Spaces:
Sleeping
Sleeping
Nikhil0987
commited on
Commit
•
5bfab8c
1
Parent(s):
b16f688
this
Browse files
auth.py
CHANGED
@@ -38,7 +38,7 @@ def login():
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flag = True
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st.experimental_rerun()
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else:
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flag = False
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if flag == False:
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st.error("Invalid username or password")
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st.stop()
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flag = True
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st.experimental_rerun()
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else:
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flag = False
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if flag == False:
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st.error("Invalid username or password")
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st.stop()
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chat.py
CHANGED
@@ -16,7 +16,7 @@ def Chat():
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if ans["scores"][0] > 0.85:
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st.session_state["user"] = "visitor"
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with st.chat_message("assistant"):
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"You are now sleeping in dream"
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st.experimental_rerun()
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else:
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with st.chat_message("assistant"):
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if ans["scores"][0] > 0.85:
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st.session_state["user"] = "visitor"
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with st.chat_message("assistant"):
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"You are now sleeping in dream"
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st.experimental_rerun()
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else:
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with st.chat_message("assistant"):
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convo.py
CHANGED
@@ -11,7 +11,7 @@ def convo():
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# candidate_labels = ["HELP", "PROBLEM SOLVE", "GENERAL TALK"]
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-
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ans = chatbot(conversation)
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# add_user_input = st.button("Add User Input")
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# candidate_labels = ["HELP", "PROBLEM SOLVE", "GENERAL TALK"]
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ans = chatbot(conversation)
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# add_user_input = st.button("Add User Input")
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home.py
CHANGED
@@ -21,7 +21,7 @@ def dashboard():
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"gfjfvjhvjhv"
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elif selected == "Chat":
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Chat()
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elif selected == "Conversation":
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convo()
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elif selected == "Logout":
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st.session_state["user"] = "visitor"
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"gfjfvjhvjhv"
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elif selected == "Chat":
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Chat()
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elif selected == "Conversation":
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convo()
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elif selected == "Logout":
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st.session_state["user"] = "visitor"
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qa.py
ADDED
@@ -0,0 +1,44 @@
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from transformers import pipeline
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import streamlit as st
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# def que():
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# question = st.text_input("ASk me a question")
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# oracle = pipeline(task= "question-answering",model="deepset/roberta-base-squad2")
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# oracle(question="Where do I live?", context="My name is Wolfgang and I live in Berlin")
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def question_answering(question, context):
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"""Answers a question given a context."""
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# Load the question answering model.
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qa_model = pipeline("question-answering")
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# Prepare the inputs for the model.
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inputs = {
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"question": question,
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"context": context,
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}
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# Get the answer from the model.
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output = qa_model(**inputs)
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answer = output["answer_start"]
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# Return the answer.
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return context[answer : answer + output["answer_length"]]
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if __name__ == "__main__":
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# Get the question and context.
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question = "What is the capital of France?"
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context = "The capital of France is Paris."
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# Get the answer.
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answer = question_answering(question, context)
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# Print the answer.
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print(answer)
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