[Test] Add initial multi modal cases of Qwen2.5-VL-7B-Instruct for disaggregated encoder (#5301)

### What this PR does / why we need it?
This PR adds disaggregated encoder  tests for Qwen2.5-VL-7B-Instruct 
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
by running the test
by running ci

- vLLM version: release/v0.12.0

---------

Signed-off-by: wangyu31577 <wangyu31577@hundsun.com>
Signed-off-by: wangyu <53896905+yenuo26@users.noreply.github.com>
Co-authored-by: wangyu31577 <wangyu31577@hundsun.com>

tests/e2e/nightly/single_node/models/test_qwen2_5_vl_7b_epd.py

@@ -0,0 +1,110 @@
+# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
+# Copyright 2023 The vLLM team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# This file is a part of the vllm-ascend project.
+#
+
+import pytest
+from vllm.utils.network_utils import get_open_port
+
+from tests.e2e.conftest import DisaggEpdProxy, RemoteEPDServer
+from tools.aisbench import run_aisbench_cases
+
+MODELS = [
+    "Qwen/Qwen2.5-VL-7B-Instruct",
+]
+SHARED_STORAGE_PATH = "/dev/shm/epd/storage"
+TENSOR_PARALLELS = [1]
+
+warmup_cases = [{
+    "case_type": "performance",
+    "dataset_path": "vllm-ascend/textvqa-perf-1080p",
+    "request_conf": "vllm_api_stream_chat",
+    "dataset_conf": "textvqa/textvqa_gen_base64",
+    "num_prompts": 50,
+    "max_out_len": 20,
+    "batch_size": 32,
+    "request_rate": 0,
+    "baseline": 1,
+    "threshold": 0.97
+}]
+aisbench_cases = [{
+    "case_type": "accuracy",
+    "dataset_path": "vllm-ascend/textvqa-lite",
+    "request_conf": "vllm_api_stream_chat",
+    "dataset_conf": "textvqa/textvqa_gen_base64",
+    "max_out_len": 2048,
+    "batch_size": 128,
+    "baseline": 82.05,
+    "threshold": 5
+}, {
+    "case_type": "performance",
+    "dataset_path": "vllm-ascend/textvqa-perf-1080p",
+    "request_conf": "vllm_api_stream_chat",
+    "dataset_conf": "textvqa/textvqa_gen_base64",
+    "num_prompts": 512,
+    "max_out_len": 256,
+    "batch_size": 128,
+    "request_rate": 0,
+    "baseline": 1,
+    "threshold": 0.97
+}]
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("model", MODELS)
+@pytest.mark.parametrize("tp_size", TENSOR_PARALLELS)
+async def test_models(model: str, tp_size: int) -> None:
+    encode_port = get_open_port()
+    pd_port = get_open_port()
+    vllm_server_args = [
+        [
+            "--port",
+            str(encode_port), "--model", model, "--gpu-memory-utilization",
+            "0.01", "--tensor-parallel-size",
+            str(tp_size), "--enforce-eager", "--no-enable-prefix-caching",
+            "--max-model-len", "10000", "--max-num-batched-tokens", "10000",
+            "--max-num-seqs", "1", "--ec-transfer-config",
+            '{"ec_connector_extra_config":{"shared_storage_path":"' +
+            SHARED_STORAGE_PATH +
+            '"},"ec_connector":"ECExampleConnector","ec_role": "ec_producer"}'
+        ],
+        [
+            "--port",
+            str(pd_port), "--model", model, "--gpu-memory-utilization", "0.95",
+            "--tensor-parallel-size",
+            str(tp_size), "--enforce-eager", "--max-model-len", "10000",
+            "--max-num-batched-tokens", "10000", "--max-num-seqs", "128",
+            "--ec-transfer-config",
+            '{"ec_connector_extra_config":{"shared_storage_path":"' +
+            SHARED_STORAGE_PATH +
+            '"},"ec_connector":"ECExampleConnector","ec_role": "ec_consumer"}'
+        ]
+    ]
+    proxy_port = get_open_port()
+    proxy_args = [
+        "--host", "127.0.0.1", "--port",
+        str(proxy_port), "--encode-servers-urls",
+        f"http://localhost:{encode_port}", "--decode-servers-urls",
+        f"http://localhost:{pd_port}", "--prefill-servers-urls", "disable"
+    ]
+
+    with RemoteEPDServer(vllm_serve_args=vllm_server_args) as _:
+        with DisaggEpdProxy(proxy_args=proxy_args) as _:
+            # warm up
+            run_aisbench_cases(model=model,
+                               port=proxy_port,
+                               aisbench_cases=warmup_cases)
+            # aisbench test
+            run_aisbench_cases(model, proxy_port, aisbench_cases)