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import logging
import sys
from pathlib import Path
from obsei.sink.elasticsearch_sink import ElasticSearchSink, ElasticSearchSinkConfig
from obsei.source.twitter_source import TwitterSource, TwitterSourceConfig
from obsei.analyzer.classification_analyzer import (
ClassificationAnalyzerConfig,
ZeroShotClassificationAnalyzer,
)
logger = logging.getLogger(__name__)
logging.basicConfig(stream=sys.stdout, level=logging.INFO)
dir_path = Path(__file__).resolve().parent.parent
source_config = TwitterSourceConfig(
keywords="@Handle",
lookup_period="1h", # 1 Hour
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()
text_analyzer = ZeroShotClassificationAnalyzer(
model_name_or_path="joeddav/bart-large-mnli-yahoo-answers",
)
# Start Elasticsearch server locally
# `docker run -d --name elasticsearch -p 9200:9200 -e "discovery.type=single-node" elasticsearch:7.9.2`
sink_config = ElasticSearchSinkConfig(
host="localhost",
port=9200,
index_name="test",
)
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__}'")
sink = ElasticSearchSink()
sink_response = sink.send_data(analyzer_response_list, sink_config)
logger.info(f"sink_response='{sink_response}'")
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