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Runtime error
Update app.py
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app.py
CHANGED
@@ -11,10 +11,60 @@ from datetime import datetime
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from openai import ChatCompletion
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from xml.etree import ElementTree as ET
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from bs4 import BeautifulSoup
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openai.api_key = os.getenv('OPENAI_KEY')
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st.set_page_config(page_title='Streamlit
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def chat_with_model(prompts):
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model = "gpt-3.5-turbo"
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#model = "gpt-4-32k" # 32k tokens between prompt and inference tokens
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@@ -92,7 +142,6 @@ def read_file_content(file):
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return ""
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def main():
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st.title("Chat with AI")
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prompts = ['']
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file_content = ""
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from openai import ChatCompletion
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from xml.etree import ElementTree as ET
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from bs4 import BeautifulSoup
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from streamlit.theme import Theme
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openai.api_key = os.getenv('OPENAI_KEY')
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#st.set_page_config(page_title='GPT Streamlit Document Reasoner', layout='wide')
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st.set_page_config(
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page_title="GPT Streamlit Document Reasoner",
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layout="wide",
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theme=Theme(
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primary_color="#F63366",
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secondary_background_color="#F0F2F6",
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text_color="#262730",
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font="sans serif",
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),
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)
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st.title("Chat with AI")
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# Create a sidebar with menus
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st.sidebar.title("Menu")
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menu = ["Option 1", "Option 2", "Option 3"]
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choice = st.sidebar.selectbox("Choose an option", menu)
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if choice == "Option 1":
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st.sidebar.write("You selected Option 1")
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elif choice == "Option 2":
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st.sidebar.write("You selected Option 2")
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elif choice == "Option 3":
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st.sidebar.write("You selected Option 3")
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# Create a slider in the sidebar
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max_length = st.sidebar.slider(
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"Max document length", min_value=3000, max_value=24000, value=3000, step=1000
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)
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# Truncate document
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def truncate_document(document, length):
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return document[:length]
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# Assume you have a document called my_document
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# my_document = 'your long string here'
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# truncated_document = truncate_document(my_document, max_length)
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# st.write(f"Truncated document: {truncated_document}")
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# Create two tabs
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tab = st.selectbox("Choose a tab", ["Tab 1", "Tab 2"])
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if tab == "Tab 1":
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st.header("Tab 1")
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st.write("This is some information for Tab 1")
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elif tab == "Tab 2":
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st.header("Tab 2")
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st.write("This is some information for Tab 2")
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def chat_with_model(prompts):
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model = "gpt-3.5-turbo"
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#model = "gpt-4-32k" # 32k tokens between prompt and inference tokens
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return ""
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def main():
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prompts = ['']
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file_content = ""
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