How to use OpenAI for PDF

using IronPdf;
using IronPdf.AI;
using Microsoft.SemanticKernel;
using Microsoft.SemanticKernel.Connectors.OpenAI;
using Microsoft.SemanticKernel.Memory;
using System;
using System.Threading.Tasks;

// This code demonstrates how to use IronPdf with Semantic Kernel OpenAI components
// to summarize the content of a PDF document. Ensure that you have the necessary
// API keys and endpoints properly set up.

// Setup OpenAI credentials
var azureEndpoint = "<<enter your azure endpoint here>>";
var apiKey = "<<enter your azure API key here>>";

// Build the Semantic Kernel with OpenAI capabilities
var builder = Kernel.CreateBuilder()
    .AddAzureOpenAITextEmbeddingGeneration("oaiembed", azureEndpoint, apiKey)
    .AddAzureOpenAIChatCompletion("oaichat", azureEndpoint, apiKey);
var kernel = builder.Build();

// Setup Memory configuration
var memoryBuilder = new MemoryBuilder()
    // Optionally, configure a new ChromaMemoryStore if needed. Uncomment the following line and provide the correct URL.
// .WithMemoryStore(new ChromaMemoryStore("http://127.0.0.1:8000"))
    .WithMemoryStore(new VolatileMemoryStore())
    .WithAzureOpenAITextEmbeddingGeneration("oaiembed", azureEndpoint, apiKey);
var memory = memoryBuilder.Build();

// Initialize IronAI with the configured kernel and memory
IronDocumentAI.Initialize(kernel, memory);

// Configure the IronPdf license
License.LicenseKey = "<<enter your IronPdf license key here>>";

// Import and process the PDF document
PdfDocument pdf = PdfDocument.FromFile("wikipedia.pdf");

// Asynchronous method to summarize the document
async Task SummarizeDocumentAsync()
{
    Console.WriteLine("Please wait while I summarize the document...");

    // Summarize the document's contents using AI
    // Ensure the proper async method call format
    string summary = await pdf.SummarizeAsync();

    // Output the generated summary
    Console.WriteLine($"Document summary: {summary}\n\n");
}

// Use an async context to call the summarization method
// Ensure the project supports async Main or is invoked within an async scope.
await SummarizeDocumentAsync();

Imports IronPdf
Imports IronPdf.AI
Imports Microsoft.SemanticKernel
Imports Microsoft.SemanticKernel.Connectors.OpenAI
Imports Microsoft.SemanticKernel.Memory
Imports System
Imports System.Threading.Tasks

' This code demonstrates how to use IronPdf with Semantic Kernel OpenAI components
' to summarize the content of a PDF document. Ensure that you have the necessary
' API keys and endpoints properly set up.

' Setup OpenAI credentials
Private azureEndpoint = "<<enter your azure endpoint here>>"
Private apiKey = "<<enter your azure API key here>>"

' Build the Semantic Kernel with OpenAI capabilities
Private builder = Kernel.CreateBuilder().AddAzureOpenAITextEmbeddingGeneration("oaiembed", azureEndpoint, apiKey).AddAzureOpenAIChatCompletion("oaichat", azureEndpoint, apiKey)
Private kernel = builder.Build()

' Setup Memory configuration
Private memoryBuilder = (New MemoryBuilder()).WithMemoryStore(New VolatileMemoryStore()).WithAzureOpenAITextEmbeddingGeneration("oaiembed", azureEndpoint, apiKey)
Private memory = memoryBuilder.Build()

' Initialize IronAI with the configured kernel and memory
IronDocumentAI.Initialize(kernel, memory)

' Configure the IronPdf license
License.LicenseKey = "<<enter your IronPdf license key here>>"

' Import and process the PDF document
Dim pdf As PdfDocument = PdfDocument.FromFile("wikipedia.pdf")

' Asynchronous method to summarize the document
'INSTANT VB TODO TASK: Local functions are not converted by Instant VB:
'async Task SummarizeDocumentAsync()
'{
'	Console.WriteLine("Please wait while I summarize the document...");
'
'	' Summarize the document's contents using AI
'	' Ensure the proper async method call format
'	string summary = await pdf.SummarizeAsync();
'
'	' Output the generated summary
'	Console.WriteLine(string.Format("Document summary: {0}" + vbLf + vbLf, summary));
'}

' Use an async context to call the summarization method
' Ensure the project supports async Main or is invoked within an async scope.
Await SummarizeDocumentAsync()

using IronPdf;
using IronPdf.AI;
using Microsoft.SemanticKernel;
using Microsoft.SemanticKernel.Connectors.OpenAI;
using Microsoft.SemanticKernel.Memory;
using System;
using System.Threading.Tasks;

// This setup code integrates the OpenAI services using Azure and initializes
// necessary dependencies for processing text and document queries.

// Set up the OpenAI integration with Azure
var azureEndpoint = "<<enter your azure endpoint here>>";
var apiKey = "<<enter your azure API key here>>";

// Build and configure the kernel to use OpenAI for text embedding and chat completion
var builder = Kernel.CreateBuilder()
    .AddAzureOpenAITextEmbeddingGeneration("oaiembed", azureEndpoint, apiKey)
    .AddAzureOpenAIChatCompletion("oaichat", azureEndpoint, apiKey);

var kernel = builder.Build();

// Set up memory for the semantic kernel, leveraging a simple volatile store.
// Optionally, ChromaMemoryStore can be used for additional features.
var memoryBuilder = new MemoryBuilder()
    .WithMemoryStore(new VolatileMemoryStore())
    .WithAzureOpenAITextEmbeddingGeneration("oaiembed", azureEndpoint, apiKey);

var memory = memoryBuilder.Build();

// Initialize IronAI with the kernel and memory configuration
IronDocumentAI.Initialize(kernel, memory);

// Set the license key for Iron Pdf to ensure it functions correctly
License.LicenseKey = "<<enter your IronPdf license key here>>";

// Import a PDF document that will be queried
PdfDocument pdf = PdfDocument.FromFile("wikipedia.pdf");

while (true)
{
    Console.Write("User Input: ");
    string userInput = Console.ReadLine();

    // Query the PDF document using the user input asynchronously,
    // blocking call with `.Result` is generally not recommended due to potential for deadlocks,
    // but is retained here for simplicity. Consider using `await` in an `async` method in production code.
    Task<string> queryTask = pdf.QueryAsync(userInput);
    string response = queryTask.Result;

    Console.WriteLine($"\n{response}");
}

Imports Microsoft.VisualBasic
Imports IronPdf
Imports IronPdf.AI
Imports Microsoft.SemanticKernel
Imports Microsoft.SemanticKernel.Connectors.OpenAI
Imports Microsoft.SemanticKernel.Memory
Imports System
Imports System.Threading.Tasks

' This setup code integrates the OpenAI services using Azure and initializes
' necessary dependencies for processing text and document queries.

' Set up the OpenAI integration with Azure
Private azureEndpoint = "<<enter your azure endpoint here>>"
Private apiKey = "<<enter your azure API key here>>"

' Build and configure the kernel to use OpenAI for text embedding and chat completion
Private builder = Kernel.CreateBuilder().AddAzureOpenAITextEmbeddingGeneration("oaiembed", azureEndpoint, apiKey).AddAzureOpenAIChatCompletion("oaichat", azureEndpoint, apiKey)

Private kernel = builder.Build()

' Set up memory for the semantic kernel, leveraging a simple volatile store.
' Optionally, ChromaMemoryStore can be used for additional features.
Private memoryBuilder = (New MemoryBuilder()).WithMemoryStore(New VolatileMemoryStore()).WithAzureOpenAITextEmbeddingGeneration("oaiembed", azureEndpoint, apiKey)

Private memory = memoryBuilder.Build()

' Initialize IronAI with the kernel and memory configuration
IronDocumentAI.Initialize(kernel, memory)

' Set the license key for Iron Pdf to ensure it functions correctly
License.LicenseKey = "<<enter your IronPdf license key here>>"

' Import a PDF document that will be queried
Dim pdf As PdfDocument = PdfDocument.FromFile("wikipedia.pdf")

Do
	Console.Write("User Input: ")
	Dim userInput As String = Console.ReadLine()

	' Query the PDF document using the user input asynchronously,
	' blocking call with `.Result` is generally not recommended due to potential for deadlocks,
	' but is retained here for simplicity. Consider using `await` in an `async` method in production code.
	Dim queryTask As Task(Of String) = pdf.QueryAsync(userInput)
	Dim response As String = queryTask.Result

	Console.WriteLine($vbLf & "{response}")
Loop