File size: 1,513 Bytes
cbb225c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 |
from copy import deepcopy
from typing import List, Dict, Optional, Any
from flows.base_flows import AtomicFlow
from flows.utils import logging
from .wikipediaAPI import WikipediaAPIWrapper
log = logging.get_logger(__name__)
class WikiSearchAtomicFlow(AtomicFlow):
REQUIRED_KEYS_CONFIG = ["lang", "top_k_results", "doc_content_chars_max"]
REQUIRED_KEYS_CONSTRUCTOR = []
SUPPORTS_CACHING: bool = True
api_wrapper: WikipediaAPIWrapper
def __init__(self, **kwargs):
super().__init__(**kwargs)
def run(self,
input_data: Dict[str, Any]) -> Dict[str, Any]:
# ~~~ Process input ~~~
term = input_data.get("search_term", None)
api_wrapper = WikipediaAPIWrapper(
lang=self.flow_config["lang"],
top_k_results=self.flow_config["top_k_results"],
doc_content_chars_max=self.flow_config["doc_content_chars_max"]
)
# ~~~ Call ~~~
if page_content := api_wrapper._fetch_page(term):
search_response = {"wiki_content": page_content, "relevant_pages": None}
else:
page_titles = api_wrapper.search_page_titles(term)
search_response = {"wiki_content": None, "relevant_pages": f"Could not find [{term}]. similar: {page_titles}"}
# Log the update to the flow messages list
observation = search_response["wiki_content"] if search_response["wiki_content"] else search_response["relevant_pages"]
return {"wiki_content": observation}
|