe) to join the community and share your thoughts!\n\n## Features\n- [x] Persistent Juptyer kernel backend for data manipulation during conversation\n- [x] Run entirely locally, keeping your data private\n- [x] Natural language chat, visualizations/plots, and direct download of data assets\n- [x] Easy to use docker-images for one-line deployment\n- [x] Load multiple tables directly into the chat\n- [x] Search for data and load CSVs directly from github\n- [x] Option to use OpenAI's GPT-3.5 or GPT-4 (requires API key)\n- [ ] WIP: GGML based mode (CPU only, no GPU required)\n- [ ] WIP: Rollback kernel state when undo ~using `criu`~ (re-execute all cells)\n- [ ] TODO: Support for more data sources (e.g. SQL, S3, PySpark etc.)\n- [ ] TODO: Export a conversation as a notebook or html\n\n## Things you can ask DataDM\n- [x] Load data from a URL\n- [x] Clean data by removing duplicates, nulls, outliers, etc.\n- [x] Join data from multiple tables into a single output table\n- [x] Visualize data with plots and charts\n- [x] Ask whatever you want to your very own private code-interpreter\n\n## Quickstart\n\nYou can use docker, colab, or install locally.\n\n### 1. Docker to run locally\n```bash\ndocker run -e OPENAI_API_KEY={{YOUR_API_KEY_HERE}} -p 7860:7860 -it ghcr.io/approximatelabs/datadm:latest\n```\n\nFor local-mode using StarChat model (requiring a CUDA device with at least 24GB of RAM)\n```bash\ndocker run --gpus all -p 7860:7860 -it ghcr.io/approximatelabs/datadm:latest-cuda\n```\n\n### 2. Colab to run in the cloud\n[](https://colab.research.google.com/github/approximatelabs/datadm/blob/main/datadm.ipynb)\n\n\n### 3. Use as a python package\n\n> \u26a0\ufe0f datadm used this way runs LLM generated code in your userspace\n\nFor local-data, cloud-model mode (no GPU required) - requires an OpenAI API key\n```bash\n$ pip install datadm\n$ datadm\n```\n\nFor local-mode using StarChat model (requiring a CUDA device with at least 24GB of RAM)\n```bash\n$ pip install \"datadm[cuda]\"\n$ datadm\n```\n\n## Special Thanks\n\n* [starchat-beta](https://huggingface.co/HuggingFaceH4/starchat-beta) ([starcoder](https://github.com/bigcode-project/starcoder) with [databricks-dolly](https://huggingface.co/datasets/databricks/databricks-dolly-15k) and [OpenAssistant/oasst1](https://huggingface.co/datasets/OpenAssistant/oasst1))\n* [Guidance](https://github.com/microsoft/guidance)\n* [HuggingFace](https://huggingface.co/)\n* [OpenAI](https://openai.com/)\n\n## Contributions\n\nContributions are welcome! Feel free to submit a PR or open an issue.\n\n## Community\n\nJoin the [Discord](https://discord.gg/kW9nBQErGe) to chat with the team\n\nCheck out our other projects: [sketch](https://github.com/approximatelabs/sketch) and [approximatelabs](https://approximatelabs.com)\n",
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