Currently, it’s unclear whether an FAQ item is generated from a
document, derived from a conversation, or added manually.
This PR resolves the issue by providing visibility into the source of
each FAQ. Users can now see whether an FAQ was generated or manually
added and, if applicable, by whom.
- Move the document_id to a polymorphic relation (documentable).
- Updated the APIs to accommodate the change.
- Update the service to add corresponding references.
- Updated the specs.
<img width="1007" alt="Screenshot 2025-01-15 at 11 27 56 PM"
src="https://github.com/user-attachments/assets/7d58f798-19c0-4407-b3e2-748a919d14af"
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Co-authored-by: Sivin Varghese <64252451+iamsivin@users.noreply.github.com>
This PR introduces support for an assistant filter on the documents page.
- Moved the existing assistant filter functionality to a standalone, reusable component.
- Updated the documents page and responses page to use the component
This PR introduces a review step for generated FAQs, allowing a human to
validate and approve them before use in customer interactions. While
hallucinations are minimal, this step ensures accurate and reliable FAQs
for Captain to use during LLM calls when responding to customers.
- Added a status field for the FAQ
- Allow the filter on the UI.
<img width="1072" alt="Screenshot 2025-01-15 at 6 39 26 PM"
src="https://github.com/user-attachments/assets/81dfc038-31e9-40e6-8a09-586ebc4e8384"
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Previously, the Reports API fetched data based on event triggers. For
example, when an event occurred on an account, the system would
automatically retrieve and display updated information. However, this
approach was designed under the assumption that reports would be
accessed by a small number of users and on an infrequent basis (e.g.,
once daily or weekly).
In scenarios where large customers have multiple team members actively
monitoring reports, this event-driven approach led to an excessive
number of requests, significantly straining the system.
This PR introduces a interval-based fetching of reports instead of the
event-driven model.
Shivam Mishra