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This commit is contained in:
@@ -61,20 +61,21 @@
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- `api_key`:接口访问密钥(同时用于 8000 与 8001)
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- `tensor_parallel_size`:张量并行数,双卡建议 `2`
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- `dtype`:推理精度,默认 `bfloat16`
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- `selected_model`:当前生效模型,留空时回退到 `default_model`
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- `models.selected`:当前生效模型,留空时回退到 `models.default`
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## config.json 说明
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`config.json` 采用以下结构:
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- 顶层 `default_model`:默认模型名
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- 顶层其他键:每个模型的配置档位
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- `models.default`:默认模型名
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- `models.selected`:当前生效模型名
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- `models.profiles`:模型配置集合
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- 每个模型至少建议包含:`hf_model_id`、`ctx`、`max_num_seqs`、`max_tokens`、`gpu_util`、`valid_tp`
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启动时会按以下优先级选模型:
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1. `config.json` 中 `selected_model`
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2. `config.json` 中 `default_model`
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1. `config.json` 中 `models.selected`
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2. `config.json` 中 `models.default`
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模型被选中后,会自动覆盖运行参数,包括:
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@@ -88,7 +89,7 @@
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## 部署步骤
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1. 修改 `config.json` 中的 `selected_model` 与服务参数。
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1. 修改 `config.json` 中的 `models.selected` 与服务参数。
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2. 构建并启动容器:
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@@ -129,8 +130,9 @@ curl -X POST "http://localhost:8001/v1/chat/completions" \
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- Base URL 使用 `http://<服务器IP>:8001/v1`
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- API Key 使用 `config.json` 中 `api_key`
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- 模型名使用 `config.json` 中 `served_model_name`
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- 模型名使用 `config.json` 中 `models.profiles.<模型名>.served_model_name`
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- 若使用工具调用,`config.json` 中应配置 `tool_call_parser` 与 `enable_auto_tool_choice`
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- 所有路径按 Ubuntu 规范填写,本地模型建议使用 `/opt/model/<模型目录>`
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## 双 AMD R9700 调优建议
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@@ -138,4 +140,3 @@ curl -X POST "http://localhost:8001/v1/chat/completions" \
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- 首次部署建议设置 `GPU_MEMORY_UTILIZATION=0.90`,稳定后再调高
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- 若模型较大且吞吐压力高,可逐步调低 `MAX_MODEL_LEN` 或 `MAX_NUM_SEQS`
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- 确保宿主机已正确安装 ROCm 驱动并暴露 `/dev/kfd` 与 `/dev/dri`
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+58
-54
@@ -9,62 +9,66 @@
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"port": 8001
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}
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},
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"api_key": "",
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"api_key": "sk-szcjw",
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"tensor_parallel_size": 2,
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"dtype": "bfloat16",
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"revision": "",
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"default_model": "Qwen3.5-35B-A3B-GPTQ-Int4",
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"selected_model": "Qwen3.5-35B-A3B-GPTQ-Int4",
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"Qwen3-Next-80B-A3B-Instruct-AWQ-4bit": {
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"ctx": "24576",
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"trust_remote": true,
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"valid_tp": [2],
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"max_num_seqs": "32",
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"max_tokens": "16384",
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"gpu_util": "0.98",
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"enforce_eager": false,
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"env": {
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"VLLM_USE_TRITON_AWQ": "1"
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},
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"tool_call_parser": "qwen3_xml",
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"enable_auto_tool_choice": true,
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"served_model_name": "Qwen3-Next-80B-A3B-Instruct-AWQ-4bit",
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"hf_model_id": "cpatonn/Qwen3-Next-80B-A3B-Instruct-AWQ-4bit"
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},
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"GLM-4.7-Flash-AWQ": {
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"ctx": "32768",
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"trust_remote": true,
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"valid_tp": [1, 2],
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"max_num_seqs": "64",
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"max_tokens": "32768",
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"gpu_util": "0.98",
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"tool_call_parser": "qwen3_xml",
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"enable_auto_tool_choice": true,
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"served_model_name": "GLM-4.7-Flash-AWQ",
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"hf_model_id": "THUDM/GLM-4.7-Flash-AWQ"
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},
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"Qwen3.5-27B-FP8": {
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"ctx": "32768",
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"trust_remote": true,
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"valid_tp": [1, 2],
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"max_num_seqs": "64",
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"max_tokens": "32768",
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"gpu_util": "0.98",
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"tool_call_parser": "qwen3_xml",
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"enable_auto_tool_choice": true,
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"served_model_name": "Qwen3.5-27B-FP8",
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"hf_model_id": "RedHatAI/Qwen3.5-27B-FP8-dynamic"
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},
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"Qwen3.5-35B-A3B-GPTQ-Int4": {
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"ctx": "32768",
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"trust_remote": true,
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"valid_tp": [1, 2],
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"max_num_seqs": "64",
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"max_tokens": "32768",
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"gpu_util": "0.98",
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"tool_call_parser": "qwen3_xml",
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"enable_auto_tool_choice": true,
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"served_model_name": "Qwen3.5-35B-A3B-GPTQ-Int4",
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"hf_model_id": "Qwen/Qwen3.5-35B-A3B-GPTQ-Int4"
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"models": {
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"default": "Qwen3.5-35B-A3B-GPTQ-Int4",
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"selected": "Qwen3.5-35B-A3B-GPTQ-Int4",
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"profiles": {
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"Qwen3-Next-80B-A3B-Instruct-AWQ-4bit": {
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"ctx": "24576",
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"trust_remote": true,
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"valid_tp": [2],
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"max_num_seqs": "32",
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"max_tokens": "16384",
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"gpu_util": "0.98",
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"enforce_eager": false,
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"env": {
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"VLLM_USE_TRITON_AWQ": "1"
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},
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"tool_call_parser": "qwen3_xml",
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"enable_auto_tool_choice": true,
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"served_model_name": "Qwen3-Next-80B-A3B-Instruct-AWQ-4bit",
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"hf_model_id": "cpatonn/Qwen3-Next-80B-A3B-Instruct-AWQ-4bit"
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},
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"GLM-4.7-Flash-AWQ": {
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"ctx": "32768",
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"trust_remote": true,
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"valid_tp": [1, 2],
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"max_num_seqs": "64",
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"max_tokens": "32768",
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"gpu_util": "0.98",
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"tool_call_parser": "qwen3_xml",
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"enable_auto_tool_choice": true,
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"served_model_name": "GLM-4.7-Flash-AWQ",
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"hf_model_id": "THUDM/GLM-4.7-Flash-AWQ"
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},
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"Qwen3.5-27B-FP8": {
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"ctx": "32768",
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"trust_remote": true,
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"valid_tp": [1, 2],
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"max_num_seqs": "64",
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"max_tokens": "32768",
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"gpu_util": "0.98",
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"tool_call_parser": "qwen3_xml",
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"enable_auto_tool_choice": true,
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"served_model_name": "Qwen3.5-27B-FP8",
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"hf_model_id": "RedHatAI/Qwen3.5-27B-FP8-dynamic"
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},
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"Qwen3.5-35B-A3B-GPTQ-Int4": {
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"ctx": "32768",
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"trust_remote": true,
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"valid_tp": [1, 2],
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"max_num_seqs": "64",
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"max_tokens": "32768",
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"gpu_util": "0.98",
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"tool_call_parser": "qwen3_xml",
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"enable_auto_tool_choice": true,
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"served_model_name": "Qwen3.5-35B-A3B-GPTQ-Int4",
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"hf_model_id": "Qwen/Qwen3.5-35B-A3B-GPTQ-Int4"
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}
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}
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}
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}
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+2
-2
@@ -10,7 +10,7 @@ services:
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- "8000:8000"
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volumes:
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- /opt/model:/opt/model:ro
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- d:/project/rocm_vllm_nightly/rocm_vllm_nightly/config.json:/workspace/config.json:ro
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- ./config.json:/workspace/config.json:ro
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devices:
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- /dev/kfd
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- /dev/dri
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@@ -35,7 +35,7 @@ services:
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- "8001:8001"
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volumes:
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- /opt/model:/opt/model:ro
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- d:/project/rocm_vllm_nightly/rocm_vllm_nightly/config.json:/workspace/config.json:ro
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- ./config.json:/workspace/config.json:ro
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devices:
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- /dev/kfd
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- /dev/dri
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