| """HTTP API using the original runtime ENGINE. No sample or fake results.""" |
| from flask import Flask, jsonify, request |
| from dataclasses import asdict, is_dataclass |
| from runtime import engine as nll |
|
|
| flask_app = Flask(__name__) |
| flask_app.config["MAX_CONTENT_LENGTH"] = 1024 * 1024 |
|
|
| @flask_app.get("/health") |
| def health(): |
| return jsonify(status="ok", rule_count=len(nll.RULES), parser_ready="parser" in nll.nlp().pipe_names) |
|
|
| @flask_app.post("/rewrite") |
| def rewrite(): |
| data = request.get_json(silent=True) or {} |
| text = data.get("text", "") |
| if not isinstance(text, str) or not text.strip(): |
| return jsonify(error="text must be a nonempty string"), 400 |
| if len(text) > 50000: |
| return jsonify(error="text exceeds 50,000 characters"), 413 |
| workflow = data.get("workflow", "Edit / Paraphrase Only") |
| mode = data.get("mode", "Balanced") |
| discipline = data.get("discipline", "Auto Detect") |
| terms = data.get("protected_terms", "") |
| if workflow not in ("Scan Only", "Scan & Neutralize", "Edit / Paraphrase Only"): |
| return jsonify(error="unsupported workflow"), 400 |
| if mode not in ("Minimal", "Balanced", "Structural"): |
| return jsonify(error="unsupported mode"), 400 |
| if not isinstance(terms, str): |
| return jsonify(error="protected_terms must be string"), 400 |
| try: |
| try: |
| r = nll.ENGINE.process(text, workflow, mode, discipline, terms, None) |
| except TypeError: |
| r = nll.ENGINE.process(text=text, workflow=workflow, mode=mode, discipline=discipline, terms_text=terms, progress=None) |
| value = asdict(r) if is_dataclass(r) else r |
| return jsonify(value) |
| except Exception: |
| flask_app.logger.exception("NLL request failed") |
| return jsonify(error="processing failed; inspect server logs"), 500 |
|
|
