add ml-based version of this

app.py

@@ -0,0 +1,42 @@
+import streamlit as st
+import pandas as pd
+from transformers import pipeline
+import base64
+
+def upload_and_extract_text():
+    uploaded_file = st.file_uploader("Upload PDF file", type=["pdf"])
+
+    if uploaded_file is not None:
+        ocr_pipeline = pipeline("text2text-generation", model="google/t5-v1_1-large")
+        extracted_text = ocr_pipeline(uploaded_file.read(), max_length=1024, do_sample=False)[0]["generated_text"]
+        return extracted_text
+
+def text_to_dataframe(text):
+    lines = text.split("\n")
+    data = []
+    for line in lines:
+        data.append([line])
+    df = pd.DataFrame(data, columns=["Text"])
+    return df
+
+def main():
+    st.title("PDF to Spreadsheet Converter")
+    st.write("Upload a PDF file to extract text and save it as a spreadsheet.")
+
+    extracted_text = upload_and_extract_text()
+
+    if extracted_text is not None:
+        st.write("### Extracted Text")
+        st.write(extracted_text)
+
+        df = text_to_dataframe(extracted_text)
+        st.write("### Spreadsheet Preview")
+        st.write(df)
+
+        csv = df.to_csv(index=False)
+        b64 = base64.b64encode(csv.encode()).decode()
+        href = f'<a href="data:file/csv;base64,{b64}" download="extracted_text.csv">Download Extracted Text as CSV</a>'
+        st.markdown(href, unsafe_allow_html=True)
+
+if __name__ == "__main__":
+    main()

requirements.txt

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+streamlit==1.3.0
+transformers==4.13.0
+pandas==1.4.1