mirror of
https://git.mirrors.martin98.com/https://github.com/mendableai/firecrawl
synced 2025-06-04 11:24:40 +08:00
121 lines
3.7 KiB
Python
121 lines
3.7 KiB
Python
import time
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import nest_asyncio
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import uuid
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import asyncio
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from firecrawl.firecrawl import AsyncFirecrawlApp
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from pydantic import BaseModel, Field
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from typing import List
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app = AsyncFirecrawlApp(api_url="https://api.firecrawl.dev")
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async def example_scrape():
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# Scrape a website:
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scrape_result = await app.scrape_url('example.com', formats=["markdown", "html"])
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print(scrape_result.markdown)
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async def example_batch_scrape():
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# Batch scrape
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urls = ['https://example.com', 'https://docs.firecrawl.dev']
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# Synchronous batch scrape
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batch_result = await app.batch_scrape_urls(urls, formats=["markdown", "html"])
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print("Synchronous Batch Scrape Result:")
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print(batch_result.data[0].markdown)
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# Asynchronous batch scrape
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async_batch_result = await app.async_batch_scrape_urls(urls, formats=["markdown", "html"])
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print("\nAsynchronous Batch Scrape Result:")
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print(async_batch_result)
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async def example_crawl():
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# Crawl a website:
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crawl_result = await app.crawl_url('firecrawl.dev', exclude_paths=['blog/*'])
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print(crawl_result.data[0].markdown)
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# Asynchronous Crawl a website:
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async_result = await app.async_crawl_url('firecrawl.dev', exclude_paths=['blog/*'])
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print(async_result)
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crawl_status = await app.check_crawl_status(async_result.id)
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print(crawl_status)
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attempts = 15
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while attempts > 0 and crawl_status.status != 'completed':
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print(crawl_status)
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crawl_status = await app.check_crawl_status(async_result.id)
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attempts -= 1
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await asyncio.sleep(1) # Use async sleep instead of time.sleep
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crawl_status = await app.check_crawl_status(async_result.id)
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print(crawl_status)
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async def example_llm_extraction():
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# Define schema to extract contents into using pydantic
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class ArticleSchema(BaseModel):
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title: str
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points: int
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by: str
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commentsURL: str
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class TopArticlesSchema(BaseModel):
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top: List[ArticleSchema] = Field(..., description="Top 5 stories")
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extract_config = JsonConfig(schema=TopArticlesSchema.model_json_schema())
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llm_extraction_result = await app.scrape_url('https://news.ycombinator.com', formats=["extract"], extract=extract_config)
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print(llm_extraction_result.extract)
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async def example_map_and_extract():
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# Map a website:
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map_result = await app.map_url('https://firecrawl.dev', search="blog")
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print(map_result)
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# Extract URLs:
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class ExtractSchema(BaseModel):
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title: str
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description: str
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links: List[str]
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# Define the schema using Pydantic
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extract_schema = ExtractSchema.schema()
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# Perform the extraction
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extract_result = await app.extract(['https://firecrawl.dev'], prompt="Extract the title, description, and links from the website", schema=extract_schema)
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print(extract_result)
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# Define event handlers for websocket
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def on_document(detail):
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print("DOC", detail)
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def on_error(detail):
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print("ERR", detail['error'])
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def on_done(detail):
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print("DONE", detail['status'])
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async def example_websocket_crawl():
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# Initiate the crawl job and get the watcher
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watcher = await app.crawl_url_and_watch('firecrawl.dev', { 'excludePaths': ['blog/*'], 'limit': 5 })
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# Add event listeners
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watcher.add_event_listener("document", on_document)
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watcher.add_event_listener("error", on_error)
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watcher.add_event_listener("done", on_done)
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# Start the watcher
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await watcher.connect()
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async def main():
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nest_asyncio.apply()
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await example_scrape()
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await example_batch_scrape()
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await example_crawl()
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await example_llm_extraction()
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await example_map_and_extract()
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await example_websocket_crawl()
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if __name__ == "__main__":
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asyncio.run(main())
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