151 lines
4.0 KiB
TypeScript
151 lines
4.0 KiB
TypeScript
import { option, createAction } from '@typebot.io/forge'
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import { isDefined } from '@typebot.io/lib'
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import { auth } from '../auth'
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import { parseMessages } from '../helpers/parseMessages'
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import { OpenAIStream } from 'ai'
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// @ts-ignore
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import MistralClient from '../helpers/client'
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const nativeMessageContentSchema = {
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content: option.string.layout({
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inputType: 'textarea',
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placeholder: 'Content',
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}),
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}
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const systemMessageItemSchema = option
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.object({
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role: option.literal('system'),
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})
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.extend(nativeMessageContentSchema)
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const userMessageItemSchema = option
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.object({
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role: option.literal('user'),
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})
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.extend(nativeMessageContentSchema)
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const assistantMessageItemSchema = option
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.object({
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role: option.literal('assistant'),
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})
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.extend(nativeMessageContentSchema)
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const dialogueMessageItemSchema = option.object({
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role: option.literal('Dialogue'),
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dialogueVariableId: option.string.layout({
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inputType: 'variableDropdown',
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placeholder: 'Dialogue variable',
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}),
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startsBy: option.enum(['user', 'assistant']).layout({
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label: 'starts by',
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direction: 'row',
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defaultValue: 'user',
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}),
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})
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export const options = option.object({
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model: option.string.layout({
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placeholder: 'Select a model',
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fetcher: 'fetchModels',
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}),
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messages: option
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.array(
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option.discriminatedUnion('role', [
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systemMessageItemSchema,
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userMessageItemSchema,
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assistantMessageItemSchema,
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dialogueMessageItemSchema,
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])
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)
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.layout({ accordion: 'Messages', itemLabel: 'message', isOrdered: true }),
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responseMapping: option.saveResponseArray(['Message content']).layout({
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accordion: 'Save response',
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}),
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})
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export const createChatCompletion = createAction({
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name: 'Create chat completion',
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auth,
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options,
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turnableInto: [
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{
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blockId: 'openai',
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},
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{
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blockId: 'together-ai',
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},
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{ blockId: 'open-router' },
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{
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blockId: 'anthropic',
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transform: (options) => ({
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...options,
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model: undefined,
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action: 'Create Chat Message',
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responseMapping: options.responseMapping?.map((res: any) =>
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res.item === 'Message content'
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? { ...res, item: 'Message Content' }
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: res
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),
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}),
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},
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],
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getSetVariableIds: (options) =>
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options.responseMapping?.map((res) => res.variableId).filter(isDefined) ??
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[],
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fetchers: [
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{
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id: 'fetchModels',
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dependencies: [],
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fetch: async ({ credentials }) => {
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const client = new MistralClient(credentials.apiKey)
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const listModelsResponse: any = await client.listModels()
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return (
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listModelsResponse.data
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.sort(
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(a: { created: number }, b: { created: number }) =>
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b.created - a.created
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)
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.map((model: { id: any }) => model.id) ?? []
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)
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},
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},
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],
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run: {
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server: async ({ credentials: { apiKey }, options, variables, logs }) => {
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if (!options.model) return logs.add('No model selected')
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const client = new MistralClient(apiKey)
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const response: any = await client.chat({
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model: options.model,
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messages: parseMessages({ options, variables }),
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})
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options.responseMapping?.forEach((mapping) => {
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if (!mapping.variableId) return
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if (!mapping.item || mapping.item === 'Message content')
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variables.set(mapping.variableId, response.choices[0].message.content)
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})
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},
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stream: {
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getStreamVariableId: (options) =>
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options.responseMapping?.find(
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(res) => res.item === 'Message content' || !res.item
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)?.variableId,
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run: async ({ credentials: { apiKey }, options, variables }) => {
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if (!options.model) return
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const client = new MistralClient(apiKey)
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const response: any = client.chatStream({
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model: options.model,
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messages: parseMessages({ options, variables }),
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})
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return OpenAIStream(response)
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},
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},
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},
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})
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