mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-12-01 20:04:04 +01:00
153 lines
6.7 KiB
Python
153 lines
6.7 KiB
Python
import asyncio
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import functools
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import threading
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import time
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import traceback
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from threading import Thread
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from typing import Callable, Optional
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from modules import shared
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from modules.chat import load_character_memoized
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from modules.presets import load_preset_memoized
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# We use a thread local to store the asyncio lock, so that each thread
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# has its own lock. This isn't strictly necessary, but it makes it
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# such that if we can support multiple worker threads in the future,
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# thus handling multiple requests in parallel.
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api_tls = threading.local()
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def build_parameters(body, chat=False):
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generate_params = {
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'max_new_tokens': int(body.get('max_new_tokens', body.get('max_length', 200))),
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'auto_max_new_tokens': bool(body.get('auto_max_new_tokens', False)),
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'max_tokens_second': int(body.get('max_tokens_second', 0)),
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'do_sample': bool(body.get('do_sample', True)),
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'temperature': float(body.get('temperature', 0.5)),
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'top_p': float(body.get('top_p', 1)),
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'typical_p': float(body.get('typical_p', body.get('typical', 1))),
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'epsilon_cutoff': float(body.get('epsilon_cutoff', 0)),
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'eta_cutoff': float(body.get('eta_cutoff', 0)),
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'tfs': float(body.get('tfs', 1)),
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'top_a': float(body.get('top_a', 0)),
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'repetition_penalty': float(body.get('repetition_penalty', body.get('rep_pen', 1.1))),
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'repetition_penalty_range': int(body.get('repetition_penalty_range', 0)),
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'encoder_repetition_penalty': float(body.get('encoder_repetition_penalty', 1.0)),
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'top_k': int(body.get('top_k', 0)),
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'min_length': int(body.get('min_length', 0)),
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'no_repeat_ngram_size': int(body.get('no_repeat_ngram_size', 0)),
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'num_beams': int(body.get('num_beams', 1)),
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'penalty_alpha': float(body.get('penalty_alpha', 0)),
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'length_penalty': float(body.get('length_penalty', 1)),
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'early_stopping': bool(body.get('early_stopping', False)),
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'mirostat_mode': int(body.get('mirostat_mode', 0)),
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'mirostat_tau': float(body.get('mirostat_tau', 5)),
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'mirostat_eta': float(body.get('mirostat_eta', 0.1)),
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'grammar_string': str(body.get('grammar_string', '')),
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'guidance_scale': float(body.get('guidance_scale', 1)),
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'negative_prompt': str(body.get('negative_prompt', '')),
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'seed': int(body.get('seed', -1)),
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'add_bos_token': bool(body.get('add_bos_token', True)),
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'truncation_length': int(body.get('truncation_length', body.get('max_context_length', 2048))),
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'custom_token_bans': str(body.get('custom_token_bans', '')),
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'ban_eos_token': bool(body.get('ban_eos_token', False)),
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'skip_special_tokens': bool(body.get('skip_special_tokens', True)),
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'custom_stopping_strings': '', # leave this blank
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'stopping_strings': body.get('stopping_strings', []),
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}
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preset_name = body.get('preset', 'None')
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if preset_name not in ['None', None, '']:
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preset = load_preset_memoized(preset_name)
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generate_params.update(preset)
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if chat:
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character = body.get('character')
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instruction_template = body.get('instruction_template', shared.settings['instruction_template'])
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if str(instruction_template) == "None":
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instruction_template = "Vicuna-v1.1"
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if str(character) == "None":
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character = "Assistant"
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name1, name2, _, greeting, context, _ = load_character_memoized(character, str(body.get('your_name', shared.settings['name1'])), '', instruct=False)
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name1_instruct, name2_instruct, _, _, context_instruct, turn_template = load_character_memoized(instruction_template, '', '', instruct=True)
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generate_params.update({
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'mode': str(body.get('mode', 'chat')),
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'name1': str(body.get('name1', name1)),
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'name2': str(body.get('name2', name2)),
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'context': str(body.get('context', context)),
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'greeting': str(body.get('greeting', greeting)),
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'name1_instruct': str(body.get('name1_instruct', name1_instruct)),
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'name2_instruct': str(body.get('name2_instruct', name2_instruct)),
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'context_instruct': str(body.get('context_instruct', context_instruct)),
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'turn_template': str(body.get('turn_template', turn_template)),
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'chat-instruct_command': str(body.get('chat_instruct_command', body.get('chat-instruct_command', shared.settings['chat-instruct_command']))),
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'history': body.get('history', {'internal': [], 'visible': []})
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})
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return generate_params
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def try_start_cloudflared(port: int, tunnel_id: str, max_attempts: int = 3, on_start: Optional[Callable[[str], None]] = None):
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Thread(target=_start_cloudflared, args=[
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port, tunnel_id, max_attempts, on_start], daemon=True).start()
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def _start_cloudflared(port: int, tunnel_id: str, max_attempts: int = 3, on_start: Optional[Callable[[str], None]] = None):
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try:
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from flask_cloudflared import _run_cloudflared
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except ImportError:
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print('You should install flask_cloudflared manually')
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raise Exception(
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'flask_cloudflared not installed. Make sure you installed the requirements.txt for this extension.')
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for _ in range(max_attempts):
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try:
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if tunnel_id is not None:
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public_url = _run_cloudflared(port, port + 1, tunnel_id=tunnel_id)
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else:
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public_url = _run_cloudflared(port, port + 1)
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if on_start:
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on_start(public_url)
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return
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except Exception:
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traceback.print_exc()
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time.sleep(3)
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raise Exception('Could not start cloudflared.')
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def _get_api_lock(tls) -> asyncio.Lock:
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"""
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The streaming and blocking API implementations each run on their own
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thread, and multiplex requests using asyncio. If multiple outstanding
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requests are received at once, we will try to acquire the shared lock
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shared.generation_lock multiple times in succession in the same thread,
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which will cause a deadlock.
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To avoid this, we use this wrapper function to block on an asyncio
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lock, and then try and grab the shared lock only while holding
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the asyncio lock.
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"""
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if not hasattr(tls, "asyncio_lock"):
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tls.asyncio_lock = asyncio.Lock()
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return tls.asyncio_lock
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def with_api_lock(func):
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"""
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This decorator should be added to all streaming API methods which
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require access to the shared.generation_lock. It ensures that the
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tls.asyncio_lock is acquired before the method is called, and
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released afterwards.
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"""
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@functools.wraps(func)
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async def api_wrapper(*args, **kwargs):
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async with _get_api_lock(api_tls):
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return await func(*args, **kwargs)
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return api_wrapper
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