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[Docs] Sync docs_new with legacy docs and update migration redirects (#23337)

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Co-authored-by: Mingyi <wisclmy0611@gmail.com>
This commit is contained in:
zijiexia
2026-04-21 00:15:17 -07:00
committed by GitHub
co-authored by Mingyi
parent f63def8510
commit 900aad5f72
179 changed files with 16014 additions and 8162 deletions
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docs_new/docs/references/frontend/frontend_tutorial.ipynb
+4 -4
View File
@@ -42,7 +42,7 @@
" \"python -m sglang.launch_server --model-path Qwen/Qwen2.5-7B-Instruct --host 0.0.0.0 --log-level warning\"\n",
")\n",
"\n",
"wait_for_server(f\"http://localhost:{port}\")\n",
"wait_for_server(f\"http://localhost:{port}\", process=server_process)\n",
"print(f\"Server started on http://localhost:{port}\")"
]
},
@@ -385,7 +385,7 @@
"## Multi-modal Generation\n",
"\n",
"You may use SGLang frontend language to define multi-modal prompts.\n",
"See [here](https://docs.sglang.io/supported_models/generative_models.html) for supported models."
"See [here](https://docs.sglang.io/supported_models/text_generation/multimodal_language_models.html) for supported models."
]
},
{
@@ -398,7 +398,7 @@
" \"python -m sglang.launch_server --model-path Qwen/Qwen2.5-VL-7B-Instruct --host 0.0.0.0 --log-level warning\"\n",
")\n",
"\n",
"wait_for_server(f\"http://localhost:{port}\")\n",
"wait_for_server(f\"http://localhost:{port}\", process=server_process)\n",
"print(f\"Server started on http://localhost:{port}\")"
]
},
@@ -430,7 +430,7 @@
" s += assistant(gen(\"answer\", max_tokens=256))\n",
"\n",
"\n",
"image_url = \"https://github.com/sgl-project/sglang/blob/main/examples/assets/example_image.png?raw=true\"\n",
"image_url = \"https://raw.githubusercontent.com/sgl-project/sglang/main/examples/assets/example_image.png\"\n",
"image_bytes, _ = load_image(image_url)\n",
"state = image_qa(image_bytes, \"What is in the image?\")\n",
"print_highlight(state[\"answer\"])"
docs_new/docs/references/frontend/frontend_tutorial.mdx
+5 -36
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@@ -5,13 +5,10 @@ metatags:
---
SGLang frontend language can be used to define simple and easy prompts in a convenient, structured way.
## Launch A Server
Launch the server in your terminal and wait for it to initialize.
```python Example
from sglang import assistant_begin, assistant_end
from sglang import assistant, function, gen, system, user
@@ -26,14 +23,12 @@ server_process, port = launch_server_cmd(
"python -m sglang.launch_server --model-path Qwen/Qwen2.5-7B-Instruct --host 0.0.0.0 --log-level warning"
)
wait_for_server(f"http://localhost:{port}")
wait_for_server(f"http://localhost:{port}", process=server_process)
print(f"Server started on http://localhost:{port}")
```
Set the default backend. Note: Besides the local server, you may use also `OpenAI` or other API endpoints.
```python Example
set_default_backend(RuntimeEndpoint(f"http://localhost:{port}"))
```
@@ -42,8 +37,6 @@ set_default_backend(RuntimeEndpoint(f"http://localhost:{port}"))
The most simple way of using SGLang frontend language is a simple question answer dialog between a user and an assistant.
```python Example
@function
def basic_qa(s, question):
@@ -52,7 +45,6 @@ def basic_qa(s, question):
s += assistant(gen("answer", max_tokens=512))
```
```python Example
state = basic_qa("List 3 countries and their capitals.")
print_highlight(state["answer"])
@@ -62,8 +54,6 @@ print_highlight(state["answer"])
SGLang frontend language can also be used to define multi-turn dialogs.
```python Example
@function
def multi_turn_qa(s):
@@ -84,8 +74,6 @@ print_highlight(state["second_answer"])
You may use any Python code within the function to define more complex control flows.
```python Example
@function
def tool_use(s, question):
@@ -112,8 +100,6 @@ print_highlight(state["expression"])
Use `fork` to launch parallel prompts. Because `sgl.gen` is non-blocking, the for loop below issues two generation calls in parallel.
```python Example
@function
def tip_suggestion(s):
@@ -144,8 +130,6 @@ print_highlight(state["summary"])
Use `regex` to specify a regular expression as a decoding constraint. This is only supported for local models.
```python Example
@function
def regular_expression_gen(s):
@@ -165,8 +149,6 @@ print_highlight(state["answer"])
Use `regex` to define a `JSON` decoding schema.
```python Example
character_regex = (
r"""\{\n"""
@@ -202,8 +184,6 @@ print_highlight(state["json_output"])
Use `run_batch` to run a batch of prompts.
```python Example
@function
def text_qa(s, question):
@@ -228,8 +208,6 @@ for i, state in enumerate(states):
Use `stream` to stream the output to the user.
```python Example
@function
def text_qa(s, question):
@@ -247,9 +225,7 @@ for out in state.text_iter():
## Complex Prompts
You may use `{system|user|assistant}_{begin|end}` to define complex prompts.
You may use `&#123;system|user|assistant&#125;_&#123;begin|end&#125;` to define complex prompts.
```python Example
@function
@@ -269,7 +245,6 @@ state = chat_example()
print_highlight(state["answer"])
```
```python Example
terminate_process(server_process)
```
@@ -277,28 +252,23 @@ terminate_process(server_process)
## Multi-modal Generation
You may use SGLang frontend language to define multi-modal prompts.
See [here](../../supported-models/large-language-models) for supported models.
See [here](../../supported-models/multimodal_language_models) for supported models.
```python Example
server_process, port = launch_server_cmd(
"python -m sglang.launch_server --model-path Qwen/Qwen2.5-VL-7B-Instruct --host 0.0.0.0 --log-level warning"
)
wait_for_server(f"http://localhost:{port}")
wait_for_server(f"http://localhost:{port}", process=server_process)
print(f"Server started on http://localhost:{port}")
```
```python Example
set_default_backend(RuntimeEndpoint(f"http://localhost:{port}"))
```
Ask a question about an image.
```python Example
@function
def image_qa(s, image_file, question):
@@ -306,13 +276,12 @@ def image_qa(s, image_file, question):
s += assistant(gen("answer", max_tokens=256))
image_url = "https://github.com/sgl-project/sglang/blob/main/examples/assets/example_image.png?raw=true"
image_url = "https://raw.githubusercontent.com/sgl-project/sglang/main/examples/assets/example_image.png"
image_bytes, _ = load_image(image_url)
state = image_qa(image_bytes, "What is in the image?")
print_highlight(state["answer"])
```
```python Example
terminate_process(server_process)
```