Add extraction feature

[arieljassan]

Add document classification feature before entity extraction.

[gemini-code-assist]

Summary of Changes

Hello @arieljassan, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request significantly enhances the gemini/use-cases section by adding a robust document processing solution. It allows users to classify documents and extract specific entities using Gemini models, all exposed through a Flask web service designed for deployment on Google Cloud Run. The primary goal is to provide a flexible, AI-powered tool for handling varied document structures, making it easier to integrate advanced document intelligence into applications.

Highlights

• New Feature: Document Classification and Entity Extraction: This pull request introduces a new use case that leverages Gemini models for both document classification and subsequent entity extraction, providing a flexible solution for structured information retrieval from various document types.
• Cloud Run Deployment: The new feature is packaged as a Flask-based web application, complete with a Dockerfile and a deployment script (deploy.sh), enabling easy deployment to Google Cloud Run for scalable and managed access.
• Configurable Extraction and Classification: The solution is highly configurable via a config.json file, allowing users to define different document types, their corresponding extraction schemas, and classification categories, making it adaptable to diverse use cases.
• API Endpoints: Three distinct API endpoints are provided: /extract for direct entity extraction, /classify for document classification, and /classify_and_extract for a combined operation where the document is first classified and then extracted based on the determined type.

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[gemini-code-assist]

Code Review

This pull request introduces a valuable new feature for document classification and entity extraction using Gemini. The overall structure is sound, with a clear separation of concerns between the web server, processing logic, and utilities. My feedback primarily focuses on improving logging practices for better monitoring, enhancing the robustness of configuration loading, and ensuring full adherence to the repository's style guide, particularly in the documentation and SDK usage. These changes will improve the maintainability and reliability of the new service.

[gemini-code-assist]

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[holtskinner]

@arieljassan Can you do a rebase on this branch? It's currently showing all of the commits without the ones pulled from main.