AI/text-generation-webui
1
0
Fork 0
mirror of https://github.com/oobabooga/text-generation-webui.git synced 2024-10-01 01:26:03 -04:00
Code Issues Packages Projects Releases Wiki Activity

Use BLIP directly + some simplifications

Browse Source
This commit is contained in:
oobabooga 2023-02-14 23:55:46 -03:00
parent a7d98f494a
commit 8c3ef58e00
3 changed files with 48 additions and 39 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

21
modules/bot_picture.py
View File

@ -1,9 +1,14 @@
from nataili_blip.model_manager import BlipModelManager
from nataili_blip.caption import Caption
import requests
import torch
from PIL import Image
from transformers import BlipForConditionalGeneration
from transformers import BlipProcessor
def load_model():
model_name = "BLIP"
mm = BlipModelManager()
mm.download_model(model_name)
mm.load_blip(model_name)
return Caption(mm.loaded_models[model_name]["model"], mm.loaded_models[model_name]["device"])
processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base", torch_dtype=torch.float16).to("cuda")
# raw_image = Image.open('/tmp/istockphoto-470604022-612x612.jpg').convert('RGB')
def caption_image(raw_image):
inputs = processor(raw_image, return_tensors="pt").to("cuda", torch.float16)
out = model.generate(**inputs, max_new_tokens=100)
return processor.decode(out[0], skip_special_tokens=True)

1
requirements.txt
View File

@ -4,5 +4,4 @@ bitsandbytes==0.37.0
gradio==3.15.0
numpy
safetensors==0.2.8
nataili_blip
git+https://github.com/huggingface/transformers

65
server.py
View File

@ -101,7 +101,6 @@ if args.deepspeed:
if args.picture and (args.cai_chat or args.chat):
import modules.bot_picture as bot_picture
blip = bot_picture.load_model()
def load_model(model_name):
print(f"Loading {model_name}...")
@ -567,11 +566,11 @@ def extract_message_from_reply(question, reply, current, other, check, extension
return reply, next_character_found, substring_found
def chatbot_wrapper(text, tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, history_size, picture):
original_text = text
def chatbot_wrapper(text, tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, history_size, picture=None):
if args.picture and picture is not None:
text, original_text = generate_chat_picture(picture, name1, name2)
text, visible_text = generate_chat_picture(picture, name1, name2)
else:
visible_text = text
text = apply_extensions(text, "input")
question = generate_chat_prompt(text, tokens, name1, name2, context, history_size)
@ -581,14 +580,14 @@ def chatbot_wrapper(text, tokens, do_sample, max_new_tokens, temperature, top_p,
for reply in generate_reply(question, tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, eos_token=eos_token, stopping_string=f"\n{name1}:"):
reply, next_character_found, substring_found = extract_message_from_reply(question, reply, name2, name1, check, extensions=True)
history['internal'][-1] = [text, reply]
history['visible'][-1] = [original_text, apply_extensions(reply, "output")]
history['visible'][-1] = [visible_text, apply_extensions(reply, "output")]
if not substring_found:
yield history['visible'], None
yield history['visible']
if next_character_found:
break
yield history['visible'], None
yield history['visible']
def impersonate_wrapper(text, tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, history_size, picture):
def impersonate_wrapper(text, tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, history_size, picture=None):
question = generate_chat_prompt(text, tokens, name1, name2, context, history_size, impersonate=True)
eos_token = '\n' if check else None
for reply in generate_reply(question, tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, eos_token=eos_token, stopping_string=f"\n{name2}:"):
@ -599,20 +598,20 @@ def impersonate_wrapper(text, tokens, do_sample, max_new_tokens, temperature, to
break
yield apply_extensions(reply, "output")
def cai_chatbot_wrapper(text, tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, history_size, picture):
for _history, _ in chatbot_wrapper(text, tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, history_size, picture):
yield generate_chat_html(_history, name1, name2, character), None
def cai_chatbot_wrapper(text, tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, history_size, picture=None):
for _history in chatbot_wrapper(text, tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, history_size, picture):
yield generate_chat_html(_history, name1, name2, character)
def regenerate_wrapper(text, tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, history_size, picture):
def regenerate_wrapper(text, tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, history_size, picture=None):
last = history['visible'].pop()
history['internal'].pop()
text = last[0]
if args.cai_chat:
for i, _ in cai_chatbot_wrapper(text, tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, history_size, picture):
yield i, None
for i in cai_chatbot_wrapper(text, tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, history_size, picture):
yield i
else:
for i, _ in chatbot_wrapper(text, tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, history_size, picture):
yield i, None
for i in chatbot_wrapper(text, tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, history_size, picture):
yield i
def remove_last_message(name1, name2):
if not history['internal'][-1][0] == '<|BEGIN-VISIBLE-CHAT|>':
@ -802,12 +801,12 @@ def upload_your_profile_picture(img):
print(f'Profile picture saved to "img_me.png"')
def generate_chat_picture(picture, name1, name2):
text = f'*{name1} sends {name2} a picture that contains the following: "{blip(picture)}"*'
text = f'*{name1} sends {name2} a picture that contains the following: "{bot_picture.caption_image(picture)}"*'
buffer = BytesIO()
picture.save(buffer, format="JPEG")
img_str = base64.b64encode(buffer.getvalue()).decode('utf-8')
original_text = f'<img src="data:image/jpeg;base64,{img_str}">'
return text, original_text
visible_text = f'<img src="data:image/jpeg;base64,{img_str}">'
return text, visible_text
# Global variables
available_models = get_available_models()
@ -881,7 +880,7 @@ if args.chat or args.cai_chat:
buttons["Replace last reply"] = gr.Button("Replace last reply")
if args.picture:
with gr.Row():
picture_select = gr.Image(label="Send a picture", type='pil', display_label=True)
picture_select = gr.Image(label="Send a picture", type='pil')
with gr.Row():
with gr.Column():
@ -927,17 +926,20 @@ if args.chat or args.cai_chat:
if args.extensions is not None:
create_extensions_block()
input_params = [textbox, max_new_tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, history_size_slider, picture_select]
output_params = [display, picture_select]
input_params = [textbox, max_new_tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, history_size_slider]
if args.picture:
input_params.append(picture_select)
if args.cai_chat:
gen_events.append(buttons["Generate"].click(cai_chatbot_wrapper, input_params, output_params, show_progress=args.no_stream, api_name="textgen"))
gen_events.append(textbox.submit(cai_chatbot_wrapper, input_params, output_params, show_progress=args.no_stream))
picture_select.upload(cai_chatbot_wrapper, input_params, output_params, show_progress=args.no_stream)
gen_events.append(buttons["Generate"].click(cai_chatbot_wrapper, input_params, display, show_progress=args.no_stream, api_name="textgen"))
gen_events.append(textbox.submit(cai_chatbot_wrapper, input_params, display, show_progress=args.no_stream))
if args.picture:
picture_select.upload(cai_chatbot_wrapper, input_params, display, show_progress=args.no_stream)
else:
gen_events.append(buttons["Generate"].click(chatbot_wrapper, input_params, output_params, show_progress=args.no_stream, api_name="textgen"))
gen_events.append(textbox.submit(chatbot_wrapper, input_params, output_params, show_progress=args.no_stream))
picture_select.upload(chatbot_wrapper, input_params, output_params, show_progress=args.no_stream)
gen_events.append(buttons["Regenerate"].click(regenerate_wrapper, input_params, output_params, show_progress=args.no_stream))
gen_events.append(buttons["Generate"].click(chatbot_wrapper, input_params, display, show_progress=args.no_stream, api_name="textgen"))
gen_events.append(textbox.submit(chatbot_wrapper, input_params, display, show_progress=args.no_stream))
if args.picture:
picture_select.upload(chatbot_wrapper, input_params, display, show_progress=args.no_stream)
gen_events.append(buttons["Regenerate"].click(regenerate_wrapper, input_params, display, show_progress=args.no_stream))
gen_events.append(buttons["Impersonate"].click(impersonate_wrapper, input_params, textbox, show_progress=args.no_stream))
buttons["Send last reply to input"].click(send_last_reply_to_input, [], textbox, show_progress=args.no_stream)
@ -949,11 +951,14 @@ if args.chat or args.cai_chat:
buttons["Upload character"].click(upload_character, [upload_char, upload_img], [character_menu])
for i in ["Generate", "Regenerate", "Replace last reply"]:
buttons[i].click(lambda x: "", textbox, textbox, show_progress=False)
textbox.submit(lambda x: "", textbox, textbox, show_progress=False)
character_menu.change(load_character, [character_menu, name1, name2], [name2, context, display])
upload_img_tavern.upload(upload_tavern_character, [upload_img_tavern, name1, name2], [character_menu])
upload.upload(load_history, [upload, name1, name2], [])
upload_img_me.upload(upload_your_profile_picture, [upload_img_me], [])
if args.picture:
picture_select.upload(lambda : None, [], [picture_select], show_progress=False)
if args.cai_chat:
upload.upload(redraw_html, [name1, name2], [display])