set inference workers to daemon, add finally to inference worker, hide estimated avg tps

llm_server/routes/helpers/http.py

@@ -29,6 +29,16 @@ def cache_control(seconds):
     return decorator
 
 
+# TODO:
+#   File "/srv/server/local-llm-server/llm_server/routes/request_handler.py", line 240, in before_request
+#     response = require_api_key()
+#                ^^^^^^^^^^^^^^^^^
+#   File "/srv/server/local-llm-server/llm_server/routes/helpers/http.py", line 50, in require_api_key
+#     if token.startswith('SYSTEM__') or opts.auth_required:
+#        ^^^^^^^^^^^^^^^^
+# AttributeError: 'NoneType' object has no attribute 'startswith'
+
+
 def require_api_key(json_body: dict = None):
     if json_body:
         request_json = json_body

llm_server/routes/queue.py

@@ -107,6 +107,7 @@ def worker():
         # TODO: only increment if not valid SYSTEM__ token
         redis.incr('active_gen_workers')
 
+        try:
             start_time = time.time()
             success, response, error_msg = generator(request_json_body)
             end_time = time.time()
@@ -117,7 +118,7 @@ def worker():
 
             event = DataEvent(event_id)
             event.set((success, response, error_msg))
-
+        finally:
             decrement_ip_count(client_ip, 'processing_ips')
 
             # TODO: only decrement if not valid SYSTEM__ token
@@ -126,4 +127,6 @@ def worker():
 
 def start_workers(num_workers: int):
     for _ in range(num_workers):
-        threading.Thread(target=worker).start()
+        t = threading.Thread(target=worker)
+        t.daemon = True
+        t.start()

llm_server/routes/v1/generate_stats.py

@@ -57,7 +57,9 @@ def generate_stats(regen: bool = False):
 
     active_gen_workers = get_active_gen_workers()
     proompters_in_queue = len(priority_queue)
-    estimated_avg_tps = redis.get('estimated_avg_tps', float, default=0)
+
+    # This is so wildly inaccurate it's disabled until I implement stats reporting into VLLM.
+    # estimated_avg_tps = redis.get('estimated_avg_tps', float, default=0)
 
     if opts.average_generation_time_mode == 'database':
         average_generation_time = redis.get('average_generation_elapsed_sec', float, default=0)
@@ -99,7 +101,7 @@ def generate_stats(regen: bool = False):
             'proompts_total': get_total_proompts() if opts.show_num_prompts else None,
             'uptime': int((datetime.now() - server_start_time).total_seconds()) if opts.show_uptime else None,
             'average_generation_elapsed_sec': int(gen_time_calc),
-            'estimated_avg_tps': estimated_avg_tps,
+            # 'estimated_avg_tps': estimated_avg_tps,
             'tokens_generated': sum_column('prompts', 'response_tokens') if opts.show_total_output_tokens else None,
             'nvidia': netdata_stats
         },

llm_server/routes/v1/generate_stream.py

@@ -88,6 +88,14 @@ def stream(ws):
 
                     partial_response = b''
 
+# TODO: handle when the backend is offline
+# Traceback (most recent call last):
+#   File "/srv/server/local-llm-server/llm_server/routes/v1/generate_stream.py", line 91, in stream
+#     for chunk in response.iter_content(chunk_size=1):
+#                  ^^^^^^^^^^^^^^^^^^^^^
+# AttributeError: 'NoneType' object has no attribute 'iter_content'
+
+
                     for chunk in response.iter_content(chunk_size=1):
                         partial_response += chunk
                         if partial_response.endswith(b'\x00'):

server.py

@@ -33,10 +33,15 @@ from llm_server.stream import init_socketio
 # TODO: set the max tokens to that of the lowest backend
 # TODO: implement RRD backend loadbalancer option
 
+# Lower priority
+# TODO: the processing stat showed -1 and I had to restart the server
 # TODO: simulate OpenAI error messages regardless of endpoint
 # TODO: send extra headers when ratelimited?
 # TODO: make sure log_prompt() is used everywhere, including errors and invalid requests
 # TODO: unify logging thread in a function and use async/await instead
+# TODO: move the netdata stats to a seperate part of the stats and have it set to the currently selected backend
+# TODO: have VLLM reply with stats (TPS, generated token count, processing time)
+# TODO: add config reloading via stored redis variables
 
 # Done, but need to verify
 # TODO: add more excluding to SYSTEM__ tokens
@@ -166,6 +171,8 @@ def pre_fork(server):
 
     # Start background processes
     start_workers(opts.concurrent_gens)
+    print(f'Started {opts.concurrent_gens} inference workers.')
+
     start_moderation_workers(opts.openai_moderation_workers)
     process_avg_gen_time_background_thread = Thread(target=process_avg_gen_time)
     process_avg_gen_time_background_thread.daemon = True