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import hashlib
import json
import os
import sys
import streamlit as st
import pypdfium2 as pdfium
from huggingface_hub import HfApi, hf_hub_download
ROOT_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
if ROOT_DIR not in sys.path:
sys.path.insert(0, ROOT_DIR)
from extractor import extract_using_openai_from_pdf_bytes, TEMPLATE_REGISTRY
SAMPLE_DATASET_REPO = os.getenv(
"SAMPLE_DATASET_REPO",
"pradyten/pdf-extractor-samples",
)
st.set_page_config(page_title="PDF Extractor", layout="wide")
st.markdown(
"""
<style>
@import url('https://fonts.googleapis.com/css2?family=Space+Grotesk:wght@500;700&family=Plus+Jakarta+Sans:wght@400;500;600&display=swap');
:root {
--bg-0: #f3ede4;
--bg-1: #fbf5ea;
--panel: #ffffff;
--border: rgba(16, 24, 40, 0.12);
--text: #121212;
--muted: #5b616b;
--accent: #d4552d;
--accent-dark: #b44725;
--shadow: 0 18px 50px rgba(20, 20, 20, 0.12);
}
html, body, [data-testid="stAppViewContainer"] {
background: radial-gradient(1200px 600px at 10% -10%, var(--bg-0) 0%, #f7f2e9 45%, var(--bg-1) 100%);
color: var(--text);
font-family: "Plus Jakarta Sans", system-ui, -apple-system, "Segoe UI", sans-serif;
}
h1, h2, h3, h4, h5 {
font-family: "Space Grotesk", system-ui, -apple-system, "Segoe UI", sans-serif;
letter-spacing: -0.02em;
}
.main .block-container {
max-width: 1200px;
padding-top: 2.5rem;
padding-bottom: 3rem;
}
div[data-testid="column"] > div {
background: var(--panel);
border: 1px solid var(--border);
border-radius: 18px;
padding: 1.25rem 1.5rem 1.5rem 1.5rem;
box-shadow: var(--shadow);
}
.stButton > button {
background: var(--accent);
color: #ffffff;
border: none;
border-radius: 999px;
padding: 0.65rem 1.4rem;
font-weight: 600;
}
.stButton > button:hover {
background: var(--accent-dark);
color: #ffffff;
}
div[data-testid="stFileUploader"] {
border: 1px dashed rgba(16, 24, 40, 0.18);
border-radius: 14px;
padding: 0.6rem;
background: rgba(248, 244, 236, 0.6);
}
.stAlert {
border-radius: 12px;
}
pre, code, .stCodeBlock {
border-radius: 12px !important;
}
#MainMenu, footer {
visibility: hidden;
}
</style>
""",
unsafe_allow_html=True,
)
def _render_pdf_preview(pdf_bytes: bytes) -> None:
pdf = None
try:
pdf = pdfium.PdfDocument(pdf_bytes)
if len(pdf) < 1:
st.info("No pages found in this PDF.")
return
page = pdf[0]
pil_image = page.render(scale=2.0).to_pil()
st.image(pil_image, caption="Preview (page 1)", use_column_width=True)
except Exception as exc: # pragma: no cover - UI preview path
st.warning(f"Preview unavailable: {exc}")
finally:
if pdf is not None:
pdf.close()
def _load_pdf_state(uploaded_file) -> tuple[bytes, str, str]:
pdf_bytes = uploaded_file.getvalue()
digest = hashlib.sha256(pdf_bytes).hexdigest()
return pdf_bytes, uploaded_file.name, digest
@st.cache_data(show_spinner=False)
def _list_sample_pdfs(repo_id: str) -> list[str]:
api = HfApi()
try:
files = api.list_repo_files(repo_id=repo_id, repo_type="dataset")
except Exception:
return []
return sorted(name for name in files if name.lower().endswith(".pdf"))
@st.cache_data(show_spinner=False)
def _load_sample_state(repo_id: str, filename: str) -> tuple[bytes, str, str]:
path = hf_hub_download(repo_id=repo_id, filename=filename, repo_type="dataset")
with open(path, "rb") as fh:
pdf_bytes = fh.read()
digest = hashlib.sha256(pdf_bytes).hexdigest()
return pdf_bytes, filename, digest
def _build_download_name(filename: str) -> str:
base = os.path.splitext(filename)[0] if filename else "extraction"
safe = "".join(ch if ch.isalnum() or ch in ("-", "_") else "_" for ch in base)
if not safe:
safe = "extraction"
return f"{safe}_extracted.json"
def _reset_pdf_state() -> None:
st.session_state.pdf_bytes = None
st.session_state.pdf_filename = None
st.session_state.pdf_digest = None
st.session_state.extract_result = None
st.session_state.extract_error = None
st.session_state.extract_digest = None
st.session_state.extract_filename = None
def _supported_doc_types() -> list[str]:
seen = []
for cfg in TEMPLATE_REGISTRY.values():
doc_type = cfg.get("document_type")
if doc_type and doc_type not in seen:
seen.append(doc_type)
return seen
if "extract_result" not in st.session_state:
st.session_state.extract_result = None
if "extract_error" not in st.session_state:
st.session_state.extract_error = None
if "extract_digest" not in st.session_state:
st.session_state.extract_digest = None
if "extract_filename" not in st.session_state:
st.session_state.extract_filename = None
if "pdf_bytes" not in st.session_state:
st.session_state.pdf_bytes = None
if "pdf_filename" not in st.session_state:
st.session_state.pdf_filename = None
if "pdf_digest" not in st.session_state:
st.session_state.pdf_digest = None
if "input_mode_prev" not in st.session_state:
st.session_state.input_mode_prev = None
st.markdown("## PDF Extractor")
st.markdown(
"Choose a sample or upload your own PDF, preview it, then click Extract "
"to generate structured JSON on the right."
)
left, right = st.columns([1, 1], gap="large")
with left:
st.markdown("### Upload + Preview")
input_mode = st.radio(
"Input source",
["Upload PDF", "Use sample"],
horizontal=True,
label_visibility="collapsed",
key="input_mode",
)
if st.session_state.input_mode_prev != input_mode:
_reset_pdf_state()
st.session_state.input_mode_prev = input_mode
selected_sample = None
uploaded_file = None
if input_mode == "Use sample":
sample_files = _list_sample_pdfs(SAMPLE_DATASET_REPO)
if not sample_files:
st.info("No sample PDFs found in the sample dataset yet.")
_reset_pdf_state()
sample_options = ["Choose a sample..."] + sample_files
sample_choice = st.selectbox(
"Choose a sample",
sample_options,
label_visibility="collapsed",
key="sample_choice",
)
selected_sample = sample_choice if sample_choice in sample_files else None
if selected_sample is None:
_reset_pdf_state()
else:
uploaded_file = st.file_uploader(
"Upload a PDF",
type=["pdf"],
accept_multiple_files=False,
label_visibility="collapsed",
key="pdf_uploader",
help="File name should include a known keyword (for example: resume, passport, i129).",
)
if input_mode == "Use sample" and selected_sample:
try:
pdf_bytes, filename, digest = _load_sample_state(
SAMPLE_DATASET_REPO,
selected_sample,
)
except Exception as exc: # pragma: no cover - sample load path
st.error(f"Sample load failed: {exc}")
else:
if st.session_state.pdf_digest != digest:
st.session_state.pdf_bytes = pdf_bytes
st.session_state.pdf_filename = filename
st.session_state.pdf_digest = digest
st.session_state.extract_result = None
st.session_state.extract_error = None
st.session_state.extract_digest = digest
st.session_state.extract_filename = filename
st.markdown(f"**Sample:** `{st.session_state.pdf_filename}`")
_render_pdf_preview(st.session_state.pdf_bytes)
elif input_mode == "Upload PDF" and uploaded_file is not None:
pdf_bytes, filename, digest = _load_pdf_state(uploaded_file)
if st.session_state.pdf_digest != digest:
st.session_state.pdf_bytes = pdf_bytes
st.session_state.pdf_filename = filename
st.session_state.pdf_digest = digest
st.session_state.extract_result = None
st.session_state.extract_error = None
st.session_state.extract_digest = digest
st.session_state.extract_filename = filename
st.markdown(f"**File:** `{st.session_state.pdf_filename}`")
_render_pdf_preview(st.session_state.pdf_bytes)
else:
st.info("Upload a PDF or choose a sample to preview it here.")
st.markdown("#### Notes")
st.caption(
"Template selection is inferred from the filename. If extraction fails, "
"rename the file to include a supported keyword (for example: "
"`resume.pdf`, `passport_jane.pdf`, `i129_petition.pdf`)."
)
st.caption(f"Sample dataset: `{SAMPLE_DATASET_REPO}`")
st.markdown("#### Supported documents")
st.markdown("\n".join(f"- {doc}" for doc in _supported_doc_types()))
with right:
st.markdown("### Extract")
model_choice = st.selectbox(
"Model",
["default", "gpt-4.1-mini", "gpt-4.1", "gpt-4o-mini", "gpt-4o"],
index=1,
help="Choose a model or use default (EXTRACTOR_MODEL_ALIAS).",
)
has_api_key = bool(os.getenv("OPENAI_API_KEY"))
if not has_api_key:
st.warning("OPENAI_API_KEY is not set. Add it to your environment or Space secrets.")
extract_clicked = st.button(
"Extract",
use_container_width=False,
disabled=st.session_state.pdf_bytes is None or not has_api_key,
)
if extract_clicked:
with st.spinner("Extracting structured JSON..."):
try:
result = extract_using_openai_from_pdf_bytes(
st.session_state.pdf_bytes,
st.session_state.pdf_filename,
model=model_choice,
)
st.session_state.extract_result = result
st.session_state.extract_error = None
except Exception as exc: # pragma: no cover - runtime error path
message = str(exc)
if "403" in message or "PermissionDenied" in message:
message = (
"OpenAI request was rejected (403). "
"Check OPENAI_API_KEY, model access, and billing."
)
st.session_state.extract_error = message
st.session_state.extract_result = None
if st.session_state.extract_error:
st.error(st.session_state.extract_error)
if st.session_state.extract_result is None:
st.info("Extraction output will appear here.")
else:
st.markdown("#### JSON Output")
json_text = json.dumps(
st.session_state.extract_result,
indent=2,
ensure_ascii=False,
)
st.code(json_text, language="json")
st.download_button(
"Download JSON",
data=json_text,
file_name=_build_download_name(st.session_state.pdf_filename or ""),
mime="application/json",
)
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