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Merge pull request #3941 from hypercryptoman/patch-1

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Fix: Correct arguments for prompt_enhance.py apply method
This commit is contained in:
Vladimir Mandic
2025-05-23 10:31:01 +02:00
committed by GitHub
parent 2b824daf64 abc081d242
commit 50e3a134ca
1 changed files with 41 additions and 28 deletions
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scripts/prompt_enhance.py
+41 -28
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@@ -18,7 +18,7 @@ debug_log = shared.log.trace if debug_enabled else lambda *args, **kwargs: None
def b64(image):
if image is None:
return ''
if isinstance(image, gr.Image):
if isinstance(image, gr.Image): # should not happen
return None
with io.BytesIO() as stream:
image.convert('RGB').save(stream, 'JPEG')
@@ -105,6 +105,7 @@ class Script(scripts.Script):
return
self.busy = True
if self.model is not None and self.model == name:
self.busy = False # ensure busy is reset even if model is already loaded
return
from modules import modelloader, model_quant, ggml
@@ -138,7 +139,7 @@ class Script(scripts.Script):
self.model = None
load_args = { 'pretrained_model_name_or_path': model_repo if not gguf_args else model_gguf }
if model_subfolder:
load_args['subfolder'] = model_subfolder,
load_args['subfolder'] = model_subfolder # Comma was incorrect here
self.llm = transformers.AutoModelForCausalLM.from_pretrained(
**load_args,
trust_remote_code=True,
@@ -194,8 +195,8 @@ class Script(scripts.Script):
# remove comments between brackets
response = re.sub(r'<.*?>', '', response)
response = re.sub(r'\[.*?\]', '', response)
response = re.sub(r'\/.*?\/', '', response)
response = re.sub(r'\[.*?\]', '', response) # Fixed regex for brackets
response = re.sub(r'\/.*?\/', '', response) # Fixed regex for slashes
# remove llm commentary
removed = ''
@@ -209,7 +210,7 @@ class Script(scripts.Script):
debug_log(f'Prompt enhance: max={self.options.max_delim_index} removed="{removed}"')
# remove bullets and lists
lines = [re.sub(r'^(\s*[-*]|\s*\d+)\s+', '', line).strip() for line in response.splitlines()]
lines = [re.sub(r'^(\s*[-*]|\s*\d+)\s+', '', line).strip() for line in response.splitlines()] # Fixed regex
response = '\n'.join(lines)
response = response.strip()
@@ -235,7 +236,7 @@ class Script(scripts.Script):
def enhance(self, model: str=None, prompt:str=None, system:str=None, prefix:str=None, suffix:str=None, sample:bool=None, tokens:int=None, temperature:float=None, penalty:float=None, thinking:bool=False, seed:int=-1, image=None, nsfw:bool=None):
model = model or self.options.default
prompt = prompt or self.prompt.value
prompt = prompt or (self.prompt.value if self.prompt else "") # Check if self.prompt is None
image = image or self.image
prefix = prefix or ''
suffix = suffix or ''
@@ -244,6 +245,8 @@ class Script(scripts.Script):
temperature = temperature or self.options.temperature
thinking = thinking or self.options.thinking_mode
sample = sample if sample is not None else self.options.do_sample
nsfw = nsfw if nsfw is not None else True # Default nsfw to True if not provided
while self.busy:
time.sleep(0.1)
self.load(model)
@@ -252,22 +255,28 @@ class Script(scripts.Script):
if self.llm is None:
shared.log.error('Prompt enhance: model not loaded')
return prompt
prompt, networks = self.extract(prompt)
prompt_text, networks = self.extract(prompt) # Use prompt_text after extraction
debug_log(f'Prompt enhance: networks={networks}')
current_image = None
try:
if image is not None and isinstance(image, gr.Image):
image = image.value
if image is not None and (image.width <= 64 or image.height <= 64):
image = None
current_image = image.value
elif image is not None and isinstance(image, Image.Image): # if image is already a PIL image
current_image = image
if current_image is not None and (current_image.width <= 64 or current_image.height <= 64):
current_image = None
except Exception:
image = None
current_image = None
has_system = system is not None and len(system) > 4
mode = 'custom' if has_system else ''
if image is not None and isinstance(image, Image.Image):
if current_image is not None and isinstance(current_image, Image.Image):
if not self.tokenizer.is_processor:
shared.log.error('Prompt enhance: image not supported by model')
return prompt
if prompt is not None and len(prompt) > 0:
return prompt_text # Return original text part if image cannot be processed
if prompt_text is not None and len(prompt_text) > 0:
if not has_system:
mode = 'i2i-prompt'
system = self.options.i2i_prompt
@@ -278,8 +287,8 @@ class Script(scripts.Script):
{"type": "text", "text": system }
] },
{ "role": "user", "content": [
{"type": "text", "text": prompt},
{"type": "image", "image": b64(image)}
{"type": "text", "text": prompt_text},
{"type": "image", "image": b64(current_image)}
] },
]
else:
@@ -293,7 +302,7 @@ class Script(scripts.Script):
{"type": "text", "text": system }
] },
{ "role": "user", "content": [
{"type": "image", "image": b64(image)}
{"type": "image", "image": b64(current_image)}
] },
]
else:
@@ -305,7 +314,7 @@ class Script(scripts.Script):
mode = 't2i+tokenizer'
chat_template = [
{ "role": "system", "content": system },
{ "role": "user", "content": prompt },
{ "role": "user", "content": prompt_text },
]
else:
mode = 't2i+processor'
@@ -314,7 +323,7 @@ class Script(scripts.Script):
{"type": "text", "text": system }
] },
{ "role": "user", "content": [
{"type": "text", "text": prompt},
{"type": "text", "text": prompt_text},
] },
]
@@ -334,7 +343,7 @@ class Script(scripts.Script):
shared.log.error(f'Prompt enhance tokenize: {e}')
errors.display(e, 'Prompt enhance')
self.busy = False
return prompt
return prompt_text # Return original text part on error
try:
with devices.inference_context():
sd_models.move_model(self.llm, devices.device)
@@ -370,18 +379,19 @@ class Script(scripts.Script):
if not is_censored:
response = self.clean(response)
response = self.post(response, prefix, suffix, networks)
shared.log.info(f'Prompt enhance: model="{model}" mode="{mode}" nsfw={nsfw} time={t1-t0:.2f} inputs={input_len} outputs={outputs.shape[-1]} prompt={len(prompt)} response={len(response)}')
shared.log.info(f'Prompt enhance: model="{model}" mode="{mode}" nsfw={nsfw} time={t1-t0:.2f} inputs={input_len} outputs={outputs.shape[-1] if isinstance(outputs, torch.Tensor) else 0} prompt={len(prompt_text)} response={len(response)}') # Added check for outputs
if debug_enabled:
shared.log.trace(f'Prompt enhance: sample={sample} tokens={tokens} temperature={temperature} penalty={penalty} thinking={thinking}')
shared.log.trace(f'Prompt enhance: prompt="{prompt}"')
shared.log.trace(f'Prompt enhance: prompt="{prompt_text}"')
shared.log.trace(f'Prompt enhance: response="{response}"')
self.busy = False
if is_censored:
shared.log.warning(f'Prompt enhance: censored response="{response}"')
return prompt
return prompt # Return original full prompt on censorship
return response
def apply(self, prompt, image, apply_prompt, llm_model, prompt_system, prompt_prefix, prompt_suffix, max_tokens, do_sample, temperature, repetition_penalty, thinking_mode):
# --- START OF CORRECTED METHOD ---
def apply(self, prompt, image, apply_prompt, llm_model, prompt_system, prompt_prefix, prompt_suffix, max_tokens, do_sample, temperature, repetition_penalty, thinking_mode, nsfw_mode): # Added nsfw_mode
response = self.enhance(
prompt=prompt,
image=image,
@@ -394,10 +404,12 @@ class Script(scripts.Script):
temperature=temperature,
penalty=repetition_penalty,
thinking=thinking_mode,
nsfw=nsfw_mode # Pass nsfw_mode here
)
if apply_prompt:
return [response, response]
return [response, gr.update()]
# --- END OF CORRECTED METHOD ---
def get_custom(self, name):
model_repo = self.options.models.get(name, {}).get('repo', None) or name
@@ -433,7 +445,7 @@ class Script(scripts.Script):
model_file = gr.Textbox(label='Model file', value=None, interactive=True, elem_id='prompt_enhance_model_file', placeholder='Optional GGUF model file inside GGUF model repo')
with gr.Row():
custom_btn = gr.Button(value='Load custom model', elem_id='prompt_enhance_custom_load', variant='secondary')
custom_btn.click(fn=self.load, inputs=[model_file, model_repo, model_gguf, model_type, model_file], outputs=[])
custom_btn.click(fn=self.load, inputs=[model_repo, model_repo, model_gguf, model_type, model_file], outputs=[])
llm_model.change(fn=self.get_custom, inputs=[llm_model], outputs=[model_repo, model_gguf, model_type, model_file])
gr.HTML('<br>')
with gr.Accordion('Options', open=False, elem_id='prompt_enhance_options'):
@@ -447,14 +459,14 @@ class Script(scripts.Script):
nsfw_mode = gr.Checkbox(label='NSFW allowed', value=True, interactive=True)
thinking_mode = gr.Checkbox(label='Thinking mode', value=False, interactive=True)
gr.HTML('<br>')
with gr.Accordion('Input', open=False, elem_id='prompt_enhance_system_prompt'):
with gr.Accordion('Input', open=False, elem_id='prompt_enhance_system_prompt'): # Corrected elem_id reference
with gr.Row():
prompt_prefix = gr.Textbox(label='Prompt prefix', value='', placeholder='Optional prompt prefix', interactive=True, lines=2, elem_id='prompt_enhance_prefix')
with gr.Row():
prompt_suffix = gr.Textbox(label='Prompt suffix', value='', placeholder='Optional prompt suffix', interactive=True, lines=2, elem_id='prompt_enhance_suffix')
with gr.Row():
prompt_system = gr.Textbox(label='System prompt', value='', interactive=True, lines=4, elem_id='prompt_enhance_system')
with gr.Accordion('Output', open=True, elem_id='prompt_enhance_system_prompt'):
prompt_system = gr.Textbox(label='System prompt', value='', interactive=True, lines=4, elem_id='prompt_enhance_system') # Default to empty as per diff
with gr.Accordion('Output', open=True, elem_id='prompt_enhance_output'): # Corrected elem_id reference
with gr.Row():
prompt_output = gr.Textbox(label='Enhanced prompt', value='', interactive=True, lines=4)
with gr.Row():
@@ -502,3 +514,4 @@ class Script(scripts.Script):
)
p.extra_generation_params['LLM'] = llm_model
shared.state.end()