local-llm-server/server.py

from llm_server.config.config import mode_ui_names

try:
    import gevent.monkey

    gevent.monkey.patch_all()
except ImportError:
    pass

from llm_server.pre_fork import server_startup
from llm_server.config.load import load_config
import os
import sys
from pathlib import Path

import simplejson as json
from flask import Flask, jsonify, render_template, request

import llm_server
from llm_server.database.conn import database
from llm_server.database.create import create_db
from llm_server.llm import get_token_count
from llm_server.routes.openai import openai_bp
from llm_server.routes.server_error import handle_server_error
from llm_server.routes.v1 import bp
from llm_server.stream import init_socketio

# TODO: have the workers handle streaming too
# TODO: add backend fallbacks. Backends at the bottom of the list are higher priority and are fallbacks if the upper ones fail
# TODO: implement background thread to test backends via sending test prompts
# TODO: if backend fails request, mark it as down
# TODO: allow setting concurrent gens per-backend
# TODO: set the max tokens to that of the lowest backend
# TODO: implement RRD backend loadbalancer option
# TODO: have VLLM reject a request if it already has n == concurrent_gens running
# TODO: add a way to cancel VLLM gens. Maybe use websockets?
# TODO: use coloredlogs

# 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
# TODO: return 200 when returning formatted sillytavern error

try:
    import vllm
except ModuleNotFoundError as e:
    print('Could not import vllm-gptq:', e)
    print('Please see README.md for install instructions.')
    sys.exit(1)

import config
from llm_server import opts
from llm_server.helpers import auto_set_base_client_api
from llm_server.llm.vllm.info import vllm_info
from llm_server.routes.cache import RedisWrapper, flask_cache
from llm_server.llm import redis
from llm_server.routes.stats import get_active_gen_workers
from llm_server.routes.v1.generate_stats import generate_stats

app = Flask(__name__)
init_socketio(app)
app.register_blueprint(bp, url_prefix='/api/v1/')
app.register_blueprint(openai_bp, url_prefix='/api/openai/v1/')
flask_cache.init_app(app)
flask_cache.clear()

script_path = os.path.dirname(os.path.realpath(__file__))
config_path_environ = os.getenv("CONFIG_PATH")
if config_path_environ:
    config_path = config_path_environ
else:
    config_path = Path(script_path, 'config', 'config.yml')

success, config, msg = load_config(config_path, script_path)
if not success:
    print('Failed to load config:', msg)
    sys.exit(1)

database.init_db(config['mysql']['host'], config['mysql']['username'], config['mysql']['password'], config['mysql']['database'])
create_db()
llm_server.llm.redis = RedisWrapper('local_llm')
create_db()


# print(app.url_map)


@app.route('/')
@app.route('/api')
@app.route('/api/openai')
@flask_cache.cached(timeout=10)
def home():
    stats = generate_stats()

    if not stats['online']:
        running_model = estimated_wait_sec = 'offline'
    else:
        running_model = redis.get('running_model', str, 'ERROR')

        active_gen_workers = get_active_gen_workers()
        if stats['queue']['queued'] == 0 and active_gen_workers >= opts.concurrent_gens:
            # There will be a wait if the queue is empty but prompts are processing, but we don't
            # know how long.
            estimated_wait_sec = f"less than {stats['stats']['average_generation_elapsed_sec']} seconds"
        else:
            estimated_wait_sec = f"{stats['queue']['estimated_wait_sec']} seconds"

    if len(config['analytics_tracking_code']):
        analytics_tracking_code = f"<script>\n{config['analytics_tracking_code']}\n</script>"
    else:
        analytics_tracking_code = ''

    if config['info_html']:
        info_html = config['info_html']
    else:
        info_html = ''

    mode_info = ''
    if opts.mode == 'vllm':
        mode_info = vllm_info

    base_client_api = redis.get('base_client_api', str)

    return render_template('home.html',
                           llm_middleware_name=opts.llm_middleware_name,
                           analytics_tracking_code=analytics_tracking_code,
                           info_html=info_html,
                           current_model=opts.manual_model_name if opts.manual_model_name else running_model,
                           client_api=f'https://{base_client_api}',
                           ws_client_api=f'wss://{base_client_api}/v1/stream' if opts.enable_streaming else None,
                           estimated_wait=estimated_wait_sec,
                           mode_name=mode_ui_names[opts.mode][0],
                           api_input_textbox=mode_ui_names[opts.mode][1],
                           streaming_input_textbox=mode_ui_names[opts.mode][2],
                           context_size=opts.context_size,
                           stats_json=json.dumps(stats, indent=4, ensure_ascii=False),
                           extra_info=mode_info,
                           openai_client_api=f'https://{base_client_api}/openai/v1' if opts.enable_openi_compatible_backend else 'disabled',
                           expose_openai_system_prompt=opts.expose_openai_system_prompt,
                           enable_streaming=opts.enable_streaming,
                           )


# TODO: add authenticated route to get the current backend URL. Add it to /v1/backend

@app.route('/<first>')
@app.route('/<first>/<path:rest>')
def fallback(first=None, rest=None):
    return jsonify({
        'code': 404,
        'msg': 'not found'
    }), 404


@app.errorhandler(500)
def server_error(e):
    return handle_server_error(e)


@app.before_request
def before_app_request():
    auto_set_base_client_api(request)


if __name__ == "__main__":
    server_startup(None)
    print('FLASK MODE - Startup complete!')
    app.run(host='0.0.0.0', threaded=False, processes=15)