Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -14,6 +14,23 @@ from PIL import Image
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import requests
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from io import BytesIO
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QV_MODEL_ID = "prithivMLmods/Qwen2-VL-OCR-2B-Instruct"
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qwen_processor = AutoProcessor.from_pretrained(QV_MODEL_ID, trust_remote_code=True)
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qwen_model = Qwen2VLForConditionalGeneration.from_pretrained(
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@@ -42,7 +59,7 @@ def model_inference(input_dict, history):
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else:
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# For simplicity, use the first provided image.
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image = load_image(files[0])
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yield "
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messages = [{
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"role": "user",
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"content": [
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@@ -121,7 +138,7 @@ def model_inference(input_dict, history):
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thread.start()
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buffer = ""
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yield "
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for new_text in streamer:
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buffer += new_text
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buffer = buffer.replace("<|im_end|>", "")
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@@ -145,7 +162,12 @@ demo = gr.ChatInterface(
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fn=model_inference,
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description="# **Multimodal OCR `@aya-vision 'prompt..'`**",
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examples=examples,
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textbox=gr.MultimodalTextbox(
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stop_btn="Stop Generation",
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multimodal=True,
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cache_examples=False,
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import requests
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from io import BytesIO
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# Helper function to return a progress bar HTML snippet.
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def progress_bar_html(label: str) -> str:
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return f'''
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<div style="display: flex; align-items: center;">
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<span style="margin-right: 10px; font-size: 14px;">{label}</span>
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<div style="width: 110px; height: 5px; background-color: #f0f0f0; border-radius: 2px; overflow: hidden;">
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<div style="width: 100%; height: 100%; background-color: #00ff3a; animation: loading 1.5s linear infinite;"></div>
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</div>
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</div>
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<style>
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@keyframes loading {{
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0% {{ transform: translateX(-100%); }}
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100% {{ transform: translateX(100%); }}
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}}
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</style>
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'''
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QV_MODEL_ID = "prithivMLmods/Qwen2-VL-OCR-2B-Instruct"
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qwen_processor = AutoProcessor.from_pretrained(QV_MODEL_ID, trust_remote_code=True)
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qwen_model = Qwen2VLForConditionalGeneration.from_pretrained(
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else:
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# For simplicity, use the first provided image.
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image = load_image(files[0])
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yield progress_bar_html("Processing with Aya-Vision")
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messages = [{
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"role": "user",
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"content": [
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thread.start()
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buffer = ""
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yield progress_bar_html("Processing with Qwen2VL OCR")
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for new_text in streamer:
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buffer += new_text
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buffer = buffer.replace("<|im_end|>", "")
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fn=model_inference,
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description="# **Multimodal OCR `@aya-vision 'prompt..'`**",
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examples=examples,
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textbox=gr.MultimodalTextbox(
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label="Query Input",
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file_types=["image"],
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file_count="multiple",
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placeholder="By default, it runs Qwen2VL OCR, Tag @aya-vision for Aya Vision 8B"
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),
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stop_btn="Stop Generation",
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multimodal=True,
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cache_examples=False,
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