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import os
import pandas as pd
from get_keywords import get_keywords
from get_articles import save_solr_articles_full
from rerank import langchain_rerank_answer, langchain_with_sources, crossencoder_rerank_answer, \
crossencoder_rerank_sentencewise, crossencoder_rerank_sentencewise_articles, no_rerank
#from feed_to_llm import feed_articles_to_gpt_with_links
from feed_to_llm_v2 import feed_articles_to_gpt_with_links
def get_response(question, rerank_type="crossencoder", llm_type="chat"):
try:
csv_path = save_solr_articles_full(question, keyword_type="rake")
reranked_out = crossencoder_rerank_answer(csv_path, question)
# Prepare source metadata for citations
citations = [
{"title": article["title"], "url": article["url"], "source": article["source"]}
for article in reranked_out
]
result = feed_articles_to_gpt_with_links(reranked_out, question, citations)
return result
except Exception as e:
return "", [], [], []
if __name__ == "__main__":
question = "How is United States fighting against tobacco addiction?"
rerank_type = "crossencoder"
llm_type = "chat"
response, links, titles, domains = get_response(question, rerank_type, llm_type)
print(response)
print(links)
print(titles)
print(domains) |