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feat(docs): update examples and documentation to replace bypass_cache with cache_mode for improved clarity

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This commit is contained in:
UncleCode
2024-11-17 19:44:45 +08:00
parent a59c107b23
commit df63a40606
17 changed files with 422 additions and 80 deletions
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10
docs/md_v2/tutorial/tutorial.md
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@@ -26,7 +26,7 @@ Here's a condensed outline of the **Installation and Setup** video content:
- Walk through a simple test script to confirm the setup:
```python
import asyncio
from crawl4ai import AsyncWebCrawler
from crawl4ai import AsyncWebCrawler, CacheMode
async def main():
async with AsyncWebCrawler(verbose=True) as crawler:
@@ -1093,7 +1093,7 @@ Here’s a comprehensive outline for the **LLM Extraction Strategy** video, cove
extraction_type="schema",
instruction="Extract model names and fees for input and output tokens from the page."
),
bypass_cache=True
cache_mode=CacheMode.BYPASS
)
print(result.extracted_content)
```
@@ -1139,7 +1139,7 @@ Here’s a comprehensive outline for the **LLM Extraction Strategy** video, cove
result = await crawler.arun(
url="https://example.com/some-article",
extraction_strategy=extraction_strategy,
bypass_cache=True
cache_mode=CacheMode.BYPASS
)
print(result.extracted_content)
```
@@ -1248,7 +1248,7 @@ Here’s a structured outline for the **Cosine Similarity Strategy** video, cove
result = await crawler.arun(
url=url,
extraction_strategy=extraction_strategy,
bypass_cache=True
cache_mode=CacheMode.BYPASS
)
print(result.extracted_content)
```
@@ -1296,7 +1296,7 @@ Here’s a structured outline for the **Cosine Similarity Strategy** video, cove
result = await crawler.arun(
url=url,
extraction_strategy=extraction_strategy,
bypass_cache=True
cache_mode=CacheMode.BYPASS
)
print(result.extracted_content)
```