[LoRA] Cleanup LoRA unused code

examples/offline_inference/multilora_inference.py

@@ -46,7 +46,6 @@ def create_test_prompts(
                 logprobs=1,
                 prompt_logprobs=1,
                 max_tokens=128,
-                stop_token_ids=[32003],
             ),
             LoRARequest("sql-lora", 1, lora_path),
         ),
@@ -57,7 +56,6 @@ def create_test_prompts(
                 logprobs=1,
                 prompt_logprobs=1,
                 max_tokens=128,
-                stop_token_ids=[32003],
             ),
             LoRARequest("sql-lora2", 2, lora_path),
         ),
@@ -98,7 +96,7 @@ def initialize_engine() -> LLMEngine:
     #   use the same rank, it is recommended to set this as low as possible.
     # max_cpu_loras: controls the size of the CPU LoRA cache.
     engine_args = EngineArgs(
-        model="meta-llama/Llama-2-7b-hf",
+        model="meta-llama/Llama-3.2-3B-Instruct",
         enable_lora=True,
         max_loras=1,
         max_lora_rank=8,
@@ -111,7 +109,7 @@ def initialize_engine() -> LLMEngine:
 def main():
     """Main function that sets up and runs the prompt processing."""
     engine = initialize_engine()
-    lora_path = snapshot_download(repo_id="yard1/llama-2-7b-sql-lora-test")
+    lora_path = snapshot_download(repo_id="jeeejeee/llama32-3b-text2sql-spider")
     test_prompts = create_test_prompts(lora_path)
     process_requests(engine, test_prompts)
 

tests/entrypoints/conftest.py

@@ -188,11 +188,11 @@ def sample_sql_statements():
 
 
 @pytest.fixture(scope="session")
-def zephyr_lora_files():
-    """Download zephyr LoRA files once per test session."""
+def qwen3_lora_files():
+    """Download Qwen3 LoRA files once per test session."""
     from huggingface_hub import snapshot_download
 
-    return snapshot_download(repo_id="typeof/zephyr-7b-beta-lora")
+    return snapshot_download(repo_id="charent/self_cognition_Alice")
 
 
 @pytest.fixture(scope="session")

tests/entrypoints/openai/test_basic.py

@@ -16,7 +16,7 @@
 
 from ...utils import RemoteOpenAIServer
 
-MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
+MODEL_NAME = "Qwen/Qwen3-0.6B"
 
 
 @pytest.fixture(scope="module")

tests/entrypoints/openai/test_chat.py

@@ -19,6 +19,14 @@
 MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
 
 
+@pytest.fixture(scope="module")
+def zephyr_lora_files():
+    """Download zephyr LoRA files once per test session."""
+    from huggingface_hub import snapshot_download
+
+    return snapshot_download(repo_id="typeof/zephyr-7b-beta-lora")
+
+
 @pytest.fixture(scope="module")
 def server(zephyr_lora_files):  # noqa: F811
     args = [

tests/entrypoints/openai/test_chunked_prompt.py

@@ -8,7 +8,7 @@
 from ...utils import RemoteOpenAIServer
 
 # any model with a chat template should work here
-MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
+MODEL_NAME = "Qwen/Qwen3-0.6B"
 
 
 @pytest.fixture(scope="module")
@@ -20,7 +20,6 @@ def server():
         "--max-model-len",
         "8192",
         "--enforce-eager",
-        # lora config below
         "--max-num-seqs",
         "128",
         "--enable-chunked-prefill",

tests/entrypoints/openai/test_lora_adapters.py

@@ -13,9 +13,8 @@
 from ...utils import RemoteOpenAIServer
 
 # any model with a chat template should work here
-MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
-# technically this needs Mistral-7B-v0.1 as base, but we're not testing
-# generation quality here
+MODEL_NAME = "Qwen/Qwen3-0.6B"
+
 
 BADREQUEST_CASES = [
     (
@@ -33,11 +32,11 @@
 
 
 @pytest.fixture(scope="module", params=[True])
-def server_with_lora_modules_json(request, zephyr_lora_files):
+def server_with_lora_modules_json(request, qwen3_lora_files):
     # Define the json format LoRA module configurations
     lora_module_1 = {
-        "name": "zephyr-lora",
-        "path": zephyr_lora_files,
+        "name": "qwen3-lora",
+        "path": qwen3_lora_files,
         "base_model_name": MODEL_NAME,
     }
 
@@ -74,35 +73,35 @@ async def client(server_with_lora_modules_json):
 
 
 @pytest.mark.asyncio
-async def test_static_lora_lineage(client: openai.AsyncOpenAI, zephyr_lora_files):
+async def test_static_lora_lineage(client: openai.AsyncOpenAI, qwen3_lora_files):
     models = await client.models.list()
     models = models.data
     served_model = models[0]
     lora_models = models[1:]
     assert served_model.id == MODEL_NAME
     assert served_model.root == MODEL_NAME
     assert served_model.parent is None
-    assert all(lora_model.root == zephyr_lora_files for lora_model in lora_models)
+    assert all(lora_model.root == qwen3_lora_files for lora_model in lora_models)
     assert all(lora_model.parent == MODEL_NAME for lora_model in lora_models)
-    assert lora_models[0].id == "zephyr-lora"
+    assert lora_models[0].id == "qwen3-lora"
 
 
 @pytest.mark.asyncio
-async def test_dynamic_lora_lineage(client: openai.AsyncOpenAI, zephyr_lora_files):
+async def test_dynamic_lora_lineage(client: openai.AsyncOpenAI, qwen3_lora_files):
     response = await client.post(
         "load_lora_adapter",
         cast_to=str,
-        body={"lora_name": "zephyr-lora-3", "lora_path": zephyr_lora_files},
+        body={"lora_name": "qwen3-lora-3", "lora_path": qwen3_lora_files},
     )
     # Ensure adapter loads before querying /models
     assert "success" in response
 
     models = await client.models.list()
     models = models.data
     dynamic_lora_model = models[-1]
-    assert dynamic_lora_model.root == zephyr_lora_files
+    assert dynamic_lora_model.root == qwen3_lora_files
     assert dynamic_lora_model.parent == MODEL_NAME
-    assert dynamic_lora_model.id == "zephyr-lora-3"
+    assert dynamic_lora_model.id == "qwen3-lora-3"
 
 
 @pytest.mark.asyncio
@@ -134,7 +133,7 @@ async def test_dynamic_lora_invalid_files(client: openai.AsyncOpenAI, tmp_path):
 async def test_dynamic_lora_badrequests(
     client: openai.AsyncOpenAI,
     tmp_path,
-    zephyr_lora_files,
+    qwen3_lora_files,
     test_name: str,
     config_change: dict,
     expected_error: str,
@@ -143,7 +142,7 @@ async def test_dynamic_lora_badrequests(
     test_dir = tmp_path / test_name
 
     # Copy adapter files
-    shutil.copytree(zephyr_lora_files, test_dir)
+    shutil.copytree(qwen3_lora_files, test_dir)
 
     # Load and modify configuration
     config_path = test_dir / "adapter_config.json"
@@ -167,7 +166,7 @@ async def test_dynamic_lora_badrequests(
 
 @pytest.mark.asyncio
 async def test_multiple_lora_adapters(
-    client: openai.AsyncOpenAI, tmp_path, zephyr_lora_files
+    client: openai.AsyncOpenAI, tmp_path, qwen3_lora_files
 ):
     """Validate that many loras can be dynamically registered and inferenced
     with concurrently"""
@@ -178,7 +177,7 @@ async def load_and_run_adapter(adapter_name: str):
         await client.post(
             "load_lora_adapter",
             cast_to=str,
-            body={"lora_name": adapter_name, "lora_path": str(zephyr_lora_files)},
+            body={"lora_name": adapter_name, "lora_path": str(qwen3_lora_files)},
         )
         for _ in range(3):
             await client.completions.create(
@@ -199,7 +198,7 @@ async def load_and_run_adapter(adapter_name: str):
 
 @pytest.mark.asyncio
 async def test_loading_invalid_adapters_does_not_break_others(
-    client: openai.AsyncOpenAI, tmp_path, zephyr_lora_files
+    client: openai.AsyncOpenAI, tmp_path, qwen3_lora_files
 ):
     invalid_files = tmp_path / "invalid_files"
     invalid_files.mkdir()
@@ -215,7 +214,7 @@ async def run_good_requests(client):
         while not stop_good_requests_event.is_set():
             try:
                 batch = await client.completions.create(
-                    model="zephyr-lora",
+                    model="qwen3-lora",
                     prompt=["Hello there", "Foo bar bazz buzz"],
                     max_tokens=5,
                 )
@@ -254,7 +253,7 @@ async def run_good_requests(client):
     await client.post(
         "load_lora_adapter",
         cast_to=str,
-        body={"lora_name": "valid", "lora_path": zephyr_lora_files},
+        body={"lora_name": "valid", "lora_path": qwen3_lora_files},
     )
     await client.completions.create(
         model="valid",
@@ -267,15 +266,15 @@ async def run_good_requests(client):
 async def test_beam_search_with_lora_adapters(
     client: openai.AsyncOpenAI,
     tmp_path,
-    zephyr_lora_files,
+    qwen3_lora_files,
 ):
     """Validate that async beam search can be used with lora."""
 
     async def load_and_run_adapter(adapter_name: str):
         await client.post(
             "load_lora_adapter",
             cast_to=str,
-            body={"lora_name": adapter_name, "lora_path": str(zephyr_lora_files)},
+            body={"lora_name": adapter_name, "lora_path": str(qwen3_lora_files)},
         )
         for _ in range(3):
             await client.completions.create(

tests/entrypoints/openai/test_models.py

@@ -8,13 +8,13 @@
 from ...utils import RemoteOpenAIServer
 
 # any model with a chat template should work here
-MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
+MODEL_NAME = "Qwen/Qwen3-0.6B"
 # technically this needs Mistral-7B-v0.1 as base, but we're not testing
 # generation quality here
 
 
 @pytest.fixture(scope="module")
-def server(zephyr_lora_files):
+def server(qwen3_lora_files):
     args = [
         # use half precision for speed and memory savings in CI environment
         "--dtype",
@@ -25,7 +25,7 @@ def server(zephyr_lora_files):
         # lora config below
         "--enable-lora",
         "--lora-modules",
-        f"zephyr-lora={zephyr_lora_files}",
+        f"qwen3-lora={qwen3_lora_files}",
         "--max-lora-rank",
         "64",
         "--max-cpu-loras",
@@ -45,12 +45,12 @@ async def client(server):
 
 
 @pytest.mark.asyncio
-async def test_check_models(client: openai.AsyncOpenAI, zephyr_lora_files):
+async def test_check_models(client: openai.AsyncOpenAI, qwen3_lora_files):
     models = await client.models.list()
     models = models.data
     served_model = models[0]
     lora_models = models[1:]
     assert served_model.id == MODEL_NAME
     assert served_model.root == MODEL_NAME
-    assert all(lora_model.root == zephyr_lora_files for lora_model in lora_models)
-    assert lora_models[0].id == "zephyr-lora"
+    assert all(lora_model.root == qwen3_lora_files for lora_model in lora_models)
+    assert lora_models[0].id == "qwen3-lora"

tests/entrypoints/openai/test_orca_metrics.py

@@ -8,7 +8,7 @@
 from ...utils import RemoteOpenAIServer
 
 # any model with a chat template should work here
-MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
+MODEL_NAME = "Qwen/Qwen3-0.6B"
 
 
 @pytest.fixture(scope="module")
@@ -110,8 +110,9 @@ async def test_single_completion(client: openai.AsyncOpenAI):
     choice = completion.choices[0]
     assert len(choice.text) >= 5
     assert choice.finish_reason == "length"
+    # When using Qwen3-0.6B, prompt tokens=[9707, 11, 847, 829, 374]
     assert completion.usage == openai.types.CompletionUsage(
-        completion_tokens=5, prompt_tokens=6, total_tokens=11
+        completion_tokens=5, prompt_tokens=5, total_tokens=10
     )
 
     # test using token IDs

tests/entrypoints/openai/test_return_tokens_as_ids.py

@@ -11,11 +11,11 @@
 
 from ...utils import RemoteOpenAIServer
 
-MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
+MODEL_NAME = "Qwen/Qwen3-0.6B"
 
 
 @pytest.fixture(scope="module")
-def default_server_args(zephyr_lora_files):
+def default_server_args(qwen3_lora_files):
     return [
         # use half precision for speed and memory savings in CI environment
         "--dtype",
@@ -28,7 +28,7 @@ def default_server_args(zephyr_lora_files):
         # lora config
         "--enable-lora",
         "--lora-modules",
-        f"zephyr-lora={zephyr_lora_files}",
+        f"qwen3-lora={qwen3_lora_files}",
         "--max-lora-rank",
         "64",
         "--max-cpu-loras",

tests/entrypoints/openai/test_tokenization.py

@@ -10,7 +10,7 @@
 from ...utils import RemoteOpenAIServer
 
 # any model with a chat template should work here
-MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
+MODEL_NAME = "Qwen/Qwen3-0.6B"
 
 
 @pytest.fixture(scope="module")

tests/entrypoints/openai/test_uds.py

@@ -10,7 +10,7 @@
 
 from ...utils import RemoteOpenAIServer
 
-MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
+MODEL_NAME = "Qwen/Qwen3-0.6B"
 
 
 @pytest.fixture(scope="module")

tests/entrypoints/sagemaker/conftest.py

@@ -9,7 +9,6 @@
 from ...utils import RemoteOpenAIServer
 
 # Model name constants used across tests
-MODEL_NAME_ZEPHYR = "HuggingFaceH4/zephyr-7b-beta"
 MODEL_NAME_SMOLLM = "HuggingFaceTB/SmolLM2-135M-Instruct"
 LORA_ADAPTER_NAME_SMOLLM = "jekunz/smollm-135m-lora-fineweb-faroese"
 

tests/lora/conftest.py

@@ -154,23 +154,6 @@ def dummy_model_gate_up() -> nn.Module:
     return model
 
 
-@pytest.fixture(scope="session")
-def llama_2_7b_base_huggingface_id():
-    # used as a base model for testing with sql lora adapter
-    return "meta-llama/Llama-2-7b-hf"
-
-
-@pytest.fixture(scope="session")
-def sql_lora_huggingface_id():
-    # huggingface repo id is used to test lora runtime downloading.
-    return "yard1/llama-2-7b-sql-lora-test"
-
-
-@pytest.fixture(scope="session")
-def sql_lora_files(sql_lora_huggingface_id):
-    return snapshot_download(repo_id=sql_lora_huggingface_id)
-
-
 @pytest.fixture(scope="session")
 def mixtral_lora_files():
     # Note: this module has incorrect adapter_config.json to test
@@ -256,8 +239,14 @@ def qwen3_lora_files():
 
 
 @pytest.fixture(scope="session")
-def llama32_lora_files():
-    return snapshot_download(repo_id="jeeejeee/llama32-3b-text2sql-spider")
+def llama32_lora_huggingface_id():
+    # huggingface repo id is used to test lora runtime downloading.
+    return "jeeejeee/llama32-3b-text2sql-spider"
+
+
+@pytest.fixture(scope="session")
+def llama32_lora_files(llama32_lora_huggingface_id):
+    return snapshot_download(repo_id=llama32_lora_huggingface_id)
 
 
 @pytest.fixture