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[Docs] Reduce custom syntax used in docs (#27009)

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Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
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Harry Mellor
2025-10-17 04:05:34 +01:00
committed by GitHub
parent 965c5f4914
commit 4ffd6e8942
65 changed files with 381 additions and 402 deletions
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2
docs/deployment/frameworks/anyscale.md
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@@ -5,7 +5,7 @@
[Anyscale](https://www.anyscale.com) is a managed, multi-cloud platform developed by the creators of Ray.
Anyscale automates the entire lifecycle of Ray clusters in your AWS, GCP, or Azure account, delivering the flexibility of open-source Ray
without the operational overhead of maintaining Kubernetes control planes, configuring autoscalers, managing observability stacks, or manually managing head and worker nodes with helper scripts like <gh-file:examples/online_serving/run_cluster.sh>.
without the operational overhead of maintaining Kubernetes control planes, configuring autoscalers, managing observability stacks, or manually managing head and worker nodes with helper scripts like [examples/online_serving/run_cluster.sh](../../../examples/online_serving/run_cluster.sh).
When serving large language models with vLLM, Anyscale can rapidly provision [production-ready HTTPS endpoints](https://docs.anyscale.com/examples/deploy-ray-serve-llms) or [fault-tolerant batch inference jobs](https://docs.anyscale.com/examples/ray-data-llm).

4
docs/deployment/frameworks/retrieval_augmented_generation.md
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@@ -36,7 +36,7 @@ pip install -U vllm \
vllm serve qwen/Qwen1.5-0.5B-Chat --port 8001
```
1. Use the script: <gh-file:examples/online_serving/retrieval_augmented_generation_with_langchain.py>
1. Use the script: [examples/online_serving/retrieval_augmented_generation_with_langchain.py](../../../examples/online_serving/retrieval_augmented_generation_with_langchain.py)
1. Run the script
@@ -74,7 +74,7 @@ pip install vllm \
vllm serve qwen/Qwen1.5-0.5B-Chat --port 8001
```
1. Use the script: <gh-file:examples/online_serving/retrieval_augmented_generation_with_llamaindex.py>
1. Use the script: [examples/online_serving/retrieval_augmented_generation_with_llamaindex.py](../../../examples/online_serving/retrieval_augmented_generation_with_llamaindex.py)
1. Run the script:

2
docs/deployment/frameworks/streamlit.md
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@@ -20,7 +20,7 @@ pip install vllm streamlit openai
vllm serve Qwen/Qwen1.5-0.5B-Chat
```
1. Use the script: <gh-file:examples/online_serving/streamlit_openai_chatbot_webserver.py>
1. Use the script: [examples/online_serving/streamlit_openai_chatbot_webserver.py](../../../examples/online_serving/streamlit_openai_chatbot_webserver.py)
1. Start the streamlit web UI and start to chat: