repo_description: Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://gpt-docs.h2o.ai/
repo_topics: ai chatgpt embeddings fedramp generative gpt gpt4all llama2 llm mixtral pdf private privategpt vectorstore
code: import ast
  import asyncio
  import selectors
  import contextlib
  import functools
  import gc
  import hashlib
  import inspect
  import io
  import json
  import os
  import pathlib
  import pickle
  import platform
  import random
  import shutil
  import subprocess
  import sys
  import threading
  import time
  import traceback
  import zipfile
  import tarfile
  from array import array
  from collections import deque
  from concurrent.futures import ProcessPoolExecutor
  from datetime import datetime
  from typing import Tuple, Callable, Dict
  from queue import Queue, Empty
  from concurrent.futures import ThreadPoolExecutor
  from urllib.parse import urlparse
  
  import filelock
  import fire
  import numpy as np
  import pandas as pd
  import psutil
  import requests
  import uuid
  import re
  from packaging import version
  
  import tabulate
  from fire import inspectutils
  from joblib import Parallel
  from tqdm.auto import tqdm
  
  from enums import split_google, invalid_json_str, docs_joiner_default, git_hash_unset, is_json_model, \
      openai_supports_functiontools, openai_supports_parallel_functiontools, does_support_functiontools
  from utils_procs import reulimit
  
  reulimit()
  
  
  def H2O_Fire(component=None):
      config_prefix = "H2OGPT_"
  
      args = sys.argv[1:]
      query_args = [arg.split("=")[0].split(" ")[0].lstrip("-") for arg in args]
  
      fn_spec = inspectutils.GetFullArgSpec(component)
      for key, value in os.environ.items():
          if not (
                  (key.startswith(config_prefix) or key.startswith(config_prefix.lower()))
                  and len(key) > len(config_prefix)
          ):
              continue  # ignore as non H2OGPT argument
  
          new_key = key[len(config_prefix):].lower()
  
          if new_key in query_args:
              continue  # ignore as already passed as script argument
  
          if new_key not in fn_spec.args:
              continue  # ignore as not a valid H2OGPT argument
  
          args.append(f"--{new_key}={value}")
  
      fire.Fire(component=component, command=args)
  
  
  def set_seed(seed: int):
      """
      Sets the seed of the entire notebook so results are the same every time we run.
      This is for REPRODUCIBILITY.
      """
      import torch
      np.random.seed(seed)
      random_state = np.random.RandomState(seed)
      random.seed(seed)
      torch.manual_seed(seed)
      torch.cuda.manual_seed(seed)
      torch.backends.cudnn.deterministic = True
      torch.backends.cudnn.benchmark = False
      os.environ['PYTHONHASHSEED'] = str(seed)
      return random_state
  
  
  def flatten_list(lis):
      """Given a list, possibly nested to any level, return it flattened."""
      new_lis = []
      for item in lis:
          if type(item) == type([]):
              new_lis.extend(flatten_list(item))
          else:
              new_lis.append(item)
      return new_lis
  
  
  def clear_torch_cache(allow_skip=False):
      if allow_skip and os.getenv('CLEAR_CLEAR_TORCH', '2') == '1' or os.getenv('CLEAR_CLEAR_TORCH', '2') == '0':
          return
      try:
          import torch
          if torch.cuda.is_available():
              torch.cuda.empty_cache()
              torch.cuda.ipc_collect()
              gc.collect()
      except RuntimeError as e:
          print("clear_torch_cache error: %s" % ''.join(traceback.format_tb(e.__traceback__)), flush=True)
  
  
  def ping():
      try:
          print('Ping: %s' % str(datetime.now()), flush=True)
      except AttributeError:
          # some programs wrap print and will fail with flush passed
          pass
  
  
  def ping_gpu():
      try:
          print('Ping_GPU: %s %s' % (str(datetime.now()), system_info()), flush=True)
      except AttributeError:
          # some programs wrap print and will fail with flush passed
          pass
      try:
          ping_gpu_memory()
      except Exception as e:
          print('Ping_GPU memory failure: %s' % str(e), flush=True)
  
  
  def ping_gpu_memory():
      from models.gpu_mem_track import MemTracker
      gpu_tracker = MemTracker()  # define a GPU tracker
      from torch.cuda import memory_summary
      gpu_tracker.track()
  
  
  def get_torch_allocated():
      import torch
      return torch.cuda.memory_allocated()
  
  
  def get_device(n_gpus=None):
      import torch
      if torch.cuda.is_available() and n_gpus != 0:
          device = "cuda"
      elif torch.backends.mps.is_built():
          device = "mps"
      else:
          device = "cpu"
  
      return device
  
  
  def system_info():
      import psutil
  
      system = {}
      # https://stackoverflow.com/questions/48951136/plot-multiple-graphs-in-one-plot-using-tensorboard
      # https://arshren.medium.com/monitoring-your-devices-in-python-5191d672f749
      try:
          temps = psutil.sensors_temperatures(fahrenheit=False)
          if 'coretemp' in temps:
              coretemp = temps['coretemp']
              temp_dict = {k.label: k.current for k in coretemp}
              for k, v in temp_dict.items():
                  system['CPU_C/%s' % k] = v
      except AttributeError:
          pass
  
      # https://github.com/gpuopenanalytics/pynvml/blob/master/help_query_gpu.txt
      try:
          from pynvml.smi import nvidia_smi
          nvsmi = nvidia_smi.getInstance()
  
          gpu_power_dict = {'W_gpu%d' % i: x['power_readings']['power_draw'] for i, x in
                            enumerate(nvsmi.DeviceQuery('power.draw')['gpu'])}
          for k, v in gpu_power_dict.items():
              system['GPU_W/%s' % k] = v
  
          gpu_temp_dict = {'C_gpu%d' % i: x['temperature']['gpu_temp'] for i, x in
                           enumerate(nvsmi.DeviceQuery('temperature.gpu')['gpu'])}
          for k, v in gpu_temp_dict.items():
              system['GPU_C/%s' % k] = v
  
          gpu_memory_free_dict = {'MiB_gpu%d' % i: x['fb_memory_usage']['free'] for i, x in
                                  enumerate(nvsmi.DeviceQuery('memory.free')['gpu'])}
          gpu_memory_total_dict = {'MiB_gpu%d' % i: x['fb_memory_usage']['total'] for i, x in
                                   enumerate(nvsmi.DeviceQuery('memory.total')['gpu'])}
          gpu_memory_frac_dict = {k: gpu_memory_free_dict[k] / gpu_memory_total_dict[k] for k in gpu_memory_total_dict}
          for k, v in gpu_memory_frac_dict.items():
              system[f'GPU_M/%s' % k] = v
      except (KeyError, ModuleNotFoundError):
          pass
      system['hash'] = get_githash()
  
      debug_mem = False
      if debug_mem:
          try:
              # pip install guppy3
              from guppy import hpy
              h = hpy()
              print(h.heap())
              print(h.heap().byvia)
              print(h.heap().byid)
          except:
              pass
  
      return system
  
  
  def system_info_print():
      try:
          df = pd.DataFrame.from_dict(system_info(), orient='index')
          # avoid slamming GPUs
          time.sleep(1)
          return df.to_markdown()
      except Exception as e:
          return "Error: %s" % str(e)
  
  
  def zip_data(root_dirs=None, zip_file=None, base_dir='./', fail_any_exception=False):
      try:
          return _zip_data(zip_file=zip_file, base_dir=base_dir, root_dirs=root_dirs)
      except Exception as e:
          traceback.print_exc()
          print('Exception in zipping: %s' % str(e))
          if not fail_any_exception:
              raise
  
  
  def _zip_data(root_dirs=None, zip_file=None, base_dir='./'):
      if isinstance(root_dirs, str):
          root_dirs = [root_dirs]
      if zip_file is None:
          datetime_str = str(datetime.now()).replace(" ", "_").replace(":", "_")
          host_name = os.getenv('HF_HOSTNAME', 'emptyhost')
          zip_file = "data_%s_%s.zip" % (datetime_str, host_name)
      assert root_dirs is not None
      base_path = os.path.dirname(zip_file)
      if not os.path.isdir(base_path) and os.path.dirname(zip_file):
          base_path = makedirs(base_path, exist_ok=True, tmp_ok=True, use_base=True)
          zip_file = os.path.join(base_path, os.path.basename(zip_file))
      with zipfile.ZipFile(zip_file, "w") as expt_zip:
          for root_dir in root_dirs:
              if root_dir is None:
                  continue
              for root, d, files in os.walk(root_dir):
                  for file in files:
                      file_to_archive = os.path.join(root, file)
                      assert os.path.exists(file_to_archive)
                      path_to_archive = os.path.relpath(file_to_archive, base_dir)
                      expt_zip.write(filename=file_to_archive, arcname=path_to_archive)
      return zip_file, zip_file
  
  
  def tar_data(root_dirs=None, tar_file=None, base_dir='./', fail_any_exception=False):
      try:
          return _tar_data(tar_file=tar_file, base_dir=base_dir, root_dirs=root_dirs)
      except Exception as e:
          traceback.print_exc()
          print('Exception in tar archiving: %s' % str(e))
          if not fail_any_exception:
              raise
  
  
  def _tar_data(root_dirs=None, tar_file=None, base_dir='./'):
      if isinstance(root_dirs, str):
          root_dirs = [root_dirs]
      if tar_file is None:
          datetime_str = str(datetime.now()).replace(" ", "_").replace(":", "_")
          host_name = os.getenv('HF_HOSTNAME', 'emptyhost')
          tar_file = "data_%s_%s.tar.gz" % (datetime_str, host_name)
      assert root_dirs is not None
      base_path = os.path.dirname(tar_file)
      if not os.path.isdir(base_path) and os.path.dirname(tar_file):
          base_path = makedirs(base_path, exist_ok=True, tmp_ok=True, use_base=True)
          tar_file = os.path.join(base_path, os.path.basename(tar_file))
      with tarfile.open(tar_file, "w:gz") as expt_tar:
          for root_dir in root_dirs:
              if root_dir is None:
                  continue
              for root, d, files in os.walk(root_dir):
                  for file in files:
                      file_to_archive = os.path.join(root, file)
                      assert os.path.exists(file_to_archive)
                      path_to_archive = os.path.relpath(file_to_archive, base_dir)
                      expt_tar.add(name=file_to_archive, arcname=path_to_archive)
      return tar_file, tar_file
  
  
  def save_generate_output(prompt=None, output=None, base_model=None, save_dir=None, where_from='unknown where from',
                           extra_dict={}, error='', sources=[], which_api='', valid_key=None,
                           h2ogpt_key='', return_dict=False, **kwargs_extra):
      if not save_dir:
          return
      try:
          return _save_generate_output(prompt=prompt, output=output, base_model=base_model, save_dir=save_dir,
                                       where_from=where_from, extra_dict=extra_dict, error=error, sources=sources,
                                       which_api=which_api, valid_key=valid_key, h2ogpt_key=h2ogpt_key,
                                       return_dict=return_dict, **kwargs_extra)
      except Exception as e:
          traceback.print_exc()
          print('Exception in saving: %s' % str(e))
  
  
  def _save_generate_tokens(response_no_refs, extra_dict):
      # tokenize at end if need to, so doesn't block generation in multi-generator case
      if extra_dict.get('ntokens') is None:
          extra_dict['ntokens'] = FakeTokenizer().num_tokens_from_string(str(response_no_refs))
          # only do below if didn't already compute ntokens, else assume also computed rate
      if extra_dict.get('ntokens') is not None and extra_dict.get('t_generate') is not None:
          extra_dict['tokens_persecond'] = extra_dict['ntokens'] / extra_dict['t_generate']
      return extra_dict
  
  
  def _save_generate_output(prompt=None, output=None, base_model=None, save_dir=None, where_from='unknown where from',
                            extra_dict={}, error='', sources=[], which_api='',
                            valid_key=None, h2ogpt_key='',
                            return_dict=False, **kwargs_extra):
      """
      Save conversation to .json, row by row.
      json_file_path is path to final JSON file. If not in ., then will attempt to make directories.
      Appends if file exists
      """
      prompt = '<not set>' if prompt is None else prompt
      output = '<not set>' if output is None else output
  
      extra_dict = _save_generate_tokens(output, extra_dict)
  
      dict_to_save = dict(prompt=prompt, text=output, time=time.ctime(),
                          base_model=base_model,
                          where_from=where_from,
                          error=error,
                          sources=sources,
                          which_api=which_api,
                          valid_key=valid_key,
                          h2ogpt_key=h2ogpt_key,
                          )
      dict_to_save.update(extra_dict)
      dict_to_save.update(kwargs_extra)
  
      if return_dict:
          return dict_to_save
  
      if os.path.exists(save_dir) and not os.path.isdir(save_dir):
          raise RuntimeError("save_dir already exists and is not a directory!")
      makedirs(save_dir, exist_ok=True)  # already should be made, can't change at this point
      import json
      with filelock.FileLock("%s.lock" % os.path.basename(save_dir)):
          # lock logging in case have concurrency
          with open(os.path.join(save_dir, "history.json"), "a") as f:
              # just add [ at start, and ] at end, and have proper JSON dataset
              f.write(
                  "  " + json.dumps(
                      dict_to_save
                  ) + ",\n"
              )
  
  
  def s3up(filename):
      try:
          return _s3up(filename)
      except Exception as e:
          traceback.print_exc()
          print('Exception for file %s in s3up: %s' % (filename, str(e)))
          return "Failed to upload %s: Error: %s" % (filename, str(e))
  
  
  def _s3up(filename):
      import boto3
  
      aws_access_key_id = os.getenv('AWS_SERVER_PUBLIC_KEY')
      aws_secret_access_key = os.getenv('AWS_SERVER_SECRET_KEY')
      bucket = os.getenv('AWS_BUCKET')
      assert aws_access_key_id, "Set AWS key"
      assert aws_secret_access_key, "Set AWS secret"
      assert bucket, "Set AWS Bucket"
  
      s3 = boto3.client('s3',
                        aws_access_key_id=os.getenv('AWS_SERVER_PUBLIC_KEY'),
                        aws_secret_access_key=os.getenv('AWS_SERVER_SECRET_KEY'),
                        )
      ret = s3.upload_file(
          Filename=filename,
          Bucket=os.getenv('AWS_BUCKET'),
          Key=filename,
      )
      if ret in [None, '']:
          return "Successfully uploaded %s" % filename
  
  
  def get_githash():
      githash = git_hash_unset
      try:
          githash = subprocess.run(['git', 'rev-parse', 'HEAD'], stdout=subprocess.PIPE).stdout.decode('utf-8')[0:-1]
          if githash in ['', None]:
              githash = git_hash_unset
      except Exception as e:
          print("git failed to run: %s" % str(e))
      if githash == git_hash_unset:
          try:
              from version import __version__
              githash = __version__
          except:
              pass
  
      if os.getenv('HARD_ASSERTS'):
          assert is_full_git_hash(githash)
  
      return githash
  
  
  def copy_code(run_id):
      """
      copy code to track changes
      :param run_id:
      :return:
      """
      rnd_num = str(random.randint(0, 2 ** 31))
      run_id = 'run_' + str(run_id)
      os.makedirs(run_id, exist_ok=True)
      me_full = os.path.join(pathlib.Path(__file__).parent.resolve(), __file__)
      me_file = os.path.basename(__file__)
      new_me = os.path.join(run_id, me_file + '_' + get_githash())
      if os.path.isfile(new_me):
          new_me = os.path.join(run_id, me_file + '_' + get_githash() + '_' + rnd_num)
          shutil.copy(me_full, new_me)
      else:
          shutil.copy(me_full, new_me)
  
  
  class NullContext(threading.local):
      """No-op context manager, executes block without doing any additional processing.
  
      Used as a stand-in if a particular block of code is only sometimes
      used with a normal context manager:
      """
  
      def __init__(self, *args, **kwargs):
          pass
  
      def __enter__(self):
          return self
  
      def __exit__(self, exc_type, exc_value, exc_traceback):
          self.finally_act()
  
      def finally_act(self):
          pass
  
  
  class AsyncNullContext(threading.local):
      """No-op async context manager, executes block without doing any additional processing.
  
      Used as a stand-in if a particular block of code is only sometimes
      used with a normal async context manager:
      """
  
      def __init__(self, *args, **kwargs):
          pass
  
      async def __aenter__(self):
          return self
  
      async def __aexit__(self, exc_type, exc_value, exc_traceback):
          await self.finally_act()
  
      async def finally_act(self):
          pass
  
  
  def wrapped_partial(func, *args, **kwargs):
      """
      Give partial properties of normal function, like __name__ attribute etc.
      :param func:
      :param args:
      :param kwargs:
      :return:
      """
      partial_func = functools.partial(func, *args, **kwargs)
      functools.update_wrapper(partial_func, func)
      return partial_func
  
  
  class ThreadException(Exception):
      pass
  
  
  class EThread(threading.Thread):
      # Function that raises the custom exception
      def __init__(self, group=None, target=None, name=None,
                   args=(), kwargs=None, *, daemon=None, streamer=None, bucket=None,
                   async_output=False):
          self.bucket = bucket
          self.streamer = streamer
          self.exc = None
          self._return = None
          self.async_output = async_output
          super().__init__(group=group, target=target, name=name, args=args, kwargs=kwargs, daemon=daemon)
  
      def run(self):
          # Variable that stores the exception, if raised by someFunction
          try:
              if self._target is not None:
                  if self.async_output:
                      self._return = asyncio.run(self._target(*self._args, **self._kwargs))
                  else:
                      self._return = self._target(*self._args, **self._kwargs)
          except BaseException as e:
              print("thread exception: %s" % str(traceback.format_exc()))
              self.bucket.put(sys.exc_info())
              self.exc = e
              if self.streamer:
                  print("make stop: %s" % str(traceback.format_exc()), flush=True)
                  self.streamer.do_stop = True
          finally:
              # Avoid a refcycle if the thread is running a function with
              # an argument that has a member that points to the thread.
              del self._target, self._args, self._kwargs
  
      def join(self, timeout=None):
          threading.Thread.join(self)
          # Since join() returns in caller thread
          # we re-raise the caught exception
          # if any was caught
          if self.exc:
              raise self.exc
          return self._return
  
  
  def import_matplotlib():
      import matplotlib
      matplotlib.use('agg')
      # KEEP THESE HERE! START
      import matplotlib.pyplot as plt
      import pandas as pd
      # to avoid dlopen deadlock in fork
      import pandas.core.computation.expressions as pd_expressions
      import pandas.core.algorithms as pd_algorithms
      import pandas.core.common as pd_com
      import numpy as np
      # KEEP THESE HERE! END
  
  
  def get_sha(value):
      return hashlib.md5(str(value).encode('utf-8')).hexdigest()
  
  
  def sanitize_filename(name, file_length_limit=250):
      """
      Sanitize file *base* names.
      :param name: name to sanitize
      :param file_length_limit: bit smaller than 256 for safety
      :return:
      """
      bad_chars = ['[', ']', ',', '/', '\\', '\\w', '\\s', '-', '+', '\"', '\'', '>', '<', ' ', '=', ')', '(', ':', '^']
      for char in bad_chars:
          name = name.replace(char, "_")
  
      length = len(name)
      sha_length = 32
      real_length_limit = file_length_limit - (sha_length + 2)
      assert real_length_limit > 0, "Bad file limit length: %s %s" % (file_length_limit, real_length_limit)
      if length > file_length_limit:
          sha = get_sha(name)
          half_real_length_limit = max(1, int(real_length_limit / 2))
          name = name[0:half_real_length_limit] + "_" + sha + "_" + name[length - half_real_length_limit:length]
  
      return name
  
  
  def shutil_rmtree(*args, **kwargs):
      path = args[0]
      assert not os.path.samefile(path,
                                  '/'), "Should not be trying to remove entire root directory: %s" % str(path)
      assert not os.path.samefile(path,
                                  './'), "Should not be trying to remove entire local directory: %s" % str(path)
      return shutil.rmtree(*args, **kwargs)
  
  
  def remove(path: str):
      try:
          if path is not None and os.path.exists(path):
              if os.path.isdir(path):
                  shutil_rmtree(path, ignore_errors=True)
              else:
                  with contextlib.suppress(FileNotFoundError):
                      os.remove(path)
      except:
          pass
  
  
  def makedirs(path, exist_ok=True, tmp_ok=False, use_base=False):
      """
      Avoid some inefficiency in os.makedirs()
      :param path:
      :param exist_ok:
      :param tmp_ok:  use /tmp if can't write locally
      :param use_base:
      :return:
      """
      if path is None:
          return path
      # if base path set, make relative to that, unless user_path absolute path
      if use_base:
          if os.path.normpath(path) == os.path.normpath(os.path.abspath(path)):
              pass
          else:
              if os.getenv('H2OGPT_BASE_PATH') is not None:
                  base_dir = os.path.normpath(os.getenv('H2OGPT_BASE_PATH'))
                  path = os.path.normpath(path)
                  if not path.startswith(base_dir):
                      path = os.path.join(os.getenv('H2OGPT_BASE_PATH', ''), path)
                      path = os.path.normpath(path)
  
      if os.path.isdir(path) and os.path.exists(path):
          assert exist_ok, "Path already exists"
          return path
      try:
          os.makedirs(path, exist_ok=exist_ok)
          return path
      except FileExistsError:
          # e.g. soft link
          return path
      except PermissionError:
          if tmp_ok:
              path0 = path
              path = os.path.join('/tmp/', path)
              print("Permission denied to %s, using %s instead" % (path0, path), flush=True)
              os.makedirs(path, exist_ok=exist_ok)
              return path
          else:
              raise
  
  
  def atomic_move_simple(src, dst):
      try:
          shutil.move(src, dst)
      except (shutil.Error, FileExistsError):
          pass
      remove(src)
  
  
  def atomic_copy(src="", dst=None, content=None):
      my_uuid = uuid.uuid4()
      src_tmp = None
      if content is not None:
          src_tmp = os.path.join('./', str(my_uuid))
          with open(src_tmp, 'wt') as f:
              f.write(content)
      elif src != "":
          src_tmp = src + str(my_uuid)
          shutil.copy(src, src_tmp)
      if src_tmp is not None:
          makedirs(os.path.dirname(dst), exist_ok=True)
          shutil.move(src_tmp, dst)
          remove(src_tmp)
  
  
  def move_tree(src, dst, include_root=True):
      makedirs(dst, exist_ok=True)
      if include_root:
          shutil.move(src, dst)
      else:
          for (path, dirs, files) in os.walk(src):
              new_path = path.replace(src, dst)
              makedirs(new_path, exist_ok=True)
              for file in files:
                  filename = os.path.join(path, file)
                  new_filename = os.path.join(new_path, file)
                  # print("%s -> %s" % (filename, new_filename))
                  try:
                      # only move if file doesn't already exist
                      # this ensures use earliest installation if used for pip install race avoidance
                      if not os.path.isfile(new_filename):
                          shutil.move(filename, new_filename)
                  except FileExistsError:
                      pass
          for (path, dirs, files) in os.walk(src):
              shutil.rmtree(path, ignore_errors=True)
  
  
  def copy_tree(src, dst, follow_symlink=False):
      makedirs(dst, exist_ok=True)
      for (path, dirs, files) in os.walk(src, followlinks=follow_symlink):
          new_path = path.replace(src, dst)
          makedirs(new_path, exist_ok=True)
          for file in files:
              filename = os.path.join(path, file)
              new_filename = os.path.join(new_path, file)
              # print("%s -> %s" % (filename, new_filename))
              try:
                  atomic_copy(filename, new_filename)
              except FileNotFoundError:
                  pass
  
  
  def download_simple(url, dest=None, overwrite=False, verbose=False):
      if dest is None:
          dest = os.path.basename(url)
      base_path = os.path.dirname(dest)
      if base_path:  # else local path
          base_path = makedirs(base_path, exist_ok=True, tmp_ok=True, use_base=True)
          dest = os.path.join(base_path, os.path.basename(dest))
  
      if os.path.isfile(dest):
          if not overwrite:
              if verbose:
                  print("Already have %s from url %s, delete file if invalid" % (dest, str(url)), flush=True)
              return dest
          else:
              remove(dest)
  
      if verbose:
          print("BEGIN get url %s" % str(url), flush=True)
      if url.startswith("file://"):
          from requests_file import FileAdapter
          s = requests.Session()
          s.mount('file://', FileAdapter())
          url_data = s.get(url, stream=True)
      else:
          url_data = requests.get(url, stream=True)
      if verbose:
          print("GOT url %s" % str(url), flush=True)
  
      if url_data.status_code != requests.codes.ok:
          msg = "Cannot get url %s, code: %s, reason: %s" % (
              str(url),
              str(url_data.status_code),
              str(url_data.reason),
          )
          raise requests.exceptions.RequestException(msg)
      url_data.raw.decode_content = True
  
      uuid_tmp = str(uuid.uuid4())[:6]
      dest_tmp = dest + "_dl_" + uuid_tmp + ".tmp"
  
      # Sizes in bytes.
      total_size = int(url_data.headers.get("content-length", 0))
      block_size = 1024
  
      with tqdm(total=total_size, unit="B", unit_scale=True) as progress_bar:
          with open(dest_tmp, "wb") as file:
              for data in url_data.iter_content(block_size):
                  progress_bar.update(len(data))
                  file.write(data)
  
      if total_size != 0 and progress_bar.n != total_size:
          raise RuntimeError("Could not download file")
  
      atomic_move_simple(dest_tmp, dest)
      if verbose:
          print("DONE url %s" % str(url), flush=True)
      return dest
  
  
  def download(url, dest=None, dest_path=None):
      if dest_path is not None:
          dest = os.path.join(dest_path, os.path.basename(url))
          if os.path.isfile(dest):
              print("already downloaded %s -> %s" % (url, dest))
              return dest
      elif dest is not None:
          if os.path.exists(dest):
              print("already downloaded %s -> %s" % (url, dest))
              return dest
      else:
          uuid_tmp = "dl2_" + str(uuid.uuid4())[:6]
          dest = uuid_tmp + os.path.basename(url)
  
      print("downloading %s to %s" % (url, dest))
  
      if url.startswith("file://"):
          from requests_file import FileAdapter
          s = requests.Session()
          s.mount('file://', FileAdapter())
          url_data = s.get(url, stream=True)
      else:
          url_data = requests.get(url, stream=True)
  
      if url_data.status_code != requests.codes.ok:
          msg = "Cannot get url %s, code: %s, reason: %s" % (
              str(url), str(url_data.status_code), str(url_data.reason))
          raise requests.exceptions.RequestException(msg)
      url_data.raw.decode_content = True
      dirname = os.path.dirname(dest)
      if dirname != "" and not os.path.isdir(dirname):
          base_path = os.path.dirname(dest)
          base_path = makedirs(base_path, exist_ok=True, tmp_ok=True, use_base=True)
          dest = os.path.join(base_path, os.path.basename(dest))
      uuid_tmp = "dl3_" + str(uuid.uuid4())[:6]
      dest_tmp = dest + "_" + uuid_tmp + ".tmp"
      with open(dest_tmp, 'wb') as f:
          shutil.copyfileobj(url_data.raw, f)
      try:
          shutil.move(dest_tmp, dest)
      except FileExistsError:
          pass
      remove(dest_tmp)
      return dest
  
  
  def get_doc(x):
      return x.page_content
  
  
  def get_source(x):
      return x.metadata.get('source', "UNKNOWN SOURCE")
  
  
  def markdown_to_html(content):
      import markdown
  
      # Create a Markdown object
      markdowner = markdown.Markdown()
  
      # Convert the Markdown block to HTML
      try:
          html = markdowner.reset().convert(content)
      except Exception as e:
          # FIXME:
          print("Invalid conversion of markdown to html: %s\n\n%s" % (content, str(e)))
          html = content
  
      return html
  
  
  def is_markdown(string):
      """Returns True if the string is markdown, False otherwise."""
  
      # Check for the presence of double square brackets
      if re.search(r'\[\[.+?\]\]', string):
          return True
  
      # Check for the presence of angle brackets
      if re.search(r'<.+?>', string):
          return False
  
      # If neither of the above patterns are found, assume the string is markdown
      return True
  
  
  def get_accordion_named(content, title, font_size=8):
      # content = content.replace('\n', '<br>')
      if is_markdown(content):
          content = markdown_to_html(content)
      return f"""<details><summary><font size="{font_size}">{title}</font></summary><font size="{font_size}">{content}</font></details>"""
  
  
  def hyde_titles(level):
      if level == 0:
          title = "HYDE 0: LLM"
      elif level == 1:
          title = "HYDE 1: Prompt+LLM embedding"
      elif level == 2:
          title = "HYDE 2: Prompt+LLM+HYDE 1 embedding"
      elif level == 3:
          title = "HYDE 3: Prompt+LLM+HYDE 1&2 embedding"
      else:
          title = "HYDE 4: Prompt+LLM+HYDE 1&2&3 embedding"
      return title
  
  
  def get_accordion(x, font_size=2, head_acc=50):
      title = x.page_content[:head_acc].replace("\n", ' ').replace("<br>", ' ').replace("<p>", ' ').replace("\r", ' ')
      content = x.page_content
      return f"""<details><summary><font size="{font_size}">{title}</font></summary><font size="{font_size}">{content}</font></details>"""
  
  
  def get_url(x, from_str=False, short_name=False, font_size=2):
      if not from_str:
          source = x.metadata['source']
      else:
          source = x
      if short_name:
          source_name = get_short_name(source)
      else:
          source_name = source
      if source.startswith('http://') or source.startswith('https://'):
          return """<font size="%s"><a href="%s" target="_blank"  rel="noopener noreferrer">%s</a></font>""" % (
              font_size, source, source_name)
      elif '<a href=' not in source:
          return """<font size="%s"><a href="file:///%s" target="_blank"  rel="noopener noreferrer">%s</a></font>""" % (
              font_size, source, source_name)
      else:
          # already filled
          return source
  
  
  def get_short_name(name, maxl=50):
      if name is None:
          return ''
      length = len(name)
      if length > maxl:
          allow_length = maxl - 3
          half_allowed = max(1, int(allow_length / 2))
          name = name[0:half_allowed] + "..." + name[length - half_allowed:length]
      return name
  
  
  def cuda_vis_check(total_gpus):
      """Helper function to count GPUs by environment variable
      Stolen from Jon's h2o4gpu utils
      """
      cudavis = os.getenv("CUDA_VISIBLE_DEVICES")
      which_gpus = []
      if cudavis is not None:
          # prune away white-space, non-numerics,
          # except commas for simple checking
          cudavis = "".join(cudavis.split())
          import re
          cudavis = re.sub("[^0-9,]", "", cudavis)
  
          lencudavis = len(cudavis)
          if lencudavis == 0:
              total_gpus = 0
          else:
              total_gpus = min(
                  total_gpus,
                  os.getenv("CUDA_VISIBLE_DEVICES").count(",") + 1)
              which_gpus = os.getenv("CUDA_VISIBLE_DEVICES").split(",")
              which_gpus = [int(x) for x in which_gpus]
      else:
          which_gpus = list(range(0, total_gpus))
  
      return total_gpus, which_gpus
  
  
  def get_ngpus_vis(raise_if_exception=True):
      ngpus_vis1 = None
  
      shell = False
      if shell:
          cmd = "nvidia-smi -L 2> /dev/null"
      else:
          cmd = ["nvidia-smi", "-L"]
  
      try:
          timeout = 5 * 3
          o = subprocess.check_output(cmd, shell=shell, timeout=timeout)
          lines = o.decode("utf-8").splitlines()
          ngpus_vis1 = 0
          for line in lines:
              if 'Failed to initialize NVML' not in line:
                  ngpus_vis1 += 1
      except (FileNotFoundError, subprocess.CalledProcessError, OSError):
          # GPU systems might not have nvidia-smi, so can't fail
          pass
      except subprocess.TimeoutExpired as e:
          print('Failed get_ngpus_vis: %s' % str(e))
          if raise_if_exception:
              raise
  
      if ngpus_vis1 is None:
          import torch
          if get_device() == 'cuda':
              ngpus_vis1 = torch.cuda.device_count() if torch.cuda.is_available() else 0
          else:
              ngpus_vis1 = 0
  
      ngpus_vis1, which_gpus = cuda_vis_check(ngpus_vis1)
      return ngpus_vis1
  
  
  def get_mem_gpus(raise_if_exception=True, ngpus=None):
      totalmem_gpus1 = 0
      usedmem_gpus1 = 0
      freemem_gpus1 = 0
  
      if ngpus == 0:
          return totalmem_gpus1, usedmem_gpus1, freemem_gpus1
  
      try:
          cmd = "nvidia-smi -q 2> /dev/null | grep -A 3 'FB Memory Usage'"
          o = subprocess.check_output(cmd, shell=True, timeout=15)
          lines = o.decode("utf-8").splitlines()
          for line in lines:
              if 'Total' in line:
                  totalmem_gpus1 += int(line.split()[2]) * 1024 ** 2
              if 'Used' in line:
                  usedmem_gpus1 += int(line.split()[2]) * 1024 ** 2
              if 'Free' in line:
                  freemem_gpus1 += int(line.split()[2]) * 1024 ** 2
      except (FileNotFoundError, subprocess.CalledProcessError, OSError):
          # GPU systems might not have nvidia-smi, so can't fail
          pass
      except subprocess.TimeoutExpired as e:
          print('Failed get_mem_gpus: %s' % str(e))
          if raise_if_exception:
              raise
  
      return totalmem_gpus1, usedmem_gpus1, freemem_gpus1
  
  
  n_gpus_global = get_ngpus_vis()
  
  
  class ForkContext(threading.local):
      """
          Set context for forking
          Ensures state is returned once done
      """
  
      def __init__(self, args=None, kwargs=None, forkdata_capable=True):
          """
          :param args:
          :param kwargs:
          :param forkdata_capable: whether fork is forkdata capable and will use copy-on-write forking of args/kwargs
          """
          self.forkdata_capable = forkdata_capable
          if self.forkdata_capable:
              self.has_args = args is not None
              self.has_kwargs = kwargs is not None
              forkdatacontext.args = args
              forkdatacontext.kwargs = kwargs
          else:
              self.has_args = False
              self.has_kwargs = False
  
      def __enter__(self):
          try:
              # flush all outputs so doesn't happen during fork -- don't print/log inside ForkContext contexts!
              sys.stdout.flush()
              sys.stderr.flush()
          except BaseException as e:
              # exit not called if exception, and don't want to leave forkdatacontext filled in that case
              print("ForkContext failure on enter: %s" % str(e))
              self.finally_act()
              raise
          return self
  
      def __exit__(self, exc_type, exc_value, exc_traceback):
          self.finally_act()
  
      def finally_act(self):
          """
              Done when exception hit or exit is reached in context
              first reset forkdatacontext as crucial to have reset even if later 2 calls fail
          :return: None
          """
          if self.forkdata_capable and (self.has_args or self.has_kwargs):
              forkdatacontext._reset()
  
  
  class _ForkDataContext(threading.local):
      def __init__(
              self,
              args=None,
              kwargs=None,
      ):
          """
          Global context for fork to carry data to subprocess instead of relying upon copy/pickle/serialization
  
          :param args: args
          :param kwargs: kwargs
          """
          assert isinstance(args, (tuple, type(None)))
          assert isinstance(kwargs, (dict, type(None)))
          self.__args = args
          self.__kwargs = kwargs
  
      @property
      def args(self) -> Tuple:
          """returns args"""
          return self.__args
  
      @args.setter
      def args(self, args):
          if self.__args is not None:
              raise AttributeError(
                  "args cannot be overwritten: %s %s" % (str(self.__args), str(self.__kwargs))
              )
  
          self.__args = args
  
      @property
      def kwargs(self) -> Dict:
          """returns kwargs"""
          return self.__kwargs
  
      @kwargs.setter
      def kwargs(self, kwargs):
          if self.__kwargs is not None:
              raise AttributeError(
                  "kwargs cannot be overwritten: %s %s" % (str(self.__args), str(self.__kwargs))
              )
  
          self.__kwargs = kwargs
  
      def _reset(self):
          """Reset fork arg-kwarg context to default values"""
          self.__args = None
          self.__kwargs = None
  
      def get_args_kwargs(self, func, args, kwargs) -> Tuple[Callable, Tuple, Dict]:
          if self.__args:
              args = self.__args[1:]
              if not func:
                  assert len(self.__args) > 0, "if have no func, must have in args"
                  func = self.__args[0]  # should always be there
          if self.__kwargs:
              kwargs = self.__kwargs
          try:
              return func, args, kwargs
          finally:
              forkdatacontext._reset()
  
      @staticmethod
      def get_args_kwargs_for_traced_func(func, args, kwargs):
          """
          Return args/kwargs out of forkdatacontext when using copy-on-write way of passing args/kwargs
          :param func: actual function ran by _traced_func, which itself is directly what mppool treats as function
          :param args:
          :param kwargs:
          :return: func, args, kwargs from forkdatacontext if used, else originals
          """
          # first 3 lines are debug
          func_was_None = func is None
          args_was_None_or_empty = args is None or len(args) == 0
          kwargs_was_None_or_empty = kwargs is None or len(kwargs) == 0
  
          forkdatacontext_args_was_None = forkdatacontext.args is None
          forkdatacontext_kwargs_was_None = forkdatacontext.kwargs is None
          func, args, kwargs = forkdatacontext.get_args_kwargs(func, args, kwargs)
          using_forkdatacontext = func_was_None and func is not None  # pulled func out of forkdatacontext.__args[0]
          assert forkdatacontext.args is None, "forkdatacontext.args should be None after get_args_kwargs"
          assert forkdatacontext.kwargs is None, "forkdatacontext.kwargs should be None after get_args_kwargs"
  
          proc_type = kwargs.get('proc_type', 'SUBPROCESS')
          if using_forkdatacontext:
              assert proc_type == "SUBPROCESS" or proc_type == "SUBPROCESS"
          if proc_type == "NORMAL":
              assert forkdatacontext_args_was_None, "if no fork, expect forkdatacontext.args None entering _traced_func"
              assert forkdatacontext_kwargs_was_None, "if no fork, expect forkdatacontext.kwargs None entering _traced_func"
          assert func is not None, "function should not be None, indicates original args[0] was None or args was None"
  
          return func, args, kwargs
  
  
  def using_conda():
      """
      Whether using conda and want to use conda
      :return:
      """
      import os, sys
      return os.path.exists(os.path.join(sys.prefix, 'conda-meta')) and os.environ.get('AVOID_FULL_CONDA') is None
  
  
  def get_python_paths():
      """
      Various python paths, same as make/get_python_paths.sh
      :return:
      """
      import os, sys
      exec_file = sys.executable
      bpath = os.path.dirname(sys.executable)
      rootpath = os.path.dirname(os.path.dirname(sys.executable))
      libpath = os.path.join(rootpath, "lib")
      includepath = os.path.join(rootpath, "include")
      from sysconfig import get_paths
      info = get_paths()
      spackagespath = info['purelib']
      pincludepath = info['platinclude']
      plibpath = info['platstdlib']
      from distutils.sysconfig import get_config_var
      plibfile = '%s/%s' % (get_config_var('LIBDIR'), get_config_var('INSTSONAME'))
      return dict(exec_file=exec_file, bpath=bpath, rootpath=rootpath, libpath=libpath, includepath=includepath,
                  spackagespath=spackagespath, pincludepath=pincludepath, plibpath=plibpath, plibfile=plibfile)
  
  
  forkdatacontext = _ForkDataContext()
  
  
  def _traced_func(func, *args, **kwargs):
      try:
          func, args, kwargs = forkdatacontext.get_args_kwargs_for_traced_func(func, args, kwargs)
          return func(*args, **kwargs)
      except BaseException as e:
          print(e)
          ex = traceback.format_exc()
          raise RuntimeError(str(ex))
  
  
  def call_subprocess_onetask(func, args=None, kwargs=None):
      if platform.system() in ['Darwin', 'Windows']:
          return func(*args, **kwargs)
      if isinstance(args, list):
          args = tuple(args)
      if args is None:
          args = ()
      if kwargs is None:
          kwargs = {}
      args = list(args)
      args = [func] + args
      args = tuple(args)
      with ForkContext(args=args, kwargs=kwargs):
          args = (None,)
          kwargs = {}
          with ProcessPoolExecutor(max_workers=1) as executor:
              future = executor.submit(_traced_func, *args, **kwargs)
              return future.result()
  
  
  class ProgressParallel(Parallel):
      def __init__(self, use_tqdm=True, total=None, *args, **kwargs):
          self._use_tqdm = use_tqdm
          self._total = total
          super().__init__(*args, **kwargs)
  
      def __call__(self, *args, **kwargs):
          with tqdm(disable=not self._use_tqdm, total=self._total) as self._pbar:
              return Parallel.__call__(self, *args, **kwargs)
  
      def print_progress(self):
          if self._total is None:
              self._pbar.total = self.n_dispatched_tasks
          self._pbar.n = self.n_completed_tasks
          self._pbar.refresh()
  
  
  def get_kwargs(func, exclude_names=None, **kwargs):
      func_names = list(inspect.signature(func).parameters)
      missing_kwargs = [x for x in func_names if x not in kwargs]
      if exclude_names:
          for k in exclude_names:
              if k in missing_kwargs:
                  missing_kwargs.remove(k)
              if k in func_names:
                  func_names.remove(k)
      assert not missing_kwargs, "Missing %s" % missing_kwargs
      kwargs = {k: v for k, v in kwargs.items() if k in func_names}
      return kwargs
  
  
  from importlib.metadata import distribution, PackageNotFoundError
  
  have_faiss = False
  
  try:
      assert distribution('faiss') is not None
      have_faiss = True
  except (PackageNotFoundError, AssertionError):
      pass
  try:
      assert distribution('faiss_gpu') is not None
      have_faiss = True
  except (PackageNotFoundError, AssertionError):
      pass
  try:
      assert distribution('faiss_cpu') is not None
      have_faiss = True
  except (PackageNotFoundError, AssertionError):
      pass
  
  have_serpapi = False
  try:
      assert distribution('google-search-results') is not None
      have_serpapi = True
  except (PackageNotFoundError, AssertionError):
      pass
  
  have_autogen = False
  try:
      assert distribution('pyautogen') is not None
      have_autogen = True
  except (PackageNotFoundError, AssertionError):
      pass
  
  
  def hash_file(file):
      try:
          import hashlib
  
          # BUF_SIZE is totally arbitrary, change for your app!
          BUF_SIZE = 65536  # lets read stuff in 64kb chunks!
  
          md5 = hashlib.md5()
          # sha1 = hashlib.sha1()
  
          if not os.path.isfile(file):
              md5.update(file.encode(encoding='UTF-8'))
          else:
              with open(file, 'rb') as f:
                  while True:
                      data = f.read(BUF_SIZE)
                      if not data:
                          break
                      md5.update(data)
                      # sha1.update(data)
      except BaseException as e:
          print("Cannot hash %s due to %s" % (file, str(e)))
          traceback.print_exc()
          return ''
      return md5.hexdigest()
  
  
  def start_faulthandler():
      # If hit server or any subprocess with signal SIGUSR1, it'll print out all threads stack trace, but wont't quit or coredump
      # If more than one fork tries to write at same time, then looks corrupted.
      import faulthandler
  
      # SIGUSR1 in h2oai/__init__.py as well
      faulthandler.enable()
      if hasattr(faulthandler, 'register'):
          # windows/mac
          import signal
          faulthandler.register(signal.SIGUSR1)
  
  
  def get_hf_server(inference_server):
      inf_split = inference_server.split("    ")
      if len(inf_split) == 3:
          assert len(inf_split) == 1 or len(inf_split) == 3
          inference_server = inf_split[0]
          headers = {"authorization": "%s %s" % (inf_split[1], inf_split[2])}
          user = None
          password = None
      else:
          ip_port_vllm = ':'.join(inference_server.split(':')[0:])
          if ip_port_vllm.startswith('https://'):
              http_prefix = 'https://'
              ip_port_vllm = ip_port_vllm[len(http_prefix):]
          elif ip_port_vllm.startswith('http://'):
              http_prefix = 'http://'
              ip_port_vllm = ip_port_vllm[len(http_prefix):]
          else:
              http_prefix = 'http://'
  
          inf_split = ip_port_vllm.split(":")
          if len(inf_split) <= 2:
              # i.e. just DNS or IP and no port or IP + port
              user = None
              password = None
          elif len(inf_split) == 3:
              # i.e. just DNS or IP, no port + user + pass = 3
              user = inf_split[len(inf_split) - 2]
              password = inf_split[len(inf_split) - 1]
              ip_port_vllm = ':'.join(inf_split[:len(inf_split) - 2])
          elif len(inf_split) == 4:
              # i.e. DNS/IP + port + user + pass = 4
              port = inf_split[len(inf_split) - 3]
              user = inf_split[len(inf_split) - 2]
              password = inf_split[len(inf_split) - 1]
              if port not in [None, 'None']:
                  ip_port_vllm = ':'.join([inf_split[0], port])
              else:
                  ip_port_vllm = inf_split[0]
  
          else:
              raise ValueError("Malformed inference_server=%s" % inference_server)
  
          headers = None
  
          # remove None if port was None
          if 'None' in ip_port_vllm.split(':'):
              ip_port_vllm = ':'.join([x for x in ip_port_vllm.split(':') if x != 'None'])
          inference_server = http_prefix + ip_port_vllm
      return inference_server, headers, user, password
  
  
  class FakeTokenizer:
      """
      1) For keeping track of model_max_length
      2) For when model doesn't directly expose tokenizer but need to count tokens
      """
  
      def __init__(self, model_max_length=2048,
                   encoding_name="cl100k_base",
                   is_openai=False,
                   is_anthropic=False,
                   is_google=False,
                   is_hf=False,
                   tokenizer=None,
                   is_llama_cpp=False,
                   is_super_fake=False,
                   is_mistral=False,
                   ):
          if model_max_length is None:
              assert not (
                      is_openai or is_anthropic or is_google), "Should have set model_max_length for OpenAI or Anthropic or Google"
              model_max_length = 2048
          self.is_openai = is_openai
          self.is_anthropic = is_anthropic
          self.is_google = is_google
          self.is_hf = is_hf
          self.is_llama_cpp = is_llama_cpp
          self.is_super_fake = is_super_fake
          self.is_mistral = is_mistral
          self.tokenizer = tokenizer
          self.model_max_length = model_max_length
          if not self.is_openai and not self.is_anthropic and not self.is_llama_cpp:
              # don't push limit, since if using fake tokenizer, only estimate, and seen underestimates by order 250
              self.model_max_length -= 250
          self.encoding_name = encoding_name
          if self.is_super_fake:
              self.encoding = None
          # The first time this runs, it will require an internet connection to download. Later runs won't need an internet connection.
          elif not (self.is_anthropic or self.is_google or self.is_mistral):
              import tiktoken
              self.encoding = tiktoken.get_encoding(self.encoding_name)
          else:
              self.encoding = None
  
      def encode(self, x, *args, return_tensors="pt", **kwargs):
          if not x:
              return dict(input_ids=[])
          if self.is_super_fake:
              input_ids = self.heuristic_encode(x)
              # avoid torch tensor
              return dict(input_ids=input_ids)
          elif self.is_llama_cpp:  # and len(x) < 4 * 4 * self.model_max_length: # don't use llama.cpp if too much
              input_ids = self.tokenizer.tokenize(b" " + x.encode("utf-8"))
          elif self.is_anthropic:
              from anthropic import Anthropic
              client = Anthropic()
              tokenizer = client.get_tokenizer()
              input_ids = tokenizer.encode(x).ids
          elif self.is_google:
              input_ids = [0] * self.tokenizer(x).total_tokens  # fake tokens
          elif self.is_hf:
              input_ids = self.tokenizer.encode(x)
          elif self.is_mistral:
              from mistral_common.protocol.instruct.request import ChatCompletionRequest
              input_ids = self.tokenizer.encode_chat_completion(
                  ChatCompletionRequest(messages=[dict(role='user', content=x)])).tokens
          else:
              input_ids = self.encoding.encode(x, disallowed_special=())
          if return_tensors == 'pt' and isinstance(input_ids, list):
              import torch
              input_ids = torch.tensor(input_ids)
          return dict(input_ids=input_ids)
  
      def decode(self, x, *args, **kwargs):
          if self.is_super_fake:
              return ['aaaa'] * len(x)  # fake
          elif self.is_llama_cpp:  # and len(x) < 4 * self.model_max_length:   # don't use llama.cpp if too much
              return self.tokenizer.detokenize(x)
          elif self.is_anthropic:
              from anthropic import Anthropic
              client = Anthropic()
              tokenizer = client.get_tokenizer()
              return tokenizer.decode(x)
          elif self.is_google:
              return ['a'] * len(x)  # fake
          elif self.is_mistral:
              return ['a'] * len(x)  # fake
          elif self.is_hf:
              return self.tokenizer.decode(x)
          # input is input_ids[0] form
          return self.encoding.decode(x)
  
      def num_tokens_from_string(self, prompt: str) -> int:
          """Returns the number of tokens in a text string."""
          if self.is_super_fake:
              return len(self.heuristic_encode(prompt))
          elif self.is_anthropic:
              from anthropic import Anthropic
              client = Anthropic()
              return client.count_tokens(prompt)
          elif self.is_google:
              return self.tokenizer(prompt)
          elif self.is_mistral:
              return len(self.encode(prompt))
          elif self.is_hf:
              return len(self.tokenizer.encode(prompt))
          num_tokens = len(self.encode(prompt)['input_ids'])
          return num_tokens
  
      def heuristic_encode(self, text: str) -> list:
          """
          A heuristic-based approach to estimate token counts.
          """
          total_tokens = len(text) // 4 if len(text) >= 4 else 1
          return [0] * total_tokens
  
      def __call__(self, x, *args, **kwargs):
          return self.encode(x, *args, **kwargs)
  
  
  def get_local_ip():
      import socket
      s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
      try:
          # doesn't even have to be reachable
          s.connect(('10.255.255.255', 1))
          IP = s.getsockname()[0]
      except Exception:
          IP = '127.0.0.1'
      finally:
          s.close()
      return IP
  
  
  try:
      assert distribution('langchain') is not None
      have_langchain = True
  except (PackageNotFoundError, AssertionError):
      have_langchain = False
  
  import distutils.spawn
  
  have_tesseract = distutils.spawn.find_executable("tesseract")
  have_libreoffice = distutils.spawn.find_executable("libreoffice")
  try:
      from weasyprint import HTML
      import doctr
  
      have_doctr = True
  except:
      have_doctr = False
  
  try:
      assert distribution('arxiv') is not None
      assert distribution('pymupdf') is not None
      have_arxiv = True
  except (PackageNotFoundError, AssertionError):
      have_arxiv = False
  
  try:
      assert distribution('pymupdf') is not None
      have_pymupdf = True
  except (PackageNotFoundError, AssertionError):
      have_pymupdf = False
  
  have_pymupdf4llm = False
  try:
      assert distribution('pymupdf4llm') is not None
      have_pymupdf4llm = False  # too slow, avoid for now
  except (PackageNotFoundError, AssertionError):
      pass
  
  try:
      assert distribution('selenium') is not None
      have_selenium = True
  except (PackageNotFoundError, AssertionError):
      have_selenium = False
  
  try:
      assert distribution('pillow') is not None
      have_pillow = True
  except (PackageNotFoundError, AssertionError):
      have_pillow = False
  
  try:
      assert distribution('playwright') is not None
      have_playwright = True
  except (PackageNotFoundError, AssertionError):
      have_playwright = False
  
  try:
      assert distribution('jq') is not None
      have_jq = True
  except (PackageNotFoundError, AssertionError):
      have_jq = False
  
  try:
      assert distribution('optimum') is not None
      have_optimum = True
  except (PackageNotFoundError, AssertionError):
      have_optimum = False
  
  try:
      assert distribution('librosa') is not None
      have_librosa = True
  except (PackageNotFoundError, AssertionError):
      have_librosa = False
  
  try:
      assert distribution('wavio') is not None
      have_wavio = True
  except (PackageNotFoundError, AssertionError):
      have_wavio = False
  
  try:
      assert distribution('soundfile') is not None
      have_soundfile = True
  except (PackageNotFoundError, AssertionError):
      have_soundfile = False
  
  try:
      assert distribution('deepspeed') is not None
      have_deepspeed = True
  except (PackageNotFoundError, AssertionError):
      have_deepspeed = False
  
  try:
      assert distribution('emoji') is not None
      have_emoji = True
  except (PackageNotFoundError, AssertionError):
      have_emoji = False
  
  try:
      assert distribution('langid') is not None
      have_langid = True
  except (PackageNotFoundError, AssertionError):
      have_langid = False
  
  try:
      assert distribution('TTS') is not None
      have_TTS = True
  except (PackageNotFoundError, AssertionError):
      have_TTS = False
  
  try:
      assert distribution('faster_whisper') is not None
      have_use_faster = True
  except (PackageNotFoundError, AssertionError):
      have_use_faster = False
  
  try:
      assert distribution('flash_attn') is not None
      have_flash_attention = True
      have_flash_attention_2 = distribution('flash_attn').version.startswith('2.')
  except (PackageNotFoundError, AssertionError):
      have_flash_attention = False
      have_flash_attention_2 = False
  
  try:
      assert distribution('gradio') is not None
      have_gradio = True
      is_gradio_version4 = distribution('gradio').version.startswith('4.')
  except (PackageNotFoundError, AssertionError):
      have_gradio = False
      is_gradio_version4 = False
  
  try:
      assert distribution('gradio_pdf') is not None
      have_gradio_pdf = is_gradio_version4
  except (PackageNotFoundError, AssertionError):
      have_gradio_pdf = False
  
  try:
      assert distribution('pyrubberband') is not None
      have_pyrubberband = True
  except (PackageNotFoundError, AssertionError):
      have_pyrubberband = False
  
  try:
      assert distribution('fiftyone') is not None
      have_fiftyone = True
  except (PackageNotFoundError, AssertionError):
      have_fiftyone = False
  
  try:
      assert distribution('diffusers') is not None
      have_diffusers = True
  except (PackageNotFoundError, AssertionError):
      have_diffusers = False
  
  try:
      assert distribution('opencv-python-headless') is not None
      have_cv2 = True
  except (PackageNotFoundError, AssertionError):
      try:
          assert distribution('opencv-python') is not None
          have_cv2 = True
      except (PackageNotFoundError, AssertionError):
          have_cv2 = False
  
  only_unstructured_urls = os.environ.get("ONLY_UNSTRUCTURED_URLS", "0") == "1"
  only_selenium = os.environ.get("ONLY_SELENIUM", "0") == "1"
  only_playwright = os.environ.get("ONLY_PLAYWRIGHT", "0") == "1"
  
  
  def set_openai(inference_server, model_name=None):
      if inference_server.startswith('sglang'):
          inference_server_split = inference_server.split(':')
          inference_server_split[1] = None
          inference_server = ':'.join([x for x in inference_server_split if x is not None])
      if inference_server.startswith('vllm') or inference_server.startswith('sglang'):
          api_key = "EMPTY"
          inf_type = inference_server.split(':')[0].strip()
          ip_port = ':'.join(inference_server.split(':')[1:])
          if ip_port.startswith('https://'):
              http_prefix = 'https://'
              ip_port = ip_port[len(http_prefix):]
              auto_v1 = False
          elif ip_port.startswith('http://'):
              http_prefix = 'http://'
              ip_port = ip_port[len(http_prefix):]
              auto_v1 = False
          else:
              http_prefix = 'http://'
              auto_v1 = True
          if inference_server.startswith('sglang') and '/v1' not in inference_server:
              auto_v1 = True
  
          address = ':'.join(ip_port.split(':')[0:1]).strip()
          api_base = http_prefix + address
          if len(ip_port.split(':')) >= 2:
              port = ip_port.split(':')[1].strip()
              if port not in [None, 'None']:
                  api_base += ':' + port
          if len(ip_port.split(':')) >= 3:
              # if not there, use EMPTY as default
              url_path = ip_port.split(':')[2].strip()
              if url_path not in [None, 'None']:
                  api_base += url_path  # assume includes prefix of / and /v1
          if auto_v1 and not api_base.endswith('/v1'):
              api_base += '/v1'
          if len(ip_port.split(':')) >= 4:
              # if not there, use EMPTY as default
              api_key = ip_port.split(':')[3].strip()
  
          from openai import OpenAI, AsyncOpenAI
          client_args = dict(base_url=api_base, api_key=api_key)
          client = OpenAI(**client_args)
          async_client = AsyncOpenAI(**client_args)
  
          return client, async_client, inf_type, None, api_base, None, api_key
      else:
          api_key = os.getenv("OPENAI_API_KEY")
          base_url = None
          deployment_type = None
          api_version = None
          inf_type = inference_server.split(':')[0].strip()
          if len(inference_server.split(':')) >= 2:
              deployment_type = inference_server.split(':')[1].strip()
          if len(inference_server.split(':')) >= 3:
              base_url = inference_server.split(':')[2].strip()
              base_url = 'https://' + base_url
          if len(inference_server.split(':')) >= 4:
              api_version = inference_server.split(':')[3].strip()
          if inference_server.startswith('openai_azure'):
              if api_version in ['None', None]:
                  # for function tools support
                  # https://github.com/Azure/azure-rest-api-specs/tree/main/specification/cognitiveservices/data-plane/AzureOpenAI/inference/preview/2023-12-01-preview
                  # https://learn.microsoft.com/en-us/azure/ai-services/openai/api-version-deprecation
                  # https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/function-calling
                  api_version = "2024-07-01-preview"
              if os.getenv('OPENAI_AZURE_KEY') is not None:
                  # use this instead if exists
                  api_key = os.getenv("OPENAI_AZURE_KEY")
          elif api_version in ['None', None]:
              api_version = None
  
          if len(inference_server.split(':')) >= 5:
              api_key0 = inference_server.split(':')[4].strip()
              if api_key0 not in ['None', None]:
                  api_key = api_key0
  
          if deployment_type == 'None':
              deployment_type = None
          if base_url == 'None':
              base_url = None
          if base_url == 'None':
              base_url = None
  
          # cannot use non-chat model, uses old openai. stuff if go through to H2OOpenAI with chat model
          if model_name:
              chat_model = (model_name.startswith("gpt-3.5-turbo") or model_name.startswith(
                  "gpt-4")) and "-instruct" not in model_name
              if chat_model and inf_type == 'openai_azure':
                  inf_type = 'openai_azure_chat'
              if chat_model and inf_type == 'openai':
                  inf_type = 'openai_chat'
  
          from openai import OpenAI, AzureOpenAI, AsyncOpenAI, AsyncAzureOpenAI
          if inf_type in ['openai_azure', 'openai_azure_chat']:
              client_args = dict(azure_deployment=deployment_type, azure_endpoint=base_url, api_version=api_version,
                                 api_key=api_key)
              client = AzureOpenAI(**client_args)
              async_client = AsyncAzureOpenAI(**client_args)
          else:
              client_args = dict(base_url=base_url, api_key=api_key)
              client = OpenAI(**client_args)
              async_client = AsyncOpenAI(**client_args)
  
          return client, async_client, inf_type, deployment_type, base_url, api_version, api_key
  
  
  def get_model_name(model_name, openai_client):
      if os.getenv('DISABLE_OPENAI_AUTO_MODEL_NAME', '0') == '1':
          return model_name
  
      # override, required for lmdeploy
      # https://github.com/InternLM/lmdeploy/issues/1674
      # https://github.com/InternLM/lmdeploy/blob/e6468e7afda6b29d4c065f296a4e893b52bd33d5/lmdeploy/serve/proxy/proxy.py#L320
      # https://lmdeploy.readthedocs.io/en/latest/serving/api_server.html#restful-api
      try:
          model_names = openai_client.models.list().data
          if len(model_names) == 1:
              model_name = openai_client.models.list().data[0].id
          else:
              print("Too few or too many models in list so do not know which to chose: given: %s list: %s" % (
                  model_name, model_names))
      except Exception as e:
          print(f"Failed to get model name from OpenAI client, using default {model_name}: {str(e)}")
      return model_name
  
  
  def get_list_or_str(x):
      if isinstance(x, list):
          return x
      elif isinstance(x, str):
          try:
              x1 = ast.literal_eval(x)
              assert isinstance(x1, list)
              return x1
          except:
              return x
      else:
          return x
  
  
  def deepcopy_by_pickle_object(object):
      """
      Faster deepcopy, can only work on things that are picklable.  Naive Deepcopy is more general.
      Same method as for class Individual
      :param object:
      :return:
      """
      gc.disable()
      new_object = pickle.loads(pickle.dumps(object, -1))
      gc.enable()
      return new_object
  
  
  def url_alive(url):
      if not isinstance(url, str):
          return False
      try:
          response = requests.head(url)
      except Exception as e:
          return False
      else:
          if response.status_code in [200, 301, 302, 307]:
              return True
          else:
              return False
  
  
  def return_good_url(url):
      # ignore status code, just see if exists or not
      for prefix in ['', 'https://', 'http://', 'https://www.', 'http://www.']:
          try:
              url_test = prefix + url
              response = requests.head(url_test, timeout=10)
          except requests.exceptions.Timeout as e:
              response = None
              url_test = None
          except Exception as e:
              response = None
              url_test = None
          if response is not None:
              # and response.status_code < 400:
              # don't do status check, if got status, then is real URL regardless of goodness, not text
              return url_test
      return None
  
  
  def is_probably_url(url):
      if not isinstance(url, str):
          return False
      # url_alive too slow
      return any(url.startswith(prefix) for prefix in ['www.', 'http://', 'https://', 'https://www.', 'http://www.'])
  
  
  def dict_to_html(x, small=True, api=False):
      x = {k: v if not in_gradio_root(v) and not is_probably_url(v) else get_url(v, from_str=True, short_name=True) for
           k, v in x.items()}
      df = pd.DataFrame(x.items(), columns=['Key', 'Value'])
      df.index = df.index + 1
      df.index.name = 'index'
      if api:
          return tabulate.tabulate(df, headers='keys')
      else:
          res = tabulate.tabulate(df, headers='keys', tablefmt='unsafehtml')
          if small:
              return "<small>" + res + "</small>"
          else:
              return res
  
  
  def split_into_sentences(text):
      # Split text by specified punctuation followed by space or end of text
      sentences = re.split(r'(?<=[.!?]) +', text)
      return sentences
  
  
  def text_to_html(x, api=False):
      if api:
          return x
      return """
  <style>
        pre {
          overflow-x: auto;
          white-space: pre-wrap;
          white-space: -moz-pre-wrap;
          white-space: -pre-wrap;
          white-space: -o-pre-wrap;
          word-wrap: break-word;
        }
  </style>
  <pre>
  %s
  </pre>
  """ % '<br>'.join(split_into_sentences(x))
  
  
  def lg_to_gr(
          **kwargs,
  ):
      # translate:
      import torch
      n_gpus = torch.cuda.device_count() if torch.cuda.is_available() else 0
      n_gpus, _ = cuda_vis_check(n_gpus)
  
      image_audio_loaders_options = ['Caption']
      if n_gpus != 0:
          image_audio_loaders_options.extend(['CaptionLarge', 'Pix2Struct'])
      if have_tesseract:
          image_audio_loaders_options.append('OCR')
      if have_doctr:
          image_audio_loaders_options.append('DocTR')
      if have_librosa:
          image_audio_loaders_options.append('ASR')
          if n_gpus != 0:
              image_audio_loaders_options.append('ASRLarge')
      if kwargs['enable_llava'] and kwargs['llava_model']:
          image_audio_loaders_options.append('LLaVa')
  
      image_audio_loaders_options0 = []
      if have_tesseract and kwargs['enable_ocr']:
          image_audio_loaders_options0.append('OCR')
      if have_doctr and kwargs['enable_doctr']:
          image_audio_loaders_options0.append('DocTR')
      if kwargs['enable_captions']:
          if kwargs['max_quality'] and n_gpus > 0:
              # BLIP2 only on GPU
              image_audio_loaders_options0.append('CaptionLarge')
          else:
              image_audio_loaders_options0.append('Caption')
      if have_librosa and kwargs['enable_transcriptions']:
          if kwargs['max_quality'] and n_gpus > 0:
              image_audio_loaders_options0.append('ASRLarge')
          else:
              image_audio_loaders_options0.append('ASR')
      if kwargs['enable_llava'] and kwargs['llava_model'] and 'vllm' not in kwargs['llava_model']:
          # Caption like llava model is only gradio based, legacy method
          #  and n_gpus > 0  # don't require local GPUs
          # LLaVa better and faster if present
          #  and kwargs['max_quality']
          image_audio_loaders_options0.append('LLaVa')
          if 'Caption' in image_audio_loaders_options0:
              image_audio_loaders_options0.remove('Caption')
          if 'CaptionLarge' in image_audio_loaders_options0:
              image_audio_loaders_options0.remove('CaptionLarge')
  
      pdf_loaders_options = ['Unstructured', 'PyPDF', 'TryHTML']
      if have_pymupdf:
          pdf_loaders_options = ['PyMuPDF'] + pdf_loaders_options
      if have_tesseract:
          pdf_loaders_options.append('OCR')
      if have_doctr:
          pdf_loaders_options.append('DocTR')
  
      pdf_loaders_options0 = []
      if have_pymupdf and kwargs['use_pymupdf'] in [True, 'auto', 'on']:
          pdf_loaders_options0.append('PyMuPDF')
      if kwargs['enable_pdf_ocr'] in [True, 'on']:
          pdf_loaders_options0.append('OCR')
      if have_doctr and kwargs['enable_pdf_doctr'] in [True, 'on']:
          pdf_loaders_options0.append('DocTR')
      # in case my pymupdf, use pypdf as backup default
      if kwargs['use_pypdf'] in [True, 'on'] and have_pymupdf or kwargs['use_pypdf'] in [True, 'auto',
                                                                                         'on'] and not have_pymupdf:
          pdf_loaders_options0.append('PyPDF')
      if kwargs['use_unstructured_pdf'] in [True, 'on']:
          pdf_loaders_options0.append('Unstructured')
      if kwargs['try_pdf_as_html'] in [True, 'on']:
          pdf_loaders_options0.append('TryHTML')
  
      url_loaders_options = []
      if only_unstructured_urls:
          url_loaders_options.append('Unstructured')
      elif have_selenium and only_selenium:
          url_loaders_options.append('Selenium')
      elif have_playwright and only_playwright:
          url_loaders_options.append('PlayWright')
      else:
          url_loaders_options.append('Unstructured')
          if have_selenium:
              url_loaders_options.append('Selenium')
          if have_playwright:
              url_loaders_options.append('PlayWright')
              url_loaders_options.append('ScrapeWithPlayWright')
          url_loaders_options.append('ScrapeWithHttp')
      url_loaders_options0 = [url_loaders_options[0]]
  
      assert set(image_audio_loaders_options0).issubset(image_audio_loaders_options), "%s %s" % (
          image_audio_loaders_options0, image_audio_loaders_options)
      assert set(pdf_loaders_options0).issubset(pdf_loaders_options), "%s %s" % (
          pdf_loaders_options0, pdf_loaders_options)
      assert set(url_loaders_options0).issubset(url_loaders_options), "%s %s" % (
          url_loaders_options0, url_loaders_options)
  
      return image_audio_loaders_options0, image_audio_loaders_options, \
          pdf_loaders_options0, pdf_loaders_options, \
          url_loaders_options0, url_loaders_options
  
  
  def enqueue_output(file, queue):
      # for line in iter(file.readline, ''):
      for line in iter(file.readline, b'' if isinstance(file, io.BufferedReader) else ''):
          queue.put(line)
      file.close()
  
  
  def read_popen_pipes(p):
      with ThreadPoolExecutor(2) as pool:
          q_stdout, q_stderr = Queue(), Queue()
  
          pool.submit(enqueue_output, p.stdout, q_stdout)
          pool.submit(enqueue_output, p.stderr, q_stderr)
  
          while True:
              if p.poll() is not None and q_stdout.empty() and q_stderr.empty():
                  break
  
              out_line = err_line = ''
  
              try:
                  out_line = q_stdout.get_nowait()
              except Empty:
                  pass
              try:
                  err_line = q_stderr.get_nowait()
              except Empty:
                  pass
  
              yield out_line, err_line
  
  
  def start_process(cmd):
      start_cmd = sys.executable + " -i -q -u"
      print_cmd = 'print("{}")'
      cmd = [start_cmd] + [cmd]
  
      process = subprocess.Popen(cmd, stdout=subprocess.PIPE)
      for c in iter(lambda: process.stdout.read(1), b''):
          sys.stdout.write(c)
  
  
  def execute_cmd_stream(cmd=None, script_content=None, cwd=None, env=None, timeout=None, capture_output=True,
                         text=True, print_tags=False, print_literal=True, print_func=print,
                         guard_func=None, sleep=0.05,
                         max_stream_length=4096, max_memory_usage=16*1024**3):
      if script_content is None and cmd is None:
          raise ValueError("Either script_content or cmd must be provided")
  
      if script_content is not None:
          script_path = 'temp_script.py'
          with open(script_path, 'w') as f:
              f.write(script_content)
          cmd = [sys.executable, script_path]
      else:
          script_path = None
          assert cmd, "cmd must be provided if script_content is None"
  
      length = 0
      try:
          # Prepare Popen arguments
          popen_kwargs = {
              'cwd': cwd,
              'env': env,
              'bufsize': 1,  # Line-buffered
              'stdout': subprocess.PIPE,
              'stderr': subprocess.PIPE,
              'universal_newlines': text,
          }
  
          with subprocess.Popen(cmd, **popen_kwargs) as p:
              # Start psutil process to monitor memory usage
              psutil_process = psutil.Process(p.pid)
  
              sel = selectors.DefaultSelector()
              sel.register(p.stdout, selectors.EVENT_READ)
              sel.register(p.stderr, selectors.EVENT_READ)
  
              stdout_data = []
              stderr_data = []
  
              start_time = time.time()
  
              while True:
                  if timeout and time.time() - start_time > timeout:
                      p.terminate()
                      raise subprocess.TimeoutExpired(cmd, timeout)
  
                  # Monitor memory usage for the main process and all its children
                  if max_memory_usage:
                      measure_t0 = time.time()
                      try:
                          # Get memory usage of the main process and its children
                          mem_info = psutil_process.memory_info().rss
                          children = psutil_process.children(recursive=True)
                          for child in children:
                              mem_info += child.memory_info().rss
                      except psutil.NoSuchProcess:
                          mem_info = 0
  
                      # Check if the total memory usage exceeds the limit
                      if mem_info > max_memory_usage:
                          try:
                              p.terminate()
                          except Exception as e:
                              print(f"Error terminating process: {e}")
                          try:
                              p.kill()
                          except Exception as e:
                              print(f"Error killing process: {e}")
                          error = f"Process and its children used memory {mem_info} that exceeded memory limit of {max_memory_usage} bytes detected in {time.time() - measure_t0}."
                          stderr_data.append(error)
                          print(f"OOM on cmd:\n\n{cmd}\n\n", flush=True, file=sys.stderr)
  
                  events = sel.select(timeout=1)
                  if not events and p.poll() is not None:
                      break  # No more events and the process has exited
  
                  for key, _ in events:
                      data = key.fileobj.readline()
                      if not data:  # EOF
                          sel.unregister(key.fileobj)
                          continue
  
                      if guard_func:
                          data = guard_func(data)
  
                      if key.fileobj is p.stdout:
                          stdout_data.append(data)
                          if length + len(data) <= max_stream_length:
                              if print_tags:
                                  if data.strip():
                                      print_func(f"STDOUT: {data.strip()}")
                              elif print_literal:
                                  print_func(data, end='')
                              else:
                                  print_func(data)
                          length += len(data)
                      elif key.fileobj is p.stderr:
                          stderr_data.append(data)
                          if length + len(data) <= max_stream_length:
                              if print_tags:
                                  if data.strip():
                                      print_func(f"STDERR: {data.strip()}")
                              elif print_literal:
                                  print_func(data, end='')
                              else:
                                  print_func(data)
                          length += len(data)
  
                  if p.poll() is not None and not sel.get_map():
                      break  # Process has exited and no more data to read
  
                  # sleep shouldn't be too long or else will get chunky streaming and not detect memory usage rapidly enough
                  # sleep shouldn't be too short or else will constantly be doing psutil stuff
                  time.sleep(sleep)
  
              p.wait(timeout=timeout)
  
          # Prepare return object similar to subprocess.CompletedProcess
          return subprocess.CompletedProcess(
              args=cmd,
              returncode=p.returncode,
              stdout=''.join(stdout_data) if capture_output else None,
              stderr=''.join(stderr_data) if capture_output else None
          )
  
      finally:
          if script_path and os.path.exists(script_path):
              os.remove(script_path)
  
  
  def str_to_list(x, allow_none=False):
      if isinstance(x, str):
          if len(x.strip()) > 0:
              if x.strip().startswith('['):
                  try:
                      x = ast.literal_eval(x.strip())
                  except Exception:
                      print("bad x: %s" % x, flush=True)
                      raise
              else:
                  raise ValueError("Invalid str_to_list for %s" % x)
          else:
              x = []
      elif x is None and not allow_none:
          x = []
      if allow_none:
          assert isinstance(x, (type(None), list))
      else:
          assert isinstance(x, list)
      return x
  
  
  def str_to_dict(x):
      if isinstance(x, str):
          if len(x.strip()) > 0:
              if x.strip().startswith('{'):
                  x = ast.literal_eval(x.strip())
              else:
                  raise ValueError("Invalid str_to_dict for %s" % x)
          else:
              x = {}
      elif x is None:
          x = {}
      assert isinstance(x, dict)
      return x
  
  
  def get_token_count(x, tokenizer, token_count_fun=None, add_special_tokens=True):
      # NOTE: Somewhat duplicates H2OTextGenerationPipeline.get_token_count()
      # handle ambiguity in if get dict or list
      other_kwargs = dict(add_special_tokens=add_special_tokens) if hasattr(tokenizer, 'add_special_tokens') else {}
      if tokenizer is not None:
          if hasattr(tokenizer, 'encode'):
              tokens = tokenizer.encode(x, **other_kwargs)
          else:
              tokens = tokenizer(x, **other_kwargs)
          if isinstance(tokens, dict) and 'input_ids' in tokens:
              tokens = tokens['input_ids']
          if isinstance(tokens, list):
              n_tokens = len(tokens)
          elif len(tokens.shape) == 2:
              n_tokens = tokens.shape[1]
          elif len(tokens.shape) == 1:
              n_tokens = tokens.shape[0]
          else:
              raise RuntimeError("Cannot handle tokens: %s" % tokens)
      elif token_count_fun is not None:
          assert callable(token_count_fun)
          other_kwargs = dict(add_special_tokens=add_special_tokens) if hasattr(token_count_fun,
                                                                                'add_special_tokens') else {}
          n_tokens = token_count_fun(x, **other_kwargs)
      else:
          tokenizer = FakeTokenizer()
          n_tokens = tokenizer.num_tokens_from_string(x)
      return n_tokens
  
  
  def reverse_ucurve_list(lst):
      if not lst:
          return []
      if len(lst) == 1:
          return lst
      if len(lst) == 2:
          return [lst[1], lst[0]]
  
      front_list = []
      end_list = []
  
      for i, item in enumerate(lst):
          if i % 2 == 0:
              end_list.append(item)
          else:
              front_list.append(item)
  
      return front_list + end_list[::-1]
  
  
  def undo_reverse_ucurve_list(lst):
      if not lst:
          return []
      if len(lst) == 1:
          return lst
      if len(lst) == 2:
          return [lst[1], lst[0]]
  
      # Split the list into two halves: the first half and the second half (reversed)
      mid = len(lst) // 2
      first_half = lst[:mid]
      second_half = lst[mid:][::-1]
  
      # Merge the two halves by taking elements alternatively from the second half and then the first half
      result = []
      for i in range(mid):
          result.append(second_half[i])
          result.append(first_half[i])
  
      # If the length of the list is odd, append the last element of the second half
      if len(lst) % 2 != 0:
          result.append(second_half[-1])
  
      return result
  
  
  def get_size(start_path='.'):
      total_size = 0
      for dirpath, dirnames, filenames in os.walk(start_path):
          for f in filenames:
              fp = os.path.join(dirpath, f)
              # skip if it is symbolic link
              if not os.path.islink(fp):
                  total_size += os.path.getsize(fp)
  
      return total_size
  
  
  def get_test_name_core():
      tn = os.environ['PYTEST_CURRENT_TEST'].split(':')[-1]
      tn = "_".join(tn.split(' ')[:-1])  # skip (call) at end
      return sanitize_filename(tn)
  
  
  class FullSet(set):
      def __contains__(self, item):
          return True
  
  
  import os
  
  
  def create_relative_symlink(target, link_name):
      """
      Creates a relative symlink to a target from a link location, ensuring parent directories exist.
      The target can be either a file or a directory.
  
      Parameters:
      - target: The path to the target file or directory. This can be an absolute or a relative path.
      - link_name: The path where the symlink will be created. This should include the name of the symlink itself.
  
      Raises:
      - ValueError: If the target does not exist.
      """
      # Ensure the target exists
      if not os.path.exists(target):
          raise ValueError("Target does not exist: " + target)
  
      # Calculate the absolute paths
      target_abs = os.path.abspath(target)
      link_dir = os.path.dirname(os.path.abspath(link_name))
  
      # Ensure the parent directory of the link exists
      os.makedirs(link_dir, exist_ok=True)
  
      # Calculate the relative path for the symlink
      relative_path = os.path.relpath(target_abs, link_dir)
  
      # Remove the link if it already exists
      if os.path.exists(link_name) or os.path.islink(link_name):
          os.remove(link_name)
  
      # Create the symlink
      os.symlink(relative_path, link_name)
      print(f"Symlink created: {link_name} -> {relative_path}")
  
  
  def get_gradio_tmp():
      gradio_tmp = '/tmp/gradio'
      makedirs(gradio_tmp, exist_ok=True)  # won't hurt if soft link if exists
      gradio_tmp = os.path.realpath(gradio_tmp)
      return gradio_tmp
  
  
  def in_gradio_root(file):
      ret = False
      ret |= isinstance(file, str) and os.path.isfile(file) and os.path.abspath(file).startswith('/tmp/gradio')
      ret |= isinstance(file, str) and os.path.isfile(file) and os.path.abspath(file).startswith(get_gradio_tmp())
      return ret
  
  
  def get_is_gradio_h2oai():
      try:
          import gradio as gr
          return gr.__h2oai__
      except:
          return False
  
  
  def split_list(input_list, split_size):
      for i in range(0, len(input_list), split_size):
          yield input_list[i:i + split_size]
  
  
  def get_lock_file(name):
      lock_type = name
      base_path = os.path.join('locks', '%s_locks' % name)
      base_path = makedirs(base_path, exist_ok=True, tmp_ok=True, use_base=True)
      lock_file = os.path.join(base_path, "%s.lock" % lock_type)
      makedirs(os.path.dirname(lock_file))  # ensure made
      return lock_file
  
  
  def merge_dict(dict1, dict2):
      ret = dict1.copy()
      ret.update(dict2)
      return ret
  
  
  def is_uuid4(string):
      # Regular expression to match the UUID v4 format
      pattern = re.compile(r'^[a-f0-9]{8}-[a-f0-9]{4}-4[a-f0-9]{3}-[89ab][a-f0-9]{3}-[a-f0-9]{12}$', re.IGNORECASE)
      return bool(pattern.match(string))
  
  
  def is_full_git_hash(s):
      # This regex checks for exactly 40 hexadecimal characters.
      return bool(re.fullmatch(r'[0-9a-f]{40}', s))
  
  
  def get_show_username(username1):
      if split_google in username1:
          show_username = split_google.join(username1.split(split_google)[0:1])
      else:
          show_username = username1
      return show_username
  
  
  # for extracting code blocks
  pattern = re.compile(r"```(.*?)(\n[\s\S]*?)?```", re.DOTALL)
  
  
  def get_code_blocks(response):
      return pattern.findall(response)
  
  
  def get_json(response, fixup=True, json_schema_type=None):
      is_list = isinstance(response, list)
      if not is_list:
          response = [response]
      response_new = [_get_json(x, fixup=fixup, json_schema_type=json_schema_type) for x in response]
      if not is_list:
          response_new = response_new[0]
      return response_new
  
  
  def extract_values(data):
      if isinstance(data, dict):
          if 'type' in data and 'value' in data:
              return data['value']
          elif 'items' in data:
              return [extract_values(item) for item in data['items']]
          elif 'properties' in data:
              return {key: extract_values(value) for key, value in data['properties'].items()}
          elif 'enum' in data:
              return data['enum']  # return the enum values
          elif 'const' in data:
              return data['const']  # return the const value
          elif 'oneOf' in data:
              return [extract_values(item) for item in data['oneOf']]
          elif 'anyOf' in data:
              return [extract_values(item) for item in data['anyOf']]
          elif 'allOf' in data:
              return [extract_values(item) for item in data['allOf']]
          else:
              return {key: extract_values(value) for key, value in data.items()}
      elif isinstance(data, list):
          return [extract_values(item) for item in data]
      else:
          return data
  
  
  # Function to check if JSON contains schema information
  def contains_schema(data):
      if isinstance(data, dict):
          if 'type' in data and 'value' in data:
              return True
          for key, value in data.items():
              if contains_schema(value):
                  return True
      elif isinstance(data, list):
          for item in data:
              if contains_schema(item):
                  return True
      return False
  
  
  # Main function to handle both schema and regular JSON
  def handle_json(data):
      if contains_schema(data):
          return extract_values(data)
      else:
          return data
  
  
  def repair_json_by_type(response, json_schema_type=None):
      # WIP for later
      if json_schema_type in ['object', None]:
          from json_repair import repair_json
          response_str = response
          response = repair_json(response)
          if response in ['""', """''""", '', None]:
              return {}
          try:
              # assumes already dict
              response = handle_json(json.loads(response))
              if isinstance(response, list) and len(response) >= 1 and not response_str.startswith('['):
                  response = response[-1]  # take last if list, if was not pure list response
              return json.dumps(response)
          except Exception as e:
              print("Did not extract_values: %s" % str(e))
              return response
      else:
          from json_repair import repair_json
          return repair_json(response)
  
  
  def _get_json(response, fixup=True, json_schema_type=None):
      if fixup:
          # first rely upon json_repair package, handles code block extraction as well automatically
          try:
              response0 = repair_json_by_type(response, json_schema_type=json_schema_type)
              if response0:
                  return response0
          except Exception as e:
              # FIXME: best effort, don't understand if package will hae issues
              print("repair_json exception1: %s: %s" % (str(e), response))
  
      # if json_repair fails, try to extract code block content
      # sIf content is found (not an empty string), return None (or possibly an empty string as per updated logic)
      response0 = extract_code_block_content(response)
      if response0:
          if fixup:
              try:
                  response0 = repair_json_by_type(response0, json_schema_type=json_schema_type)
              except Exception as e:
                  # FIXME: best effort, don't understand if package will hae issues
                  print("repair_json exception2: %s: %s" % (str(e), response))
          return response0
      # Next, check if the response looks like JSON, return it if so
      if looks_like_json(response):
          response = response.strip()
          if response.endswith('```'):
              response = response[:-3].strip()
          if fixup:
              try:
                  response = repair_json_by_type(response, json_schema_type=json_schema_type)
              except Exception as e:
                  # FIXME: best effort, don't understand if package will hae issues
                  print("repair_json exception3: %s: %s" % (str(e), response))
          return response
      # If it doesn't look like JSON, return an empty string as a default case
      return invalid_json_str
  
  
  # Adjusted pattern to match code block content accurately
  pattern_extract_codeblock = re.compile(r"```(?:[a-zA-Z]*)\s*(.*?)(```|$)", re.DOTALL)
  
  
  def preprocess_code_blocks(stream_content):
      # Remove consecutive starting code block delimiters, but keep the inner content
      stream_content = re.sub(r"```[a-zA-Z]*\n```[a-zA-Z]*", "```", stream_content)
      # Remove consecutive ending code block delimiters
      stream_content = re.sub(r"```\n```", "```", stream_content)
      return stream_content
  
  
  def extract_code_block_content(stream_content):
      # Postprocess to handle nested or consecutive code block delimiters
      stream_content = preprocess_code_blocks(stream_content)
  
      match = pattern_extract_codeblock.search(stream_content)
      if match:
          return match.group(1).strip()
      else:
          return ''
  
  
  def has_starting_code_block(text):
      pattern_partial_codeblock = re.compile(r"(^|\n|\r|<br\s*/?>)\s*```")
      return bool(pattern_partial_codeblock.search(text))
  
  
  def looks_like_json(text):
      # Strip leading whitespace and check the first non-whitespace character
      stripped_text = text.lstrip()
  
      # Check if the text starts with '{', '[', or potentially a JSON string
      if stripped_text.startswith(('{', '[', '"')):
          return True
  
      # Optionally, check for simple numeric values or null, true, false which are valid JSON
      if re.match(r'(-?\d+(\.\d+)?([eE][+-]?\d+)?|null|true|false)\s*($|[,\]}])', stripped_text):
          return True
  
      return False
  
  
  def is_json_vllm(model, base_model, inference_server, verbose=False):
      if inference_server and not inference_server.startswith('vllm') or not inference_server:
          return False
  
      if isinstance(model, dict) and 'client' in model:
          openai_client = model['client']
      else:
          openai_client, _, _, _, _, _, _ = set_openai(inference_server, model_name=base_model)
  
      vllm_version = get_vllm_version(openai_client, inference_server, verbose=verbose)
      json_vllm_version = "0.4.0"  # The version to compare against
  
      # Parse the version strings into comparable objects
      parsed_vllm_version = version.parse(vllm_version)
      parsed_json_vllm_version = version.parse(json_vllm_version)
  
      # Compare the versions
      if parsed_vllm_version >= parsed_json_vllm_version:
          return True
      else:
          return False
  
  
  def get_vllm_version(openai_client, inference_server, verbose=False):
      vllm_version = '0.3.0'
      if inference_server.startswith('vllm'):
          # https://github.com/vllm-project/vllm/blob/main/vllm/entrypoints/openai/api_server.py
          parsed_url = str(openai_client.base_url).replace("/v1", "/version")
          try:
              response = requests.get(parsed_url, timeout=int(os.getenv('REQUEST_TIMEOUT', '30')))
              if response.status_code == 200:
                  # Parsing the JSON response content to a dictionary
                  data = response.json()
                  # Accessing the version from the response
                  vllm_version = data.get('version', vllm_version)
                  if verbose:
                      print(f"vLLM Server version: {vllm_version}")
              else:
                  if verbose:
                      print(f"Failed to retrieve version, status code: {response.status_code}")
          except (requests.exceptions.Timeout, requests.exceptions.JSONDecodeError, requests.exceptions.ConnectionError):
              # if times out, assume older version, with no JSON.  Or might not be real vllm
              vllm_version = '0.3.0'
              print(f"vLLM Server version timeout, assuming: {vllm_version}")
      return vllm_version
  
  
  def get_docs_tokens(tokenizer, text_context_list=[], max_input_tokens=None, docs_joiner=docs_joiner_default):
      """
      max_input_tokens: Over all LLM calls, upper limit of total token count,
                        or single LLM call if want to know what docs fit into single call
      """
      if text_context_list is None or len(text_context_list) == 0:
          return 0, None, 0
      assert max_input_tokens is not None, "Must set max_input_tokens"
      tokens = [get_token_count(x + docs_joiner, tokenizer) for x in text_context_list]
      tokens_cumsum = np.cumsum(tokens)
      where_res = np.where(tokens_cumsum <= max_input_tokens)[0]
      # if below condition fails, then keep top_k_docs=-1 and trigger special handling next
      if where_res.shape[0] > 0:
          top_k_docs = 1 + where_res[-1]
          one_doc_size = None
          num_doc_tokens = tokens_cumsum[top_k_docs - 1]  # by index
      else:
          # if here, means 0 and just do best with 1 doc
          top_k_docs = 1
          text_context_list = text_context_list[:top_k_docs]
          # critical protection
          from h2oai_pipeline import H2OTextGenerationPipeline
          doc_content = text_context_list[0]
          doc_content, new_tokens0 = H2OTextGenerationPipeline.limit_prompt(doc_content,
                                                                            tokenizer,
                                                                            max_prompt_length=max_input_tokens)
          text_context_list[0] = doc_content
          one_doc_size = len(doc_content)
          num_doc_tokens = get_token_count(doc_content + docs_joiner, tokenizer)
          print(
              "Unexpected large chunks and can't add to context, will add 1 anyways.  Tokens %s -> %s for max_input_tokens=%s" % (
                  tokens[0], new_tokens0, max_input_tokens), flush=True)
      return top_k_docs, one_doc_size, num_doc_tokens
  
  
  def get_limited_text(hard_limit_tokens, text, tokenizer, verbose=False):
      if tokenizer is None:
          return text[:4 * hard_limit_tokens]
  
      low = 0
      high = len(text)
      best_guess = text  # Initialize best_guess to ensure it's defined
      ntokens0 = len(tokenizer.tokenize(best_guess))
      ntokens = None
  
      max_steps = 5
      steps = 0
      while low <= high:
          mid = low + (high - low) // 2  # Calculate midpoint for current search interval
          # Estimate a trial cut of the text based on mid
          trial_text_length = max(int(mid * 4), 1)  # Using mid * 4 as an estimation, ensuring at least 1 character
          trial_text = text[-trial_text_length:]  # Take text from the end, based on trial_text_length
  
          # Tokenize the trial text and count tokens
          ntokens = len(tokenizer.tokenize(trial_text))
  
          if ntokens > hard_limit_tokens:
              # If the trial exceeds the token limit, reduce 'high' to exclude the current trial length
              high = mid - 1
          else:
              # If the trial does not exceed the token limit, update 'best_guess' and increase 'low'
              best_guess = trial_text  # Update best_guess with the current trial_text
              low = mid + 1  # Attempt to include more text in the next trial
              if steps >= max_steps:
                  break
          steps += 1
  
      # 'best_guess' now contains the text that best fits the criteria
      if verbose:
          print("steps: %s ntokens0: %s/%s text0: %s ntokens: %s/%s text: %s" % (
              steps, ntokens0, hard_limit_tokens, len(text), ntokens, hard_limit_tokens, len(best_guess)))
      return best_guess
  
  
  def deduplicate_names(names):
      # Dictionary to hold the counts of each name
      name_counts = {}
      # List to store the final results
      deduplicated_names = []
  
      for name in names:
          # Check if the name already exists in the dictionary
          if name in name_counts:
              # Increment the count for this name
              name_counts[name] += 1
              # Append the new name with the count as a suffix
              deduplicated_names.append(f"{name}_{name_counts[name]}")
          else:
              # Add the name to the dictionary with a count of 0
              name_counts[name] = 0
              # Append the name as it is the first occurrence
              deduplicated_names.append(name)
  
      return deduplicated_names
  
  
  def download_image(image_url, save_dir):
      """
      Download an image from a URL and save it to a specified directory.
  
      Parameters:
      image_url (str): The URL of the image to download.
      save_dir (str): The directory path where the image will be saved.
  
      Returns:
      str or None: The file path where the image was saved, or None if an error occurred.
      """
      try:
          response = requests.get(image_url)
          response.raise_for_status()  # Check if the request was successful
  
          # Extract the file name from the URL
          parsed_url = urlparse(image_url)
          file_name = os.path.basename(parsed_url.path)
  
          # Create the full save path
          save_path = os.path.join(save_dir, file_name)
          makedirs(save_dir, exist_ok=True)
  
          # Save the image
          with open(save_path, 'wb') as file:
              file.write(response.content)
          return save_path
      except requests.exceptions.RequestException as e:
          print(f"Error downloading the image: {e}")
          return None
  
  
  # Check if the input is a URL
  url_pattern = re.compile(
      r'^(?:http|ftp)s?://'  # http:// or https://
      r'(?:(?:[A-Z0-9](?:[A-Z0-9-]{0,61}[A-Z0-9])?\.)+(?:[A-Z]{2,6}\.?|[A-Z0-9-]{2,}\.?)|'  # domain...
      r'localhost|'  # localhost...
      r'\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}|'  # ...or ipv4
      r'\[?[A-F0-9]*:[A-F0-9:]+\]?)'  # ...or ipv6
      r'(?::\d+)?'  # optional port
      r'(?:/?|[/?]\S+)$', re.IGNORECASE)
  
  
  def check_input_type(input_string):
      """
      Check if the input string is a file path, URL, or a base64 encoded image.
  
      Parameters:
      input_string (str): The input string to check.
  
      Returns:
      str: 'file', 'url', 'base64', or 'unknown' based on the input type.
      """
      if not isinstance(input_string, str):
          return 'unknown'
  
      # Check if the input string looks like a base64 encoded image
      if input_string.startswith("data:image/") or input_string.startswith("b'data:image/"):
          return 'base64'
  
      if re.match(url_pattern, input_string):
          return 'url'
  
      is_youtube = any(
          input_string.replace('http://', '').replace('https://', '').replace('www.', '').startswith(prefix) for prefix in
          url_prefixes_youtube)
      if is_youtube:
          return 'youtube'
  
      # Check if the input is a file path
      if os.path.isfile(input_string):
          return 'file'
  
      return 'unknown'
  
  
  def get_youtube_urls():
      # https://www.netify.ai/resources/applications/youtube
      base = ['googlevideo.com',
              'video.google.com',
              'video.l.google.com',
              'wide-youtube.l.google.com',
              'youtu.be',
              'youtube.ae',
              'youtube.al',
              'youtube.am',
              'youtube.at',
              'youtube.az',
              'youtube.ba',
              'youtube.be',
              'youtube.bg',
              'youtube.bh',
              'youtube.bo',
              'youtube.by',
              'youtube.ca',
              'youtube.cat',
              'youtube.ch',
              'youtube.cl',
              'youtube.co',
              'youtube.co.ae',
              'youtube.co.at',
              'youtube.co.cr',
              'youtube.co.hu',
              'youtube.co.id',
              'youtube.co.il',
              'youtube.co.in',
              'youtube.co.jp',
              'youtube.co.ke',
              'youtube.co.kr',
              'youtube.com',
              'youtube.co.ma',
              'youtube.com.ar',
              'youtube.com.au',
              'youtube.com.az',
              'youtube.com.bd',
              'youtube.com.bh',
              'youtube.com.bo',
              'youtube.com.br',
              'youtube.com.by',
              'youtube.com.co',
              'youtube.com.do',
              'youtube.com.ec',
              'youtube.com.ee',
              'youtube.com.eg',
              'youtube.com.es',
              'youtube.com.gh',
              'youtube.com.gr',
              'youtube.com.gt',
              'youtube.com.hk',
              'youtube.com.hn',
              'youtube.com.hr',
              'youtube.com.jm',
              'youtube.com.jo',
              'youtube.com.kw',
              'youtube.com.lb',
              'youtube.com.lv',
              'youtube.com.ly',
              'youtube.com.mk',
              'youtube.com.mt',
              'youtube.com.mx',
              'youtube.com.my',
              'youtube.com.ng',
              'youtube.com.ni',
              'youtube.com.om',
              'youtube.com.pa',
              'youtube.com.pe',
              'youtube.com.ph',
              'youtube.com.pk',
              'youtube.com.pt',
              'youtube.com.py',
              'youtube.com.qa',
              'youtube.com.ro',
              'youtube.com.sa',
              'youtube.com.sg',
              'youtube.com.sv',
              'youtube.com.tn',
              'youtube.com.tr',
              'youtube.com.tw',
              'youtube.com.ua',
              'youtube.com.uy',
              'youtube.com.ve',
              'youtube.co.nz',
              'youtube.co.th',
              'youtube.co.tz',
              'youtube.co.ug',
              'youtube.co.uk',
              'youtube.co.ve',
              'youtube.co.za',
              'youtube.co.zw',
              'youtube.cr',
              'youtube.cz',
              'youtube.de',
              'youtube.dk',
              'youtubeeducation.com',
              'youtube.ee',
              'youtubeembeddedplayer.googleapis.com',
              'youtube.es',
              'youtube.fi',
              'youtube.fr',
              'youtube.ge',
              'youtube.googleapis.com',
              'youtube.gr',
              'youtube.gt',
              'youtube.hk',
              'youtube.hr',
              'youtube.hu',
              'youtube.ie',
              'youtubei.googleapis.com',
              'youtube.in',
              'youtube.iq',
              'youtube.is',
              'youtube.it',
              'youtube.jo',
              'youtube.jp',
              'youtubekids.com',
              'youtube.kr',
              'youtube.kz',
              'youtube.la',
              'youtube.lk',
              'youtube.lt',
              'youtube.lu',
              'youtube.lv',
              'youtube.ly',
              'youtube.ma',
              'youtube.md',
              'youtube.me',
              'youtube.mk',
              'youtube.mn',
              'youtube.mx',
              'youtube.my',
              'youtube.ng',
              'youtube.ni',
              'youtube.nl',
              'youtube.no',
              'youtube-nocookie.com',
              'youtube.pa',
              'youtube.pe',
              'youtube.ph',
              'youtube.pk',
              'youtube.pl',
              'youtube.pr',
              'youtube.pt',
              'youtube.qa',
              'youtube.ro',
              'youtube.rs',
              'youtube.ru',
              'youtube.sa',
              'youtube.se',
              'youtube.sg',
              'youtube.si',
              'youtube.sk',
              'youtube.sn',
              'youtube.soy',
              'youtube.sv',
              'youtube.tn',
              'youtube.tv',
              'youtube.ua',
              'youtube.ug',
              'youtube-ui.l.google.com',
              'youtube.uy',
              'youtube.vn',
              'yt3.ggpht.com',
              'yt.be',
              'ytimg.com',
              'ytimg.l.google.com',
              'ytkids.app.goo.gl',
              'yt-video-upload.l.google.com']
  
      url_prefixes_youtube1 = []
      for x in base:
          url_prefixes_youtube1.extend([
              # '%s/watch?v=' % x,
              '%s' % x,
              # '%s/shorts/' % x,
          ])
      return set(url_prefixes_youtube1)
  
  
  url_prefixes_youtube = get_youtube_urls()
  
  
  def get_llama_lower_hf(llama_lower):
      if 'huggingface.co' in llama_lower and '/resolve/' in llama_lower and len(llama_lower.split('huggingface.co')) == 2:
          llama_lower_hf = llama_lower.split('huggingface.co')[1].split('resolve/')[0]
      else:
          llama_lower_hf = None
      return llama_lower_hf
  
  
  def get_depth_normal(lst):
      if isinstance(lst, list) and lst:
          return 1 + max(get_depth_normal(item) for item in lst)
      else:
          return 0
  
  
  def get_gradio_depth(lst):
      def get_depth(lst):
          if isinstance(lst, (tuple, list)) and lst:
              depths = [get_depth(item) for item in lst]
              return 1 + max(depths)
          else:
              return 0
  
      def has_single_element_sublist(lst, depth):
          if depth == 1:
              return isinstance(lst, (tuple, list)) and len(lst) == 1
          if isinstance(lst, (tuple, list)):
              return any(has_single_element_sublist(item, depth - 1) for item in lst)
          return False
  
      depth = get_depth(lst)
      if has_single_element_sublist(lst, depth):
          depth -= 1
      return depth
  
  
  def is_empty(obj):
      if obj is None:
          return True
      if isinstance(obj, (str, list, tuple, dict, set)):
          return len(obj) == 0
      if isinstance(obj, bool):
          return False
      if isinstance(obj, (int, float)):
          # Numbers can't be "empty" in the traditional sense, so go by value for them
          return False if 0 else True
      if isinstance(obj, complex):
          return obj == 0
      if isinstance(obj, bytes):
          return len(obj) == 0
      if isinstance(obj, bytearray):
          return len(obj) == 0
      if isinstance(obj, memoryview):
          return len(obj) == 0
      if isinstance(obj, range):
          return len(obj) == 0
      if isinstance(obj, frozenset):
          return len(obj) == 0
      if isinstance(obj, deque):
          return len(obj) == 0
      if isinstance(obj, array):
          return len(obj) == 0
      if isinstance(obj, (map, filter, zip)):
          # These are iterators and need to be converted to a list to check if they are empty
          return len(list(obj)) == 0
      if hasattr(obj, '__len__'):
          return len(obj) == 0
      return False
  
  
  from typing import Any, Dict, List, Union
  from typing_extensions import TypedDict
  
  
  def create_typed_dict(schema: Dict[str, Any], name: str = "Schema") -> type:
      properties = schema.get("properties", {})
      required = set(schema.get("required", []))
  
      fields: Dict[str, Union[type, Any]] = {}
      total = len(required) == len(properties)
  
      for prop, details in properties.items():
          prop_type = details.get("type")
          if prop_type == "string":
              field_type = str
          elif prop_type == "integer":
              field_type = int
          elif prop_type == "number":
              field_type = float
          elif prop_type == "boolean":
              field_type = bool
          elif prop_type == "array":
              items = details.get("items", {})
              if items.get("type") == "string":
                  field_type = List[str]
              elif items.get("type") == "object":
                  field_type = List[create_typed_dict(items, f"{name}Item")]
              else:
                  field_type = List[Any]
          elif prop_type == "object":
              field_type = create_typed_dict(details, f"{name}{prop.capitalize()}")
          else:
              field_type = Any
  
          if prop in required:
              fields[prop] = field_type
          else:
              fields[prop] = Union[field_type, None]
  
      return TypedDict(name, fields, total=total)
  
  
  def get_supports_schema(inference_server, base_model, response_format='json_object', guided_json={}, json_vllm=False,
                          just_test=False):
      if just_test:
          supports_schema = True
      else:
          supports_schema = not is_empty(guided_json) and \
                            response_format == 'json_object'
  
      supports_schema &= is_json_model(base_model, inference_server, json_vllm=json_vllm)
  
      supports_schema &= json_vllm or \
                         not is_empty(inference_server) and \
                         any(inference_server.startswith(x) for x in ['openai_chat', 'openai_azure_chat']) and \
                         not is_empty(
                             base_model) and base_model in openai_supports_functiontools + openai_supports_parallel_functiontools or \
                         not is_empty(inference_server) and \
                         inference_server.startswith('anthropic') or \
                         not is_empty(inference_server) and \
                         inference_server.startswith('google') and base_model == 'gemini-1.5-pro-latest' or \
                         not is_empty(inference_server) and \
                         inference_server.startswith('mistralai') and \
                         does_support_functiontools(inference_server, base_model)
  
      return supports_schema
  
  
  def dedup_list(x):
      x = [x.text if hasattr(x, 'text') else x for x in x]
      return list(dict.fromkeys(x))
  