Introduce RAG for personalization and history

CsabaConsulting / InspectorGadgetApp

Open Multi-Modal Personal Assistant

MIT License

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Introduce RAG for personalization and history #7

Closed MrCsabaToth closed 2 months ago

MrCsabaToth commented 3 months ago

This needs to work together with function calls and ReAct #5 / ReWOO #6

MrCsabaToth commented 3 months ago

Since objectbox (https://pub.dev/packages/objectbox) supports vector DB as well, it'd cover both history (#8) and RAG

MrCsabaToth commented 3 months ago

Note, once the basic RAG is in place, explore:

different embeddings
hybrid-search (applicable?)
auto-cut (crop documents when the score suddenly drops)
re-rank (applicable?)

MrCsabaToth commented 2 months ago

https://ai.google.dev/gemini-api/docs/embeddings#dart-flutter

final model = GenerativeModel(model: 'text-embedding-004', apiKey: apiKey);
final content = Content.text('The quick brown fox jumps over the lazy dog.');
final result = await model.embedContent(content);
print(result.embedding.values);

dimensionality is 768

MrCsabaToth commented 2 months ago

We introduced thresholds as well now.