The PDF to Text API returns plain text extracted from the uploaded PDF file. This includes all textual content, such as paragraphs, headings, bullet points, and tables, structured in a way that reflects the original document's layout as closely as possible.

The response data primarily includes a single field containing the extracted text. Depending on the implementation, additional metadata such as the original PDF file name or processing status may also be included.

The primary parameter for the POST Get Text endpoint is the PDF file itself, which must be attached to the API request. There are no additional customizable parameters for this endpoint.

The response data is organized as a JSON object, with the extracted text presented as a single string. This allows users to easily parse and utilize the text in their applications or workflows.

Typical use cases include document analysis, content extraction for databases, text-to-speech conversion, and automated workflows for processing incoming PDF files. Users can leverage the extracted text for various applications, such as sentiment analysis or data archiving.

Data accuracy is maintained through advanced algorithms that ensure precise extraction of text from PDFs. The API is designed to handle various content types and layouts, minimizing errors during the conversion process.

Users can utilize the returned text for further processing, such as indexing, searching, or integrating into other applications. The structured format allows for easy manipulation and analysis of the extracted content.

The endpoint provides access to all textual information contained within the PDF, including formatted text, tables, and lists. This comprehensive extraction enables users to access a wide range of data for various applications.

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