
Most common position in a pipeline	Before PreProcessors , or right at the beginning of an indexing pipeline
Mandatory run variables	"sources": A list of file paths or ByteStream objects
Output variables	"documents": A list of documents
API reference	Converters
GitHub link	https://github.com/deepset-ai/haystack/blob/main/haystack/components/converters/csv.py

Overview

CSVToDocument converts one or more CSV files into a text document.

The component uses UTF-8 encoding by default, but you may specify a different encoding if needed during initialization.
You can optionally attach metadata to each document with a meta parameter when running the component.

Usage

On its own

from haystack.components.converters.csv import CSVToDocument

converter = CSVToDocument()
results = converter.run(sources=["sample.csv"], meta={"date_added": datetime.now().isoformat()})
documents = results["documents"]

print(documents[0].content)
# 'col1,col2\now1,row1\nrow2row2\n'

In a pipeline

from haystack import Pipeline
from haystack.document_stores.in_memory import InMemoryDocumentStore
from haystack.components.converters import CSVToDocument
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", CSVToDocument())
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_names}})