Create app.py

app.py

@@ -0,0 +1,75 @@
+import os
+import openai
+import streamlit as st
+import PyPDF2
+
+# Set up OpenAI API key
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+# Streamlit app
+def main():
+    st.title("EB2-NIW Petition Draft Generator")
+    st.write("Upload a research paper PDF and get a drafted petition addressing the three prongs for EB2-NIW.")
+
+    # File upload
+    uploaded_file = st.file_uploader("Upload PDF", type="pdf")
+
+    if uploaded_file is not None:
+        # Extract text from PDF
+        pdf_text = extract_text_from_pdf(uploaded_file)
+
+        # Button to extract and show text from PDF
+        if st.button("Extract Text"):
+            if pdf_text:
+                st.subheader("Extracted Text:")
+                st.write(pdf_text)
+            else:
+                st.error("Failed to extract text from the PDF.")
+
+        # Button to generate petition draft
+        if st.button("Generate Petition Draft"):
+            if pdf_text.strip() == "":
+                st.error("No text extracted from the PDF. Please check the file and try again.")
+            else:
+                # Generate the petition draft based on the extracted text
+                petition_draft = generate_petition_draft(pdf_text)
+                st.success("Petition Draft:")
+                st.write(petition_draft)
+
+
+# Function to extract text from a PDF
+def extract_text_from_pdf(pdf_file):
+    pdf_reader = PyPDF2.PdfReader(pdf_file)
+    text = ""
+    for page in pdf_reader.pages:
+        text += page.extract_text()
+    return text
+
+# Function to generate EB2-NIW petition draft using GPT-3.5
+def generate_petition_draft(research_text):
+    # Prompt for GPT-3.5
+    prompt = (
+        "A researcher has asked you to draft an EB2-NIW petition. "
+        "Based on the following research paper text, draft a 2-page petition that proves the following three prongs:\n\n"
+        "Prong 1: The applicant's proposed endeavor has substantial merit and national importance.\n"
+        "Prong 2: The applicant is well-positioned to advance the proposed endeavor.\n"
+        "Prong 3: On balance, it would be beneficial to the United States to waive the requirements of the PERM labor certification.\n\n"
+        "Research paper text:\n\n" + research_text
+    )
+
+    # Generate response from GPT-3.5
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages=[
+            {"role": "system", "content": "You are an experienced immigration lawyer."},
+            {"role": "user", "content": prompt}
+        ],
+        max_tokens=5000,
+        temperature=0.1
+    )
+
+    petition_draft = response.choices[0].message['content'].strip()
+    return petition_draft
+
+if __name__ == "__main__":
+    main()