def sample_sentences(intent_name: str, intent_fst_path: str):
rand_fst = fst.Fst.read_from_string(
subprocess.check_output(
["fstrandgen", f"--npath={num_samples}", intent_fst_path]))
sentences: List[Dict[str, Any]] = []
for symbols in fstprintall(rand_fst, exclude_meta=False):
intent = symbols2intent(symbols)
sentences.append(intent)
return sentences
def make_sentences_by_intent(intent_fst: fst.Fst) -> Dict[str, Any]:
"""Get all sentences from an FST."""
from rhasspy.train.jsgf2fst import fstprintall, symbols2intent
# { intent: [ { 'text': ..., 'entities': { ... } }, ... ] }
sentences_by_intent: Dict[str, Any] = defaultdict(list)
for symbols in fstprintall(intent_fst, exclude_meta=False):
intent = symbols2intent(symbols)
intent_name = intent["intent"]["name"]
sentences_by_intent[intent_name].append(intent)
return sentences_by_intent
def recognize_fuzzy(self, text: str, eps: str = "<eps>") -> Dict[str, Any]:
"""Do fuzzy breadth-first search on FST as graph."""
from rhasspy.train.jsgf2fst import symbols2intent
# Assume lower case, white-space separated tokens
tokens = re.split(r"\s+", text)
if self.profile.get("intent.fsticuffs.ignore_unknown_words", True):
# Filter tokens
tokens = [w for w in tokens if w in self.words]
# Only run search if there are any tokens
intents = []
if len(tokens) > 0:
intent_symbols_and_costs = FsticuffsRecognizer._get_symbols_and_costs(
self.graph, tokens, stop_words=self.stop_words, eps=eps
)
for symbols, cost in intent_symbols_and_costs.values():
intent = symbols2intent(symbols, eps=eps)
intent["intent"]["confidence"] = (len(tokens) - cost) / len(tokens)
intents.append(intent)
intents = sorted(
intents, key=lambda i: i["intent"]["confidence"], reverse=True
)
self._logger.debug("Recognized %s intent(s)", len(intents))
# Use first intent
if len(intents) > 0:
intent = intents[0]
# Add slots
intent["slots"] = {}
for ev in intent["entities"]:
intent["slots"][ev["entity"]] = ev["value"]
# Add alternative intents
intent["intents"] = []
for other_intent in intents[1:]:
intent["intents"].append(other_intent)
self._logger.debug(intents)
else:
intent = empty_intent()
intent["text"] = text
return intent
def train(self, intent_fst: fst.Fst):
"""Train using an external program."""
self._logger.debug(self.command)
try:
# { intent: [ { 'text': ..., 'entities': { ... } }, ... ] }
sentences_by_intent: Dict[str, Any] = defaultdict(list)
for symbols in fstprintall(intent_fst, exclude_meta=False):
intent = symbols2intent(symbols)
intent_name = intent["intent"]["name"]
sentences_by_intent[intent_name].append(intent)
# JSON -> STDIN
json_input = json.dumps(sentences_by_intent).encode()
subprocess.run(self.command, input=json_input, check=True)
except Exception:
self._logger.exception("train")