Refactor the UI
This commit is contained in:
@@ -74,16 +74,16 @@ def generate_chat_prompt(user_input, max_new_tokens, name1, name2, context, chat
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return prompt
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def extract_message_from_reply(reply, name1, name2, stop_at_newline):
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def extract_message_from_reply(reply, state):
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next_character_found = False
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if stop_at_newline:
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if state['stop_at_newline']:
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lines = reply.split('\n')
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reply = lines[0].strip()
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if len(lines) > 1:
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next_character_found = True
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else:
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for string in [f"\n{name1}:", f"\n{name2}:"]:
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for string in [f"\n{state['name1']}:", f"\n{state['name2']}:"]:
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idx = reply.find(string)
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if idx != -1:
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reply = reply[:idx]
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@@ -92,7 +92,7 @@ def extract_message_from_reply(reply, name1, name2, stop_at_newline):
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# If something like "\nYo" is generated just before "\nYou:"
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# is completed, trim it
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if not next_character_found:
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for string in [f"\n{name1}:", f"\n{name2}:"]:
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for string in [f"\n{state['name1']}:", f"\n{state['name2']}:"]:
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for j in range(len(string) - 1, 0, -1):
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if reply[-j:] == string[:j]:
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reply = reply[:-j]
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@@ -105,21 +105,18 @@ def extract_message_from_reply(reply, name1, name2, stop_at_newline):
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return reply, next_character_found
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def chatbot_wrapper(text, generate_state, name1, name2, context, mode, end_of_turn, regenerate=False, _continue=False):
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if mode == 'instruct':
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stopping_strings = [f"\n{name1}", f"\n{name2}"]
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def chatbot_wrapper(text, state, regenerate=False, _continue=False):
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if state['mode'] == 'instruct':
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stopping_strings = [f"\n{state['name1']}", f"\n{state['name2']}"]
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else:
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stopping_strings = [f"\n{name1}:", f"\n{name2}:"]
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stopping_strings = [f"\n{state['name1']}:", f"\n{state['name2']}:"]
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# Defining some variables
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cumulative_reply = ''
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last_reply = [shared.history['internal'][-1][1], shared.history['visible'][-1][1]] if _continue else None
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just_started = True
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name1_original = name1
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visible_text = custom_generate_chat_prompt = None
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eos_token = '\n' if generate_state['stop_at_newline'] else None
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if 'pygmalion' in shared.model_name.lower():
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name1 = "You"
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eos_token = '\n' if state['stop_at_newline'] else None
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# Check if any extension wants to hijack this function call
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for extension, _ in extensions_module.iterator():
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@@ -136,28 +133,28 @@ def chatbot_wrapper(text, generate_state, name1, name2, context, mode, end_of_tu
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# Generating the prompt
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kwargs = {
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'end_of_turn': end_of_turn,
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'is_instruct': mode == 'instruct',
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'end_of_turn': state['end_of_turn'],
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'is_instruct': state['mode'] == 'instruct',
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'_continue': _continue
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}
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if custom_generate_chat_prompt is None:
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prompt = generate_chat_prompt(text, generate_state['max_new_tokens'], name1, name2, context, generate_state['chat_prompt_size'], **kwargs)
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prompt = generate_chat_prompt(text, state['max_new_tokens'], state['name1'], state['name2'], state['context'], state['chat_prompt_size'], **kwargs)
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else:
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prompt = custom_generate_chat_prompt(text, generate_state['max_new_tokens'], name1, name2, context, generate_state['chat_prompt_size'], **kwargs)
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prompt = custom_generate_chat_prompt(text, state['max_new_tokens'], state['name1'], state['name2'], state['context'], state['chat_prompt_size'], **kwargs)
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# Yield *Is typing...*
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if not any((regenerate, _continue)):
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yield shared.history['visible'] + [[visible_text, shared.processing_message]]
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# Generate
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for i in range(generate_state['chat_generation_attempts']):
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for i in range(state['chat_generation_attempts']):
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reply = None
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for reply in generate_reply(f"{prompt}{' ' if len(cumulative_reply) > 0 else ''}{cumulative_reply}", generate_state, eos_token=eos_token, stopping_strings=stopping_strings):
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for reply in generate_reply(f"{prompt}{' ' if len(cumulative_reply) > 0 else ''}{cumulative_reply}", state, eos_token=eos_token, stopping_strings=stopping_strings):
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reply = cumulative_reply + reply
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# Extracting the reply
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reply, next_character_found = extract_message_from_reply(reply, name1, name2, generate_state['stop_at_newline'])
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visible_reply = re.sub("(<USER>|<user>|{{user}})", name1_original, reply)
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reply, next_character_found = extract_message_from_reply(reply, state)
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visible_reply = re.sub("(<USER>|<user>|{{user}})", state['name1'], reply)
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visible_reply = apply_extensions(visible_reply, "output")
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# We need this global variable to handle the Stop event,
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@@ -188,28 +185,25 @@ def chatbot_wrapper(text, generate_state, name1, name2, context, mode, end_of_tu
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yield shared.history['visible']
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def impersonate_wrapper(text, generate_state, name1, name2, context, mode, end_of_turn):
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if mode == 'instruct':
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stopping_strings = [f"\n{name1}", f"\n{name2}"]
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def impersonate_wrapper(text, state):
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if state['mode'] == 'instruct':
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stopping_strings = [f"\n{state['name1']}", f"\n{state['name2']}"]
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else:
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stopping_strings = [f"\n{name1}:", f"\n{name2}:"]
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stopping_strings = [f"\n{state['name1']}:", f"\n{state['name2']}:"]
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# Defining some variables
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cumulative_reply = ''
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eos_token = '\n' if generate_state['stop_at_newline'] else None
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if 'pygmalion' in shared.model_name.lower():
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name1 = "You"
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prompt = generate_chat_prompt(text, generate_state['max_new_tokens'], name1, name2, context, generate_state['chat_prompt_size'], impersonate=True, end_of_turn=end_of_turn)
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eos_token = '\n' if state['stop_at_newline'] else None
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prompt = generate_chat_prompt(text, state['max_new_tokens'], state['name1'], state['name2'], state['context'], state['chat_prompt_size'], end_of_turn=state['end_of_turn'], impersonate=True)
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# Yield *Is typing...*
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yield shared.processing_message
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for i in range(generate_state['chat_generation_attempts']):
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for i in range(state['chat_generation_attempts']):
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reply = None
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for reply in generate_reply(f"{prompt}{' ' if len(cumulative_reply) > 0 else ''}{cumulative_reply}", generate_state, eos_token=eos_token, stopping_strings=stopping_strings):
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for reply in generate_reply(f"{prompt}{' ' if len(cumulative_reply) > 0 else ''}{cumulative_reply}", state, eos_token=eos_token, stopping_strings=stopping_strings):
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reply = cumulative_reply + reply
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reply, next_character_found = extract_message_from_reply(reply, name1, name2, generate_state['stop_at_newline'])
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reply, next_character_found = extract_message_from_reply(reply, state)
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yield reply
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if next_character_found:
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break
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@@ -220,32 +214,32 @@ def impersonate_wrapper(text, generate_state, name1, name2, context, mode, end_o
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yield reply
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def cai_chatbot_wrapper(text, generate_state, name1, name2, context, mode, end_of_turn):
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for history in chatbot_wrapper(text, generate_state, name1, name2, context, mode, end_of_turn):
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yield chat_html_wrapper(history, name1, name2, mode)
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def cai_chatbot_wrapper(text, state):
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for history in chatbot_wrapper(text, state):
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yield chat_html_wrapper(history, state['name1'], state['name2'], state['mode'])
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def regenerate_wrapper(text, generate_state, name1, name2, context, mode, end_of_turn):
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def regenerate_wrapper(text, state):
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if (len(shared.history['visible']) == 1 and not shared.history['visible'][0][0]) or len(shared.history['internal']) == 0:
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yield chat_html_wrapper(shared.history['visible'], name1, name2, mode)
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yield chat_html_wrapper(shared.history['visible'], state['name1'], state['name2'], state['mode'])
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else:
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last_visible = shared.history['visible'].pop()
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last_internal = shared.history['internal'].pop()
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# Yield '*Is typing...*'
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yield chat_html_wrapper(shared.history['visible'] + [[last_visible[0], shared.processing_message]], name1, name2, mode)
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for history in chatbot_wrapper(last_internal[0], generate_state, name1, name2, context, mode, end_of_turn, regenerate=True):
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yield chat_html_wrapper(shared.history['visible'] + [[last_visible[0], shared.processing_message]], state['name1'], state['name2'], state['mode'])
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for history in chatbot_wrapper(last_internal[0], state, regenerate=True):
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shared.history['visible'][-1] = [last_visible[0], history[-1][1]]
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yield chat_html_wrapper(shared.history['visible'], name1, name2, mode)
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yield chat_html_wrapper(shared.history['visible'], state['name1'], state['name2'], state['mode'])
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def continue_wrapper(text, generate_state, name1, name2, context, mode, end_of_turn):
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def continue_wrapper(text, state):
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if (len(shared.history['visible']) == 1 and not shared.history['visible'][0][0]) or len(shared.history['internal']) == 0:
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yield chat_html_wrapper(shared.history['visible'], name1, name2, mode)
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yield chat_html_wrapper(shared.history['visible'], state['name1'], state['name2'], state['mode'])
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else:
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# Yield ' ...'
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yield chat_html_wrapper(shared.history['visible'][:-1] + [[shared.history['visible'][-1][0], shared.history['visible'][-1][1] + ' ...']], name1, name2, mode)
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for history in chatbot_wrapper(shared.history['internal'][-1][0], generate_state, name1, name2, context, mode, end_of_turn, _continue=True):
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yield chat_html_wrapper(shared.history['visible'], name1, name2, mode)
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yield chat_html_wrapper(shared.history['visible'][:-1] + [[shared.history['visible'][-1][0], shared.history['visible'][-1][1] + ' ...']], state['name1'], state['name2'], state['mode'])
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for history in chatbot_wrapper(shared.history['internal'][-1][0], state, _continue=True):
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yield chat_html_wrapper(shared.history['visible'], state['name1'], state['name2'], state['mode'])
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def remove_last_message(name1, name2, mode):
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@@ -117,9 +117,9 @@ def stop_everything_event():
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shared.stop_everything = True
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def generate_reply(question, generate_state, eos_token=None, stopping_strings=[]):
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def generate_reply(question, state, eos_token=None, stopping_strings=[]):
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clear_torch_cache()
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seed = set_manual_seed(generate_state['seed'])
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seed = set_manual_seed(state['seed'])
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shared.stop_everything = False
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generate_params = {}
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t0 = time.time()
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@@ -134,8 +134,8 @@ def generate_reply(question, generate_state, eos_token=None, stopping_strings=[]
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# separately and terminate the function call earlier
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if any((shared.is_RWKV, shared.is_llamacpp)):
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for k in ['temperature', 'top_p', 'top_k', 'repetition_penalty']:
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generate_params[k] = generate_state[k]
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generate_params['token_count'] = generate_state['max_new_tokens']
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generate_params[k] = state[k]
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generate_params['token_count'] = state['max_new_tokens']
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try:
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if shared.args.no_stream:
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reply = shared.model.generate(context=question, **generate_params)
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@@ -164,7 +164,7 @@ def generate_reply(question, generate_state, eos_token=None, stopping_strings=[]
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print(f'Output generated in {(t1-t0):.2f} seconds ({new_tokens/(t1-t0):.2f} tokens/s, {new_tokens} tokens, context {original_tokens}, seed {seed})')
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return
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input_ids = encode(question, generate_state['max_new_tokens'], add_bos_token=generate_state['add_bos_token'])
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input_ids = encode(question, state['max_new_tokens'], add_bos_token=state['add_bos_token'])
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original_input_ids = input_ids
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output = input_ids[0]
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@@ -179,13 +179,13 @@ def generate_reply(question, generate_state, eos_token=None, stopping_strings=[]
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if not shared.args.flexgen:
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for k in ['max_new_tokens', 'do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping']:
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generate_params[k] = generate_state[k]
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generate_params[k] = state[k]
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generate_params['eos_token_id'] = eos_token_ids
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generate_params['stopping_criteria'] = stopping_criteria_list
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else:
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for k in ['max_new_tokens', 'do_sample', 'temperature']:
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generate_params[k] = generate_state[k]
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generate_params['stop'] = generate_state['eos_token_ids'][-1]
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generate_params[k] = state[k]
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generate_params['stop'] = state['eos_token_ids'][-1]
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if not shared.args.no_stream:
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generate_params['max_new_tokens'] = 8
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@@ -248,7 +248,7 @@ def generate_reply(question, generate_state, eos_token=None, stopping_strings=[]
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# Stream the output naively for FlexGen since it doesn't support 'stopping_criteria'
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else:
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for i in range(generate_state['max_new_tokens'] // 8 + 1):
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for i in range(state['max_new_tokens'] // 8 + 1):
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clear_torch_cache()
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with torch.no_grad():
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output = shared.model.generate(**generate_params)[0]
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