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Update app.py
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app.py
CHANGED
@@ -8,7 +8,9 @@ def setup_logging():
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(levelname)s - %(message)s',
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handlers=[
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)
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# Function to extract text from a PDF file
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@@ -23,8 +25,8 @@ def main():
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setup_logging()
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logging.info("Starting the Streamlit app.")
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# Initialize the
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summarizer = pipeline("summarization", model="
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# Streamlit UI
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st.title("GenAI Lab Report Analyzer")
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@@ -51,7 +53,7 @@ def main():
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elif input_type == "Audio":
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audio = st.file_uploader("Upload your audio file:", type=["wav", "mp3", "m4a"])
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if st.button("
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try:
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summary = None
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if input_type == "Text" and text:
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@@ -74,6 +76,7 @@ def main():
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summary = "Invalid input. Please provide a valid file or text."
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logging.warning("Invalid input type provided.")
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st.text_area("Report Result:", summary[0]['summary_text'] if isinstance(summary, list) else summary, height=200)
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except Exception as e:
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logging.error(f"Error during summarization: {e}")
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(levelname)s - %(message)s',
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handlers=[
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logging.StreamHandler()
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]
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)
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# Function to extract text from a PDF file
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setup_logging()
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logging.info("Starting the Streamlit app.")
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# Initialize the summarization pipeline with a public model for long medical texts
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summarizer = pipeline("summarization", model="allenai/led-large-16384-arxiv")
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# Streamlit UI
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st.title("GenAI Lab Report Analyzer")
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elif input_type == "Audio":
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audio = st.file_uploader("Upload your audio file:", type=["wav", "mp3", "m4a"])
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if st.button("Report Result"):
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try:
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summary = None
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if input_type == "Text" and text:
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summary = "Invalid input. Please provide a valid file or text."
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logging.warning("Invalid input type provided.")
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# Display the summarized result
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st.text_area("Report Result:", summary[0]['summary_text'] if isinstance(summary, list) else summary, height=200)
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except Exception as e:
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logging.error(f"Error during summarization: {e}")
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