Part of GPT-RAG
You can provision the infrastructure and deploy the whole solution using the GPT-RAG template, as instructed at: https://aka.ms/gpt-rag.
Eventually, you may want to make some adjustments to the data ingestion code and redeploy the component.
To redeploy only the ingestion component (after the initial deployment of the solution), you will need:
- Azure Developer CLI: Download azd for Windows, Other OS's.
- Powershell (Windows only): Powershell
- Git: Download Git
- Python 3.11: Download Python
Then just clone this repository and reproduce the following commands within the gpt-rag-ingestion directory:
azd auth login
azd env refresh
azd deploy
Note: when running the
azd env refresh, use the same environment name, subscription, and region used in the initial provisioning of the infrastructure.
How can I test the data ingestion component locally in VS Code?
To use version 4.0 of Document Intelligence, it is necessary to add the property DOCINT_API_VERSION with the value 2024-02-29-preview in the function app properties. It's important to check if this version is supported in the region where the service was created. More information can be found at this link. If the property has not been defined (default behavior), the version 2023-07-31 (3.1) will be used.
Document Intelligence Chunking
| Extension | Doc Int API version |
|---|---|
| 3.1, 4.0 | |
| bmp | 3.1, 4.0 |
| jpeg | 3.1, 4.0 |
| png | 3.1, 4.0 |
| tiff | 3.1, 4.0 |
| docx | 4.0 |
| pptx | 4.0 |
| xlsx | 4.0 |
| html | 4.0 |
Langchain text Splitters Chunking
| Extension | Format |
|---|---|
| txt | text |
| html | html |
| shtml | html |
| htm | html |
| py | python |
| json | json |
| csv | csv |
| epub | epub |
| rtf | rtf |
| xml | xml |
| xlsx | xlsx |
| xls | xls |
| pptx | pptx |
| ppt | ppt |
| msg | msg |
Note: First, based on the file extension check if it can be processed with Document Intelligence and then chunked. If not, just use the content extracted by AI Search and attempt to perform chunking with Langchain text splitter.
Azure Open AI Embeddings Generator
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