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https://github.com/oobabooga/text-generation-webui.git
synced 2024-11-22 08:07:56 +01:00
Use BLIP directly + some simplifications
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oobabooga
parent
a7d98f494a
commit
8c3ef58e00
@ -1,9 +1,14 @@
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from nataili_blip.model_manager import BlipModelManager
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from nataili_blip.caption import Caption
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import requests
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import torch
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from PIL import Image
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from transformers import BlipForConditionalGeneration
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from transformers import BlipProcessor
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def load_model():
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model_name = "BLIP"
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mm = BlipModelManager()
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mm.download_model(model_name)
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mm.load_blip(model_name)
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return Caption(mm.loaded_models[model_name]["model"], mm.loaded_models[model_name]["device"])
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processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
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model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base", torch_dtype=torch.float16).to("cuda")
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# raw_image = Image.open('/tmp/istockphoto-470604022-612x612.jpg').convert('RGB')
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def caption_image(raw_image):
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inputs = processor(raw_image, return_tensors="pt").to("cuda", torch.float16)
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out = model.generate(**inputs, max_new_tokens=100)
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return processor.decode(out[0], skip_special_tokens=True)
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@ -4,5 +4,4 @@ bitsandbytes==0.37.0
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gradio==3.15.0
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numpy
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safetensors==0.2.8
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nataili_blip
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git+https://github.com/huggingface/transformers
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65
server.py
65
server.py
@ -101,7 +101,6 @@ if args.deepspeed:
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if args.picture and (args.cai_chat or args.chat):
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import modules.bot_picture as bot_picture
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blip = bot_picture.load_model()
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def load_model(model_name):
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print(f"Loading {model_name}...")
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@ -567,11 +566,11 @@ def extract_message_from_reply(question, reply, current, other, check, extension
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return reply, next_character_found, substring_found
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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):
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original_text = text
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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):
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if args.picture and picture is not None:
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text, original_text = generate_chat_picture(picture, name1, name2)
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text, visible_text = generate_chat_picture(picture, name1, name2)
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else:
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visible_text = text
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text = apply_extensions(text, "input")
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question = generate_chat_prompt(text, tokens, name1, name2, context, history_size)
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@ -581,14 +580,14 @@ def chatbot_wrapper(text, tokens, do_sample, max_new_tokens, temperature, top_p,
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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}:"):
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reply, next_character_found, substring_found = extract_message_from_reply(question, reply, name2, name1, check, extensions=True)
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history['internal'][-1] = [text, reply]
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history['visible'][-1] = [original_text, apply_extensions(reply, "output")]
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history['visible'][-1] = [visible_text, apply_extensions(reply, "output")]
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if not substring_found:
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yield history['visible'], None
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yield history['visible']
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if next_character_found:
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break
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yield history['visible'], None
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yield history['visible']
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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):
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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):
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question = generate_chat_prompt(text, tokens, name1, name2, context, history_size, impersonate=True)
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eos_token = '\n' if check else None
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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}:"):
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@ -599,20 +598,20 @@ def impersonate_wrapper(text, tokens, do_sample, max_new_tokens, temperature, to
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break
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yield apply_extensions(reply, "output")
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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):
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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):
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yield generate_chat_html(_history, name1, name2, character), None
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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):
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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):
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yield generate_chat_html(_history, name1, name2, character)
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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):
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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):
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last = history['visible'].pop()
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history['internal'].pop()
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text = last[0]
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if args.cai_chat:
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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):
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yield i, None
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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):
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yield i
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else:
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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):
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yield i, None
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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):
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yield i
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def remove_last_message(name1, name2):
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if not history['internal'][-1][0] == '<|BEGIN-VISIBLE-CHAT|>':
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@ -802,12 +801,12 @@ def upload_your_profile_picture(img):
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print(f'Profile picture saved to "img_me.png"')
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def generate_chat_picture(picture, name1, name2):
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text = f'*{name1} sends {name2} a picture that contains the following: "{blip(picture)}"*'
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text = f'*{name1} sends {name2} a picture that contains the following: "{bot_picture.caption_image(picture)}"*'
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buffer = BytesIO()
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picture.save(buffer, format="JPEG")
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img_str = base64.b64encode(buffer.getvalue()).decode('utf-8')
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original_text = f'<img src="data:image/jpeg;base64,{img_str}">'
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return text, original_text
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visible_text = f'<img src="data:image/jpeg;base64,{img_str}">'
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return text, visible_text
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# Global variables
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available_models = get_available_models()
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@ -881,7 +880,7 @@ if args.chat or args.cai_chat:
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buttons["Replace last reply"] = gr.Button("Replace last reply")
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if args.picture:
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with gr.Row():
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picture_select = gr.Image(label="Send a picture", type='pil', display_label=True)
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picture_select = gr.Image(label="Send a picture", type='pil')
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with gr.Row():
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with gr.Column():
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@ -927,17 +926,20 @@ if args.chat or args.cai_chat:
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if args.extensions is not None:
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create_extensions_block()
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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]
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output_params = [display, picture_select]
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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]
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if args.picture:
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input_params.append(picture_select)
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if args.cai_chat:
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gen_events.append(buttons["Generate"].click(cai_chatbot_wrapper, input_params, output_params, show_progress=args.no_stream, api_name="textgen"))
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gen_events.append(textbox.submit(cai_chatbot_wrapper, input_params, output_params, show_progress=args.no_stream))
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picture_select.upload(cai_chatbot_wrapper, input_params, output_params, show_progress=args.no_stream)
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gen_events.append(buttons["Generate"].click(cai_chatbot_wrapper, input_params, display, show_progress=args.no_stream, api_name="textgen"))
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gen_events.append(textbox.submit(cai_chatbot_wrapper, input_params, display, show_progress=args.no_stream))
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if args.picture:
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picture_select.upload(cai_chatbot_wrapper, input_params, display, show_progress=args.no_stream)
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else:
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gen_events.append(buttons["Generate"].click(chatbot_wrapper, input_params, output_params, show_progress=args.no_stream, api_name="textgen"))
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gen_events.append(textbox.submit(chatbot_wrapper, input_params, output_params, show_progress=args.no_stream))
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picture_select.upload(chatbot_wrapper, input_params, output_params, show_progress=args.no_stream)
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gen_events.append(buttons["Regenerate"].click(regenerate_wrapper, input_params, output_params, show_progress=args.no_stream))
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gen_events.append(buttons["Generate"].click(chatbot_wrapper, input_params, display, show_progress=args.no_stream, api_name="textgen"))
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gen_events.append(textbox.submit(chatbot_wrapper, input_params, display, show_progress=args.no_stream))
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if args.picture:
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picture_select.upload(chatbot_wrapper, input_params, display, show_progress=args.no_stream)
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gen_events.append(buttons["Regenerate"].click(regenerate_wrapper, input_params, display, show_progress=args.no_stream))
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gen_events.append(buttons["Impersonate"].click(impersonate_wrapper, input_params, textbox, show_progress=args.no_stream))
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buttons["Send last reply to input"].click(send_last_reply_to_input, [], textbox, show_progress=args.no_stream)
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@ -949,11 +951,14 @@ if args.chat or args.cai_chat:
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buttons["Upload character"].click(upload_character, [upload_char, upload_img], [character_menu])
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for i in ["Generate", "Regenerate", "Replace last reply"]:
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buttons[i].click(lambda x: "", textbox, textbox, show_progress=False)
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textbox.submit(lambda x: "", textbox, textbox, show_progress=False)
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character_menu.change(load_character, [character_menu, name1, name2], [name2, context, display])
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upload_img_tavern.upload(upload_tavern_character, [upload_img_tavern, name1, name2], [character_menu])
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upload.upload(load_history, [upload, name1, name2], [])
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upload_img_me.upload(upload_your_profile_picture, [upload_img_me], [])
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if args.picture:
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picture_select.upload(lambda : None, [], [picture_select], show_progress=False)
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if args.cai_chat:
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upload.upload(redraw_html, [name1, name2], [display])
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