PDF Text Extractor
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PDF Text Extractor
jirimoravcik/pdf-text-extractor
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PDF Text Extractor allows you to extract text from PDF files. It also supports chunking of the text to prepare the data for usage with large language models.
.actor/Dockerfile
1# First, specify the base Docker image.
2# You can see the Docker images from Apify at https://hub.docker.com/r/apify/.
3# You can also use any other image from Docker Hub.
4FROM apify/actor-python:3.11
5
6# Second, copy just requirements.txt into the Actor image,
7# since it should be the only file that affects the dependency install in the next step,
8# in order to speed up the build
9COPY requirements.txt ./
10
11# Install the packages specified in requirements.txt,
12# Print the installed Python version, pip version
13# and all installed packages with their versions for debugging
14RUN echo "Python version:" \
15 && python --version \
16 && echo "Pip version:" \
17 && pip --version \
18 && echo "Installing dependencies:" \
19 && pip install -r requirements.txt \
20 && echo "All installed Python packages:" \
21 && pip freeze
22
23# Next, copy the remaining files and directories with the source code.
24# Since we do this after installing the dependencies, quick build will be really fast
25# for most source file changes.
26COPY . ./
27
28# Specify how to launch the source code of your Actor.
29# By default, the "python3 -m src" command is run
30CMD ["python3", "-m", "src"].actor/actor.json
1{
2 "actorSpecification": 1,
3 "name": "my-actor-7",
4 "title": "Scrape single page in Python",
5 "description": "Scrape data from single page with provided URL.",
6 "version": "0.0",
7 "meta": {
8 "templateId": "python-start"
9 },
10 "input": "./input_schema.json",
11 "dockerfile": "./Dockerfile"
12}.actor/input_schema.json
1{
2 "title": "Scrape data from a web page",
3 "type": "object",
4 "schemaVersion": 1,
5 "properties": {
6 "urls": {
7 "title": "URLs of the PDFs",
8 "type": "array",
9 "description": "The URLs of the PDF files.",
10 "prefill": ["https://arxiv.org/pdf/2307.12856"],
11 "editor": "stringList"
12 },
13 "performChunking": {
14 "title": "Perform chunking",
15 "description": "If set to true, the resulting text will be chunked according to the settings below",
16 "default": false,
17 "type": "boolean"
18 },
19 "chunkSize": {
20 "title": "Chunk size",
21 "type": "integer",
22 "description": "The maximum character length of each text chunk",
23 "default": 1000,
24 "minimum": 1
25 },
26 "chunkOverlap": {
27 "title": "Chunk overlap",
28 "type": "integer",
29 "description": "The character overlap between text chunks that are next to each other",
30 "default": 0,
31 "minimum": 0
32 }
33 },
34 "required": ["urls", "performChunking"]
35}src/__init__.py
src/__main__.py
1import asyncio
2import logging
3
4from apify.log import ActorLogFormatter
5
6from .main import main
7
8# Set up logging of messages from the Apify SDK
9handler = logging.StreamHandler()
10handler.setFormatter(ActorLogFormatter())
11
12apify_client_logger = logging.getLogger('apify_client')
13apify_client_logger.setLevel(logging.INFO)
14apify_client_logger.addHandler(handler)
15
16apify_logger = logging.getLogger('apify')
17apify_logger.setLevel(logging.DEBUG)
18apify_logger.addHandler(handler)
19
20asyncio.run(main())src/main.py
1from apify import Actor
2import pypdfium2 as pdfium
3import httpx, io, logging
4from langchain.text_splitter import RecursiveCharacterTextSplitter
5
6async def main():
7 async with Actor:
8 actor_input = await Actor.get_input() or {}
9 urls = actor_input.get('urls')
10 perform_chunking = actor_input.get('performChunking')
11
12 for url in urls:
13 try:
14 pdf = httpx.get(url)
15 pdf_document = pdfium.PdfDocument(io.BytesIO(pdf.content))
16 page_texts = []
17 for page in pdf_document:
18 textpage = page.get_textpage()
19 page_texts.append(textpage.get_text_range().replace('\r\n', '\n'))
20
21 if perform_chunking:
22 chunk_size, chunk_overlap = actor_input.get('chunkSize'), actor_input.get('chunkOverlap')
23 text_splitter = RecursiveCharacterTextSplitter(
24 chunk_size = chunk_size,
25 chunk_overlap = chunk_overlap,
26 )
27 page_texts = text_splitter.split_text('\n'.join(page_texts))
28
29 for i, text in enumerate(page_texts):
30 await Actor.push_data({
31 'url': url,
32 'index': i,
33 'text': text,
34 })
35 except Exception as e:
36 logging.error(f'Could not process URL {url} due to exception', e).dockerignore
1# configurations
2.idea
3
4# crawlee and apify storage folders
5apify_storage
6crawlee_storage
7storage
8
9# installed files
10.venv
11
12# git folder
13.git.editorconfig
1root = true
2
3[*]
4indent_style = space
5indent_size = 4
6charset = utf-8
7trim_trailing_whitespace = true
8insert_final_newline = true
9end_of_line = lf.gitignore
1# This file tells Git which files shouldn't be added to source control
2
3.idea
4.DS_Store
5
6apify_storage
7storage/*
8!storage/key_value_stores
9storage/key_value_stores/*
10!storage/key_value_stores/default
11storage/key_value_stores/default/*
12!storage/key_value_stores/default/INPUT.json
13
14.venv/
15.env/
16__pypackages__
17dist/
18build/
19*.egg-info/
20*.egg
21
22__pycache__
23
24.mypy_cache
25.dmypy.json
26dmypy.json
27.pytest_cache
28
29.scrapy
30*.logrequirements.txt
1# Add your dependencies here.
2# See https://pip.pypa.io/en/latest/reference/requirements-file-format/
3# for how to format them
4apify ~= 1.1.5
5httpx ~= 0.25.0
6pypdfium2 ~= 4.23.1
7langchain ~= 0.0.329Developer
Jiří MoravčíkMaintained by Community
Actor metrics
- 53 monthly users
- 99.3% runs succeeded
- 1.6 days response time
- Created in Oct 2023
- Modified 14 days ago
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