Documentation Backlog

[brandenchan]

The next set of features to be added to the website:

Usage

• Introduce a FAQ section (probably as a subpage of "Overview")
• Dedicated section about optimization of speed (this question comes up a lot and would be great to just help users with a single link. Besides document length, it should contain the levers model size and GPU / CPU) (Revamp Optimization page)
• Reformat code examples so that they don't contain |when copying/pasting them
• Think about a concept for introducing more "code snippets / recipes" (either within API reference or Usage or a central place where you can browse + search thinking ) (Investigate using Carbon for Code Snippets in Documentation #1170)
• Usage section for KGQA
• Usage of REST API (depends on Rest API Pipeline rest interface added. #1158)
• Indexing pipeline to Pipelines tutorial (Allow for batch indexing when using Pipelines #1168)
• Filtering by metadata
• Add MilvusDocumentStore to one of our tutorials
• Add GermanQuAD and GermanPR to usage
• Add GermanQuAD tutorial (#1169)
• Add footer to tutorials
• Add preprocessor to language usage page
• Convert code snippets to Carbon embeds? (Usage? API?) (Investigate using Carbon for Code Snippets in Documentation #1170)
• Collapse left side bar (Collapse Left Side Bar in Documentation Website #1171)

Benchmarks (

• Update benchmarks page
• Merging maP of DPR/Elastic and DPR/FAISS(Flat) (We need a script to do this so its not manual each time)
• Adjust scale of speed and performance so their trade off is clearer
• Change colours in graphs so they are better contrasted
• Give some interpretation of results

For the FAQ part a few questions that came up a lot in the last months:

Q: Why do I get duplicate answers in the results? A: You added your documents twice to the document store. Make sure to call doc_store.delete_all_documents() before running your indexing script a second time
Q: How can I speed up predictions? A: Splitting docs, using GPU, smaller model (we should have a better documentation page just for this topic)
3. Q: Which model to use for German / spanish / ...? A: (maybe we should update our multilingual table in the docs? )
4. Q: How to add / access metadata?
5. Q: Print predictions during eval