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20
.gitea/workflows/test.yaml
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20
.gitea/workflows/test.yaml
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name: pdf2text test
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run-name: syntax check
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on: [push]
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jobs:
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Compile:
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runs-on: ubuntu-latest
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steps:
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- name: Check out repository code
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uses: actions/checkout@v4
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- name: List files in the repository
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run: |
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ls ${{ gitea.workspace }}
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- run: echo "Install dependencies."
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- run: apt update
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- run: apt install python3
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- run: python3 -m pip install -r requirements.txt
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- run: "Check if starts correcly. Syntax check."
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- run: ./pdf2text .
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- run: echo "This job's status is ${{ job.status }}."
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@ -3,10 +3,10 @@
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I've converted 8gb of PDF's to text in one afternoon on a decade old x270 using this script. Performant enough imho. Try to get 8Gb in your LLM and getting it to actually use it. That's the challenge.
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## Convert all PDF's to text
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This is an script for converting a batch of PDF's to text for machine learning.
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This is an [script](/pdf2text) for converting a batch of PDF's to text for machine learning.
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It only has two dependencies:
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- python3
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- pdf.miner (python requirement, specified in requirements.txt file)
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- `python3`
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- `pdf.miner` (python requirement, specified in [requirements.txt](/requirements.txt) file)
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## Installation
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```bash
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@ -22,3 +22,6 @@ source .venv/bin/activate
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./pdf2text [source/destination dir]
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```
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You read that correctly, the source directory is also the destination directory.
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## Todo:
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Make decent python package so it's installable on system without having to load environment first. Not sure if worth it, it's not something you daily use.
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