Spaces:
Running
Running
Commit
·
18fcf1b
1
Parent(s):
f17b493
progress more (3.8)
Browse files
app.py
CHANGED
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@@ -39,17 +39,7 @@ def create_download_section(excel_data, pdf_data):
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else:
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st.error("Ошибка при создании Excel файла")
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if pdf_data is not None:
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st.download_button(
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label="📄 Скачать PDF протокол",
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data=pdf_data,
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file_name="протокол_анализа.pdf",
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mime="application/pdf",
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key="pdf_download"
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)
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else:
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st.error("Ошибка при создании PDF файла")
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def display_sentiment_results(row, sentiment, impact=None, reasoning=None):
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@@ -79,59 +69,8 @@ def display_sentiment_results(row, sentiment, impact=None, reasoning=None):
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st.write("---")
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class StreamlitCapture:
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def __init__(self):
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self.texts = []
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def write(self, text):
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if text and str(text).strip(): # Only capture non-empty text
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self.texts.append(str(text))
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def flush(self):
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pass
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def generate_pdf_report(texts):
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try:
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import pdfkit
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from jinja2 import Template
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st.write("Подготовка PDF...")
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html_content = """
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<html>
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<head>
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<meta charset="UTF-8">
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<style>
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body { font-family: Arial, sans-serif; }
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.content { margin: 20px; }
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</style>
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</head>
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<body>
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<div class="content">
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{% for text in texts %}
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<p>{{ text }}</p>
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{% endfor %}
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</div>
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</body>
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</html>
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"""
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template = Template(html_content)
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rendered_html = template.render(texts=texts)
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# Create PDF in memory
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st.write("Конвертация в PDF...")
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pdf_data = pdfkit.from_string(rendered_html, False) # False means return PDF as bytes
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st.write("PDF успешно создан")
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return pdf_data
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except Exception as e:
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st.warning(f"Не удалось создать PDF отчет: {str(e)}")
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st.write("Создание текстового отчета вместо PDF...")
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# Return the text as bytes if PDF generation fails
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return '\n'.join(texts).encode('utf-8')
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# Initialize sentiment analyzers
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finbert = pipeline("sentiment-analysis", model="ProsusAI/finbert")
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@@ -348,26 +287,26 @@ def process_file(uploaded_file):
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# Generate all output files
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st.write("Генерация
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# 1. Generate Excel
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excel_output = create_output_file(df, uploaded_file)
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# 2. Generate PDF
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st.write("Создание PDF протокола...")
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pdf_data = generate_pdf_report(output_capture.texts)
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# Save PDF to disk
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if pdf_data:
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# Show success message
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st.success(f"✅ Обработка и анализ завершены за умеренное время.")
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# Create download section
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create_download_section(excel_output,
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return df
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else:
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st.error("Ошибка при создании Excel файла")
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def display_sentiment_results(row, sentiment, impact=None, reasoning=None):
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st.write("---")
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# Initialize sentiment analyzers
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finbert = pipeline("sentiment-analysis", model="ProsusAI/finbert")
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# Generate all output files
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st.write("Генерация отчета...")
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# 1. Generate Excel
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excel_output = create_output_file(df, uploaded_file)
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# 2. Generate PDF
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#st.write("Создание PDF протокола...")
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#pdf_data = generate_pdf_report(output_capture.texts)
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# Save PDF to disk
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#if pdf_data:
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# with open("result.pdf", "wb") as f:
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# f.write(pdf_data)
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# st.success("PDF протокол сохранен как 'result.pdf'")
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# Show success message
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#st.success(f"✅ Обработка и анализ завершены за умеренное время.")
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# Create download section
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create_download_section(excel_output,"")
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return df
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