Docs: improve link to docs (#3860)
Co-authored-by: Chayenne <zhaochen20@outlook.com>
This commit is contained in:
@@ -26,7 +26,7 @@
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"\n",
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"Launch the server in your terminal and wait for it to initialize.\n",
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"\n",
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"**Remember to add `--chat-template llama_3_vision` to specify the vision chat template, otherwise the server only supports text, and performance degradation may occur.**\n",
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"**Remember to add** `--chat-template llama_3_vision` **to specify the vision chat template, otherwise the server only supports text, and performance degradation may occur.**\n",
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"\n",
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"We need to specify `--chat-template` for vision language models because the chat template provided in Hugging Face tokenizer only supports text."
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]
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@@ -46,7 +46,7 @@
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"\n",
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"from sglang.utils import wait_for_server, print_highlight, terminate_process\n",
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"\n",
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"embedding_process, port = launch_server_cmd(\n",
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"vision_process, port = launch_server_cmd(\n",
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" \"\"\"\n",
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"python3 -m sglang.launch_server --model-path meta-llama/Llama-3.2-11B-Vision-Instruct \\\n",
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" --chat-template=llama_3_vision\n",
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@@ -245,7 +245,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"terminate_process(embedding_process)"
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"terminate_process(vision_process)"
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]
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},
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{
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@@ -52,7 +52,7 @@ Please consult the documentation below to learn more about the parameters you ma
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* `chat_template`: The chat template to use. Deviating from the default might lead to unexpected responses. For multi-modal chat templates, refer to [here](https://docs.sglang.ai/backend/openai_api_vision.html#Chat-Template).
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* `is_embedding`: Set to true to perform [embedding](https://docs.sglang.ai/backend/openai_api_embeddings.html) / [encode](https://docs.sglang.ai/backend/native_api.html#Encode-(embedding-model)) and [reward](https://docs.sglang.ai/backend/native_api.html#Classify-(reward-model)) tasks.
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* `revision`: Adjust if a specific version of the model should be used.
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* `skip_tokenizer_init`: Set to true to provide the tokens to the engine and get the output tokens directly, typically used in RLHF.
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* `skip_tokenizer_init`: Set to true to provide the tokens to the engine and get the output tokens directly, typically used in RLHF. Please see this [example for reference](https://github.com/sgl-project/sglang/blob/main/examples/runtime/engine/input_ids.py).
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* `json_model_override_args`: Override model config with the provided JSON.
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* `delete_ckpt_after_loading`: Delete the model checkpoint after loading the model.
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@@ -27,11 +27,13 @@ The router supports two working modes:
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This will be a drop-in replacement for the existing `--dp-size` argument of SGLang Runtime. Under the hood, it uses multi-processes to launch multiple workers, wait for them to be ready, then connect the router to all workers.
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```bash
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$ python -m sglang_router.launch_server --model-path meta-llama/Meta-Llama-3.1-8B-Instruct --dp-size 1
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python -m sglang_router.launch_server --model-path meta-llama/Meta-Llama-3.1-8B-Instruct --dp-size 4
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```
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After the server is ready, you can directly send requests to the router as the same way as sending requests to each single worker.
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Please adjust the batchsize accordingly to archieve maximum throughput.
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```python
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import requests
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@@ -47,7 +49,7 @@ print(response.json())
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This is useful for multi-node DP. First, launch workers on multiple nodes, then launch a router on the main node, and connect the router to all workers.
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```bash
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$ python -m sglang_router.launch_router --worker-urls http://worker_url_1 http://worker_url_2
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python -m sglang_router.launch_router --worker-urls http://worker_url_1 http://worker_url_2
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```
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## Dynamic Scaling APIs
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@@ -59,15 +61,17 @@ We offer `/add_worker` and `/remove_worker` APIs to dynamically add or remove wo
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Usage:
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```bash
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$ curl -X POST http://localhost:30000/add_worker?url=http://worker_url_1
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curl -X POST http://localhost:30000/add_worker?url=http://worker_url_1
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```
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Example:
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```bash
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$ python -m sglang.launch_server --model-path meta-llama/Meta-Llama-3.1-8B-Instruct --port 30001
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$ curl -X POST http://localhost:30000/add_worker?url=http://127.0.0.1:30001
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Successfully added worker: http://127.0.0.1:30001
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python -m sglang.launch_server --model-path meta-llama/Meta-Llama-3.1-8B-Instruct --port 30001
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curl -X POST http://localhost:30000/add_worker?url=http://127.0.0.1:30001
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# Successfully added worker: http://127.0.0.1:30001
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```
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- `/remove_worker`
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@@ -75,14 +79,15 @@ Successfully added worker: http://127.0.0.1:30001
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Usage:
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```bash
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$ curl -X POST http://localhost:30000/remove_worker?url=http://worker_url_1
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curl -X POST http://localhost:30000/remove_worker?url=http://worker_url_1
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```
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Example:
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```bash
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$ curl -X POST http://localhost:30000/remove_worker?url=http://127.0.0.1:30001
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Successfully removed worker: http://127.0.0.1:30001
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curl -X POST http://localhost:30000/remove_worker?url=http://127.0.0.1:30001
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# Successfully removed worker: http://127.0.0.1:30001
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```
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Note:
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