https://github.com/CYQIQ/MultiCoT
Repository to demonstrate Chain of Table reasoning with multiple tables powered by LangGraph
https://github.com/CYQIQ/MultiCoT
Last synced: 5 months ago
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Repository to demonstrate Chain of Table reasoning with multiple tables powered by LangGraph
- Host: GitHub
- URL: https://github.com/CYQIQ/MultiCoT
- Owner: CYQIQ
- Created: 2024-02-14T18:52:36.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-04-09T18:21:39.000Z (about 1 year ago)
- Last Synced: 2024-08-09T02:17:17.982Z (8 months ago)
- Language: Jupyter Notebook
- Size: 910 KB
- Stars: 142
- Watchers: 3
- Forks: 22
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
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- jimsghstars - CYQIQ/MultiCoT - Repository to demonstrate Chain of Table reasoning with multiple tables powered by LangGraph (Jupyter Notebook)
README
# MultiCoT
## Overview
`MultiCoT` is a repository that demonstrates [Chain-of-Table](https://arxiv.org/abs/2401.04398) reasoning on multiple tables powered by [LangGraph](https://github.com/langchain-ai/langgraph).
Try the hosted demo: https://cyqiq-cot-demo-c27oq5sqda-uc.a.run.app/
## Installation
Follow these steps to set up `MultiCoT`:
1. **Clone the Repository**
```
git clone https://github.com/CYQIQ/MultiCoT.git
```
2. **Install Dependencies**
Navigate to the repository directory and run:
```
pip install -r requirements.txt
```
3. **Configure API Keys**
Create a `.env` file in the root directory. Add your OpenAI API key and LangChain API details as follows:
```
OPENAI_API_KEY="..."
LANGCHAIN_API_KEY="..."
LANGCHAIN_TRACING_V2="..."
LANGCHAIN_ENDPOINT="..."
LANGCHAIN_PROJECT="..."
```
## Usage
For detailed instructions on how to run `MultiCoT`, refer to the `CYQIQ_COT.ipynb` Jupyter Notebook within the repository.
## Data
The `data` directory includes an example dataset comprised of 6 CSV files necessary to run the notebook. To run MultiCoT with your own data, change the data loading logic and the table descriptions in `CYQIQ_COT.ipynb`
## Help
Feel free to email us at [email protected]
## Acknowledgments
- Big thanks to [@hwchase17](https://github.com/hwchase17) and team [LangChain](https://github.com/langchain-ai) for their amazing guides.
- Big thanks to [@zaturalma2](https://github.com/zaturalma2) for helping put the notebook together.