twenty/packages/twenty-front/src/modules/ai/utils/getToolDisplayMessage.ts
Félix Malfait 6f251a6f8e
Add @mention support in AI Chat input (#17943)
## Summary
- Add `@mention` support to the AI Chat text input by replacing the
plain textarea with a minimal Tiptap editor and building a shared
`mention` module with reusable Tiptap extensions (`MentionTag`,
`MentionSuggestion`), search hook (`useMentionSearch`), and suggestion
menu — all shared with the existing BlockNote-based Notes mentions to
avoid code duplication
- Mentions are serialized as
`[[record:objectName:recordId:displayName]]` markdown (the format
already understood by the backend and rendered in chat messages), and
displayed using the existing `RecordLink` chip component for visual
consistency
- Fix images in chat messages overflowing their container by
constraining to `max-width: 100%`
- Fix web_search tool display showing literal `{query}` instead of the
actual query (ICU single-quote escaping issue in Lingui `t` tagged
templates)

## Test plan
- [ ] Open AI Chat, type `@` and verify the suggestion menu appears with
searchable records
- [ ] Select a mention from the dropdown (via click or keyboard
Enter/ArrowUp/Down) and verify the record chip renders inline
- [ ] Send a message containing a mention and verify it appears
correctly in the conversation as a clickable `RecordLink`
- [ ] Verify Enter sends the message when the suggestion menu is closed,
and selects a mention when the menu is open
- [ ] Verify images in AI chat responses are constrained to the
container width
- [ ] Verify the web_search tool step shows the actual search query
(e.g. "Searched the web for Salesforce") instead of `{query}`
- [ ] Verify Notes @mentions still work as before


Made with [Cursor](https://cursor.com)

---------

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-02-14 14:37:33 +01:00

131 lines
3.5 KiB
TypeScript

import { t } from '@lingui/core/macro';
import { isNonEmptyString } from '@sniptt/guards';
import { z } from 'zod';
import { type ToolInput } from '@/ai/types/ToolInput';
import { isDefined } from 'twenty-shared/utils';
const DirectQuerySchema = z.object({ query: z.string() });
const NestedQuerySchema = z.object({
action: z.object({ query: z.string() }),
});
const CustomLoadingMessageSchema = z.object({ loadingMessage: z.string() });
const ExecuteToolSchema = z.object({
toolName: z.coerce.string(),
arguments: z.unknown(),
});
const LearnToolsSchema = z.object({ toolNames: z.array(z.string()) });
const LoadSkillsSchema = z.object({ skillNames: z.array(z.string()) });
const extractSearchQuery = (input: ToolInput): string => {
const direct = DirectQuerySchema.safeParse(input);
if (direct.success) {
return direct.data.query;
}
const nested = NestedQuerySchema.safeParse(input);
if (nested.success) {
return nested.data.action.query;
}
return '';
};
const extractCustomLoadingMessage = (input: ToolInput): string | null => {
const parsed = CustomLoadingMessageSchema.safeParse(input);
return parsed.success ? parsed.data.loadingMessage : null;
};
export const resolveToolInput = (
input: ToolInput,
toolName: string,
): { resolvedInput: ToolInput; resolvedToolName: string } => {
if (toolName !== 'execute_tool') {
return { resolvedInput: input, resolvedToolName: toolName };
}
const parsed = ExecuteToolSchema.safeParse(input);
if (!parsed.success) {
return { resolvedInput: input, resolvedToolName: toolName };
}
return {
resolvedInput: parsed.data.arguments as ToolInput,
resolvedToolName: parsed.data.toolName,
};
};
const extractLearnToolNames = (input: ToolInput): string => {
const parsed = LearnToolsSchema.safeParse(input);
return parsed.success ? parsed.data.toolNames.join(', ') : '';
};
const extractSkillNames = (input: ToolInput): string => {
const parsed = LoadSkillsSchema.safeParse(input);
return parsed.success ? parsed.data.skillNames.join(', ') : '';
};
const formatToolName = (toolName: string): string => {
return toolName.replace(/_/g, ' ');
};
export const getToolDisplayMessage = (
input: ToolInput,
toolName: string,
isFinished?: boolean,
): string => {
const { resolvedInput, resolvedToolName } = resolveToolInput(input, toolName);
const byStatus = (finished: string, inProgress: string): string =>
isFinished ? finished : inProgress;
if (resolvedToolName === 'web_search') {
const query = extractSearchQuery(resolvedInput);
if (isNonEmptyString(query)) {
return byStatus(
t`Searched the web for ${query}`,
t`Searching the web for ${query}`,
);
}
return byStatus(t`Searched the web`, t`Searching the web`);
}
if (resolvedToolName === 'learn_tools') {
const names = extractLearnToolNames(resolvedInput);
if (isNonEmptyString(names)) {
return byStatus(t`Learned ${names}`, t`Learning ${names}`);
}
return byStatus(t`Learned tools`, t`Learning tools...`);
}
if (resolvedToolName === 'load_skills') {
const names = extractSkillNames(resolvedInput);
if (isNonEmptyString(names)) {
return byStatus(t`Loaded ${names}`, t`Loading ${names}`);
}
return byStatus(t`Loaded skills`, t`Loading skills...`);
}
const customMessage = extractCustomLoadingMessage(resolvedInput);
if (isDefined(customMessage)) {
return customMessage;
}
const formattedName = formatToolName(resolvedToolName);
return byStatus(t`Ran ${formattedName}`, t`Running ${formattedName}`);
};