Web Scraping with Local LLMs using Ollama and WebHarvy

WebHarvy's AI-assisted scraping feature lets you extract unstructured data using a language model. One of the best things about this feature is that you can use a free, locally-running AI model on your own PC, no API key, no subscription, and no data leaving your machine. This guide walks you through setting up Ollama on Windows and connecting it to WebHarvy.

What is Ollama?

Ollama is a free, open-source tool that lets you download and run large language models (LLMs) directly on your Windows, Mac, or Linux PC. Once installed, it runs a local server in the background that applications like WebHarvy can connect to - just like connecting to a cloud AI service, but entirely on your own computer.

This means you get the benefits of AI-assisted web scraping without any ongoing costs or privacy concerns.

Step 1: Install Ollama on Windows

Installing Ollama on Windows is straightforward - just download and run the installer.

1. Open your browser and go to https://ollama.com/download/windows.
2. Click the Download for Windows button. This will download an installer file named something like OllamaSetup.exe.
3. Once downloaded, double-click the installer file to run it.
4. Follow the on-screen prompts and click Install. The installation takes only a minute or two.
5. After installation, Ollama starts automatically and runs silently in the background. You will see the Ollama icon in the Windows system tray (bottom-right of your taskbar).

That's it! Ollama is now installed and running on your PC.

Step 2: Choose an AI Model

Ollama supports a wide range of open-source AI models. You can browse all available models at the official Ollama model library:

https://ollama.com/library

On this page you will find popular models such as Llama 3, Mistral, Phi-3, Gemma, and many others. Each model listing shows the model's size, the hardware requirements, and a description of what it is good at.

For general web scraping and data extraction tasks, a mid-size model like llama3.2 or mistral works well without requiring a high-end GPU. If you have a newer PC with a dedicated graphics card, you can run larger, more capable models.

Once you have picked a model, note down its name (shown in bold on the library page) - you will need it in the next step.

Step 3: Download and Run the Model

To download and start a model, you use the Windows Command Prompt (also called the terminal or command line).

How to open the Command Prompt

1. Press the Windows key on your keyboard (or click the Start button).
2. Type cmd in the search box.
3. Click on Command Prompt in the search results to open it.

A black window with a blinking cursor will appear. This is the Command Prompt.

Run the model

In the Command Prompt window, type the following command and press Enter:

ollama run llama3.2

Replace llama3.2 with the name of whatever model you chose from the library. If the model is not yet downloaded, Ollama will automatically download it first (this may take a few minutes depending on your internet speed and the model size). Once it finishes, the model will start and be ready to accept requests.

You can close the Command Prompt window — the model will continue running in the background, and Ollama will serve it on http://localhost:11434 by default.

Step 4: Connect Ollama to WebHarvy

With Ollama running, open WebHarvy and configure it to use the local model for AI-assisted extraction.

1. In WebHarvy, open Settings (from the main menu or toolbar).
2. Go to the AI tab in the Settings window.
3. Under the AI provider options, select Ollama (or Local LLM / Ollama).
4. In the Server URL field, enter: http://localhost:11434
5. In the Model field, enter the model name you are running — for example, llama3.2.
6. Click Save or OK to apply the settings.

WebHarvy will now use your local Ollama model whenever the AI extraction feature is used. No API key or internet connection is required for the AI part.

For more details, refer to the Web Scraping using AI page.

Step 5: Scrape Using AI in WebHarvy

Once Ollama is connected, you can use AI-assisted extraction while configuring a scrape:

1. In WebHarvy, navigate to the website you want to scrape.
2. Click anywhere on the page to start selecting data.
3. In the selection options that appear, click More Options and then choose Extract with AI.

4. In the dialog that opens, select the area of the page to extract from - either the section highlighted using mouse or the entire page.
5. Choose whether to extract from the displayed text or the underlying HTML code.

6. Type a prompt describing what data you want to extract - for example: "Extract the product rating"
7. Click Extract. WebHarvy will send the content to your local Ollama model and return the extracted data.
8. Click the Add button to add the selected data to your configuration.

This approach is particularly useful for pages with unstructured content, such as extracting summaries, sentiment, or data that does not have a clear repeating HTML structure.

Why Use a Local LLM for Web Scraping?

Free to use - No API costs or subscriptions. Run as many scrapes as you like.
Privacy - Your data never leaves your PC. Ideal for scraping sensitive or confidential sources.
Works offline - Once the model is downloaded, no internet is needed for AI processing.
No rate limits - Cloud AI services often limit how many requests you can make per minute. With a local model, there are no such restrictions.