# Deduplicate RAG Documents with Content Hashes

**Use case:** 

Extract clean text from a public static page with its source URL, retrieval time and SHA-256 content fingerprint. Use the hash to identify unchanged documents before re-indexing a RAG knowledge base. This verified example uses example.com; compare hashes between runs in your workflow.

## Input

```json
{
  "urls": [
    "https://example.com/"
  ]
}
```

## Output

```json
{
  "url": {
    "label": "Source",
    "format": "link"
  },
  "title": {
    "label": "Title",
    "format": "text"
  },
  "characters": {
    "label": "Characters",
    "format": "number"
  },
  "text": {
    "label": "Text",
    "format": "text"
  },
  "status": {
    "label": "Status"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Web Page Text Extractor for AI & RAG Actor is ready to run with the inputs already set for "Deduplicate RAG Documents with Content Hashes". [Sign up or log in](https://console.apify.com/create-task-from-example/L5rOQdAdPkZxQrhLs) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Deduplicate RAG Documents with Content Hashes" task

The Web Page Text Extractor for AI & RAG Actor will start running based on the input automatically. You can also change all the input fields, like public page urls, to match your specific use case.

### 3. Receive the "Deduplicate RAG Documents with Content Hashes" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as source, title, characters, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Deduplicate RAG Documents with Content Hashes" task via API](https://apify.com/riparazionecomputerecellulari/my-actor.md).

## About this Actor

This example demonstrates how to use [Web Page Text Extractor for AI & RAG](https://apify.com/riparazionecomputerecellulari/my-actor.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/riparazionecomputerecellulari/my-actor.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/riparazionecomputerecellulari/my-actor.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).