mirror of
https://github.com/twentyhq/twenty
synced 2026-04-21 13:37:22 +00:00
Add AI model pricing, Bedrock provider, and InferenceProvider/ModelFamily split (#18155)
## Summary - **Model pricing overhaul**: All model constants updated with accurate pricing in dollars per 1M tokens, including cached input rates, cache creation rates, and tiered >200k context pricing - **New providers**: Added Google (Gemini 3.x), Mistral, and AWS Bedrock as inference providers. Bedrock serves Claude Opus 4.6 and Sonnet 4.6 via AWS, with proper credential handling following the existing S3/SES pattern - **InferenceProvider/ModelFamily split**: Refactored `ModelProvider` into two orthogonal enums — `InferenceProvider` (who serves the model: auth, SDK, metadata format) and `ModelFamily` (who created it: token counting semantics). This eliminates growing `||` chains for token normalization checks like `excludesCachedTokens` - **Billing improvements**: Reasoning tokens charged at output rate, cache token discounts applied accurately, real errors thrown to Sentry on billing failures ## Test plan - [x] All existing unit tests updated and passing (23 tests across 3 test files) - [x] Lint passes for both twenty-server and twenty-front - [ ] CI checks pass Made with [Cursor](https://cursor.com) --------- Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
Félix Malfait
GitHub
parent
a900b4a4b4
commit
41f09c5a4c
37 changed files with 1462 additions and 383 deletions
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@ -679,12 +679,13 @@ export type CheckUserExistOutput = {
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export type ClientAiModelConfig = {
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__typename?: 'ClientAIModelConfig';
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deprecated?: Maybe<Scalars['Boolean']>;
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inputCostPer1kTokensInCredits: Scalars['Float'];
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inferenceProvider: InferenceProvider;
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inputCostPerMillionTokensInCredits: Scalars['Float'];
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label: Scalars['String'];
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modelFamily?: Maybe<ModelFamily>;
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modelId: Scalars['String'];
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nativeCapabilities?: Maybe<NativeModelCapabilities>;
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outputCostPer1kTokensInCredits: Scalars['Float'];
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provider: ModelProvider;
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outputCostPerMillionTokensInCredits: Scalars['Float'];
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};
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export type ClientConfig = {
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@ -1883,6 +1884,18 @@ export enum IndexType {
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GIN = 'GIN'
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}
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export enum InferenceProvider {
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ANTHROPIC = 'ANTHROPIC',
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BEDROCK = 'BEDROCK',
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GOOGLE = 'GOOGLE',
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GROQ = 'GROQ',
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MISTRAL = 'MISTRAL',
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NONE = 'NONE',
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OPENAI = 'OPENAI',
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OPENAI_COMPATIBLE = 'OPENAI_COMPATIBLE',
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XAI = 'XAI'
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}
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export type InitiateTwoFactorAuthenticationProvisioningOutput = {
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__typename?: 'InitiateTwoFactorAuthenticationProvisioningOutput';
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uri: Scalars['String'];
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@ -2155,12 +2168,11 @@ export type MetadataEventWithQueryIds = {
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queryIds: Array<Scalars['String']>;
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};
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export enum ModelProvider {
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export enum ModelFamily {
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ANTHROPIC = 'ANTHROPIC',
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GROQ = 'GROQ',
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NONE = 'NONE',
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GOOGLE = 'GOOGLE',
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MISTRAL = 'MISTRAL',
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OPENAI = 'OPENAI',
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OPENAI_COMPATIBLE = 'OPENAI_COMPATIBLE',
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XAI = 'XAI'
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}
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@ -15,7 +15,9 @@ import { Paragraph } from '@tiptap/extension-paragraph';
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import { Strike } from '@tiptap/extension-strike';
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import { Text } from '@tiptap/extension-text';
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import { Underline } from '@tiptap/extension-underline';
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import { Dropcursor, Placeholder, UndoRedo } from '@tiptap/extensions';
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import { Dropcursor } from '@tiptap/extensions/drop-cursor';
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import { Placeholder } from '@tiptap/extensions/placeholder';
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import { UndoRedo } from '@tiptap/extensions/undo-redo';
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import { type Editor, useEditor } from '@tiptap/react';
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import { marked } from 'marked';
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import { type DependencyList, useMemo } from 'react';
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@ -3,7 +3,7 @@ import { Document } from '@tiptap/extension-document';
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import { HardBreak } from '@tiptap/extension-hard-break';
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import { Paragraph } from '@tiptap/extension-paragraph';
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import { Text } from '@tiptap/extension-text';
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import { Placeholder } from '@tiptap/extensions';
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import { Placeholder } from '@tiptap/extensions/placeholder';
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import { useEditor } from '@tiptap/react';
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import { useCallback, useMemo } from 'react';
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import { isDefined } from 'twenty-shared/utils';
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@ -4,6 +4,7 @@ import { type SelectOption } from 'twenty-ui/input';
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import { DEFAULT_FAST_MODEL } from '@/ai/constants/DefaultFastModel';
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import { DEFAULT_SMART_MODEL } from '@/ai/constants/DefaultSmartModel';
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import { useRecoilValueV2 } from '@/ui/utilities/state/jotai/hooks/useRecoilValueV2';
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import { MODEL_FAMILY_CONFIG } from '~/pages/settings/ai/constants/SettingsAiModelProviders';
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export const useAiModelOptions = (
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includeDeprecated = false,
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@ -18,11 +19,21 @@ export const useAiModelOptions = (
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model.modelId === DEFAULT_FAST_MODEL ||
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model.modelId === DEFAULT_SMART_MODEL
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? model.label
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: `${model.label} (${model.provider})`,
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: `${model.label} (${getModelFamilyLabel(model.modelFamily) ?? model.inferenceProvider})`,
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}))
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.sort((a, b) => a.label.localeCompare(b.label));
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};
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const getModelFamilyLabel = (
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modelFamily: string | null | undefined,
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): string | undefined => {
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if (!modelFamily) {
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return undefined;
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}
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return MODEL_FAMILY_CONFIG[modelFamily]?.label || modelFamily;
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};
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export const useAiModelLabel = (
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modelId: string | undefined,
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includeProvider = true,
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@ -47,5 +58,5 @@ export const useAiModelLabel = (
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return model.label;
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}
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return `${model.label} (${model.provider})`;
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return `${model.label} (${getModelFamilyLabel(model.modelFamily) ?? model.inferenceProvider})`;
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};
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@ -6,7 +6,8 @@ import { Extension } from '@tiptap/core';
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import Document from '@tiptap/extension-document';
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import Paragraph from '@tiptap/extension-paragraph';
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import Text from '@tiptap/extension-text';
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import { Placeholder, UndoRedo } from '@tiptap/extensions';
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import { Placeholder } from '@tiptap/extensions/placeholder';
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import { UndoRedo } from '@tiptap/extensions/undo-redo';
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import { Plugin, PluginKey } from '@tiptap/pm/state';
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import { type Editor, useEditor } from '@tiptap/react';
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import { isDefined } from 'twenty-shared/utils';
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@ -4,7 +4,8 @@ import Document from '@tiptap/extension-document';
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import HardBreak from '@tiptap/extension-hard-break';
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import Paragraph from '@tiptap/extension-paragraph';
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import Text from '@tiptap/extension-text';
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import { Placeholder, UndoRedo } from '@tiptap/extensions';
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import { Placeholder } from '@tiptap/extensions/placeholder';
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import { UndoRedo } from '@tiptap/extensions/undo-redo';
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import { AllSelection, TextSelection } from '@tiptap/pm/state';
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import { type Editor, useEditor } from '@tiptap/react';
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import { isDefined, parseJson } from 'twenty-shared/utils';
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@ -12,7 +12,7 @@ import { t } from '@lingui/core/macro';
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import { H2Title, IconBolt } from 'twenty-ui/display';
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import { Card, Section } from 'twenty-ui/layout';
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import { useUpdateWorkspaceMutation } from '~/generated-metadata/graphql';
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import { PROVIDER_CONFIG } from '~/pages/settings/ai/constants/SettingsAiModelProviders';
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import { MODEL_FAMILY_CONFIG } from '~/pages/settings/ai/constants/SettingsAiModelProviders';
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const VIRTUAL_MODEL_IDS: Set<string> = new Set([
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DEFAULT_SMART_MODEL,
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@ -39,7 +39,11 @@ export const SettingsAIModelsTab = () => {
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.map((model) => ({
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value: model.modelId,
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label: model.label,
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Icon: PROVIDER_CONFIG[model.provider.toUpperCase()]?.Icon,
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Icon: (model.modelFamily
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? (MODEL_FAMILY_CONFIG[model.modelFamily] ??
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MODEL_FAMILY_CONFIG.FALLBACK)
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: MODEL_FAMILY_CONFIG.FALLBACK
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).Icon,
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}));
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const handleDefaultModelChange = async (value: string) => {
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@ -1,7 +1,6 @@
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import {
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IconBrandAnthropic,
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IconBrandGoogle,
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IconBrandGroq,
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IconBrandMistral,
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IconBrandOpenai,
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IconBrandXai,
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@ -9,15 +8,16 @@ import {
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type IconComponent,
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} from 'twenty-ui/display';
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export const PROVIDER_CONFIG: Record<
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// Keyed by the server-side ModelFamily enum values (lowercase) since
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// the client config is fetched via REST, not GraphQL.
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export const MODEL_FAMILY_CONFIG: Record<
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string,
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{ label: string; Icon: IconComponent }
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> = {
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OPENAI: { label: 'OpenAI', Icon: IconBrandOpenai },
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ANTHROPIC: { label: 'Anthropic', Icon: IconBrandAnthropic },
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XAI: { label: 'xAI', Icon: IconBrandXai },
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GOOGLE: { label: 'Google', Icon: IconBrandGoogle },
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GROQ: { label: 'Groq', Icon: IconBrandGroq },
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MISTRAL: { label: 'Mistral', Icon: IconBrandMistral },
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NONE: { label: '', Icon: IconRobot },
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openai: { label: 'OpenAI', Icon: IconBrandOpenai },
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anthropic: { label: 'Anthropic', Icon: IconBrandAnthropic },
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xai: { label: 'xAI', Icon: IconBrandXai },
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google: { label: 'Google', Icon: IconBrandGoogle },
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mistral: { label: 'Mistral', Icon: IconBrandMistral },
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FALLBACK: { label: '', Icon: IconRobot },
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};
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@ -15,8 +15,11 @@
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"typeorm": "../../node_modules/typeorm/.bin/typeorm"
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},
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"dependencies": {
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"@ai-sdk/amazon-bedrock": "^3.0.83",
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"@ai-sdk/anthropic": "^2.0.17",
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"@ai-sdk/google": "^2.0.54",
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"@ai-sdk/groq": "^2.0.34",
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"@ai-sdk/mistral": "^2.0.28",
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"@ai-sdk/openai": "^2.0.30",
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"@ai-sdk/provider-utils": "^3.0.9",
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"@ai-sdk/xai": "^2.0.19",
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@ -4,8 +4,9 @@ import { SupportDriver } from 'src/engine/core-modules/twenty-config/interfaces/
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import { ClientConfigService } from 'src/engine/core-modules/client-config/services/client-config.service';
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import {
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InferenceProvider,
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ModelFamily,
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type ModelId,
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ModelProvider,
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} from 'src/engine/metadata-modules/ai/ai-models/constants/ai-models.const';
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import { ClientConfigController } from './client-config.controller';
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@ -52,9 +53,10 @@ describe('ClientConfigController', () => {
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{
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modelId: 'gpt-4o' as ModelId,
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label: 'GPT-4o',
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provider: ModelProvider.OPENAI,
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inputCostPer1kTokensInCredits: 2.5,
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outputCostPer1kTokensInCredits: 10.0,
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modelFamily: ModelFamily.OPENAI,
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inferenceProvider: InferenceProvider.OPENAI,
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inputCostPerMillionTokensInCredits: 2500000,
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outputCostPerMillionTokensInCredits: 10000000,
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},
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],
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authProviders: {
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@ -7,16 +7,21 @@ import { CaptchaDriverType } from 'src/engine/core-modules/captcha/interfaces';
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import { FeatureFlagKey } from 'src/engine/core-modules/feature-flag/enums/feature-flag-key.enum';
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import { AuthProvidersDTO } from 'src/engine/core-modules/workspace/dtos/public-workspace-data-output';
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import {
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InferenceProvider,
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ModelFamily,
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ModelId,
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ModelProvider,
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} from 'src/engine/metadata-modules/ai/ai-models/constants/ai-models.const';
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registerEnumType(FeatureFlagKey, {
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name: 'FeatureFlagKey',
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});
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registerEnumType(ModelProvider, {
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name: 'ModelProvider',
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registerEnumType(InferenceProvider, {
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name: 'InferenceProvider',
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});
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registerEnumType(ModelFamily, {
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name: 'ModelFamily',
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});
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@ObjectType()
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@ -36,14 +41,17 @@ export class ClientAIModelConfig {
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@Field(() => String)
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label: string;
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@Field(() => ModelProvider)
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provider: ModelProvider;
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@Field(() => ModelFamily, { nullable: true })
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modelFamily?: ModelFamily;
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@Field(() => InferenceProvider)
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inferenceProvider: InferenceProvider;
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@Field(() => Number)
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inputCostPer1kTokensInCredits: number;
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inputCostPerMillionTokensInCredits: number;
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@Field(() => Number)
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outputCostPer1kTokensInCredits: number;
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outputCostPerMillionTokensInCredits: number;
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@Field(() => NativeModelCapabilities, { nullable: true })
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nativeCapabilities?: NativeModelCapabilities;
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@ -12,12 +12,12 @@ import {
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import { DomainServerConfigService } from 'src/engine/core-modules/domain/domain-server-config/services/domain-server-config.service';
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import { PUBLIC_FEATURE_FLAGS } from 'src/engine/core-modules/feature-flag/constants/public-feature-flag.const';
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import { TwentyConfigService } from 'src/engine/core-modules/twenty-config/twenty-config.service';
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import { convertCentsToBillingCredits } from 'src/engine/metadata-modules/ai/ai-billing/utils/convert-cents-to-billing-credits.util';
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import { convertDollarsToBillingCredits } from 'src/engine/metadata-modules/ai/ai-billing/utils/convert-dollars-to-billing-credits.util';
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import {
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AI_MODELS,
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DEFAULT_FAST_MODEL,
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DEFAULT_SMART_MODEL,
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ModelProvider,
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InferenceProvider,
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} from 'src/engine/metadata-modules/ai/ai-models/constants/ai-models.const';
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import { AiModelRegistryService } from 'src/engine/metadata-modules/ai/ai-models/services/ai-model-registry.service';
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@ -54,16 +54,17 @@ export class ClientConfigService {
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return {
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modelId: registeredModel.modelId,
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label: builtInModel?.label || registeredModel.modelId,
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provider: registeredModel.provider,
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modelFamily: builtInModel?.modelFamily,
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inferenceProvider: registeredModel.inferenceProvider,
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nativeCapabilities: builtInModel?.nativeCapabilities,
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inputCostPer1kTokensInCredits: builtInModel
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? convertCentsToBillingCredits(
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builtInModel.inputCostPer1kTokensInCents,
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inputCostPerMillionTokensInCredits: builtInModel
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? convertDollarsToBillingCredits(
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builtInModel.inputCostPerMillionTokens,
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)
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: 0,
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outputCostPer1kTokensInCredits: builtInModel
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? convertCentsToBillingCredits(
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builtInModel.outputCostPer1kTokensInCents,
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outputCostPerMillionTokensInCredits: builtInModel
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? convertDollarsToBillingCredits(
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builtInModel.outputCostPerMillionTokens,
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)
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: 0,
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deprecated: builtInModel?.deprecated,
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@ -96,16 +97,16 @@ export class ClientConfigService {
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{
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modelId: DEFAULT_SMART_MODEL,
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label: `Smart (${defaultPerformanceModelLabel})`,
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provider: ModelProvider.NONE,
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inputCostPer1kTokensInCredits: 0,
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outputCostPer1kTokensInCredits: 0,
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inferenceProvider: InferenceProvider.NONE,
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inputCostPerMillionTokensInCredits: 0,
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outputCostPerMillionTokensInCredits: 0,
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},
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{
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modelId: DEFAULT_FAST_MODEL,
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label: `Fast (${defaultSpeedModelLabel})`,
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provider: ModelProvider.NONE,
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inputCostPer1kTokensInCredits: 0,
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outputCostPer1kTokensInCredits: 0,
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inferenceProvider: InferenceProvider.NONE,
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inputCostPerMillionTokensInCredits: 0,
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outputCostPerMillionTokensInCredits: 0,
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},
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);
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}
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@ -1196,7 +1196,7 @@ export class ConfigVariables {
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})
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@IsOptional()
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DEFAULT_AI_SPEED_MODEL_ID =
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'gpt-4.1-mini,claude-haiku-4-5-20251001,grok-3-mini';
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'gpt-5-mini,claude-haiku-4-5-20251001,gemini-3-flash-preview,grok-4-1-fast-reasoning,mistral-large-latest';
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@ConfigVariablesMetadata({
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group: ConfigVariablesGroup.LLM,
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@ -1205,7 +1205,8 @@ export class ConfigVariables {
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type: ConfigVariableType.STRING,
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})
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@IsOptional()
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DEFAULT_AI_PERFORMANCE_MODEL_ID = 'gpt-4.1,claude-sonnet-4-5-20250929,grok-4';
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DEFAULT_AI_PERFORMANCE_MODEL_ID =
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'gpt-5.2,claude-sonnet-4-6,gemini-3.1-pro-preview,grok-4,mistral-large-latest';
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@ConfigVariablesMetadata({
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group: ConfigVariablesGroup.LLM,
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@ -1271,6 +1272,60 @@ export class ConfigVariables {
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@IsOptional()
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GROQ_API_KEY: string;
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@ConfigVariablesMetadata({
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group: ConfigVariablesGroup.LLM,
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isSensitive: true,
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description: 'API key for Google AI (Gemini) integration',
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type: ConfigVariableType.STRING,
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})
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@IsOptional()
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GOOGLE_API_KEY: string;
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@ConfigVariablesMetadata({
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group: ConfigVariablesGroup.LLM,
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isSensitive: true,
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description: 'API key for Mistral AI integration',
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type: ConfigVariableType.STRING,
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})
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@IsOptional()
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MISTRAL_API_KEY: string;
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@ConfigVariablesMetadata({
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group: ConfigVariablesGroup.LLM,
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description: 'AWS region for Bedrock integration (e.g., us-east-1)',
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type: ConfigVariableType.STRING,
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})
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@IsAWSRegion()
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@IsOptional()
|
||||
AWS_BEDROCK_REGION: AwsRegion;
|
||||
|
||||
@ConfigVariablesMetadata({
|
||||
group: ConfigVariablesGroup.LLM,
|
||||
isSensitive: true,
|
||||
description: 'AWS access key ID for Bedrock authentication',
|
||||
type: ConfigVariableType.STRING,
|
||||
})
|
||||
@IsOptional()
|
||||
AWS_BEDROCK_ACCESS_KEY_ID: string;
|
||||
|
||||
@ConfigVariablesMetadata({
|
||||
group: ConfigVariablesGroup.LLM,
|
||||
isSensitive: true,
|
||||
description: 'AWS secret access key for Bedrock authentication',
|
||||
type: ConfigVariableType.STRING,
|
||||
})
|
||||
@IsOptional()
|
||||
AWS_BEDROCK_SECRET_ACCESS_KEY: string;
|
||||
|
||||
@ConfigVariablesMetadata({
|
||||
group: ConfigVariablesGroup.LLM,
|
||||
isSensitive: true,
|
||||
description: 'AWS session token for Bedrock (for IAM role-based auth)',
|
||||
type: ConfigVariableType.STRING,
|
||||
})
|
||||
@IsOptional()
|
||||
AWS_BEDROCK_SESSION_TOKEN: string;
|
||||
|
||||
@ConfigVariablesMetadata({
|
||||
group: ConfigVariablesGroup.SERVER_CONFIG,
|
||||
description: 'Enable or disable multi-workspace support',
|
||||
|
|
|
|||
|
|
@ -19,6 +19,7 @@ import { type WorkspaceAuthContext } from 'src/engine/core-modules/auth/types/wo
|
|||
import { ToolCategory } from 'src/engine/core-modules/tool-provider/enums/tool-category.enum';
|
||||
import { ToolRegistryService } from 'src/engine/core-modules/tool-provider/services/tool-registry.service';
|
||||
import { type AgentExecutionResult } from 'src/engine/metadata-modules/ai/ai-agent-execution/types/agent-execution-result.type';
|
||||
import { extractCacheCreationTokensFromSteps } from 'src/engine/metadata-modules/ai/ai-billing/utils/extract-cache-creation-tokens.util';
|
||||
import {
|
||||
AgentException,
|
||||
AgentExceptionCode,
|
||||
|
|
@ -185,6 +186,10 @@ export class AgentAsyncExecutorService {
|
|||
},
|
||||
});
|
||||
|
||||
const cacheCreationTokens = extractCacheCreationTokensFromSteps(
|
||||
textResponse.steps,
|
||||
);
|
||||
|
||||
const agentSchema =
|
||||
agent?.responseFormat?.type === 'json'
|
||||
? agent.responseFormat.schema
|
||||
|
|
@ -194,6 +199,7 @@ export class AgentAsyncExecutorService {
|
|||
return {
|
||||
result: { response: textResponse.text },
|
||||
usage: textResponse.usage,
|
||||
cacheCreationTokens,
|
||||
};
|
||||
}
|
||||
|
||||
|
|
@ -222,6 +228,7 @@ export class AgentAsyncExecutorService {
|
|||
(textResponse.usage?.totalTokens ?? 0) +
|
||||
(output.usage?.totalTokens ?? 0),
|
||||
},
|
||||
cacheCreationTokens,
|
||||
};
|
||||
} catch (error) {
|
||||
if (error instanceof AgentException) {
|
||||
|
|
|
|||
|
|
@ -3,4 +3,5 @@ import { type LanguageModelUsage } from 'ai';
|
|||
export interface AgentExecutionResult {
|
||||
result: object;
|
||||
usage: LanguageModelUsage;
|
||||
cacheCreationTokens: number;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -3,12 +3,40 @@ import { Test, type TestingModule } from '@nestjs/testing';
|
|||
import { BILLING_FEATURE_USED } from 'src/engine/core-modules/billing/constants/billing-feature-used.constant';
|
||||
import { BillingMeterEventName } from 'src/engine/core-modules/billing/enums/billing-meter-event-names';
|
||||
import { AIBillingService } from 'src/engine/metadata-modules/ai/ai-billing/services/ai-billing.service';
|
||||
import {
|
||||
InferenceProvider,
|
||||
ModelFamily,
|
||||
} from 'src/engine/metadata-modules/ai/ai-models/constants/ai-models-types.const';
|
||||
import { AiModelRegistryService } from 'src/engine/metadata-modules/ai/ai-models/services/ai-model-registry.service';
|
||||
import { WorkspaceEventEmitter } from 'src/engine/workspace-event-emitter/workspace-event-emitter';
|
||||
|
||||
describe('AIBillingService', () => {
|
||||
let service: AIBillingService;
|
||||
let mockWorkspaceEventEmitter: jest.Mocked<WorkspaceEventEmitter>;
|
||||
let mockAiModelRegistryService: jest.Mocked<
|
||||
Pick<AiModelRegistryService, 'getEffectiveModelConfig'>
|
||||
>;
|
||||
|
||||
const openaiModelConfig = {
|
||||
modelId: 'gpt-4o',
|
||||
label: 'GPT-4o',
|
||||
modelFamily: ModelFamily.OPENAI,
|
||||
inferenceProvider: InferenceProvider.OPENAI,
|
||||
inputCostPerMillionTokens: 2.5,
|
||||
outputCostPerMillionTokens: 10.0,
|
||||
cachedInputCostPerMillionTokens: 1.25,
|
||||
};
|
||||
|
||||
const anthropicModelConfig = {
|
||||
modelId: 'claude-sonnet-4-5-20250929',
|
||||
label: 'Claude Sonnet 4.5',
|
||||
modelFamily: ModelFamily.ANTHROPIC,
|
||||
inferenceProvider: InferenceProvider.ANTHROPIC,
|
||||
inputCostPerMillionTokens: 3.0,
|
||||
outputCostPerMillionTokens: 15.0,
|
||||
cachedInputCostPerMillionTokens: 0.3,
|
||||
cacheCreationCostPerMillionTokens: 3.75,
|
||||
};
|
||||
|
||||
const mockTokenUsage = {
|
||||
inputTokens: 1000,
|
||||
|
|
@ -22,13 +50,7 @@ describe('AIBillingService', () => {
|
|||
};
|
||||
|
||||
const mockAiModelRegistryMethods = {
|
||||
getEffectiveModelConfig: jest.fn().mockReturnValue({
|
||||
modelId: 'gpt-4o',
|
||||
label: 'GPT-4o',
|
||||
provider: 'openai',
|
||||
inputCostPer1kTokensInCents: 0.25,
|
||||
outputCostPer1kTokensInCents: 1.0,
|
||||
}),
|
||||
getEffectiveModelConfig: jest.fn().mockReturnValue(openaiModelConfig),
|
||||
};
|
||||
|
||||
const module: TestingModule = await Test.createTestingModule({
|
||||
|
|
@ -47,6 +69,7 @@ describe('AIBillingService', () => {
|
|||
|
||||
service = module.get<AIBillingService>(AIBillingService);
|
||||
mockWorkspaceEventEmitter = module.get(WorkspaceEventEmitter);
|
||||
mockAiModelRegistryService = module.get(AiModelRegistryService);
|
||||
});
|
||||
|
||||
it('should be defined', () => {
|
||||
|
|
@ -54,40 +77,190 @@ describe('AIBillingService', () => {
|
|||
});
|
||||
|
||||
describe('calculateCost', () => {
|
||||
it('should calculate cost correctly for valid model and token usage', async () => {
|
||||
const costInCents = await service.calculateCost('gpt-4o', mockTokenUsage);
|
||||
it('should calculate cost correctly for basic token usage', () => {
|
||||
const costInDollars = service.calculateCost('gpt-4o', {
|
||||
usage: mockTokenUsage,
|
||||
});
|
||||
|
||||
// Expected: (1000/1000 * 0.25) + (500/1000 * 1.0) = 0.25 + 0.5 = 0.75 cents
|
||||
expect(costInCents).toBe(0.75);
|
||||
// (1000/1M * 2.5) + (500/1M * 10.0) = 0.0025 + 0.005 = 0.0075
|
||||
expect(costInDollars).toBeCloseTo(0.0075);
|
||||
});
|
||||
|
||||
it('should calculate cost correctly with different token usage', async () => {
|
||||
const differentTokenUsage = {
|
||||
inputTokens: 2000,
|
||||
outputTokens: 1000,
|
||||
totalTokens: 3000,
|
||||
};
|
||||
it('should apply cached rate for OpenAI cached tokens', () => {
|
||||
const costInDollars = service.calculateCost('gpt-4o', {
|
||||
usage: {
|
||||
inputTokens: 1000,
|
||||
outputTokens: 500,
|
||||
totalTokens: 1500,
|
||||
cachedInputTokens: 600,
|
||||
},
|
||||
});
|
||||
|
||||
const costInCents = await service.calculateCost(
|
||||
'gpt-4o',
|
||||
differentTokenUsage,
|
||||
// OpenAI: inputTokens includes cached, so adjusted = 1000 - 600 = 400
|
||||
// inputCost = (400/1M * 2.5) = 0.001
|
||||
// cachedCost = (600/1M * 1.25) = 0.00075
|
||||
// outputCost = (500/1M * 10.0) = 0.005
|
||||
// total = 0.00675
|
||||
expect(costInDollars).toBeCloseTo(0.00675);
|
||||
});
|
||||
|
||||
it('should not subtract cached tokens from input for Anthropic', () => {
|
||||
mockAiModelRegistryService.getEffectiveModelConfig.mockReturnValue(
|
||||
anthropicModelConfig as ReturnType<
|
||||
AiModelRegistryService['getEffectiveModelConfig']
|
||||
>,
|
||||
);
|
||||
|
||||
// Expected: (2000/1000 * 0.25) + (1000/1000 * 1.0) = 0.5 + 1.0 = 1.5 cents
|
||||
expect(costInCents).toBe(1.5);
|
||||
const costInDollars = service.calculateCost(
|
||||
'claude-sonnet-4-5-20250929',
|
||||
{
|
||||
usage: {
|
||||
inputTokens: 400,
|
||||
outputTokens: 500,
|
||||
totalTokens: 900,
|
||||
cachedInputTokens: 600,
|
||||
},
|
||||
cacheCreationTokens: 200,
|
||||
},
|
||||
);
|
||||
|
||||
// Anthropic: inputTokens already excludes cached
|
||||
// inputCost = (400/1M * 3.0) = 0.0012
|
||||
// cachedCost = (600/1M * 0.3) = 0.00018
|
||||
// cacheCreationCost = (200/1M * 3.75) = 0.00075
|
||||
// outputCost = (500/1M * 15.0) = 0.0075
|
||||
// total = 0.00963
|
||||
expect(costInDollars).toBeCloseTo(0.00963);
|
||||
});
|
||||
|
||||
it('should charge reasoning tokens at the output rate without double-counting for OpenAI', () => {
|
||||
const costInDollars = service.calculateCost('gpt-4o', {
|
||||
usage: {
|
||||
inputTokens: 1000,
|
||||
outputTokens: 500,
|
||||
totalTokens: 2000,
|
||||
reasoningTokens: 500,
|
||||
},
|
||||
});
|
||||
|
||||
// OpenAI: outputTokens (500) already includes reasoningTokens (500)
|
||||
// adjustedOutput = 500 - 500 = 0
|
||||
// inputCost = (1000/1M * 2.5) = 0.0025
|
||||
// outputCost = (0/1M * 10.0) = 0.0
|
||||
// reasoningCost = (500/1M * 10.0) = 0.005
|
||||
// total = 0.0075
|
||||
expect(costInDollars).toBeCloseTo(0.0075);
|
||||
});
|
||||
|
||||
it('should fall back to input rate when cachedInputCostPerMillionTokens is undefined', () => {
|
||||
mockAiModelRegistryService.getEffectiveModelConfig.mockReturnValue({
|
||||
...openaiModelConfig,
|
||||
cachedInputCostPerMillionTokens: undefined,
|
||||
} as ReturnType<AiModelRegistryService['getEffectiveModelConfig']>);
|
||||
|
||||
const costInDollars = service.calculateCost('gpt-4o', {
|
||||
usage: {
|
||||
inputTokens: 1000,
|
||||
outputTokens: 500,
|
||||
totalTokens: 1500,
|
||||
cachedInputTokens: 600,
|
||||
},
|
||||
});
|
||||
|
||||
// Falls back to full input rate for cached tokens
|
||||
// adjusted = 1000 - 600 = 400
|
||||
// inputCost = (400/1M * 2.5) = 0.001
|
||||
// cachedCost = (600/1M * 2.5) = 0.0015 (fallback to input rate)
|
||||
// outputCost = (500/1M * 10.0) = 0.005
|
||||
// total = 0.0075
|
||||
expect(costInDollars).toBeCloseTo(0.0075);
|
||||
});
|
||||
|
||||
it('should use long context pricing when input exceeds threshold', () => {
|
||||
const anthropicWithLongContext = {
|
||||
...anthropicModelConfig,
|
||||
longContextCost: {
|
||||
inputCostPerMillionTokens: 6.0,
|
||||
outputCostPerMillionTokens: 22.5,
|
||||
cachedInputCostPerMillionTokens: 0.6,
|
||||
cacheCreationCostPerMillionTokens: 7.5,
|
||||
thresholdTokens: 200_000,
|
||||
},
|
||||
};
|
||||
|
||||
mockAiModelRegistryService.getEffectiveModelConfig.mockReturnValue(
|
||||
anthropicWithLongContext as ReturnType<
|
||||
AiModelRegistryService['getEffectiveModelConfig']
|
||||
>,
|
||||
);
|
||||
|
||||
const costInDollars = service.calculateCost(
|
||||
'claude-sonnet-4-5-20250929',
|
||||
{
|
||||
usage: {
|
||||
inputTokens: 150_000,
|
||||
outputTokens: 1000,
|
||||
totalTokens: 251_000,
|
||||
cachedInputTokens: 100_000,
|
||||
},
|
||||
},
|
||||
);
|
||||
|
||||
// Anthropic: total input = 150k + 100k + 0 = 250k > 200k threshold
|
||||
// Uses long context rates
|
||||
// inputCost = (150_000/1M * 6.0) = 0.9
|
||||
// cachedCost = (100_000/1M * 0.6) = 0.06
|
||||
// outputCost = (1000/1M * 22.5) = 0.0225
|
||||
// total = 0.9825
|
||||
expect(costInDollars).toBeCloseTo(0.9825);
|
||||
});
|
||||
|
||||
it('should use standard pricing when input is below threshold', () => {
|
||||
const anthropicWithLongContext = {
|
||||
...anthropicModelConfig,
|
||||
longContextCost: {
|
||||
inputCostPerMillionTokens: 6.0,
|
||||
outputCostPerMillionTokens: 22.5,
|
||||
cachedInputCostPerMillionTokens: 0.6,
|
||||
cacheCreationCostPerMillionTokens: 7.5,
|
||||
thresholdTokens: 200_000,
|
||||
},
|
||||
};
|
||||
|
||||
mockAiModelRegistryService.getEffectiveModelConfig.mockReturnValue(
|
||||
anthropicWithLongContext as ReturnType<
|
||||
AiModelRegistryService['getEffectiveModelConfig']
|
||||
>,
|
||||
);
|
||||
|
||||
const costInDollars = service.calculateCost(
|
||||
'claude-sonnet-4-5-20250929',
|
||||
{
|
||||
usage: {
|
||||
inputTokens: 50_000,
|
||||
outputTokens: 1000,
|
||||
totalTokens: 51_000,
|
||||
},
|
||||
},
|
||||
);
|
||||
|
||||
// Total input = 50k < 200k threshold -> standard rates
|
||||
// inputCost = (50_000/1M * 3.0) = 0.15
|
||||
// outputCost = (1000/1M * 15.0) = 0.015
|
||||
// total = 0.165
|
||||
expect(costInDollars).toBeCloseTo(0.165);
|
||||
});
|
||||
});
|
||||
|
||||
describe('calculateAndBillUsage', () => {
|
||||
it('should calculate cost and emit billing event when model exists', async () => {
|
||||
await service.calculateAndBillUsage(
|
||||
it('should calculate cost and emit billing event when model exists', () => {
|
||||
service.calculateAndBillUsage(
|
||||
'gpt-4o',
|
||||
mockTokenUsage,
|
||||
{ usage: mockTokenUsage },
|
||||
'workspace-1',
|
||||
'agent-id-123',
|
||||
);
|
||||
|
||||
// Expected credits: (0.75 cents / 100) * 1000 = 0.0075 * 1000 = 7.5 credits, rounded to 8
|
||||
expect(
|
||||
mockWorkspaceEventEmitter.emitCustomBatchEvent,
|
||||
).toHaveBeenCalledWith(
|
||||
|
|
|
|||
|
|
@ -1,15 +1,21 @@
|
|||
import { Injectable, Logger } from '@nestjs/common';
|
||||
|
||||
import { LanguageModelUsage } from 'ai';
|
||||
import { type LanguageModelUsage } from 'ai';
|
||||
|
||||
import { BILLING_FEATURE_USED } from 'src/engine/core-modules/billing/constants/billing-feature-used.constant';
|
||||
import { BillingMeterEventName } from 'src/engine/core-modules/billing/enums/billing-meter-event-names';
|
||||
import { type BillingUsageEvent } from 'src/engine/core-modules/billing/types/billing-usage-event.type';
|
||||
import { convertCentsToBillingCredits } from 'src/engine/metadata-modules/ai/ai-billing/utils/convert-cents-to-billing-credits.util';
|
||||
import { type ModelId } from 'src/engine/metadata-modules/ai/ai-models/constants/ai-models.const';
|
||||
import { computeCostBreakdown } from 'src/engine/metadata-modules/ai/ai-billing/utils/compute-cost-breakdown.util';
|
||||
import { convertDollarsToBillingCredits } from 'src/engine/metadata-modules/ai/ai-billing/utils/convert-dollars-to-billing-credits.util';
|
||||
import { type ModelId } from 'src/engine/metadata-modules/ai/ai-models/constants/ai-models-types.const';
|
||||
import { AiModelRegistryService } from 'src/engine/metadata-modules/ai/ai-models/services/ai-model-registry.service';
|
||||
import { WorkspaceEventEmitter } from 'src/engine/workspace-event-emitter/workspace-event-emitter';
|
||||
|
||||
export type BillingUsageInput = {
|
||||
usage: LanguageModelUsage;
|
||||
cacheCreationTokens?: number;
|
||||
};
|
||||
|
||||
@Injectable()
|
||||
export class AIBillingService {
|
||||
private readonly logger = new Logger(AIBillingService.name);
|
||||
|
|
@ -19,38 +25,45 @@ export class AIBillingService {
|
|||
private readonly aiModelRegistryService: AiModelRegistryService,
|
||||
) {}
|
||||
|
||||
async calculateCost(
|
||||
modelId: ModelId,
|
||||
usage: LanguageModelUsage,
|
||||
): Promise<number> {
|
||||
calculateCost(modelId: ModelId, billingInput: BillingUsageInput): number {
|
||||
const model = this.aiModelRegistryService.getEffectiveModelConfig(modelId);
|
||||
|
||||
if (!model) {
|
||||
throw new Error(`AI model with id ${modelId} not found`);
|
||||
}
|
||||
|
||||
const inputCost =
|
||||
((usage.inputTokens ?? 0) / 1000) * model.inputCostPer1kTokensInCents;
|
||||
const outputCost =
|
||||
((usage.outputTokens ?? 0) / 1000) * model.outputCostPer1kTokensInCents;
|
||||
const { usage, cacheCreationTokens = 0 } = billingInput;
|
||||
|
||||
const totalCost = inputCost + outputCost;
|
||||
const breakdown = computeCostBreakdown(model, {
|
||||
inputTokens: usage.inputTokens,
|
||||
outputTokens: usage.outputTokens,
|
||||
reasoningTokens: usage.reasoningTokens,
|
||||
cachedInputTokens: usage.cachedInputTokens,
|
||||
cacheCreationTokens,
|
||||
});
|
||||
|
||||
this.logger.log(
|
||||
`Calculated cost for model ${modelId}: ${totalCost} cents (input: ${inputCost}, output: ${outputCost})`,
|
||||
`Cost for ${model.modelId}: $${breakdown.totalCostInDollars.toFixed(6)} ` +
|
||||
`(input: ${breakdown.tokenCounts.adjustedInputTokens}, ` +
|
||||
`cached: ${breakdown.tokenCounts.cachedInputTokens}, ` +
|
||||
`cacheCreation: ${breakdown.tokenCounts.cacheCreationTokens}, ` +
|
||||
`output: ${breakdown.tokenCounts.adjustedOutputTokens}, ` +
|
||||
`reasoning: ${breakdown.tokenCounts.reasoningTokens})`,
|
||||
);
|
||||
|
||||
return totalCost;
|
||||
return breakdown.totalCostInDollars;
|
||||
}
|
||||
|
||||
async calculateAndBillUsage(
|
||||
calculateAndBillUsage(
|
||||
modelId: ModelId,
|
||||
usage: LanguageModelUsage,
|
||||
billingInput: BillingUsageInput,
|
||||
workspaceId: string,
|
||||
agentId?: string | null,
|
||||
): Promise<void> {
|
||||
const costInCents = await this.calculateCost(modelId, usage);
|
||||
const creditsUsed = Math.round(convertCentsToBillingCredits(costInCents));
|
||||
): void {
|
||||
const costInDollars = this.calculateCost(modelId, billingInput);
|
||||
const creditsUsed = Math.round(
|
||||
convertDollarsToBillingCredits(costInDollars),
|
||||
);
|
||||
|
||||
this.sendAiTokenUsageEvent(workspaceId, creditsUsed, modelId, agentId);
|
||||
}
|
||||
|
|
|
|||
|
|
@ -0,0 +1,98 @@
|
|||
import {
|
||||
type AIModelConfig,
|
||||
ModelFamily,
|
||||
} from 'src/engine/metadata-modules/ai/ai-models/constants/ai-models-types.const';
|
||||
|
||||
export type TokenUsageInput = {
|
||||
inputTokens?: number;
|
||||
outputTokens?: number;
|
||||
reasoningTokens?: number;
|
||||
cachedInputTokens?: number;
|
||||
cacheCreationTokens?: number;
|
||||
};
|
||||
|
||||
export type CostBreakdown = {
|
||||
totalCostInDollars: number;
|
||||
inputCostInDollars: number;
|
||||
outputCostInDollars: number;
|
||||
tokenCounts: {
|
||||
adjustedInputTokens: number;
|
||||
adjustedOutputTokens: number;
|
||||
cachedInputTokens: number;
|
||||
cacheCreationTokens: number;
|
||||
reasoningTokens: number;
|
||||
totalInputTokens: number;
|
||||
};
|
||||
};
|
||||
|
||||
const safeNumber = (value: number | undefined): number => {
|
||||
const result = value ?? 0;
|
||||
|
||||
return Number.isFinite(result) ? result : 0;
|
||||
};
|
||||
|
||||
// Input token semantics differ by model family:
|
||||
// Anthropic: inputTokens excludes cached and cache creation tokens
|
||||
// OpenAI/xAI/Groq/Google: inputTokens includes cached tokens
|
||||
// Output token semantics also differ:
|
||||
// Anthropic: outputTokens excludes reasoning (thinking) tokens
|
||||
// OpenAI/xAI/Groq/Google: outputTokens includes reasoning tokens
|
||||
export const computeCostBreakdown = (
|
||||
model: AIModelConfig,
|
||||
usage: TokenUsageInput,
|
||||
): CostBreakdown => {
|
||||
const rawInputTokens = safeNumber(usage.inputTokens);
|
||||
const rawOutputTokens = safeNumber(usage.outputTokens);
|
||||
const reasoningTokens = safeNumber(usage.reasoningTokens);
|
||||
const cachedInputTokens = safeNumber(usage.cachedInputTokens);
|
||||
const cacheCreationTokens = safeNumber(usage.cacheCreationTokens);
|
||||
|
||||
const isAnthropicFamily = model.modelFamily === ModelFamily.ANTHROPIC;
|
||||
|
||||
const adjustedInputTokens = isAnthropicFamily
|
||||
? rawInputTokens
|
||||
: Math.max(0, rawInputTokens - cachedInputTokens);
|
||||
|
||||
const adjustedOutputTokens = isAnthropicFamily
|
||||
? rawOutputTokens
|
||||
: Math.max(0, rawOutputTokens - reasoningTokens);
|
||||
|
||||
const totalInputTokens = isAnthropicFamily
|
||||
? rawInputTokens + cachedInputTokens + cacheCreationTokens
|
||||
: rawInputTokens + cacheCreationTokens;
|
||||
|
||||
const costInfo =
|
||||
model.longContextCost &&
|
||||
totalInputTokens > model.longContextCost.thresholdTokens
|
||||
? model.longContextCost
|
||||
: model;
|
||||
|
||||
const inputRate = costInfo.inputCostPerMillionTokens;
|
||||
const outputRate = costInfo.outputCostPerMillionTokens;
|
||||
const cachedRate = costInfo.cachedInputCostPerMillionTokens ?? inputRate;
|
||||
const cacheCreationRate =
|
||||
costInfo.cacheCreationCostPerMillionTokens ?? inputRate;
|
||||
|
||||
const inputCostInDollars =
|
||||
(adjustedInputTokens / 1_000_000) * inputRate +
|
||||
(cachedInputTokens / 1_000_000) * cachedRate +
|
||||
(cacheCreationTokens / 1_000_000) * cacheCreationRate;
|
||||
|
||||
const outputCostInDollars =
|
||||
(adjustedOutputTokens / 1_000_000) * outputRate +
|
||||
(reasoningTokens / 1_000_000) * outputRate;
|
||||
|
||||
return {
|
||||
totalCostInDollars: inputCostInDollars + outputCostInDollars,
|
||||
inputCostInDollars,
|
||||
outputCostInDollars,
|
||||
tokenCounts: {
|
||||
adjustedInputTokens,
|
||||
adjustedOutputTokens,
|
||||
cachedInputTokens,
|
||||
cacheCreationTokens,
|
||||
reasoningTokens,
|
||||
totalInputTokens,
|
||||
},
|
||||
};
|
||||
};
|
||||
|
|
@ -1,8 +0,0 @@
|
|||
import { DOLLAR_TO_CREDIT_MULTIPLIER } from 'src/engine/metadata-modules/ai/ai-billing/constants/dollar-to-credit-multiplier';
|
||||
|
||||
// Converts cost in cents to cost in credits
|
||||
// Formula: credits = (cents / 100) * DOLLAR_TO_CREDIT_MULTIPLIER
|
||||
// Where DOLLAR_TO_CREDIT_MULTIPLIER = 1_000_000 (so $0.000_001 = 1 credit)
|
||||
// Example: 1 cent = (1 / 100) * 1_000_000 = 10_000 credits
|
||||
export const convertCentsToBillingCredits = (cents: number): number =>
|
||||
(cents / 100) * DOLLAR_TO_CREDIT_MULTIPLIER;
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
import { DOLLAR_TO_CREDIT_MULTIPLIER } from 'src/engine/metadata-modules/ai/ai-billing/constants/dollar-to-credit-multiplier';
|
||||
|
||||
export const convertDollarsToBillingCredits = (dollars: number): number =>
|
||||
dollars * DOLLAR_TO_CREDIT_MULTIPLIER;
|
||||
|
|
@ -0,0 +1,28 @@
|
|||
type ProviderMetadataLike = Record<string, Record<string, unknown> | undefined>;
|
||||
|
||||
// Anthropic and Bedrock report cache creation tokens in provider metadata
|
||||
// rather than the standard usage object. Anthropic exposes it as a
|
||||
// top-level camelCase field; Bedrock nests it under `usage`.
|
||||
export const extractCacheCreationTokensFromSteps = (
|
||||
steps: Array<{ providerMetadata?: ProviderMetadataLike }>,
|
||||
): number => {
|
||||
return steps.reduce((sum, step) => {
|
||||
return sum + extractCacheCreationTokens(step.providerMetadata);
|
||||
}, 0);
|
||||
};
|
||||
|
||||
export const extractCacheCreationTokens = (
|
||||
providerMetadata: ProviderMetadataLike | undefined,
|
||||
): number => {
|
||||
const anthropicMeta = providerMetadata?.anthropic as
|
||||
| Record<string, unknown>
|
||||
| undefined;
|
||||
const bedrockUsage = (providerMetadata?.bedrock as Record<string, unknown>)
|
||||
?.usage as Record<string, unknown> | undefined;
|
||||
|
||||
return (
|
||||
(anthropicMeta?.cacheCreationInputTokens as number | undefined) ??
|
||||
(bedrockUsage?.cacheWriteInputTokens as number | undefined) ??
|
||||
0
|
||||
);
|
||||
};
|
||||
|
|
@ -16,8 +16,11 @@ import {
|
|||
AgentExceptionCode,
|
||||
} from 'src/engine/metadata-modules/ai/ai-agent/agent.exception';
|
||||
import { type BrowsingContextType } from 'src/engine/metadata-modules/ai/ai-agent/types/browsingContext.type';
|
||||
import { convertCentsToBillingCredits } from 'src/engine/metadata-modules/ai/ai-billing/utils/convert-cents-to-billing-credits.util';
|
||||
import { computeCostBreakdown } from 'src/engine/metadata-modules/ai/ai-billing/utils/compute-cost-breakdown.util';
|
||||
import { convertDollarsToBillingCredits } from 'src/engine/metadata-modules/ai/ai-billing/utils/convert-dollars-to-billing-credits.util';
|
||||
import { extractCacheCreationTokens } from 'src/engine/metadata-modules/ai/ai-billing/utils/extract-cache-creation-tokens.util';
|
||||
import { toDisplayCredits } from 'src/engine/core-modules/billing/utils/to-display-credits.util';
|
||||
import { type AIModelConfig } from 'src/engine/metadata-modules/ai/ai-models/constants/ai-models-types.const';
|
||||
import { AgentChatThreadEntity } from 'src/engine/metadata-modules/ai/ai-chat/entities/agent-chat-thread.entity';
|
||||
|
||||
import { AgentChatService } from './agent-chat.service';
|
||||
|
|
@ -129,20 +132,16 @@ export class AgentChatStreamingService {
|
|||
if (part.type === 'finish-step') {
|
||||
const stepInput = part.usage?.inputTokens ?? 0;
|
||||
const stepCached = part.usage?.cachedInputTokens ?? 0;
|
||||
|
||||
// Anthropic excludes cached/created tokens from input_tokens,
|
||||
// reporting them separately as cache_creation_input_tokens
|
||||
const anthropicUsage = (
|
||||
part as {
|
||||
providerMetadata?: {
|
||||
anthropic?: {
|
||||
usage?: { cache_creation_input_tokens?: number };
|
||||
};
|
||||
};
|
||||
}
|
||||
).providerMetadata?.anthropic?.usage;
|
||||
const stepCacheCreation =
|
||||
anthropicUsage?.cache_creation_input_tokens ?? 0;
|
||||
const stepCacheCreation = extractCacheCreationTokens(
|
||||
(
|
||||
part as {
|
||||
providerMetadata?: Record<
|
||||
string,
|
||||
Record<string, unknown> | undefined
|
||||
>;
|
||||
}
|
||||
).providerMetadata,
|
||||
);
|
||||
|
||||
totalCacheCreationTokens += stepCacheCreation;
|
||||
lastStepConversationSize =
|
||||
|
|
@ -150,31 +149,16 @@ export class AgentChatStreamingService {
|
|||
}
|
||||
|
||||
if (part.type === 'finish') {
|
||||
const inputTokens =
|
||||
(part.totalUsage?.inputTokens ?? 0) +
|
||||
(part.totalUsage?.cachedInputTokens ?? 0) +
|
||||
totalCacheCreationTokens;
|
||||
const outputTokens = part.totalUsage?.outputTokens ?? 0;
|
||||
const cachedInputTokens =
|
||||
part.totalUsage?.cachedInputTokens ?? 0;
|
||||
|
||||
const inputCostInCents =
|
||||
(inputTokens / 1000) *
|
||||
modelConfig.inputCostPer1kTokensInCents;
|
||||
const outputCostInCents =
|
||||
(outputTokens / 1000) *
|
||||
modelConfig.outputCostPer1kTokensInCents;
|
||||
|
||||
const inputCredits = Math.round(
|
||||
convertCentsToBillingCredits(inputCostInCents),
|
||||
);
|
||||
const outputCredits = Math.round(
|
||||
convertCentsToBillingCredits(outputCostInCents),
|
||||
);
|
||||
const { inputCredits, outputCredits, tokenCounts } =
|
||||
computeStreamCosts(
|
||||
modelConfig,
|
||||
part.totalUsage,
|
||||
totalCacheCreationTokens,
|
||||
);
|
||||
|
||||
streamUsage = {
|
||||
inputTokens,
|
||||
outputTokens,
|
||||
inputTokens: tokenCounts.totalInputTokens,
|
||||
outputTokens: tokenCounts.outputTokens,
|
||||
inputCredits,
|
||||
outputCredits,
|
||||
};
|
||||
|
|
@ -182,9 +166,9 @@ export class AgentChatStreamingService {
|
|||
return {
|
||||
createdAt: new Date().toISOString(),
|
||||
usage: {
|
||||
inputTokens,
|
||||
outputTokens,
|
||||
cachedInputTokens,
|
||||
inputTokens: tokenCounts.totalInputTokens,
|
||||
outputTokens: tokenCounts.outputTokens,
|
||||
cachedInputTokens: tokenCounts.cachedInputTokens,
|
||||
inputCredits: toDisplayCredits(inputCredits),
|
||||
outputCredits: toDisplayCredits(outputCredits),
|
||||
conversationSize: lastStepConversationSize,
|
||||
|
|
@ -254,3 +238,38 @@ export class AgentChatStreamingService {
|
|||
}
|
||||
}
|
||||
}
|
||||
|
||||
function computeStreamCosts(
|
||||
modelConfig: AIModelConfig,
|
||||
totalUsage:
|
||||
| {
|
||||
inputTokens?: number;
|
||||
outputTokens?: number;
|
||||
cachedInputTokens?: number;
|
||||
reasoningTokens?: number;
|
||||
}
|
||||
| undefined,
|
||||
cacheCreationTokens: number,
|
||||
) {
|
||||
const breakdown = computeCostBreakdown(modelConfig, {
|
||||
inputTokens: totalUsage?.inputTokens,
|
||||
outputTokens: totalUsage?.outputTokens,
|
||||
cachedInputTokens: totalUsage?.cachedInputTokens,
|
||||
reasoningTokens: totalUsage?.reasoningTokens,
|
||||
cacheCreationTokens,
|
||||
});
|
||||
|
||||
return {
|
||||
inputCredits: Math.round(
|
||||
convertDollarsToBillingCredits(breakdown.inputCostInDollars),
|
||||
),
|
||||
outputCredits: Math.round(
|
||||
convertDollarsToBillingCredits(breakdown.outputCostInDollars),
|
||||
),
|
||||
tokenCounts: {
|
||||
totalInputTokens: breakdown.tokenCounts.totalInputTokens,
|
||||
outputTokens: totalUsage?.outputTokens ?? 0,
|
||||
cachedInputTokens: breakdown.tokenCounts.cachedInputTokens,
|
||||
},
|
||||
};
|
||||
}
|
||||
|
|
|
|||
|
|
@ -18,6 +18,7 @@ import { getAppPath, isDefined } from 'twenty-shared/utils';
|
|||
|
||||
import { type CodeExecutionStreamEmitter } from 'src/engine/core-modules/tool-provider/interfaces/tool-provider.interface';
|
||||
|
||||
import { ExceptionHandlerService } from 'src/engine/core-modules/exception-handler/exception-handler.service';
|
||||
import { WorkspaceDomainsService } from 'src/engine/core-modules/domain/workspace-domains/services/workspace-domains.service';
|
||||
import { COMMON_PRELOAD_TOOLS } from 'src/engine/core-modules/tool-provider/constants/common-preload-tools.const';
|
||||
import { wrapToolsWithOutputSerialization } from 'src/engine/core-modules/tool-provider/output-serialization/wrap-tools-with-output-serialization.util';
|
||||
|
|
@ -36,6 +37,7 @@ import { AGENT_CONFIG } from 'src/engine/metadata-modules/ai/ai-agent/constants/
|
|||
import { type BrowsingContextType } from 'src/engine/metadata-modules/ai/ai-agent/types/browsingContext.type';
|
||||
import { repairToolCall } from 'src/engine/metadata-modules/ai/ai-agent/utils/repair-tool-call.util';
|
||||
import { AIBillingService } from 'src/engine/metadata-modules/ai/ai-billing/services/ai-billing.service';
|
||||
import { extractCacheCreationTokensFromSteps } from 'src/engine/metadata-modules/ai/ai-billing/utils/extract-cache-creation-tokens.util';
|
||||
import { SystemPromptBuilderService } from 'src/engine/metadata-modules/ai/ai-chat/services/system-prompt-builder.service';
|
||||
import {
|
||||
extractCodeInterpreterFiles,
|
||||
|
|
@ -43,7 +45,7 @@ import {
|
|||
} from 'src/engine/metadata-modules/ai/ai-chat/utils/extract-code-interpreter-files.util';
|
||||
import {
|
||||
type AIModelConfig,
|
||||
ModelProvider,
|
||||
InferenceProvider,
|
||||
} from 'src/engine/metadata-modules/ai/ai-models/constants/ai-models.const';
|
||||
import { AI_TELEMETRY_CONFIG } from 'src/engine/metadata-modules/ai/ai-models/constants/ai-telemetry.const';
|
||||
import { AiModelRegistryService } from 'src/engine/metadata-modules/ai/ai-models/services/ai-model-registry.service';
|
||||
|
|
@ -74,6 +76,7 @@ export class ChatExecutionService {
|
|||
private readonly agentActorContextService: AgentActorContextService,
|
||||
private readonly workspaceDomainsService: WorkspaceDomainsService,
|
||||
private readonly systemPromptBuilder: SystemPromptBuilderService,
|
||||
private readonly exceptionHandlerService: ExceptionHandlerService,
|
||||
) {}
|
||||
|
||||
async streamChat({
|
||||
|
|
@ -137,7 +140,7 @@ export class ChatExecutionService {
|
|||
// These are callable directly AND as fallback through execute_tool.
|
||||
const directTools: ToolSet = {
|
||||
...wrapToolsWithOutputSerialization(preloadedTools),
|
||||
...this.getNativeWebSearchTool(registeredModel.provider),
|
||||
...this.getNativeWebSearchTool(registeredModel.inferenceProvider),
|
||||
};
|
||||
|
||||
// ToolSet is constant for the entire conversation — no mutation.
|
||||
|
|
@ -192,9 +195,11 @@ export class ChatExecutionService {
|
|||
role: 'system',
|
||||
content: systemPrompt,
|
||||
providerOptions:
|
||||
registeredModel.provider === ModelProvider.ANTHROPIC
|
||||
registeredModel.inferenceProvider === InferenceProvider.ANTHROPIC
|
||||
? { anthropic: { cacheControl: { type: 'ephemeral' } } }
|
||||
: undefined,
|
||||
: registeredModel.inferenceProvider === InferenceProvider.BEDROCK
|
||||
? { bedrock: { cacheControl: { type: 'ephemeral' } } }
|
||||
: undefined,
|
||||
};
|
||||
|
||||
const stream = streamText({
|
||||
|
|
@ -219,17 +224,19 @@ export class ChatExecutionService {
|
|||
},
|
||||
});
|
||||
|
||||
stream.usage
|
||||
.then((usage) => {
|
||||
Promise.all([stream.usage, stream.steps])
|
||||
.then(([usage, steps]) => {
|
||||
const cacheCreationTokens = extractCacheCreationTokensFromSteps(steps);
|
||||
|
||||
this.aiBillingService.calculateAndBillUsage(
|
||||
registeredModel.modelId,
|
||||
usage,
|
||||
{ usage, cacheCreationTokens },
|
||||
workspace.id,
|
||||
null,
|
||||
);
|
||||
})
|
||||
.catch((error) => {
|
||||
this.logger.error('Failed to bill usage:', error);
|
||||
this.exceptionHandlerService.captureExceptions([error]);
|
||||
});
|
||||
|
||||
return {
|
||||
|
|
@ -308,14 +315,28 @@ export class ChatExecutionService {
|
|||
return context;
|
||||
}
|
||||
|
||||
private getNativeWebSearchTool(provider: ModelProvider): ToolSet {
|
||||
switch (provider) {
|
||||
case ModelProvider.ANTHROPIC:
|
||||
private getNativeWebSearchTool(
|
||||
inferenceProvider: InferenceProvider,
|
||||
): ToolSet {
|
||||
switch (inferenceProvider) {
|
||||
case InferenceProvider.ANTHROPIC:
|
||||
return { web_search: anthropic.tools.webSearch_20250305() };
|
||||
case ModelProvider.OPENAI:
|
||||
case InferenceProvider.BEDROCK: {
|
||||
const bedrockProvider =
|
||||
this.aiModelRegistryService.getBedrockProvider();
|
||||
|
||||
if (bedrockProvider) {
|
||||
return {
|
||||
web_search:
|
||||
bedrockProvider.tools.webSearch_20250305() as ToolSet[string],
|
||||
};
|
||||
}
|
||||
|
||||
return {};
|
||||
}
|
||||
case InferenceProvider.OPENAI:
|
||||
return { web_search: openai.tools.webSearch() };
|
||||
case ModelProvider.GROQ:
|
||||
// Type assertion needed due to @ai-sdk/groq tool type mismatch
|
||||
case InferenceProvider.GROQ:
|
||||
return {
|
||||
web_search: groq.tools.browserSearch({}) as ToolSet[string],
|
||||
};
|
||||
|
|
|
|||
|
|
@ -1,12 +1,23 @@
|
|||
export enum ModelProvider {
|
||||
export enum InferenceProvider {
|
||||
NONE = 'none',
|
||||
OPENAI = 'openai',
|
||||
ANTHROPIC = 'anthropic',
|
||||
BEDROCK = 'bedrock',
|
||||
GOOGLE = 'google',
|
||||
MISTRAL = 'mistral',
|
||||
OPENAI_COMPATIBLE = 'open_ai_compatible',
|
||||
XAI = 'xai',
|
||||
GROQ = 'groq',
|
||||
}
|
||||
|
||||
export enum ModelFamily {
|
||||
OPENAI = 'openai',
|
||||
ANTHROPIC = 'anthropic',
|
||||
GOOGLE = 'google',
|
||||
MISTRAL = 'mistral',
|
||||
XAI = 'xai',
|
||||
}
|
||||
|
||||
export const DEFAULT_FAST_MODEL = 'default-fast-model' as const;
|
||||
export const DEFAULT_SMART_MODEL = 'default-smart-model' as const;
|
||||
|
||||
|
|
@ -14,27 +25,41 @@ export type ModelId =
|
|||
| typeof DEFAULT_FAST_MODEL
|
||||
| typeof DEFAULT_SMART_MODEL
|
||||
// OpenAI models
|
||||
| 'gpt-5.2'
|
||||
| 'gpt-5-mini'
|
||||
| 'gpt-4.1'
|
||||
| 'gpt-4.1-mini'
|
||||
| 'gpt-4o'
|
||||
| 'gpt-4o-mini'
|
||||
| 'gpt-4-turbo'
|
||||
| 'gpt-4.1'
|
||||
| 'gpt-4.1-mini'
|
||||
| 'o3'
|
||||
| 'o4-mini'
|
||||
// Anthropic models
|
||||
| 'claude-opus-4-6'
|
||||
| 'claude-sonnet-4-6'
|
||||
| 'claude-sonnet-4-5-20250929'
|
||||
| 'claude-haiku-4-5-20251001'
|
||||
| 'claude-opus-4-5-20251101'
|
||||
| 'claude-opus-4-20250514'
|
||||
| 'claude-sonnet-4-20250514'
|
||||
| 'claude-3-5-haiku-20241022'
|
||||
| 'claude-opus-4-5-20251101'
|
||||
| 'claude-sonnet-4-5-20250929'
|
||||
| 'claude-haiku-4-5-20251001'
|
||||
// xAI models
|
||||
| 'grok-3'
|
||||
| 'grok-3-mini'
|
||||
| 'grok-4'
|
||||
| 'grok-4-1-fast-reasoning'
|
||||
| 'grok-3'
|
||||
| 'grok-3-mini'
|
||||
// Google models
|
||||
| 'gemini-3.1-pro-preview'
|
||||
| 'gemini-3-flash-preview'
|
||||
| 'gemini-2.5-pro'
|
||||
| 'gemini-2.5-flash'
|
||||
// Bedrock models (Anthropic via AWS)
|
||||
| 'anthropic.claude-opus-4-6-v1'
|
||||
| 'anthropic.claude-sonnet-4-6'
|
||||
// Groq models
|
||||
| 'openai/gpt-oss-120b'
|
||||
// Mistral models
|
||||
| 'mistral-large-latest'
|
||||
| string; // Allow custom model names
|
||||
|
||||
export type SupportedFileType =
|
||||
|
|
@ -48,13 +73,25 @@ export type SupportedFileType =
|
|||
| 'text/csv'
|
||||
| 'application/json';
|
||||
|
||||
export type LongContextCost = {
|
||||
inputCostPerMillionTokens: number;
|
||||
outputCostPerMillionTokens: number;
|
||||
cachedInputCostPerMillionTokens?: number;
|
||||
cacheCreationCostPerMillionTokens?: number;
|
||||
thresholdTokens: number;
|
||||
};
|
||||
|
||||
export interface AIModelConfig {
|
||||
modelId: ModelId;
|
||||
label: string;
|
||||
description: string;
|
||||
provider: ModelProvider;
|
||||
inputCostPer1kTokensInCents: number;
|
||||
outputCostPer1kTokensInCents: number;
|
||||
modelFamily: ModelFamily;
|
||||
inferenceProvider: InferenceProvider;
|
||||
inputCostPerMillionTokens: number;
|
||||
outputCostPerMillionTokens: number;
|
||||
cachedInputCostPerMillionTokens?: number;
|
||||
cacheCreationCostPerMillionTokens?: number;
|
||||
longContextCost?: LongContextCost;
|
||||
contextWindowTokens: number;
|
||||
maxOutputTokens: number;
|
||||
supportedFileTypes?: SupportedFileType[];
|
||||
|
|
|
|||
|
|
@ -6,21 +6,24 @@ import { AiModelRegistryService } from 'src/engine/metadata-modules/ai/ai-models
|
|||
import {
|
||||
AI_MODELS,
|
||||
DEFAULT_SMART_MODEL,
|
||||
ModelProvider,
|
||||
InferenceProvider,
|
||||
} from './ai-models.const';
|
||||
|
||||
describe('AI_MODELS', () => {
|
||||
it('should have at least one model per provider', () => {
|
||||
const providers = [
|
||||
ModelProvider.OPENAI,
|
||||
ModelProvider.ANTHROPIC,
|
||||
ModelProvider.XAI,
|
||||
ModelProvider.GROQ,
|
||||
it('should have at least one model per inference provider', () => {
|
||||
const inferenceProviders = [
|
||||
InferenceProvider.OPENAI,
|
||||
InferenceProvider.ANTHROPIC,
|
||||
InferenceProvider.BEDROCK,
|
||||
InferenceProvider.GOOGLE,
|
||||
InferenceProvider.XAI,
|
||||
InferenceProvider.GROQ,
|
||||
InferenceProvider.MISTRAL,
|
||||
];
|
||||
|
||||
providers.forEach((provider) => {
|
||||
inferenceProviders.forEach((inferenceProvider) => {
|
||||
const modelsForProvider = AI_MODELS.filter(
|
||||
(model) => model.provider === provider,
|
||||
(model) => model.inferenceProvider === inferenceProvider,
|
||||
);
|
||||
|
||||
expect(modelsForProvider.length).toBeGreaterThan(0);
|
||||
|
|
@ -32,9 +35,10 @@ describe('AI_MODELS', () => {
|
|||
expect(model.modelId).toBeDefined();
|
||||
expect(model.label).toBeDefined();
|
||||
expect(model.description).toBeDefined();
|
||||
expect(model.provider).toBeDefined();
|
||||
expect(model.inputCostPer1kTokensInCents).toBeDefined();
|
||||
expect(model.outputCostPer1kTokensInCents).toBeDefined();
|
||||
expect(model.modelFamily).toBeDefined();
|
||||
expect(model.inferenceProvider).toBeDefined();
|
||||
expect(model.inputCostPerMillionTokens).toBeDefined();
|
||||
expect(model.outputCostPerMillionTokens).toBeDefined();
|
||||
expect(model.contextWindowTokens).toBeGreaterThan(0);
|
||||
expect(model.maxOutputTokens).toBeGreaterThan(0);
|
||||
});
|
||||
|
|
@ -47,17 +51,21 @@ describe('AI_MODELS', () => {
|
|||
expect(uniqueModelIds.size).toBe(modelIds.length);
|
||||
});
|
||||
|
||||
it('should have at least one non-deprecated model per provider', () => {
|
||||
const providers = [
|
||||
ModelProvider.OPENAI,
|
||||
ModelProvider.ANTHROPIC,
|
||||
ModelProvider.XAI,
|
||||
ModelProvider.GROQ,
|
||||
it('should have at least one non-deprecated model per inference provider', () => {
|
||||
const inferenceProviders = [
|
||||
InferenceProvider.OPENAI,
|
||||
InferenceProvider.ANTHROPIC,
|
||||
InferenceProvider.BEDROCK,
|
||||
InferenceProvider.GOOGLE,
|
||||
InferenceProvider.XAI,
|
||||
InferenceProvider.GROQ,
|
||||
InferenceProvider.MISTRAL,
|
||||
];
|
||||
|
||||
providers.forEach((provider) => {
|
||||
inferenceProviders.forEach((inferenceProvider) => {
|
||||
const activeModelsForProvider = AI_MODELS.filter(
|
||||
(model) => model.provider === provider && !model.deprecated,
|
||||
(model) =>
|
||||
model.inferenceProvider === inferenceProvider && !model.deprecated,
|
||||
);
|
||||
|
||||
expect(activeModelsForProvider.length).toBeGreaterThan(0);
|
||||
|
|
@ -88,35 +96,35 @@ describe('AiModelRegistryService', () => {
|
|||
});
|
||||
|
||||
it('should return effective model config for DEFAULT_SMART_MODEL', () => {
|
||||
MOCK_CONFIG_SERVICE.get.mockReturnValue('gpt-4o');
|
||||
MOCK_CONFIG_SERVICE.get.mockReturnValue('gpt-5.2');
|
||||
|
||||
expect(() => SERVICE.getEffectiveModelConfig(DEFAULT_SMART_MODEL)).toThrow(
|
||||
'No AI models are available. Please configure at least one AI provider API key (OPENAI_API_KEY, ANTHROPIC_API_KEY, XAI_API_KEY, or GROQ_API_KEY).',
|
||||
'No AI models are available. Please configure at least one AI provider (OPENAI_API_KEY, ANTHROPIC_API_KEY, AWS_BEDROCK_REGION, GOOGLE_API_KEY, XAI_API_KEY, GROQ_API_KEY, or MISTRAL_API_KEY).',
|
||||
);
|
||||
});
|
||||
|
||||
it('should return effective model config for DEFAULT_SMART_MODEL when models are available', () => {
|
||||
MOCK_CONFIG_SERVICE.get.mockReturnValue('gpt-4o');
|
||||
MOCK_CONFIG_SERVICE.get.mockReturnValue('gpt-5.2');
|
||||
|
||||
jest.spyOn(SERVICE, 'getAvailableModels').mockReturnValue([
|
||||
{
|
||||
modelId: 'gpt-4o',
|
||||
provider: ModelProvider.OPENAI,
|
||||
modelId: 'gpt-5.2',
|
||||
inferenceProvider: InferenceProvider.OPENAI,
|
||||
model: {} as any,
|
||||
},
|
||||
]);
|
||||
|
||||
jest.spyOn(SERVICE, 'getModel').mockReturnValue({
|
||||
modelId: 'gpt-4o',
|
||||
provider: ModelProvider.OPENAI,
|
||||
modelId: 'gpt-5.2',
|
||||
inferenceProvider: InferenceProvider.OPENAI,
|
||||
model: {} as any,
|
||||
});
|
||||
|
||||
const RESULT = SERVICE.getEffectiveModelConfig(DEFAULT_SMART_MODEL);
|
||||
|
||||
expect(RESULT).toBeDefined();
|
||||
expect(RESULT.modelId).toBe('gpt-4o');
|
||||
expect(RESULT.provider).toBe(ModelProvider.OPENAI);
|
||||
expect(RESULT.modelId).toBe('gpt-5.2');
|
||||
expect(RESULT.inferenceProvider).toBe(InferenceProvider.OPENAI);
|
||||
});
|
||||
|
||||
it('should return effective model config for DEFAULT_SMART_MODEL with custom model', () => {
|
||||
|
|
@ -125,14 +133,14 @@ describe('AiModelRegistryService', () => {
|
|||
jest.spyOn(SERVICE, 'getAvailableModels').mockReturnValue([
|
||||
{
|
||||
modelId: 'mistral',
|
||||
provider: ModelProvider.OPENAI_COMPATIBLE,
|
||||
inferenceProvider: InferenceProvider.OPENAI_COMPATIBLE,
|
||||
model: {} as any,
|
||||
},
|
||||
]);
|
||||
|
||||
jest.spyOn(SERVICE, 'getModel').mockReturnValue({
|
||||
modelId: 'mistral',
|
||||
provider: ModelProvider.OPENAI_COMPATIBLE,
|
||||
inferenceProvider: InferenceProvider.OPENAI_COMPATIBLE,
|
||||
model: {} as any,
|
||||
});
|
||||
|
||||
|
|
@ -140,25 +148,24 @@ describe('AiModelRegistryService', () => {
|
|||
|
||||
expect(RESULT).toBeDefined();
|
||||
expect(RESULT.modelId).toBe('mistral');
|
||||
expect(RESULT.provider).toBe(ModelProvider.OPENAI_COMPATIBLE);
|
||||
expect(RESULT.inferenceProvider).toBe(InferenceProvider.OPENAI_COMPATIBLE);
|
||||
expect(RESULT.label).toBe('mistral');
|
||||
expect(RESULT.inputCostPer1kTokensInCents).toBe(0);
|
||||
expect(RESULT.outputCostPer1kTokensInCents).toBe(0);
|
||||
expect(RESULT.inputCostPerMillionTokens).toBe(0);
|
||||
expect(RESULT.outputCostPerMillionTokens).toBe(0);
|
||||
});
|
||||
|
||||
it('should return effective model config for specific model', () => {
|
||||
const RESULT = SERVICE.getEffectiveModelConfig('gpt-4o-mini');
|
||||
const RESULT = SERVICE.getEffectiveModelConfig('gpt-5.2');
|
||||
|
||||
expect(RESULT).toBeDefined();
|
||||
expect(RESULT.modelId).toBe('gpt-4o-mini');
|
||||
expect(RESULT.provider).toBe(ModelProvider.OPENAI);
|
||||
expect(RESULT.modelId).toBe('gpt-5.2');
|
||||
expect(RESULT.inferenceProvider).toBe(InferenceProvider.OPENAI);
|
||||
});
|
||||
|
||||
it('should return effective model config for custom model', () => {
|
||||
// Mock that the custom model exists in registry
|
||||
jest.spyOn(SERVICE, 'getModel').mockReturnValue({
|
||||
modelId: 'mistral',
|
||||
provider: ModelProvider.OPENAI_COMPATIBLE,
|
||||
inferenceProvider: InferenceProvider.OPENAI_COMPATIBLE,
|
||||
model: {} as any,
|
||||
});
|
||||
|
||||
|
|
@ -166,10 +173,10 @@ describe('AiModelRegistryService', () => {
|
|||
|
||||
expect(RESULT).toBeDefined();
|
||||
expect(RESULT.modelId).toBe('mistral');
|
||||
expect(RESULT.provider).toBe(ModelProvider.OPENAI_COMPATIBLE);
|
||||
expect(RESULT.inferenceProvider).toBe(InferenceProvider.OPENAI_COMPATIBLE);
|
||||
expect(RESULT.label).toBe('mistral');
|
||||
expect(RESULT.inputCostPer1kTokensInCents).toBe(0);
|
||||
expect(RESULT.outputCostPer1kTokensInCents).toBe(0);
|
||||
expect(RESULT.inputCostPerMillionTokens).toBe(0);
|
||||
expect(RESULT.outputCostPerMillionTokens).toBe(0);
|
||||
});
|
||||
|
||||
it('should throw error for non-existent model', () => {
|
||||
|
|
@ -181,9 +188,8 @@ describe('AiModelRegistryService', () => {
|
|||
});
|
||||
|
||||
it('should find first available model from comma-separated list', () => {
|
||||
// First model not available, second model available
|
||||
MOCK_CONFIG_SERVICE.get.mockReturnValue(
|
||||
'gpt-4.1-mini,claude-haiku-4-5-20251001,grok-3-mini',
|
||||
'gpt-5-mini,claude-haiku-4-5-20251001,gemini-3-flash-preview',
|
||||
);
|
||||
|
||||
const getModelSpy = jest
|
||||
|
|
@ -192,7 +198,7 @@ describe('AiModelRegistryService', () => {
|
|||
if (modelId === 'claude-haiku-4-5-20251001') {
|
||||
return {
|
||||
modelId: 'claude-haiku-4-5-20251001',
|
||||
provider: ModelProvider.ANTHROPIC,
|
||||
inferenceProvider: InferenceProvider.ANTHROPIC,
|
||||
model: {} as any,
|
||||
};
|
||||
}
|
||||
|
|
@ -204,7 +210,7 @@ describe('AiModelRegistryService', () => {
|
|||
|
||||
expect(result).toBeDefined();
|
||||
expect(result.modelId).toBe('claude-haiku-4-5-20251001');
|
||||
expect(getModelSpy).toHaveBeenCalledWith('gpt-4.1-mini');
|
||||
expect(getModelSpy).toHaveBeenCalledWith('gpt-5-mini');
|
||||
expect(getModelSpy).toHaveBeenCalledWith('claude-haiku-4-5-20251001');
|
||||
});
|
||||
|
||||
|
|
@ -215,7 +221,7 @@ describe('AiModelRegistryService', () => {
|
|||
jest.spyOn(SERVICE, 'getAvailableModels').mockReturnValue([
|
||||
{
|
||||
modelId: 'fallback-model',
|
||||
provider: ModelProvider.OPENAI_COMPATIBLE,
|
||||
inferenceProvider: InferenceProvider.OPENAI_COMPATIBLE,
|
||||
model: {} as any,
|
||||
},
|
||||
]);
|
||||
|
|
|
|||
|
|
@ -1,7 +1,8 @@
|
|||
export {
|
||||
DEFAULT_FAST_MODEL,
|
||||
DEFAULT_SMART_MODEL,
|
||||
ModelProvider,
|
||||
InferenceProvider,
|
||||
ModelFamily,
|
||||
type AIModelConfig,
|
||||
type ModelId,
|
||||
type SupportedFileType,
|
||||
|
|
@ -9,13 +10,19 @@ export {
|
|||
|
||||
import { type AIModelConfig } from './ai-models-types.const';
|
||||
import { ANTHROPIC_MODELS } from './anthropic-models.const';
|
||||
import { BEDROCK_MODELS } from './bedrock-models.const';
|
||||
import { GOOGLE_MODELS } from './google-models.const';
|
||||
import { GROQ_MODELS } from './groq-models.const';
|
||||
import { MISTRAL_MODELS } from './mistral-models.const';
|
||||
import { OPENAI_MODELS } from './openai-models.const';
|
||||
import { XAI_MODELS } from './xai-models.const';
|
||||
|
||||
export const AI_MODELS: AIModelConfig[] = [
|
||||
...OPENAI_MODELS,
|
||||
...ANTHROPIC_MODELS,
|
||||
...BEDROCK_MODELS,
|
||||
...GOOGLE_MODELS,
|
||||
...XAI_MODELS,
|
||||
...GROQ_MODELS,
|
||||
...MISTRAL_MODELS,
|
||||
];
|
||||
|
|
|
|||
|
|
@ -1,15 +1,64 @@
|
|||
import { type AIModelConfig, ModelProvider } from './ai-models-types.const';
|
||||
import {
|
||||
type AIModelConfig,
|
||||
InferenceProvider,
|
||||
ModelFamily,
|
||||
} from './ai-models-types.const';
|
||||
|
||||
export const ANTHROPIC_MODELS: AIModelConfig[] = [
|
||||
// Active models
|
||||
{
|
||||
modelId: 'claude-opus-4-5-20251101',
|
||||
label: 'Claude Opus 4.5',
|
||||
modelId: 'claude-opus-4-6',
|
||||
label: 'Claude Opus 4.6',
|
||||
description:
|
||||
'Most powerful Claude model excelling in complex reasoning, coding, and agentic tasks',
|
||||
provider: ModelProvider.ANTHROPIC,
|
||||
inputCostPer1kTokensInCents: 0.5,
|
||||
outputCostPer1kTokensInCents: 2.5,
|
||||
'Flagship Claude model for software engineering, scientific reasoning, and agent teams',
|
||||
modelFamily: ModelFamily.ANTHROPIC,
|
||||
inferenceProvider: InferenceProvider.ANTHROPIC,
|
||||
inputCostPerMillionTokens: 5.0,
|
||||
outputCostPerMillionTokens: 25.0,
|
||||
cachedInputCostPerMillionTokens: 0.5,
|
||||
cacheCreationCostPerMillionTokens: 6.25,
|
||||
longContextCost: {
|
||||
inputCostPerMillionTokens: 10.0,
|
||||
outputCostPerMillionTokens: 37.5,
|
||||
cachedInputCostPerMillionTokens: 1.0,
|
||||
cacheCreationCostPerMillionTokens: 12.5,
|
||||
thresholdTokens: 200_000,
|
||||
},
|
||||
contextWindowTokens: 1000000,
|
||||
maxOutputTokens: 128000,
|
||||
supportedFileTypes: [
|
||||
'image/png',
|
||||
'image/jpeg',
|
||||
'image/gif',
|
||||
'image/webp',
|
||||
'application/pdf',
|
||||
'text/plain',
|
||||
'text/html',
|
||||
'text/csv',
|
||||
],
|
||||
doesSupportThinking: true,
|
||||
nativeCapabilities: {
|
||||
webSearch: true,
|
||||
},
|
||||
},
|
||||
{
|
||||
modelId: 'claude-sonnet-4-6',
|
||||
label: 'Claude Sonnet 4.6',
|
||||
description:
|
||||
'Most capable Sonnet model with strong coding, computer use, and agent planning',
|
||||
modelFamily: ModelFamily.ANTHROPIC,
|
||||
inferenceProvider: InferenceProvider.ANTHROPIC,
|
||||
inputCostPerMillionTokens: 3.0,
|
||||
outputCostPerMillionTokens: 15.0,
|
||||
cachedInputCostPerMillionTokens: 0.3,
|
||||
cacheCreationCostPerMillionTokens: 3.75,
|
||||
longContextCost: {
|
||||
inputCostPerMillionTokens: 6.0,
|
||||
outputCostPerMillionTokens: 22.5,
|
||||
cachedInputCostPerMillionTokens: 0.6,
|
||||
cacheCreationCostPerMillionTokens: 7.5,
|
||||
thresholdTokens: 200_000,
|
||||
},
|
||||
contextWindowTokens: 200000,
|
||||
maxOutputTokens: 64000,
|
||||
supportedFileTypes: [
|
||||
|
|
@ -31,10 +80,20 @@ export const ANTHROPIC_MODELS: AIModelConfig[] = [
|
|||
modelId: 'claude-sonnet-4-5-20250929',
|
||||
label: 'Claude Sonnet 4.5',
|
||||
description:
|
||||
'Advanced model for coding tasks and complex agent-based workflows with 1M context',
|
||||
provider: ModelProvider.ANTHROPIC,
|
||||
inputCostPer1kTokensInCents: 0.3,
|
||||
outputCostPer1kTokensInCents: 1.5,
|
||||
'Previous gen Sonnet with 1M native context for long-context workflows',
|
||||
modelFamily: ModelFamily.ANTHROPIC,
|
||||
inferenceProvider: InferenceProvider.ANTHROPIC,
|
||||
inputCostPerMillionTokens: 3.0,
|
||||
outputCostPerMillionTokens: 15.0,
|
||||
cachedInputCostPerMillionTokens: 0.3,
|
||||
cacheCreationCostPerMillionTokens: 3.75,
|
||||
longContextCost: {
|
||||
inputCostPerMillionTokens: 6.0,
|
||||
outputCostPerMillionTokens: 22.5,
|
||||
cachedInputCostPerMillionTokens: 0.6,
|
||||
cacheCreationCostPerMillionTokens: 7.5,
|
||||
thresholdTokens: 200_000,
|
||||
},
|
||||
contextWindowTokens: 1000000,
|
||||
maxOutputTokens: 64000,
|
||||
supportedFileTypes: [
|
||||
|
|
@ -55,11 +114,13 @@ export const ANTHROPIC_MODELS: AIModelConfig[] = [
|
|||
{
|
||||
modelId: 'claude-haiku-4-5-20251001',
|
||||
label: 'Claude Haiku 4.5',
|
||||
description:
|
||||
'Fast and cost-effective model optimized for high-speed processing',
|
||||
provider: ModelProvider.ANTHROPIC,
|
||||
inputCostPer1kTokensInCents: 0.1,
|
||||
outputCostPer1kTokensInCents: 0.5,
|
||||
description: 'Fast and cost-effective model for high-speed processing',
|
||||
modelFamily: ModelFamily.ANTHROPIC,
|
||||
inferenceProvider: InferenceProvider.ANTHROPIC,
|
||||
inputCostPerMillionTokens: 1.0,
|
||||
outputCostPerMillionTokens: 5.0,
|
||||
cachedInputCostPerMillionTokens: 0.1,
|
||||
cacheCreationCostPerMillionTokens: 1.25,
|
||||
contextWindowTokens: 200000,
|
||||
maxOutputTokens: 64000,
|
||||
supportedFileTypes: [
|
||||
|
|
@ -77,43 +138,27 @@ export const ANTHROPIC_MODELS: AIModelConfig[] = [
|
|||
webSearch: true,
|
||||
},
|
||||
},
|
||||
{
|
||||
modelId: 'claude-3-5-haiku-20241022',
|
||||
label: 'Claude Haiku 3.5',
|
||||
description:
|
||||
'Fast and efficient model optimized for speed and cost-effectiveness',
|
||||
provider: ModelProvider.ANTHROPIC,
|
||||
inputCostPer1kTokensInCents: 0.08,
|
||||
outputCostPer1kTokensInCents: 0.4,
|
||||
contextWindowTokens: 200000,
|
||||
maxOutputTokens: 8192,
|
||||
supportedFileTypes: [
|
||||
'image/png',
|
||||
'image/jpeg',
|
||||
'image/gif',
|
||||
'image/webp',
|
||||
'application/pdf',
|
||||
'text/plain',
|
||||
'text/html',
|
||||
'text/csv',
|
||||
],
|
||||
doesSupportThinking: false,
|
||||
nativeCapabilities: {
|
||||
webSearch: true,
|
||||
},
|
||||
},
|
||||
|
||||
// Deprecated models - kept for backward compatibility with existing agents
|
||||
{
|
||||
modelId: 'claude-opus-4-20250514',
|
||||
label: 'Claude Opus 4',
|
||||
description:
|
||||
'Most powerful Claude model with extended thinking for complex reasoning tasks',
|
||||
provider: ModelProvider.ANTHROPIC,
|
||||
inputCostPer1kTokensInCents: 1.5,
|
||||
outputCostPer1kTokensInCents: 7.5,
|
||||
modelId: 'claude-opus-4-5-20251101',
|
||||
label: 'Claude Opus 4.5',
|
||||
description: 'Previous flagship model superseded by Opus 4.6',
|
||||
modelFamily: ModelFamily.ANTHROPIC,
|
||||
inferenceProvider: InferenceProvider.ANTHROPIC,
|
||||
inputCostPerMillionTokens: 5.0,
|
||||
outputCostPerMillionTokens: 25.0,
|
||||
cachedInputCostPerMillionTokens: 0.5,
|
||||
cacheCreationCostPerMillionTokens: 6.25,
|
||||
longContextCost: {
|
||||
inputCostPerMillionTokens: 10.0,
|
||||
outputCostPerMillionTokens: 37.5,
|
||||
cachedInputCostPerMillionTokens: 1.0,
|
||||
cacheCreationCostPerMillionTokens: 12.5,
|
||||
thresholdTokens: 200_000,
|
||||
},
|
||||
contextWindowTokens: 200000,
|
||||
maxOutputTokens: 8192,
|
||||
maxOutputTokens: 64000,
|
||||
supportedFileTypes: [
|
||||
'image/png',
|
||||
'image/jpeg',
|
||||
|
|
@ -133,11 +178,20 @@ export const ANTHROPIC_MODELS: AIModelConfig[] = [
|
|||
{
|
||||
modelId: 'claude-sonnet-4-20250514',
|
||||
label: 'Claude Sonnet 4',
|
||||
description:
|
||||
'Balanced model with strong performance and extended thinking capabilities',
|
||||
provider: ModelProvider.ANTHROPIC,
|
||||
inputCostPer1kTokensInCents: 0.3,
|
||||
outputCostPer1kTokensInCents: 1.5,
|
||||
description: 'Previous gen Sonnet superseded by Sonnet 4.6',
|
||||
modelFamily: ModelFamily.ANTHROPIC,
|
||||
inferenceProvider: InferenceProvider.ANTHROPIC,
|
||||
inputCostPerMillionTokens: 3.0,
|
||||
outputCostPerMillionTokens: 15.0,
|
||||
cachedInputCostPerMillionTokens: 0.3,
|
||||
cacheCreationCostPerMillionTokens: 3.75,
|
||||
longContextCost: {
|
||||
inputCostPerMillionTokens: 6.0,
|
||||
outputCostPerMillionTokens: 22.5,
|
||||
cachedInputCostPerMillionTokens: 0.6,
|
||||
cacheCreationCostPerMillionTokens: 7.5,
|
||||
thresholdTokens: 200_000,
|
||||
},
|
||||
contextWindowTokens: 200000,
|
||||
maxOutputTokens: 8192,
|
||||
supportedFileTypes: [
|
||||
|
|
@ -156,4 +210,60 @@ export const ANTHROPIC_MODELS: AIModelConfig[] = [
|
|||
},
|
||||
deprecated: true,
|
||||
},
|
||||
{
|
||||
modelId: 'claude-opus-4-20250514',
|
||||
label: 'Claude Opus 4',
|
||||
description: 'Legacy Opus model with extended thinking',
|
||||
modelFamily: ModelFamily.ANTHROPIC,
|
||||
inferenceProvider: InferenceProvider.ANTHROPIC,
|
||||
inputCostPerMillionTokens: 15.0,
|
||||
outputCostPerMillionTokens: 75.0,
|
||||
cachedInputCostPerMillionTokens: 1.5,
|
||||
cacheCreationCostPerMillionTokens: 18.75,
|
||||
contextWindowTokens: 200000,
|
||||
maxOutputTokens: 8192,
|
||||
supportedFileTypes: [
|
||||
'image/png',
|
||||
'image/jpeg',
|
||||
'image/gif',
|
||||
'image/webp',
|
||||
'application/pdf',
|
||||
'text/plain',
|
||||
'text/html',
|
||||
'text/csv',
|
||||
],
|
||||
doesSupportThinking: true,
|
||||
nativeCapabilities: {
|
||||
webSearch: true,
|
||||
},
|
||||
deprecated: true,
|
||||
},
|
||||
{
|
||||
modelId: 'claude-3-5-haiku-20241022',
|
||||
label: 'Claude Haiku 3.5',
|
||||
description: 'Legacy fast model superseded by Haiku 4.5',
|
||||
modelFamily: ModelFamily.ANTHROPIC,
|
||||
inferenceProvider: InferenceProvider.ANTHROPIC,
|
||||
inputCostPerMillionTokens: 0.8,
|
||||
outputCostPerMillionTokens: 4.0,
|
||||
cachedInputCostPerMillionTokens: 0.08,
|
||||
cacheCreationCostPerMillionTokens: 1.0,
|
||||
contextWindowTokens: 200000,
|
||||
maxOutputTokens: 8192,
|
||||
supportedFileTypes: [
|
||||
'image/png',
|
||||
'image/jpeg',
|
||||
'image/gif',
|
||||
'image/webp',
|
||||
'application/pdf',
|
||||
'text/plain',
|
||||
'text/html',
|
||||
'text/csv',
|
||||
],
|
||||
doesSupportThinking: false,
|
||||
nativeCapabilities: {
|
||||
webSearch: true,
|
||||
},
|
||||
deprecated: true,
|
||||
},
|
||||
];
|
||||
|
|
|
|||
|
|
@ -0,0 +1,78 @@
|
|||
import {
|
||||
type AIModelConfig,
|
||||
InferenceProvider,
|
||||
ModelFamily,
|
||||
} from './ai-models-types.const';
|
||||
|
||||
export const BEDROCK_MODELS: AIModelConfig[] = [
|
||||
{
|
||||
modelId: 'anthropic.claude-opus-4-6-v1',
|
||||
label: 'Claude Opus 4.6 (Bedrock)',
|
||||
description:
|
||||
'Flagship Claude model via AWS Bedrock for enterprise deployments',
|
||||
modelFamily: ModelFamily.ANTHROPIC,
|
||||
inferenceProvider: InferenceProvider.BEDROCK,
|
||||
inputCostPerMillionTokens: 5.0,
|
||||
outputCostPerMillionTokens: 25.0,
|
||||
cachedInputCostPerMillionTokens: 0.5,
|
||||
cacheCreationCostPerMillionTokens: 6.25,
|
||||
longContextCost: {
|
||||
inputCostPerMillionTokens: 10.0,
|
||||
outputCostPerMillionTokens: 37.5,
|
||||
cachedInputCostPerMillionTokens: 1.0,
|
||||
cacheCreationCostPerMillionTokens: 12.5,
|
||||
thresholdTokens: 200_000,
|
||||
},
|
||||
contextWindowTokens: 1000000,
|
||||
maxOutputTokens: 128000,
|
||||
supportedFileTypes: [
|
||||
'image/png',
|
||||
'image/jpeg',
|
||||
'image/gif',
|
||||
'image/webp',
|
||||
'application/pdf',
|
||||
'text/plain',
|
||||
'text/html',
|
||||
'text/csv',
|
||||
],
|
||||
doesSupportThinking: true,
|
||||
nativeCapabilities: {
|
||||
webSearch: true,
|
||||
},
|
||||
},
|
||||
{
|
||||
modelId: 'anthropic.claude-sonnet-4-6',
|
||||
label: 'Claude Sonnet 4.6 (Bedrock)',
|
||||
description:
|
||||
'Balanced Claude model via AWS Bedrock with strong coding and agent planning',
|
||||
modelFamily: ModelFamily.ANTHROPIC,
|
||||
inferenceProvider: InferenceProvider.BEDROCK,
|
||||
inputCostPerMillionTokens: 3.0,
|
||||
outputCostPerMillionTokens: 15.0,
|
||||
cachedInputCostPerMillionTokens: 0.3,
|
||||
cacheCreationCostPerMillionTokens: 3.75,
|
||||
longContextCost: {
|
||||
inputCostPerMillionTokens: 6.0,
|
||||
outputCostPerMillionTokens: 22.5,
|
||||
cachedInputCostPerMillionTokens: 0.6,
|
||||
cacheCreationCostPerMillionTokens: 7.5,
|
||||
thresholdTokens: 200_000,
|
||||
},
|
||||
contextWindowTokens: 200000,
|
||||
maxOutputTokens: 64000,
|
||||
supportedFileTypes: [
|
||||
'image/png',
|
||||
'image/jpeg',
|
||||
'image/gif',
|
||||
'image/webp',
|
||||
'application/pdf',
|
||||
'text/plain',
|
||||
'text/html',
|
||||
'text/csv',
|
||||
],
|
||||
doesSupportThinking: true,
|
||||
nativeCapabilities: {
|
||||
webSearch: true,
|
||||
},
|
||||
},
|
||||
];
|
||||
|
|
@ -0,0 +1,81 @@
|
|||
import {
|
||||
type AIModelConfig,
|
||||
InferenceProvider,
|
||||
ModelFamily,
|
||||
} from './ai-models-types.const';
|
||||
|
||||
export const GOOGLE_MODELS: AIModelConfig[] = [
|
||||
// Active models
|
||||
{
|
||||
modelId: 'gemini-3.1-pro-preview',
|
||||
label: 'Gemini 3.1 Pro',
|
||||
description:
|
||||
'Most advanced Gemini model for reasoning, coding, and agentic workflows',
|
||||
modelFamily: ModelFamily.GOOGLE,
|
||||
inferenceProvider: InferenceProvider.GOOGLE,
|
||||
inputCostPerMillionTokens: 2.0,
|
||||
outputCostPerMillionTokens: 12.0,
|
||||
cachedInputCostPerMillionTokens: 0.2,
|
||||
longContextCost: {
|
||||
inputCostPerMillionTokens: 4.0,
|
||||
outputCostPerMillionTokens: 18.0,
|
||||
cachedInputCostPerMillionTokens: 0.4,
|
||||
thresholdTokens: 200_000,
|
||||
},
|
||||
contextWindowTokens: 1048576,
|
||||
maxOutputTokens: 65536,
|
||||
supportedFileTypes: ['image/png', 'image/jpeg', 'image/gif', 'image/webp'],
|
||||
doesSupportThinking: true,
|
||||
},
|
||||
{
|
||||
modelId: 'gemini-3-flash-preview',
|
||||
label: 'Gemini 3 Flash',
|
||||
description: 'Fast frontier-class Gemini model at low cost with 1M context',
|
||||
modelFamily: ModelFamily.GOOGLE,
|
||||
inferenceProvider: InferenceProvider.GOOGLE,
|
||||
inputCostPerMillionTokens: 0.5,
|
||||
outputCostPerMillionTokens: 3.0,
|
||||
cachedInputCostPerMillionTokens: 0.05,
|
||||
contextWindowTokens: 1048576,
|
||||
maxOutputTokens: 65536,
|
||||
supportedFileTypes: ['image/png', 'image/jpeg', 'image/gif', 'image/webp'],
|
||||
doesSupportThinking: true,
|
||||
},
|
||||
|
||||
// Deprecated models - kept for backward compatibility with existing agents
|
||||
{
|
||||
modelId: 'gemini-2.5-pro',
|
||||
label: 'Gemini 2.5 Pro',
|
||||
description: 'Previous gen Gemini Pro superseded by 3.1 Pro',
|
||||
modelFamily: ModelFamily.GOOGLE,
|
||||
inferenceProvider: InferenceProvider.GOOGLE,
|
||||
inputCostPerMillionTokens: 1.25,
|
||||
outputCostPerMillionTokens: 10.0,
|
||||
cachedInputCostPerMillionTokens: 0.315,
|
||||
longContextCost: {
|
||||
inputCostPerMillionTokens: 2.5,
|
||||
outputCostPerMillionTokens: 15.0,
|
||||
thresholdTokens: 200_000,
|
||||
},
|
||||
contextWindowTokens: 1048576,
|
||||
maxOutputTokens: 65536,
|
||||
supportedFileTypes: ['image/png', 'image/jpeg', 'image/gif', 'image/webp'],
|
||||
doesSupportThinking: true,
|
||||
deprecated: true,
|
||||
},
|
||||
{
|
||||
modelId: 'gemini-2.5-flash',
|
||||
label: 'Gemini 2.5 Flash',
|
||||
description: 'Previous gen Flash superseded by Gemini 3 Flash',
|
||||
modelFamily: ModelFamily.GOOGLE,
|
||||
inferenceProvider: InferenceProvider.GOOGLE,
|
||||
inputCostPerMillionTokens: 0.3,
|
||||
outputCostPerMillionTokens: 2.5,
|
||||
cachedInputCostPerMillionTokens: 0.075,
|
||||
contextWindowTokens: 1048576,
|
||||
maxOutputTokens: 65536,
|
||||
supportedFileTypes: ['image/png', 'image/jpeg', 'image/gif', 'image/webp'],
|
||||
doesSupportThinking: true,
|
||||
deprecated: true,
|
||||
},
|
||||
];
|
||||
|
|
@ -1,14 +1,20 @@
|
|||
import { type AIModelConfig, ModelProvider } from './ai-models-types.const';
|
||||
import {
|
||||
type AIModelConfig,
|
||||
InferenceProvider,
|
||||
ModelFamily,
|
||||
} from './ai-models-types.const';
|
||||
|
||||
export const GROQ_MODELS: AIModelConfig[] = [
|
||||
{
|
||||
modelId: 'openai/gpt-oss-120b',
|
||||
label: 'GPT-OSS 120B (Groq)',
|
||||
description:
|
||||
'Large-scale open-source model with browser search, served via Groq inference',
|
||||
provider: ModelProvider.GROQ,
|
||||
inputCostPer1kTokensInCents: 0.059,
|
||||
outputCostPer1kTokensInCents: 0.079,
|
||||
'Large-scale open-source model with ultra-fast inference via Groq',
|
||||
modelFamily: ModelFamily.OPENAI,
|
||||
inferenceProvider: InferenceProvider.GROQ,
|
||||
inputCostPerMillionTokens: 0.15,
|
||||
outputCostPerMillionTokens: 0.6,
|
||||
cachedInputCostPerMillionTokens: 0.075,
|
||||
contextWindowTokens: 128000,
|
||||
maxOutputTokens: 16384,
|
||||
},
|
||||
|
|
|
|||
|
|
@ -0,0 +1,20 @@
|
|||
import {
|
||||
type AIModelConfig,
|
||||
InferenceProvider,
|
||||
ModelFamily,
|
||||
} from './ai-models-types.const';
|
||||
|
||||
export const MISTRAL_MODELS: AIModelConfig[] = [
|
||||
{
|
||||
modelId: 'mistral-large-latest',
|
||||
label: 'Mistral Large',
|
||||
description:
|
||||
'Flagship Mistral model with strong reasoning and 256K context',
|
||||
modelFamily: ModelFamily.MISTRAL,
|
||||
inferenceProvider: InferenceProvider.MISTRAL,
|
||||
inputCostPerMillionTokens: 0.5,
|
||||
outputCostPerMillionTokens: 1.5,
|
||||
contextWindowTokens: 256000,
|
||||
maxOutputTokens: 8192,
|
||||
},
|
||||
];
|
||||
|
|
@ -1,15 +1,54 @@
|
|||
import { type AIModelConfig, ModelProvider } from './ai-models-types.const';
|
||||
import {
|
||||
type AIModelConfig,
|
||||
InferenceProvider,
|
||||
ModelFamily,
|
||||
} from './ai-models-types.const';
|
||||
|
||||
export const OPENAI_MODELS: AIModelConfig[] = [
|
||||
// Active models
|
||||
{
|
||||
modelId: 'gpt-5.2',
|
||||
label: 'GPT-5.2',
|
||||
description:
|
||||
'Most advanced OpenAI model for coding, agentic tasks, and complex reasoning',
|
||||
modelFamily: ModelFamily.OPENAI,
|
||||
inferenceProvider: InferenceProvider.OPENAI,
|
||||
inputCostPerMillionTokens: 1.75,
|
||||
outputCostPerMillionTokens: 14.0,
|
||||
cachedInputCostPerMillionTokens: 0.175,
|
||||
contextWindowTokens: 400000,
|
||||
maxOutputTokens: 128000,
|
||||
supportedFileTypes: ['image/png', 'image/jpeg', 'image/gif', 'image/webp'],
|
||||
doesSupportThinking: true,
|
||||
nativeCapabilities: {
|
||||
webSearch: true,
|
||||
},
|
||||
},
|
||||
{
|
||||
modelId: 'gpt-5-mini',
|
||||
label: 'GPT-5 Mini',
|
||||
description: 'Fast and cost-efficient GPT-5 variant for well-defined tasks',
|
||||
modelFamily: ModelFamily.OPENAI,
|
||||
inferenceProvider: InferenceProvider.OPENAI,
|
||||
inputCostPerMillionTokens: 0.25,
|
||||
outputCostPerMillionTokens: 2.0,
|
||||
cachedInputCostPerMillionTokens: 0.025,
|
||||
contextWindowTokens: 128000,
|
||||
maxOutputTokens: 32768,
|
||||
supportedFileTypes: ['image/png', 'image/jpeg', 'image/gif', 'image/webp'],
|
||||
nativeCapabilities: {
|
||||
webSearch: true,
|
||||
},
|
||||
},
|
||||
{
|
||||
modelId: 'gpt-4.1',
|
||||
label: 'GPT-4.1',
|
||||
description:
|
||||
'Advanced model excelling in coding, instruction following, and long-context comprehension',
|
||||
provider: ModelProvider.OPENAI,
|
||||
inputCostPer1kTokensInCents: 0.2,
|
||||
outputCostPer1kTokensInCents: 0.8,
|
||||
description: 'Strong model with 1M context, cost-effective output pricing',
|
||||
modelFamily: ModelFamily.OPENAI,
|
||||
inferenceProvider: InferenceProvider.OPENAI,
|
||||
inputCostPerMillionTokens: 2.0,
|
||||
outputCostPerMillionTokens: 8.0,
|
||||
cachedInputCostPerMillionTokens: 0.5,
|
||||
contextWindowTokens: 1047576,
|
||||
maxOutputTokens: 32768,
|
||||
supportedFileTypes: ['image/png', 'image/jpeg', 'image/gif', 'image/webp'],
|
||||
|
|
@ -20,11 +59,12 @@ export const OPENAI_MODELS: AIModelConfig[] = [
|
|||
{
|
||||
modelId: 'gpt-4.1-mini',
|
||||
label: 'GPT-4.1 Mini',
|
||||
description:
|
||||
'Fast and cost-efficient version of GPT-4.1 optimized for low latency',
|
||||
provider: ModelProvider.OPENAI,
|
||||
inputCostPer1kTokensInCents: 0.04,
|
||||
outputCostPer1kTokensInCents: 0.16,
|
||||
description: 'Budget-friendly model with 1M context for lightweight tasks',
|
||||
modelFamily: ModelFamily.OPENAI,
|
||||
inferenceProvider: InferenceProvider.OPENAI,
|
||||
inputCostPerMillionTokens: 0.4,
|
||||
outputCostPerMillionTokens: 1.6,
|
||||
cachedInputCostPerMillionTokens: 0.1,
|
||||
contextWindowTokens: 1047576,
|
||||
maxOutputTokens: 32768,
|
||||
supportedFileTypes: ['image/png', 'image/jpeg', 'image/gif', 'image/webp'],
|
||||
|
|
@ -32,14 +72,18 @@ export const OPENAI_MODELS: AIModelConfig[] = [
|
|||
webSearch: true,
|
||||
},
|
||||
},
|
||||
|
||||
// Deprecated models - kept for backward compatibility with existing agents
|
||||
{
|
||||
modelId: 'o3',
|
||||
label: 'o3',
|
||||
description:
|
||||
'Powerful reasoning model excelling in complex queries, coding, math, and science',
|
||||
provider: ModelProvider.OPENAI,
|
||||
inputCostPer1kTokensInCents: 0.2,
|
||||
outputCostPer1kTokensInCents: 0.8,
|
||||
'Reasoning model for complex queries, coding, math, and science',
|
||||
modelFamily: ModelFamily.OPENAI,
|
||||
inferenceProvider: InferenceProvider.OPENAI,
|
||||
inputCostPerMillionTokens: 2.0,
|
||||
outputCostPerMillionTokens: 8.0,
|
||||
cachedInputCostPerMillionTokens: 0.5,
|
||||
contextWindowTokens: 200000,
|
||||
maxOutputTokens: 100000,
|
||||
supportedFileTypes: ['image/png', 'image/jpeg', 'image/gif', 'image/webp'],
|
||||
|
|
@ -47,15 +91,18 @@ export const OPENAI_MODELS: AIModelConfig[] = [
|
|||
nativeCapabilities: {
|
||||
webSearch: true,
|
||||
},
|
||||
deprecated: true,
|
||||
},
|
||||
{
|
||||
modelId: 'o4-mini',
|
||||
label: 'o4-mini',
|
||||
description:
|
||||
'Cost-effective reasoning model excelling in math, coding, and visual tasks',
|
||||
provider: ModelProvider.OPENAI,
|
||||
inputCostPer1kTokensInCents: 0.11,
|
||||
outputCostPer1kTokensInCents: 0.44,
|
||||
'Cost-effective reasoning model for math, coding, and visual tasks',
|
||||
modelFamily: ModelFamily.OPENAI,
|
||||
inferenceProvider: InferenceProvider.OPENAI,
|
||||
inputCostPerMillionTokens: 1.1,
|
||||
outputCostPerMillionTokens: 4.4,
|
||||
cachedInputCostPerMillionTokens: 0.275,
|
||||
contextWindowTokens: 200000,
|
||||
maxOutputTokens: 100000,
|
||||
supportedFileTypes: ['image/png', 'image/jpeg', 'image/gif', 'image/webp'],
|
||||
|
|
@ -63,17 +110,18 @@ export const OPENAI_MODELS: AIModelConfig[] = [
|
|||
nativeCapabilities: {
|
||||
webSearch: true,
|
||||
},
|
||||
deprecated: true,
|
||||
},
|
||||
|
||||
// Deprecated models - kept for backward compatibility with existing agents
|
||||
{
|
||||
modelId: 'gpt-4o',
|
||||
label: 'GPT-4o',
|
||||
description:
|
||||
'Most advanced multimodal model with strong reasoning, vision, and coding capabilities',
|
||||
provider: ModelProvider.OPENAI,
|
||||
inputCostPer1kTokensInCents: 0.25,
|
||||
outputCostPer1kTokensInCents: 1.0,
|
||||
'Previous generation multimodal model with strong reasoning and vision',
|
||||
modelFamily: ModelFamily.OPENAI,
|
||||
inferenceProvider: InferenceProvider.OPENAI,
|
||||
inputCostPerMillionTokens: 2.5,
|
||||
outputCostPerMillionTokens: 10.0,
|
||||
cachedInputCostPerMillionTokens: 1.25,
|
||||
contextWindowTokens: 128000,
|
||||
maxOutputTokens: 16384,
|
||||
supportedFileTypes: ['image/png', 'image/jpeg', 'image/gif', 'image/webp'],
|
||||
|
|
@ -85,11 +133,12 @@ export const OPENAI_MODELS: AIModelConfig[] = [
|
|||
{
|
||||
modelId: 'gpt-4o-mini',
|
||||
label: 'GPT-4o Mini',
|
||||
description:
|
||||
'Fast and cost-efficient model for lightweight tasks and high-volume operations',
|
||||
provider: ModelProvider.OPENAI,
|
||||
inputCostPer1kTokensInCents: 0.015,
|
||||
outputCostPer1kTokensInCents: 0.06,
|
||||
description: 'Previous generation fast model for lightweight tasks',
|
||||
modelFamily: ModelFamily.OPENAI,
|
||||
inferenceProvider: InferenceProvider.OPENAI,
|
||||
inputCostPerMillionTokens: 0.15,
|
||||
outputCostPerMillionTokens: 0.6,
|
||||
cachedInputCostPerMillionTokens: 0.075,
|
||||
contextWindowTokens: 128000,
|
||||
maxOutputTokens: 16384,
|
||||
supportedFileTypes: ['image/png', 'image/jpeg', 'image/gif', 'image/webp'],
|
||||
|
|
@ -101,17 +150,14 @@ export const OPENAI_MODELS: AIModelConfig[] = [
|
|||
{
|
||||
modelId: 'gpt-4-turbo',
|
||||
label: 'GPT-4 Turbo',
|
||||
description:
|
||||
'Previous generation high-performance model with vision capabilities',
|
||||
provider: ModelProvider.OPENAI,
|
||||
inputCostPer1kTokensInCents: 1.0,
|
||||
outputCostPer1kTokensInCents: 3.0,
|
||||
description: 'Legacy high-performance model with vision capabilities',
|
||||
modelFamily: ModelFamily.OPENAI,
|
||||
inferenceProvider: InferenceProvider.OPENAI,
|
||||
inputCostPerMillionTokens: 10.0,
|
||||
outputCostPerMillionTokens: 30.0,
|
||||
contextWindowTokens: 128000,
|
||||
maxOutputTokens: 4096,
|
||||
supportedFileTypes: ['image/png', 'image/jpeg', 'image/gif', 'image/webp'],
|
||||
nativeCapabilities: {
|
||||
webSearch: false,
|
||||
},
|
||||
deprecated: true,
|
||||
},
|
||||
];
|
||||
|
|
|
|||
|
|
@ -1,32 +1,21 @@
|
|||
import { type AIModelConfig, ModelProvider } from './ai-models-types.const';
|
||||
import {
|
||||
type AIModelConfig,
|
||||
InferenceProvider,
|
||||
ModelFamily,
|
||||
} from './ai-models-types.const';
|
||||
|
||||
export const XAI_MODELS: AIModelConfig[] = [
|
||||
// Active models
|
||||
{
|
||||
modelId: 'grok-4-1-fast-reasoning',
|
||||
label: 'Grok 4.1 Fast',
|
||||
description:
|
||||
'Next-generation tool-calling agent with 2M context for advanced agentic workflows',
|
||||
provider: ModelProvider.XAI,
|
||||
inputCostPer1kTokensInCents: 0.02,
|
||||
outputCostPer1kTokensInCents: 0.05,
|
||||
contextWindowTokens: 2000000,
|
||||
maxOutputTokens: 8192,
|
||||
supportedFileTypes: ['image/png', 'image/jpeg', 'image/gif', 'image/webp'],
|
||||
doesSupportThinking: true,
|
||||
nativeCapabilities: {
|
||||
webSearch: true,
|
||||
twitterSearch: true,
|
||||
},
|
||||
},
|
||||
{
|
||||
modelId: 'grok-4',
|
||||
label: 'Grok-4',
|
||||
description:
|
||||
'Most capable Grok model with enhanced reasoning, web and Twitter search',
|
||||
provider: ModelProvider.XAI,
|
||||
inputCostPer1kTokensInCents: 0.3,
|
||||
outputCostPer1kTokensInCents: 1.5,
|
||||
modelFamily: ModelFamily.XAI,
|
||||
inferenceProvider: InferenceProvider.XAI,
|
||||
inputCostPerMillionTokens: 3.0,
|
||||
outputCostPerMillionTokens: 15.0,
|
||||
cachedInputCostPerMillionTokens: 0.75,
|
||||
contextWindowTokens: 256000,
|
||||
maxOutputTokens: 8192,
|
||||
supportedFileTypes: ['image/png', 'image/jpeg', 'image/gif', 'image/webp'],
|
||||
|
|
@ -35,14 +24,37 @@ export const XAI_MODELS: AIModelConfig[] = [
|
|||
twitterSearch: true,
|
||||
},
|
||||
},
|
||||
{
|
||||
modelId: 'grok-4-1-fast-reasoning',
|
||||
label: 'Grok 4.1 Fast',
|
||||
description:
|
||||
'Next-generation tool-calling agent with 2M context for advanced agentic workflows',
|
||||
modelFamily: ModelFamily.XAI,
|
||||
inferenceProvider: InferenceProvider.XAI,
|
||||
inputCostPerMillionTokens: 0.2,
|
||||
outputCostPerMillionTokens: 0.5,
|
||||
cachedInputCostPerMillionTokens: 0.05,
|
||||
contextWindowTokens: 2000000,
|
||||
maxOutputTokens: 8192,
|
||||
supportedFileTypes: ['image/png', 'image/jpeg', 'image/gif', 'image/webp'],
|
||||
doesSupportThinking: true,
|
||||
nativeCapabilities: {
|
||||
webSearch: true,
|
||||
twitterSearch: true,
|
||||
},
|
||||
},
|
||||
|
||||
// Deprecated models - kept for backward compatibility with existing agents
|
||||
{
|
||||
modelId: 'grok-3',
|
||||
label: 'Grok-3',
|
||||
description:
|
||||
'Advanced model with web and Twitter search, optimized for real-time information',
|
||||
provider: ModelProvider.XAI,
|
||||
inputCostPer1kTokensInCents: 0.3,
|
||||
outputCostPer1kTokensInCents: 1.5,
|
||||
modelFamily: ModelFamily.XAI,
|
||||
inferenceProvider: InferenceProvider.XAI,
|
||||
inputCostPerMillionTokens: 3.0,
|
||||
outputCostPerMillionTokens: 15.0,
|
||||
cachedInputCostPerMillionTokens: 0.75,
|
||||
contextWindowTokens: 131072,
|
||||
maxOutputTokens: 8192,
|
||||
supportedFileTypes: ['image/png', 'image/jpeg', 'image/gif', 'image/webp'],
|
||||
|
|
@ -50,15 +62,18 @@ export const XAI_MODELS: AIModelConfig[] = [
|
|||
webSearch: true,
|
||||
twitterSearch: true,
|
||||
},
|
||||
deprecated: true,
|
||||
},
|
||||
{
|
||||
modelId: 'grok-3-mini',
|
||||
label: 'Grok-3 Mini',
|
||||
description:
|
||||
'Lightweight model with web and Twitter search for fast, cost-effective operations',
|
||||
provider: ModelProvider.XAI,
|
||||
inputCostPer1kTokensInCents: 0.03,
|
||||
outputCostPer1kTokensInCents: 0.05,
|
||||
modelFamily: ModelFamily.XAI,
|
||||
inferenceProvider: InferenceProvider.XAI,
|
||||
inputCostPerMillionTokens: 0.3,
|
||||
outputCostPerMillionTokens: 0.5,
|
||||
cachedInputCostPerMillionTokens: 0.07,
|
||||
contextWindowTokens: 131072,
|
||||
maxOutputTokens: 8192,
|
||||
supportedFileTypes: ['image/png', 'image/jpeg', 'image/gif', 'image/webp'],
|
||||
|
|
@ -66,5 +81,6 @@ export const XAI_MODELS: AIModelConfig[] = [
|
|||
webSearch: true,
|
||||
twitterSearch: true,
|
||||
},
|
||||
deprecated: true,
|
||||
},
|
||||
];
|
||||
|
|
|
|||
|
|
@ -6,23 +6,30 @@ import { ProviderOptions } from '@ai-sdk/provider-utils';
|
|||
import { ToolSet } from 'ai';
|
||||
|
||||
import { AGENT_CONFIG } from 'src/engine/metadata-modules/ai/ai-agent/constants/agent-config.const';
|
||||
import { ModelProvider } from 'src/engine/metadata-modules/ai/ai-models/constants/ai-models.const';
|
||||
import { RegisteredAIModel } from 'src/engine/metadata-modules/ai/ai-models/services/ai-model-registry.service';
|
||||
import { InferenceProvider } from 'src/engine/metadata-modules/ai/ai-models/constants/ai-models.const';
|
||||
import {
|
||||
AiModelRegistryService,
|
||||
RegisteredAIModel,
|
||||
} from 'src/engine/metadata-modules/ai/ai-models/services/ai-model-registry.service';
|
||||
import { FlatAgentWithRoleId } from 'src/engine/metadata-modules/flat-agent/types/flat-agent.type';
|
||||
|
||||
@Injectable()
|
||||
export class AgentModelConfigService {
|
||||
constructor() {}
|
||||
constructor(
|
||||
private readonly aiModelRegistryService: AiModelRegistryService,
|
||||
) {}
|
||||
|
||||
getProviderOptions(
|
||||
model: RegisteredAIModel,
|
||||
agent: FlatAgentWithRoleId,
|
||||
): ProviderOptions {
|
||||
switch (model.provider) {
|
||||
case ModelProvider.XAI:
|
||||
switch (model.inferenceProvider) {
|
||||
case InferenceProvider.XAI:
|
||||
return this.getXaiProviderOptions(agent);
|
||||
case ModelProvider.ANTHROPIC:
|
||||
case InferenceProvider.ANTHROPIC:
|
||||
return this.getAnthropicProviderOptions(model);
|
||||
case InferenceProvider.BEDROCK:
|
||||
return this.getBedrockProviderOptions(model);
|
||||
default:
|
||||
return {};
|
||||
}
|
||||
|
|
@ -38,13 +45,25 @@ export class AgentModelConfigService {
|
|||
return tools;
|
||||
}
|
||||
|
||||
switch (model.provider) {
|
||||
case ModelProvider.ANTHROPIC:
|
||||
switch (model.inferenceProvider) {
|
||||
case InferenceProvider.ANTHROPIC:
|
||||
if (agent.modelConfiguration.webSearch?.enabled) {
|
||||
tools.web_search = anthropic.tools.webSearch_20250305();
|
||||
}
|
||||
break;
|
||||
case ModelProvider.OPENAI:
|
||||
case InferenceProvider.BEDROCK: {
|
||||
if (agent.modelConfiguration.webSearch?.enabled) {
|
||||
const bedrockProvider =
|
||||
this.aiModelRegistryService.getBedrockProvider();
|
||||
|
||||
if (bedrockProvider) {
|
||||
tools.web_search =
|
||||
bedrockProvider.tools.webSearch_20250305() as ToolSet[string];
|
||||
}
|
||||
}
|
||||
break;
|
||||
}
|
||||
case InferenceProvider.OPENAI:
|
||||
if (agent.modelConfiguration.webSearch?.enabled) {
|
||||
tools.web_search = openai.tools.webSearch();
|
||||
}
|
||||
|
|
@ -99,4 +118,19 @@ export class AgentModelConfigService {
|
|||
},
|
||||
};
|
||||
}
|
||||
|
||||
private getBedrockProviderOptions(model: RegisteredAIModel): ProviderOptions {
|
||||
if (!model.doesSupportThinking) {
|
||||
return {};
|
||||
}
|
||||
|
||||
return {
|
||||
bedrock: {
|
||||
thinking: {
|
||||
type: 'enabled',
|
||||
budgetTokens: AGENT_CONFIG.REASONING_BUDGET_TOKENS,
|
||||
},
|
||||
},
|
||||
};
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -1,7 +1,13 @@
|
|||
import { Injectable } from '@nestjs/common';
|
||||
|
||||
import {
|
||||
createAmazonBedrock,
|
||||
type AmazonBedrockProvider,
|
||||
} from '@ai-sdk/amazon-bedrock';
|
||||
import { anthropic } from '@ai-sdk/anthropic';
|
||||
import { google } from '@ai-sdk/google';
|
||||
import { groq } from '@ai-sdk/groq';
|
||||
import { mistral } from '@ai-sdk/mistral';
|
||||
import { createOpenAI, openai } from '@ai-sdk/openai';
|
||||
import { xai } from '@ai-sdk/xai';
|
||||
import { type LanguageModel } from 'ai';
|
||||
|
|
@ -15,17 +21,21 @@ import {
|
|||
AI_MODELS,
|
||||
DEFAULT_FAST_MODEL,
|
||||
DEFAULT_SMART_MODEL,
|
||||
ModelProvider,
|
||||
InferenceProvider,
|
||||
ModelFamily,
|
||||
type AIModelConfig,
|
||||
} from 'src/engine/metadata-modules/ai/ai-models/constants/ai-models.const';
|
||||
import { ANTHROPIC_MODELS } from 'src/engine/metadata-modules/ai/ai-models/constants/anthropic-models.const';
|
||||
import { BEDROCK_MODELS } from 'src/engine/metadata-modules/ai/ai-models/constants/bedrock-models.const';
|
||||
import { GOOGLE_MODELS } from 'src/engine/metadata-modules/ai/ai-models/constants/google-models.const';
|
||||
import { GROQ_MODELS } from 'src/engine/metadata-modules/ai/ai-models/constants/groq-models.const';
|
||||
import { MISTRAL_MODELS } from 'src/engine/metadata-modules/ai/ai-models/constants/mistral-models.const';
|
||||
import { OPENAI_MODELS } from 'src/engine/metadata-modules/ai/ai-models/constants/openai-models.const';
|
||||
import { XAI_MODELS } from 'src/engine/metadata-modules/ai/ai-models/constants/xai-models.const';
|
||||
|
||||
export interface RegisteredAIModel {
|
||||
modelId: string;
|
||||
provider: ModelProvider;
|
||||
inferenceProvider: InferenceProvider;
|
||||
model: LanguageModel;
|
||||
doesSupportThinking?: boolean;
|
||||
}
|
||||
|
|
@ -33,13 +43,19 @@ export interface RegisteredAIModel {
|
|||
@Injectable()
|
||||
export class AiModelRegistryService {
|
||||
private modelRegistry: Map<string, RegisteredAIModel> = new Map();
|
||||
private bedrockProvider: AmazonBedrockProvider | null = null;
|
||||
|
||||
constructor(private twentyConfigService: TwentyConfigService) {
|
||||
this.buildModelRegistry();
|
||||
}
|
||||
|
||||
getBedrockProvider(): AmazonBedrockProvider | null {
|
||||
return this.bedrockProvider;
|
||||
}
|
||||
|
||||
private buildModelRegistry(): void {
|
||||
this.modelRegistry.clear();
|
||||
this.bedrockProvider = null;
|
||||
|
||||
const openaiApiKey = this.twentyConfigService.get('OPENAI_API_KEY');
|
||||
|
||||
|
|
@ -65,6 +81,24 @@ export class AiModelRegistryService {
|
|||
this.registerGroqModels();
|
||||
}
|
||||
|
||||
const googleApiKey = this.twentyConfigService.get('GOOGLE_API_KEY');
|
||||
|
||||
if (googleApiKey) {
|
||||
this.registerGoogleModels();
|
||||
}
|
||||
|
||||
const mistralApiKey = this.twentyConfigService.get('MISTRAL_API_KEY');
|
||||
|
||||
if (mistralApiKey) {
|
||||
this.registerMistralModels();
|
||||
}
|
||||
|
||||
const bedrockRegion = this.twentyConfigService.get('AWS_BEDROCK_REGION');
|
||||
|
||||
if (bedrockRegion) {
|
||||
this.registerBedrockModels(bedrockRegion);
|
||||
}
|
||||
|
||||
const openaiCompatibleBaseUrl = this.twentyConfigService.get(
|
||||
'OPENAI_COMPATIBLE_BASE_URL',
|
||||
);
|
||||
|
|
@ -84,7 +118,7 @@ export class AiModelRegistryService {
|
|||
OPENAI_MODELS.forEach((modelConfig) => {
|
||||
this.modelRegistry.set(modelConfig.modelId, {
|
||||
modelId: modelConfig.modelId,
|
||||
provider: ModelProvider.OPENAI,
|
||||
inferenceProvider: InferenceProvider.OPENAI,
|
||||
model: openai(modelConfig.modelId),
|
||||
doesSupportThinking: modelConfig.doesSupportThinking,
|
||||
});
|
||||
|
|
@ -95,7 +129,7 @@ export class AiModelRegistryService {
|
|||
ANTHROPIC_MODELS.forEach((modelConfig) => {
|
||||
this.modelRegistry.set(modelConfig.modelId, {
|
||||
modelId: modelConfig.modelId,
|
||||
provider: ModelProvider.ANTHROPIC,
|
||||
inferenceProvider: InferenceProvider.ANTHROPIC,
|
||||
model: anthropic(modelConfig.modelId),
|
||||
doesSupportThinking: modelConfig.doesSupportThinking,
|
||||
});
|
||||
|
|
@ -106,7 +140,7 @@ export class AiModelRegistryService {
|
|||
XAI_MODELS.forEach((modelConfig) => {
|
||||
this.modelRegistry.set(modelConfig.modelId, {
|
||||
modelId: modelConfig.modelId,
|
||||
provider: ModelProvider.XAI,
|
||||
inferenceProvider: InferenceProvider.XAI,
|
||||
model: xai(modelConfig.modelId),
|
||||
doesSupportThinking: modelConfig.doesSupportThinking,
|
||||
});
|
||||
|
|
@ -117,13 +151,63 @@ export class AiModelRegistryService {
|
|||
GROQ_MODELS.forEach((modelConfig) => {
|
||||
this.modelRegistry.set(modelConfig.modelId, {
|
||||
modelId: modelConfig.modelId,
|
||||
provider: ModelProvider.GROQ,
|
||||
inferenceProvider: InferenceProvider.GROQ,
|
||||
model: groq(modelConfig.modelId),
|
||||
doesSupportThinking: modelConfig.doesSupportThinking,
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
private registerGoogleModels(): void {
|
||||
GOOGLE_MODELS.forEach((modelConfig) => {
|
||||
this.modelRegistry.set(modelConfig.modelId, {
|
||||
modelId: modelConfig.modelId,
|
||||
inferenceProvider: InferenceProvider.GOOGLE,
|
||||
model: google(modelConfig.modelId),
|
||||
doesSupportThinking: modelConfig.doesSupportThinking,
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
private registerMistralModels(): void {
|
||||
MISTRAL_MODELS.forEach((modelConfig) => {
|
||||
this.modelRegistry.set(modelConfig.modelId, {
|
||||
modelId: modelConfig.modelId,
|
||||
inferenceProvider: InferenceProvider.MISTRAL,
|
||||
model: mistral(modelConfig.modelId),
|
||||
doesSupportThinking: modelConfig.doesSupportThinking,
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
private registerBedrockModels(region: string): void {
|
||||
const accessKeyId = this.twentyConfigService.get(
|
||||
'AWS_BEDROCK_ACCESS_KEY_ID',
|
||||
);
|
||||
const secretAccessKey = this.twentyConfigService.get(
|
||||
'AWS_BEDROCK_SECRET_ACCESS_KEY',
|
||||
);
|
||||
const sessionToken = this.twentyConfigService.get(
|
||||
'AWS_BEDROCK_SESSION_TOKEN',
|
||||
);
|
||||
|
||||
this.bedrockProvider = createAmazonBedrock({
|
||||
region,
|
||||
...(accessKeyId && secretAccessKey
|
||||
? { accessKeyId, secretAccessKey, sessionToken }
|
||||
: {}),
|
||||
});
|
||||
|
||||
BEDROCK_MODELS.forEach((modelConfig) => {
|
||||
this.modelRegistry.set(modelConfig.modelId, {
|
||||
modelId: modelConfig.modelId,
|
||||
inferenceProvider: InferenceProvider.BEDROCK,
|
||||
model: this.bedrockProvider!(modelConfig.modelId),
|
||||
doesSupportThinking: modelConfig.doesSupportThinking,
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
private registerOpenAICompatibleModels(
|
||||
baseUrl: string,
|
||||
modelNamesString: string,
|
||||
|
|
@ -142,7 +226,7 @@ export class AiModelRegistryService {
|
|||
modelNames.forEach((modelId) => {
|
||||
this.modelRegistry.set(modelId, {
|
||||
modelId,
|
||||
provider: ModelProvider.OPENAI_COMPATIBLE,
|
||||
inferenceProvider: InferenceProvider.OPENAI_COMPATIBLE,
|
||||
model: provider(modelId),
|
||||
});
|
||||
});
|
||||
|
|
@ -189,7 +273,7 @@ export class AiModelRegistryService {
|
|||
|
||||
if (!model) {
|
||||
throw new AgentException(
|
||||
'No AI models are available. Please configure at least one AI provider API key (OPENAI_API_KEY, ANTHROPIC_API_KEY, XAI_API_KEY, or GROQ_API_KEY).',
|
||||
'No AI models are available. Please configure at least one AI provider (OPENAI_API_KEY, ANTHROPIC_API_KEY, AWS_BEDROCK_REGION, GOOGLE_API_KEY, XAI_API_KEY, GROQ_API_KEY, or MISTRAL_API_KEY).',
|
||||
AgentExceptionCode.API_KEY_NOT_CONFIGURED,
|
||||
);
|
||||
}
|
||||
|
|
@ -211,7 +295,7 @@ export class AiModelRegistryService {
|
|||
|
||||
if (!model) {
|
||||
throw new AgentException(
|
||||
'No AI models are available. Please configure at least one AI provider API key (OPENAI_API_KEY, ANTHROPIC_API_KEY, XAI_API_KEY, or GROQ_API_KEY).',
|
||||
'No AI models are available. Please configure at least one AI provider (OPENAI_API_KEY, ANTHROPIC_API_KEY, AWS_BEDROCK_REGION, GOOGLE_API_KEY, XAI_API_KEY, GROQ_API_KEY, or MISTRAL_API_KEY).',
|
||||
AgentExceptionCode.API_KEY_NOT_CONFIGURED,
|
||||
);
|
||||
}
|
||||
|
|
@ -221,7 +305,6 @@ export class AiModelRegistryService {
|
|||
|
||||
getEffectiveModelConfig(modelId: string): AIModelConfig {
|
||||
if (modelId === DEFAULT_FAST_MODEL || modelId === DEFAULT_SMART_MODEL) {
|
||||
// getDefaultSpeedModel/getDefaultPerformanceModel will throw AgentException if no models available
|
||||
const defaultModel =
|
||||
modelId === DEFAULT_FAST_MODEL
|
||||
? this.getDefaultSpeedModel()
|
||||
|
|
@ -265,15 +348,29 @@ export class AiModelRegistryService {
|
|||
modelId: registeredModel.modelId,
|
||||
label: registeredModel.modelId,
|
||||
description: `Custom model: ${registeredModel.modelId}`,
|
||||
provider: registeredModel.provider,
|
||||
inputCostPer1kTokensInCents: 0,
|
||||
outputCostPer1kTokensInCents: 0,
|
||||
modelFamily: this.inferModelFamily(registeredModel.inferenceProvider),
|
||||
inferenceProvider: registeredModel.inferenceProvider,
|
||||
inputCostPerMillionTokens: 0,
|
||||
outputCostPerMillionTokens: 0,
|
||||
contextWindowTokens: 128000,
|
||||
maxOutputTokens: 4096,
|
||||
};
|
||||
}
|
||||
|
||||
// Force refresh the registry (useful if config changes)
|
||||
private inferModelFamily(inferenceProvider: InferenceProvider): ModelFamily {
|
||||
const providerToFamily: Partial<Record<InferenceProvider, ModelFamily>> = {
|
||||
[InferenceProvider.OPENAI]: ModelFamily.OPENAI,
|
||||
[InferenceProvider.ANTHROPIC]: ModelFamily.ANTHROPIC,
|
||||
[InferenceProvider.BEDROCK]: ModelFamily.ANTHROPIC,
|
||||
[InferenceProvider.GOOGLE]: ModelFamily.GOOGLE,
|
||||
[InferenceProvider.MISTRAL]: ModelFamily.MISTRAL,
|
||||
[InferenceProvider.XAI]: ModelFamily.XAI,
|
||||
[InferenceProvider.GROQ]: ModelFamily.OPENAI,
|
||||
};
|
||||
|
||||
return providerToFamily[inferenceProvider] ?? ModelFamily.OPENAI;
|
||||
}
|
||||
|
||||
refreshRegistry(): void {
|
||||
this.buildModelRegistry();
|
||||
}
|
||||
|
|
@ -283,7 +380,7 @@ export class AiModelRegistryService {
|
|||
agent?.modelId ?? DEFAULT_SMART_MODEL,
|
||||
);
|
||||
|
||||
await this.validateApiKey(aiModel.provider);
|
||||
await this.validateApiKey(aiModel.inferenceProvider);
|
||||
const registeredModel = this.getModel(aiModel.modelId);
|
||||
|
||||
if (!registeredModel) {
|
||||
|
|
@ -296,23 +393,32 @@ export class AiModelRegistryService {
|
|||
return registeredModel;
|
||||
}
|
||||
|
||||
async validateApiKey(provider: ModelProvider): Promise<void> {
|
||||
async validateApiKey(inferenceProvider: InferenceProvider): Promise<void> {
|
||||
let apiKey: string | undefined;
|
||||
|
||||
switch (provider) {
|
||||
case ModelProvider.OPENAI:
|
||||
switch (inferenceProvider) {
|
||||
case InferenceProvider.OPENAI:
|
||||
apiKey = this.twentyConfigService.get('OPENAI_API_KEY');
|
||||
break;
|
||||
case ModelProvider.ANTHROPIC:
|
||||
case InferenceProvider.ANTHROPIC:
|
||||
apiKey = this.twentyConfigService.get('ANTHROPIC_API_KEY');
|
||||
break;
|
||||
case ModelProvider.XAI:
|
||||
case InferenceProvider.XAI:
|
||||
apiKey = this.twentyConfigService.get('XAI_API_KEY');
|
||||
break;
|
||||
case ModelProvider.GROQ:
|
||||
case InferenceProvider.GROQ:
|
||||
apiKey = this.twentyConfigService.get('GROQ_API_KEY');
|
||||
break;
|
||||
case ModelProvider.OPENAI_COMPATIBLE:
|
||||
case InferenceProvider.GOOGLE:
|
||||
apiKey = this.twentyConfigService.get('GOOGLE_API_KEY');
|
||||
break;
|
||||
case InferenceProvider.MISTRAL:
|
||||
apiKey = this.twentyConfigService.get('MISTRAL_API_KEY');
|
||||
break;
|
||||
case InferenceProvider.BEDROCK:
|
||||
apiKey = this.twentyConfigService.get('AWS_BEDROCK_REGION');
|
||||
break;
|
||||
case InferenceProvider.OPENAI_COMPATIBLE:
|
||||
apiKey = this.twentyConfigService.get('OPENAI_COMPATIBLE_API_KEY');
|
||||
break;
|
||||
default:
|
||||
|
|
@ -321,7 +427,7 @@ export class AiModelRegistryService {
|
|||
|
||||
if (!apiKey) {
|
||||
throw new AgentException(
|
||||
`${provider.toUpperCase()} API key not configured. Please set the appropriate environment variable.`,
|
||||
`${inferenceProvider.toUpperCase()} API key not configured. Please set the appropriate environment variable.`,
|
||||
AgentExceptionCode.API_KEY_NOT_CONFIGURED,
|
||||
);
|
||||
}
|
||||
|
|
|
|||
|
|
@ -78,8 +78,8 @@ export class AiAgentWorkflowAction implements WorkflowAction {
|
|||
const executionContext =
|
||||
await this.workflowExecutionContextService.getExecutionContext(runInfo);
|
||||
|
||||
const { result, usage } = await this.aiAgentExecutionService.executeAgent(
|
||||
{
|
||||
const { result, usage, cacheCreationTokens } =
|
||||
await this.aiAgentExecutionService.executeAgent({
|
||||
agent,
|
||||
userPrompt: resolveInput(prompt, context) as string,
|
||||
actorContext: executionContext.isActingOnBehalfOfUser
|
||||
|
|
@ -87,12 +87,11 @@ export class AiAgentWorkflowAction implements WorkflowAction {
|
|||
: undefined,
|
||||
rolePermissionConfig: executionContext.rolePermissionConfig,
|
||||
authContext: executionContext.authContext,
|
||||
},
|
||||
);
|
||||
});
|
||||
|
||||
await this.aiBillingService.calculateAndBillUsage(
|
||||
agent?.modelId ?? DEFAULT_SMART_MODEL,
|
||||
usage,
|
||||
{ usage, cacheCreationTokens },
|
||||
workspaceId,
|
||||
agent?.id || null,
|
||||
);
|
||||
|
|
|
|||
83
yarn.lock
83
yarn.lock
|
|
@ -24,6 +24,34 @@ __metadata:
|
|||
languageName: node
|
||||
linkType: hard
|
||||
|
||||
"@ai-sdk/amazon-bedrock@npm:^3.0.83":
|
||||
version: 3.0.83
|
||||
resolution: "@ai-sdk/amazon-bedrock@npm:3.0.83"
|
||||
dependencies:
|
||||
"@ai-sdk/anthropic": "npm:2.0.66"
|
||||
"@ai-sdk/provider": "npm:2.0.1"
|
||||
"@ai-sdk/provider-utils": "npm:3.0.21"
|
||||
"@smithy/eventstream-codec": "npm:^4.0.1"
|
||||
"@smithy/util-utf8": "npm:^4.0.0"
|
||||
aws4fetch: "npm:^1.0.20"
|
||||
peerDependencies:
|
||||
zod: ^3.25.76 || ^4.1.8
|
||||
checksum: 10c0/66072ecf1bc3183f6028fe8bf5f99a8d03986bdffc5836b8508193de58df701058bdc98b3724e9dc47ed0a924edc150712b0c8a6595c0f3a52ba4d30b9029b63
|
||||
languageName: node
|
||||
linkType: hard
|
||||
|
||||
"@ai-sdk/anthropic@npm:2.0.66":
|
||||
version: 2.0.66
|
||||
resolution: "@ai-sdk/anthropic@npm:2.0.66"
|
||||
dependencies:
|
||||
"@ai-sdk/provider": "npm:2.0.1"
|
||||
"@ai-sdk/provider-utils": "npm:3.0.21"
|
||||
peerDependencies:
|
||||
zod: ^3.25.76 || ^4.1.8
|
||||
checksum: 10c0/9137e26280efe245986b3a0ea469bb075e46d3e45050faa608b13f289575dd044e5271c56abaad0f9532f543fbe5681d25141674bd5d47fcd5520c5173cd23fe
|
||||
languageName: node
|
||||
linkType: hard
|
||||
|
||||
"@ai-sdk/anthropic@npm:^2.0.17":
|
||||
version: 2.0.17
|
||||
resolution: "@ai-sdk/anthropic@npm:2.0.17"
|
||||
|
|
@ -48,6 +76,18 @@ __metadata:
|
|||
languageName: node
|
||||
linkType: hard
|
||||
|
||||
"@ai-sdk/google@npm:^2.0.54":
|
||||
version: 2.0.54
|
||||
resolution: "@ai-sdk/google@npm:2.0.54"
|
||||
dependencies:
|
||||
"@ai-sdk/provider": "npm:2.0.1"
|
||||
"@ai-sdk/provider-utils": "npm:3.0.21"
|
||||
peerDependencies:
|
||||
zod: ^3.25.76 || ^4.1.8
|
||||
checksum: 10c0/d1f244924b6f0484c2c683b189f4e64c8667814b16291fad12935432e7e89d5921351d69ab1971457fabb51e7239eb2f56a1da6ff2f46a86e4ce23b0bb12f019
|
||||
languageName: node
|
||||
linkType: hard
|
||||
|
||||
"@ai-sdk/groq@npm:^2.0.34":
|
||||
version: 2.0.34
|
||||
resolution: "@ai-sdk/groq@npm:2.0.34"
|
||||
|
|
@ -60,6 +100,18 @@ __metadata:
|
|||
languageName: node
|
||||
linkType: hard
|
||||
|
||||
"@ai-sdk/mistral@npm:^2.0.28":
|
||||
version: 2.0.28
|
||||
resolution: "@ai-sdk/mistral@npm:2.0.28"
|
||||
dependencies:
|
||||
"@ai-sdk/provider": "npm:2.0.1"
|
||||
"@ai-sdk/provider-utils": "npm:3.0.21"
|
||||
peerDependencies:
|
||||
zod: ^3.25.76 || ^4.1.8
|
||||
checksum: 10c0/dd993fe477da8e053c68e162a52f0fcbf7671b2a0f8dd4b9a9db57fe780f17cd7ef2b08512e85b0b97a5622f57e085000c56aab102cf381bba1e0e5043c67306
|
||||
languageName: node
|
||||
linkType: hard
|
||||
|
||||
"@ai-sdk/openai-compatible@npm:1.0.30":
|
||||
version: 1.0.30
|
||||
resolution: "@ai-sdk/openai-compatible@npm:1.0.30"
|
||||
|
|
@ -97,6 +149,19 @@ __metadata:
|
|||
languageName: node
|
||||
linkType: hard
|
||||
|
||||
"@ai-sdk/provider-utils@npm:3.0.21":
|
||||
version: 3.0.21
|
||||
resolution: "@ai-sdk/provider-utils@npm:3.0.21"
|
||||
dependencies:
|
||||
"@ai-sdk/provider": "npm:2.0.1"
|
||||
"@standard-schema/spec": "npm:^1.0.0"
|
||||
eventsource-parser: "npm:^3.0.6"
|
||||
peerDependencies:
|
||||
zod: ^3.25.76 || ^4.1.8
|
||||
checksum: 10c0/272645109b4990c1367d46fd8982ee3436f88f4f5ec96d78f98c928052dcee6e9a7df326558d908d73901a5c0a84b3374c31722bb78579c2efd3417afb2100fb
|
||||
languageName: node
|
||||
linkType: hard
|
||||
|
||||
"@ai-sdk/provider-utils@npm:3.0.9, @ai-sdk/provider-utils@npm:^3.0.9":
|
||||
version: 3.0.9
|
||||
resolution: "@ai-sdk/provider-utils@npm:3.0.9"
|
||||
|
|
@ -20797,7 +20862,7 @@ __metadata:
|
|||
languageName: node
|
||||
linkType: hard
|
||||
|
||||
"@smithy/eventstream-codec@npm:^4.2.8":
|
||||
"@smithy/eventstream-codec@npm:^4.0.1, @smithy/eventstream-codec@npm:^4.2.8":
|
||||
version: 4.2.8
|
||||
resolution: "@smithy/eventstream-codec@npm:4.2.8"
|
||||
dependencies:
|
||||
|
|
@ -21339,7 +21404,7 @@ __metadata:
|
|||
languageName: node
|
||||
linkType: hard
|
||||
|
||||
"@smithy/util-utf8@npm:^4.2.0":
|
||||
"@smithy/util-utf8@npm:^4.0.0, @smithy/util-utf8@npm:^4.2.0":
|
||||
version: 4.2.0
|
||||
resolution: "@smithy/util-utf8@npm:4.2.0"
|
||||
dependencies:
|
||||
|
|
@ -24162,7 +24227,7 @@ __metadata:
|
|||
languageName: node
|
||||
linkType: hard
|
||||
|
||||
"@types/lodash.kebabcase@npm:^4.1.7":
|
||||
"@types/lodash.kebabcase@npm:^4.1.7, @types/lodash.kebabcase@npm:^4.1.9":
|
||||
version: 4.1.9
|
||||
resolution: "@types/lodash.kebabcase@npm:4.1.9"
|
||||
dependencies:
|
||||
|
|
@ -29266,6 +29331,13 @@ __metadata:
|
|||
languageName: node
|
||||
linkType: hard
|
||||
|
||||
"aws4fetch@npm:^1.0.20":
|
||||
version: 1.0.20
|
||||
resolution: "aws4fetch@npm:1.0.20"
|
||||
checksum: 10c0/a4eac7bd0d1c3e611c17ed1ef41ac0b48c0a8e74a985ad968c071e74d94586d3572edc943b43fa5ca756c686ea73baa2f48e264d657bb8c2e95c8e0037d48a87
|
||||
languageName: node
|
||||
linkType: hard
|
||||
|
||||
"axe-core@npm:^4.10.0":
|
||||
version: 4.10.3
|
||||
resolution: "axe-core@npm:4.10.3"
|
||||
|
|
@ -58672,6 +58744,7 @@ __metadata:
|
|||
"@types/fs-extra": "npm:^11.0.0"
|
||||
"@types/inquirer": "npm:^9.0.0"
|
||||
"@types/lodash.camelcase": "npm:^4.3.7"
|
||||
"@types/lodash.kebabcase": "npm:^4.1.9"
|
||||
"@types/node": "npm:^24.0.0"
|
||||
"@types/react": "npm:18.2.66"
|
||||
"@types/react-dom": "npm:18.2.22"
|
||||
|
|
@ -58691,6 +58764,7 @@ __metadata:
|
|||
inquirer: "npm:^10.0.0"
|
||||
jsonc-parser: "npm:^3.2.0"
|
||||
lodash.camelcase: "npm:^4.3.0"
|
||||
lodash.kebabcase: "npm:^4.1.1"
|
||||
playwright: "npm:^1.56.1"
|
||||
preact: "npm:^10.28.3"
|
||||
react: "npm:^18.2.0"
|
||||
|
|
@ -58716,8 +58790,11 @@ __metadata:
|
|||
version: 0.0.0-use.local
|
||||
resolution: "twenty-server@workspace:packages/twenty-server"
|
||||
dependencies:
|
||||
"@ai-sdk/amazon-bedrock": "npm:^3.0.83"
|
||||
"@ai-sdk/anthropic": "npm:^2.0.17"
|
||||
"@ai-sdk/google": "npm:^2.0.54"
|
||||
"@ai-sdk/groq": "npm:^2.0.34"
|
||||
"@ai-sdk/mistral": "npm:^2.0.28"
|
||||
"@ai-sdk/openai": "npm:^2.0.30"
|
||||
"@ai-sdk/provider-utils": "npm:^3.0.9"
|
||||
"@ai-sdk/xai": "npm:^2.0.19"
|
||||
|
|
|
|||
Loading…
Reference in a new issue