rework find available prot to nolonger be a fixture

app_tests/benchmark_tests/llm/sglang_benchmarks/shortfin_benchmark_test.py

@@ -84,9 +84,7 @@ def test_shortfin_benchmark(
     model_path = tmp_dir / model_param_file_name
 
     # Start shortfin llm server
-    port = find_available_port()
-    server_process = start_llm_server(
-        port,
+    server_process, port = start_llm_server(
         tokenizer_path,
         config_path,
         vmfb_path,

app_tests/integration_tests/llm/sglang/conftest.py

@@ -27,11 +27,10 @@
 logger = logging.getLogger(__name__)
 
 
-@pytest.fixture(scope="module")
-def register_shortfin_backend(available_port):
+def register_shortfin_backend(port):
     backend = sgl.Shortfin(
         chat_template=get_chat_template("llama-3-instruct"),
-        base_url=f"http://localhost:{available_port}",
+        base_url=f"http://localhost:{port}",
     )
     sgl.set_default_backend(backend)
 
@@ -73,7 +72,7 @@ def available_port():
 
 
 @pytest.fixture(scope="module")
-def start_server(request, pre_process_model, available_port):
+def start_server(request, pre_process_model):
     os.environ["ROCR_VISIBLE_DEVICES"] = "1"
     device_settings = request.param["device_settings"]
 
@@ -85,8 +84,7 @@ def start_server(request, pre_process_model, available_port):
     config_path = export_dir / "config.json"
 
     logger.info("Starting server...")
-    server_process = start_llm_server(
-        available_port,
+    server_process, port = start_llm_server(
         tokenizer_path,
         config_path,
         vmfb_path,
@@ -96,7 +94,7 @@ def start_server(request, pre_process_model, available_port):
     )
     logger.info("Server started")
 
-    yield server_process
+    yield server_process, port
 
     server_process.terminate()
     server_process.wait()

app_tests/integration_tests/llm/sglang/sglang_frontend_test.py

@@ -32,6 +32,14 @@
 ACCEPTED_THRESHOLD = 0.7
 
 
+def register_shortfin_backend(port):
+    backend = sgl.Shortfin(
+        chat_template=get_chat_template("llama-3-instruct"),
+        base_url=f"http://localhost:{port}",
+    )
+    sgl.set_default_backend(backend)
+
+
 def compute_similarity(model: SentenceTransformer, sentence_1: str, sentence_2: str):
     embeddings = model.encode([sentence_1, sentence_2])
     return util.pytorch_cos_sim(embeddings[0], embeddings[1]).item()
@@ -72,7 +80,10 @@ def tip_suggestion(s):
     ],
     indirect=True,
 )
-def test_multi_turn_qa(load_comparison_model, start_server, register_shortfin_backend):
+def test_multi_turn_qa(load_comparison_model, start_server):
+    server, port = start_server
+    register_shortfin_backend(port)
+
     model = load_comparison_model
 
     question_1 = "Name the capital city of the USA."
@@ -130,9 +141,10 @@ def test_multi_turn_qa(load_comparison_model, start_server, register_shortfin_ba
     ],
     indirect=True,
 )
-def test_stream_multi_turn_qa(
-    load_comparison_model, start_server, register_shortfin_backend
-):
+def test_stream_multi_turn_qa(load_comparison_model, start_server):
+    server, port = start_server
+    register_shortfin_backend(port)
+
     def clean_message(message: str):
         """Remove chat tags from message before comparison.
 
@@ -183,9 +195,9 @@ def clean_message(message: str):
     ],
     indirect=True,
 )
-def test_batch_multi_turn_qa(
-    load_comparison_model, start_server, register_shortfin_backend
-):
+def test_batch_multi_turn_qa(load_comparison_model, start_server):
+    server, port = start_server
+    register_shortfin_backend(port)
     model = load_comparison_model
 
     question_1_1 = "Name the capital city of the USA."
@@ -287,7 +299,9 @@ def test_batch_multi_turn_qa(
     ],
     indirect=True,
 )
-def test_fork(load_comparison_model, start_server, register_shortfin_backend):
+def test_fork(load_comparison_model, start_server):
+    server, port = start_server
+    register_shortfin_backend(port)
     model = load_comparison_model
 
     logger.info("Testing fork...")

app_tests/integration_tests/llm/shortfin/conftest.py

@@ -150,16 +150,15 @@ def llm_server(request, model_test_dir, write_config, available_port):
     parameters_path = tmp_dir / model_file
 
     # Start llm server
-    server_process = start_llm_server(
-        available_port,
+    server_process, port = start_llm_server(
         tokenizer_path,
         config_path,
         vmfb_path,
         parameters_path,
         settings,
     )
     logger.info("LLM server started!" + end_log_group())
-    yield server_process
+    yield server_process, port
     # Teardown: kill the server
     server_process.terminate()
     server_process.wait()

app_tests/integration_tests/llm/utils.py

@@ -173,7 +173,8 @@ def start_llm_server(
     timeout=10,
     multi=False,
 ):
-    logger.info("Starting LLM server...")
+    port = find_available_port()
+    logger.info(f"Starting LLM server on port {port}...")
     if multi:
         server_process = multiprocessing.Process(
             target=subprocess.Popen(
@@ -204,7 +205,7 @@ def start_llm_server(
     logger.info("Process started... waiting for server")
     # Wait for server to start
     wait_for_server(f"http://localhost:{port}", timeout)
-    return server_process
+    return server_process, port
 
 
 def start_log_group(headline):