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littlebird13
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a99513a
1
Parent(s):
c579c5e
Update app.py
Browse files
app.py
CHANGED
@@ -7,11 +7,15 @@ from pathlib import Path
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import secrets
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import dashscope
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from dashscope import MultiModalConversation, Generation
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YOUR_API_TOKEN = os.getenv('YOUR_API_TOKEN')
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dashscope.api_key = YOUR_API_TOKEN
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math_messages = []
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def process_image(image):
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global math_messages
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math_messages = [] # reset when upload image
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uploaded_file_dir = os.environ.get("GRADIO_TEMP_DIR") or str(
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@@ -19,12 +23,17 @@ def process_image(image):
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)
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os.makedirs(uploaded_file_dir, exist_ok=True)
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name = f"tmp{secrets.token_hex(20)}.jpg"
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filename = os.path.join(uploaded_file_dir, name)
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image.save(filename)
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#
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messages = [{
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'role': 'system',
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'content': [{'text': 'You are a helpful assistant.'}]
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@@ -38,6 +47,7 @@ def process_image(image):
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response = MultiModalConversation.call(model='qwen-vl-max-0809', messages=messages)
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os.remove(filename)
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return response.output.choices[0]["message"]["content"]
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@@ -46,7 +56,7 @@ def get_math_response(image_description, user_question):
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global math_messages
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if not math_messages:
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math_messages.append({'role': 'system', 'content': 'You are a helpful math assistant.'})
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math_messages = math_messages[:1]
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if image_description is not None:
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content = f'Image description: {image_description}\n\n'
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else:
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@@ -72,11 +82,18 @@ def get_math_response(image_description, user_question):
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math_messages.append({'role': 'assistant', 'content': answer})
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def math_chat_bot(image, question):
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yield from get_math_response(image_description, question)
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css = """
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@@ -85,31 +102,68 @@ css = """
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#qwen-md .katex-display>.katex>.katex-html { display: inline; }
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"""
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],
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outputs=gr.Markdown(label="answer", latex_delimiters=[
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{"left": "\\(", "right": "\\)", "display": True},
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{"left": "\\begin\{equation\}", "right": "\\end\{equation\}", "display": True},
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{"left": "\\begin\{align\}", "right": "\\end\{align\}", "display": True},
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{"left": "\\begin\{alignat\}", "right": "\\end\{alignat\}", "display": True},
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{"left": "\\begin\{gather\}", "right": "\\end\{gather\}", "display": True},
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{"left": "\\begin\{CD\}", "right": "\\end\{CD\}", "display": True},
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{"left": "\\[", "right": "\\]", "display": True}
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], elem_id="qwen-md"),
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# title="📖 Qwen2 Math Demo",
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allow_flagging='never',
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description="""\
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<p align="center"><img src="https://modelscope.oss-cn-beijing.aliyuncs.com/resource/qwen.png" style="height: 60px"/><p>"""
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<center><font size=3>This WebUI is based on Qwen2-VL for OCR and Qwen2-Math for mathematical reasoning. You can input either images or texts of mathematical or arithmetic problems.</center>"""
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import secrets
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import dashscope
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from dashscope import MultiModalConversation, Generation
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from PIL import Image
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# 设置API密钥
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YOUR_API_TOKEN = os.getenv('YOUR_API_TOKEN')
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dashscope.api_key = YOUR_API_TOKEN
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math_messages = []
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def process_image(image, shouldConvert):
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# 获取上传文件的目录
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global math_messages
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math_messages = [] # reset when upload image
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uploaded_file_dir = os.environ.get("GRADIO_TEMP_DIR") or str(
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)
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os.makedirs(uploaded_file_dir, exist_ok=True)
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# 创建临时文件路径
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name = f"tmp{secrets.token_hex(20)}.jpg"
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filename = os.path.join(uploaded_file_dir, name)
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# 保存上传的图片
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if shouldConvert:
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new_img = Image.new('RGB', size=(image.width, image.height), color=(255, 255, 255))
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new_img.paste(image, (0, 0), mask=image)
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image = new_img
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image.save(filename)
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# 调用qwen-vl-max-0809模型处理图片
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messages = [{
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'role': 'system',
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'content': [{'text': 'You are a helpful assistant.'}]
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response = MultiModalConversation.call(model='qwen-vl-max-0809', messages=messages)
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# 清理临时文件
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os.remove(filename)
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return response.output.choices[0]["message"]["content"]
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global math_messages
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if not math_messages:
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math_messages.append({'role': 'system', 'content': 'You are a helpful math assistant.'})
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math_messages = math_messages[:1]
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if image_description is not None:
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content = f'Image description: {image_description}\n\n'
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else:
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math_messages.append({'role': 'assistant', 'content': answer})
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def math_chat_bot(image, sketchpad, question, state):
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current_tab_index = state["tab_index"]
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image_description = None
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# Upload
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if current_tab_index == 0:
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if image is not None:
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image_description = process_image(image)
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# Sketch
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elif current_tab_index == 1:
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print(sketchpad)
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if sketchpad and sketchpad["composite"]:
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image_description = process_image(sketchpad["composite"], True)
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yield from get_math_response(image_description, question)
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css = """
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#qwen-md .katex-display>.katex>.katex-html { display: inline; }
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"""
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def tabs_select(e: gr.SelectData, _state):
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_state["tab_index"] = e.index
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# 创建Gradio接口
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with gr.Blocks(css=css) as demo:
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gr.HTML("""\
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<p align="center"><img src="https://modelscope.oss-cn-beijing.aliyuncs.com/resource/qwen.png" style="height: 60px"/><p>"""
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"""<center><font size=8>📖 千问数学解题机器人</center>"""
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"""\
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<center><font size=3>This WebUI is based on Qwen2-VL for OCR and Qwen2-Math for mathematical reasoning. You can input either images or texts of mathematical or arithmetic problems.</center>"""
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)
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state = gr.State({"tab_index": 0})
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with gr.Row():
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with gr.Column():
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with gr.Tabs() as input_tabs:
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with gr.Tab("Upload"):
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input_image = gr.Image(type="pil", label="Upload"),
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with gr.Tab("Sketch"):
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input_sketchpad = gr.Sketchpad(type="pil", label="Sketch", layers=False)
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input_tabs.select(fn=tabs_select, inputs=[state])
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input_text = gr.Textbox(label="input your question")
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with gr.Row():
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with gr.Column():
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clear_btn = gr.ClearButton(
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[*input_image, input_sketchpad, input_text])
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with gr.Column():
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submit_btn = gr.Button("Submit", variant="primary")
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with gr.Column():
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output_md = gr.Markdown(label="answer",
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latex_delimiters=[{
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"left": "\\(",
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"right": "\\)",
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"display": True
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}, {
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"left": "\\begin\{equation\}",
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"right": "\\end\{equation\}",
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"display": True
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}, {
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"left": "\\begin\{align\}",
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"right": "\\end\{align\}",
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"display": True
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}, {
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"left": "\\begin\{alignat\}",
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"right": "\\end\{alignat\}",
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"display": True
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}, {
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"left": "\\begin\{gather\}",
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"right": "\\end\{gather\}",
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"display": True
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}, {
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"left": "\\begin\{CD\}",
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"right": "\\end\{CD\}",
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"display": True
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}, {
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"left": "\\[",
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"right": "\\]",
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"display": True
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}],
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elem_id="qwen-md")
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submit_btn.click(
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fn=math_chat_bot,
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inputs=[*input_image, input_sketchpad, input_text, state],
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outputs=output_md)
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demo.launch()
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