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| import asyncio | |
| import functools | |
| import threading | |
| import time | |
| import traceback | |
| from threading import Thread | |
| from typing import Callable, Optional | |
| from modules import shared | |
| from modules.chat import load_character_memoized | |
| from modules.presets import load_preset_memoized | |
| # We use a thread local to store the asyncio lock, so that each thread | |
| # has its own lock. This isn't strictly necessary, but it makes it | |
| # such that if we can support multiple worker threads in the future, | |
| # thus handling multiple requests in parallel. | |
| api_tls = threading.local() | |
| def build_parameters(body, chat=False): | |
| generate_params = { | |
| 'max_new_tokens': int(body.get('max_new_tokens', body.get('max_length', 200))), | |
| 'do_sample': bool(body.get('do_sample', True)), | |
| 'temperature': float(body.get('temperature', 0.5)), | |
| 'top_p': float(body.get('top_p', 1)), | |
| 'typical_p': float(body.get('typical_p', body.get('typical', 1))), | |
| 'epsilon_cutoff': float(body.get('epsilon_cutoff', 0)), | |
| 'eta_cutoff': float(body.get('eta_cutoff', 0)), | |
| 'tfs': float(body.get('tfs', 1)), | |
| 'top_a': float(body.get('top_a', 0)), | |
| 'repetition_penalty': float(body.get('repetition_penalty', body.get('rep_pen', 1.1))), | |
| 'repetition_penalty_range': int(body.get('repetition_penalty_range', 0)), | |
| 'encoder_repetition_penalty': float(body.get('encoder_repetition_penalty', 1.0)), | |
| 'top_k': int(body.get('top_k', 0)), | |
| 'min_length': int(body.get('min_length', 0)), | |
| 'no_repeat_ngram_size': int(body.get('no_repeat_ngram_size', 0)), | |
| 'num_beams': int(body.get('num_beams', 1)), | |
| 'penalty_alpha': float(body.get('penalty_alpha', 0)), | |
| 'length_penalty': float(body.get('length_penalty', 1)), | |
| 'early_stopping': bool(body.get('early_stopping', False)), | |
| 'mirostat_mode': int(body.get('mirostat_mode', 0)), | |
| 'mirostat_tau': float(body.get('mirostat_tau', 5)), | |
| 'mirostat_eta': float(body.get('mirostat_eta', 0.1)), | |
| 'seed': int(body.get('seed', -1)), | |
| 'add_bos_token': bool(body.get('add_bos_token', True)), | |
| 'truncation_length': int(body.get('truncation_length', body.get('max_context_length', 2048))), | |
| 'ban_eos_token': bool(body.get('ban_eos_token', False)), | |
| 'skip_special_tokens': bool(body.get('skip_special_tokens', True)), | |
| 'custom_stopping_strings': '', # leave this blank | |
| 'stopping_strings': body.get('stopping_strings', []), | |
| } | |
| preset_name = body.get('preset', 'None') | |
| if preset_name not in ['None', None, '']: | |
| preset = load_preset_memoized(preset_name) | |
| generate_params.update(preset) | |
| if chat: | |
| character = body.get('character') | |
| instruction_template = body.get('instruction_template', shared.settings['instruction_template']) | |
| if str(instruction_template) == "None": | |
| instruction_template = "Vicuna-v1.1" | |
| name1, name2, _, greeting, context, _ = load_character_memoized(character, str(body.get('your_name', shared.settings['name1'])), shared.settings['name2'], instruct=False) | |
| name1_instruct, name2_instruct, _, _, context_instruct, turn_template = load_character_memoized(instruction_template, '', '', instruct=True) | |
| generate_params.update({ | |
| 'stop_at_newline': bool(body.get('stop_at_newline', shared.settings['stop_at_newline'])), | |
| 'chat_generation_attempts': int(body.get('chat_generation_attempts', shared.settings['chat_generation_attempts'])), | |
| 'mode': str(body.get('mode', 'chat')), | |
| 'name1': name1, | |
| 'name2': name2, | |
| 'context': context, | |
| 'greeting': greeting, | |
| 'name1_instruct': name1_instruct, | |
| 'name2_instruct': name2_instruct, | |
| 'context_instruct': body.get('context_instruct', context_instruct), | |
| 'turn_template': turn_template, | |
| 'chat-instruct_command': str(body.get('chat-instruct_command', shared.settings['chat-instruct_command'])), | |
| 'history': body.get('history', {'internal': [], 'visible': []}) | |
| }) | |
| return generate_params | |
| def try_start_cloudflared(port: int, max_attempts: int = 3, on_start: Optional[Callable[[str], None]] = None): | |
| Thread(target=_start_cloudflared, args=[ | |
| port, max_attempts, on_start], daemon=True).start() | |
| def _start_cloudflared(port: int, max_attempts: int = 3, on_start: Optional[Callable[[str], None]] = None): | |
| try: | |
| from flask_cloudflared import _run_cloudflared | |
| except ImportError: | |
| print('You should install flask_cloudflared manually') | |
| raise Exception( | |
| 'flask_cloudflared not installed. Make sure you installed the requirements.txt for this extension.') | |
| for _ in range(max_attempts): | |
| try: | |
| public_url = _run_cloudflared(port, port + 1) | |
| if on_start: | |
| on_start(public_url) | |
| return | |
| except Exception: | |
| traceback.print_exc() | |
| time.sleep(3) | |
| raise Exception('Could not start cloudflared.') | |
| def _get_api_lock(tls) -> asyncio.Lock: | |
| """ | |
| The streaming and blocking API implementations each run on their own | |
| thread, and multiplex requests using asyncio. If multiple outstanding | |
| requests are received at once, we will try to acquire the shared lock | |
| shared.generation_lock multiple times in succession in the same thread, | |
| which will cause a deadlock. | |
| To avoid this, we use this wrapper function to block on an asyncio | |
| lock, and then try and grab the shared lock only while holding | |
| the asyncio lock. | |
| """ | |
| if not hasattr(tls, "asyncio_lock"): | |
| tls.asyncio_lock = asyncio.Lock() | |
| return tls.asyncio_lock | |
| def with_api_lock(func): | |
| """ | |
| This decorator should be added to all streaming API methods which | |
| require access to the shared.generation_lock. It ensures that the | |
| tls.asyncio_lock is acquired before the method is called, and | |
| released afterwards. | |
| """ | |
| async def api_wrapper(*args, **kwargs): | |
| async with _get_api_lock(api_tls): | |
| return await func(*args, **kwargs) | |
| return api_wrapper | |