Samples related to Content Design (CD) for retrieval-augmented generation (RAG).
Notebook | Description |
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1. Filter input ( link )
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Use the Natural Langauge Understanding service on IBM Cloud to filter out malicious input (eg. Javascript injection) |
2. Classify input ( link )
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Use a large language model in IBM watsonx.ai to classify user input into one of these categories:
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3. Remove HAP, PII ( link )
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Remove hate, abuse, and profanity (HAP) as well as personal identifiable information (PII) |
4. Identify FAQs ( link )
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Match a given question with frequently asked questions |
5. Boost search ( link )
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Improve search success using several techniques:
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6. Prompt by question type ( link )
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Given relevant articles from a knowledge base, prompt a large language model to format answers to questions differently, depending on the question type:
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7. Select best answer ( link )
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Select the best of several generated answers |
8. Regression testing ( link )
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Test whether a change to the RAG solution causes the solution to get better or worse |
9. Testing topics ( link )
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Test how well a topic can answer given user questions |
10. HTML to text ( link )
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Convert HTML to text |
11. Answer Natural Questions ( link )
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Answer a subset of questions from the Natural Questions benchmark |