Hello @baptisteArno, As we discussed in issue #1315 we created a basic implementation of Anthropic’s Claude AI block. This block is based on the OpenAI block and shares a similar structure. The most notable changes in this PR are: - Added the Claude AI block. - Added relevant documentation for the new block. - Formatted some other source files in order to pass git pre-hook checks. Some notes to be made: - Currently there is no way to dynamically fetch the model’s versions since there is no endpoint provided by the SDK. - All pre version-3 Claude models are hard-coded constant variables. - We have opened an issue for that on the SDK repository [here](https://github.com/anthropics/anthropic-sdk-typescript/issues/313). - We can implement in a new PR Claude’s new [Vision system](https://docs.anthropic.com/claude/docs/vision) which allows for image analysis and understanding. - This can be done in a later phase, given that you agree of course. <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit - **New Features** - Introduced the Anthropic block for creating chat messages with Claude AI in Typebot. - Added functionality to create chat messages using Anthropic AI SDK with configurable options. - Implemented encrypted credentials for Anthropic account integration. - Added constants and helpers for better handling of chat messages with Anthropic models. - Included Anthropic block in the list of enabled and forged blocks for broader access. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Co-authored-by: Retr0-01 <contact@retr0.dev> Co-authored-by: Baptiste Arnaud <baptiste.arnaud95@gmail.com> Co-authored-by: Baptiste Arnaud <contact@baptiste-arnaud.fr>
136 lines
3.6 KiB
TypeScript
136 lines
3.6 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 MistralClient from '@mistralai/mistralai'
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import { parseMessages } from '../helpers/parseMessages'
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import { OpenAIStream } from 'ai'
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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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blockType: 'openai',
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},
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{
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blockType: 'together-ai',
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},
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{ blockType: 'open-router' },
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{ blockType: 'anthropic' },
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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 = await client.listModels()
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return (
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listModelsResponse.data
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.sort((a, b) => b.created - a.created)
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.map((model) => 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 = 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 = 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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// @ts-ignore https://github.com/vercel/ai/issues/936
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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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