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import streamlit as st
from PIL import Image
from ocr_utils import extract_receipt_text, extract_from_text, transcribe_audio
from streamlit_mic_recorder import mic_recorder
import tempfile
import os
# ------------------ Streamlit UI ------------------
st.set_page_config(page_title="SmartReceipt AI", layout="centered")
st.title("SmartReceipt AI")
st.write("Provide your text or speech And upload a receipt image to extract structured plain-text.")
# Session state
if "user_text" not in st.session_state:
st.session_state.user_text = ""
if "uploaded_image" not in st.session_state:
st.session_state.uploaded_image = None
if "ocr_result" not in st.session_state:
st.session_state.ocr_result = None
# ---------------- Input: User Text or Speech ----------------
st.subheader("Enter text or record speech")
# Text input field
st.session_state.user_text = st.text_area("Type your input here:", st.session_state.user_text, height=100)
# Mic recorder
audio = mic_recorder(
start_prompt="Start Recording",
stop_prompt="Stop Recording",
just_once=True,
use_container_width=True
)
if audio and "bytes" in audio:
with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp_file:
tmp_file.write(audio["bytes"])
tmp_path = tmp_file.name
transcribed_text = transcribe_audio(tmp_path)
st.session_state.user_text = transcribed_text
st.text_area("Transcribed Text:", transcribed_text, height=100)
os.remove(tmp_path)
# ---------------- Input: Receipt Image ----------------
uploaded_file = st.file_uploader("Upload a receipt (JPG/PNG)", type=["jpg", "jpeg", "png"])
if uploaded_file:
st.session_state.uploaded_image = uploaded_file
image = Image.open(uploaded_file)
st.image(image, caption="Uploaded Receipt", width=400)
# ---------------- Run OCR ----------------
if st.button("Analyze Receipt"):
if st.session_state.user_text.strip() and st.session_state.uploaded_image:
with st.spinner("Processing..."):
ocr_text = extract_receipt_text(st.session_state.uploaded_image)
model_input_text = st.session_state.user_text
final_result = extract_from_text(f"User Prompt: {model_input_text}\n\n{ocr_text}")
st.session_state.ocr_result = final_result
else:
st.warning("Please provide both a user prompt (text or speech) and a receipt image.")
# ---------------- Show Result ----------------
if st.session_state.ocr_result:
st.subheader("Extracted Receipt Text")
st.text_area("OCR Result", st.session_state.ocr_result, height=400)
st.download_button(
"Download Receipt as TXT",
data=st.session_state.ocr_result,
file_name="receipt_output.txt",
mime="text/plain"
)
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