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Hello everyone! I’m a complete beginner at Pipedream and coding in general. I’m following a tutorial by Thomas Frank (How to Take Perfect Notes with Your Voice Using ChatGPT and Notion), I’m trying to connect my generated transcript to chatgpt and now I am getting an error I don’t know how to fix: SyntaxError: The requested module ‘openai’ does not provide an export named ‘Configuration’
Maybe this is obvious for you, but I have no clue what to do… please help! 
Here is my code:
import { Configuration, OpenAIApi } from "openai"
import { encode, decode } from "gpt-3-encoder"
export default defineComponent({
props: {
openai: {
type: "app",
app: "openai",
}
},
async run({steps, $}) {
// Import the transcript from the previous step
const transcript = steps.create_transcription.$return_value.transcription
// Set the max number of input tokens
const maxTokens = 2000
// Initialize OpenAI
const openAIkey = this.openai.$auth.api_key
const configuration = new Configuration({
apiKey: openAIkey,
});
const openai = new OpenAIApi(configuration);
// Split the transcript into shorter strings if needed, based on GPT token limit
function splitTranscript(encodedTranscript, maxTokens) {
const stringsArray = []
let currentIndex = 0
while (currentIndex < encodedTranscript.length) {
let endIndex = Math.min(currentIndex + maxTokens, encodedTranscript.length)
// Find the next period
while (endIndex < encodedTranscript.length && decode([encodedTranscript[endIndex]]) !== ".") {
endIndex++
}
// Include the period in the current string
if (endIndex < encodedTranscript.length) {
endIndex++
}
// Add the current chunk to the stringsArray
const chunk = encodedTranscript.slice(currentIndex, endIndex)
stringsArray.push(decode(chunk))
currentIndex = endIndex
}
return stringsArray
}
const encoded = encode(transcript)
const stringsArray = splitTranscript(encoded, maxTokens)
const result = await sendToChat(stringsArray)
return result
// Function to send transcript string(s) to Chat API
async function sendToChat (stringsArray) {
const resultsArray = []
for (let arr of stringsArray) {
// Define the prompt
const prompt = `Analyze the transcript provided below, then provide the following:
Key "title:" - add a title.
Key "summary" - create a summary.
Key "main_points" - add an array of the main points. Limit each item to 100 words, and limit the list to 10 items.
Key "action_items:" - add an array of action items. Limit each item to 100 words, and limit the list to 5 items.
Key "follow_up:" - add an array of follow-up questions. Limit each item to 100 words, and limit the list to 5 items.
Key "stories:" - add an array of an stories, examples, or cited works found in the transcript. Limit each item to 200 words, and limit the list to 5 items.
Key "arguments:" - add an array of potential arguments against the transcript. Limit each item to 100 words, and limit the list to 5 items.
Key "related_topics:" - add an array of topics related to the transcript. Limit each item to 100 words, and limit the list to 5 items.
Key "sentiment" - add a sentiment analysis
Ensure that the final element of any array within the JSON object is not followed by a comma.
Transcript:
${arr}`
let retries = 3
while (retries > 0) {
try {
const completion = await openai.createChatCompletion({
model: "gpt-3.5-turbo",
messages: [{role: "user", content: prompt}, {role: "system", content: `You are an assistant that only speaks JSON. Do not write normal text.
Example formatting:
{
"title": "Notion Buttons",
"summary": "A collection of buttons for Notion",
"action_items": [
"item 1",
"item 2",
"item 3"
],
"follow_up": [
"item 1",
"item 2",
"item 3"
],
"arguments": [
"item 1",
"item 2",
"item 3"
],
"related_topics": [
"item 1",
"item 2",
"item 3"
]
"sentiment": "positive"
}
`}],
temperature: 0.2
});
resultsArray.push(completion)
break
} catch (error) {
if(error.response && error.response.status === 500) {
retries--
if (retries == 0) {
throw new Error("Failed to get a response from OpenAI Chat API after 3 attempts.")
}
console.log("OpenAI Chat API returned a 500 error. Retrying...")
} else {
throw error
}
}
}
}
return resultsArray
}
},
})