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Add vector database to the cloud #193
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The problem with not being able to do ful text search can be fixed by just not using full text search! I will try and implement it with lancedb and get a cloud version up and running it will require an update of Seracher class to handle async connections. |
The async error is addressed: https://github.com/lancedb/lancedb/pull/1102/files I have missed the point that I need to have adlfs installed. I will do that now and see if that works |
I believe in 0.9 of lancedb it has been fixed. I haven't found out which thing fixed it. Anyways the sync seems to be working. New problem is that the latency is too much. I.e it is taking about 15 seconds for a query. Might be working looking at smb file share, managed disk or other searhcing techniques to reduce latency. |
I am trying to deploy it with Heroku. I am getting an error that is todo with pyarrow. 2024-07-05T01:42:57.584452+00:00 app[web.1]: File "pyarrow/_fs.pyx", line 471, in pyarrow._fs.FileSystem.from_uri |
This now works and the only error is that requests times are longer than 30 seconds. |
Previously the viewer worked by having the data simply in a data folder.
The viewer currently works only locally by just giving a local address to the viewer app.
However it would be better to have a database that is in the cloud and seperate from the webapp
There is a curent problem with lancedb as it doesnt support fts in the cloud:
https://lancedb.github.io/lancedb/python/saas-python/#lancedb.remote.table.RemoteTable.search
Therefore I might have a look at qdrant or another vector search software package
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