added the initial implementation

.env

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+OPENAI_API_KEY=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

.vscode/settings.json

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+{
+	"[python]": {
+		"editor.defaultFormatter": "ms-python.black-formatter"
+	},
+	"python.formatting.provider": "none"
+}

app.py

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+import streamlit as st
+import openai
+import os
+import re
+import ast
+
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+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."
+
+USER_PROMPT_1 = "Are you clear about your role?"
+
+ASSISTANT_PROMPT_1 = "Sure, I'm ready to help you with your NER task. Please provide me with the necessary information to get started."
+GUIDELINES_PROMPT = (
+    "Entity Definition:\n"
+    "1. PERSON: Short name or full name of a person from any geographic regions.\n"
+    "2. DATE: Any format of dates. Dates can also be in natural language.\n"
+    "3. LOC: Name of any geographic location, like cities, countries, continents, districts etc.\n"
+    "\n"
+    "Output Format:\n"
+    "{{'PERSON': [list of entities present], 'DATE': [list of entities present], 'LOC': [list of entities present]}}\n"
+    "If no entities are presented in any categories keep it None\n"
+    "\n"
+    "Examples:\n"
+    "\n"
+    "1. Sentence: Mr. Jacob lives in Madrid since 12th January 2015.\n"
+    "Output: {{'PERSON': ['Mr. Jacob'], 'DATE': ['12th January 2015'], 'LOC': ['Madrid']}}\n"
+    "\n"
+    "2. Sentence: Mr. Rajeev Mishra and Sunita Roy are friends and they meet each other on 24/03/1998.\n"
+    "Output: {{'PERSON': ['Mr. Rajeev Mishra', 'Sunita Roy'], 'DATE': ['24/03/1998'], 'LOC': ['None']}}\n"
+    "\n"
+    "3. Sentence: {}\n"
+    "Output: "
+)
+
+
+COLORED_ENTITY = {"PERSON": "red", "DATE": "blue", "LOC": "green"}
+
+
+def openai_chat_completion_response(final_prompt):
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages=[
+            {"role": "system", "content": SYSTEM_PROMPT},
+            {"role": "user", "content": USER_PROMPT_1},
+            {"role": "assistant", "content": ASSISTANT_PROMPT_1},
+            {"role": "user", "content": final_prompt},
+        ],
+    )
+
+    return response["choices"][0]["message"]["content"].strip(" \n")
+
+
+my_sentence = st.text_input("Your Sentence")
+if st.button("Submit"):
+    GUIDELINES_PROMPT = GUIDELINES_PROMPT.format(my_sentence)
+    ners = openai_chat_completion_response(GUIDELINES_PROMPT)
+    ners_dictionary = ast.literal_eval(ners)
+    for entity_type, entity_list in ners_dictionary.items():
+        entity_list = list(set(entity_list))
+        for ent in entity_list:
+            if ent != "None":
+                my_sentence = re.sub(
+                    ent,
+                    ":"
+                    + COLORED_ENTITY[entity_type]
+                    + "["
+                    + ent
+                    + "\["
+                    + entity_type
+                    + "\]"
+                    + "]",
+                    my_sentence,
+                )
+    st.markdown(my_sentence)

requirements.txt

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+streamlit
+openai