update home, update readme, calculate estimated wait based on database stats

README.md

@@ -2,12 +2,8 @@
 
 _A HTTP API to serve local LLM Models._
 
-
-
 The purpose of this server is to abstract your LLM backend from your frontend API. This enables you to make changes to (or even switch) your backend without affecting your clients.
 
-
-
 ### Install
 
 1. `sudo apt install redis`
@@ -16,25 +12,18 @@ The purpose of this server is to abstract your LLM backend from your frontend AP
 4. `pip install -r requirements.txt`
 5. `python3 server.py`
 
-
-
 An example systemctl service file is provided in `other/local-llm.service`.
 
-
-
 ### Configure
 
-First, set up your LLM backend. Currently, only [oobabooga/text-generation-webui](https://github.com/oobabooga/text-generation-webui) is supported, but eventually [huggingface/text-generation-inference](https://github.com/huggingface/text-generation-inference) will be the default.
+First, set up your LLM backend. Currently, only [oobabooga/text-generation-webui](https://github.com/oobabooga/text-generation-webui) is supported, but
+eventually [huggingface/text-generation-inference](https://github.com/huggingface/text-generation-inference) will be the default.
 
 Then, configure this server. The config file is located at `config/config.yml.sample` so copy it to `config/config.yml`.
 
-
-
 1. Set `backend_url` to the base API URL of your backend.
 2. Set `token_limit` to the configured token limit of the backend. This number is shown to clients and on the home page.
 
-
-
 To set up token auth, add rows to the `token_auth` table in the SQLite database.
 
 `token`: the token/password.
@@ -51,6 +40,11 @@ To set up token auth, add rows to the `token_auth` table in the SQLite database.
 
 `disabled`: mark the token as disabled.
 
+### 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 graphics
+cards, you should probably clear the `generation_time` time column in the `prompts` table.
+
 ### To Do
 
 - Implement streaming

llm_server/config.py

@@ -10,12 +10,13 @@ config_default_vars = {
     'show_num_prompts': True,
     'show_uptime': True,
     'analytics_tracking_code': '',
+    'average_generation_time_mode': 'database',
 }
 config_required_vars = ['token_limit', 'concurrent_gens', 'mode', 'llm_middleware_name']
 
 mode_ui_names = {
-    'oobabooga': 'Text Gen WebUI (ooba)',
-    'hf-textgen': 'UNDEFINED',
+    'oobabooga': ('Text Gen WebUI (ooba)', 'Blocking API url'),
+    'hf-textgen': ('UNDEFINED', 'UNDEFINED'),
 }
 
 

llm_server/database.py

@@ -92,3 +92,12 @@ def get_number_of_rows(table_name):
     result = cur.fetchone()
     conn.close()
     return result[0]
+
+
+def average_column(table_name, column_name):
+    conn = sqlite3.connect(opts.database_path)
+    cursor = conn.cursor()
+    cursor.execute(f"SELECT AVG({column_name}) FROM {table_name}")
+    result = cursor.fetchone()
+    conn.close()
+    return result[0]

llm_server/opts.py

@@ -14,3 +14,4 @@ http_host = None
 verify_ssl = True
 show_num_prompts = True
 show_uptime = True
+average_generation_time_mode = 'database'

llm_server/routes/v1/generate_stats.py

@@ -3,6 +3,7 @@ from datetime import datetime
 
 from llm_server import opts
 from llm_server.llm.info import get_running_model
+from llm_server.routes.cache import redis
 from llm_server.routes.queue import priority_queue
 from llm_server.routes.stats import SemaphoreCheckerThread, calculate_avg_gen_time, get_active_gen_workers, get_total_proompts, server_start_time
 
@@ -21,8 +22,18 @@ def generate_stats():
     #     waits = [elapsed for end, elapsed in t]
     #     estimated_wait = int(sum(waits) / len(waits))
 
-    average_generation_time = int(calculate_avg_gen_time())
     proompters_in_queue = len(priority_queue) + get_active_gen_workers()
+    average_tps = float(redis.get('average_tps'))
+
+    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)
+    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)
+    else:
+        raise Exception
 
     # TODO: https://stackoverflow.com/questions/22721579/sorting-a-nested-ordereddict-by-key-recursively
     return {
@@ -32,6 +43,7 @@ def generate_stats():
             'total_proompts': 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': average_generation_time,
+            'average_tps': average_tps,
         },
         'online': online,
         'mode': opts.mode,
@@ -39,7 +51,7 @@ def generate_stats():
         'endpoints': {
             'blocking': opts.full_client_api,
         },
-        'estimated_wait_sec': int((average_generation_time * proompters_in_queue) / opts.concurrent_gens),
+        'estimated_wait_sec': estimated_wait_sec,
         'timestamp': int(time.time()),
         'openaiKeys': '∞',
         'anthropicKeys': '∞',

llm_server/routes/v1/proxy.py

@@ -1,16 +1,8 @@
-import time
-from datetime import datetime
+from flask import jsonify
 
-from flask import jsonify, request
-
-from llm_server import opts
 from . import bp
 from .generate_stats import generate_stats
-from .. import stats
 from ..cache import cache
-from ..queue import priority_queue
-from ..stats import SemaphoreCheckerThread, calculate_avg_gen_time, get_active_gen_workers
-from ...llm.info import get_running_model
 
 
 @bp.route('/stats', methods=['GET'])

llm_server/threads.py

@@ -4,6 +4,7 @@ from threading import Thread
 import requests
 
 from llm_server import opts
+from llm_server.database import average_column
 from llm_server.routes.cache import redis
 
 
@@ -13,9 +14,21 @@ class BackendHealthCheck(Thread):
     def __init__(self):
         Thread.__init__(self)
         self.daemon = True
+        redis.set('average_generation_elapsed_sec', 0)
+        redis.set('average_tps', 0)
+        redis.set('average_output_tokens', 0)
+        redis.set('backend_online', 0)
 
     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)

server.py

@@ -60,11 +60,15 @@ if not opts.verify_ssl:
 
 flushed_keys = redis.flush()
 print('Flushed', len(flushed_keys), 'keys from Redis.')
-redis.set('backend_online', 0)
 
 if config['load_num_prompts']:
     redis.set('proompts', get_number_of_rows('prompts'))
 
+if config['average_generation_time_mode'] not in ['database', 'minute']:
+    print('Invalid value for config item "average_generation_time_mode":', config['average_generation_time_mode'])
+    sys.exit(1)
+opts.average_generation_time_mode = config['average_generation_time_mode']
+
 start_workers(opts.concurrent_gens)
 
 # cleanup_thread = Thread(target=elapsed_times_cleanup)
@@ -113,7 +117,8 @@ def home():
                            current_model=running_model,
                            client_api=opts.full_client_api,
                            estimated_wait=estimated_wait_sec,
-                           mode_name=mode_ui_names[opts.mode],
+                           mode_name=mode_ui_names[opts.mode][0],
+                           api_input_textbox=mode_ui_names[opts.mode][1],
                            context_size=opts.context_size,
                            stats_json=json.dumps(stats, indent=4, ensure_ascii=False)
                            )

templates/home.html

@@ -14,6 +14,8 @@
             background-color: #ffb6c16e;
             padding: 1em;
             display: inline-block;
+            margin: auto;
+            max-width: 95%;
         }
 
         a, a:visited {
@@ -25,6 +27,12 @@
             text-align: center;
         }
 
+        pre {
+            white-space: pre-wrap;
+            word-wrap: break-word;
+            text-align: justify;
+        }
+
         @media only screen and (max-width: 600px) {
             .container {
                 padding: 1em;
@@ -51,7 +59,7 @@
         <strong>Instructions:</strong>
         <ol>
             <li>Set your API type to <kbd>{{ mode_name }}</kbd></li>
-            <li>Enter <kbd>{{ client_api }}</kbd> in the <kbd>Blocking API url</kbd> textbox.</li>
+            <li>Enter <kbd>{{ client_api }}</kbd> in the <kbd>{{ api_input_textbox }}</kbd> textbox.</li>
             <li>Click <kbd>Connect</kbd> to test the connection.</li>
             <li>Open your preset config and set <kbd>Context Size</kbd> to {{ context_size }}.</li>
             <li>Follow this guide to get set up: <a href="https://rentry.org/freellamas" target="_blank">rentry.org/freellamas</a></li>