def classify_text(text_list):
text_analyzer = ZeroShotClassificationAnalyzer(
model_name_or_path="joeddav/bart-large-mnli-yahoo-answers", )
return text_analyzer.analyze_input(
source_response_list=text_list,
analyzer_config=ClassificationAnalyzerConfig(labels=[
"no parking", "registration issue", "app issue", "payment issue"
], ))
def zero_shot_analyzer():
return ZeroShotClassificationAnalyzer(
model_name_or_path="typeform/mobilebert-uncased-mnli", )
)
# Fetch full news article
source_config_with_full_text = GoogleNewsConfig(
query="bitcoin",
max_results=5,
fetch_article=True,
lookup_period="1d",
)
source = GoogleNewsSource()
analyzer_config = ClassificationAnalyzerConfig(
labels=["buy", "sell", "going up", "going down"], )
text_analyzer = ZeroShotClassificationAnalyzer(
model_name_or_path="typeform/mobilebert-uncased-mnli", device="auto")
news_articles_without_full_text = source.lookup(
source_config_without_full_text)
news_articles_with_full_text = source.lookup(source_config_with_full_text)
analyzer_responses_without_full_text = text_analyzer.analyze_input(
source_response_list=news_articles_without_full_text,
analyzer_config=analyzer_config,
)
analyzer_responses_with_full_text = text_analyzer.analyze_input(
source_response_list=news_articles_with_full_text,
analyzer_config=analyzer_config)
dir_path = Path(__file__).resolve().parent.parent
source_config = TwitterSourceConfig(
keywords=[os.environ['DAILYGET_QUERY']],
lookup_period=os.environ['DAILYGET_LOOKUP_PERIOD'],
tweet_fields=["author_id", "conversation_id", "created_at", "id", "public_metrics", "text"],
user_fields=["id", "name", "public_metrics", "username", "verified"],
expansions=["author_id"],
place_fields=None,
max_tweets=10,
)
source = TwitterSource()
sink = DailyGetSink()
text_analyzer = ZeroShotClassificationAnalyzer(
model_name_or_path="joeddav/bart-large-mnli-yahoo-answers",
# model_name_or_path="joeddav/xlm-roberta-large-xnli",
)
source_response_list = source.lookup(source_config)
for idx, source_response in enumerate(source_response_list):
logger.info(f"source_response#'{idx}'='{source_response.__dict__}'")
analyzer_response_list = text_analyzer.analyze_input(
source_response_list=source_response_list,
analyzer_config=ClassificationAnalyzerConfig(
labels=["service", "delay", "tracking", "no response", "missing items", "delivery", "mask"],
)
)
for idx, an_response in enumerate(analyzer_response_list):
logger.info(f"analyzer_response#'{idx}'='{an_response.__dict__}'")
)
source = TwitterSource()
# To start jira server locally `atlas-run-standalone --product jira`
jira_sink_config = JiraSinkConfig(
url="http://localhost:2990/jira",
username=SecretStr("admin"),
password=SecretStr("admin"),
issue_type={"name": "Task"},
project={"key": "CUS"},
)
jira_sink = JiraSink()
text_analyzer = ZeroShotClassificationAnalyzer(
model_name_or_path="joeddav/bart-large-mnli-yahoo-answers"
)
source_response_list = source.lookup(source_config)
for idx, source_response in enumerate(source_response_list):
logger.info(f"source_response#'{idx}'='{source_response.__dict__}'")
analyzer_response_list = text_analyzer.analyze_input(
source_response_list=source_response_list,
analyzer_config=ClassificationAnalyzerConfig(
labels=["service", "delay", "performance"],
),
)
for idx, an_response in enumerate(analyzer_response_list):
logger.info(f"analyzer_response#'{idx}'='{an_response.__dict__}'")
def zero_shot_analyzer():
return ZeroShotClassificationAnalyzer(
model_name_or_path="joeddav/bart-large-mnli-yahoo-answers",
)
from obsei.sink.pandas_sink import PandasSink, PandasSinkConfig
from obsei.source.playstore_scrapper import (
PlayStoreScrapperConfig,
PlayStoreScrapperSource,
)
logger = logging.getLogger(__name__)
logging.basicConfig(stream=sys.stdout, level=logging.INFO)
source_config = PlayStoreScrapperConfig(countries=["us"],
package_name="com.apcoaconnect",
max_count=3)
source = PlayStoreScrapperSource()
text_analyzer = ZeroShotClassificationAnalyzer(
model_name_or_path="typeform/mobilebert-uncased-mnli", device="auto")
# initialize pandas sink config
sink_config = PandasSinkConfig(dataframe=DataFrame())
# initialize pandas sink
sink = PandasSink()
source_response_list = source.lookup(source_config)
analyzer_response_list = text_analyzer.analyze_input(
source_response_list=source_response_list,
analyzer_config=ClassificationAnalyzerConfig(labels=[
"no parking", "registration issue", "app issue", "payment issue"
], ),
)
from obsei.source.playstore_scrapper import (
PlayStoreScrapperConfig,
PlayStoreScrapperSource,
)
logger = logging.getLogger(__name__)
logging.basicConfig(stream=sys.stdout, level=logging.INFO)
source_config = PlayStoreScrapperConfig(
app_url=
'https://play.google.com/store/apps/details?id=com.google.android.gm&hl=en_IN&gl=US',
max_count=3)
source = PlayStoreScrapperSource()
text_analyzer = ZeroShotClassificationAnalyzer(
model_name_or_path="typeform/mobilebert-uncased-mnli", device="auto")
source_response_list = source.lookup(source_config)
for idx, source_response in enumerate(source_response_list):
logger.info(f"source_response#'{idx}'='{source_response.__dict__}'")
analyzer_response_list = text_analyzer.analyze_input(
source_response_list=source_response_list,
analyzer_config=ClassificationAnalyzerConfig(
labels=["interface", "slow", "battery"], ),
)
for idx, an_response in enumerate(analyzer_response_list):
logger.info(f"analyzer_response#'{idx}'='{an_response.__dict__}'")