How to Chat with PDFs Using AI via API

In this tutorial, I’ll show you how to leverage an AI chatbot API to interact with PDFs (or other document formats) by uploading them to the Easy-Peasy.AI platform. This step-by-step guide will walk you through the creation of a bot, uploading a source document, testing the bot’s knowledge, and integrating it via API.

Why Chat with PDFs via AI?

Gone are the days of manually combing through lengthy PDF documents to find specific information. AI-powered chatbots allow you to upload a document, ask it a question, and get precise answers in seconds. Whether you’re analyzing financial reports, legal documents, or any kind of structured data, this API-powered solution offers both convenience and flexibility.

Step 1: Create a Chatbot on Easy-Peasy.AI

The first step is to create a chatbot on the Easy-Peasy.AI platform. Once you’re logged in:

1. Navigate to the Bot Creation Page.
2. Configure basic settings for your bot:
   • Select the bot model.
   • Update instructions (to guide the bot's behavior).
   • Adjust temperature settings (to control the bot's creativity).

This configuration ensures your bot is optimized for extracting the information you need.

Step 2: Upload Your PDF as a Knowledge Source

To make your bot smarter, you need to upload knowledge sources it will reference when replying to questions. Here's how:

1. Go to the Knowledge Tab of your bot.
2. Click on Add New Source and select Files.
3. Upload your PDF file (for this example, we’re using Tesla's earnings report).
4. The AI will process the uploaded PDF and make it available for the bot to use.

Note: Along with PDFs, you can upload other formats like CSV, DOCX, or even provide a website URL for AI to crawl.

Step 3: Test the Bot on the Web Interface

Once the PDF is processed, you can test the bot’s ability to answer questions:

1. Open the Bot URL (a shareable link).
2. Ask the bot a question based on the uploaded PDF.
   • Example: "How many vehicles did Tesla produce?"
3. Observe the response. The bot should provide accurate answers based on the data in the document.

Step 4: API Integration

Now comes the fun part—integrating the bot into your application using the Easy-Peasy.AI API. Follow these steps:

Access the API Settings

1. Go to the Integration Tab of your bot.
2. Select API to view the API options. Here you’ll find:
   • A prepared API endpoint.
   • Example code snippets (in multiple languages).
   • Your API key.

Test the API

You can test the API directly from the platform:

1. Paste your question into the input box (e.g., "How many vehicles did Tesla produce?").
2. Click the Test API button and observe the response.

The API will return the same answer as the bot interface.

Use the API with Node.js

Here’s a Node.js example to query the bot via API:

const axios = require("axios");

const main = async () => {
  const response = await axios.post(
    "YOUR_BOT_URL",
    {
      message: "how many vehicles were produced?",
      history: [],
      stream: false,
    },
    {
      headers: {
        "content-type": "application/json",
        "x-api-key": "YOUR_API_KEY",
      },
    }
  );

  console.log(response.data);
};

main();

In this code:

• Replace YOUR_BOT_URL with your bot's URL from the Integration tab.
• Replace YOUR_API_KEY with the API key provided by Easy-Peasy.AI.

Run the script, and you’ll receive a response from the bot with the same accuracy as seen in the web interface.

Step 5: Advanced Features

The API allows for more advanced integrations, such as:

• Adding Chat History: Pass previous conversation history to maintain context during multi-turn conversations.
• Embedding the Bot: Embed the bot’s web interface into your own website.
• Uploading Additional Sources: Add multiple PDFs, text documents, or even crawl entire websites.

Conclusion

By using chatbot API, you can transform static PDFs into dynamic, interactive bots capable of answering questions instantly. Whether you’re building an application, conducting research, or simply looking for an intelligent document assistant, this solution is both accessible and powerful.

If you found this tutorial helpful, feel free to leave a comment or share your own use cases. Let me know if you’d like to see more detailed examples or tutorials on related topics!

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