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Small fixes
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docs.json

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"pages": [
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"v4/examples/gpt-oss",
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"v4/examples/openai-compatible-endpoint-vllm",
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"v4/examples/sglang"
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"v4/examples/deploy-a-vision-language-model-with-sglang"
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]
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},
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{

v4/examples/sglang.mdx renamed to v4/examples/deploy-a-vision-language-model-with-sglang.mdx

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In order to score the advertisement, we will be using one of the core differentiators of SGLang, `fork`, which allows us to run many prompts in parallel and bring the results together in the end. This
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allows us to execute alot of simulaneous requests with no increase in total latency. Lastly, we bring these results together and structure them in a specific format to return to the user.
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````python
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```python
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@function
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def analyze_ad(s, image, ad_description, dimensions):
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s += sgl.system("Evaluate an advertisement about an company's description.")

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