如何使用 OpenAI for PDF

查克尼特·宾

2024年一月22日

更新 2024年十二月11日

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OpenAI是一个人工智能研究实验室，由营利性的OpenAI LP和其非营利性的母公司OpenAI Inc组成。它的成立目标是以一种造福全人类的方式推进数字智能的发展。 OpenAI 在人工智能的多个领域进行研究。(人工智能)并旨在开发安全、有益且易于获取的人工智能技术。

"(《世界人权宣言》)IronPdf.Extensions.AINuGet 包现在支持 OpenAI 进行 PDF 增强：摘要、查询和记忆。该软件包使用Microsoft语义内核.

开始使用IronPDF

立即在您的项目中开始使用IronPDF，并享受免费试用。

第一步：

如何使用 OpenAI for PDF

下载 C# 库以利用 OpenAI for PDF
为 OpenAI 准备 Azure 端点和 API 密钥
导入目标 PDF 文档
使用 总结 方法生成 PDF 摘要
使用 查询 连续查询方法

立即在您的项目中开始使用IronPDF，并享受免费试用。

第一步：

除了IronPdf此外，您还需要以下两个软件包：

总结PDF示例

要使用 OpenAI 功能，需要一个 Azure 端点和一个 API 密钥。根据下面的代码示例配置语义内核。导入PDF文档并使用Summarize方法生成PDF文档的摘要。您可以从OpenAI for PDF 摘要示例.

请注意

您将遇到 SKEXP0001、SKEXP0010 和 SKEXP0050 错误。这是因为语义内核方法是试验性的。在您的 .csproj 文件中添加以下代码，以消除这些错误。

<PropertyGroup&gt；

&lt;无警告&gt;美元(NoWarn);SKEXP0001,SKEXP0010,SKEXP0050&lt;/NoWarn&gt;

</PropertyGroup&gt；

:path=/static-assets/pdf/content-code-examples/how-to/openai-summarize.cs

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

// Setup OpenAI
var azureEndpoint = "<<enter your azure endpoint here>>";
var apiKey = "<<enter your azure API key here>>";
var builder = Kernel.CreateBuilder()
    .AddAzureOpenAITextEmbeddingGeneration("oaiembed", azureEndpoint, apiKey)
    .AddAzureOpenAIChatCompletion("oaichat", azureEndpoint, apiKey);
var kernel = builder.Build();

// Setup Memory
var memory_builder = new MemoryBuilder()
    // optionally use new ChromaMemoryStore("http://127.0.0.1:8000") (see https://github.com/microsoft/semantic-kernel/blob/main/dotnet/notebooks/09-memory-with-chroma.ipynb)
    .WithMemoryStore(new VolatileMemoryStore())
    .WithAzureOpenAITextEmbeddingGeneration("oaiembed", azureEndpoint, apiKey);
var memory = memory_builder.Build();

// Initialize IronAI
IronDocumentAI.Initialize(kernel, memory);

License.LicenseKey = "<<enter your IronPdf license key here";

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

// Summarize the document
Console.WriteLine("Please wait while I summarize the document...");
string summary = await pdf.Summarize(); // optionally pass AI instance or use AI instance directly
Console.WriteLine($"Document summary: {summary}\n\n");

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

' Setup OpenAI
Private azureEndpoint = "<<enter your azure endpoint here>>"
Private apiKey = "<<enter your azure API key here>>"
Private builder = Kernel.CreateBuilder().AddAzureOpenAITextEmbeddingGeneration("oaiembed", azureEndpoint, apiKey).AddAzureOpenAIChatCompletion("oaichat", azureEndpoint, apiKey)
Private kernel = builder.Build()

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

' Initialize IronAI
IronDocumentAI.Initialize(kernel, memory)

License.LicenseKey = "<<enter your IronPdf license key here"

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

' Summarize the document
Console.WriteLine("Please wait while I summarize the document...")
Dim summary As String = Await pdf.Summarize() ' optionally pass AI instance or use AI instance directly
Console.WriteLine($"Document summary: {summary}" & vbLf & vbLf)

$vbLabelText $csharpLabel

产出摘要

连续查询示例

一种查询可能不适用于所有场景。 "(《世界人权宣言》)IronPdf.Extensions.AI软件包还提供了一种查询方法，允许用户执行连续查询。

:path=/static-assets/pdf/content-code-examples/how-to/openai-query.cs

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

// Setup OpenAI
var azureEndpoint = "<<enter your azure endpoint here>>";
var apiKey = "<<enter your azure API key here>>";
var builder = Kernel.CreateBuilder()
    .AddAzureOpenAITextEmbeddingGeneration("oaiembed", azureEndpoint, apiKey)
    .AddAzureOpenAIChatCompletion("oaichat", azureEndpoint, apiKey);
var kernel = builder.Build();

// Setup Memory
var memory_builder = new MemoryBuilder()
    // optionally use new ChromaMemoryStore("http://127.0.0.1:8000") (see https://github.com/microsoft/semantic-kernel/blob/main/dotnet/notebooks/09-memory-with-chroma.ipynb)
    .WithMemoryStore(new VolatileMemoryStore())
    .WithAzureOpenAITextEmbeddingGeneration("oaiembed", azureEndpoint, apiKey);
var memory = memory_builder.Build();

// Initialize IronAI
IronDocumentAI.Initialize(kernel, memory);

License.LicenseKey = "<<enter your IronPdf license key here";

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

// Continuous query
while (true)
{
    Console.Write("User Input: ");
    var response = await pdf.Query(Console.ReadLine());
    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

' Setup OpenAI
Private azureEndpoint = "<<enter your azure endpoint here>>"
Private apiKey = "<<enter your azure API key here>>"
Private builder = Kernel.CreateBuilder().AddAzureOpenAITextEmbeddingGeneration("oaiembed", azureEndpoint, apiKey).AddAzureOpenAIChatCompletion("oaichat", azureEndpoint, apiKey)
Private kernel = builder.Build()

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

' Initialize IronAI
IronDocumentAI.Initialize(kernel, memory)

License.LicenseKey = "<<enter your IronPdf license key here"

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

' Continuous query
Do
	Console.Write("User Input: ")
	Dim response = Await pdf.Query(Console.ReadLine())
	Console.WriteLine($vbLf & "{response}")
Loop

$vbLabelText $csharpLabel

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