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Update app.py
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app.py
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import gradio as gr
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import pandas as pd
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from functools import partial
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# history is a list of list
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# [[user_input_str, bot_response_str], ...]
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class EchoingTutor:
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# create basic initialization function
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def __init__(self):
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self.conversation_memory = []
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self.flattened_conversation = ''
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def add_user_message(self, user_message):
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self.conversation_memory.append([user_message, None])
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self.flattened_conversation = self.flattened_conversation + '\n\n' + 'User: ' + user_message
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def get_conversation_history(chat_tutor):
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return chat_tutor.conversation_memory, chat_tutor
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css="""
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#sources-container {
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overflow: scroll !important; /* Needs to override default formatting */
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/*max-height: 20em; */ /* Arbitrary value */
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}
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#sources-container > div { padding-bottom: 1em !important; /* Arbitrary value */ }
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.short-height > * > * { min-height: 0 !important; }
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.translucent { opacity: 0.5; }
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.textbox_label { padding-bottom: .5em; }
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"""
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with gr.Blocks(css=css) as demo:
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#initialize tutor (with state)
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study_tutor = gr.State(EchoingTutor())
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#
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with gr.Box():
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gr.Markdown("### OpenAI API Key ")
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gr.HTML("""<span>Embed your OpenAI API key below; if you haven't created one already, visit
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<a href="https://platform.openai.com/account/api-keys">platform.openai.com/account/api-keys</a>
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to sign up for an account and get your personal API key</span>""",
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elem_classes="textbox_label")
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api_input = gr.Textbox(show_label=False, type="password", container=False, autofocus=True,
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placeholder="βββββββββββββββββ", value='')
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api_input.submit(fn=embed_key, inputs=[api_input, study_tutor], outputs=study_tutor)
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api_input.blur(fn=embed_key, inputs=[api_input, study_tutor], outputs=study_tutor)
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# Chatbot interface
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gr.Markdown("""
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## Chat with the Model
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import os
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import gradio as gr
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import pandas as pd
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from functools import partial
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# history is a list of list
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# [[user_input_str, bot_response_str], ...]
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class EchoingTutor(SlightlyDelusionalTutor):
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def add_user_message(self, user_message):
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self.conversation_memory.append([user_message, None])
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self.flattened_conversation = self.flattened_conversation + '\n\n' + 'User: ' + user_message
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def get_conversation_history(chat_tutor):
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return chat_tutor.conversation_memory, chat_tutor
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with gr.Blocks() as demo:
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#initialize tutor (with state)
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study_tutor = gr.State(EchoingTutor())
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# API Authentication
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# Instead of ask students to provide key, the key is now directly provided by the instructor
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embed_key(os.environ.get("OPENAI_API_KEY"), study_tutor)
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# Chatbot interface
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gr.Markdown("""
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## Chat with the Model
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