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Chat with a compact language model for high-quality responses
Tim Dolan
macadeliccc
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Recent Activity
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7 days ago
Automated web scraping with playwright is becoming easier by the day. Now, using ollama tool calling, its possible to perform very high accuracy web scraping (in some cases 100% accurate) through just asking an LLM to scrape the content for you.
This can be completed in a multistep process similar to cohere's platform. If you have tried the cohere playground with web scraping, this will feel very similar. In my experience, the Llama 3.1 version is much better due to the larger context window. Both tools are great, but the difference is the ollama + playwright version is completely controlled by you.
All you need to do is wrap your scraper in a function:
```
async def query_web_scraper(url: str) -> dict:
scraper = WebScraper(headless=False)
return await scraper.query_page_content(url)
```
and then make your request:
```
# First API call: Send the query and function description to the model
response = ollama.chat(
model=model,
messages=messages,
tools=[
{
'type': 'function',
'function': {
'name': 'query_web_scraper',
'description': 'Scrapes the content of a web page and returns the structured JSON object with titles, articles, and associated links.',
'parameters': {
'type': 'object',
'properties': {
'url': {
'type': 'string',
'description': 'The URL of the web page to scrape.',
},
},
'required': ['url'],
},
},
},
]
)
```
To learn more:
Github w/ Playground: https://github.com/tdolan21/tool-calling-playground/blob/main/notebooks/ollama-playwright-web-scraping.ipynb
Complete Guide: https://medium.com/@tdolan21/building-an-llm-powered-web-scraper-with-ollama-and-playwright-6274d5d938b5
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