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Update app.py

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  1. app.py +13 -162
app.py CHANGED
@@ -1,169 +1,20 @@
1
  import gradio as gr
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- import os
 
 
 
3
 
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- os.system('pip install dashscope -U')
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- import tempfile
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- 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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- from PIL import Image
11
 
 
12
 
13
- # 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=False):
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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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- Path(tempfile.gettempdir()) / "gradio"
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- )
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- os.makedirs(uploaded_file_dir, exist_ok=True)
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-
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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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-
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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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- }, {
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- 'role': 'user',
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- 'content': [
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- {'image': f'file://{filename}'},
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- {'text': 'Please describe the math-related content in this image, ensuring that any LaTeX formulas are correctly transcribed. Non-mathematical details do not need to be described.'}
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- ]
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- }]
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-
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- response = MultiModalConversation.call(model='qwen-vl-max-0809', messages=messages)
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-
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- # 清理临时文件
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- os.remove(filename)
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-
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- return response.output.choices[0]["message"]["content"]
54
 
55
- def get_math_response(image_description, user_question):
56
- global math_messages
57
- 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]
60
- 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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- content = ''
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- query = f"{content}User question: {user_question}"
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- math_messages.append({'role': 'user', 'content': query})
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- response = Generation.call(
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- model="qwen2-math-72b-instruct",
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- messages=math_messages,
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- result_format='message',
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- stream=True
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- )
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- answer = None
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- for resp in response:
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- if resp.output is None:
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- continue
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- answer = resp.output.choices[0].message.content
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- yield answer.replace("\\", "\\\\")
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- print(f'query: {query}\nanswer: {answer}')
79
- if answer is None:
80
- math_messages.pop()
81
- else:
82
- math_messages.append({'role': 'assistant', 'content': answer})
83
 
84
-
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- def math_chat_bot(image, sketchpad, question, state):
86
- current_tab_index = state["tab_index"]
87
- image_description = None
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- # Upload
89
- if current_tab_index == 0:
90
- if image is not None:
91
- image_description = process_image(image)
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- # Sketch
93
- elif current_tab_index == 1:
94
- print(sketchpad)
95
- if sketchpad and sketchpad["composite"]:
96
- image_description = process_image(sketchpad["composite"], True)
97
- yield from get_math_response(image_description, question)
98
-
99
- css = """
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- #qwen-md .katex-display { display: inline; }
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- #qwen-md .katex-display>.katex { display: inline; }
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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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- def tabs_select(e: gr.SelectData, _state):
106
- _state["tab_index"] = e.index
107
-
108
-
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- # 创建Gradio接口
110
- with gr.Blocks(css=css) as demo:
111
- 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>"""
113
- """<center><font size=8>📖 Qwen2-Math Demo</center>"""
114
- """\
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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>"""
116
- )
117
- state = gr.State({"tab_index": 0})
118
- with gr.Row():
119
- with gr.Column():
120
- with gr.Tabs() as input_tabs:
121
- with gr.Tab("Upload"):
122
- input_image = gr.Image(type="pil", label="Upload"),
123
- with gr.Tab("Sketch"):
124
- input_sketchpad = gr.Sketchpad(type="pil", label="Sketch", layers=False)
125
- input_tabs.select(fn=tabs_select, inputs=[state])
126
- input_text = gr.Textbox(label="input your question")
127
- with gr.Row():
128
- with gr.Column():
129
- clear_btn = gr.ClearButton(
130
- [*input_image, input_sketchpad, input_text])
131
- with gr.Column():
132
- submit_btn = gr.Button("Submit", variant="primary")
133
- with gr.Column():
134
- output_md = gr.Markdown(label="answer",
135
- latex_delimiters=[{
136
- "left": "\\(",
137
- "right": "\\)",
138
- "display": True
139
- }, {
140
- "left": "\\begin\{equation\}",
141
- "right": "\\end\{equation\}",
142
- "display": True
143
- }, {
144
- "left": "\\begin\{align\}",
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- "right": "\\end\{align\}",
146
- "display": True
147
- }, {
148
- "left": "\\begin\{alignat\}",
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- "right": "\\end\{alignat\}",
150
- "display": True
151
- }, {
152
- "left": "\\begin\{gather\}",
153
- "right": "\\end\{gather\}",
154
- "display": True
155
- }, {
156
- "left": "\\begin\{CD\}",
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- "right": "\\end\{CD\}",
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- "display": True
159
- }, {
160
- "left": "\\[",
161
- "right": "\\]",
162
- "display": True
163
- }],
164
- elem_id="qwen-md")
165
- submit_btn.click(
166
- fn=math_chat_bot,
167
- inputs=[*input_image, input_sketchpad, input_text, state],
168
- outputs=output_md)
169
  demo.launch()
 
1
  import gradio as gr
2
+ from transformers import pipeline
3
+ def generate_response(text):
4
+ # Load the Qwen2-Math pipeline
5
+ pipe = pipeline("text-generation", model="qwen2-math-72b-instruct")
6
 
7
+ # Generate the response
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+ response = pipe(text, max_length=512)[0]['generated_text']
 
 
 
 
 
9
 
10
+ return response
11
 
12
+ with gr.Blocks() as demo:
13
+ gr.Markdown("## Math Reasoning Chatbot")
14
+ txt = gr.Textbox(label="Enter your math problem")
15
+ btn = gr.Button("Submit")
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+ output = gr.Textbox()
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
17
 
18
+ btn.click(fn=generate_response, inputs=txt, outputs=output)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  demo.launch()