File size: 2,973 Bytes
50a8ea3 | 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 | import os
import tempfile
from fastapi import FastAPI, File, HTTPException, UploadFile
from gradio_client import Client, handle_file
import pymupdf
app = FastAPI(
title="Civic & RTI PDF Simplifier API",
description="Transforms bureaucratic RTI/civic PDF documents into plain-language summaries.",
version="1.0.0",
)
HF_SPACE_ID = "Ronak0/RC"
# Connect to the live Gradio Space instance running your fine-tuned model
try:
client = Client(HF_SPACE_ID)
except Exception as e:
client = None
print(f"[WARNING] Could not initialize Gradio client connection: {e}")
def extract_pdf_chunks(
pdf_path: str, chunk_size: int = 180, max_chunks: int = 6
) -> list[str]:
doc = pymupdf.open(pdf_path)
collected_lines = []
for page in doc:
text = page.get_text("text")
lines = [
line.strip()
for line in text.split("\n")
if len(line.strip().split()) >= 5
]
collected_lines.extend(lines)
full_text = " ".join(collected_lines)
words = full_text.split()
if not words:
return []
chunks = [
" ".join(words[i : i + chunk_size])
for i in range(0, len(words), chunk_size)
]
return chunks[:max_chunks]
@app.get("/")
def root():
return {
"status": "online",
"service": "Civic & RTI PDF Simplifier API",
"connected_space": HF_SPACE_ID,
}
@app.post("/simplify")
async def simplify_pdf(file: UploadFile = File(...)):
if not file.filename.lower().endswith(".pdf"):
raise HTTPException(
status_code=400,
detail="Invalid file format. Please upload a valid PDF document.",
)
with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmp:
tmp.write(await file.read())
tmp_path = tmp.name
try:
# 1. First attempt: Pass PDF directly to your fine-tuned Space pipeline
if client is not None:
try:
raw_result = client.predict(
pdf_file=handle_file(tmp_path), api_name="/predict"
)
if raw_result and isinstance(raw_result, str):
points = [
p.strip() for p in raw_result.split("\n\n") if p.strip()
]
return {"filename": file.filename, "simplified_points": points}
except Exception as err:
print(f"[INFO] Direct space call fallback: {err}")
# 2. Local fallback chunk extraction if direct space payload differs
chunks = extract_pdf_chunks(tmp_path)
if not chunks:
return {
"filename": file.filename,
"simplified_points": [
"No readable text could be extracted from this document."
],
}
return {
"filename": file.filename,
"simplified_points": [
f"Extracted Section {i+1}: {chunk[:160]}..."
for i, chunk in enumerate(chunks)
],
}
finally:
if os.path.exists(tmp_path):
os.remove(tmp_path) |