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Create app.py
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app.py
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import os, io, re, json
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import streamlit as st
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from PIL import Image
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import pdfplumber # text layer for PDFs
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from pdf2image import convert_from_bytes # render image-only PDFs
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import pytesseract # OCR
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APP_TITLE = "Flyer → Image-to-Text (Where & When)"
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st.set_page_config(page_title=APP_TITLE, page_icon="📰", layout="centered")
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st.title("📰 Flyer → Where & When")
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st.caption("Upload a flyer (PDF/JPG/PNG). I’ll read it and pull out the date, time, and location.")
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# ----------- helpers -----------
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DATE_PAT = r"(\b\w{3,9}\b\s+\d{1,2}(?:,\s*\d{4})?)|\b\d{1,2}/\d{1,2}/\d{2,4}\b"
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TIME_PAT = r"\b(\d{1,2}:\d{2}\s*[AP]M|\d{1,2}\s*[AP]M)\b"
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LOC_HINTS = r"(Location|Where|Address|Venue|At)[:\-\s]+(.+)"
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def pdf_bytes_to_text(pdf_bytes: bytes) -> str:
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# Try selectable text first
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parts = []
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try:
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with pdfplumber.open(io.BytesIO(pdf_bytes)) as pdf:
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for page in pdf.pages:
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t = page.extract_text() or ""
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if t.strip():
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parts.append(t)
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except Exception:
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pass
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if parts:
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return "\n\n".join(parts)
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# Fallback to OCR (image-only PDFs)
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txts = []
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images = convert_from_bytes(pdf_bytes, fmt="png", dpi=200)
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for img in images:
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txts.append(pytesseract.image_to_string(img))
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return "\n".join(txts)
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def image_bytes_to_text(img_bytes: bytes) -> str:
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img = Image.open(io.BytesIO(img_bytes)).convert("RGB")
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return pytesseract.image_to_string(img)
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def extract_where_when(text: str):
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# Date(s)
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dates = re.findall(DATE_PAT, text, flags=re.I)
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# re.findall returns tuples from the alternation; flatten/clean:
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clean_dates = []
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for tup in dates:
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s = [t for t in tup if t]
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if s: clean_dates.append(s[0])
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# Time(s)
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times = re.findall(TIME_PAT, text, flags=re.I)
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# Location (first good hint line)
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loc_match = re.search(LOC_HINTS, text, flags=re.I)
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location = loc_match.group(2).strip() if loc_match else ""
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return {
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"dates_found": clean_dates,
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"times_found": times,
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"location": location
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}
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# ----------- UI -----------
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uploaded = st.file_uploader("Upload flyer", type=["pdf", "png", "jpg", "jpeg"])
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manual_text = st.text_area(
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"Or paste text manually (optional)",
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height=160,
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placeholder="If OCR struggles, paste the flyer words here…"
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)
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if st.button("Read flyer"):
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if not uploaded and not manual_text.strip():
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st.warning("Please upload a file or paste some text.")
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st.stop()
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raw_text = ""
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if uploaded:
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if uploaded.type == "application/pdf":
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raw_text = pdf_bytes_to_text(uploaded.read())
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else:
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raw_text = image_bytes_to_text(uploaded.read())
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# If user pasted text, prefer that (it may be cleaner than OCR)
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combined_text = manual_text.strip() or raw_text
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if not combined_text.strip():
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st.error("I couldn’t read any text. Try exporting your Canva flyer as a higher-resolution PNG or a text-based PDF.")
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st.stop()
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results = extract_where_when(combined_text)
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st.success("Done! Here’s what I found:")
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col1, col2 = st.columns(2)
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with col1:
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st.markdown("**Date(s) detected:**")
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if results["dates_found"]:
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st.write(", ".join(results["dates_found"]))
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else:
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st.write("—")
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st.markdown("**Time(s) detected:**")
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if results["times_found"]:
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st.write(", ".join(results["times_found"]))
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else:
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st.write("—")
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with col2:
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st.markdown("**Location detected:**")
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st.write(results["location"] or "—")
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st.markdown("---")
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st.markdown("**All extracted text (for reference):**")
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st.code(combined_text[:3000]) # avoid huge pastes
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st.download_button(
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"Download JSON",
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data=json.dumps(results, indent=2),
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file_name="where_when.json",
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mime="application/json"
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)
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