File size: 6,587 Bytes
cba2c8f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 |
import streamlit as st
from pathlib import Path
import requests
API_URL = "http://localhost:8000"
# ----------------------------------
# Setup folders (UI only)
# ----------------------------------
BASE_DIR = Path.cwd()
QUERY_DIR = BASE_DIR / "queries"
QUERY_DIR.mkdir(parents=True, exist_ok=True)
# ----------------------------------
# Session state init (CRITICAL FIX)
# ----------------------------------
if "saved_docs" not in st.session_state:
st.session_state.saved_docs = []
if "saved_once" not in st.session_state:
st.session_state.saved_once = set() # prevents duplicates
saved_docs = st.session_state.saved_docs
# ----------------------------------
# UI
# ----------------------------------
st.set_page_config(page_title="Exam Pipeline", layout="wide")
st.title("📘 Exam Question Processing Pipeline")
api_key = "your_groq_api_key_here" # Replace with your actual API key or use st.text_input to get from user
num_docs = st.number_input(
"Number of documents",
min_value=1,
step=1
)
# ----------------------------------
# Upload Section
# ----------------------------------
for i in range(num_docs):
st.subheader(f"Document {i+1}")
doc_type = st.radio(
"Input type",
["Images", "PDF"],
key=f"type_{i}"
)
# -------- Images --------
if doc_type == "Images":
uploaded_images = st.file_uploader(
"Upload images",
type=["png", "jpg", "jpeg"],
accept_multiple_files=True,
key=f"img_{i}"
)
if uploaded_images and st.button(f"Save Images as PDF (Doc {i+1})"):
unique_key = f"img_{i}_{','.join(img.name for img in uploaded_images)}"
if unique_key not in st.session_state.saved_once:
res = requests.post(
f"{API_URL}/images-to-pdf",
files=[
("files", (img.name, img.getvalue(), img.type))
for img in uploaded_images
]
)
if res.status_code != 200:
st.error(res.text)
st.stop()
data = res.json()
if "error" in data:
st.error(data["error"])
st.stop()
pdf_path = data["path"]
saved_docs.append(pdf_path)
st.session_state.saved_once.add(unique_key)
st.success(f"Saved → {pdf_path}")
else:
st.info("Images already saved for this document.")
# -------- PDF --------
else:
uploaded_pdf = st.file_uploader(
"Upload PDF",
type=["pdf"],
key=f"pdf_{i}"
)
if uploaded_pdf:
unique_key = f"pdf_{i}_{uploaded_pdf.name}"
if unique_key not in st.session_state.saved_once:
res = requests.post(
f"{API_URL}/save-pdf",
files={
"file": (
uploaded_pdf.name,
uploaded_pdf.getvalue(),
"application/pdf"
)
}
)
if res.status_code != 200:
st.error(res.text)
st.stop()
data = res.json()
if "error" in data:
st.error(data["error"])
st.stop()
pdf_path = data["path"]
saved_docs.append(pdf_path)
st.session_state.saved_once.add(unique_key)
st.success(f"Saved → {pdf_path}")
else:
st.info("PDF already saved for this document.")
# ----------------------------------
# Run Pipeline
# ----------------------------------
import time
import time
if st.button("🚀 Run Full Pipeline"):
if not api_key:
st.error("❌ API key required")
st.stop()
if not saved_docs:
st.error("❌ Please upload images or PDFs first")
st.stop()
# ---------------- START PIPELINE ----------------
start_res = requests.post(
f"{API_URL}/run-pipeline",
params={"api_key": api_key},
json=saved_docs
)
if start_res.status_code != 200:
st.error(start_res.text)
st.stop()
start_data = start_res.json()
job_id = start_data.get("job_id")
if not job_id:
st.error("❌ Failed to start pipeline")
st.stop()
# ---------------- STATUS POLLING ----------------
st.subheader("🚀 Pipeline Progress")
status_box = st.empty()
final_result = None
while True:
status_res = requests.get(f"{API_URL}/job-status/{job_id}")
if status_res.status_code != 200:
st.error(status_res.text)
st.stop()
status_data = status_res.json()
status_text = status_data.get("status", "Unknown status")
status_box.info(status_text)
# ❌ error case
if status_text.startswith("❌"):
st.error(status_text)
st.stop()
# ✅ completed
if status_text == "✅ Completed":
final_result = status_data.get("result")
break
time.sleep(1)
# ---------------- FINAL OUTPUT ----------------
if not final_result:
st.error("Pipeline finished but no result returned")
st.stop()
st.success("✅ Pipeline completed successfully!")
final_pdf = final_result["final_pdf"]
freq_json = final_result["frequency_json"]
with open(final_pdf, "rb") as f:
st.download_button(
"📥 Download Final PDF",
f,
file_name="Exam_Frequency_Report.pdf"
)
with open(freq_json, "rb") as f:
st.download_button(
"📥 Download Frequency JSON",
f,
file_name="output_frequency.json"
)
# ----------------------------------
# Debug view (UNCHANGED)
# ----------------------------------
st.subheader("📂 PDFs available in queries/")
st.write([str(p) for p in QUERY_DIR.glob("*.pdf")])
st.subheader("📂 Recently Uploaded PDFs (This Session Only)")
if saved_docs:
st.write(saved_docs)
else:
st.info("No documents uploaded in this session.")
|