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| # 📓 Notebooks | |
| Jupyter/Colab notebooks to create the Search pipeline and generate questions, using [ 🔍 Haystack](https://github.com/deepset-ai/haystack). | |
| ## [Indexing and pipeline creation](./indexing_and_pipeline_creation.ipynb) | |
| This notebook is inspired by ["Build Your First QA System" tutorial](https://haystack.deepset.ai/tutorials/first-qa-system), from Haystack documentation. | |
| Here we use a collection of articles about Twin Peaks to answer a variety of questions about that awesome TV series! | |
| The following steps are performed: | |
| - load and preprocess data | |
| - create (FAISS) document store and write documents | |
| - initialize retriever and generate document embeddings | |
| - initialize reader | |
| - compose and try Question Answering pipeline | |
| - save and export (FAISS) index | |
| ## [Question generation](./question_generation.ipynb) | |
| This notebook is inspired by [Question Generation tutorial](https://haystack.deepset.ai/tutorials/question-generation), from Haystack documentation. | |
| Here we use a collection of articles about Twin Peaks to generate a variety of questions about that awesome TV series! | |
| The following steps are performed: | |
| - load data | |
| - create document store and write documents | |
| - generate questions and save them | |