218 lines
8.8 KiB
TypeScript
218 lines
8.8 KiB
TypeScript
import { openai } from "@ai-sdk/openai";
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import { anthropic } from '@ai-sdk/anthropic'
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import { convertToCoreMessages, streamText, tool } from "ai";
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import { CodeInterpreter } from '@e2b/code-interpreter'
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import { z } from "zod";
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import { geolocation } from '@vercel/functions'
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// Allow streaming responses up to 30 seconds
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export const maxDuration = 30;
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export async function POST(req: Request) {
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const { messages, model } = await req.json();
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const { latitude, longitude, city } = geolocation(req)
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let ansmodel;
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if (model === "claude-3-5-sonnet-20240620") {
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ansmodel = anthropic("claude-3-5-sonnet-20240620")
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} else {
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ansmodel = openai(model)
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}
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const result = await streamText({
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model: ansmodel,
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messages: convertToCoreMessages(messages),
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system:
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"You are an AI web search engine that helps users find information on the internet." +
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"Always start with running the tool(s) and then and then only write your response AT ALL COSTS!" +
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"Never write a response without running the tool(s) first!\n\n" +
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"Do not announce that your going to run a tool, just run it and then write your response AT ALL COSTS!!!!!." +
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"Tool Usage Instructions:\n" +
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"The user is located in " + city + " at latitude " + latitude + " and longitude " + longitude + "." +
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"Use this geolocation data for weather tool, when the user doesn't provide a specific location." +
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"You use the 'web_search' tool to search for information on the internet." +
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"Always call the 'web_search' tool to get the information, no need to do a chain of thought or say anything else, go straight to the point." +
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"Once you have found the information, you provide the user with the information you found in brief like a news paper detail." +
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"The detail should be 3-5 paragraphs in 10-12 sentences, some time pointers, each with citations in the [Text](link) format always!" +
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"Citations can be inline of the text like this: Hey there! [Google](https://google.com) is a search engine." +
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"Do not start the responses with newline characters, always start with the first sentence." +
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"When the user asks about a Stock, you should 'always' first gather news about it with web search tool, then show the chart and then write your response. Follow these steps in this order only!" +
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"Never use the retrieve tool for general search. Always use it when the user provides an url! " +
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"For weather related questions, use get_weather_data tool and write your response. No need to call any other tool. Put citation to OpenWeatherMaps API everytime." +
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"Use the 'programming' tool to execute Python code for cases like calculating, sorting, etc. that require computation. " +
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"The environment is like a jupyter notebook so don't write or use print statements at all costs!, just the variables.\n\n" +
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"The current date is: " +
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new Date()
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.toLocaleDateString("en-US", {
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year: "numeric",
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month: "short",
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day: "2-digit",
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weekday: "short",
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})
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.replace(/(\w+), (\w+) (\d+), (\d+)/, "$4-$2-$3 ($1)") +
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"." +
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"Rules for the response:\n" +
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"Never use the heading format in your response!." +
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"IMPORTANT!!!: Refrain from saying things like that mention that your going to perform a certain action, example: 'Certainly! I'll search for information about OpenAI GPT-4o mini using the web search tool.'",
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tools: {
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web_search: tool({
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description: 'Search the web for information with the given query, max results and search depth.',
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parameters: z.object({
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query: z.string()
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.describe('The search query to look up on the web.'),
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maxResults: z.number()
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.describe('The maximum number of results to return. Default to be used is 10.'),
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searchDepth:
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z.enum(['basic', 'advanced'])
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.describe('The search depth to use for the search. Default is basic.')
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}),
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execute: async ({ query, maxResults, searchDepth }: { query: string, maxResults: number, searchDepth: 'basic' | 'advanced' }) => {
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const apiKey = process.env.TAVILY_API_KEY
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const response = await fetch('https://api.tavily.com/search', {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json'
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},
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body: JSON.stringify({
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api_key: apiKey,
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query,
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max_results: maxResults < 5 ? 5 : maxResults,
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search_depth: searchDepth,
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include_images: true,
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include_answers: true
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})
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})
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const data = await response.json()
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let context = data.results.map((obj: { url: any; content: any; title: any; raw_content: any; }) => {
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return {
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url: obj.url,
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title: obj.title,
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content: obj.content,
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raw_content: obj.raw_content
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}
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})
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return {
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results: context
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}
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}
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}),
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retrieve: tool({
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description: 'Retrieve the information from a URL.',
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parameters: z.object({
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url: z.string().describe('The URL to retrieve the information from.')
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}),
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execute: async ({ url }: { url: string }) => {
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let hasError = false
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let results;
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try {
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const response = await fetch(`https://r.jina.ai/${url}`, {
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method: 'GET',
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headers: {
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Accept: 'application/json',
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'X-With-Generated-Alt': 'true'
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}
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})
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const json = await response.json()
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if (!json.data || json.data.length === 0) {
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hasError = true
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} else {
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// Limit the content to 5000 characters
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if (json.data.content.length > 5000) {
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json.data.content = json.data.content.slice(0, 5000)
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}
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results = {
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results: [
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{
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title: json.data.title,
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content: json.data.content,
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url: json.data.url
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}
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],
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query: '',
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images: []
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}
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}
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} catch (error) {
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hasError = true
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console.error('Retrieve API error:', error)
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}
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if (hasError || !results) {
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return results
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}
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return results
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}
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}),
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get_weather_data: tool({
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description: "Get the weather data for the given coordinates.",
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parameters: z.object({
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lat: z.number().describe('The latitude of the location.'),
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lon: z.number().describe('The longitude of the location.')
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}),
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execute: async ({ lat, lon }: { lat: number, lon: number }) => {
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const apiKey = process.env.OPENWEATHER_API_KEY
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const response = await fetch(`https://api.openweathermap.org/data/2.5/forecast?lat=${lat}&lon=${lon}&appid=${apiKey}`)
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const data = await response.json()
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return data
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}
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}),
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stock_chart_ui: tool({
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description: 'Display the stock chart for the given stock symbol after web search.',
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parameters: z.object({
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symbol: z.string().describe('The stock symbol to display the chart for.')
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}),
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}),
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programming: tool({
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description: 'Write and execute Python code.',
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parameters: z.object({
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code: z.string().describe('The Python code to execute.')
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}),
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execute: async ({ code }: { code: string }) => {
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const sandbox = await CodeInterpreter.create()
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const execution = await sandbox.notebook.execCell(code)
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if (execution.results.length > 0) {
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let message: string = '';
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for (const result of execution.results) {
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if (result.isMainResult) {
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message += `${result.text}\n`
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} else {
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message += `${result.text}\n`
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}
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if (result.formats().length > 0) {
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message += `It has following formats: ${result.formats()}\n`
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}
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}
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return message
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}
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if (
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execution.logs.stdout.length > 0 ||
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execution.logs.stderr.length > 0
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) {
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let message = ''
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if (execution.logs.stdout.length > 0) {
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message += `${execution.logs.stdout.join('\n')}\n`
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}
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if (execution.logs.stderr.length > 0) {
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message += `${execution.logs.stderr.join('\n')}\n`
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}
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return message
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}
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return 'There was no output of the execution.'
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}
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}),
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},
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});
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return result.toAIStreamResponse();
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}
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