Spaces:
Sleeping
Sleeping
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b86230c
1
Parent(s):
f86b5db
system prompt
Browse files
README.md
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---
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title:
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emoji:
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colorFrom: blue
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sdk: streamlit
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license: mit
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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title: Research Questions
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emoji: 📚
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sdk: streamlit
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license: mit
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---
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A simple app to provide students feedback on their research questions.
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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from langchain.callbacks.base import BaseCallbackHandler
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from langchain.chat_models import ChatOpenAI
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from langchain.schema import HumanMessage
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import streamlit as st
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import os
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class StreamHandler(BaseCallbackHandler):
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def __init__(self, container, initial_text="", display_method='markdown'):
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if check_password():
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query = st.text_input("Input your research question", value="How do biases in AI student evaluations compare to documented biases in human evaluations?")
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ask_button = st.button("ask")
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st.markdown("### GPT-3.5 response")
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chat_box = st.empty()
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stream_handler = StreamHandler(chat_box, display_method='write')
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chat = ChatOpenAI(max_tokens=
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#st.markdown("### together box")
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if query and ask_button:
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response = chat([HumanMessage(content=query)])
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from langchain.callbacks.base import BaseCallbackHandler
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from langchain.chat_models import ChatOpenAI
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from langchain.schema import HumanMessage, SystemMessage
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import streamlit as st
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import os
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# from langchain.prompts.chat import (
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# ChatPromptTemplate,
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# SystemMessagePromptTemplate,
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# HumanMessagePromptTemplate,
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# )
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class StreamHandler(BaseCallbackHandler):
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def __init__(self, container, initial_text="", display_method='markdown'):
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if check_password():
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st.markdown("Get instant feedback on your research question")
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query = st.text_input("Input your research question", value="How do biases in AI student evaluations compare to documented biases in human evaluations?")
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ask_button = st.button("ask")
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st.markdown("### GPT-3.5 response")
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chat_box = st.empty()
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stream_handler = StreamHandler(chat_box, display_method='write')
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chat = ChatOpenAI(max_tokens=5000, streaming=True, callbacks=[stream_handler])
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query_combined = "Please provide constructive feedback in English on this proposed research question, suggesting how it might be improved: <research_question>" + query + "</research_question>."
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#st.markdown("### together box")
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messages = [
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SystemMessage(
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content="""You are a helpful research assistant that provides feedback to university students and researchers on their ideas for a research question, \
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in particular for Masters students planning to write a Master's Thesis. A good research question should be narrow enough that it can be well-addressed in a 20-30 page \
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literature review, and provides guidance to focus the literature review, and points towards specific areas of scientific literature that should be included. A good research question also provides guidance on the methodological (empirical) approach needed to answer the question. """
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),
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HumanMessage(
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content=query_combined
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),
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]
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=
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if query and ask_button:
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response = chat(messages) # [HumanMessage(content=query)])
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