Stop using title frontmatter and fix doc that can only be reached by search (#20623)

Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>

docs/serving/distributed_serving.md

@@ -1,6 +1,4 @@
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-title: Distributed Inference and Serving
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+# Distributed Inference and Serving
 
 ## How to decide the distributed inference strategy?
 

docs/serving/integrations/langchain.md

@@ -1,6 +1,4 @@
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-title: LangChain
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+# LangChain
 
 vLLM is also available via [LangChain](https://github.com/langchain-ai/langchain) .
 

docs/serving/integrations/llamaindex.md

@@ -1,6 +1,4 @@
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-title: LlamaIndex
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+# LlamaIndex
 
 vLLM is also available via [LlamaIndex](https://github.com/run-llama/llama_index) .
 

docs/serving/offline_inference.md

@@ -1,6 +1,4 @@
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-title: Offline Inference
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+# Offline Inference
 
 Offline inference is possible in your own code using vLLM's [`LLM`][vllm.LLM] class.
 
@@ -23,7 +21,7 @@ The available APIs depend on the model type:
 !!! info
     [API Reference][offline-inference-api]
 
-### Ray Data LLM API
+## Ray Data LLM API
 
 Ray Data LLM is an alternative offline inference API that uses vLLM as the underlying engine.
 This API adds several batteries-included capabilities that simplify large-scale, GPU-efficient inference:

docs/serving/openai_compatible_server.md

@@ -1,6 +1,4 @@
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-title: OpenAI-Compatible Server
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+# OpenAI-Compatible Server
 
 vLLM provides an HTTP server that implements OpenAI's [Completions API](https://platform.openai.com/docs/api-reference/completions), [Chat API](https://platform.openai.com/docs/api-reference/chat), and more! This functionality lets you serve models and interact with them using an HTTP client.