News RAG Converter
Pricing
from $1.50 / 1,000 results
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News RAG Converter
Transform news articles into clean, structured data for AI pipelines. Strips ads and boilerplate, outputs JSON ready for vector databases and RAG systems.
Pricing
from $1.50 / 1,000 results
Rating
0.0
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Developer
Igor Araujo
Maintained by CommunityActor stats
0
Bookmarked
2
Total users
1
Monthly active users
3 days ago
Last modified
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An Apify Actor that fetches articles from URLs and extracts clean, structured content suitable for RAG (Retrieval-Augmented Generation) and LLM ingestion. Uses trafilatura for intelligent text extraction with a BeautifulSoup fallback.
How It Works
- Fetches each article URL via HTTP
- Extracts content using trafilatura (ML-based extraction) with BeautifulSoup fallback
- Returns clean markdown + structured JSON (title, author, date, full text)
- Optimized for RAG pipelines and LLM context windows
Input
| Field | Type | Description | Default | Required |
|---|---|---|---|---|
urls | array | List of article URLs to process (1-100) | - | Yes |
format | string | Output format: markdown, json, or both | both | No |
Sample Input
{"urls": ["https://example.com/article-1","https://example.com/article-2"],"format": "both"}
Sample Output
Each item in the dataset includes:
{"url": "https://example.com/article-1","title": "Breaking News: Major Discovery","author": "Jane Doe","date": "2026-07-03T12:00:00Z","text_length": 4523,"error": "","fetched_at": "2026-07-03T15:30:00Z","full_text": "The full article text...","markdown": "# Breaking News: Major Discovery\n\n**Author:** Jane Doe\n\n..."}
Use Cases
- Building RAG knowledge bases from news articles
- LLM fine-tuning dataset preparation
- Research and content aggregation
- Automated news digest generation
Pricing
Pay-per-event at $0.002 per result item.