clean up

llm_server/database/conn.py

@@ -5,20 +5,20 @@ class DatabaseConnection:
     host: str = None
     username: str = None
     password: str = None
-    database: str = None
+    database_name: str = None
 
-    def init_db(self, host, username, password, database):
+    def init_db(self, host, username, password, database_name):
         self.host = host
         self.username = username
         self.password = password
-        self.database = database
+        self.database_name = database_name
 
     def cursor(self):
         db = pymysql.connect(
             host=self.host,
             user=self.username,
             password=self.password,
-            database=self.database,
+            database=self.database_name,
             charset='utf8mb4',
             autocommit=True,
         )

llm_server/routes/ooba_request_handler.py

@@ -4,7 +4,6 @@ import flask
 from flask import jsonify, request
 
 from llm_server import opts
-from llm_server.database.database import do_db_log
 from llm_server.database.log_to_db import log_to_db
 from llm_server.routes.helpers.client import format_sillytavern_err
 from llm_server.routes.request_handler import RequestHandler

llm_server/workers/inferencer.py

@@ -35,6 +35,7 @@ def worker(backend_url):
                 redis.publish(event_id, 'begin')
                 for item in pubsub.listen():
                     if item['type'] == 'message' and item['data'].decode('utf-8') == 'finished':
+                        # The streaming endpoint has said that it has finished
                         break
                     time.sleep(0.1)
             else:
@@ -47,6 +48,7 @@ def worker(backend_url):
         finally:
             decrement_ip_count(client_ip, 'processing_ips')
             decr_active_workers(selected_model, backend_url)
+        print('Worker finished processing for', client_ip)
 
 
 def start_workers(cluster: dict):

llm_server/workers/logger.py

@@ -1,4 +1,5 @@
 import pickle
+import traceback
 
 import redis
 
@@ -17,11 +18,14 @@ def db_logger():
     p.subscribe('database-logger')
 
     for message in p.listen():
-        if message['type'] == 'message':
-            data = pickle.loads(message['data'])
-            function_name = data['function']
-            args = data['args']
-            kwargs = data['kwargs']
+        try:
+            if message['type'] == 'message':
+                data = pickle.loads(message['data'])
+                function_name = data['function']
+                args = data['args']
+                kwargs = data['kwargs']
 
-            if function_name == 'log_prompt':
-                do_db_log(*args, **kwargs)
+                if function_name == 'log_prompt':
+                    do_db_log(*args, **kwargs)
+        except:
+            traceback.print_exc()

llm_server/workers/printer.py

@@ -25,4 +25,4 @@ def console_printer():
                 processing_count += redis.get(k, default=0, dtype=int)
         backends = [k for k, v in cluster_config.all().items() if v['online']]
         logger.info(f'REQUEST QUEUE -> Processing: {processing_count} | Queued: {len(priority_queue)} | Backends Online: {len(backends)}')
-        time.sleep(1)
+        time.sleep(10)

other/gradio/gradio_chat.py

@@ -75,7 +75,8 @@ def stream_response(prompt, history):
             messages=messages,
             temperature=0,
             max_tokens=300,
-            stream=True
+            stream=True,
+            headers={'LLM-Source': 'huggingface-demo'}
         )
     except Exception:
         raise gr.Error("Failed to reach inference endpoint.")