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‎AppV4/htmlTemplates.py

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css = '''
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<style>
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.chat-message {
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padding: 1.5rem; border-radius: 0.5rem; margin-bottom: 1rem; display: flex
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}
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.chat-message.user {
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background-color: #2b313e
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}
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.chat-message.bot {
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background-color: #475063
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}
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.chat-message .avatar {
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width: 12%;
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}
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.chat-message .avatar img {
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max-width: 60px;
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max-height: 60px;
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border-radius: 50%;
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object-fit: cover;
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}
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.chat-message .message {
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width: 90%;
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padding: 0 .35rem;
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color: #fff;
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}
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'''
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bot_template = '''
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<div class="chat-message bot">
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<div class="avatar">
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<img src="https://www.sideshow.com/storage/product-images/2171/c-3po_star-wars_square.jpg">
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</div>
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<div class="message">{{MSG}}</div>
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</div>
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'''
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user_template = '''
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<div class="chat-message user">
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<div class="avatar">
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<img src="https://resizing.flixster.com/ocuc8yjm8Fu5UK5Ze8lbdp58m9Y=/300x300/v2/https://flxt.tmsimg.com/assets/p11759522_i_h9_aa.jpg">
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</div>
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<div class="message">{{MSG}}</div>
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</div>
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'''

‎AppV4/main.py

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import os
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from PIL import Image
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from dotenv import load_dotenv
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from PyPDF2 import PdfReader
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import streamlit as st
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import openai
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from langchain.text_splitter import CharacterTextSplitter
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from langchain.llms import OpenAI
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from langchain.memory import ConversationBufferMemory
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from langchain.chains import LLMChain
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from langchain.prompts import PromptTemplate
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from langchain.embeddings import OpenAIEmbeddings
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from langchain.vectorstores import FAISS
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from langchain.chains import RetrievalQA
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from langchain.chains import ConversationalRetrievalChain
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from htmlTemplates import css, bot_template, user_template
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from prompts import CHAT_TEMPLATE, INITIAL_TEMPLATE
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from prompts import CORRECTION_CONTEXT, COMPLETION_CONTEXT, OPTIMIZATION_CONTEXT, GENERAL_ASSISTANT_CONTEXT, GENERATION_CONTEXT, COMMENTING_CONTEXT, EXPLANATION_CONTEXT
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def page_config():
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st.set_page_config(page_title="GPT-4 Coding Asssistant", page_icon="computer")
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st.write(css, unsafe_allow_html=True)
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def init_ses_states():
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st.session_state.setdefault('chat_history', [])
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st.session_state.setdefault('initial_input', "")
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def page_title_header():
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top_image = Image.open('trippyPattern.png')
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st.image(top_image)
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st.title("GPT-4 Coding Assistant")
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st.caption("Powered by OpenAI, LangChain, Streamlit")
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def sidebar():
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global language, scenario, temperature, scenario_context
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languages = ['Python', 'GoLang', 'JavaScript', 'Java', 'C', 'C++', 'C#']
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scenarios = ['General Assistant', 'Code Correction', 'Code Completion', 'Code Commenting', 'Code Optimization', 'Code Generation', 'Code Explanation']
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scenario_context_map = {
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"Code Correction": CORRECTION_CONTEXT,
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"Code Completion": COMPLETION_CONTEXT,
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"Code Optimization": OPTIMIZATION_CONTEXT,
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"General Assistant": GENERAL_ASSISTANT_CONTEXT,
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"Code Generation": GENERATION_CONTEXT,
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"Code Commenting": COMMENTING_CONTEXT,
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"Code Explanation": EXPLANATION_CONTEXT
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}
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with st.sidebar:
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with st.expander(label="Settings", expanded=True):
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language = st.selectbox(label="Language", options=languages, index=0)
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scenario = st.selectbox(label="Scenario", options=scenarios, index=0)
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scenario_context = scenario_context_map.get(scenario, "")
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temperature = st.slider(label="Temperature", min_value=0.0, max_value=1.0, value=0.5)
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def display_convo():
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with st.container():
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for i, message in enumerate(reversed(st.session_state.chat_history)):
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if i % 2 == 0:
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st.markdown(bot_template.replace("{{MSG}}", message), unsafe_allow_html=True)
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else:
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st.markdown(user_template.replace("{{MSG}}", message), unsafe_allow_html=True)
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def handle_initial_submit():
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initial_template = PromptTemplate(
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input_variables=['input','language','scenario','scenario_context'],
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template= INITIAL_TEMPLATE
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)
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initial_llm_chain = create_llm_chain(prompt_template=initial_template)
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initial_input = st.text_area(label=f"User Input", height=300)
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if (st.button(f'Submit Initial Input') and initial_input):
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st.session_state.initial_input = initial_input
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st.session_state['chat_history'] = []
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with st.spinner('Generating Response...'):
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initial_response = initial_llm_chain.run(input=initial_input,
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language=language,
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scenario=scenario,
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scenario_context=scenario_context)
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st.session_state.chat_history.append(initial_response)
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def handle_user_message():
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chat_template = PromptTemplate(
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input_variables=['input','user_message','language','scenario','chat_history'],
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template=CHAT_TEMPLATE
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)
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chat_llm_chain = create_llm_chain(prompt_template=chat_template)
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if st.session_state.chat_history:
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user_message = st.text_input("Further Questions for Coding AI?", key="user_input")
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if st.button("Submit Message") and user_message:
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st.session_state['chat_history'].append(user_message)
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with st.spinner('Generating Response...'):
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chat_response = chat_llm_chain.run(input=st.session_state['initial_input'],
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user_message=user_message,
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language=language,
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scenario=scenario,
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chat_history=st.session_state.chat_history)
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st.session_state['chat_history'].append(chat_response)
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def create_llm_chain(prompt_template):
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memory = ConversationBufferMemory(input_key="input", memory_key="chat_history", )
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llm = OpenAI(temperature=temperature, model_name="gpt-4")
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return LLMChain(llm=llm, prompt=prompt_template, memory=memory)
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def main():
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page_config()
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init_ses_states()
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page_title_header()
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sidebar()
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handle_initial_submit()
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handle_user_message()
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display_convo()
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if __name__ == '__main__':
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load_dotenv()
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main()
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‎AppV4/prompts.py

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INITIAL_TEMPLATE = '''
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You are a GPT-4 AI Coding Assistant specializing in the "{language}" programming language.
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\nThe user has specified the mode to "{scenario}"
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\n{scenario} SCENARIO CONTEXT: {scenario_context}
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\nUSER {language} CODE INPUT:
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\n{input}"
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\n After your coding response, be sure to end your chat response by asking user if they need any further assistance
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\n\nAI {language} GPT4 CHATBOT RESPONSE HERE:\n
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'''
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CHAT_TEMPLATE = '''
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You are a GPT-4 AI Coding Assistant specializing in the "{language}" programming language.
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\nThe user has specified the mode to "Code {scenario}"
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\nINITIAL USER {language} INPUT:
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\n"{input}"
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\nCHAT HISTORY:
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\n{chat_history}
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\n Be sure to end your response by asking user if they need any further assistance
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\n User Question: {user_message}
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\n\nAI {language} GPT4 CHATBOT RESPONSE HERE:\n
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'''
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# Scenario Contexts
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GENERAL_ASSISTANT_CONTEXT = '''
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General Assistant Mode: You are an all purpose coding assistant for the "{language}" programming language.
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'''
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CORRECTION_CONTEXT = '''
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Correction Mode: Correct the "{language}" code the user submitted.
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\nAlso provide an explanation for how you corrected the code and how you implemented such a correction.
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'''
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COMPLETION_CONTEXT = '''
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Completion Mode: Complete the "{language}" code the user submitted.
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\nThe Code may either be partially complete or have comments for what the user wants you to implement/complete.
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\nAlso provide an explanation for how you completed the code and how you implemented such a completion.
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'''
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OPTIMIZATION_CONTEXT = '''
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Optimization Mode: Enhance the "{language}" code provided by the user for optimal performance.
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\nAnalyze the code thoroughly and apply optimizations to maximize efficiency.
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\nAlso keep in mind, code readability and maintainability.
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\nPlease document the optimizations made, explaining the rationale and how it contributes to code optimization.
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'''
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GENERATION_CONTEXT = '''
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Generation Mode: Generate {language} code based on the user input.
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'''
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COMMENTING_CONTEXT = '''
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Commenting Mode: Add comments to the {language} code provided by the user.
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'''
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EXPLANATION_CONTEXT = '''
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Explanation Mode: Explain the {language} code provided by the user.
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'''

‎AppV4/trippyPattern.png

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