mirror of
https://github.com/oobabooga/text-generation-webui.git
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59 lines
2.3 KiB
Python
59 lines
2.3 KiB
Python
import base64
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from io import BytesIO
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import gradio as gr
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import torch
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from transformers import BlipForConditionalGeneration, BlipProcessor
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from modules import chat, shared, ui_chat
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from modules.ui import gather_interface_values
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from modules.utils import gradio
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input_hijack = {
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'state': False,
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'value': ["", ""]
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}
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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.float32).to("cpu")
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def chat_input_modifier(text, visible_text, state):
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global input_hijack
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if input_hijack['state']:
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input_hijack['state'] = False
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return input_hijack['value']
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else:
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return text, visible_text
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def caption_image(raw_image):
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inputs = processor(raw_image.convert('RGB'), return_tensors="pt").to("cpu", torch.float32)
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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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def generate_chat_picture(picture, name1, name2):
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text = f'*{name1} sends {name2} a picture that contains the following: “{caption_image(picture)}”*'
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# lower the resolution of sent images for the chat, otherwise the log size gets out of control quickly with all the base64 values in visible history
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picture.thumbnail((300, 300))
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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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visible_text = f'<img src="data:image/jpeg;base64,{img_str}" alt="{text}">'
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return text, visible_text
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def ui():
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picture_select = gr.Image(label='Send a picture', type='pil')
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# Prepare the input hijack, update the interface values, call the generation function, and clear the picture
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picture_select.upload(
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lambda picture, name1, name2: input_hijack.update({
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"state": True,
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"value": generate_chat_picture(picture, name1, name2)
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}), [picture_select, shared.gradio['name1'], shared.gradio['name2']], None).then(
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gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
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chat.generate_chat_reply_wrapper, gradio(ui_chat.inputs), gradio('display', 'history'), show_progress=False).then(
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lambda: None, None, picture_select, show_progress=False)
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