How to use llm to parse news ?

[GOOD-N-LCM]

Thank you for your project, it is very nice!
But I tried to parse the news using Ollama, and the project could not meet my needs properly.

This my code:

import os
import asyncio
from crawl4ai import AsyncWebCrawler, CacheMode
from crawl4ai.extraction_strategy import LLMExtractionStrategy
from pydantic import BaseModel, Field

class KnowledgeGraph(BaseModel):
title: str
content: str

async def main(url):
async with AsyncWebCrawler(
verbose=True,
user_agent_mode="random",
user_agent_generator_config={
"device_type": "mobile",
"os_type": "android"
},
) as crawler:
result = await crawler.arun(
url=url,
cache_mode=CacheMode.BYPASS,
remove_overlay_elements=True,
word_count_threshold=1,
extraction_strategy=LLMExtractionStrategy(

            provider="ollama/qwen2.5:14b",

            schema=KnowledgeGraph.schema(),
            extraction_type="schema",
            instruction="""Extract title and content from the given text.
            """
        ),            
        bypass_cache=True,
    )
    print(result.extracted_content)

if name == "main":

url = 'https://www.bloomberg.com/news/articles/2025-01-07/nvidia-ceo-unveils-more-powerful-graphics-cards-at-ces-event?srnd=homepage-asia'
asyncio.run(main(url))

[devatbosch]

@GOOD-N-LCM, can you plz specify/elaborate whats the issue you are facing...

I may assist then...