mirror of
https://github.com/windmill-labs/windmill.git
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748 lines
18 KiB
TypeScript
748 lines
18 KiB
TypeScript
import { OpenAI } from 'openai'
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import { OpenAPI, ResourceService, type Script } from '../../gen'
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import type { Writable } from 'svelte/store'
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import { Anthropic } from '@anthropic-ai/sdk'
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import type { DBSchema, GraphqlSchema, SQLSchema } from '$lib/stores'
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import { formatResourceTypes } from './utils'
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import { EDIT_CONFIG, FIX_CONFIG, GEN_CONFIG } from './prompts'
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import { Mistral } from '@mistralai/mistralai'
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import { buildClientSchema, printSchema } from 'graphql'
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import type {
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ChatCompletionCreateParamsStreaming,
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ChatCompletionMessageParam
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} from 'openai/resources/index.mjs'
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import type { MessageCreateParams, MessageParam } from '@anthropic-ai/sdk/resources/messages.mjs'
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import type { ChatCompletionRequest } from '@mistralai/mistralai/models/components/chatcompletionrequest'
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import type {
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SystemMessage,
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UserMessage,
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AssistantMessage,
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ToolMessage,
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CompletionEvent,
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ContentChunk
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} from '@mistralai/mistralai/models/components'
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export const SUPPORTED_LANGUAGES = new Set(Object.keys(GEN_CONFIG.prompts))
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export type AiProviderTypes = 'openai' | 'anthropic' | 'mistral'
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interface AiProvider {
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init: (workspace: string, updateClient: boolean, token?: string) => void
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}
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class WorkspacedMistral implements AiProvider {
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private client: Mistral | undefined
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init(workspace: string, updateClient: boolean, token?: string) {
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if (!this.client || updateClient) {
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this.client = initWorkspaceAiProvider(workspace, 'mistral', token) as unknown as Mistral
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}
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}
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getClient() {
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if (!this.client) {
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throw new Error('AnthropicAi not initialized')
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}
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return this.client
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}
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}
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export namespace MistralAi {
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export let workspace = new WorkspacedMistral()
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export const mistralConfig: ChatCompletionRequest = {
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temperature: 0,
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model: null,
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maxTokens: 32000,
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messages: []
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}
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export type MistralParamsMessage =
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| (SystemMessage & { role: 'system' })
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| (UserMessage & { role: 'user' })
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| (AssistantMessage & { role: 'assistant' })
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| (ToolMessage & { role: 'tool' })
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export function retrieveTextValue(chunks: string | ContentChunk[] | null | undefined): string {
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let response = ''
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if (Array.isArray(chunks)) {
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for (const chunk of chunks) {
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if (chunk.type === 'text') {
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response += chunk.text
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}
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}
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return response
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}
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return chunks as string
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}
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}
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class WorkspacedAnthropic implements AiProvider {
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private client: Anthropic | undefined
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init(workspace: string, updateClient: boolean, token: string | undefined = undefined) {
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if (!this.client || updateClient) {
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this.client = initWorkspaceAiProvider(workspace, 'anthropic', token) as unknown as Anthropic
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}
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}
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getClient() {
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if (!this.client) {
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throw new Error('AnthropicAi not initialized')
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}
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return this.client
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}
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}
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export namespace AnthropicAi {
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export let workspace = new WorkspacedAnthropic()
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export const config: MessageCreateParams = {
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temperature: 0,
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max_tokens: 8192,
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model: 'claude-3-5-sonnet-20241022',
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messages: []
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}
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export function getSystemPromptAndArrayMessages(
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messages: ChatCompletionMessageParam[]
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): [string, MessageParam[]] {
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let system: string | undefined = undefined
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if (messages[0].role == 'system') {
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system = messages[0].content as string
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messages.shift()
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}
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const anthropicMessages: MessageParam[] = messages.map((message) => {
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return {
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role: message.role == 'user' ? 'user' : 'assistant',
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content: message.content as string
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}
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})
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return [system as string, anthropicMessages ?? []]
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}
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export function retrieveTextValue(part: Anthropic.Messages.RawMessageStreamEvent) {
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let response = ''
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if (part.type == 'content_block_delta') {
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if (part.delta.type == 'text_delta') {
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response = part.delta.text
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} else {
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response = part.delta.partial_json
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}
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}
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return response
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}
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}
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class WorkspacedOpenai implements AiProvider {
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private client: OpenAI | undefined
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init(workspace: string, updateClient: boolean, token: string | undefined = undefined) {
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if (!this.client || updateClient) {
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this.client = initWorkspaceAiProvider(workspace, 'openai', token) as unknown as OpenAI
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}
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}
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getClient() {
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if (!this.client) {
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throw new Error('OpenAI not initialized')
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}
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return this.client
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}
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}
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export namespace OpenAi {
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export let workspace = new WorkspacedOpenai()
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export const openaiConfig: ChatCompletionCreateParamsStreaming = {
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temperature: 0,
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max_tokens: 16384,
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model: 'gpt-4o-2024-08-06',
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seed: 42,
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stream: true,
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messages: []
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}
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export function retrieveTextValue(part: OpenAI.Chat.Completions.ChatCompletionChunk) {
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return part.choices[0]?.delta?.content || ''
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}
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}
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export function initAllAiWorkspace(workspace: string, updateClient: boolean = false) {
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OpenAi.workspace.init(workspace, updateClient)
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AnthropicAi.workspace.init(workspace, updateClient)
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MistralAi.workspace.init(workspace, updateClient)
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}
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function initWorkspaceAiProvider(
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workspace: string,
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aiProvider: AiProviderTypes,
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token: string | undefined = undefined
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): Anthropic | OpenAI | Mistral {
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const baseURL = `${location.origin}${OpenAPI.BASE}/w/${workspace}/ai/proxy`
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let client
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switch (aiProvider) {
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case 'openai': {
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client = new OpenAI({
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baseURL,
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apiKey: 'fake-key',
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defaultHeaders: {
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Authorization: token ? `Bearer ${token}` : ''
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},
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dangerouslyAllowBrowser: true
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})
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break
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}
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case 'anthropic': {
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client = new Anthropic({
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baseURL,
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apiKey: 'fake-key',
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defaultHeaders: {
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Authorization: token ? `Bearer ${token}` : ''
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},
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dangerouslyAllowBrowser: true
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})
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break
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}
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case 'mistral': {
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client = new Mistral({
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serverURL: baseURL
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})
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}
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}
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return client
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}
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export async function testKey({
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apiKey,
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abortController,
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messages,
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aiProvider
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}: {
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apiKey?: string
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messages: ChatCompletionMessageParam[]
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abortController: AbortController
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aiProvider: AiProviderTypes
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}) {
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if (apiKey) {
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switch (aiProvider) {
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case 'openai': {
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const openai = new OpenAI({
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apiKey,
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dangerouslyAllowBrowser: true
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})
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await openai.chat.completions.create(
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{
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...OpenAi.openaiConfig,
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messages,
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stream: false
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},
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{
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signal: abortController.signal
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}
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)
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break
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}
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case 'anthropic': {
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const anthropic = new Anthropic({
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apiKey,
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dangerouslyAllowBrowser: true
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})
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const [, anthropicMessages] = AnthropicAi.getSystemPromptAndArrayMessages(messages)
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await anthropic.messages.create(
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{
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...AnthropicAi.config,
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messages: anthropicMessages,
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stream: false
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},
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{
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signal: abortController.signal
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}
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)
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break
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}
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case 'mistral': {
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const mistral = new Mistral({
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apiKey
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})
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await mistral.chat.complete(
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{
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...MistralAi.mistralConfig,
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model: 'codestral-latest',
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stream: false,
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messages: messages as MistralAi.MistralParamsMessage[]
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},
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{
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fetchOptions: {
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signal: abortController.signal,
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headers: {
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'content-type': 'application/json'
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}
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}
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}
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)
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break
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}
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}
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} else {
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await getNonStreamingCompletion(messages, abortController, aiProvider, undefined, true)
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}
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}
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interface BaseOptions {
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language: Script['language'] | 'frontend' | 'transformer'
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dbSchema: DBSchema | undefined
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workspace: string
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}
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interface ScriptGenerationOptions extends BaseOptions {
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description: string
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type: 'gen'
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}
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interface EditScriptOptions extends BaseOptions {
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description: string
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code: string
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type: 'edit'
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}
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interface FixScriptOpions extends BaseOptions {
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code: string
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error: string
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type: 'fix'
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}
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type CopilotOptions = ScriptGenerationOptions | EditScriptOptions | FixScriptOpions
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async function getResourceTypes(scriptOptions: CopilotOptions) {
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const elems =
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scriptOptions.type === 'gen' || scriptOptions.type === 'edit' ? [scriptOptions.description] : []
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if (scriptOptions.type === 'edit' || scriptOptions.type === 'fix') {
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const { code } = scriptOptions
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const mainSig =
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scriptOptions.language === 'python3'
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? code.match(/def main\((.*?)\)/s)
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: code.match(/function main\((.*?)\)/s)
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if (mainSig) {
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elems.push(mainSig[1])
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}
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const matches = code.matchAll(/^(?:type|class) ([a-zA-Z0-9_]+)/gm)
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for (const match of matches) {
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elems.push(match[1])
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}
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}
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const resourceTypes = await ResourceService.queryResourceTypes({
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workspace: scriptOptions.workspace,
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text: elems.join(';'),
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limit: 3
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})
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return resourceTypes
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}
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export async function addResourceTypes(scriptOptions: CopilotOptions, prompt: string) {
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if (['deno', 'bun', 'nativets', 'python3', 'php'].includes(scriptOptions.language)) {
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const resourceTypes = await getResourceTypes(scriptOptions)
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const resourceTypesText = formatResourceTypes(
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resourceTypes,
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['deno', 'bun', 'nativets'].includes(scriptOptions.language)
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? 'typescript'
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: (scriptOptions.language as 'python3' | 'php')
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)
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prompt = prompt.replace('{resourceTypes}', resourceTypesText)
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}
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return prompt
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}
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export const MAX_SCHEMA_LENGTH = 100000 * 3.5
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export function addThousandsSeparator(n: number) {
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return n.toFixed().replace(/\B(?=(\d{3})+(?!\d))/g, "'")
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}
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export function stringifySchema(
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dbSchema: Omit<SQLSchema, 'stringified'> | Omit<GraphqlSchema, 'stringified'>
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) {
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const { schema, lang } = dbSchema
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if (lang === 'graphql') {
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let graphqlSchema = printSchema(buildClientSchema(schema))
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return graphqlSchema
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} else {
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let smallerSchema: {
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[schemaKey: string]: {
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[tableKey: string]: Array<[string, string, boolean, string?]>
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}
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} = {}
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for (const schemaKey in schema) {
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smallerSchema[schemaKey] = {}
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for (const tableKey in schema[schemaKey]) {
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smallerSchema[schemaKey][tableKey] = []
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for (const colKey in schema[schemaKey][tableKey]) {
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const col = schema[schemaKey][tableKey][colKey]
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const p: [string, string, boolean, string?] = [colKey, col.type, col.required]
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if (col.default) {
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p.push(col.default)
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}
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smallerSchema[schemaKey][tableKey].push(p)
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}
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}
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}
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let finalSchema: typeof smallerSchema | (typeof smallerSchema)['schemaKey'] = smallerSchema
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if (dbSchema.publicOnly) {
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finalSchema =
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smallerSchema.public || smallerSchema.PUBLIC || smallerSchema.dbo || smallerSchema
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} else if (lang === 'mysql' && Object.keys(smallerSchema).length === 1) {
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finalSchema = smallerSchema[Object.keys(smallerSchema)[0]]
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}
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return JSON.stringify(finalSchema)
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}
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}
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function addDBSChema(scriptOptions: CopilotOptions, prompt: string) {
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const { dbSchema, language } = scriptOptions
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if (
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dbSchema &&
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['postgresql', 'mysql', 'snowflake', 'bigquery', 'mssql', 'graphql', 'oracledb'].includes(language) && // make sure we are using a SQL/query language
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language === dbSchema.lang // make sure we are using the same language as the schema
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) {
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let { stringified } = dbSchema
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if (dbSchema.lang === 'graphql') {
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if (stringified.length > MAX_SCHEMA_LENGTH) {
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stringified = stringified.slice(0, MAX_SCHEMA_LENGTH) + '...'
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}
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prompt = prompt + '\nHere is the GraphQL schema: <schema>\n' + stringified + '\n</schema>'
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} else {
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if (stringified.length > MAX_SCHEMA_LENGTH) {
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stringified = stringified.slice(0, MAX_SCHEMA_LENGTH) + '...'
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}
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prompt =
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prompt +
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"\nHere's the database schema, each column is in the format [name, type, required, default?]: <dbschema>\n" +
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stringified +
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'\n</dbschema>'
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}
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}
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return prompt
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}
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async function getPrompts(scriptOptions: CopilotOptions) {
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const promptsConfig = PROMPTS_CONFIGS[scriptOptions.type]
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let prompt = promptsConfig.prompts[scriptOptions.language].prompt
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if (scriptOptions.type !== 'fix') {
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prompt = prompt.replace('{description}', scriptOptions.description)
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}
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if (scriptOptions.type !== 'gen') {
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prompt = prompt.replace('{code}', scriptOptions.code)
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}
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if (scriptOptions.type === 'fix') {
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if (scriptOptions.language === 'frontend') {
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throw new Error('Fixing frontend code is not supported')
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}
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prompt = prompt.replace('{error}', scriptOptions.error)
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}
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prompt = await addResourceTypes(scriptOptions, prompt)
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prompt = addDBSChema(scriptOptions, prompt)
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return { prompt, systemPrompt: promptsConfig.system }
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}
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const PROMPTS_CONFIGS = {
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fix: FIX_CONFIG,
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edit: EDIT_CONFIG,
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gen: GEN_CONFIG
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}
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|
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export async function getNonStreamingCompletion(
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messages: ChatCompletionMessageParam[],
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abortController: AbortController,
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aiProvider: AiProviderTypes,
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model = OpenAi.openaiConfig.model,
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noCache?: boolean
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) {
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let response: string | undefined = ''
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const queryOptions = {
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query: {
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no_cache: noCache
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},
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signal: abortController.signal
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}
|
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switch (aiProvider) {
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case 'openai': {
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const openaiClient = OpenAi.workspace.getClient()
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const completion = await openaiClient.chat.completions.create(
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{
|
|
...OpenAi.openaiConfig,
|
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messages,
|
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stream: false,
|
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model
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},
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queryOptions
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)
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response = completion.choices[0]?.message.content || ''
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break
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}
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case 'anthropic': {
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const anthropicClient = AnthropicAi.workspace.getClient()
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|
const [system, anthropicMessages] = AnthropicAi.getSystemPromptAndArrayMessages(messages)
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const message = await anthropicClient.messages.create(
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{
|
|
...AnthropicAi.config,
|
|
system,
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messages: anthropicMessages,
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stream: false
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},
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queryOptions
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)
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response = message.content[0].type === 'text' ? message.content[0].text : ''
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break
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}
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case 'mistral': {
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const mistralClient = MistralAi.workspace.getClient()
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const message = await mistralClient.chat.complete(
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{
|
|
...MistralAi.mistralConfig,
|
|
model: 'codestral-latest',
|
|
stream: false,
|
|
messages: messages as MistralAi.MistralParamsMessage[]
|
|
},
|
|
{
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|
fetchOptions: {
|
|
signal: abortController.signal,
|
|
cache: 'no-store'
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|
}
|
|
}
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)
|
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response = MistralAi.retrieveTextValue(message.choices && message.choices[0].message.content)
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break
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}
|
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}
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return response
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}
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|
|
export async function getCompletion(
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|
messages: ChatCompletionMessageParam[],
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|
abortController: AbortController,
|
|
aiProvider: AiProviderTypes,
|
|
model = OpenAi.openaiConfig.model
|
|
) {
|
|
switch (aiProvider) {
|
|
case 'anthropic': {
|
|
const anthropicClient = AnthropicAi.workspace.getClient()
|
|
const [system, anthropicMessages] = AnthropicAi.getSystemPromptAndArrayMessages(messages)
|
|
|
|
const completion = await anthropicClient.messages.create(
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|
{
|
|
...AnthropicAi.config,
|
|
system,
|
|
messages: anthropicMessages,
|
|
stream: true
|
|
},
|
|
{ signal: abortController.signal }
|
|
)
|
|
return completion
|
|
}
|
|
case 'openai': {
|
|
const openaiClient = OpenAi.workspace.getClient()
|
|
const completion = await openaiClient.chat.completions.create(
|
|
{
|
|
...OpenAi.openaiConfig,
|
|
messages,
|
|
model
|
|
},
|
|
{
|
|
signal: abortController.signal
|
|
}
|
|
)
|
|
return completion
|
|
}
|
|
case 'mistral': {
|
|
const mistralClient = MistralAi.workspace.getClient()
|
|
const message = await mistralClient.chat.stream(
|
|
{
|
|
...MistralAi.mistralConfig,
|
|
model: 'codestral-latest',
|
|
messages: messages as MistralAi.MistralParamsMessage[]
|
|
},
|
|
{
|
|
fetchOptions: {
|
|
signal: abortController.signal,
|
|
cache: 'no-store'
|
|
}
|
|
}
|
|
)
|
|
return message
|
|
}
|
|
}
|
|
}
|
|
|
|
export function getResponseFromEvent(
|
|
part:
|
|
| Anthropic.Messages.RawMessageStreamEvent
|
|
| OpenAI.Chat.Completions.ChatCompletionChunk
|
|
| CompletionEvent,
|
|
aiProvider: AiProviderTypes
|
|
): string {
|
|
switch (aiProvider) {
|
|
case 'openai': {
|
|
const messages = part as OpenAI.Chat.Completions.ChatCompletionChunk
|
|
return OpenAi.retrieveTextValue(messages)
|
|
}
|
|
case 'anthropic': {
|
|
const messages = part as Anthropic.Messages.RawMessageStreamEvent
|
|
return AnthropicAi.retrieveTextValue(messages)
|
|
}
|
|
case 'mistral': {
|
|
const messages = part as CompletionEvent
|
|
return MistralAi.retrieveTextValue(messages.data.choices[0].delta.content)
|
|
}
|
|
}
|
|
}
|
|
|
|
export async function copilot(
|
|
scriptOptions: CopilotOptions,
|
|
generatedCode: Writable<string>,
|
|
abortController: AbortController,
|
|
aiProvider: AiProviderTypes,
|
|
generatedExplanation?: Writable<string>
|
|
) {
|
|
const { prompt, systemPrompt } = await getPrompts(scriptOptions)
|
|
|
|
const completion = await getCompletion(
|
|
[
|
|
{
|
|
role: 'system',
|
|
content: systemPrompt
|
|
},
|
|
{
|
|
role: 'user',
|
|
content: prompt
|
|
}
|
|
],
|
|
abortController,
|
|
aiProvider
|
|
)
|
|
|
|
let response = ''
|
|
let code = ''
|
|
for await (const part of completion) {
|
|
response += getResponseFromEvent(part, aiProvider)
|
|
let match = response.match(/```[a-zA-Z]+\n([\s\S]*?)\n```/)
|
|
|
|
if (match) {
|
|
// if we have a full code block
|
|
code = match[1]
|
|
generatedCode.set(code)
|
|
|
|
if (scriptOptions.type === 'fix') {
|
|
// in fix mode, check for explanation
|
|
let explanationMatch = response.match(/<explanation>([\s\S]+)<\/explanation>/)
|
|
|
|
if (explanationMatch) {
|
|
const explanation = explanationMatch[1].trim()
|
|
generatedExplanation?.set(explanation)
|
|
break
|
|
}
|
|
|
|
explanationMatch = response.match(/<explanation>([\s\S]+)/)
|
|
|
|
if (!explanationMatch) {
|
|
continue
|
|
}
|
|
|
|
const explanation = explanationMatch[1].replace(/<\/?e?x?p?l?a?n?a?t?i?o?n?>?$/, '').trim()
|
|
|
|
generatedExplanation?.set(explanation)
|
|
|
|
continue
|
|
} else {
|
|
// otherwise stop generating
|
|
break
|
|
}
|
|
}
|
|
|
|
// partial code block, keep going
|
|
match = response.match(/```[a-zA-Z]+\n([\s\S]*)/)
|
|
|
|
if (!match) {
|
|
continue
|
|
}
|
|
|
|
code = match[1]
|
|
if (!code.endsWith('`')) {
|
|
// skip displaying if possible that part of three ticks (end of code block)s
|
|
generatedCode.set(code)
|
|
}
|
|
}
|
|
|
|
// make sure we display the latest and complete code
|
|
generatedCode.set(code)
|
|
|
|
if (code.length === 0) {
|
|
throw new Error('No code block found')
|
|
}
|
|
|
|
return code
|
|
}
|
|
|
|
function getStringEndDelta(prev: string, now: string) {
|
|
return now.slice(prev.length)
|
|
}
|
|
|
|
export async function deltaCodeCompletion(
|
|
messages: ChatCompletionMessageParam[],
|
|
generatedCodeDelta: Writable<string>,
|
|
abortController: AbortController,
|
|
aiProvider: AiProviderTypes
|
|
) {
|
|
const completion = await getCompletion(messages, abortController, aiProvider)
|
|
|
|
let response = ''
|
|
let code = ''
|
|
let delta = ''
|
|
for await (const part of completion) {
|
|
response += getResponseFromEvent(part, aiProvider)
|
|
let match = response.match(/```[a-zA-Z]+\n([\s\S]*?)\n```/)
|
|
|
|
if (match) {
|
|
// if we have a full code block
|
|
delta = getStringEndDelta(code, match[1])
|
|
code = match[1]
|
|
generatedCodeDelta.set(delta)
|
|
|
|
break
|
|
}
|
|
|
|
// partial code block, keep going
|
|
match = response.match(/```[a-zA-Z]+\n([\s\S]*)/)
|
|
|
|
if (!match) {
|
|
continue
|
|
}
|
|
|
|
if (!match[1].endsWith('`')) {
|
|
// skip udpating if possible that part of three ticks (end of code block)s
|
|
delta = getStringEndDelta(code, match[1])
|
|
generatedCodeDelta.set(delta)
|
|
code = match[1]
|
|
}
|
|
}
|
|
|
|
if (code.length === 0) {
|
|
throw new Error('No code block found')
|
|
}
|
|
|
|
return code
|
|
}
|