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Runtime error
Runtime error
Update app.py
Browse files
app.py
CHANGED
@@ -4,6 +4,41 @@ import json
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from PIL import Image
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from urllib.parse import quote # Ensure this import is included
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# Set page configuration with a title and favicon
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st.set_page_config(
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page_title="🗺️🛠️ RolePlayAI",
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@@ -28,9 +63,149 @@ with st.expander("Help / About 📚", expanded=False):
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- 🎮 **How to Play:** Start your quest with URL challenges, like `?q=Cyberpunk` or `?query=Dungeons and Dragons`.
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''')
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def get_image_as_base64(url):
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response = requests.get(url)
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if response.status_code == 200:
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@@ -38,22 +213,64 @@ def get_image_as_base64(url):
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return base64.b64encode(response.content).decode("utf-8")
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else:
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return None
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-
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def create_download_link(filename, base64_str):
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href = f'<a href="data:file/png;base64,{base64_str}" download="{filename}">Download Image</a>'
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return href
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-
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-
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-
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with st.sidebar:
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st.markdown("""### 🗺️🛠️ RolePlayAI""")
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-
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st.markdown(download_link, unsafe_allow_html=True)
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else:
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st.sidebar.write("Failed to load the image.")
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# ------------------------------------------------------------- Art Card Sidebar
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@@ -360,44 +577,6 @@ def display_content_or_image(query):
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-
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-
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# Imports
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import base64
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import glob
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import json
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import math
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import openai
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import os
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import pytz
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import re
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import requests
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import streamlit as st
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import textract
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import time
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import zipfile
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import huggingface_hub
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import dotenv
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from audio_recorder_streamlit import audio_recorder
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from bs4 import BeautifulSoup
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from collections import deque
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from datetime import datetime
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from dotenv import load_dotenv
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from huggingface_hub import InferenceClient
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from io import BytesIO
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#from langchain.chat_models import ChatOpenAI
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#from langchain.chains import ConversationalRetrievalChain
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#from langchain.embeddings import OpenAIEmbeddings
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#from langchain.memory import ConversationBufferMemory
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#from langchain.text_splitter import CharacterTextSplitter
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#from langchain.vectorstores import FAISS
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from openai import ChatCompletion
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from PyPDF2 import PdfReader
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from templates import bot_template, css, user_template
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from xml.etree import ElementTree as ET
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import streamlit.components.v1 as components # Import Streamlit Components for HTML5
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def add_Med_Licensing_Exam_Dataset():
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import streamlit as st
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from datasets import load_dataset
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@@ -669,35 +848,6 @@ def truncate_document(document, length):
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def divide_document(document, max_length):
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return [document[i:i+max_length] for i in range(0, len(document), max_length)]
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-
# 9. Sidebar with UI controls to review and re-run prompts and continue responses
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@st.cache_resource
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def get_table_download_link(file_path):
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with open(file_path, 'r') as file:
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data = file.read()
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b64 = base64.b64encode(data.encode()).decode()
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file_name = os.path.basename(file_path)
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ext = os.path.splitext(file_name)[1] # get the file extension
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if ext == '.txt':
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mime_type = 'text/plain'
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elif ext == '.py':
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mime_type = 'text/plain'
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elif ext == '.xlsx':
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mime_type = 'text/plain'
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elif ext == '.csv':
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mime_type = 'text/plain'
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elif ext == '.htm':
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mime_type = 'text/html'
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elif ext == '.md':
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mime_type = 'text/markdown'
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elif ext == '.wav':
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mime_type = 'audio/wav'
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else:
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mime_type = 'application/octet-stream' # general binary data type
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href = f'<a href="data:{mime_type};base64,{b64}" target="_blank" download="{file_name}">{file_name}</a>'
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return href
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def CompressXML(xml_text):
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root = ET.fromstring(xml_text)
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for elem in list(root.iter()):
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filename = generate_filename(user_prompt, choice)
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create_file(filename, user_prompt, response, should_save)
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# Compose a file sidebar of markdown md files:
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all_files = glob.glob("*.md")
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all_files = [file for file in all_files if len(os.path.splitext(file)[0]) >= 10] # exclude files with short names
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all_files.sort(key=lambda x: (os.path.splitext(x)[1], x), reverse=True) # sort by file type and file name in descending order
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if st.sidebar.button("🗑 Delete All Text"):
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for file in all_files:
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os.remove(file)
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st.experimental_rerun()
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if st.sidebar.button("⬇️ Download All"):
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zip_file = create_zip_of_files(all_files)
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st.sidebar.markdown(get_zip_download_link(zip_file), unsafe_allow_html=True)
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file_contents=''
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next_action=''
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for file in all_files:
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col1, col2, col3, col4, col5 = st.sidebar.columns([1,6,1,1,1]) # adjust the ratio as needed
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with col1:
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if st.button("🌐", key="md_"+file): # md emoji button
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with open(file, 'r') as f:
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file_contents = f.read()
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next_action='md'
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with col2:
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st.markdown(get_table_download_link(file), unsafe_allow_html=True)
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with col3:
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if st.button("📂", key="open_"+file): # open emoji button
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with open(file, 'r') as f:
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file_contents = f.read()
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next_action='open'
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with col4:
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if st.button("🔍", key="read_"+file): # search emoji button
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with open(file, 'r') as f:
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file_contents = f.read()
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next_action='search'
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with col5:
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if st.button("🗑", key="delete_"+file):
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os.remove(file)
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st.experimental_rerun()
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if len(file_contents) > 0:
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if next_action=='open':
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file_content_area = st.text_area("File Contents:", file_contents, height=500)
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if next_action=='md':
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st.markdown(file_contents)
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buttonlabel = '🔍Run with Llama and GPT.'
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if st.button(key='RunWithLlamaandGPT', label = buttonlabel):
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user_prompt = file_contents
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# Llama versus GPT Battle!
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all=""
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try:
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st.write('🔍Running with Llama.')
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response = StreamLLMChatResponse(file_contents)
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filename = generate_filename(user_prompt, "md")
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create_file(filename, file_contents, response, should_save)
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all=response
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#SpeechSynthesis(response)
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except:
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st.markdown('Llama is sleeping. Restart ETA 30 seconds.')
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# gpt
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try:
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st.write('🔍Running with GPT.')
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response2 = chat_with_model(user_prompt, file_contents, model_choice)
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filename2 = generate_filename(file_contents, choice)
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create_file(filename2, user_prompt, response, should_save)
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all=all+response2
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#SpeechSynthesis(response2)
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except:
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st.markdown('GPT is sleeping. Restart ETA 30 seconds.')
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SpeechSynthesis(all)
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if next_action=='search':
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file_content_area = st.text_area("File Contents:", file_contents, height=500)
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st.write('🔍Running with Llama and GPT.')
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user_prompt = file_contents
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# Llama versus GPT Battle!
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all=""
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try:
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st.write('🔍Running with Llama.')
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response = StreamLLMChatResponse(file_contents)
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filename = generate_filename(user_prompt, ".md")
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create_file(filename, file_contents, response, should_save)
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all=response
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#SpeechSynthesis(response)
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except:
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st.markdown('Llama is sleeping. Restart ETA 30 seconds.')
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# gpt
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try:
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st.write('🔍Running with GPT.')
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response2 = chat_with_model(user_prompt, file_contents, model_choice)
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filename2 = generate_filename(file_contents, choice)
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create_file(filename2, user_prompt, response, should_save)
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all=all+response2
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#SpeechSynthesis(response2)
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except:
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st.markdown('GPT is sleeping. Restart ETA 30 seconds.')
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SpeechSynthesis(all)
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# Function to encode file to base64
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def get_base64_encoded_file(file_path):
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with open(file_path, "rb") as file:
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from PIL import Image
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from urllib.parse import quote # Ensure this import is included
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# Imports
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import base64
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import glob
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import json
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import math
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import openai
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import os
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import pytz
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import re
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import requests
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import streamlit as st
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import textract
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import time
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import zipfile
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import huggingface_hub
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import dotenv
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from audio_recorder_streamlit import audio_recorder
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from bs4 import BeautifulSoup
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from collections import deque
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from datetime import datetime
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from dotenv import load_dotenv
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from huggingface_hub import InferenceClient
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from io import BytesIO
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from openai import ChatCompletion
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from PyPDF2 import PdfReader
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from templates import bot_template, css, user_template
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from xml.etree import ElementTree as ET
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import streamlit.components.v1 as components # Import Streamlit Components for HTML5
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# Set page configuration with a title and favicon
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st.set_page_config(
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page_title="🗺️🛠️ RolePlayAI",
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- 🎮 **How to Play:** Start your quest with URL challenges, like `?q=Cyberpunk` or `?query=Dungeons and Dragons`.
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''')
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# 9. Sidebar with UI controls to review and re-run prompts and continue responses
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@st.cache_resource
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def get_table_download_link(file_path):
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with open(file_path, 'r') as file:
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data = file.read()
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b64 = base64.b64encode(data.encode()).decode()
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file_name = os.path.basename(file_path)
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ext = os.path.splitext(file_name)[1] # get the file extension
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if ext == '.txt':
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mime_type = 'text/plain'
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elif ext == '.py':
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mime_type = 'text/plain'
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elif ext == '.xlsx':
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mime_type = 'text/plain'
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elif ext == '.csv':
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mime_type = 'text/plain'
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elif ext == '.htm':
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mime_type = 'text/html'
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elif ext == '.md':
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mime_type = 'text/markdown'
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elif ext == '.wav':
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mime_type = 'audio/wav'
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else:
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mime_type = 'application/octet-stream' # general binary data type
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href = f'<a href="data:{mime_type};base64,{b64}" target="_blank" download="{file_name}">{file_name}</a>'
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return href
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def FileSidebar():
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# ----------------------------------------------------- File Sidebar for Jump Gates ------------------------------------------
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# Compose a file sidebar of markdown md files:
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all_files = glob.glob("*.md")
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all_files = [file for file in all_files if len(os.path.splitext(file)[0]) >= 10] # exclude files with short names
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all_files.sort(key=lambda x: (os.path.splitext(x)[1], x), reverse=True) # sort by file type and file name in descending order
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if st.sidebar.button("🗑 Delete All Text"):
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for file in all_files:
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os.remove(file)
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st.experimental_rerun()
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if st.sidebar.button("⬇️ Download All"):
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zip_file = create_zip_of_files(all_files)
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st.sidebar.markdown(get_zip_download_link(zip_file), unsafe_allow_html=True)
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file_contents=''
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next_action=''
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for file in all_files:
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col1, col2, col3, col4, col5 = st.sidebar.columns([1,6,1,1,1]) # adjust the ratio as needed
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with col1:
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if st.button("🌐", key="md_"+file): # md emoji button
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with open(file, 'r') as f:
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file_contents = f.read()
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next_action='md'
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with col2:
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st.markdown(get_table_download_link(file), unsafe_allow_html=True)
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with col3:
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if st.button("📂", key="open_"+file): # open emoji button
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with open(file, 'r') as f:
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file_contents = f.read()
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next_action='open'
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125 |
+
with col4:
|
126 |
+
if st.button("🔍", key="read_"+file): # search emoji button
|
127 |
+
with open(file, 'r') as f:
|
128 |
+
file_contents = f.read()
|
129 |
+
next_action='search'
|
130 |
+
with col5:
|
131 |
+
if st.button("🗑", key="delete_"+file):
|
132 |
+
os.remove(file)
|
133 |
+
st.experimental_rerun()
|
134 |
+
|
135 |
+
|
136 |
+
if len(file_contents) > 0:
|
137 |
+
if next_action=='open':
|
138 |
+
file_content_area = st.text_area("File Contents:", file_contents, height=500)
|
139 |
+
if next_action=='md':
|
140 |
+
st.markdown(file_contents)
|
141 |
+
|
142 |
+
buttonlabel = '🔍Run with Llama and GPT.'
|
143 |
+
if st.button(key='RunWithLlamaandGPT', label = buttonlabel):
|
144 |
+
user_prompt = file_contents
|
145 |
+
|
146 |
+
# Llama versus GPT Battle!
|
147 |
+
all=""
|
148 |
+
try:
|
149 |
+
st.write('🔍Running with Llama.')
|
150 |
+
response = StreamLLMChatResponse(file_contents)
|
151 |
+
filename = generate_filename(user_prompt, "md")
|
152 |
+
create_file(filename, file_contents, response, should_save)
|
153 |
+
all=response
|
154 |
+
#SpeechSynthesis(response)
|
155 |
+
except:
|
156 |
+
st.markdown('Llama is sleeping. Restart ETA 30 seconds.')
|
157 |
+
|
158 |
+
# gpt
|
159 |
+
try:
|
160 |
+
st.write('🔍Running with GPT.')
|
161 |
+
response2 = chat_with_model(user_prompt, file_contents, model_choice)
|
162 |
+
filename2 = generate_filename(file_contents, choice)
|
163 |
+
create_file(filename2, user_prompt, response, should_save)
|
164 |
+
all=all+response2
|
165 |
+
#SpeechSynthesis(response2)
|
166 |
+
except:
|
167 |
+
st.markdown('GPT is sleeping. Restart ETA 30 seconds.')
|
168 |
+
|
169 |
+
SpeechSynthesis(all)
|
170 |
+
|
171 |
+
|
172 |
+
if next_action=='search':
|
173 |
+
file_content_area = st.text_area("File Contents:", file_contents, height=500)
|
174 |
+
st.write('🔍Running with Llama and GPT.')
|
175 |
+
|
176 |
+
user_prompt = file_contents
|
177 |
+
|
178 |
+
# Llama versus GPT Battle!
|
179 |
+
all=""
|
180 |
+
try:
|
181 |
+
st.write('🔍Running with Llama.')
|
182 |
+
response = StreamLLMChatResponse(file_contents)
|
183 |
+
filename = generate_filename(user_prompt, ".md")
|
184 |
+
create_file(filename, file_contents, response, should_save)
|
185 |
+
all=response
|
186 |
+
#SpeechSynthesis(response)
|
187 |
+
except:
|
188 |
+
st.markdown('Llama is sleeping. Restart ETA 30 seconds.')
|
189 |
+
|
190 |
+
# gpt
|
191 |
+
try:
|
192 |
+
st.write('🔍Running with GPT.')
|
193 |
+
response2 = chat_with_model(user_prompt, file_contents, model_choice)
|
194 |
+
filename2 = generate_filename(file_contents, choice)
|
195 |
+
create_file(filename2, user_prompt, response, should_save)
|
196 |
+
all=all+response2
|
197 |
+
#SpeechSynthesis(response2)
|
198 |
+
except:
|
199 |
+
st.markdown('GPT is sleeping. Restart ETA 30 seconds.')
|
200 |
+
|
201 |
+
SpeechSynthesis(all)
|
202 |
+
|
203 |
+
FileSidebar()
|
204 |
+
# ----------------------------------------------------- File Sidebar for Jump Gates ------------------------------------------
|
205 |
+
|
206 |
+
|
207 |
+
# ---- Art Card Sidebar with Random Selection of image------------------------------
|
208 |
+
|
209 |
def get_image_as_base64(url):
|
210 |
response = requests.get(url)
|
211 |
if response.status_code == 200:
|
|
|
213 |
return base64.b64encode(response.content).decode("utf-8")
|
214 |
else:
|
215 |
return None
|
216 |
+
|
217 |
def create_download_link(filename, base64_str):
|
218 |
href = f'<a href="data:file/png;base64,{base64_str}" download="{filename}">Download Image</a>'
|
219 |
return href
|
220 |
|
221 |
+
# List of image URLs
|
222 |
+
image_urls = [
|
223 |
+
"https://cdn-uploads.huggingface.co/production/uploads/620630b603825909dcbeba35/o1FI3G_BueAAanLBeqoo3.png",
|
224 |
+
# "https://cdn-uploads.huggingface.co/production/uploads/620630b603825909dcbeba35/gv1xmIiXh1NGTeeV-cYF2.png",
|
225 |
+
# "https://cdn-uploads.huggingface.co/production/uploads/620630b603825909dcbeba35/2YsnDyc_nDNW71PPKozdN.png",
|
226 |
+
# "https://cdn-uploads.huggingface.co/production/uploads/620630b603825909dcbeba35/G_GkRD_IT3f14K7gWlbwi.png"
|
227 |
+
]
|
228 |
|
229 |
+
# Select a random URL from the list
|
230 |
+
selected_image_url = random.choice(image_urls)
|
231 |
+
|
232 |
+
# Get the base64 encoded string of the selected image
|
233 |
+
selected_image_base64 = get_image_as_base64(selected_image_url)
|
234 |
+
|
235 |
+
if selected_image_base64 is not None:
|
236 |
with st.sidebar:
|
237 |
st.markdown("""### 🗺️🛠️ RolePlayAI""")
|
238 |
+
# Display the image
|
239 |
+
st.markdown(f"")
|
240 |
+
|
241 |
+
# Create and display the download link
|
242 |
+
download_link = create_download_link("downloaded_image.png", selected_image_base64)
|
243 |
st.markdown(download_link, unsafe_allow_html=True)
|
244 |
else:
|
245 |
st.sidebar.write("Failed to load the image.")
|
246 |
+
|
247 |
+
# ---- Art Card Sidebar with random selection of image. -------------------------------
|
248 |
+
|
249 |
+
|
250 |
+
|
251 |
+
#def get_image_as_base64(url):
|
252 |
+
# response = requests.get(url)
|
253 |
+
# if response.status_code == 200:
|
254 |
+
# Convert the image to base64
|
255 |
+
# return base64.b64encode(response.content).decode("utf-8")
|
256 |
+
# else:
|
257 |
+
# return None
|
258 |
+
|
259 |
+
#def create_download_link(filename, base64_str):
|
260 |
+
# href = f'<a href="data:file/png;base64,{base64_str}" download="{filename}">Download Image</a>'
|
261 |
+
# return href
|
262 |
+
|
263 |
+
#image_url = "https://cdn-uploads.huggingface.co/production/uploads/620630b603825909dcbeba35/o1FI3G_BueAAanLBeqoo3.png"
|
264 |
+
|
265 |
+
#image_base64 = get_image_as_base64(image_url)
|
266 |
+
#if image_base64 is not None:
|
267 |
+
# with st.sidebar:
|
268 |
+
# st.markdown("""### 🗺️🛠️ RolePlayAI""")
|
269 |
+
# st.markdown(f"")
|
270 |
+
# download_link = create_download_link("downloaded_image.png", image_base64)
|
271 |
+
# st.markdown(download_link, unsafe_allow_html=True)
|
272 |
+
#else:
|
273 |
+
# st.sidebar.write("Failed to load the image.")
|
274 |
# ------------------------------------------------------------- Art Card Sidebar
|
275 |
|
276 |
|
|
|
577 |
|
578 |
|
579 |
|
|
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|
|
|
580 |
def add_Med_Licensing_Exam_Dataset():
|
581 |
import streamlit as st
|
582 |
from datasets import load_dataset
|
|
|
848 |
def divide_document(document, max_length):
|
849 |
return [document[i:i+max_length] for i in range(0, len(document), max_length)]
|
850 |
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
851 |
def CompressXML(xml_text):
|
852 |
root = ET.fromstring(xml_text)
|
853 |
for elem in list(root.iter()):
|
|
|
1264 |
filename = generate_filename(user_prompt, choice)
|
1265 |
create_file(filename, user_prompt, response, should_save)
|
1266 |
|
|
|
|
|
|
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|
1267 |
# Function to encode file to base64
|
1268 |
def get_base64_encoded_file(file_path):
|
1269 |
with open(file_path, "rb") as file:
|