https://github.com/azure-samples/multimodal_rag_python
Python notebook for solving overlapping tables problem with Azure document intelligence , semantic chunking, RAG , Azure AI Search
https://github.com/azure-samples/multimodal_rag_python
aisearch documentintelligence langchain rag
Last synced: about 1 year ago
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Python notebook for solving overlapping tables problem with Azure document intelligence , semantic chunking, RAG , Azure AI Search
- Host: GitHub
- URL: https://github.com/azure-samples/multimodal_rag_python
- Owner: Azure-Samples
- Created: 2024-09-04T11:35:14.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-09-04T12:06:52.000Z (almost 2 years ago)
- Last Synced: 2025-03-29T12:03:35.768Z (about 1 year ago)
- Topics: aisearch, documentintelligence, langchain, rag
- Language: Jupyter Notebook
- Homepage:
- Size: 10.7 KB
- Stars: 9
- Watchers: 9
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Hierarchical data and multimodal RAG using Semantic Chunking and Langchain
This repo is built as a demo for the Hierarchical data table which overlaps to different pages without header. It uses Langchain, Semantic Chunking, Azure Document intelligence and AI Search
Please insert your file and try the lab
## Prerequisites
Before running the notebook, make sure you have the following installed:
1. Python: Install the latest version of Python from the official website.
2. Jupyter Notebook: Install Jupyter Notebook using the following command in PowerShell:
```
pip install jupyter
```
To replace the multi_page_table.pdf with your document, follow these steps:
1. Open the existing document.
2. Locate the multi_page_table section.
3. Replace the content of the multi_page_table.pdf path with the path of the existing document and change the name references
4. Save the changes.
## Steps
1. Clone the repository:
```
git clone
```
2. Navigate to the project directory:
```
cd
```
3. Create a virtual environment (optional but recommended):
```
python -m venv venv
```
4. Activate the virtual environment:
```
.\venv\Scripts\activate
```
5. Install the required dependencies:
```
pip install -r requirements.txt
```
6. Install Jupyter Notebook:
```
pip install jupyter
```
7. Launch Jupyter Notebook:
```
jupyter notebook
```
8. In your web browser, navigate to the notebook file (`lab.ipynb`) and open it.
9. Run the notebook cells one by one to execute the demo , replace the document location
That's it! You have successfully run the demo Python notebook in Windows PowerShell.