async def classifier_learn_intent(request):
req_data = request.json
if "label" not in req_data \
or "examples" not in req_data \
or not (type(req_data["examples"]) == list):
return s_json({"code": 400, "msg": "invalid request"})
label = req_data["label"]
examples = req_data["examples"]
classifier.learn_intent(label, examples)
return s_json({"code": 0, "msg": "success"})
async def classifier_learn(request):
req_data = request.json
if "label" not in req_data \
or not req_data["label"] \
or "sentence" not in req_data \
or not req_data["sentence"]:
return s_json({"code": 400, "msg": "invalid request"})
label = req_data["label"]
sentence = req_data["sentence"]
classifier.learn(label, sentence)
return s_json({"code": 0, "msg": "success"})
async def chat_reply(request):
req_data = request.json
if "index" not in req_data \
or type(req_data["index"]) != str \
or "say" not in req_data \
or type(req_data["say"]) != str \
or "threshold" not in req_data \
or type(req_data["threshold"]) != float:
return s_json({"code": 400, "msg": "invalid request"})
chat_index = req_data["index"]
threshold = req_data["threshold"]
say = req_data["say"]
r = chat.reply(say, threshold, chat_index)
return s_json({"code": 0, "msg": "success", "proto": r})
async def classifier_predict(request):
req_data = request.json
if "sentence" not in req_data \
or type(req_data["sentence"]) != str \
or "possibles" not in req_data \
or type(req_data["possibles"]) != list \
or "threshold" not in req_data \
or type(req_data["threshold"]) != float \
or "limit" not in req_data \
or type(req_data["limit"]) != int:
return s_json({"code": 400, "msg": "invalid request"})
sentence = req_data["sentence"]
possibles = req_data["possibles"]
threshold = req_data["threshold"]
limit = req_data["limit"]
sentence_doc = classifier.nlp(sentence)
prediction = classifier.predict(sentence_doc, possibles, threshold, limit)
return s_json({"code": 0, "msg": "success", "proto": prediction})
async def chat_learn(request):
req_data = request.json
if "cid" not in req_data \
or type(req_data["cid"]) != str \
or "say" not in req_data \
or type(req_data["say"]) != str \
or "reply" not in req_data \
or type(req_data["reply"]) != str \
or "index" not in req_data \
or type(req_data["index"]) != str:
return s_json({"code": 400, "msg": "invalid request"})
cid = req_data["cid"]
say = req_data["say"]
reply = req_data["reply"]
chat_index = req_data["index"]
if not cid or not say or not reply:
return s_json({"code": 400, "msg": "invalid request"})
chat.learn(cid, say, reply, chat_index)
return s_json({"code": 0, "msg": "success"})
async def index(request):
sentence_doc = classifier.nlp("hello world")
prediction = classifier.predict(sentence_doc, [], 0.75, 5)
return s_json({"test": prediction})