import os
import sys
from pathlib import Path
from threading import Thread
import simplejson as json
from flask import Flask, jsonify, render_template, request

import llm_server
from llm_server.database.conn import db_pool
from llm_server.database.create import create_db
from llm_server.database.database import get_number_of_rows
from llm_server.llm.oobabooga.ooba_backend import OobaboogaBackend
from llm_server.llm.vllm.vllm_backend import VLLMBackend
from llm_server.routes.openai import openai_bp
from llm_server.routes.server_error import handle_server_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.config import ConfigLoader, config_default_vars, config_required_vars, mode_ui_names
from llm_server.helpers import resolve_path
from llm_server.llm.vllm.info import vllm_info
from llm_server.routes.cache import cache, redis
from llm_server.routes.queue import start_workers
from llm_server.routes.stats import SemaphoreCheckerThread, process_avg_gen_time
from llm_server.routes.v1 import bp
from llm_server.routes.v1.generate_stats import generate_stats
from llm_server.stream import init_socketio
from llm_server.threads import MainBackgroundThread, cache_stats

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')

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

# Resolve relative directory to the directory of the script
if config['database_path'].startswith('./'):
    config['database_path'] = resolve_path(script_path, config['database_path'].strip('./'))

db_pool.init_db(config['mysql']['host'], config['mysql']['username'], config['mysql']['password'], config['mysql']['database'])
create_db()

if config['mode'] not in ['oobabooga', 'vllm']:
    print('Unknown mode:', config['mode'])
    sys.exit(1)
opts.mode = config['mode']
opts.auth_required = config['auth_required']
opts.log_prompts = config['log_prompts']
opts.concurrent_gens = config['concurrent_gens']
opts.frontend_api_client = config['frontend_api_client']
opts.context_size = config['token_limit']
opts.show_num_prompts = config['show_num_prompts']
opts.show_uptime = config['show_uptime']
opts.backend_url = config['backend_url'].strip('/')
opts.show_total_output_tokens = config['show_total_output_tokens']
opts.netdata_root = config['netdata_root']
opts.simultaneous_requests_per_ip = config['simultaneous_requests_per_ip']
opts.show_backend_info = config['show_backend_info']
opts.max_new_tokens = config['max_new_tokens']
opts.manual_model_name = config['manual_model_name']
opts.llm_middleware_name = config['llm_middleware_name']
opts.enable_openi_compatible_backend = config['enable_openi_compatible_backend']
opts.openai_system_prompt = config['openai_system_prompt']
opts.expose_openai_system_prompt = config['expose_openai_system_prompt']
opts.enable_streaming = config['enable_streaming']
opts.openai_api_key = config['openai_api_key']

opts.verify_ssl = config['verify_ssl']
if not opts.verify_ssl:
    import urllib3

    urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)

flushed_keys = redis.flush()
print('Flushed', len(flushed_keys), 'keys from Redis.')

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']


if opts.mode == 'oobabooga':
    raise NotImplementedError
    # llm_server.llm.tokenizer = OobaboogaBackend()
elif opts.mode == 'vllm':
    llm_server.llm.tokenizer = llm_server.llm.vllm.tokenize
else:
    raise Exception

# Start background processes
start_workers(opts.concurrent_gens)
process_avg_gen_time_background_thread = Thread(target=process_avg_gen_time)
process_avg_gen_time_background_thread.daemon = True
process_avg_gen_time_background_thread.start()
MainBackgroundThread().start()
SemaphoreCheckerThread().start()

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

# This needs to be started after Flask is initalized
stats_updater_thread = Thread(target=cache_stats)
stats_updater_thread.daemon = True
stats_updater_thread.start()


# print(app.url_map)


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

    if not bool(redis.get('backend_online')) or not stats['online']:
        running_model = estimated_wait_sec = 'offline'
    else:
        running_model = opts.running_model

        if stats['queue']['queued'] == 0 and stats['queue']['processing'] > 0:
            # 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

    x = redis.get('base_client_api')
    base_client_api = x.decode() if x else None
    del x

    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=stats['endpoints']['blocking'],
                           ws_client_api=stats['endpoints']['streaming'],
                           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,
                           )


@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():
    if not opts.http_host:
        opts.http_host = request.headers.get("Host")
    if not redis.get('base_client_api'):
        redis.set('base_client_api', f'{request.headers.get("Host")}/{opts.frontend_api_client.strip("/")}')


if __name__ == "__main__":
    app.run(host='0.0.0.0', threaded=False, processes=15)