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import streamlit as st
import requests
# ----------------- Streamlit Setup ----------------- #
st.set_page_config(page_title="Lease Agreement Extractor (OCR + AI)", layout="centered")
st.title("πŸ“„ Lease Agreement Extractor (OCR + AI)")
# ----------------- Assistant & API Config ----------------- #
OPENAI_ASSISTANT_ID = "asst_xBnNfiyWmVa4iF3CgXwJnmBt" # Replace with your assistant ID
OPENAI_API_KEY = "YOUR_OPENAI_API_KEY" # Replace with your OpenAI key
HEADERS = {
"Authorization": f"Bearer {OPENAI_API_KEY}",
"Content-Type": "application/json"
}
# ----------------- Upload Interface ----------------- #
uploaded_file = st.file_uploader("Upload a lease agreement (PDF, PNG, JPG)", type=["pdf", "png", "jpg", "jpeg"])
def upload_file_to_openai(file_bytes, filename):
files = {
"file": (filename, file_bytes, "application/octet-stream")
}
response = requests.post("https://api.openai.com/v1/files", headers={"Authorization": f"Bearer {OPENAI_API_KEY}"}, files=files)
return response.json().get("id")
def create_thread_and_run(file_id):
# Create thread
thread_res = requests.post("https://api.openai.com/v1/threads", headers=HEADERS, json={})
thread_data = thread_res.json()
thread_id = thread_data.get("id")
# Run assistant with structured lease extraction prompt
run_payload = {
"assistant_id": OPENAI_ASSISTANT_ID,
"instructions": """
You are an AI assistant designed to extract structured lease data from any uploaded agreement, even if it is scanned. Your responsibilities are:
- Accept PDF or image-based lease documents.
- Use OCR (Optical Character Recognition) if the document is non-selectable or scanned.
- Parse and extract key structured data fields from lease agreements.
- Output results in JSON format following a fixed schema.
OCR & Extraction Rules:
1. If text cannot be extracted normally, perform OCR using image-to-text on each page.
2. Preserve paragraph structure, detect headers, signature blocks, tables, and dates.
Expected JSON Output:
{
"document_title": "Lease Agreement Title or File Name",
"parties": {
"lessor": "Name of Lessor",
"lessee": "Name of Lessee"
},
"property_description": "Detailed description of leased property",
"term": {
"start_date": "YYYY-MM-DD",
"end_date": "YYYY-MM-DD",
"renewal_options": "Yes/No or Clause Text"
},
"financials": {
"monthly_rent": "Amount",
"deposit": "Amount",
"escalation_clause": "Text if present"
},
"obligations": {
"maintenance": "Lessor/Lessee",
"insurance": "Lessor/Lessee",
"subletting": "Allowed/Not allowed"
},
"signatures": [
{
"party": "Party Name",
"signed_by": "Full Name",
"date": "YYYY-MM-DD",
"position": "Title if listed"
}
],
"raw_text_per_page": {
"page_1": "Full OCR text of page 1",
"page_2": "Full OCR text of page 2"
}
}
πŸ“Œ Behaviors:
- Automatically detect if OCR is needed.
- Normalize dates to YYYY-MM-DD.
- Use "Not Found" or null where info is missing.
- Return JSON only.
- If OCR text is low-confidence, include: "low_confidence": true
""",
"file_ids": [file_id]
}
run_res = requests.post(f"https://api.openai.com/v1/threads/{thread_id}/runs", headers=HEADERS, json=run_payload)
run_data = run_res.json()
run_id = run_data.get("id")
return thread_id, run_id
# ----------------- Main UI Flow ----------------- #
if uploaded_file is not None:
st.success("πŸ“„ File uploaded successfully.")
if st.button("πŸš€ Run Lease Extraction"):
with st.spinner("Uploading and invoking assistant..."):
file_id = upload_file_to_openai(uploaded_file.getvalue(), uploaded_file.name)
if file_id:
thread_id, run_id = create_thread_and_run(file_id)
st.success("βœ… Assistant run started!")
st.code(f"Thread ID: {thread_id}", language="text")
st.code(f"Run ID: {run_id}", language="text")
st.markdown("πŸ“Œ You can retrieve results via OpenAI API using these IDs.")
else:
st.error("❌ File upload to OpenAI failed.")
else:
st.info("Please upload a lease agreement file to begin.")