[Docs] Sync docs_new with legacy docs and update migration redirects (#23337)
Co-authored-by: Mingyi <wisclmy0611@gmail.com>
This commit is contained in:
@@ -10,7 +10,7 @@
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"\n",
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"- `/generate` (text generation model)\n",
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"- `/get_model_info`\n",
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"- `/get_server_info`\n",
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"- `/server_info`\n",
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"- `/health`\n",
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"- `/health_generate`\n",
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"- `/flush_cache`\n",
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@@ -49,7 +49,7 @@
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" \"python3 -m sglang.launch_server --model-path qwen/qwen2.5-0.5b-instruct --host 0.0.0.0 --log-level warning\"\n",
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")\n",
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"\n",
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"wait_for_server(f\"http://localhost:{port}\")"
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"wait_for_server(f\"http://localhost:{port}\", process=server_process)"
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]
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},
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{
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@@ -57,7 +57,7 @@
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"metadata": {},
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"source": [
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"## Generate (text generation model)\n",
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"Generate completions. This is similar to the `/v1/completions` in OpenAI API. Detailed parameters can be found in the [sampling parameters](sampling_params)."
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"Generate completions. This is similar to the `/v1/completions` in OpenAI API. Detailed parameters can be found in the [sampling parameters](sampling_params.md)."
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]
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},
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{
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@@ -140,7 +140,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"url = f\"http://localhost:{port}/get_server_info\"\n",
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"url = f\"http://localhost:{port}/server_info\"\n",
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"\n",
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"response = requests.get(url)\n",
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"print_highlight(response.text)"
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@@ -185,7 +185,15 @@
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"source": [
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"## Flush Cache\n",
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"\n",
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"Flush the radix cache. It will be automatically triggered when the model weights are updated by the `/update_weights` API."
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"Flush the radix cache. It will be automatically triggered when the model weights are updated by the `/update_weights` API.\n",
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"\n",
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"Parameters:\n",
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"- `timeout` (query, float, default `0`, unit: seconds): Wait time for idle state before flushing. `0` means fail fast if not idle. When HiCache async operations are in-flight, a non-zero timeout allows the server to wait until idle before flushing, avoiding unnecessary 400 errors.\n",
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"\n",
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"```bash\n",
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"# With timeout (wait up to 30s for idle state)\n",
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"curl -s -X POST \"http://127.0.0.1:30000/flush_cache?timeout=30\"\n",
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"```"
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]
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},
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{
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@@ -265,7 +273,7 @@
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"source": [
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"## Encode (embedding model)\n",
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"\n",
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"Encode text into embeddings. Note that this API is only available for [embedding models](openai_api_embeddings) and will raise an error for generation models.\n",
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"Encode text into embeddings. Note that this API is only available for [embedding models](openai_api_embeddings.ipynb) and will raise an error for generation models.\n",
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"Therefore, we launch a new server to server an embedding model."
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]
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},
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@@ -280,7 +288,7 @@
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" --host 0.0.0.0 --is-embedding --log-level warning\n",
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"\"\"\")\n",
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"\n",
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"wait_for_server(f\"http://localhost:{port}\")"
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"wait_for_server(f\"http://localhost:{port}\", process=embedding_process)"
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]
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},
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{
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@@ -327,7 +335,7 @@
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" --host 0.0.0.0 --disable-radix-cache --chunked-prefill-size -1 --attention-backend triton --is-embedding --log-level warning\n",
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"\"\"\")\n",
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"\n",
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"wait_for_server(f\"http://localhost:{port}\")"
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"wait_for_server(f\"http://localhost:{port}\", process=reranker_process)"
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]
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},
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{
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@@ -393,7 +401,7 @@
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" --host 0.0.0.0 --log-level warning\n",
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"\"\"\")\n",
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"\n",
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"wait_for_server(f\"http://localhost:{port}\")"
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"wait_for_server(f\"http://localhost:{port}\", process=score_process)"
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]
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},
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{
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@@ -454,7 +462,7 @@
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"python3 -m sglang.launch_server --model-path Skywork/Skywork-Reward-Llama-3.1-8B-v0.2 --host 0.0.0.0 --is-embedding --log-level warning\n",
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"\"\"\")\n",
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"\n",
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"wait_for_server(f\"http://localhost:{port}\")"
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"wait_for_server(f\"http://localhost:{port}\", process=reward_process)"
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]
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},
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{
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@@ -518,7 +526,7 @@
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" \"python3 -m sglang.launch_server --model-path Qwen/Qwen1.5-MoE-A2.7B --host 0.0.0.0 --expert-distribution-recorder-mode stat --log-level warning\"\n",
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")\n",
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"\n",
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"wait_for_server(f\"http://localhost:{port}\")"
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"wait_for_server(f\"http://localhost:{port}\", process=expert_record_server_process)"
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]
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},
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{
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@@ -571,7 +579,7 @@
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"python3 -m sglang.launch_server --model-path qwen/qwen2.5-0.5b-instruct\n",
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"\"\"\")\n",
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"\n",
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"wait_for_server(f\"http://localhost:{port}\")"
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"wait_for_server(f\"http://localhost:{port}\", process=tokenizer_free_server_process)"
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]
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},
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{
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