openai-cookbook/examples/chatgpt/sharepoint_azure_function/solution_two_preprocessing.js
rupert-openai f6ea13ebed
Fixes to Sharepoint (Return Text) GPT Action Page (#1308)
Co-authored-by: Aaron Wilkowitz <157151487+aaronwilkowitz-openai@users.noreply.github.com>
2024-07-25 10:41:27 -04:00

241 lines
11 KiB
JavaScript

const { Client } = require('@microsoft/microsoft-graph-client');
const pdfParse = require('pdf-parse');
const { Buffer } = require('buffer');
const path = require('path');
const axios = require('axios');
const qs = require('querystring');
const { OpenAI } = require("openai");
//// --------- ENVIRONMENT CONFIGURATION AND INITIALIZATION ---------
// Function to initialize Microsoft Graph client
const initGraphClient = (accessToken) => {
return Client.init({
authProvider: (done) => {
done(null, accessToken); // Pass the access token for Graph API calls
}
});
};
//// --------- AUTHENTICATION AND TOKEN MANAGEMENT ---------
// Function to obtain OBO token. This will take the access token in request header (scoped to this Function App) and generate a new token to use for Graph API
const getOboToken = async (userAccessToken) => {
const { TENANT_ID, CLIENT_ID, MICROSOFT_PROVIDER_AUTHENTICATION_SECRET } = process.env;
const scope = 'https://graph.microsoft.com/.default';
const oboTokenUrl = `https://login.microsoftonline.com/${TENANT_ID}/oauth2/v2.0/token`;
const params = {
client_id: CLIENT_ID,
client_secret: MICROSOFT_PROVIDER_AUTHENTICATION_SECRET,
grant_type: 'urn:ietf:params:oauth:grant-type:jwt-bearer',
assertion: userAccessToken,
requested_token_use: 'on_behalf_of',
scope: scope
};
try {
const response = await axios.post(oboTokenUrl, qs.stringify(params), {
headers: {
'Content-Type': 'application/x-www-form-urlencoded'
}
});
return response.data.access_token; // OBO token
} catch (error) {
console.error('Error obtaining OBO token:', error.response?.data || error.message);
throw error;
}
};
//// --------- DOCUMENT PROCESSING ---------
// Function to fetch drive item content and convert to text
const getDriveItemContent = async (client, driveId, itemId, name) => {
try {
const fileType = path.extname(name).toLowerCase();
// the below files types are the ones that are able to be converted to PDF to extract the text. See https://learn.microsoft.com/en-us/graph/api/driveitem-get-content-format?view=graph-rest-1.0&tabs=http
const allowedFileTypes = ['.pdf', '.doc', '.docx', '.odp', '.ods', '.odt', '.pot', '.potm', '.potx', '.pps', '.ppsx', '.ppsxm', '.ppt', '.pptm', '.pptx', '.rtf'];
// filePath changes based on file type, adding ?format=pdf to convert non-pdf types to pdf for text extraction, so all files in allowedFileTypes above are converted to pdf
const filePath = `/drives/${driveId}/items/${itemId}/content` + ((fileType === '.pdf' || fileType === '.txt' || fileType === '.csv') ? '' : '?format=pdf');
if (allowedFileTypes.includes(fileType)) {
response = await client.api(filePath).getStream();
// The below takes the chunks in response and combines
let chunks = [];
for await (let chunk of response) {
chunks.push(chunk);
}
let buffer = Buffer.concat(chunks);
// the below extracts the text from the PDF.
const pdfContents = await pdfParse(buffer);
return pdfContents.text;
} else if (fileType === '.txt') {
// If the type is txt, it does not need to create a stream and instead just grabs the content
response = await client.api(filePath).get();
return response;
} else if (fileType === '.csv') {
response = await client.api(filePath).getStream();
let chunks = [];
for await (let chunk of response) {
chunks.push(chunk);
}
let buffer = Buffer.concat(chunks);
let dataString = buffer.toString('utf-8');
return dataString
} else {
return 'Unsupported File Type';
}
} catch (error) {
console.error('Error fetching drive content:', error);
throw new Error(`Failed to fetch content for ${name}: ${error.message}`);
}
};
// Function to get relevant parts of text using got-4o-mini.
const getRelevantParts = async (text, query) => {
try {
// We use your OpenAI key to initialize the OpenAI client
const openAIKey = process.env["OPENAI_API_KEY"];
const openai = new OpenAI({
apiKey: openAIKey,
});
const response = await openai.chat.completions.create({
// Using gpt-4o-mini due to speed to prevent timeouts. You can tweak this prompt as needed
model: "gpt-4o-mini",
messages: [
{"role": "system", "content": "You are a helpful assistant that finds relevant content in text based on a query. You only return the relevant sentences, and you return a maximum of 10 sentences"},
{"role": "user", "content": `Based on this question: **"${query}"**, get the relevant parts from the following text:*****\n\n${text}*****. If you cannot answer the question based on the text, respond with 'No information provided'`}
],
// using temperature of 0 since we want to just extract the relevant content
temperature: 0,
// using max_tokens of 1000, but you can customize this based on the number of documents you are searching.
max_tokens: 1000
});
return response.choices[0].message.content;
} catch (error) {
console.error('Error with OpenAI:', error);
return 'Error processing text with OpenAI' + error;
}
};
//// --------- AZURE FUNCTION LOGIC ---------
// Below is what the Azure Function executes
module.exports = async function (context, req) {
const query = req.query.query || (req.body && req.body.query);
const searchTerm = req.query.searchTerm || (req.body && req.body.searchTerm);
if (!req.headers.authorization) {
context.res = {
status: 400,
body: 'Authorization header is missing'
};
return;
}
/// The below takes the token passed to the function, to use to get an OBO token.
const bearerToken = req.headers.authorization.split(' ')[1];
let accessToken;
try {
accessToken = await getOboToken(bearerToken);
} catch (error) {
context.res = {
status: 500,
body: `Failed to obtain OBO token: ${error.message}`
};
return;
}
// Initialize the Graph Client using the initGraphClient function defined above
let client = initGraphClient(accessToken);
// this is the search body to be used in the Microsft Graph Search API: https://learn.microsoft.com/en-us/graph/search-concept-files
const requestBody = {
requests: [
{
entityTypes: ['driveItem'],
query: {
queryString: searchTerm
},
from: 0,
// the below is set to summarize the top 10 search results from the Graph API, but can configure based on your documents.
size: 10
}
]
};
try {
// Function to tokenize content (e.g., based on words).
const tokenizeContent = (content) => {
return content.split(/\s+/);
};
// Function to break tokens into 10k token windows for got-4o-mini
const breakIntoTokenWindows = (tokens) => {
const tokenWindows = []
const maxWindowTokens = 10000; // 10k tokens
let startIndex = 0;
while (startIndex < tokens.length) {
const window = tokens.slice(startIndex, startIndex + maxWindowTokens);
tokenWindows.push(window);
startIndex += maxWindowTokens;
}
return tokenWindows;
};
// This is where we are doing the search
const list = await client.api('/search/query').post(requestBody);
const processList = async () => {
// This will go through and for each search response, grab the contents of the file and summarize with got-4o-mini
const results = [];
await Promise.all(list.value[0].hitsContainers.map(async (container) => {
for (const hit of container.hits) {
if (hit.resource["@odata.type"] === "#microsoft.graph.driveItem") {
const { name, id } = hit.resource;
// We use the below to grab the URL of the file to include in the response
const webUrl = hit.resource.webUrl.replace(/\s/g, "%20");
// The Microsoft Graph API ranks the reponses, so we use this to order it
const rank = hit.rank;
// The below is where the file lives
const driveId = hit.resource.parentReference.driveId;
const contents = await getDriveItemContent(client, driveId, id, name);
if (contents !== 'Unsupported File Type') {
// Tokenize content using function defined previously
const tokens = tokenizeContent(contents);
// Break tokens into 10k token windows
const tokenWindows = breakIntoTokenWindows(tokens);
// Process each token window and combine results
const relevantPartsPromises = tokenWindows.map(window => getRelevantParts(window.join(' '), query));
const relevantParts = await Promise.all(relevantPartsPromises);
const combinedResults = relevantParts.join('\n'); // Combine results
results.push({ name, webUrl, rank, contents: combinedResults });
}
else {
results.push({ name, webUrl, rank, contents: 'Unsupported File Type' });
}
}
}
}));
return results;
};
let results;
if (list.value[0].hitsContainers[0].total == 0) {
// Return no results found to the API if the Microsoft Graph API returns no results
results = 'No results found';
} else {
// If the Microsoft Graph API does return results, then run processList to iterate through.
results = await processList();
results.sort((a, b) => a.rank - b.rank);
}
context.res = {
status: 200,
body: results
};
} catch (error) {
context.res = {
status: 500,
body: `Error performing search or processing results: ${error.message}`,
};
}
};