chandralegend
commited on
Commit
•
31bcbcd
1
Parent(s):
9564722
table added for guidlines
Browse files
app.py
CHANGED
@@ -4,37 +4,79 @@ import os
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import re
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import ast
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openai.api_key = os.getenv("OPENAI_API_KEY")
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SYSTEM_PROMPT = "You are a smart and intelligent Named Entity Recognition (NER) system. I will provide you the definition of the entities you need to extract, the sentence from where your extract the entities and the output format with examples."
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USER_PROMPT_1 = "Are you clear about your role?"
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ASSISTANT_PROMPT_1 = "Sure, I'm ready to help you with your NER task. Please provide me with the necessary information to get started."
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GUIDELINES_PROMPT = (
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"Entity Definition:\n"
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"1. PERSON: Short name or full name of a person from any geographic regions.\n"
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"2. DATE: Any format of dates. Dates can also be in natural language.\n"
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"3. LOC: Name of any geographic location, like cities, countries, continents, districts etc.\n"
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"\n"
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"Output Format:\n"
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"{{'PERSON': [list of entities present], 'DATE': [list of entities present], 'LOC': [list of entities present]}}\n"
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"If no entities are presented in any categories keep it None\n"
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"\n"
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"Examples:\n"
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"\n"
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"1. Sentence: Mr. Jacob lives in Madrid since 12th January 2015.\n"
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"Output: {{'PERSON': ['Mr. Jacob'], 'DATE': ['12th January 2015'], 'LOC': ['Madrid']}}\n"
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"\n"
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"2. Sentence: Mr. Rajeev Mishra and Sunita Roy are friends and they meet each other on 24/03/1998.\n"
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"Output: {{'PERSON': ['Mr. Rajeev Mishra', 'Sunita Roy'], 'DATE': ['24/03/1998'], 'LOC': ['None']}}\n"
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"\n"
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"3. Sentence: {}\n"
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"Output: "
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)
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COLORED_ENTITY = {"PERSON": "red", "DATE": "blue", "LOC": "green"}
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def openai_chat_completion_response(final_prompt):
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@@ -54,22 +96,17 @@ def openai_chat_completion_response(final_prompt):
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my_sentence = st.text_input("Your Sentence")
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if st.button("Submit"):
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GUIDELINES_PROMPT = GUIDELINES_PROMPT.format(my_sentence)
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ners = openai_chat_completion_response(GUIDELINES_PROMPT)
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ners_dictionary = ast.literal_eval(ners)
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for entity_type, entity_list in ners_dictionary.items():
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entity_list = list(set(entity_list))
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for ent in entity_list:
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if ent != "None":
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my_sentence = re.sub(
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ent,
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":"
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+ COLORED_ENTITY[entity_type]
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+ "["
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+ ent
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+ "\["
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+ entity_type
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+ "\]"
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+ "]",
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my_sentence,
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)
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st.markdown(my_sentence)
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import re
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import ast
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st.title("Named Entity Recognition (NER) with GPT-3")
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if "guidelines" not in st.session_state:
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st.session_state["guidelines"] = [
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{
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"entity": "PERSON",
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"definition": "Short name or full name of a person from any geographic regions.",
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"color": "red",
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},
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{
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"entity": "DATE",
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"definition": "Any format of dates. Dates can also be in natural language.",
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"color": "green",
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},
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{
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"entity": "LOC",
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"definition": "Name of any geographic location, like cities, countries, continents, districts etc.",
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"color": "blue",
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},
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]
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st.header("Guidelines")
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# display guidelines in a table
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st.table(st.session_state["guidelines"])
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st.write("You can add new guidelines here.")
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new_entity = st.text_input("Entity")
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new_definition = st.text_input("Definition")
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color = st.color_picker("Pick a color", "#00f900")
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if st.button("Add Guideline"):
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st.session_state["guidelines"].append(
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{"entity": new_entity, "definition": new_definition, "color": color}
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)
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new_entity = ""
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new_definition = ""
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examples = [
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{
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"sentence": "Mr. Jacob lives in Madrid since 12th January 2015.",
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"output": "{{'PERSON': ['Mr. Jacob'], 'DATE': ['12th January 2015'], 'LOC': ['Madrid']}}",
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},
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{
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"sentence": "Mr. Rajeev Mishra and Sunita Roy are friends and they meet each other on 24/03/1998.",
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"output": "{{'PERSON': ['Mr. Rajeev Mishra', 'Sunita Roy'], 'DATE': ['24/03/1998'], 'LOC': ['None']}}",
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},
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]
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def generate_guidelines_prompt(guidelines):
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guidelines_prompt = "Entity Definition:\n"
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for guideline in guidelines:
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guidelines_prompt += f"{guideline['entity']}: {guideline['definition']}\n"
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guidelines_prompt += "\nOutput Format:\n"
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guidelines_prompt += "{{'PERSON': [list of entities present], 'DATE': [list of entities present], 'LOC': [list of entities present]}}\n"
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guidelines_prompt += "If no entities are presented in any categories keep it None\n"
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guidelines_prompt += "\nExamples:\n\n"
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for i, example in enumerate(examples):
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guidelines_prompt += f"{i+1}. Sentence: {example['sentence']}\n"
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guidelines_prompt += f"Output: {example['output']}\n\n"
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guidelines_prompt += str(len(examples) + 1) + ". Sentence: {}\n"
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guidelines_prompt += "Output: "
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return guidelines_prompt
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openai.api_key = os.getenv("OPENAI_API_KEY")
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SYSTEM_PROMPT = "You are a smart and intelligent Named Entity Recognition (NER) system. I will provide you the definition of the entities you need to extract, the sentence from where your extract the entities and the output format with examples."
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USER_PROMPT_1 = "Are you clear about your role?"
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ASSISTANT_PROMPT_1 = "Sure, I'm ready to help you with your NER task. Please provide me with the necessary information to get started."
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GUIDELINES_PROMPT = generate_guidelines_prompt(st.session_state["guidelines"])
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def openai_chat_completion_response(final_prompt):
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my_sentence = st.text_input("Your Sentence")
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if st.button("Submit"):
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GUIDELINES_PROMPT = GUIDELINES_PROMPT.format(my_sentence)
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print(GUIDELINES_PROMPT)
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ners = openai_chat_completion_response(GUIDELINES_PROMPT)
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ners_dictionary = ast.literal_eval(ners)
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for entity_type, entity_list in ners_dictionary.items():
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entity_list = list(set(entity_list))
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color = st.session_state["guidelines"][entity_type]["color"]
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for ent in entity_list:
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if ent != "None":
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my_sentence = re.sub(
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ent,
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":" + color + "[" + ent + "\[" + entity_type + "\]" + "]",
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my_sentence,
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)
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st.markdown(my_sentence)
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