TikaDocumentConverter
An integration for converting files of different types (PDF, DOCX, HTML, and more) to documents.
Name | TikaDocumentConverter |
Folder path | /converters/ |
Most common position in a pipeline | Before PreProcessors, or right at the beginning of an indexing pipeline |
Mandatory input variables | "sources": File paths |
Output variables | "documents": A list of documents |
Overview
The TikaDocumentConverter
component converts files of different types (pdf, docx, html, and others) into documents. You can use it in an indexing pipeline to index the contents of files into a Document Store. It takes a list of file paths or ByteStream
objects as input and outputs the converted result as a list of documents. Optionally, you can attach metadata to the documents through the meta
input parameter.
This integration uses Apache Tika to parse the files and requires a running Tika server.
The easiest way to run Tika is by using Docker: docker run -d -p 127.0.0.1:9998:9998 apache/tika:latest
.
For more options on running Tika on Docker, see the Tika documentation.
When you initialize the TikaDocumentConverter
component, you can specify a custom URL of the Tika server you are using through the parameter tika_url
. The default URL is "http://localhost:9998/tika"
.
Usage
You need to install tika
package to use the TikaDocumentConverter
component:
pip install tika
On its own
from haystack.components.converters import TikaDocumentConverter
converter = TikaDocumentConverter()
converter.run(sources=[Path("my_file.pdf")])
In a pipeline
from haystack import Pipeline
from haystack.document_stores.in_memory import InMemoryDocumentStore
from haystack.components.converters import TikaDocumentConverter
from haystack.components.preprocessors import DocumentCleaner
from haystack.components.preprocessors import DocumentSplitter
from haystack.components.writers import DocumentWriter
document_store = InMemoryDocumentStore()
pipeline = Pipeline()
pipeline.add_component("converter", TikaDocumentConverter())
pipeline.add_component("cleaner", DocumentCleaner())
pipeline.add_component("splitter", DocumentSplitter(split_by="sentence", split_length=5))
pipeline.add_component("writer", DocumentWriter(document_store=document_store))
pipeline.connect("converter", "cleaner")
pipeline.connect("cleaner", "splitter")
pipeline.connect("splitter", "writer")
pipeline.run({"converter": {"sources": file_paths}})
Updated 7 months ago