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Unverified Commit 3b60558d authored by Chayenne's avatar Chayenne Committed by GitHub
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Native api (#1886) 


Co-authored-by: default avatarChayenne <zhaochenyang@g.ucla.edu>
parent 5a9a4f41
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.github/workflows/release-docs.yml
View file @ 3b60558d
...@@ -9,6 +9,10 @@ on: ...@@ -9,6 +9,10 @@ on:
- 'python/sglang/version.py' - 'python/sglang/version.py'
workflow_dispatch: workflow_dispatch:
concurrency:
group: execute-notebook-${{ github.ref }}
cancel-in-progress: true
jobs: jobs:
execute-and-deploy: execute-and-deploy:
runs-on: 1-gpu-runner runs-on: 1-gpu-runner
......
docs/Makefile
View file @ 3b60558d
# Minimal makefile for Sphinx documentation # Minimal makefile for Sphinx documentation
# #
# You can set these variables from the command line, and also # You can set these variables from the terminal, and also
# from the environment for the first two. # from the environment for the first two.
SPHINXOPTS ?= SPHINXOPTS ?=
SPHINXBUILD ?= sphinx-build SPHINXBUILD ?= sphinx-build
......
docs/backend/native_api.ipynb
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...@@ -4,7 +4,7 @@ ...@@ -4,7 +4,7 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"# Native Server API\n", "# Native API\n",
"\n", "\n",
"Apart from the OpenAI compatible API, the SGLang Runtime also provides its native server API. We introduce these following API:\n", "Apart from the OpenAI compatible API, the SGLang Runtime also provides its native server API. We introduce these following API:\n",
"\n", "\n",
...@@ -254,7 +254,7 @@ ...@@ -254,7 +254,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 11, "execution_count": 22,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
......
docs/backend/openai_api_completions.ipynb
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...@@ -36,7 +36,7 @@ ...@@ -36,7 +36,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -69,7 +69,7 @@ ...@@ -69,7 +69,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 2, "execution_count": null,
"metadata": { "metadata": {
"execution": { "execution": {
"iopub.execute_input": "2024-11-01T02:45:16.624550Z", "iopub.execute_input": "2024-11-01T02:45:16.624550Z",
...@@ -110,7 +110,7 @@ ...@@ -110,7 +110,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 3, "execution_count": null,
"metadata": { "metadata": {
"execution": { "execution": {
"iopub.execute_input": "2024-11-01T02:45:18.090228Z", "iopub.execute_input": "2024-11-01T02:45:18.090228Z",
...@@ -151,12 +151,12 @@ ...@@ -151,12 +151,12 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"Streaming mode is also supported" "Streaming mode is also supported."
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 4, "execution_count": null,
"metadata": { "metadata": {
"execution": { "execution": {
"iopub.execute_input": "2024-11-01T02:45:21.195226Z", "iopub.execute_input": "2024-11-01T02:45:21.195226Z",
...@@ -190,7 +190,7 @@ ...@@ -190,7 +190,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 5, "execution_count": null,
"metadata": { "metadata": {
"execution": { "execution": {
"iopub.execute_input": "2024-11-01T02:45:21.676813Z", "iopub.execute_input": "2024-11-01T02:45:21.676813Z",
...@@ -226,7 +226,7 @@ ...@@ -226,7 +226,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 6, "execution_count": null,
"metadata": { "metadata": {
"execution": { "execution": {
"iopub.execute_input": "2024-11-01T02:45:23.186337Z", "iopub.execute_input": "2024-11-01T02:45:23.186337Z",
...@@ -272,7 +272,7 @@ ...@@ -272,7 +272,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 7, "execution_count": null,
"metadata": { "metadata": {
"execution": { "execution": {
"iopub.execute_input": "2024-11-01T02:45:26.772016Z", "iopub.execute_input": "2024-11-01T02:45:26.772016Z",
...@@ -334,7 +334,7 @@ ...@@ -334,7 +334,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 8, "execution_count": null,
"metadata": { "metadata": {
"execution": { "execution": {
"iopub.execute_input": "2024-11-01T02:45:26.796422Z", "iopub.execute_input": "2024-11-01T02:45:26.796422Z",
...@@ -389,7 +389,7 @@ ...@@ -389,7 +389,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 9, "execution_count": null,
"metadata": { "metadata": {
"execution": { "execution": {
"iopub.execute_input": "2024-11-01T02:45:29.812339Z", "iopub.execute_input": "2024-11-01T02:45:29.812339Z",
...@@ -472,7 +472,7 @@ ...@@ -472,7 +472,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 10, "execution_count": null,
"metadata": { "metadata": {
"execution": { "execution": {
"iopub.execute_input": "2024-11-01T02:45:54.854018Z", "iopub.execute_input": "2024-11-01T02:45:54.854018Z",
...@@ -567,7 +567,7 @@ ...@@ -567,7 +567,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 6, "execution_count": 11,
"metadata": { "metadata": {
"execution": { "execution": {
"iopub.execute_input": "2024-11-01T02:46:07.896114Z", "iopub.execute_input": "2024-11-01T02:46:07.896114Z",
...@@ -587,6 +587,18 @@ ...@@ -587,6 +587,18 @@
"display_name": "Python 3 (ipykernel)", "display_name": "Python 3 (ipykernel)",
"language": "python", "language": "python",
"name": "python3" "name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.7"
} }
}, },
"nbformat": 4, "nbformat": 4,
......
docs/backend/openai_api_vision.ipynb
View file @ 3b60558d
...@@ -36,7 +36,7 @@ ...@@ -36,7 +36,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 13, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -63,21 +63,19 @@ ...@@ -63,21 +63,19 @@
"source": [ "source": [
"## Using cURL\n", "## Using cURL\n",
"\n", "\n",
"Once the server is up, you can send test requests using curl." "Once the server is up, you can send test requests using curl or requests."
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 15, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"import subprocess\n", "import subprocess\n",
"\n", "\n",
"curl_command = \"\"\"\n", "curl_command = \"\"\"\n",
"curl http://localhost:30010/v1/chat/completions \\\n", "curl -s http://localhost:30010/v1/chat/completions \\\n",
" -H \"Content-Type: application/json\" \\\n",
" -H \"Authorization: Bearer None\" \\\n",
" -d '{\n", " -d '{\n",
" \"model\": \"meta-llama/Llama-3.2-11B-Vision-Instruct\",\n", " \"model\": \"meta-llama/Llama-3.2-11B-Vision-Instruct\",\n",
" \"messages\": [\n", " \"messages\": [\n",
...@@ -105,18 +103,61 @@ ...@@ -105,18 +103,61 @@
"print_highlight(response)" "print_highlight(response)"
] ]
}, },
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Using OpenAI Compatible API w/ Requests"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import requests\n",
"\n",
"url = \"http://localhost:30010/v1/chat/completions\"\n",
"\n",
"data = {\n",
" \"model\": \"meta-llama/Llama-3.2-11B-Vision-Instruct\",\n",
" \"messages\": [\n",
" {\n",
" \"role\": \"user\",\n",
" \"content\": [\n",
" {\n",
" \"type\": \"text\",\n",
" \"text\": \"What’s in this image?\"\n",
" },\n",
" {\n",
" \"type\": \"image_url\",\n",
" \"image_url\": {\n",
" \"url\": \"https://github.com/sgl-project/sglang/blob/main/test/lang/example_image.png?raw=true\"\n",
" }\n",
" }\n",
" ]\n",
" }\n",
" ],\n",
" \"max_tokens\": 300\n",
"}\n",
"\n",
"response = requests.post(url, json=data)\n",
"print_highlight(response.text)"
]
},
{ {
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"## Using OpenAI Python Client\n", "## Using OpenAI Python Client\n",
"\n", "\n",
"You can use the OpenAI Python API library to send requests." "Also, you can use the OpenAI Python API library to send requests."
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 16, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -160,7 +201,7 @@ ...@@ -160,7 +201,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 11, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -202,7 +243,7 @@ ...@@ -202,7 +243,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 17, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -233,6 +274,18 @@ ...@@ -233,6 +274,18 @@
"display_name": "Python 3 (ipykernel)", "display_name": "Python 3 (ipykernel)",
"language": "python", "language": "python",
"name": "python3" "name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.7"
} }
}, },
"nbformat": 4, "nbformat": 4,
......
docs/backend/embedding_model.ipynb → docs/backend/openai_embedding_api.ipynb
View file @ 3b60558d
...@@ -4,7 +4,7 @@ ...@@ -4,7 +4,7 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"# Embedding Model\n", "# OpenAI APIs - Embedding\n",
"\n", "\n",
"SGLang supports embedding models in the same way as completion models. Here are some example models:\n", "SGLang supports embedding models in the same way as completion models. Here are some example models:\n",
"\n", "\n",
...@@ -62,7 +62,7 @@ ...@@ -62,7 +62,7 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"## Use Curl" "## Using cURL"
] ]
}, },
{ {
...@@ -83,8 +83,6 @@ ...@@ -83,8 +83,6 @@
"text = \"Once upon a time\"\n", "text = \"Once upon a time\"\n",
"\n", "\n",
"curl_text = f\"\"\"curl -s http://localhost:30010/v1/embeddings \\\n", "curl_text = f\"\"\"curl -s http://localhost:30010/v1/embeddings \\\n",
" -H \"Content-Type: application/json\" \\\n",
" -H \"Authorization: Bearer None\" \\\n",
" -d '{{\"model\": \"Alibaba-NLP/gte-Qwen2-7B-instruct\", \"input\": \"{text}\"}}'\"\"\"\n", " -d '{{\"model\": \"Alibaba-NLP/gte-Qwen2-7B-instruct\", \"input\": \"{text}\"}}'\"\"\"\n",
"\n", "\n",
"text_embedding = json.loads(subprocess.check_output(curl_text, shell=True))[\"data\"][0][\n", "text_embedding = json.loads(subprocess.check_output(curl_text, shell=True))[\"data\"][0][\n",
...@@ -98,7 +96,37 @@ ...@@ -98,7 +96,37 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"## Using OpenAI Compatible API" "## Using OpenAI Compatible API w/ Requests"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import requests\n",
"\n",
"text = \"Once upon a time\"\n",
"\n",
"response = requests.post(\n",
" \"http://localhost:30010/v1/embeddings\",\n",
" json={\n",
" \"model\": \"Alibaba-NLP/gte-Qwen2-7B-instruct\",\n",
" \"input\": text\n",
" }\n",
")\n",
"\n",
"text_embedding = response.json()[\"data\"][0][\"embedding\"]\n",
"\n",
"print_highlight(f\"Text embedding (first 10): {text_embedding[:10]}\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Using OpenAI Python Client"
] ]
}, },
{ {
...@@ -160,8 +188,6 @@ ...@@ -160,8 +188,6 @@
"input_ids = tokenizer.encode(text)\n", "input_ids = tokenizer.encode(text)\n",
"\n", "\n",
"curl_ids = f\"\"\"curl -s http://localhost:30010/v1/embeddings \\\n", "curl_ids = f\"\"\"curl -s http://localhost:30010/v1/embeddings \\\n",
" -H \"Content-Type: application/json\" \\\n",
" -H \"Authorization: Bearer None\" \\\n",
" -d '{{\"model\": \"Alibaba-NLP/gte-Qwen2-7B-instruct\", \"input\": {json.dumps(input_ids)}}}'\"\"\"\n", " -d '{{\"model\": \"Alibaba-NLP/gte-Qwen2-7B-instruct\", \"input\": {json.dumps(input_ids)}}}'\"\"\"\n",
"\n", "\n",
"input_ids_embedding = json.loads(subprocess.check_output(curl_ids, shell=True))[\"data\"][\n", "input_ids_embedding = json.loads(subprocess.check_output(curl_ids, shell=True))[\"data\"][\n",
...@@ -173,7 +199,7 @@ ...@@ -173,7 +199,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 5, "execution_count": null,
"metadata": { "metadata": {
"execution": { "execution": {
"iopub.execute_input": "2024-11-01T02:48:01.875204Z", "iopub.execute_input": "2024-11-01T02:48:01.875204Z",
......
docs/index.rst
View file @ 3b60558d
...@@ -25,6 +25,7 @@ The core features include: ...@@ -25,6 +25,7 @@ The core features include:
backend/openai_api_completions.ipynb backend/openai_api_completions.ipynb
backend/openai_api_vision.ipynb backend/openai_api_vision.ipynb
backend/openai_embedding_api.ipynb
backend/native_api.ipynb backend/native_api.ipynb
backend/backend.md backend/backend.md
......
docs/start/send_request.ipynb
View file @ 3b60558d
...@@ -22,12 +22,12 @@ ...@@ -22,12 +22,12 @@
"--port 30000 --host 0.0.0.0\n", "--port 30000 --host 0.0.0.0\n",
"```\n", "```\n",
"\n", "\n",
"in your terminal and wait for the server to be ready." "in your terminal and wait for the server to be ready. Once the server is running, you can send test requests using curl or requests. The server implements the [OpenAI-compatible API](https://platform.openai.com/docs/api-reference/chat)."
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 7, "execution_count": null,
"metadata": { "metadata": {
"execution": { "execution": {
"iopub.execute_input": "2024-11-01T02:46:13.611212Z", "iopub.execute_input": "2024-11-01T02:46:13.611212Z",
...@@ -59,14 +59,36 @@ ...@@ -59,14 +59,36 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"## Send a Request\n", "## Using cURL\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import subprocess, json\n",
"\n", "\n",
"Once the server is up, you can send test requests using curl. The server implements the [OpenAI-compatible API](https://platform.openai.com/docs/api-reference/)." "curl_command = \"\"\"\n",
"curl -s http://localhost:30000/v1/chat/completions \\\n",
" -d '{\"model\": \"meta-llama/Meta-Llama-3.1-8B-Instruct\", \"messages\": [{\"role\": \"system\", \"content\": \"You are a helpful assistant.\"}, {\"role\": \"user\", \"content\": \"What is a LLM?\"}]}'\n",
"\"\"\"\n",
"\n",
"response = json.loads(subprocess.check_output(curl_command, shell=True))\n",
"print_highlight(response)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Using OpenAI Compatible API w/ Requests"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 9, "execution_count": null,
"metadata": { "metadata": {
"execution": { "execution": {
"iopub.execute_input": "2024-11-01T02:46:42.813656Z", "iopub.execute_input": "2024-11-01T02:46:42.813656Z",
...@@ -77,30 +99,20 @@ ...@@ -77,30 +99,20 @@
}, },
"outputs": [], "outputs": [],
"source": [ "source": [
"import subprocess\n", "import requests\n",
"\n", "\n",
"curl_command = \"\"\"\n", "url = \"http://localhost:30000/v1/chat/completions\"\n",
"curl http://localhost:30000/v1/chat/completions \\\\\n", "\n",
" -H \"Content-Type: application/json\" \\\\\n", "data = {\n",
" -H \"Authorization: Bearer None\" \\\\\n",
" -d '{\n",
" \"model\": \"meta-llama/Meta-Llama-3.1-8B-Instruct\",\n", " \"model\": \"meta-llama/Meta-Llama-3.1-8B-Instruct\",\n",
" \"messages\": [\n", " \"messages\": [\n",
" {\n", " {\"role\": \"system\", \"content\": \"You are a helpful assistant.\"},\n",
" \"role\": \"system\",\n", " {\"role\": \"user\", \"content\": \"What is a LLM?\"}\n",
" \"content\": \"You are a helpful assistant.\"\n",
" },\n",
" {\n",
" \"role\": \"user\",\n",
" \"content\": \"What is an LLM? Tell me in one sentence.\"\n",
" }\n",
" ]\n", " ]\n",
" }'\n", "}\n",
"\"\"\"\n",
"\n", "\n",
"response = subprocess.check_output(curl_command, shell=True).decode()\n", "response = requests.post(url, json=data)\n",
"\n", "print_highlight(response.json())"
"print_highlight(response)"
] ]
}, },
{ {
...@@ -109,12 +121,12 @@ ...@@ -109,12 +121,12 @@
"source": [ "source": [
"## Using OpenAI Python Client\n", "## Using OpenAI Python Client\n",
"\n", "\n",
"You can use the OpenAI Python API library to send requests." "You can also use the OpenAI Python API library to send requests."
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 3, "execution_count": null,
"metadata": { "metadata": {
"execution": { "execution": {
"iopub.execute_input": "2024-11-01T02:46:51.439372Z", "iopub.execute_input": "2024-11-01T02:46:51.439372Z",
...@@ -138,7 +150,6 @@ ...@@ -138,7 +150,6 @@
" temperature=0,\n", " temperature=0,\n",
" max_tokens=64,\n", " max_tokens=64,\n",
")\n", ")\n",
"\n",
"print_highlight(response)" "print_highlight(response)"
] ]
}, },
...@@ -148,13 +159,12 @@ ...@@ -148,13 +159,12 @@
"source": [ "source": [
"## Using Native Generation APIs\n", "## Using Native Generation APIs\n",
"\n", "\n",
"You can also use the native `/generate` endpoint. It provides more flexiblity.\n", "You can also use the native `/generate` endpoint with requests, which provides more flexiblity. An API reference is available at [Sampling Parameters](https://sgl-project.github.io/references/sampling_params.html)."
"An API reference is available at [Sampling Parameters](https://sgl-project.github.io/references/sampling_params.html)."
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 5, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -196,6 +206,18 @@ ...@@ -196,6 +206,18 @@
"display_name": "Python 3 (ipykernel)", "display_name": "Python 3 (ipykernel)",
"language": "python", "language": "python",
"name": "python3" "name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.7"
} }
}, },
"nbformat": 4, "nbformat": 4,
......
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