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Code for the blog post "Scaling NLP indexing pipelines with KEDA"

  • Scaling NLP indexing pipelines with KEDA and Haystack — Part 1: The Application (link)
  • Scaling NLP indexing pipelines with KEDA and Haystack — Part 2: Deployment (link)

Development

To run the consumer locally against localstack, we need to start localstack by running the following command:

# Start localstack
docker-compose up 

Afterwards, we install the dependencies and run the consumer:

pip3 install -r requirements.txt
python3 consumer.py

You should see logs like

❯ python3 consumer.py
2023-04-21 15:34:26 [info     ] No files to upload
2023-04-21 15:34:31 [info     ] Found files                    files=[PosixPath('/tmp/test.txt'), PosixPath('/tmp/test.txt'), PosixPath('/tmp/test.txt'), PosixPath('/tmp/test.txt')]
2023-04-21 15:34:31 [info     ] No files to upload
2023-04-21 15:34:36 [info     ] No files to upload

To upload files to test the consumer, we can run the following command:

python3 upload.py

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Example code for scaling NLP indexing pipelines with KEDA

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