AnswerDotAI / AnswerDotAI/RAGatouille
Support exporting index to HuggingFace Hub
- Dominant language
- Python
- Stars
- 4k
- Forks
- 276
- PR merge metrics
- No merged PRs in 30d
Description
Indexing is time consuming, and oftentimes people would like to be able to easily share pre-built index for various common datasets, for general domain application (wikipedia, code documentation...) and evaluation purposes.
A simple way to support this would be to add a `util` function that'd export the full index folder to the huggingface model, effectively exporting both the ColBERT config + the compressed vectors, allowing you to to do something like `RAGPretrainedModel.from_prebuilt_index("EXAMPLE_USER/Wikipedia")` and immediately begin querying the index.
Contributor guide
No contributing guide indexed for this repository
Research direction
Start by locating the utility functions that create or load a full index folder and the RAGPretrainedModel.from_prebuilt_index entry point. Check how ColBERT configuration and compressed vectors are stored; done means an index can be exported to HuggingFace Hub and loaded from a repository such as EXAMPLE_USER/Wikipedia for querying.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- huggingface, python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 38/100