Dodaje opcje do mockowania NLU

This commit is contained in:
s495727 2024-06-10 17:44:48 +02:00
parent ff0b4af87c
commit f4d9bff809
2 changed files with 22 additions and 16 deletions

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@ -1,12 +1,12 @@
from service.dialog_state_monitor import DialogStateMonitor
from service.dialog_policy import DialogPolicy
from service.natural_languag_understanding import NaturalLanguageUnderstanding
from service.natural_language_generation import NaturalLanguageGeneration, parse_frame
from service.natural_language_generation import NaturalLanguageGeneration
from service.templates import templates
from convlab.dialog_agent import PipelineAgent
# initialize classes
nlu = NaturalLanguageUnderstanding() # NLU
nlu = NaturalLanguageUnderstanding(use_mocks=False) # NLU
monitor = DialogStateMonitor() # DSM
dialog_policy = DialogPolicy() # DP
language_generation = NaturalLanguageGeneration(templates) # NLG

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@ -1,4 +1,3 @@
from flair.models import SequenceTagger
from utils.nlu_utils import predict_single, predict_and_annotate
from model.frame import Frame, Slot
import random
@ -42,7 +41,12 @@ SLOTS:
"""
class NaturalLanguageUnderstanding():
def __init__(self):
def __init__(self, use_mocks=False):
if use_mocks:
self.use_mocks = True
return
from flair.models import SequenceTagger
print("\n========================================================")
print("Models are loading, it may take a moment, please wait...")
print("========================================================\n")
@ -86,14 +90,16 @@ class NaturalLanguageUnderstanding():
return slots
def predict(self, text: str):
if not self.use_mocks:
act = self.__predict_intention(text)
slots = self.__predict_slot(text)
frame = Frame(source = 'user', act = act, slots = slots)
# uncomment to quickly mock the response
# frames = [
# Frame(source="user", act = "inform/order", slots=[Slot(name="pizza", value="barcelona")]),
# Frame(source="user", act = "welcomemsg", slots=[]),
# Frame(source="user", act = "request/menu", slots=[]),
# ]
# return random.choice(frames)
return frame
else:
frames = [
Frame(source="user", act = "inform/order", slots=[Slot(name="pizza", value="barcelona")]),
Frame(source="user", act = "welcomemsg", slots=[]),
Frame(source="user", act = "request/menu", slots=[]),
]
return random.choice(frames)