Create app.py

app.py

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+import streamlit as st
+import docx
+import PyPDF2
+from transformers import pipeline
+import tempfile
+
+# Load Hugging Face model
+@st.cache_resource
+def load_pipeline():
+    return pipeline("question-answering", model="deepset/roberta-base-squad2")
+
+qa_pipeline = load_pipeline()
+
+def read_pdf(file):
+    text = ""
+    pdf_reader = PyPDF2.PdfReader(file)
+    for page in pdf_reader.pages:
+        text += page.extract_text() + "\n"
+    return text
+
+def read_word(file):
+    doc = docx.Document(file)
+    text = ""
+    for para in doc.paragraphs:
+        text += para.text + "\n"
+    return text
+
+def extract_text(uploaded_file):
+    file_type = uploaded_file.name.split('.')[-1].lower()
+    if file_type == 'pdf':
+        text = read_pdf(uploaded_file)
+    elif file_type == 'docx':
+        text = read_word(uploaded_file)
+    else:
+        st.error("Unsupported file type. Please upload a PDF or Word file.")
+        text = None
+    return text
+
+# Streamlit interface
+def main():
+    st.title("📄 File Reader & Hugging Face Q&A Application")
+    st.write("Upload a PDF or Word file and ask questions based on its content.")
+
+    # File upload
+    uploaded_file = st.file_uploader("Choose a PDF or Word file", type=["pdf", "docx"])
+
+    if uploaded_file is not None:
+        with tempfile.NamedTemporaryFile(delete=False) as temp_file:
+            temp_file.write(uploaded_file.read())
+            temp_file_path = temp_file.name
+
+        # Extract and display text
+        file_text = extract_text(temp_file_path)
+        if file_text:
+            st.text_area("File Content", file_text[:1000] + "... (truncated for display)")
+
+            # Question-answering
+            question = st.text_input("Ask a question based on the file content:")
+
+            if st.button("Get Answer"):
+                if question.strip():
+                    try:
+                        result = qa_pipeline(question=question, context=file_text)
+                        st.success(f"Answer: {result['answer']}")
+                    except Exception as e:
+                        st.error(f"Error generating answer: {str(e)}")
+                else:
+                    st.warning("Please enter a question.")
+
+if __name__ == "__main__":
+    main()