How to build next-gen search engine using Apache Tika (with python code)

In this article, you will learn how to set up & run Apache Tika and use it in Python for semantic search.

The goal is to find relevant documents and specific parts of those documents regardless of the file format.

In the second article of this series, I will demonstrate how to utilize evidences with LLM model to generate answers to questions based on your documents. This approach not only enables you to locate desired information efficiently but also allows you to pose questions about the content within the documents themselves!

To give you more context, let’s say we have a case with legal document search:

• Scenario: A law firm has 1,000 legal documents including contracts, agreements, and case files stored in various formats like PDF, DOCX, and TXT for a client.
• Use Case: Using Apache Tika, the firm can extract text from all these documents and index them (with embeddings). This allows lawyers to quickly search for specific clauses, terms, or precedents across all documents. For instance, they could search for all instances of a particular legal term or phrase that appears in the contracts to ensure compliance or to prepare for a case.