server: tests: assert embeddings are actually computed, make the embeddings endpoint configurable.

Add logs to investigate why the CI server test job is not starting

examples/server/tests/features/server.feature

@@ -8,6 +8,7 @@ Feature: llama.cpp server
     And   42 as server seed
     And   32 KV cache size
     And   1 slots
+    And   embeddings extraction
     And   32 server max tokens to predict
     Then  the server is starting
     Then  the server is healthy

examples/server/tests/features/steps/steps.py

@@ -4,6 +4,7 @@ import os
 import re
 import socket
 import subprocess
+import time
 from contextlib import closing
 from re import RegexFlag
 
@@ -21,13 +22,14 @@ def step_server_config(context, server_fqdn, server_port):
 
     context.base_url = f'http://{context.server_fqdn}:{context.server_port}'
 
-    context.server_continuous_batching = False
     context.model_alias = None
     context.n_ctx = None
     context.n_predict = None
     context.n_server_predict = None
     context.n_slots = None
     context.server_api_key = None
+    context.server_continuous_batching = False
+    context.server_embeddings = False
     context.server_seed = None
     context.user_api_key = None
 
@@ -70,15 +72,26 @@ def step_server_n_predict(context, n_predict):
 def step_server_continuous_batching(context):
     context.server_continuous_batching = True
 
+@step(u'embeddings extraction')
+def step_server_embeddings(context):
+    context.server_embeddings = True
+
 
 @step(u"the server is starting")
 def step_start_server(context):
     start_server_background(context)
+    attempts = 0
     while True:
         with closing(socket.socket(socket.AF_INET, socket.SOCK_STREAM)) as sock:
             result = sock.connect_ex((context.server_fqdn, context.server_port))
             if result == 0:
+                print("server started!")
                 return
+            attempts += 1
+            if attempts > 20:
+                assert False, "server not started"
+            print("waiting for server to start...")
+            time.sleep(0.1)
 
 
 @step(u"the server is {expecting_status}")
@@ -301,6 +314,11 @@ def step_compute_embedding(context):
 @step(u'embeddings are generated')
 def step_compute_embeddings(context):
     assert len(context.embeddings) > 0
+    embeddings_computed = False
+    for emb in context.embeddings:
+        if emb != 0:
+            embeddings_computed = True
+    assert embeddings_computed, f"Embeddings: {context.embeddings}"
 
 
 @step(u'an OAI compatible embeddings computation request for')
@@ -436,7 +454,8 @@ async def oai_chat_completions(user_prompt,
                                     json=payload,
                                     headers=headers) as response:
                 if enable_streaming:
-                    print("payload", payload)
+                    # FIXME: does not work; the server is generating only one token
+                    print("DEBUG payload", payload)
                     assert response.status == 200
                     assert response.headers['Access-Control-Allow-Origin'] == origin
                     assert response.headers['Content-Type'] == "text/event-stream"
@@ -453,7 +472,7 @@ async def oai_chat_completions(user_prompt,
                         if 'content' in delta:
                             completion_response['content'] += delta['content']
                             completion_response['timings']['predicted_n'] += 1
-                        print(f"XXXXXXXXXXXXXXXXXcompletion_response: {completion_response}")
+                        print(f"DEBUG completion_response: {completion_response}")
                 else:
                     if expect_api_error is None or not expect_api_error:
                         assert response.status == 200
@@ -500,7 +519,7 @@ async def oai_chat_completions(user_prompt,
                     'predicted_n': chat_completion.usage.completion_tokens
                 }
             }
-    print("OAI response formatted to llama.cpp", completion_response)
+    print("OAI response formatted to llama.cpp:", completion_response)
     return completion_response
 
 
@@ -567,7 +586,7 @@ async def wait_for_health_status(context,
                 # Sometimes health requests are triggered after completions are predicted
                 if expected_http_status_code == 503:
                     if len(context.completions) == 0:
-                        print("\x1b[5;37;43mWARNING: forcing concurrents completions tasks,"
+                        print("\x1b[33;42mWARNING: forcing concurrents completions tasks,"
                               " busy health check missed\x1b[0m")
                         n_completions = await gather_concurrent_completions_tasks(context)
                         if n_completions > 0:
@@ -604,6 +623,8 @@ def start_server_background(context):
     ]
     if context.server_continuous_batching:
         server_args.append('--cont-batching')
+    if context.server_embeddings:
+        server_args.append('--embedding')
     if context.model_alias is not None:
         server_args.extend(['--alias', context.model_alias])
     if context.server_seed is not None:
@@ -620,3 +641,4 @@ def start_server_background(context):
     context.server_process = subprocess.Popen(
         [str(arg) for arg in [context.server_path, *server_args]],
         close_fds=True)
+    print(f"server pid={context.server_process.pid}")