def nntranslate_api(version=1):
""" Translate text manually entered by the user, by passing the request
to a neural network server and returning its result back """
if not (1 <= version <= 1):
return better_jsonify(valid=False, reason="Unsupported version")
try:
segmented = True
trnsl_src = None
if "application/json" in request.headers["Content-Type"]:
trnsl_src = request.json["pgs"]
src_lang = request.json["src_lang"]
tgt_lang = request.json["tgt_lang"]
else:
segmented = False
trnsl_src = text_from_request(request)
src_lang = request.form.get("src_lang")
tgt_lang = request.form.get("tgt_lang")
if not trnsl_src:
return better_jsonify(valid=False, reason="Invalid request")
except:
return better_jsonify(valid=False, reason="Invalid request")
if segmented:
result = TranslateClient.request_segmented(trnsl_src, src_lang, tgt_lang)
else:
result = TranslateClient.request_text(trnsl_src, src_lang, tgt_lang)
return better_jsonify(valid=True, result=result)
def nnparse_api(version=1):
""" Analyze text manually entered by the user, by passing the request
to a neural network server and returning its result back """
if not (1 <= version <= 1):
return better_jsonify(valid=False, reason="Unsupported version")
try:
text = text_from_request(request)
except:
return better_jsonify(valid=False, reason="Invalid request")
results = ParsingClient.request_sentence(text)
if results is None:
return better_jsonify(valid=False, reason="Service unavailable")
nnTree = results["outputs"]
scores = results["scores"]
result = {
"tree": nnTree.to_dict(),
"width": nnTree.width(),
"height": nnTree.height(),
"scores": scores,
}
return better_jsonify(valid=True, result=result)