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Steven EnamakelandGitHub
7db71408bd
* Enhance draft message handling in streaming edits
- Introduced a new `draft_sent` field in the `StreamingState` struct to track when a draft message has been posted, decoupling the existence of a draft from the ability to edit it.
- Updated the `flush_streaming_edit` function to set `draft_sent` upon posting a draft, ensuring that duplicate messages are not sent if the backend fails to return an ID.
- Modified the `finalize_channel_reply` function to prevent sending a fresh message if a draft was already posted without an ID, improving user experience by avoiding duplicate bubbles.
These changes enhance the robustness of message handling during streaming edits, ensuring a smoother interaction for users.
* feat(onboarding): enhance LocalAIStep for low-RAM device handling
- Added logic to determine if the device is below the RAM threshold, defaulting to a cloud AI fallback if necessary.
- Introduced a new UI for low-RAM devices, informing users about the cloud mode and providing options to continue with cloud AI or force-enable local AI.
- Updated the `ensureRecommendedLocalAiPresetIfNeeded` function to return a `recommend_disabled` flag based on device RAM.
- Enhanced tests to cover new cloud fallback UI and local AI consent handling.
These changes improve the onboarding experience by providing clearer options based on device capabilities.
* style: apply prettier formatting to LocalAIStep
* feat(local_ai): unlock model selection + add Disabled/cloud fallback option
- Remove MVP ceiling that clamped selection to the 2-4 GB tier, in bootstrap
and in the apply_preset RPC — users can now pick any tier.
- Add special "disabled" tier string to apply_preset that toggles
config.local_ai.enabled = false so the app uses the cloud summarizer.
- Presets RPC now returns local_ai_enabled so the UI can render the
currently-active state correctly.
- Rewrite DeviceCapabilitySection: tiers are now clickable buttons that
call apply_preset; adds a "Disabled — Cloud fallback" card at the top
marked "Recommended" on low-RAM devices and "Active" when enabled=false.
- Remove the MVP message copy from the model tier panel.
- Remove unread-count badge from the bottom tab bar.
* refactor(onboarding): streamline LocalAIStep and update local AI preset handling
- Removed the `ensureRecommendedLocalAiPresetIfNeeded` function call from `LocalAIStep`, replacing it with `openhumanLocalAiPresets` to directly fetch preset information.
- Updated the logic in `ensureRecommendedLocalAiPresetIfNeeded` to ensure the recommended tier is applied correctly based on user consent, improving clarity in the local AI setup process.
- Enhanced tests to mock the new `openhumanLocalAiPresets` function, ensuring coverage for low-RAM device scenarios and local AI consent handling.
- Updated documentation in the `schemas.rs` file to reflect changes in the data structure returned by the presets RPC.
These changes improve the onboarding experience by providing a more direct and efficient method for managing local AI presets based on device capabilities.
* test(LocalAIStep): improve mock implementation for local AI presets
- Refactored the mock for `openhumanLocalAiPresets` to enhance readability and maintainability.
- Ensured the mock returns consistent device information and preset details for testing scenarios.
- This change supports better test coverage and clarity in the LocalAIStep component's behavior during onboarding.
* fix(local_ai): preserve hadSelectedTier semantics in bootstrap return
hadSelectedTier / selectedTier represent the incoming state ("was a tier
already selected before this call"), not the post-apply state. Setting
both to the just-applied tier broke the existing localAiBootstrap
contract and the unit test that encodes it.
The Rust-side persistence fix is independent: removing the
recommend_disabled short-circuit ensures openhumanLocalAiApplyPreset
actually writes the selected tier to disk on the opt-in path, so
config_with_recommended_tier_if_unselected() honors the user's choice.
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