[Docs] Switch to better markdown linting pre-commit hook (#21851)

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

examples/offline_inference/disaggregated-prefill-v1/README.md

@@ -5,6 +5,6 @@ This example contains scripts that demonstrate disaggregated prefill in the offl
 ## Files
 
 - `run.sh` - A helper script that will run `prefill_example.py` and `decode_example.py` sequentially.
-  - Make sure you are in the `examples/offline_inference/disaggregated-prefill-v1` directory before running `run.sh`.
+    - Make sure you are in the `examples/offline_inference/disaggregated-prefill-v1` directory before running `run.sh`.
 - `prefill_example.py` - A script which performs prefill only, saving the KV state to the `local_storage` directory and the prompts to `output.txt`.
 - `decode_example.py` - A script which performs decode only, loading the KV state from the `local_storage` directory and the prompts from `output.txt`.

examples/offline_inference/openai_batch/README.md

@@ -19,9 +19,9 @@ We currently support `/v1/chat/completions`, `/v1/embeddings`, and `/v1/score` e
 ## Pre-requisites
 
 * The examples in this document use `meta-llama/Meta-Llama-3-8B-Instruct`.
-  - Create a [user access token](https://huggingface.co/docs/hub/en/security-tokens)
-  - Install the token on your machine (Run `huggingface-cli login`).
-  - Get access to the gated model by [visiting the model card](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) and agreeing to the terms and conditions.
+    * Create a [user access token](https://huggingface.co/docs/hub/en/security-tokens)
+    * Install the token on your machine (Run `huggingface-cli login`).
+    * Get access to the gated model by [visiting the model card](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) and agreeing to the terms and conditions.
 
 ## Example 1: Running with a local file
 
@@ -105,7 +105,7 @@ To integrate with cloud blob storage, we recommend using presigned urls.
 
 * [Create an S3 bucket](https://docs.aws.amazon.com/AmazonS3/latest/userguide/creating-bucket.html).
 * The `awscli` package (Run `pip install awscli`) to configure your credentials and interactively use s3.
-  - [Configure your credentials](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-quickstart.html).
+    * [Configure your credentials](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-quickstart.html).
 * The `boto3` python package (Run `pip install boto3`) to generate presigned urls.
 
 ### Step 1: Upload your input script

examples/others/lmcache/README.md

@@ -28,16 +28,20 @@ to run disaggregated prefill and benchmark the performance.
 ### Components
 
 #### Server Scripts
+
 - `disagg_prefill_lmcache_v1/disagg_vllm_launcher.sh` - Launches individual vLLM servers for prefill/decode, and also launches the proxy server.
 - `disagg_prefill_lmcache_v1/disagg_proxy_server.py` - FastAPI proxy server that coordinates between prefiller and decoder
 - `disagg_prefill_lmcache_v1/disagg_example_nixl.sh` - Main script to run the example
 
 #### Configuration
+
 - `disagg_prefill_lmcache_v1/configs/lmcache-prefiller-config.yaml` - Configuration for prefiller server
 - `disagg_prefill_lmcache_v1/configs/lmcache-decoder-config.yaml` - Configuration for decoder server
 
 #### Log Files
+
 The main script generates several log files:
+
 - `prefiller.log` - Logs from the prefill server
 - `decoder.log` - Logs from the decode server
 - `proxy.log` - Logs from the proxy server

examples/others/logging_configuration.md

@@ -8,11 +8,11 @@ of logging configurations that range from simple-and-inflexible to
 more-complex-and-more-flexible.
 
 - No vLLM logging (simple and inflexible)
-  - Set `VLLM_CONFIGURE_LOGGING=0` (leaving `VLLM_LOGGING_CONFIG_PATH` unset)
+    - Set `VLLM_CONFIGURE_LOGGING=0` (leaving `VLLM_LOGGING_CONFIG_PATH` unset)
 - vLLM's default logging configuration (simple and inflexible)
-  - Leave `VLLM_CONFIGURE_LOGGING` unset or set `VLLM_CONFIGURE_LOGGING=1`
+    - Leave `VLLM_CONFIGURE_LOGGING` unset or set `VLLM_CONFIGURE_LOGGING=1`
 - Fine-grained custom logging configuration (more complex, more flexible)
-  - Leave `VLLM_CONFIGURE_LOGGING` unset or set `VLLM_CONFIGURE_LOGGING=1` and
+    - Leave `VLLM_CONFIGURE_LOGGING` unset or set `VLLM_CONFIGURE_LOGGING=1` and
     set `VLLM_LOGGING_CONFIG_PATH=<path-to-logging-config.json>`
 
 ## Logging Configuration Environment Variables