structued well
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71
apps/PatientDataExtractorService/main.py
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71
apps/PatientDataExtractorService/main.py
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from flask import Flask, request, jsonify
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import fitz # PyMuPDF
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import re
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app = Flask(__name__)
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DOB_RE = re.compile(r'(?<!\d)(\d{1,2})/(\d{1,2})/(\d{4})(?!\d)')
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ID_RE = re.compile(r'^\d{8,14}$') # 8–14 digits, whole line
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# lines that tell us we've moved past the name/DOB area
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STOP_WORDS = {
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'eligibility', 'coverage', 'age band', 'date of', 'service',
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'tooth', 'number', 'surface', 'procedure', 'code', 'description',
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'provider', 'printed on', 'member id', 'name', 'date of birth'
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}
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@app.route("/extract", methods=["POST"])
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def extract():
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file = request.files['pdf']
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doc = fitz.open(stream=file.read(), filetype="pdf")
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text = "\n".join(page.get_text("text") for page in doc)
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lines = [line.strip() for line in text.splitlines() if line.strip()]
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member_id = ""
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name = ""
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dob = ""
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# 1) Find the first plausible member ID (8–14 digits)
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id_idx = -1
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for i, line in enumerate(lines):
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if ID_RE.match(line):
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member_id = line
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id_idx = i
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break
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if id_idx == -1:
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return jsonify({"memberId": "", "name": "", "dob": ""})
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# 2) Scan forward to collect name + DOB; handle both same-line and next-line cases
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collected = []
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j = id_idx + 1
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while j < len(lines):
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low = lines[j].lower()
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if any(sw in low for sw in STOP_WORDS):
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break
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collected.append(lines[j])
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# If we already found a DOB, we can stop early
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if DOB_RE.search(lines[j]):
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break
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j += 1
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# Flatten the collected chunk to search for a date (works if DOB is on same line or next)
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blob = " ".join(collected).strip()
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m = DOB_RE.search(blob)
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if m:
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dob = m.group(0)
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# name is everything before the date within the same blob
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name = blob[:m.start()].strip()
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else:
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# fallback: if we didn't find a date, assume first collected line(s) are name
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name = blob
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return jsonify({
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"memberId": member_id,
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"name": name,
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"dob": dob
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})
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if __name__ == "__main__":
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app.run(port=5001)
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