feat:add qwen3

src/emd/commands/deploy.py

@@ -399,6 +399,7 @@ def deploy(
             else:
                 gpu_num = get_gpu_num()
                 support_gpu_num = model.supported_instances[0].gpu_num
+                support_gpu_num = support_gpu_num or gpu_num
                 default_gpus_str = ",".join([str(i) for i in range(min(gpu_num,support_gpu_num))])
                 gpus_to_deploy = questionary.text(
                         "input the local gpu ids to deploy the model (e.g. 0,1,2):",

src/emd/models/engines.py

@@ -108,6 +108,11 @@ class KtransformersEngine(OpenAICompitableEngine):
 
 vllm_deepseek_r1_distill_llama_engine071 = vllm_deepseek_r1_distill_qwen_engine071
 
+vllm_deepseek_r1_engine084 = VllmEngine(**{
+            **vllm_engine064.model_dump(),
+            "engine_dockerfile_config": {"VERSION":"v0.8.4"},
+            "default_cli_args": "--max_num_seq 10 --max_model_len 16000 --chat-template emd/models/chat_templates/deepseek_r1.jinja"
+})
 
 vllm_qwen2d5_72b_engine064 = VllmEngine(**{
              **vllm_engine064.model_dump(),
@@ -140,9 +145,9 @@ class KtransformersEngine(OpenAICompitableEngine):
 
 vllm_qwen3_engin084 = VllmEngine(**{
              **vllm_engine064.model_dump(),
-             "engine_dockerfile_config": {"VERSION":"v0.8.4"},
+             "engine_dockerfile_config": {"VERSION":"v0.8.5"},
             "environment_variables": "export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True",
-            "default_cli_args": " --max_model_len 16000 --disable-log-stats  --enable-reasoning --reasoning-parser deepseek_r1 --enable-auto-tool-choice --tool-call-parser hermes --enable-prefix-caching"
+            "default_cli_args": " --max_model_len 16000 --max_num_seq 30 --disable-log-stats  --enable-reasoning --reasoning-parser deepseek_r1 --enable-auto-tool-choice --tool-call-parser hermes --enable-prefix-caching"
 })
 
 
@@ -165,7 +170,7 @@ class KtransformersEngine(OpenAICompitableEngine):
             "engine_dockerfile_config": {"VERSION":"v0.8.4"},
             "dockerfile_name":"Dockerfile_qwen25_vl",
             "environment_variables": "export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True",
-            "default_cli_args": " --max_model_len 32000 --disable-log-stats --limit-mm-per-prompt image=1,video=1 --max_num_seq 1 --gpu_memory_utilization 0.9"
+            "default_cli_args": " --max_model_len 32000 --disable-log-stats --limit-mm-per-prompt image=1,video=1 --max_num_seq 1 --gpu_memory_utilization 0.7"
 })
 
 vllm_qwq_engine073 = VllmEngine(**{

src/emd/models/llms/deepseek.py

@@ -7,6 +7,7 @@
     llama_cpp_deepseek_r1_distill_engineb9ab0a4,
     tgi_deepseek_r1_llama_70b_engine301,
     ktransformers_engine,
+    vllm_deepseek_r1_engine084
 )
 from ..services import (
     sagemaker_service,
@@ -450,6 +451,31 @@
     )
 )
 
+Model.register(
+    dict(
+        model_id = "DeepSeek-R1",
+        supported_engines=[vllm_deepseek_r1_engine084],
+        supported_instances=[
+            local_instance
+        ],
+        supported_services=[
+            local_service
+        ],
+        supported_frameworks=[
+            fastapi_framework
+        ],
+        allow_china_region=True,
+        need_prepare_model=False,
+        huggingface_model_id="unsloth/DeepSeek-R1",
+        modelscope_model_id="unsloth/DeepSeek-R1",
+        require_huggingface_token=False,
+        application_scenario="Agent, tool use, translation, summary",
+        description="The latest series of DeepSeek LLMs for reasoning",
+        model_type=ModelType.LLM,
+        model_series=DEEPSEEK_REASONING_MODEL
+    )
+)
+
 Model.register(
     dict(
         model_id = "deepseek-r1-671b-4bit_gguf",

src/emd/models/llms/qwen.py

@@ -578,7 +578,7 @@
             g5d4xlarge_instance,
             g5d8xlarge_instance,
             g5d16xlarge_instance,
-            g4dn2xlarge_instance,
+            # g4dn2xlarge_instance,
             # g5d24xlarge_instance,
             # g5d48xlarge_instance,
             local_instance
@@ -671,6 +671,44 @@
     )
 )
 
+
+# ValueError("type fp8e4nv not supported in this architecture. The supported fp8 dtypes are ('fp8e4b15', 'fp8e5')")
+# The g5 instance may not support fp8e4nv
+# Model.register(
+#     dict(
+#         model_id = "Qwen3-14B-FP8",
+#         supported_engines=[vllm_qwen3_engin084],
+#         supported_instances=[
+#             g5d2xlarge_instance,
+#             g5d4xlarge_instance,
+#             g5d8xlarge_instance,
+#             g5d16xlarge_instance,
+#             # g4dn2xlarge_instance,
+#             # g5d24xlarge_instance,
+#             # g5d48xlarge_instance,
+#             local_instance
+#         ],
+#         supported_services=[
+#             sagemaker_service,
+#             sagemaker_async_service,
+#             ecs_service,
+#             local_service
+#         ],
+#         supported_frameworks=[
+#             fastapi_framework
+#         ],
+#         allow_china_region=True,
+#         huggingface_model_id="Qwen/Qwen3-14B-FP8",
+#         modelscope_model_id="Qwen/Qwen3-14B-FP8",
+#         require_huggingface_token=False,
+#         application_scenario="Agent, tool use, translation, summary",
+#         description="The latest series of Qwen LLMs, offers base and tuned models from 0.5B to 72B\n parameters, featuring enhanced knowledge, improved coding and math skills, better instruction\n following, long-text generation, structured data handling, 128K token context support, and\n multilingual capabilities for 29+ languages.",
+#         model_type=ModelType.LLM,
+#         model_series=QWEN3_SERIES
+#     )
+# )
+
+
 Model.register(
     dict(
         model_id = "Qwen3-32B",
@@ -735,3 +773,52 @@
         model_series=QWEN3_SERIES
     )
 )
+
+
+Model.register(
+    dict(
+        model_id = "Qwen3-235B-A22B",
+        supported_engines=[vllm_qwen3_engin084],
+        supported_instances=[
+            local_instance
+        ],
+        supported_services=[
+            local_service
+        ],
+        supported_frameworks=[
+            fastapi_framework
+        ],
+        allow_china_region=True,
+        huggingface_model_id="Qwen/Qwen3-235B-A22B",
+        modelscope_model_id="Qwen/Qwen3-235B-A22B",
+        require_huggingface_token=False,
+        application_scenario="Agent, tool use, translation, summary",
+        description="The latest series of Qwen LLMs, offers base and tuned models from 0.5B to 72B\n parameters, featuring enhanced knowledge, improved coding and math skills, better instruction\n following, long-text generation, structured data handling, 128K token context support, and\n multilingual capabilities for 29+ languages.",
+        model_type=ModelType.LLM,
+        model_series=QWEN3_SERIES
+    )
+)
+
+Model.register(
+    dict(
+        model_id = "Qwen3-235B-A22B-FP8",
+        supported_engines=[vllm_qwen3_engin084],
+        supported_instances=[
+            local_instance
+        ],
+        supported_services=[
+            local_service
+        ],
+        supported_frameworks=[
+            fastapi_framework
+        ],
+        allow_china_region=True,
+        huggingface_model_id="Qwen/Qwen3-235B-A22B-FP8",
+        modelscope_model_id="Qwen/Qwen3-235B-A22B-FP8",
+        require_huggingface_token=False,
+        application_scenario="Agent, tool use, translation, summary",
+        description="The latest series of Qwen LLMs, offers base and tuned models from 0.5B to 72B\n parameters, featuring enhanced knowledge, improved coding and math skills, better instruction\n following, long-text generation, structured data handling, 128K token context support, and\n multilingual capabilities for 29+ languages.",
+        model_type=ModelType.LLM,
+        model_series=QWEN3_SERIES
+    )
+)