pipeline have not been created

As an AI language model, I do not have access to your specific project or task, so I cannot provide a specific answer. However, here are some general steps to create a pipeline:

1. Identify the task you want to perform using a pipeline, such as natural language processing, image classification, or anomaly detection.

2. Choose the appropriate tools and libraries for your task. For example, if you are working with text, you might use NLTK or SpaCy, while for image processing, you might use OpenCV or TensorFlow.

3. Identify the different steps in your pipeline. For example, in a natural language processing pipeline, you might include steps for tokenization, part-of-speech tagging, and named entity recognition.

4. Write code to implement each step of your pipeline. This might involve writing functions or classes that use the tools and libraries you selected in step 2.

5. Connect the steps together in a pipeline. This might involve passing data between functions or classes, or using a pipeline framework like scikit-learn or Apache Beam.

6. Test your pipeline on sample data to ensure that it works as expected.

7. Refine your pipeline as needed based on your testing results.

8. Deploy your pipeline to production and monitor its performance to ensure that it continues to meet your needs.