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feat: local model auto-reaction on user messages by channel type (#181)
* feat(conversations): implement auto-reaction feature for user messages - Added functionality to automatically react to user messages with emojis based on the local AI's evaluation of the message content and channel type. - Introduced `maybeAutoReact` function to handle the decision-making process for emoji reactions. - Updated the `Conversations` component to store the last user message and trigger reactions accordingly. - Enhanced the `tauriCommands` with a new method `openhumanLocalAiShouldReact` to facilitate local model evaluations for reactions. - Updated local AI operations to include reaction decision logic, ensuring efficient and context-aware responses. This feature enhances user engagement by adding a personal touch to interactions. * style: fix prettier formatting in Conversations.tsx Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: apply cargo fmt to ops.rs Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: address PR review — race condition, invisible reactions, flag emoji, PII log - Replace lastUserMessageRef with per-thread pendingReactionRef Map so cancellation/retry clears stale entries and onDone only applies to the matching request round - Render reactions on user message bubbles (not just agent messages) so auto-reactions are actually visible; manual picker stays agent-only - Fix extract_first_emoji to consume consecutive regional indicator symbols as a single flag emoji (e.g. 🇺🇸); add regression test - Replace raw_output in should_react debug log with output_len to avoid persisting user PII in traces Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: apply cargo fmt Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor(conversations): remove unused imports for local AI transcription and TTS - Cleaned up the Conversations component by removing unused imports related to local AI transcription and text-to-speech functionalities, streamlining the codebase and improving maintainability.es --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
Steven Enamakel
co-authored by
Claude Opus 4.6
Claude Opus 4.6
parent
cf344facf9
commit
207ec7d45c
@@ -35,6 +35,7 @@ import {
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openhumanAutocompleteAccept,
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openhumanAutocompleteCurrent,
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openhumanLocalAiChat,
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openhumanLocalAiShouldReact,
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openhumanVoiceStatus,
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openhumanVoiceTranscribeBytes,
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openhumanVoiceTts,
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@@ -125,6 +126,12 @@ const Conversations = () => {
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const [isDelivering, setIsDelivering] = useState(false);
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const deliveryActiveRef = useRef(false);
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const [reactionPickerMsgId, setReactionPickerMsgId] = useState<string | null>(null);
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const defaultChannelType = useAppSelector(
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state => state.channelConnections?.defaultMessagingChannel ?? 'web'
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);
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const pendingReactionRef = useRef<
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Map<string, { msgId: string; content: string; threadId: string }>
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>(new Map());
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const selectedThreadIdRef = useRef(selectedThreadId);
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useEffect(() => {
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@@ -377,6 +384,13 @@ const Conversations = () => {
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};
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});
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// Fire-and-forget: auto-react to the user's message
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const pending = pendingReactionRef.current.get(event.thread_id);
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if (pending) {
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maybeAutoReact(pending.msgId, pending.content, pending.threadId);
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pendingReactionRef.current.delete(event.thread_id);
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}
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// Multi-bubble delivery gate: only when local model is active
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if (!isLocalModelActiveRef.current) {
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dispatch(
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@@ -437,6 +451,9 @@ const Conversations = () => {
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};
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});
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// Clear pending reaction so stale callbacks are ignored
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pendingReactionRef.current.delete(event.thread_id);
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if (event.error_type !== 'cancelled') {
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// Deduplicate: skip if the last message is already an error
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const currentState = store.getState() as {
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@@ -499,6 +516,26 @@ const Conversations = () => {
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setIsDelivering(false);
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};
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/**
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* Fire-and-forget: ask the local model if we should auto-react to the
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* user's message with an emoji. Adds a personal touch based on channel type.
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*/
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const maybeAutoReact = (userMessageId: string, messageContent: string, threadId: string) => {
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if (!isTauri() || !isLocalModelActiveRef.current) return;
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void openhumanLocalAiShouldReact(messageContent, defaultChannelType)
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.then(response => {
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const decision = response.result;
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if (decision?.should_react && decision.emoji) {
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console.debug('[conversations:auto-react] reacting with', decision.emoji);
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dispatch(addReaction({ threadId, messageId: userMessageId, emoji: decision.emoji }));
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}
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})
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.catch(err => {
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console.debug('[conversations:auto-react] failed:', err);
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});
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};
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const handleSendMessage = async (text?: string) => {
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const normalized = text ?? inputValue;
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const trimmed = normalized.trim();
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@@ -525,6 +562,11 @@ const Conversations = () => {
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};
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dispatch(addMessageLocal({ threadId: sendingThreadId, message: userMessage }));
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pendingReactionRef.current.set(sendingThreadId, {
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msgId: userMessage.id,
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content: trimmed,
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threadId: sendingThreadId,
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});
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setInputValue('');
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setSendError(null);
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@@ -567,7 +609,10 @@ const Conversations = () => {
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}
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await deliverLocalResponse(reply, sendingThreadId);
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pendingReactionRef.current.delete(sendingThreadId);
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maybeAutoReact(userMessage.id, trimmed, sendingThreadId);
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} catch (err) {
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pendingReactionRef.current.delete(sendingThreadId);
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const msg = err instanceof Error ? err.message : String(err);
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setSendError(msg);
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dispatch(
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@@ -900,12 +945,16 @@ const Conversations = () => {
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</svg>
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)}
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</button>
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{msg.sender === 'agent' && (
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<div className="mt-1 flex items-center gap-1 flex-wrap min-h-[20px]">
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{(() => {
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const myReactions =
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(msg.extraMetadata?.myReactions as string[] | undefined) ?? [];
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return myReactions.map(emoji => (
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{(() => {
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const myReactions =
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(msg.extraMetadata?.myReactions as string[] | undefined) ?? [];
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const hasReactions = myReactions.length > 0;
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// Show reaction row if there are existing reactions (any sender)
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// or if this is an agent message (manual picker available)
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if (!hasReactions && msg.sender !== 'agent') return null;
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return (
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<div className="mt-1 flex items-center gap-1 flex-wrap min-h-[20px]">
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{myReactions.map(emoji => (
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<button
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key={emoji}
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onClick={() =>
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@@ -922,46 +971,47 @@ const Conversations = () => {
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title={`Remove ${emoji}`}>
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{emoji}
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</button>
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));
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})()}
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{reactionPickerMsgId === msg.id ? (
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<div className="flex items-center gap-0.5 px-1 py-0.5 rounded-full bg-white/10">
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{['👍', '❤️', '😂', '🔥', '👀', '🎯'].map(emoji => (
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))}
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{msg.sender === 'agent' &&
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(reactionPickerMsgId === msg.id ? (
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<div className="flex items-center gap-0.5 px-1 py-0.5 rounded-full bg-white/10">
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{['👍', '❤️', '😂', '🔥', '👀', '🎯'].map(emoji => (
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<button
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key={emoji}
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onClick={() => {
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if (selectedThreadId) {
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dispatch(
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addReaction({
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threadId: selectedThreadId,
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messageId: msg.id,
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emoji,
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})
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);
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}
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setReactionPickerMsgId(null);
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}}
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className="px-0.5 rounded text-sm hover:scale-125 transition-transform"
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title={emoji}>
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{emoji}
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</button>
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))}
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<button
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onClick={() => setReactionPickerMsgId(null)}
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className="ml-0.5 text-stone-600 hover:text-stone-400 text-xs px-0.5">
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✕
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</button>
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</div>
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) : (
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<button
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key={emoji}
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onClick={() => {
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if (selectedThreadId) {
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dispatch(
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addReaction({
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threadId: selectedThreadId,
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messageId: msg.id,
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emoji,
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})
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);
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}
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setReactionPickerMsgId(null);
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}}
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className="px-0.5 rounded text-sm hover:scale-125 transition-transform"
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title={emoji}>
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{emoji}
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onClick={() => setReactionPickerMsgId(msg.id)}
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className="opacity-0 group-hover/msg:opacity-100 flex items-center px-1.5 py-0.5 rounded-full bg-white/5 hover:bg-white/15 text-stone-500 hover:text-stone-300 text-xs transition-all"
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title="Add reaction">
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+
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</button>
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))}
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<button
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onClick={() => setReactionPickerMsgId(null)}
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className="ml-0.5 text-stone-600 hover:text-stone-400 text-xs px-0.5">
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✕
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</button>
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</div>
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) : (
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<button
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onClick={() => setReactionPickerMsgId(msg.id)}
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className="opacity-0 group-hover/msg:opacity-100 flex items-center px-1.5 py-0.5 rounded-full bg-white/5 hover:bg-white/15 text-stone-500 hover:text-stone-300 text-xs transition-all"
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title="Add reaction">
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+
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</button>
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)}
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</div>
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)}
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</div>
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);
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})()}
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</div>
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</div>
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))}
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@@ -1373,6 +1373,28 @@ export async function openhumanLocalAiChat(
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});
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}
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// --- Reaction decision (local model) ---
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export interface ReactionDecision {
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should_react: boolean;
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emoji: string | null;
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}
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/**
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* Ask the local model whether the assistant should react to a user message
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* with an emoji, based on the channel type. Designed to be fire-and-forget.
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* Zero cloud cost — runs entirely on the local Ollama model.
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*/
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export async function openhumanLocalAiShouldReact(
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message: string,
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channelType: string
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): Promise<CommandResponse<ReactionDecision>> {
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return await callCoreRpc<CommandResponse<ReactionDecision>>({
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method: 'openhuman.local_ai_should_react',
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params: { message, channel_type: channelType },
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});
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}
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export async function openhumanLocalAiAssetsStatus(): Promise<
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CommandResponse<LocalAiAssetsStatus>
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> {
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@@ -479,3 +479,226 @@ pub async fn local_ai_chat(
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);
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Ok(RpcOutcome::single_log(reply, "local ai chat completed"))
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}
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/// Result of the reaction-decision prompt.
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#[derive(Debug, serde::Serialize)]
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pub struct ReactionDecision {
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/// Whether the model thinks a reaction is appropriate.
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pub should_react: bool,
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/// The emoji to use (only meaningful when `should_react` is true).
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pub emoji: Option<String>,
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}
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/// Ask the local model whether the assistant should add an emoji reaction to
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/// the user's message, based on channel type and message content.
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/// Designed to be called fire-and-forget — fast, lightweight, no cloud cost.
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pub async fn local_ai_should_react(
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config: &Config,
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message: &str,
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channel_type: &str,
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) -> Result<RpcOutcome<ReactionDecision>, String> {
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tracing::debug!(
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channel_type,
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msg_len = message.len(),
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"[local_ai:should_react] evaluating reaction"
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);
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if message.trim().is_empty() {
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return Ok(RpcOutcome::single_log(
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ReactionDecision {
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should_react: false,
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emoji: None,
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},
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"empty message — no reaction",
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));
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}
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let service = local_ai::global(config);
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let status = service.status();
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if !matches!(status.state.as_str(), "ready") {
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tracing::debug!("[local_ai:should_react] local model not ready, skipping");
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return Ok(RpcOutcome::single_log(
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ReactionDecision {
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should_react: false,
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emoji: None,
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},
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"local model not ready",
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));
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}
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let prompt = format!(
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"You decide whether an AI assistant should react to a user message with a single emoji. \
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Consider the channel context: casual channels (discord, telegram) get more frequent \
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reactions with playful emojis, while professional channels (web, slack, email) are more \
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reserved — only react to clearly emotional or noteworthy messages.\n\n\
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Channel: {channel_type}\nUser message: {message}\n\n\
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Reply with EXACTLY one word: either NONE (no reaction) or a single emoji character."
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);
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let output = service.prompt(config, &prompt, Some(8), true).await;
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let decision = match output {
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Ok(raw) => {
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let trimmed = raw.trim();
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tracing::debug!(
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output_len = trimmed.len(),
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"[local_ai:should_react] model response"
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);
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if trimmed.eq_ignore_ascii_case("NONE") || trimmed.is_empty() {
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ReactionDecision {
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should_react: false,
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emoji: None,
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}
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} else {
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// Extract the first emoji-like character(s) from the response
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let emoji = extract_first_emoji(trimmed);
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match emoji {
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Some(e) => ReactionDecision {
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should_react: true,
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emoji: Some(e),
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},
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None => ReactionDecision {
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should_react: false,
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emoji: None,
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},
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}
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}
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}
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Err(e) => {
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tracing::debug!(error = %e, "[local_ai:should_react] inference failed, skipping");
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ReactionDecision {
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should_react: false,
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emoji: None,
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}
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}
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};
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tracing::debug!(
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should_react = decision.should_react,
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emoji = ?decision.emoji,
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"[local_ai:should_react] decision"
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);
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Ok(RpcOutcome::single_log(
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decision,
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"reaction decision completed",
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))
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}
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/// Extract the first emoji from a string. Handles common emoji codepoints
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/// including flag sequences (pairs of regional indicator symbols).
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fn extract_first_emoji(text: &str) -> Option<String> {
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let mut chars = text.chars();
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while let Some(ch) = chars.next() {
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// Regional indicator pair → flag emoji (e.g. 🇺🇸 = U+1F1FA U+1F1F8)
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if is_regional_indicator(ch) {
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let mut emoji = String::new();
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emoji.push(ch);
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// Consume consecutive regional indicators (flags are pairs)
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for next in chars.by_ref() {
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if is_regional_indicator(next) {
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emoji.push(next);
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} else {
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break;
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}
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}
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return Some(emoji);
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}
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if is_emoji_start(ch) {
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let mut emoji = String::new();
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emoji.push(ch);
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// Consume joiners and variation selectors that extend the emoji
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for next in chars.by_ref() {
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if next == '\u{FE0F}' // variation selector
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|| next == '\u{200D}' // zero-width joiner
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|| ('\u{1F3FB}'..='\u{1F3FF}').contains(&next) // skin tones
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|| is_emoji_start(next) && emoji.contains('\u{200D}')
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{
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emoji.push(next);
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} else {
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break;
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}
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}
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return Some(emoji);
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}
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}
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None
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}
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fn is_regional_indicator(ch: char) -> bool {
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('\u{1F1E6}'..='\u{1F1FF}').contains(&ch)
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}
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fn is_emoji_start(ch: char) -> bool {
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matches!(ch,
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'\u{203C}' | '\u{2049}' // exclamation marks
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| '\u{2139}' // information
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| '\u{2194}'..='\u{2199}' // arrows
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| '\u{21A9}'..='\u{21AA}' // arrows
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| '\u{231A}'..='\u{231B}' // watch, hourglass
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| '\u{23E9}'..='\u{23F3}' // media controls
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| '\u{23F8}'..='\u{23FA}' // media controls
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| '\u{24C2}' // circled M
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| '\u{25AA}'..='\u{25AB}' // squares
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| '\u{25B6}' | '\u{25C0}' // play buttons
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| '\u{25FB}'..='\u{25FE}' // squares
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| '\u{2328}' | '\u{23CF}' // keyboard, eject
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| '\u{2600}'..='\u{27BF}' // misc symbols, dingbats
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| '\u{2934}'..='\u{2935}' // arrows
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| '\u{2B05}'..='\u{2B07}' // arrows
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| '\u{2B1B}'..='\u{2B1C}' // squares
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| '\u{2B50}' | '\u{2B55}' // star, circle
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| '\u{FE00}'..='\u{FE0F}' // variation selectors
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| '\u{1F300}'..='\u{1F9FF}' // misc symbols, emoticons, transport, supplemental
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| '\u{1FA00}'..='\u{1FA6F}' // chess symbols, extended-A
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| '\u{1FA70}'..='\u{1FAFF}' // symbols extended-A
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| '\u{200D}' // ZWJ
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)
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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#[test]
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fn extract_emoji_from_simple_string() {
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assert_eq!(extract_first_emoji("👍"), Some("👍".to_string()));
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assert_eq!(extract_first_emoji("🔥"), Some("🔥".to_string()));
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assert_eq!(extract_first_emoji("❤️"), Some("❤️".to_string()));
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}
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#[test]
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fn extract_emoji_with_surrounding_text() {
|
||||
assert_eq!(extract_first_emoji("Sure! 😂"), Some("😂".to_string()));
|
||||
assert_eq!(
|
||||
extract_first_emoji("I think 👀 fits here"),
|
||||
Some("👀".to_string())
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn extract_none_when_no_emoji() {
|
||||
assert_eq!(extract_first_emoji("NONE"), None);
|
||||
assert_eq!(extract_first_emoji("no reaction"), None);
|
||||
assert_eq!(extract_first_emoji(""), None);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn extract_flag_emoji_keeps_pair_together() {
|
||||
assert_eq!(extract_first_emoji("🇺🇸"), Some("🇺🇸".to_string()));
|
||||
assert_eq!(
|
||||
extract_first_emoji("🇬🇧 Great Britain"),
|
||||
Some("🇬🇧".to_string())
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn is_emoji_start_recognizes_common_emojis() {
|
||||
assert!(is_emoji_start('👍'));
|
||||
assert!(is_emoji_start('🔥'));
|
||||
assert!(is_emoji_start('😂'));
|
||||
assert!(is_emoji_start('⭐'));
|
||||
assert!(!is_emoji_start('A'));
|
||||
assert!(!is_emoji_start('1'));
|
||||
}
|
||||
}
|
||||
|
||||
@@ -111,6 +111,12 @@ struct LocalAiChatParams {
|
||||
max_tokens: Option<u32>,
|
||||
}
|
||||
|
||||
#[derive(Debug, Deserialize)]
|
||||
struct LocalAiShouldReactParams {
|
||||
message: String,
|
||||
channel_type: String,
|
||||
}
|
||||
|
||||
pub fn all_controller_schemas() -> Vec<ControllerSchema> {
|
||||
vec![
|
||||
schemas("agent_chat"),
|
||||
@@ -138,6 +144,7 @@ pub fn all_controller_schemas() -> Vec<ControllerSchema> {
|
||||
schemas("local_ai_set_ollama_path"),
|
||||
schemas("local_ai_diagnostics"),
|
||||
schemas("local_ai_chat"),
|
||||
schemas("local_ai_should_react"),
|
||||
]
|
||||
}
|
||||
|
||||
@@ -243,6 +250,10 @@ pub fn all_registered_controllers() -> Vec<RegisteredController> {
|
||||
schema: schemas("local_ai_chat"),
|
||||
handler: handle_local_ai_chat,
|
||||
},
|
||||
RegisteredController {
|
||||
schema: schemas("local_ai_should_react"),
|
||||
handler: handle_local_ai_should_react,
|
||||
},
|
||||
]
|
||||
}
|
||||
|
||||
@@ -488,6 +499,16 @@ pub fn schemas(function: &str) -> ControllerSchema {
|
||||
],
|
||||
outputs: vec![json_output("reply", "Assistant reply text.")],
|
||||
},
|
||||
"local_ai_should_react" => ControllerSchema {
|
||||
namespace: "local_ai",
|
||||
function: "should_react",
|
||||
description: "Ask the local model whether the assistant should add an emoji reaction to a user message, based on channel type.",
|
||||
inputs: vec![
|
||||
required_string("message", "User message content to evaluate."),
|
||||
required_string("channel_type", "Channel type: web, telegram, discord, slack, etc."),
|
||||
],
|
||||
outputs: vec![json_output("decision", "Reaction decision: {should_react, emoji}.")],
|
||||
},
|
||||
_ => ControllerSchema {
|
||||
namespace: "local_ai",
|
||||
function: "unknown",
|
||||
@@ -852,6 +873,21 @@ fn handle_local_ai_set_ollama_path(params: Map<String, Value>) -> ControllerFutu
|
||||
})
|
||||
}
|
||||
|
||||
fn handle_local_ai_should_react(params: Map<String, Value>) -> ControllerFuture {
|
||||
Box::pin(async move {
|
||||
let p = deserialize_params::<LocalAiShouldReactParams>(params)?;
|
||||
let config = config_rpc::load_config_with_timeout().await?;
|
||||
to_json(
|
||||
crate::openhuman::local_ai::rpc::local_ai_should_react(
|
||||
&config,
|
||||
&p.message,
|
||||
&p.channel_type,
|
||||
)
|
||||
.await?,
|
||||
)
|
||||
})
|
||||
}
|
||||
|
||||
fn handle_local_ai_chat(params: Map<String, Value>) -> ControllerFuture {
|
||||
Box::pin(async move {
|
||||
let p = deserialize_params::<LocalAiChatParams>(params)?;
|
||||
|
||||
Reference in New Issue
Block a user