log model used in request so we can pull the correct averages when we change models

README.md

@@ -42,10 +42,12 @@ To set up token auth, add rows to the `token_auth` table in the SQLite database.
 
 ### Use
 
-**DO NOT** lose your database. It's used for calculating the estimated wait time based on average TPS and response tokens and if you lose those stats your numbers will be inaccurate until the database fills back up again. If you change GPUs, you should probably clear the `generation_time` time column in the `prompts` table.
+**DO NOT** lose your database. It's used for calculating the estimated wait time based on average TPS and response tokens and if you lose those stats your numbers will be inaccurate until the database fills back up again. If you change GPUs, you
+should probably clear the `generation_time` time column in the `prompts` table.
 
 ### To Do
 
 - Implement streaming
 - Add `huggingface/text-generation-inference`
 - Convince Oobabooga to implement concurrent generation
+- Make sure stats work when starting from an empty database

llm_server/database.py

@@ -24,6 +24,7 @@ def init_db():
                 response_tokens INTEGER,
                 response_status INTEGER,
                 generation_time FLOAT,
+                model TEXT,
                 parameters TEXT CHECK (parameters IS NULL OR json_valid(parameters)),
                 headers TEXT CHECK (headers IS NULL OR json_valid(headers)),
                 timestamp INTEGER
@@ -59,8 +60,8 @@ def log_prompt(ip, token, prompt, response, gen_time, parameters, headers, backe
     timestamp = int(time.time())
     conn = sqlite3.connect(opts.database_path)
     c = conn.cursor()
-    c.execute("INSERT INTO prompts VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
+    c.execute("INSERT INTO prompts VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
-              (ip, token, prompt, prompt_tokens, response, response_tokens, backend_response_code, gen_time, json.dumps(parameters), json.dumps(headers), timestamp))
+              (ip, token, prompt, prompt_tokens, response, response_tokens, backend_response_code, gen_time, opts.running_model, json.dumps(parameters), json.dumps(headers), timestamp))
     conn.commit()
     conn.close()
 
@@ -108,6 +109,15 @@ def average_column(table_name, column_name):
     return result[0]
 
 
+def average_column_for_model(table_name, column_name, model_name):
+    conn = sqlite3.connect(opts.database_path)
+    cursor = conn.cursor()
+    cursor.execute(f"SELECT AVG({column_name}) FROM {table_name} WHERE model = ?", (model_name,))
+    result = cursor.fetchone()
+    conn.close()
+    return result[0]
+
+
 def sum_column(table_name, column_name):
     conn = sqlite3.connect(opts.database_path)
     cursor = conn.cursor()

llm_server/routes/v1/generate_stats.py

@@ -34,7 +34,7 @@ def generate_stats():
     if opts.average_generation_time_mode == 'database':
         average_generation_time = int(float(redis.get('average_generation_elapsed_sec')))
         average_output_tokens = int(float(redis.get('average_output_tokens')))
-        estimated_wait_sec = int(((average_output_tokens / average_tps) * proompters_in_queue) / opts.concurrent_gens)
+        estimated_wait_sec = int(((average_output_tokens / average_tps) * proompters_in_queue) / opts.concurrent_gens) if average_tps > 0 else 0
     elif opts.average_generation_time_mode == 'minute':
         average_generation_time = int(calculate_avg_gen_time())
         estimated_wait_sec = int((average_generation_time * proompters_in_queue) / opts.concurrent_gens)

llm_server/threads.py

@@ -4,7 +4,7 @@ from threading import Thread
 import requests
 
 from llm_server import opts
-from llm_server.database import average_column
+from llm_server.database import average_column_for_model
 from llm_server.routes.cache import redis
 
 
@@ -24,14 +24,6 @@ class MainBackgroundThread(Thread):
 
     def run(self):
         while True:
-            average_generation_elapsed_sec = average_column('prompts', 'generation_time') if not None else 0
-            redis.set('average_generation_elapsed_sec', average_generation_elapsed_sec)
-
-            average_output_tokens = average_column('prompts', 'response_tokens') if not None else 0
-            redis.set('average_output_tokens', average_output_tokens)
-            average_tps = round(average_output_tokens / average_generation_elapsed_sec, 2)
-            redis.set('average_tps', average_tps)
-
             if opts.mode == 'oobabooga':
                 try:
                     r = requests.get(f'{opts.backend_url}/api/v1/model', timeout=3, verify=opts.verify_ssl)
@@ -45,4 +37,14 @@ class MainBackgroundThread(Thread):
                 pass
             else:
                 raise Exception
+
+            average_generation_elapsed_sec = average_column_for_model('prompts', 'generation_time', opts.running_model) or 0
+            redis.set('average_generation_elapsed_sec', average_generation_elapsed_sec)
+
+            average_output_tokens = average_column_for_model('prompts', 'response_tokens', opts.running_model) or 0
+            redis.set('average_output_tokens', average_output_tokens)
+
+            # Avoid division by zero
+            average_tps = round(average_output_tokens / average_generation_elapsed_sec, 2) if average_generation_elapsed_sec > 0 else 0
+            redis.set('average_tps', average_tps)
             time.sleep(60)