To use Haystack for extracting structured data from documents, you first need to set up your environment by installing Haystack and its dependencies. Haystack is an open-source framework designed for building search systems and includes tools for document processing and data extraction. You can install it using pip, typically with a command like pip install farm-haystack. Once that’s done, you will need to choose the specific document reader and processing techniques suitable for your use case. For example, if you are working with PDFs or Word documents, consider using the Document Store and Pipelines provided by Haystack to interact with different document formats effectively.
Next, you need to load your documents into the Haystack framework. The standard approach involves using the Document Store, where you can upload your documents in various formats. Haystack supports several document stores such as Elasticsearch and FAISS. Once documents are loaded, you can define a pipeline that specifies how to process these documents for data extraction. For structured data extraction, you may consider using the FARMReader or TQA (Table Question Answering) which is particularly useful when extracting information from tables in documents. The pipeline is modular, allowing you to add different components for processing, such as pre-processing steps, readers to perform the extraction, and post-processing to structure the output data as required.
Finally, after setting up the pipeline, you can run it to extract data. Invoke the pipeline with your input documents, and the readers will analyze the content to retrieve structured information based on your queries. The results can be formatted for storage or further analysis. For example, if you are extracting customer data from invoices, your queries might target specific fields like “customer name,” “invoice number,” or “total amount.” By directing queries to the right components and properly configuring the pipeline, you can achieve accurate and organized data outputs tailored to your applications.