* Declare BaseComponent * Brainstorming base class for LLM call * Define base LLM * Add tests * Clean telemetry environment for accurate testing * Fix README * Fix typing * add base document reader * update test * update requirements * Cosmetic change * update requirements * reformat --------- Co-authored-by: trducng <trungduc1992@gmail.com>
33 lines
1.1 KiB
Python
33 lines
1.1 KiB
Python
from pathlib import Path
|
|
|
|
from langchain.schema import Document as LangchainDocument
|
|
from llama_index.node_parser import SimpleNodeParser
|
|
|
|
from kotaemon.documents.base import Document, HaystackDocument
|
|
from kotaemon.loaders import AutoReader
|
|
|
|
|
|
def test_pdf_reader():
|
|
reader = AutoReader("PDFReader")
|
|
dirpath = Path(__file__).parent
|
|
documents = reader.load_data(dirpath / "resources/dummy.pdf")
|
|
|
|
# check document reader output
|
|
assert len(documents) == 1
|
|
|
|
first_doc = documents[0]
|
|
assert isinstance(first_doc, Document)
|
|
assert first_doc.text.lower().replace(" ", "") == "dummypdffile"
|
|
|
|
# check conversion output
|
|
haystack_doc = first_doc.to_haystack_format()
|
|
assert isinstance(haystack_doc, HaystackDocument)
|
|
|
|
langchain_doc = first_doc.to_langchain_format()
|
|
assert isinstance(langchain_doc, LangchainDocument)
|
|
|
|
# test chunking using NodeParser from llama-index
|
|
node_parser = SimpleNodeParser.from_defaults(chunk_size=100, chunk_overlap=20)
|
|
nodes = node_parser.get_nodes_from_documents(documents)
|
|
assert len(nodes) > 0
|