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Long query leads to "Something went wrong"
When we input a very long query and use Fuzzy matching, we are experiencing a "Something went wrong" error. We should investigate this issue. An example of this is: https://github.manticoresearch.com/manticoresoftware/manticoresearch?query=after+daemon+ …
Long query leads to "Something went wrong"
Long query leads to "Something went wrong"
Implement the query suggestion logic
We should design and display query suggestions in the same way Google does, and use the latest code from Buddy to accomplish this. The user input should bounce with a slight delay, and with almost every keystroke, we should render and display a popup …
Long query leads to "Something went wrong"
We need to consider and implement a way to configure and toggle fuzzy search options in the user interface. We should be able to: Turn fuzzy search on or off Enable or disable different keyboard layouts Potentially adjust other fuzziness settings
Long query leads to "Something went wrong"
Possibility to search across all repositories of the organization
We need to add the ability to search across all the organization's repositories. This shouldn't trigger a reindexing of all repos, but it should enable searching through all the organization's data. We'll need to modify the structure to make this happen …
Long query leads to "Something went wrong"
Show comments on state filter change for those issue state only (JOIN in the demo)
When we work with filters and search, we can currently filter by the state that only issues and pull requests have. However, when we change the state to open or close, we still search for comments everywhere. As discussed before, it would be a good idea …
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Demo: change closed issue/PR color to github's
We should add the latest update from Buddy to work with the Manticore GitHub demo. This will allow us to validate its quality on a large dataset and assess how fast it is. The purpose of this integration is to use the latest version of Buddy and make …
Change internal architecture of storing data
Replace "Vector search" with "Semantic search" in the demo
Rename 'Vector Search' to 'Semantic Search'. Prepare and upload a new database dump containing only vector embeddings for our repositories. This will make it lighter and easier to get started.
Change internal architecture of storing data
Let's add vector search to the demo using one of the most popular models. Implement the tokenizers Rust extension. Pick the best starting model. Add logic to handle various models and the option to adjust them at the start.
Change internal architecture of storing data
Various fixes and improvements to the Demo
improve exceptions handling, especially the exception which is thrown when the token has exceeded its limit experiment more with the facets UI to make it less confusing (grey out filters that would result in zero results etc.) deploy a new version of the …
Change internal architecture of storing data
Experiment with distributed table
Try to use a distributed table with issue and comment tables in it and CALL AUTOCOMPLETE on it to validate whether it works as expected or not.
Change internal architecture of storing data
Search across all organization's repositories
Implement the query suggestion logic
Implement the query suggestion logic
We should consider adding logic that will allow us to find similar issues/comments in the same way we do in our Image demo.
Update to separate table per organization schema
Add instructions for restoring backup from the dump
Change internal architecture of storing data
We should migrate to a system where we store each organization in a separate table. This approach will allow us to maintain the logic for searching one, two, or multiple repositories within a single organization. It will also help us narrow down query …
Various fixes and improvements to the Demo
Consider enabling bigram_index to improve autocomplete
…Here The autocomplete results could be better if they included native support . It's currently impossible likely because bigram_index is not enabled. If we do it, the results may be better. E.g.: mysql> drop table if exists t; create table t(f text) min_ …
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