mirror of
https://github.com/MODSetter/SurfSense.git
synced 2026-05-31 19:45:15 +02:00
- Removed the eligibility gate for model selection in the automation creation process, allowing users to choose models directly in the builder. - Updated the `AutomationBuilderForm` to incorporate model selection logic, ensuring that selected models are validated and preserved during automation creation and editing. - Simplified the `AutomationsContent` and `AutomationNewContent` components by eliminating unnecessary eligibility checks and alerts. - Enhanced the user experience by integrating model selection directly into the automation approval process, ensuring that only billable models are used. - Refactored related tests to cover new model selection behavior and ensure proper validation of user-selected models.
150 lines
4.5 KiB
TypeScript
150 lines
4.5 KiB
TypeScript
"use client";
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import { useAtomValue } from "jotai";
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import { useMemo } from "react";
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import {
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globalImageGenConfigsAtom,
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imageGenConfigsAtom,
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} from "@/atoms/image-gen-config/image-gen-config-query.atoms";
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import {
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globalNewLLMConfigsAtom,
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llmPreferencesAtom,
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newLLMConfigsAtom,
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} from "@/atoms/new-llm-config/new-llm-config-query.atoms";
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import {
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globalVisionLLMConfigsAtom,
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visionLLMConfigsAtom,
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} from "@/atoms/vision-llm-config/vision-llm-config-query.atoms";
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/**
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* A single model the user may pick for an automation slot.
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*/
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export interface EligibleModelOption {
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id: number;
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name: string;
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/** Underlying model identifier (e.g. `gpt-4o`); shown as secondary text. */
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modelName: string;
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provider: string;
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/** `true` for user BYOK configs (positive ids), `false` for premium globals. */
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isBYOK: boolean;
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}
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export interface EligibleModelKind {
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options: EligibleModelOption[];
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/** Default selection: the search-space pref when eligible, else first option. */
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defaultId: number | null;
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/** O(1) id → option lookup for trigger labels (avoids per-render `.find()`). */
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byId: Map<number, EligibleModelOption>;
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}
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export interface AutomationEligibleModels {
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llm: EligibleModelKind;
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image: EligibleModelKind;
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vision: EligibleModelKind;
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isLoading: boolean;
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}
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interface GlobalConfigLike {
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id: number;
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name: string;
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model_name: string;
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provider: string;
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is_premium?: boolean;
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is_auto_mode?: boolean;
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}
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interface UserConfigLike {
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id: number;
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name: string;
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model_name: string;
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provider: string;
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}
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/**
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* Build the eligible option list for one model kind: premium globals
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* (`is_premium === true`, never Auto mode) followed by all BYOK configs.
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*/
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function buildKind(
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globals: GlobalConfigLike[] | undefined,
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byok: UserConfigLike[] | undefined,
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prefId: number | null | undefined
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): EligibleModelKind {
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const premiumGlobals: EligibleModelOption[] = (globals ?? [])
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.filter((c) => c.is_premium === true && !c.is_auto_mode)
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.map((c) => ({
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id: c.id,
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name: c.name,
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modelName: c.model_name,
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provider: c.provider,
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isBYOK: false,
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}));
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const byokOptions: EligibleModelOption[] = (byok ?? []).map((c) => ({
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id: c.id,
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name: c.name,
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modelName: c.model_name,
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provider: c.provider,
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isBYOK: true,
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}));
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const options = [...premiumGlobals, ...byokOptions];
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const byId = new Map<number, EligibleModelOption>(options.map((o) => [o.id, o]));
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let defaultId: number | null = null;
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if (prefId != null && byId.has(prefId)) {
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defaultId = prefId;
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} else if (options.length > 0) {
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defaultId = options[0].id;
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}
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return { options, defaultId, byId };
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}
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/**
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* Lists the LLM / image / vision models that are eligible for automations
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* (premium globals + user BYOK — never free globals or Auto mode), with a
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* default selection seeded from the search space's role preferences.
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*
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* Everything is derived during render from the existing config query atoms;
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* there are no effects, so option lists/maps keep stable references.
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*/
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export function useAutomationEligibleModels(): AutomationEligibleModels {
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const { data: llmUserConfigs, isLoading: llmUserLoading } = useAtomValue(newLLMConfigsAtom);
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const { data: llmGlobalConfigs, isLoading: llmGlobalLoading } =
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useAtomValue(globalNewLLMConfigsAtom);
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const { data: preferences, isLoading: prefsLoading } = useAtomValue(llmPreferencesAtom);
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const { data: imageGlobalConfigs, isLoading: imageGlobalLoading } =
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useAtomValue(globalImageGenConfigsAtom);
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const { data: imageUserConfigs, isLoading: imageUserLoading } = useAtomValue(imageGenConfigsAtom);
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const { data: visionGlobalConfigs, isLoading: visionGlobalLoading } = useAtomValue(
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globalVisionLLMConfigsAtom
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);
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const { data: visionUserConfigs, isLoading: visionUserLoading } =
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useAtomValue(visionLLMConfigsAtom);
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const llm = useMemo(
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() => buildKind(llmGlobalConfigs, llmUserConfigs, preferences?.agent_llm_id),
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[llmGlobalConfigs, llmUserConfigs, preferences?.agent_llm_id]
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);
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const image = useMemo(
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() => buildKind(imageGlobalConfigs, imageUserConfigs, preferences?.image_generation_config_id),
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[imageGlobalConfigs, imageUserConfigs, preferences?.image_generation_config_id]
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);
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const vision = useMemo(
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() => buildKind(visionGlobalConfigs, visionUserConfigs, preferences?.vision_llm_config_id),
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[visionGlobalConfigs, visionUserConfigs, preferences?.vision_llm_config_id]
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);
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const isLoading =
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llmUserLoading ||
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llmGlobalLoading ||
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prefsLoading ||
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imageGlobalLoading ||
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imageUserLoading ||
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visionGlobalLoading ||
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visionUserLoading;
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return useMemo(() => ({ llm, image, vision, isLoading }), [llm, image, vision, isLoading]);
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}
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