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Update app.py
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app.py
CHANGED
@@ -1,6 +1,7 @@
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import streamlit as st
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from annotated_text import annotated_text
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from refined.inference.processor import Refined
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# Sidebar
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st.sidebar.image("logo-wordlift.png")
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@@ -29,6 +30,14 @@ def get_wikidata_id(entity_string):
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entity_link = "https://www.wikidata.org/wiki/" + entity_id
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return {"id": entity_id, "link": entity_link}
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# Create the form
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with st.form(key='my_form'):
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text_input = st.text_area(label='Enter a sentence')
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@@ -39,17 +48,16 @@ if text_input:
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entities = refined_model.process_text(text_input)
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entities_map = {}
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-
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for entity in entities:
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single_entity_list = str(entity).strip('][').replace("\'", "").split(', ')
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if len(single_entity_list) >= 2 and "wikidata" in single_entity_list[1]:
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entities_map[single_entity_list[0].strip()] = get_wikidata_id(single_entity_list[1])
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combined_entity_info_dictionary = dict([(k, [entities_map[k],
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def get_entity_description(entity_string, combined_entity_info_dictionary):
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return combined_entity_info_dictionary[entity_string][1]
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if submit_button:
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# Prepare a list to hold the final output
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@@ -57,13 +65,26 @@ if text_input:
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# Replace each entity in the text with its annotated version
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for entity_string, entity_info in entities_map.items():
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-
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text_input = text_input.replace(entity_string, f'{{{str(entity_annotation)}}}', 1)
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# Split the modified text_input into a list
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text_list = text_input.split("{")
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-
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for item in text_list:
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if "}" in item:
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item_list = item.split("}")
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import streamlit as st
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from annotated_text import annotated_text
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from refined.inference.processor import Refined
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import requests
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# Sidebar
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st.sidebar.image("logo-wordlift.png")
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entity_link = "https://www.wikidata.org/wiki/" + entity_id
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return {"id": entity_id, "link": entity_link}
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def get_entity_data(entity_link):
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try:
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response = requests.get(f'https://api.wordlift.io/id/{entity_link}')
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return response.json()
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except Exception as e:
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print(f"Exception when fetching data for entity: {entity_link}. Exception: {e}")
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return None
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# Create the form
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with st.form(key='my_form'):
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text_input = st.text_area(label='Enter a sentence')
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entities = refined_model.process_text(text_input)
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entities_map = {}
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entities_data = {}
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for entity in entities:
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single_entity_list = str(entity).strip('][').replace("\'", "").split(', ')
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if len(single_entity_list) >= 2 and "wikidata" in single_entity_list[1]:
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entities_map[single_entity_list[0].strip()] = get_wikidata_id(single_entity_list[1])
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entity_data = get_entity_data(entities_map[single_entity_list[0].strip()]["link"])
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if entity_data is not None:
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entities_data[single_entity_list[0].strip()] = entity_data
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combined_entity_info_dictionary = dict([(k, [entities_map[k], entities_data[k] if k in entities_data else None]) for k in entities_map])
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if submit_button:
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# Prepare a list to hold the final output
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# Replace each entity in the text with its annotated version
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for entity_string, entity_info in entities_map.items():
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entity_data = entities_data.get(entity_string, None)
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entity_type = None
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if entity_data is not None:
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entity_type = entity_data.get("@type", None)
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# Use different colors based on the entity's type
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color = "#8ef" # Default color
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if entity_type == "Place":
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color = "#f00"
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elif entity_type == "Organization":
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color = "#0f0"
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elif entity_type == "Person":
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color = "#00f"
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entity_annotation = (entity_string, entity_info["id"], color)
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text_input = text_input.replace(entity_string, f'{{{str(entity_annotation)}}}', 1)
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# Split the modified text_input into a list
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text_list = text_input.split("{")
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for item in text_list:
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if "}" in item:
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item_list = item.split("}")
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