71d4581110
refactor(ai-client): moving tool handling and client into seperate folders
2025-04-04 22:03:46 +01:00
8a165c2042
wip(orchestrator): basic scaffolding for the agent
2025-04-04 20:40:31 +01:00
745265773b
feat(notes): allowing frontend to save
2025-04-01 20:54:15 +00:00
f72ee73020
feat(notes): saving the notes for any images for easy text searching
2025-04-01 20:45:43 +00:00
901f214f9d
feat(contacts): events can now have organizers
2025-03-31 18:40:36 +00:00
b6969127eb
fix(backend): SQL statements without returns
2025-03-26 16:51:46 +00:00
a576355e7c
feat: creating events and attaching locations
2025-03-26 16:16:48 +00:00
6f938a34e3
feat(tool-calling) Big refactor on how tool calling is handled
...
these commits are too big
2025-03-22 20:46:26 +00:00
7debe6bab2
feat(locations): allowing AI to attach it to the image
2025-03-22 17:47:02 +00:00
4c4bf7a9e4
feat(location): working e2e with tool calling
2025-03-22 12:22:31 +00:00
aad45fcf52
feat(tool-calls): listLocation tool call handling
2025-03-22 11:14:00 +00:00
7c473e054a
feat: using tools for event loocation agent
2025-03-22 10:12:51 +00:00
f042c9dfcc
feat: working e2e solution
2025-03-20 17:59:00 +00:00
072eebc0bf
feat(events): also working
2025-03-18 18:37:12 +00:00
28dd02a47d
feat(locations): now working
2025-03-18 18:18:01 +00:00
2e1809aa27
refactor(text,tags,links): to foreign key to image instead of user_image
2025-03-18 17:48:38 +00:00
439f729150
fix: returning whole tag object
2025-03-16 18:29:15 +00:00
1d5d90c3b5
refactor(models): using more organised structure
2025-03-16 18:13:30 +00:00
d4c6aa0310
feat(tags): correctly inserting new tags and adding them to images
2025-03-11 22:47:28 +00:00
9e3896a30f
feat: super basic image search
2025-03-08 15:37:10 +00:00
03a4d49ee6
feat: sending base64 image to backend
...
This is silly, but binary is apparently hard to do????
2025-03-08 12:30:16 +00:00
53c4ec1869
fix: using json response header
2025-03-07 14:14:40 +00:00
5192aeb70f
wip: Using mistral instead of OpenAi
2025-03-07 13:42:50 +00:00
1f16cfb30b
refactor: tables for image and processing_image
...
This allows a single table to be used to process images, meaning if
anything happens to the system we can always return to polling the
database and process these images individually.
Because of this we also want an `image` table to contain the actual
binary data for the image, so we aren't selecting and writing it each
time, as it is potentially a bottleneck.
2025-02-26 20:01:56 +00:00
2a37e37c4b
refactor: using chi router + bug fixes
2025-02-26 18:04:30 +00:00
c36fb1c0d6
feat: saving AI information to database
2025-02-24 21:00:05 +00:00
e26835861d
feat: method for getting images
2025-02-24 20:05:56 +00:00
e69d7b5c08
feat: methods to get image
2025-02-24 20:02:58 +00:00
c9cd0df9ca
feat: working docker image and compose file
2025-02-24 19:44:19 +00:00
050126116c
refactor: moving all files to backend
2025-02-22 23:30:59 +00:00
