├── AppV1
    ├── .env.example
    └── main.py
├── AppV2
    ├── .env
    ├── htmlTemplates.py
    └── main.py
├── AppV3
    ├── .env
    ├── htmlTemplates.py
    ├── main.py
    ├── prompts.py
    └── trippyPattern.png
├── AppV4
    ├── .env
    ├── htmlTemplates.py
    ├── main.py
    ├── prompts.py
    └── trippyPattern.png
├── AppV5
    ├── .env
    ├── htmlTemplates.py
    ├── main.py
    ├── prompts.py
    ├── requirements.txt
    └── trippyPattern.png
├── AppV6
    ├── .env
    ├── htmlTemplates.py
    ├── main.py
    ├── prompts.py
    ├── requirements.txt
    └── trippyPattern.png
├── AppV7
    ├── .env
    ├── db_functions.py
    ├── htmlTemplates.py
    ├── main.py
    ├── prompts.py
    ├── requirements.txt
    └── trippyPattern.png
└── README.md


/AppV1/.env.example:
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1 | OPENAI_API_KEY=
2 | 


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/AppV1/main.py:
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 1 | import os
 2 | from dotenv import load_dotenv
 3 | import streamlit as st
 4 | import openai
 5 | from langchain.llms import OpenAI
 6 | from langchain.memory import ConversationBufferMemory
 7 | from langchain.chains import LLMChain
 8 | from langchain.prompts import PromptTemplate
 9 | 
10 | 
11 | def init_ses_states():
12 |     if 'chatHistory' not in st.session_state: 
13 |         st.session_state['chatHistory'] = []
14 | 
15 | 
16 | def sidebar():
17 |     global language, scenario, temperature
18 |     languages = ['Python',
19 |                 'JavaScript',
20 |                 'GoLang',
21 |                 'C',
22 |                 'C++',
23 |                 'C#'
24 |                 ]
25 |     scenarios = ['Code Correction',
26 |                 'Snippet Completion',
27 |                 ]
28 |     with st.sidebar:
29 |         with st.expander(label="Settings", expanded=True):
30 |             language = st.selectbox(label="Language", options=languages)
31 |             scenario = st.selectbox(label="Scenario", options=scenarios)
32 |             temperature = st.slider(label="Temperature", min_value=0.0, max_value=1.0,value=0.5)
33 | 
34 | 
35 | def main():
36 |     st.set_page_config(page_title="GPT-4 Coding Asssistant", page_icon="computer")
37 |     init_ses_states()
38 |     sidebar()
39 |     st.title("GPT-4 Coding Assistant")
40 |     st.caption("Powered by OpenAI, LangChain, Streamlit")
41 |     template = PromptTemplate(
42 |         input_variables=['input','language','scenario'],
43 |         template='''
44 |         You are an AI Coding Assistant specializing in the "{language}" programming language.
45 |         \nThe user has specified the mode to "{scenario}"
46 |         \nUSER {language} CODE INPUT: 
47 |         \n"{input}"
48 |         '''
49 |     )
50 |     memory = ConversationBufferMemory(input_key="input", memory_key="chat_history")
51 |     llm = OpenAI(temperature=temperature, model_name="gpt-4")
52 |     llm_chain = LLMChain(llm=llm, prompt=template, memory=memory)
53 |     user_input = st.text_area(label=f"Input {language} Code", height=400)
54 |     if (st.button('Submit') and user_input):
55 |         with st.spinner('Generating Response...'):   
56 |             response = llm_chain.run(input=user_input, language=language, scenario=scenario)
57 |             st.write(response)
58 | 
59 | 
60 | if __name__ == '__main__':
61 |     load_dotenv()
62 |     main()
63 | 
64 | 


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/AppV2/.env:
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1 | OPENAI_API_KEY=
2 | 


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/AppV2/htmlTemplates.py:
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 1 | css = '''
 2 | <style>
 3 | .chat-message {
 4 |     padding: 1.5rem; border-radius: 0.5rem; margin-bottom: 1rem; display: flex
 5 | }
 6 | .chat-message.user {
 7 |     background-color: #2b313e
 8 | }
 9 | .chat-message.bot {
10 |     background-color: #475063
11 | }
12 | .chat-message .avatar {
13 |   width: 12%;
14 | }
15 | .chat-message .avatar img {
16 |   max-width: 60px;
17 |   max-height: 60px;
18 |   border-radius: 50%;
19 |   object-fit: cover;
20 | }
21 | .chat-message .message {
22 |   width: 90%;
23 |   padding: 0 .35rem;
24 |   color: #fff;
25 | }
26 | '''
27 | 
28 | bot_template = '''
29 | <div class="chat-message bot">
30 |     <div class="avatar">
31 |         <img src="https://www.sideshow.com/storage/product-images/2171/c-3po_star-wars_square.jpg">
32 |     </div>
33 |     <div class="message">{{MSG}}</div>
34 | </div>
35 | '''
36 | 
37 | user_template = '''
38 | <div class="chat-message user">
39 |     <div class="avatar">
40 |         <img src="https://resizing.flixster.com/ocuc8yjm8Fu5UK5Ze8lbdp58m9Y=/300x300/v2/https://flxt.tmsimg.com/assets/p11759522_i_h9_aa.jpg">
41 |     </div>    
42 |     <div class="message">{{MSG}}</div>
43 | </div>
44 | '''
45 | 


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/AppV2/main.py:
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 1 | import os
 2 | from dotenv import load_dotenv
 3 | import streamlit as st
 4 | import openai
 5 | from langchain.llms import OpenAI
 6 | from langchain.memory import ConversationBufferMemory
 7 | from langchain.chains import LLMChain
 8 | from langchain.prompts import PromptTemplate
 9 | from htmlTemplates import css, bot_template, user_template
10 | 
11 | 
12 | def init_ses_states():
13 |     if 'chat_history' not in st.session_state: 
14 |         st.session_state['chat_history'] = []
15 | 
16 | 
17 | def sidebar():
18 |     global language, scenario, temperature
19 |     languages = ['Python','JavaScript','GoLang','C','C++','C#']
20 |     scenarios = ['Code Correction','Snippet Completion']
21 |     with st.sidebar:
22 |         with st.expander(label="Settings", expanded=True):
23 |             language = st.selectbox(label="Language", options=languages)
24 |             scenario = st.selectbox(label="Scenario", options=scenarios)
25 |             temperature = st.slider(label="Temperature", min_value=0.0, max_value=1.0,value=0.5)
26 | 
27 | 
28 | def display_convo():
29 |     with st.container():
30 |         for i, message in enumerate(reversed(st.session_state.chat_history)):
31 |             if i % 2 == 0:
32 |                  st.markdown(bot_template.replace("{{MSG}}", message), unsafe_allow_html=True)
33 |             else:
34 |                 st.markdown(user_template.replace("{{MSG}}", message), unsafe_allow_html=True)
35 | 
36 | 
37 | 
38 | def main():
39 |     st.set_page_config(page_title="GPT-4 Coding Asssistant", page_icon="computer")
40 |     st.write(css, unsafe_allow_html=True)
41 |     init_ses_states()
42 |     sidebar()
43 |     st.title("GPT-4 Coding Assistant")
44 |     st.caption("Powered by OpenAI, LangChain, Streamlit")
45 | 
46 |     initial_template = PromptTemplate(
47 |         input_variables=['input','language','scenario'],
48 |         template='''
49 |         You are a GPT-4 AI Coding Assistant specializing in the "{language}" programming language.
50 |         \nThe user has specified the mode to "{scenario}"
51 |         \nUSER {language} CODE INPUT: 
52 |         \n{input}"
53 |         \n Be sure to end your response by asking user if they need any further assistance
54 |         \n\nAI {language} GPT4 CHATBOT RESPONSE HERE:\n
55 |         '''
56 |     )
57 |     chat_template = PromptTemplate(
58 |         input_variables=['input','language','scenario','chat_history'],
59 |         template='''
60 |         You are a GPT-4 AI Coding Assistant specializing in the "{language}" programming language.
61 |         \nThe user has specified the mode to "{scenario}"
62 |         \nINITIAL USER {language} INPUT: 
63 |         \n"{input}"
64 |         \nCHAT HISTORY:
65 |         \n{chat_history}
66 |         \n Be sure to end your response by asking user if they need any further assistance
67 |         \n\nAI {language} GPT4 CHATBOT RESPONSE HERE:\n
68 |         '''
69 |     )
70 |     memory = ConversationBufferMemory(input_key="input", memory_key="chat_history")
71 |     llm = OpenAI(temperature=temperature, model_name="gpt-4")
72 |     initial_llm_chain = LLMChain(llm=llm, prompt=initial_template, memory=memory)
73 |     chat_llm_chain = LLMChain(llm=llm, prompt=chat_template, memory=memory)
74 |     initial_input = st.text_area(label=f"Input {language} Code", height=300)
75 |     if (st.button(f'Submit {language} Code') and initial_input):
76 |         st.session_state['chat_history'] = []
77 |         with st.spinner('Generating Response...'):   
78 |             initial_response = initial_llm_chain.run(input=initial_input, language=language, scenario=scenario)
79 |             st.session_state.chat_history.append(initial_response)
80 |     if st.session_state.chat_history != []:
81 |         user_message = st.text_input("Further Questions for Coding AI?", key="user_input")
82 |         if st.button("Submit Message") and user_message:
83 |             st.session_state['chat_history'].append(user_message)
84 |             with st.spinner('Generating Response...'):  
85 |                 chat_response = chat_llm_chain.run(input=user_message, 
86 |                                                     language=language, 
87 |                                                     scenario=scenario, 
88 |                                                     chat_history=st.session_state.chat_history)
89 |                 st.session_state['chat_history'].append(chat_response)
90 |     display_convo()
91 | 
92 | if __name__ == '__main__':
93 |     load_dotenv()
94 |     main()
95 | 
96 | 


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/AppV3/.env:
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1 | OPENAI_API_KEY=
2 | 


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/AppV3/htmlTemplates.py:
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 1 | css = '''
 2 | <style>
 3 | .chat-message {
 4 |     padding: 1.5rem; border-radius: 0.5rem; margin-bottom: 1rem; display: flex
 5 | }
 6 | .chat-message.user {
 7 |     background-color: #2b313e
 8 | }
 9 | .chat-message.bot {
10 |     background-color: #475063
11 | }
12 | .chat-message .avatar {
13 |   width: 12%;
14 | }
15 | .chat-message .avatar img {
16 |   max-width: 60px;
17 |   max-height: 60px;
18 |   border-radius: 50%;
19 |   object-fit: cover;
20 | }
21 | .chat-message .message {
22 |   width: 90%;
23 |   padding: 0 .35rem;
24 |   color: #fff;
25 | }
26 | '''
27 | 
28 | bot_template = '''
29 | <div class="chat-message bot">
30 |     <div class="avatar">
31 |         <img src="https://www.sideshow.com/storage/product-images/2171/c-3po_star-wars_square.jpg">
32 |     </div>
33 |     <div class="message">{{MSG}}</div>
34 | </div>
35 | '''
36 | 
37 | user_template = '''
38 | <div class="chat-message user">
39 |     <div class="avatar">
40 |         <img src="https://resizing.flixster.com/ocuc8yjm8Fu5UK5Ze8lbdp58m9Y=/300x300/v2/https://flxt.tmsimg.com/assets/p11759522_i_h9_aa.jpg">
41 |     </div>    
42 |     <div class="message">{{MSG}}</div>
43 | </div>
44 | '''
45 | 


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/AppV3/main.py:
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  1 | import os
  2 | from PIL import Image
  3 | from dotenv import load_dotenv
  4 | from PyPDF2 import PdfReader
  5 | import streamlit as st
  6 | import openai
  7 | from langchain.text_splitter import CharacterTextSplitter
  8 | from langchain.llms import OpenAI
  9 | from langchain.memory import ConversationBufferMemory
 10 | from langchain.chains import LLMChain
 11 | from langchain.prompts import PromptTemplate
 12 | from langchain.embeddings import OpenAIEmbeddings
 13 | from langchain.vectorstores import FAISS
 14 | from langchain.chains import RetrievalQA
 15 | from langchain.chains import ConversationalRetrievalChain
 16 | from htmlTemplates import css, bot_template, user_template
 17 | from prompts import CHAT_TEMPLATE, INITIAL_TEMPLATE
 18 | from prompts import CORRECTION_CONTEXT, COMPLETION_CONTEXT, OPTIMIZATION_CONTEXT, GENERAL_ASSISTANT_CONTEXT, GENERATION_CONTEXT, COMMENTING_CONTEXT, EXPLANATION_CONTEXT
 19 | 
 20 | 
 21 | def init_ses_states():
 22 |     st.session_state.setdefault('chat_history', [])
 23 |     st.session_state.setdefault('initial_input', "")
 24 | 
 25 | def sidebar():
 26 |     global language, scenario, temperature, scenario_context, pdf_docs
 27 |     languages = ['Python', 'GoLang', 'JavaScript', 'Java', 'C', 'C++', 'C#']
 28 |     scenarios = ['General Assistant', 'Code Correction', 'Code Completion', 'Code Commenting', 'Code Optimization', 'Code Generation', 'Code Explanation']
 29 |     scenario_context_map = {
 30 |         "Code Correction": CORRECTION_CONTEXT,
 31 |         "Code Completion": COMPLETION_CONTEXT,
 32 |         "Code Optimization": OPTIMIZATION_CONTEXT,
 33 |         "General Assistant": GENERAL_ASSISTANT_CONTEXT,
 34 |         "Code Generation": GENERATION_CONTEXT,
 35 |         "Code Commenting": COMMENTING_CONTEXT,
 36 |         "Code Explanation": EXPLANATION_CONTEXT
 37 |     }
 38 | 
 39 |     with st.sidebar:
 40 |         with st.expander(label="Settings", expanded=True):
 41 |             language = st.selectbox(label="Language", options=languages, index=0)
 42 |             scenario = st.selectbox(label="Scenario", options=scenarios, index=0)
 43 |             scenario_context = scenario_context_map.get(scenario, "")
 44 |             temperature = st.slider(label="Temperature", min_value=0.0, max_value=1.0, value=0.5)
 45 | 
 46 | 
 47 | def display_convo():
 48 |     with st.container():
 49 |         for i, message in enumerate(reversed(st.session_state.chat_history)):
 50 |             if i % 2 == 0:
 51 |                  st.markdown(bot_template.replace("{{MSG}}", message), unsafe_allow_html=True)
 52 |             else:
 53 |                 st.markdown(user_template.replace("{{MSG}}", message), unsafe_allow_html=True)
 54 | 
 55 | 
 56 | def main():
 57 |     st.set_page_config(page_title="GPT-4 Coding Asssistant", page_icon="computer")
 58 |     st.write(css, unsafe_allow_html=True)
 59 |     init_ses_states()
 60 |     sidebar()
 61 |     top_image = Image.open('trippyPattern.png')
 62 |     st.image(top_image)
 63 |     st.title("GPT-4 Coding Assistant")
 64 |     st.caption("Powered by OpenAI, LangChain, Streamlit")
 65 | 
 66 |     initial_template = PromptTemplate(
 67 |         input_variables=['input','language','scenario','scenario_context'],
 68 |         template= INITIAL_TEMPLATE)
 69 |     chat_template = PromptTemplate(
 70 |         input_variables=['input','user_message','language','scenario','chat_history'],
 71 |         template=CHAT_TEMPLATE)
 72 |     memory = ConversationBufferMemory(input_key="input", memory_key="chat_history", )
 73 |     llm = OpenAI(temperature=temperature, model_name="gpt-4")
 74 |     chat_llm_chain = LLMChain(llm=llm, prompt=chat_template, memory=memory)
 75 |     initial_llm_chain = LLMChain(llm=llm, prompt=initial_template, memory=memory)
 76 |     initial_input = st.text_area(label=f"User Input", height=300)
 77 | 
 78 |     if (st.button(f'Submit Initial Input') and initial_input):
 79 |         st.session_state['chat_history'] = []
 80 |         with st.spinner('Generating Response...'):   
 81 |             initial_response = initial_llm_chain.run(input=initial_input, 
 82 |                                                     language=language, 
 83 |                                                     scenario=scenario,
 84 |                                                     scenario_context=scenario_context)
 85 |         st.session_state.chat_history.append(initial_response)
 86 | 
 87 |     if st.session_state.chat_history:
 88 |         user_message = st.text_input("Further Questions for Coding AI?", key="user_input")
 89 |         if st.button("Submit Message") and user_message:
 90 |             st.session_state['chat_history'].append(user_message)
 91 |             with st.spinner('Generating Response...'):  
 92 |                 chat_response = chat_llm_chain.run(input=st.session_state['initial_input'],
 93 |                                                    user_message=user_message,
 94 |                                                     language=language, 
 95 |                                                     scenario=scenario,
 96 |                                                     chat_history=st.session_state.chat_history)
 97 |                 st.session_state['chat_history'].append(chat_response)
 98 |     display_convo()
 99 | 
100 | 
101 | if __name__ == '__main__':
102 |     load_dotenv()
103 |     main()
104 | 
105 | 


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/AppV3/prompts.py:
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 1 | INITIAL_TEMPLATE = '''
 2 |     You are a GPT-4 AI Coding Assistant specializing in the "{language}" programming language.
 3 |     \nThe user has specified the mode to "{scenario}"
 4 |     \n{scenario} SCENARIO CONTEXT: {scenario_context}
 5 |     \nUSER {language} CODE INPUT: 
 6 |     \n{input}"
 7 |     \n After your coding response, be sure to end your chat response by asking user if they need any further assistance
 8 |     \n\nAI {language} GPT4 CHATBOT RESPONSE HERE:\n
 9 | '''
10 | 
11 | 
12 | CHAT_TEMPLATE = '''
13 |     You are a GPT-4 AI Coding Assistant specializing in the "{language}" programming language.
14 |     \nThe user has specified the mode to "Code {scenario}"
15 |     \nINITIAL USER {language} INPUT: 
16 |     \n"{input}"
17 |     \nCHAT HISTORY:
18 |     \n{chat_history}
19 |     \n Be sure to end your response by asking user if they need any further assistance
20 |     \n User Question: {user_message}
21 |     \n\nAI {language} GPT4 CHATBOT RESPONSE HERE:\n
22 | '''
23 | 
24 | 
25 | # Scenario Contexts
26 | 
27 | GENERAL_ASSISTANT_CONTEXT = '''
28 | General Assistant Mode: You are an all purpose coding assistant for the "{language}" programming language.
29 | '''
30 | 
31 | CORRECTION_CONTEXT = '''
32 | Correction Mode: Correct the "{language}" code the user submitted.
33 | \nAlso provide an explanation for how you corrected the code and how you implemented such a correction.
34 | '''
35 | 
36 | COMPLETION_CONTEXT = '''
37 | Completion Mode: Complete the "{language}" code the user submitted.
38 | \nThe Code may either be partially complete or have comments for what the user wants you to implement/complete.
39 | \nAlso provide an explanation for how you completed the code and how you implemented such a completion.
40 | '''
41 | 
42 | OPTIMIZATION_CONTEXT = '''
43 | Optimization Mode: Enhance the "{language}" code provided by the user for optimal performance.
44 | \nAnalyze the code thoroughly and apply optimizations to maximize efficiency.
45 | \nAlso keep in mind, code readability and maintainability.
46 | \nPlease document the optimizations made, explaining the rationale and how it contributes to code optimization.
47 | '''
48 | 
49 | GENERATION_CONTEXT = '''
50 | Generation Mode: Generate {language} code based on the user input.
51 | '''
52 | 
53 | COMMENTING_CONTEXT = '''
54 | Commenting Mode: Add comments to the {language} code provided by the user.
55 | '''
56 | 
57 | EXPLANATION_CONTEXT = '''
58 | Explanation Mode: Explain the {language} code provided by the user.
59 | '''
60 | 


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/AppV3/trippyPattern.png:
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https://raw.githubusercontent.com/Luis96920/GPT4-Programming-Assistant/34e61ffd199e7401d345adb165fdebb55077bbb9/AppV3/trippyPattern.png


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/AppV4/.env:
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1 | OPENAI_API_KEY=
2 | 


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/AppV4/htmlTemplates.py:
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 1 | css = '''
 2 | <style>
 3 | .chat-message {
 4 |     padding: 1.5rem; border-radius: 0.5rem; margin-bottom: 1rem; display: flex
 5 | }
 6 | .chat-message.user {
 7 |     background-color: #2b313e
 8 | }
 9 | .chat-message.bot {
10 |     background-color: #475063
11 | }
12 | .chat-message .avatar {
13 |   width: 12%;
14 | }
15 | .chat-message .avatar img {
16 |   max-width: 60px;
17 |   max-height: 60px;
18 |   border-radius: 50%;
19 |   object-fit: cover;
20 | }
21 | .chat-message .message {
22 |   width: 90%;
23 |   padding: 0 .35rem;
24 |   color: #fff;
25 | }
26 | '''
27 | 
28 | bot_template = '''
29 | <div class="chat-message bot">
30 |     <div class="avatar">
31 |         <img src="https://www.sideshow.com/storage/product-images/2171/c-3po_star-wars_square.jpg">
32 |     </div>
33 |     <div class="message">{{MSG}}</div>
34 | </div>
35 | '''
36 | 
37 | user_template = '''
38 | <div class="chat-message user">
39 |     <div class="avatar">
40 |         <img src="https://resizing.flixster.com/ocuc8yjm8Fu5UK5Ze8lbdp58m9Y=/300x300/v2/https://flxt.tmsimg.com/assets/p11759522_i_h9_aa.jpg">
41 |     </div>    
42 |     <div class="message">{{MSG}}</div>
43 | </div>
44 | '''
45 | 


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/AppV4/main.py:
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  1 | import os
  2 | from PIL import Image
  3 | from dotenv import load_dotenv
  4 | from PyPDF2 import PdfReader
  5 | import streamlit as st
  6 | import openai
  7 | from langchain.text_splitter import CharacterTextSplitter
  8 | from langchain.llms import OpenAI
  9 | from langchain.memory import ConversationBufferMemory
 10 | from langchain.chains import LLMChain
 11 | from langchain.prompts import PromptTemplate
 12 | from langchain.embeddings import OpenAIEmbeddings
 13 | from langchain.vectorstores import FAISS
 14 | from langchain.chains import RetrievalQA
 15 | from langchain.chains import ConversationalRetrievalChain
 16 | from htmlTemplates import css, bot_template, user_template
 17 | from prompts import CHAT_TEMPLATE, INITIAL_TEMPLATE
 18 | from prompts import CORRECTION_CONTEXT, COMPLETION_CONTEXT, OPTIMIZATION_CONTEXT, GENERAL_ASSISTANT_CONTEXT, GENERATION_CONTEXT, COMMENTING_CONTEXT, EXPLANATION_CONTEXT
 19 | 
 20 | 
 21 | def page_config():
 22 |     st.set_page_config(page_title="GPT-4 Coding Asssistant", page_icon="computer")
 23 |     st.write(css, unsafe_allow_html=True)
 24 | 
 25 | 
 26 | def init_ses_states():
 27 |     st.session_state.setdefault('chat_history', [])
 28 |     st.session_state.setdefault('initial_input', "")
 29 | 
 30 | 
 31 | def page_title_header():
 32 |     top_image = Image.open('trippyPattern.png')
 33 |     st.image(top_image)
 34 |     st.title("GPT-4 Coding Assistant")
 35 |     st.caption("Powered by OpenAI, LangChain, Streamlit")
 36 | 
 37 | 
 38 | def sidebar():
 39 |     global language, scenario, temperature, scenario_context
 40 |     languages = ['Python', 'GoLang', 'JavaScript', 'Java', 'C', 'C++', 'C#']
 41 |     scenarios = ['General Assistant', 'Code Correction', 'Code Completion', 'Code Commenting', 'Code Optimization', 'Code Generation', 'Code Explanation']
 42 |     scenario_context_map = {
 43 |         "Code Correction": CORRECTION_CONTEXT,
 44 |         "Code Completion": COMPLETION_CONTEXT,
 45 |         "Code Optimization": OPTIMIZATION_CONTEXT,
 46 |         "General Assistant": GENERAL_ASSISTANT_CONTEXT,
 47 |         "Code Generation": GENERATION_CONTEXT,
 48 |         "Code Commenting": COMMENTING_CONTEXT,
 49 |         "Code Explanation": EXPLANATION_CONTEXT
 50 |     }
 51 | 
 52 |     with st.sidebar:
 53 |         with st.expander(label="Settings", expanded=True):
 54 |             language = st.selectbox(label="Language", options=languages, index=0)
 55 |             scenario = st.selectbox(label="Scenario", options=scenarios, index=0)
 56 |             scenario_context = scenario_context_map.get(scenario, "")
 57 |             temperature = st.slider(label="Temperature", min_value=0.0, max_value=1.0, value=0.5)
 58 | 
 59 | 
 60 | def display_convo():
 61 |     with st.container():
 62 |         for i, message in enumerate(reversed(st.session_state.chat_history)):
 63 |             if i % 2 == 0:
 64 |                  st.markdown(bot_template.replace("{{MSG}}", message), unsafe_allow_html=True)
 65 |             else:
 66 |                 st.markdown(user_template.replace("{{MSG}}", message), unsafe_allow_html=True)
 67 | 
 68 | 
 69 | def handle_initial_submit():
 70 |     initial_template = PromptTemplate(
 71 |         input_variables=['input','language','scenario','scenario_context'],
 72 |         template= INITIAL_TEMPLATE
 73 |     )
 74 |     initial_llm_chain = create_llm_chain(prompt_template=initial_template)
 75 |     initial_input = st.text_area(label=f"User Input", height=300)
 76 |     if (st.button(f'Submit Initial Input') and initial_input):
 77 |         st.session_state.initial_input = initial_input
 78 |         st.session_state['chat_history'] = []
 79 |         with st.spinner('Generating Response...'):   
 80 |             initial_response = initial_llm_chain.run(input=initial_input, 
 81 |                                                     language=language, 
 82 |                                                     scenario=scenario,
 83 |                                                     scenario_context=scenario_context)
 84 |         st.session_state.chat_history.append(initial_response)
 85 | 
 86 | 
 87 | def handle_user_message():
 88 |     chat_template = PromptTemplate(
 89 |         input_variables=['input','user_message','language','scenario','chat_history'],
 90 |         template=CHAT_TEMPLATE
 91 |     )
 92 |     chat_llm_chain = create_llm_chain(prompt_template=chat_template)
 93 |     if st.session_state.chat_history:
 94 |         user_message = st.text_input("Further Questions for Coding AI?", key="user_input")
 95 |         if st.button("Submit Message") and user_message:
 96 |             st.session_state['chat_history'].append(user_message)
 97 |             with st.spinner('Generating Response...'):  
 98 |                 chat_response = chat_llm_chain.run(input=st.session_state['initial_input'],
 99 |                                                    user_message=user_message,
100 |                                                     language=language, 
101 |                                                     scenario=scenario,
102 |                                                     chat_history=st.session_state.chat_history)
103 |                 st.session_state['chat_history'].append(chat_response)
104 | 
105 | 
106 | def create_llm_chain(prompt_template):
107 |     memory = ConversationBufferMemory(input_key="input", memory_key="chat_history", )
108 |     llm = OpenAI(temperature=temperature, model_name="gpt-4")
109 |     return LLMChain(llm=llm, prompt=prompt_template, memory=memory)
110 | 
111 | 
112 | def main():
113 |     page_config()
114 |     init_ses_states()
115 |     page_title_header()
116 |     sidebar()
117 |     handle_initial_submit()
118 |     handle_user_message()
119 |     display_convo()
120 | 
121 | 
122 | if __name__ == '__main__':
123 |     load_dotenv()
124 |     main()
125 | 
126 | 


--------------------------------------------------------------------------------
/AppV4/prompts.py:
--------------------------------------------------------------------------------
 1 | INITIAL_TEMPLATE = '''
 2 |     You are a GPT-4 AI Coding Assistant specializing in the "{language}" programming language.
 3 |     \nThe user has specified the mode to "{scenario}"
 4 |     \n{scenario} SCENARIO CONTEXT: {scenario_context}
 5 |     \nUSER {language} CODE INPUT: 
 6 |     \n{input}"
 7 |     \n After your coding response, be sure to end your chat response by asking user if they need any further assistance
 8 |     \n\nAI {language} GPT4 CHATBOT RESPONSE HERE:\n
 9 | '''
10 | 
11 | 
12 | CHAT_TEMPLATE = '''
13 |     You are a GPT-4 AI Coding Assistant specializing in the "{language}" programming language.
14 |     \nThe user has specified the mode to "Code {scenario}"
15 |     \nINITIAL USER {language} INPUT: 
16 |     \n"{input}"
17 |     \nCHAT HISTORY:
18 |     \n{chat_history}
19 |     \n Be sure to end your response by asking user if they need any further assistance
20 |     \n User Question: {user_message}
21 |     \n\nAI {language} GPT4 CHATBOT RESPONSE HERE:\n
22 | '''
23 | 
24 | 
25 | # Scenario Contexts
26 | 
27 | GENERAL_ASSISTANT_CONTEXT = '''
28 | General Assistant Mode: You are an all purpose coding assistant for the "{language}" programming language.
29 | '''
30 | 
31 | CORRECTION_CONTEXT = '''
32 | Correction Mode: Correct the "{language}" code the user submitted.
33 | \nAlso provide an explanation for how you corrected the code and how you implemented such a correction.
34 | '''
35 | 
36 | COMPLETION_CONTEXT = '''
37 | Completion Mode: Complete the "{language}" code the user submitted.
38 | \nThe Code may either be partially complete or have comments for what the user wants you to implement/complete.
39 | \nAlso provide an explanation for how you completed the code and how you implemented such a completion.
40 | '''
41 | 
42 | OPTIMIZATION_CONTEXT = '''
43 | Optimization Mode: Enhance the "{language}" code provided by the user for optimal performance.
44 | \nAnalyze the code thoroughly and apply optimizations to maximize efficiency.
45 | \nAlso keep in mind, code readability and maintainability.
46 | \nPlease document the optimizations made, explaining the rationale and how it contributes to code optimization.
47 | '''
48 | 
49 | GENERATION_CONTEXT = '''
50 | Generation Mode: Generate {language} code based on the user input.
51 | '''
52 | 
53 | COMMENTING_CONTEXT = '''
54 | Commenting Mode: Add comments to the {language} code provided by the user.
55 | '''
56 | 
57 | EXPLANATION_CONTEXT = '''
58 | Explanation Mode: Explain the {language} code provided by the user.
59 | '''


--------------------------------------------------------------------------------
/AppV4/trippyPattern.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/Luis96920/GPT4-Programming-Assistant/34e61ffd199e7401d345adb165fdebb55077bbb9/AppV4/trippyPattern.png


--------------------------------------------------------------------------------
/AppV5/.env:
--------------------------------------------------------------------------------
1 | OPENAI_API_KEY=
2 | 


--------------------------------------------------------------------------------
/AppV5/htmlTemplates.py:
--------------------------------------------------------------------------------
 1 | css = '''
 2 | <style>
 3 | .chat-message {
 4 |     padding: 1.5rem; border-radius: 0.5rem; margin-bottom: 1rem; display: flex
 5 | }
 6 | .chat-message.user {
 7 |     background-color: #2b313e
 8 | }
 9 | .chat-message.bot {
10 |     background-color: #475063
11 | }
12 | .chat-message .avatar {
13 |   width: 12%;
14 | }
15 | .chat-message .avatar img {
16 |   max-width: 60px;
17 |   max-height: 60px;
18 |   border-radius: 50%;
19 |   object-fit: cover;
20 | }
21 | .chat-message .message {
22 |   width: 90%;
23 |   padding: 0 .35rem;
24 |   color: #fff;
25 | }
26 | '''
27 | 
28 | bot_template = '''
29 | <div class="chat-message bot">
30 |     <div class="avatar">
31 |         <img src="https://www.sideshow.com/storage/product-images/2171/c-3po_star-wars_square.jpg">
32 |     </div>
33 |     <div class="message">{{MSG}}</div>
34 | </div>
35 | '''
36 | 
37 | user_template = '''
38 | <div class="chat-message user">
39 |     <div class="avatar">
40 |         <img src="https://resizing.flixster.com/ocuc8yjm8Fu5UK5Ze8lbdp58m9Y=/300x300/v2/https://flxt.tmsimg.com/assets/p11759522_i_h9_aa.jpg">
41 |     </div>    
42 |     <div class="message">{{MSG}}</div>
43 | </div>
44 | '''
45 | 


--------------------------------------------------------------------------------
/AppV5/main.py:
--------------------------------------------------------------------------------
  1 | import os
  2 | from PIL import Image
  3 | from dotenv import load_dotenv
  4 | from PyPDF2 import PdfReader
  5 | import streamlit as st
  6 | import openai
  7 | from langchain.text_splitter import CharacterTextSplitter
  8 | from langchain.llms import OpenAI
  9 | from langchain.memory import ConversationBufferMemory
 10 | from langchain.chains import LLMChain
 11 | from langchain.prompts import PromptTemplate
 12 | from langchain.embeddings import OpenAIEmbeddings
 13 | from langchain.vectorstores import FAISS
 14 | from langchain.chains import RetrievalQA
 15 | from langchain.chains import ConversationalRetrievalChain
 16 | from htmlTemplates import css, bot_template, user_template
 17 | from prompts import CHAT_TEMPLATE, INITIAL_TEMPLATE
 18 | from prompts import CORRECTION_CONTEXT, COMPLETION_CONTEXT, OPTIMIZATION_CONTEXT, GENERAL_ASSISTANT_CONTEXT, \
 19 |     GENERATION_CONTEXT, COMMENTING_CONTEXT, EXPLANATION_CONTEXT, LEETCODE_CONTEXT, SHORTENING_CONTEXT
 20 | 
 21 | 
 22 | def page_config():
 23 |     st.set_page_config(page_title="GPT-4 Coding Asssistant", page_icon="computer")
 24 |     st.write(css, unsafe_allow_html=True)
 25 | 
 26 | 
 27 | def init_ses_states():
 28 |     st.session_state.setdefault('chat_history', [])
 29 |     st.session_state.setdefault('initial_input', "")
 30 | 
 31 | 
 32 | def page_title_header():
 33 |     top_image = Image.open('trippyPattern.png')
 34 |     st.image(top_image)
 35 |     st.title("GPT-4 Coding Assistant")
 36 |     st.caption("Powered by OpenAI, LangChain, Streamlit")
 37 | 
 38 | 
 39 | def sidebar():
 40 |     global language, scenario, temperature, scenario_context
 41 |     languages = ['Python', 'GoLang', 'JavaScript', 'Java', 'C', 'C++', 'C#', 'SQL']
 42 |     scenarios = ['General Assistant', 'Code Correction', 'Code Completion', 'Code Commenting', 'Code Optimization', 
 43 |                  'Code Shortener','Code Generation', 'Code Explanation', 'LeetCode Solver']
 44 |     scenario_context_map = {
 45 |         "Code Correction": CORRECTION_CONTEXT,
 46 |         "Code Completion": COMPLETION_CONTEXT,
 47 |         "Code Optimization": OPTIMIZATION_CONTEXT,
 48 |         "General Assistant": GENERAL_ASSISTANT_CONTEXT,
 49 |         "Code Generation": GENERATION_CONTEXT,
 50 |         "Code Commenting": COMMENTING_CONTEXT,
 51 |         "Code Explanation": EXPLANATION_CONTEXT,
 52 |         "LeetCode Solver": LEETCODE_CONTEXT,
 53 |         "Code Shortener": SHORTENING_CONTEXT
 54 |     }
 55 | 
 56 |     with st.sidebar:
 57 |         with st.expander(label="Settings", expanded=True):
 58 |             language = st.selectbox(label="Language", options=languages, index=0)
 59 |             scenario = st.selectbox(label="Scenario", options=scenarios, index=0)
 60 |             scenario_context = scenario_context_map.get(scenario, "")
 61 |             temperature = st.slider(label="Temperature", min_value=0.0, max_value=1.0, value=0.5)
 62 | 
 63 | 
 64 | def display_convo():
 65 |     with st.container():
 66 |         for i, message in enumerate(reversed(st.session_state.chat_history)):
 67 |             if i % 2 == 0:
 68 |                  st.markdown(bot_template.replace("{{MSG}}", message), unsafe_allow_html=True)
 69 |             else:
 70 |                 st.markdown(user_template.replace("{{MSG}}", message), unsafe_allow_html=True)
 71 | 
 72 | 
 73 | def handle_initial_submit():
 74 |     initial_template = PromptTemplate(
 75 |         input_variables=['input','language','scenario','scenario_context'],
 76 |         template= INITIAL_TEMPLATE
 77 |     )
 78 |     initial_llm_chain = create_llm_chain(prompt_template=initial_template)
 79 |     initial_input = st.text_area(label=f"User Input", height=300)
 80 |     if (st.button(f'Submit Initial Input') and initial_input):
 81 |         st.session_state.initial_input = initial_input
 82 |         st.session_state['chat_history'] = []
 83 |         with st.spinner('Generating Response...'):   
 84 |             initial_response = initial_llm_chain.run(input=initial_input, 
 85 |                                                     language=language, 
 86 |                                                     scenario=scenario,
 87 |                                                     scenario_context=scenario_context)
 88 |         st.session_state.chat_history.append(initial_response)
 89 | 
 90 | 
 91 | def handle_user_message():
 92 |     chat_template = PromptTemplate(
 93 |         input_variables=['input','user_message','language','scenario','chat_history'],
 94 |         template=CHAT_TEMPLATE
 95 |     )
 96 |     chat_llm_chain = create_llm_chain(prompt_template=chat_template)
 97 |     if st.session_state.chat_history:
 98 |         user_message = st.text_area("Further Questions for Coding AI?", key="user_input", height=60)
 99 |         if st.button("Submit Message") and user_message:
100 |             st.session_state['chat_history'].append(user_message)
101 |             with st.spinner('Generating Response...'):  
102 |                 chat_response = chat_llm_chain.run(input=st.session_state['initial_input'],
103 |                                                    user_message=user_message,
104 |                                                     language=language, 
105 |                                                     scenario=scenario,
106 |                                                     chat_history=st.session_state.chat_history)
107 |                 st.session_state['chat_history'].append(chat_response)
108 | 
109 | 
110 | def create_llm_chain(prompt_template):
111 |     memory = ConversationBufferMemory(input_key="input", memory_key="chat_history", )
112 |     llm = OpenAI(temperature=temperature, model_name="gpt-4")
113 |     return LLMChain(llm=llm, prompt=prompt_template, memory=memory)
114 | 
115 | 
116 | def display_file_code(filename):
117 |     with open(filename, "r") as file:
118 |         code = file.read()
119 |     with st.expander(filename, expanded=False):
120 |         st.code(code, language='python')
121 | 
122 | 
123 | def main():
124 |     page_config()
125 |     init_ses_states()
126 |     page_title_header()
127 |     sidebar()
128 |     deploy_tab, code_tab = st.tabs(['Deployment','Source Code'])
129 |     with deploy_tab:
130 |         handle_initial_submit()
131 |         handle_user_message()
132 |         display_convo()
133 |     with code_tab:
134 |         st.subheader("Source Code")
135 |         display_file_code("main.py")
136 |         display_file_code("htmlTemplates.py")
137 |         display_file_code("prompts.py")
138 |         display_file_code("requirements.txt")
139 | 
140 | if __name__ == '__main__':
141 |     load_dotenv()
142 |     main()
143 | 
144 | 


--------------------------------------------------------------------------------
/AppV5/prompts.py:
--------------------------------------------------------------------------------
 1 | INITIAL_TEMPLATE = '''
 2 |     You are a GPT-4 AI Coding Assistant specializing in the "{language}" programming language.
 3 |     \nThe user has specified the mode to "{scenario}"
 4 |     \n{scenario} SCENARIO CONTEXT: {scenario_context}
 5 |     \nUSER {language} CODE INPUT: 
 6 |     \n{input}"
 7 |     \n After your coding response, be sure to end your chat response by asking user if they need any further assistance
 8 |     \n\nAI {language} GPT4 CHATBOT RESPONSE HERE:\n
 9 | '''
10 | 
11 | 
12 | CHAT_TEMPLATE = '''
13 |     You are a GPT-4 AI Coding Assistant specializing in the "{language}" programming language.
14 |     \nThe user has specified the mode to "Code {scenario}"
15 |     \nINITIAL USER {language} INPUT: 
16 |     \n"{input}"
17 |     \nCHAT HISTORY:
18 |     \n{chat_history}
19 |     \n Be sure to end your response by asking user if they need any further assistance
20 |     \n User Question: {user_message}
21 |     \n\nAI {language} GPT4 CHATBOT RESPONSE HERE:\n
22 | '''
23 | 
24 | 
25 | # Scenario Contexts
26 | 
27 | GENERAL_ASSISTANT_CONTEXT = '''
28 | General Assistant Mode: You are an all purpose coding assistant for the "{language}" programming language.
29 | '''
30 | 
31 | CORRECTION_CONTEXT = '''
32 | Correction Mode: Correct the "{language}" code the user submitted.
33 | \nAlso provide an explanation for how you corrected the code and how you implemented such a correction.
34 | '''
35 | 
36 | COMPLETION_CONTEXT = '''
37 | Completion Mode: Complete the "{language}" code the user submitted.
38 | \nThe Code may either be partially complete or have comments for what the user wants you to implement/complete.
39 | \nAlso provide an explanation for how you completed the code and how you implemented such a completion.
40 | '''
41 | 
42 | OPTIMIZATION_CONTEXT = '''
43 | Optimization Mode: Enhance the "{language}" code provided by the user for optimal performance.
44 | \nAnalyze the code thoroughly and apply optimizations to maximize efficiency.
45 | \nAlso keep in mind, code readability and maintainability.
46 | \nPlease document the optimizations made, explaining the rationale and how it contributes to code optimization.
47 | '''
48 | 
49 | SHORTENING_CONTEXT = '''
50 | Shortening Mode: Shorten the user's {language} code as much as possible, use as few characters and as fews lines
51 | as possible.
52 | '''
53 | 
54 | GENERATION_CONTEXT = '''
55 | Generation Mode: Generate {language} code based on the user input.
56 | '''
57 | 
58 | COMMENTING_CONTEXT = '''
59 | Commenting Mode: Add comments to the {language} code provided by the user.
60 | '''
61 | 
62 | EXPLANATION_CONTEXT = '''
63 | Explanation Mode: Explain the {language} code provided by the user.
64 | '''
65 | 
66 | LEETCODE_CONTEXT = '''
67 | LeetCode Solver Mode: You are given a {language} LeetCode from the user.
68 | \nNow solve that Leetcode problem 
69 | '''


--------------------------------------------------------------------------------
/AppV5/requirements.txt:
--------------------------------------------------------------------------------
 1 | aiohttp==3.8.4
 2 | aiosignal==1.3.1
 3 | altair==5.0.1
 4 | async-timeout==4.0.2
 5 | attrs==23.1.0
 6 | blinker==1.6.2
 7 | cachetools==5.3.1
 8 | certifi==2023.5.7
 9 | charset-normalizer==3.1.0
10 | click==8.1.4
11 | colorama==0.4.6
12 | dataclasses-json==0.5.9
13 | decorator==5.1.1
14 | faiss-cpu==1.7.4
15 | frozenlist==1.3.3
16 | gitdb==4.0.10
17 | GitPython==3.1.31
18 | greenlet==2.0.2
19 | idna==3.4
20 | importlib-metadata==6.7.0
21 | Jinja2==3.1.2
22 | jsonschema==4.18.0
23 | jsonschema-specifications==2023.6.1
24 | langchain==0.0.226
25 | langchainplus-sdk==0.0.20
26 | markdown-it-py==3.0.0
27 | MarkupSafe==2.1.3
28 | marshmallow==3.19.0
29 | marshmallow-enum==1.5.1
30 | mdurl==0.1.2
31 | multidict==6.0.4
32 | mypy-extensions==1.0.0
33 | numexpr==2.8.4
34 | numpy==1.25.0
35 | openai==0.27.8
36 | openapi-schema-pydantic==1.2.4
37 | packaging==23.1
38 | pandas==2.0.3
39 | Pillow==9.5.0
40 | protobuf==4.23.4
41 | pyarrow==12.0.1
42 | pydantic==1.10.11
43 | pydeck==0.8.1b0
44 | Pygments==2.15.1
45 | Pympler==1.0.1
46 | PyPDF2==3.0.1
47 | python-dateutil==2.8.2
48 | python-dotenv==1.0.0
49 | pytz==2023.3
50 | pytz-deprecation-shim==0.1.0.post0
51 | PyYAML==6.0
52 | referencing==0.29.1
53 | regex==2023.6.3
54 | requests==2.31.0
55 | rich==13.4.2
56 | rpds-py==0.8.8
57 | six==1.16.0
58 | smmap==5.0.0
59 | SQLAlchemy==2.0.18
60 | streamlit==1.24.0
61 | tenacity==8.2.2
62 | tiktoken==0.4.0
63 | toml==0.10.2
64 | toolz==0.12.0
65 | tornado==6.3.2
66 | tqdm==4.65.0
67 | typing-inspect==0.9.0
68 | typing_extensions==4.7.1
69 | tzdata==2023.3
70 | tzlocal==4.3.1
71 | urllib3==2.0.3
72 | validators==0.20.0
73 | watchdog==3.0.0
74 | yarl==1.9.2
75 | zipp==3.15.0
76 | 


--------------------------------------------------------------------------------
/AppV5/trippyPattern.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/Luis96920/GPT4-Programming-Assistant/34e61ffd199e7401d345adb165fdebb55077bbb9/AppV5/trippyPattern.png


--------------------------------------------------------------------------------
/AppV6/.env:
--------------------------------------------------------------------------------
1 | OPENAI_API_KEY=
2 | 


--------------------------------------------------------------------------------
/AppV6/htmlTemplates.py:
--------------------------------------------------------------------------------
 1 | css = '''
 2 | <style>
 3 | .chat-message {
 4 |     padding: 1.5rem; border-radius: 0.5rem; margin-bottom: 1rem; display: flex
 5 | }
 6 | .chat-message.user {
 7 |     background-color: #2b313e
 8 | }
 9 | .chat-message.bot {
10 |     background-color: #475063
11 | }
12 | .chat-message .avatar {
13 |   width: 12%;
14 | }
15 | .chat-message .avatar img {
16 |   max-width: 60px;
17 |   max-height: 60px;
18 |   border-radius: 50%;
19 |   object-fit: cover;
20 | }
21 | .chat-message .message {
22 |   width: 90%;
23 |   padding: 0 .35rem;
24 |   color: #fff;
25 | }
26 | '''
27 | 
28 | bot_template = '''
29 | <div class="chat-message bot">
30 |     <div class="avatar">
31 |         <img src="https://www.sideshow.com/storage/product-images/2171/c-3po_star-wars_square.jpg">
32 |     </div>
33 |     <div class="message">{{MSG}}</div>
34 | </div>
35 | '''
36 | 
37 | user_template = '''
38 | <div class="chat-message user">
39 |     <div class="avatar">
40 |         <img src="https://resizing.flixster.com/ocuc8yjm8Fu5UK5Ze8lbdp58m9Y=/300x300/v2/https://flxt.tmsimg.com/assets/p11759522_i_h9_aa.jpg">
41 |     </div>    
42 |     <div class="message">{{MSG}}</div>
43 | </div>
44 | '''
45 | 


--------------------------------------------------------------------------------
/AppV6/main.py:
--------------------------------------------------------------------------------
  1 | import os
  2 | from PIL import Image
  3 | from dotenv import load_dotenv
  4 | from PyPDF2 import PdfReader
  5 | import streamlit as st
  6 | from streamlit_extras.let_it_rain import rain
  7 | import openai
  8 | from langchain.text_splitter import CharacterTextSplitter
  9 | from langchain.llms import OpenAI
 10 | from langchain.memory import ConversationBufferMemory
 11 | from langchain.prompts import PromptTemplate
 12 | from langchain.embeddings import OpenAIEmbeddings
 13 | from langchain.vectorstores import FAISS
 14 | from langchain.chains import LLMChain, ConversationalRetrievalChain, RetrievalQA
 15 | from langchain.chat_models import ChatOpenAI
 16 | from htmlTemplates import css, bot_template, user_template
 17 | from prompts import CHAT_TEMPLATE, INITIAL_TEMPLATE
 18 | from prompts import CORRECTION_CONTEXT, COMPLETION_CONTEXT, OPTIMIZATION_CONTEXT, GENERAL_ASSISTANT_CONTEXT, \
 19 |     GENERATION_CONTEXT, COMMENTING_CONTEXT, EXPLANATION_CONTEXT, LEETCODE_CONTEXT, SHORTENING_CONTEXT
 20 | 
 21 | 
 22 | def page_config():
 23 |     st.set_page_config(page_title="GPT-4 Coding Asssistant", page_icon="computer")
 24 |     st.write(css, unsafe_allow_html=True)
 25 | 
 26 | 
 27 | def init_ses_states():
 28 |     st.session_state.setdefault('chat_history', [])
 29 |     st.session_state.setdefault('initial_input', "")
 30 |     st.session_state.setdefault("initial_context", "")
 31 |     st.session_state.setdefault('scenario_context', "")
 32 |     st.session_state.setdefault('docs_processed', False)
 33 |     st.session_state.setdefault('docs_chain', None)
 34 |     st.session_state.setdefault('user_authenticated', False)
 35 | 
 36 | 
 37 | def page_title_header():
 38 |     top_image = Image.open('trippyPattern.png')
 39 |     st.image(top_image)
 40 |     st.title("GPT-4 Coding Assistant")
 41 |     st.caption("Powered by OpenAI, LangChain, Streamlit")
 42 | 
 43 | 
 44 | def get_pdf_text(pdf_docs):
 45 |     text = ""
 46 |     for pdf in pdf_docs:
 47 |         pdf_reader = PdfReader(pdf)
 48 |         for page in pdf_reader.pages:
 49 |             text += page.extract_text()
 50 |     return text
 51 | 
 52 | 
 53 | def get_text_chunks(text):
 54 |     text_splitter = CharacterTextSplitter(
 55 |         separator="\n",
 56 |         chunk_size=1000,
 57 |         chunk_overlap=200,
 58 |         length_function=len
 59 |     )
 60 |     chunks = text_splitter.split_text(text)
 61 |     return chunks
 62 | 
 63 | 
 64 | def get_vectorstore(text_chunks):
 65 |     embeddings = OpenAIEmbeddings()
 66 |     vectorstore = FAISS.from_texts(texts=text_chunks, embedding=embeddings)
 67 |     return vectorstore
 68 | 
 69 | 
 70 | def create_retrieval_chain(vectorstore):
 71 |     llm = ChatOpenAI(temperature=temperature, model_name=model)
 72 |     memory = ConversationBufferMemory(memory_key='chat_history', return_messages=True)
 73 |     conversation_chain = ConversationalRetrievalChain.from_llm(
 74 |         llm=llm,
 75 |         retriever=vectorstore.as_retriever(),
 76 |         memory=memory
 77 |     )
 78 |     return conversation_chain
 79 | 
 80 | 
 81 | def create_llm_chain(prompt_template):
 82 |     memory = ConversationBufferMemory(input_key="input", memory_key="chat_history", )
 83 |     llm = OpenAI(temperature=temperature, model_name=model)
 84 |     return LLMChain(llm=llm, prompt=prompt_template, memory=memory)
 85 | 
 86 | 
 87 | def sidebar():
 88 |     global language, scenario, temperature, model, scenario_context, libraries, pdf_docs
 89 |     languages = sorted(['Python', 'GoLang','TypeScript', 'JavaScript', 'Java', 'C', 'C++', 'C#', 'R', 'SQL'])
 90 |     python_libs = sorted(["Pandas",'Numpy','Scipy','Scikit-Learn','PyTorch','TensorFlow','Streamlit','Flask','FastAPI'])
 91 |     scenarios = ['General Assistant', 'Code Correction', 'Code Completion', 'Code Commenting', 'Code Optimization', 
 92 |                  'Code Shortener','Code Generation', 'Code Explanation', 'LeetCode Solver']
 93 |     scenario_context_map = {
 94 |         "Code Correction": CORRECTION_CONTEXT,
 95 |         "Code Completion": COMPLETION_CONTEXT,
 96 |         "Code Optimization": OPTIMIZATION_CONTEXT,
 97 |         "General Assistant": GENERAL_ASSISTANT_CONTEXT,
 98 |         "Code Generation": GENERATION_CONTEXT,
 99 |         "Code Commenting": COMMENTING_CONTEXT,
100 |         "Code Explanation": EXPLANATION_CONTEXT,
101 |         "LeetCode Solver": LEETCODE_CONTEXT,
102 |         "Code Shortener": SHORTENING_CONTEXT,
103 |     }
104 | 
105 |     with st.sidebar:
106 |         with st.expander(label="Coding Settings", expanded=True):
107 |             language = st.selectbox(label="Language", options=languages, index=0)
108 |             if language == "Python":
109 |                 libraries = st.multiselect(label="Libraries",options=python_libs)
110 |             else:
111 |                 libraries=""
112 |             scenario = st.selectbox(label="Scenario", options=scenarios, index=0)
113 |             scenario_context = scenario_context_map.get(scenario, "")
114 |         
115 |         with st.expander("Chatbot Settings", expanded=True):
116 |             model = st.selectbox("Language Model", options=['gpt-4','gpt-4-0613','gpt-3.5-turbo'])
117 |             temperature = st.slider(label="Temperature", min_value=0.0, max_value=1.0, value=0.5)
118 |         
119 |         with st.expander(label="User Docs",expanded=True):
120 |             pdf_docs = st.file_uploader("Upload Docs Here",type=['PDF'],accept_multiple_files=True)
121 |             if pdf_docs:
122 |                 if st.button("Process Docs"):
123 |                     raw_text = get_pdf_text(pdf_docs)
124 |                     text_chunks = get_text_chunks(raw_text)
125 |                     vectorstore = get_vectorstore(text_chunks)
126 |                     initial_llm_chain = create_retrieval_chain(vectorstore=vectorstore)
127 |                     st.session_state.docs_chain = initial_llm_chain
128 |                     st.session_state.docs_processed = True
129 |                     st.write("Docs Succesfully Processed")
130 |             else:
131 |                 st.session_state.docs_processed = False
132 | 
133 | 
134 | def display_convo():
135 |     with st.container():
136 |         for i, message in enumerate(reversed(st.session_state.chat_history)):
137 |             if i % 2 == 0:
138 |                  st.markdown(bot_template.replace("{{MSG}}", message), unsafe_allow_html=True)
139 |             else:
140 |                 st.markdown(user_template.replace("{{MSG}}", message), unsafe_allow_html=True)
141 | 
142 | 
143 | def handle_initial_submit():
144 |     global code_input, code_context
145 |     initial_template = PromptTemplate(
146 |         input_variables=['input','language','scenario','scenario_context','code_context','libraries'],
147 |         template= INITIAL_TEMPLATE
148 |     )
149 |     if pdf_docs and st.session_state.docs_processed:
150 |         initial_llm_chain =st.session_state.docs_chain
151 |     else:
152 |         initial_llm_chain = create_llm_chain(prompt_template=initial_template)
153 |     code_input = st.text_area(label=f"User Code", height=300)
154 |     code_context = st.text_area(label="Additional Context", height=60)
155 |     if (st.button(f'Submit Initial Input') and (code_input or code_context)):
156 |         st.session_state.initial_input = code_input
157 |         st.session_state.initial_context = code_context
158 |         st.session_state['chat_history'] = []
159 |         with st.spinner('Generating Response...'):
160 |             if st.session_state.docs_processed:
161 |                 llm_input = initial_template.format(input=code_input,
162 |                                                 code_context=code_context, 
163 |                                                 language=language, 
164 |                                                 scenario=scenario,
165 |                                                 scenario_context=scenario_context,
166 |                                                 libraries=libraries)
167 |                 initial_response = initial_llm_chain({'question':llm_input})['answer']
168 |             else: 
169 |                 initial_response = initial_llm_chain.run(input=code_input,
170 |                                                         code_context=code_context, 
171 |                                                         language=language, 
172 |                                                         scenario=scenario,
173 |                                                         scenario_context=scenario_context,
174 |                                                         libraries=libraries)
175 |         st.session_state.chat_history.append(f"AI: {initial_response}")
176 | 
177 | 
178 | def handle_user_message():
179 |     chat_template = PromptTemplate(
180 |         input_variables=['input','code_context','user_message','language','scenario','scenario_context','chat_history','libraries'],
181 |         template=CHAT_TEMPLATE
182 |     )
183 |     if st.session_state.docs_processed:
184 |         chat_llm_chain = st.session_state.docs_chain
185 |     else:
186 |         chat_llm_chain = create_llm_chain(prompt_template=chat_template)
187 |     if st.session_state.chat_history:
188 |         user_message = st.text_area("Further Questions for Coding AI?", key="user_input", height=60)
189 |         if st.button("Submit Message") and user_message:
190 |             st.session_state['chat_history'].append(f"USER: {user_message}\n")
191 |             with st.spinner('Generating Response...'):
192 |                 if st.session_state.docs_processed: # Fix this
193 |                     chat_input = chat_template.format(input=st.session_state.initial_input,
194 |                                                     code_context=st.session_state.initial_context,
195 |                                                     user_message=user_message, 
196 |                                                     language=language, 
197 |                                                     scenario=scenario,
198 |                                                     scenario_context=scenario_context,
199 |                                                     libraries=libraries)
200 |                     chat_response = chat_llm_chain({'question':chat_input})['answer']
201 |                 else:
202 |                     chat_response = chat_llm_chain.run(input=st.session_state['initial_input'],
203 |                                                         user_message=user_message,
204 |                                                         code_context=st.session_state.initial_context,
205 |                                                         language=language, 
206 |                                                         scenario=scenario,
207 |                                                         scenario_context=scenario_context,
208 |                                                         chat_history=st.session_state.chat_history,
209 |                                                         libraries=libraries)
210 |                 st.session_state['chat_history'].append(f"AI: {chat_response}\n")
211 | 
212 | 
213 | def display_file_code(filename):
214 |     with open(filename, "r") as file:
215 |         with st.expander(filename, expanded=False):
216 |             st.code(file.read(), language='python')
217 | 
218 | 
219 | def display_all_code():
220 |     st.subheader("GitHub Link")
221 |     st.write("https://github.com/petermartens98/GPT4-Programming-Assistant")
222 |     st.subheader("Source Code")
223 |     files = ["main.py", "htmlTemplates.py", "prompts.py", "requirements.txt"]
224 |     for file in files:
225 |         display_file_code(file)
226 | 
227 | 
228 | def main():
229 |     page_config()
230 |     init_ses_states()
231 |     page_title_header()
232 |     sidebar()
233 |     if st.session_state.docs_processed:
234 |         deploy_tab, code_tab, docs_tab = st.tabs(['Deployment','Source Code','Doc Analysis'])
235 |         with docs_tab:
236 |             st.caption("Coming Soon")
237 |     else:
238 |         deploy_tab, code_tab = st.tabs(['Deployment','Source Code'])
239 |     with deploy_tab:
240 |         handle_initial_submit()
241 |         handle_user_message()
242 |         display_convo()
243 |     with code_tab: 
244 |         display_all_code()
245 | 
246 | 
247 | if __name__ == '__main__':
248 |     load_dotenv()
249 |     main()
250 | 
251 | 


--------------------------------------------------------------------------------
/AppV6/prompts.py:
--------------------------------------------------------------------------------
 1 | INITIAL_TEMPLATE = '''
 2 |     You are a GPT-4 AI Coding Assistant specializing in the "{language}" programming language.
 3 |     \nAlso consider these additional {language} librarieS: {libraries}
 4 |     \nAlthough your main language is {language}, you should draw inspiration from all possible sources.
 5 |     \nYou should come as helpful, confindent, multifunctional, and welcoming.
 6 |     \nThe user has specified the mode to "{scenario}"
 7 |     \n{scenario} SCENARIO CONTEXT: {scenario_context}
 8 |     \nUSER {language} CODE INPUT: 
 9 |     \n{input}
10 |     \nADDITIONAL CONTEXT FROM USER: {code_context}
11 |     \nBefore returning your response be sure its the best and most optimal solution.
12 |     \nAfter your coding response, be sure to end your chat response by asking user if they need any further assistance
13 |     \n\nAI {language} GPT4 CHATBOT RESPONSE HERE:\n
14 | '''
15 | 
16 | 
17 | CHAT_TEMPLATE = '''
18 |     You are a GPT-4 AI Coding Assistant specializing in the "{language}" programming language.
19 |     \nAlso consider these additional {language} librarieS: {libraries}
20 |     \nYou should come as helpful, confindent, multifunctional, and welcoming.
21 |     \nThe user has specified the mode to "Code {scenario}"
22 |     \n{scenario} SCENARIO CONTEXT: {scenario_context}
23 |     \nINITIAL USER {language} INPUT: 
24 |     \n"{input}"
25 |     \nCHAT HISTORY:
26 |     \n{chat_history}
27 |     \nADDITIONAL CONTEXT FROM USER: {code_context}
28 |     \n Be sure to end your response by asking user if they need any further assistance
29 |     \n User Question: {user_message}
30 |     \n\nAI {language} GPT4 CHATBOT RESPONSE HERE:\n
31 | '''
32 | 
33 | 
34 | # Scenario Contexts
35 | 
36 | GENERAL_ASSISTANT_CONTEXT = '''
37 | General Assistant Mode: You are an all purpose coding assistant for the "{language}" programming language.
38 | '''
39 | 
40 | CORRECTION_CONTEXT = '''
41 | Correction Mode: Correct the "{language}" code the user submitted.
42 | \nIdentify and rectify any errors while maintaining the intended functionality of the code.
43 | \nAnalyze and optimize user syntax
44 | \nAdd or remove any code necessary to fix and corrext the user code
45 | \nAlso provide an explanation for how you corrected the code and how you implemented such a correction.
46 | '''
47 | 
48 | COMPLETION_CONTEXT = '''
49 | Completion Mode: Complete the "{language}" code the user submitted.
50 | \nThe Code may either be partially complete or have comments for what the user wants you to implement/complete.
51 | \nAlso provide an explanation for how you completed the code and how you implemented such a completion.
52 | '''
53 | 
54 | OPTIMIZATION_CONTEXT = '''
55 | Optimization Mode: Enhance the "{language}" code provided by the user for optimal performance.
56 | \nAnalyze the code thoroughly and apply optimizations to maximize efficiency.
57 | \nAlso keep in mind, code readability and maintainability.
58 | \nPlease document the optimizations made, explaining the rationale and how it contributes to code optimization.
59 | '''
60 | 
61 | SHORTENING_CONTEXT = '''
62 | Shortening Mode: Shorten the user's {language} code as much as possible, use as few characters and as fews lines
63 | as possible.
64 | '''
65 | 
66 | GENERATION_CONTEXT = '''
67 | Generation Mode: Generate {language} code based on the user input.
68 | '''
69 | 
70 | COMMENTING_CONTEXT = '''
71 | Commenting Mode: Add comments to the {language} code provided by the user.
72 | '''
73 | 
74 | EXPLANATION_CONTEXT = '''
75 | Explanation Mode: Explain the {language} code provided by the user.
76 | '''
77 | 
78 | LEETCODE_CONTEXT = '''
79 | LeetCode Solver Mode: You have been provided with a LeetCode problem in {language} by the user.
80 | \nCarefully analyze the problem statement.
81 | \nMake sure to thoroughly understand the problem requirements and constraints.
82 | \nConsider any edge cases that may arise and handle them appropriately
83 | \nEfficiency and correctness are crucial in solving LeetCode problems. Therefore, strive to optimize your 
84 | solution by considering time and space complexities. Your goal is to produce a solution that is both accurate and efficient.
85 | \nConsider multiple solutions to the problem and go with the most optimal solution
86 | \nAfter you come up with a solution, be sure to shorten and optimize
87 | \nNow proceed to solve the user-submitted LeetCode problem.
88 | '''
89 | 
90 | DAN_PROMPT = '''
91 | coming soon
92 | '''
93 | 
94 | # Incorrect code generator prompt
95 | 
96 | # Multiple Choice Solver and Generator


--------------------------------------------------------------------------------
/AppV6/requirements.txt:
--------------------------------------------------------------------------------
 1 | aiohttp==3.8.4
 2 | aiosignal==1.3.1
 3 | altair==5.0.1
 4 | async-timeout==4.0.2
 5 | attrs==23.1.0
 6 | blinker==1.6.2
 7 | cachetools==5.3.1
 8 | certifi==2023.5.7
 9 | charset-normalizer==3.1.0
10 | click==8.1.4
11 | colorama==0.4.6
12 | dataclasses-json==0.5.9
13 | decorator==5.1.1
14 | faiss-cpu==1.7.4
15 | frozenlist==1.3.3
16 | gitdb==4.0.10
17 | GitPython==3.1.31
18 | greenlet==2.0.2
19 | idna==3.4
20 | importlib-metadata==6.7.0
21 | Jinja2==3.1.2
22 | jsonschema==4.18.0
23 | jsonschema-specifications==2023.6.1
24 | langchain==0.0.226
25 | langchainplus-sdk==0.0.20
26 | markdown-it-py==3.0.0
27 | MarkupSafe==2.1.3
28 | marshmallow==3.19.0
29 | marshmallow-enum==1.5.1
30 | mdurl==0.1.2
31 | multidict==6.0.4
32 | mypy-extensions==1.0.0
33 | numexpr==2.8.4
34 | numpy==1.25.0
35 | openai==0.27.8
36 | openapi-schema-pydantic==1.2.4
37 | packaging==23.1
38 | pandas==2.0.3
39 | Pillow==9.5.0
40 | protobuf==4.23.4
41 | pyarrow==12.0.1
42 | pydantic==1.10.11
43 | pydeck==0.8.1b0
44 | Pygments==2.15.1
45 | Pympler==1.0.1
46 | PyPDF2==3.0.1
47 | python-dateutil==2.8.2
48 | python-dotenv==1.0.0
49 | pytz==2023.3
50 | pytz-deprecation-shim==0.1.0.post0
51 | PyYAML==6.0
52 | referencing==0.29.1
53 | regex==2023.6.3
54 | requests==2.31.0
55 | rich==13.4.2
56 | rpds-py==0.8.8
57 | six==1.16.0
58 | smmap==5.0.0
59 | SQLAlchemy==2.0.18
60 | streamlit==1.24.0
61 | tenacity==8.2.2
62 | tiktoken==0.4.0
63 | toml==0.10.2
64 | toolz==0.12.0
65 | tornado==6.3.2
66 | tqdm==4.65.0
67 | typing-inspect==0.9.0
68 | typing_extensions==4.7.1
69 | tzdata==2023.3
70 | tzlocal==4.3.1
71 | urllib3==2.0.3
72 | validators==0.20.0
73 | watchdog==3.0.0
74 | yarl==1.9.2
75 | zipp==3.15.0
76 | 


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/AppV6/trippyPattern.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/Luis96920/GPT4-Programming-Assistant/34e61ffd199e7401d345adb165fdebb55077bbb9/AppV6/trippyPattern.png


--------------------------------------------------------------------------------
/AppV7/.env:
--------------------------------------------------------------------------------
1 | OPENAI_API_KEY=
2 | 


--------------------------------------------------------------------------------
/AppV7/db_functions.py:
--------------------------------------------------------------------------------
  1 | import sqlite3
  2 | 
  3 | 
  4 | def create_users_db():
  5 |     conn = sqlite3.connect('MASTER.db')
  6 |     cursor = conn.cursor()
  7 |     cursor.execute("""
  8 |         CREATE TABLE IF NOT EXISTS Users (
  9 |             user_id INTEGER PRIMARY KEY AUTOINCREMENT,
 10 |             email TEXT,
 11 |             password TEXT
 12 |         )
 13 |     """)
 14 |     conn.commit()
 15 |     conn.close()
 16 | 
 17 | 
 18 | def create_messages_db():
 19 |     conn = sqlite3.connect('MASTER.db')
 20 |     cursor = conn.cursor()
 21 |     cursor.execute("""
 22 |         CREATE TABLE IF NOT EXISTS Messages (
 23 |             message_id INTEGER PRIMARY KEY AUTOINCREMENT,
 24 |             thread_id TEXT,
 25 |             role TEXT,
 26 |             message TEXT,
 27 |             user_id INTEGER,
 28 |             FOREIGN KEY(user_id) REFERENCES Users(user_id)
 29 |         )
 30 |     """)
 31 |     conn.commit()
 32 |     conn.close()
 33 | 
 34 | 
 35 | def write_to_messages_db(thread_id, role, message):
 36 |     conn = sqlite3.connect('MASTER.db')
 37 |     cursor = conn.cursor()
 38 |     insert_query = """
 39 |         INSERT INTO Messages (thread_id, role, message)
 40 |         VALUES (?, ?, ?)
 41 |     """
 42 |     cursor.execute(insert_query, (thread_id, role, message))
 43 |     conn.commit()
 44 |     conn.close()
 45 | 
 46 | 
 47 | def get_all_thread_messages(thread_id):
 48 |     conn = sqlite3.connect('MASTER.db')
 49 |     cursor = conn.cursor()
 50 |     cursor.execute('''SELECT message 
 51 |                       FROM Messages
 52 |                       WHERE thread_id = ?
 53 |                       ORDER BY message_id''', (thread_id,))
 54 |     rows = cursor.fetchall()
 55 |     conn.close()
 56 |     return [i[0] for i in rows]
 57 | 
 58 | 
 59 | def get_unique_thread_ids():
 60 |     conn = sqlite3.connect('MASTER.db')
 61 |     cursor = conn.cursor()
 62 |     cursor.execute("SELECT DISTINCT thread_id FROM Messages")
 63 |     unique_thread_ids = reversed([row[0] for row in cursor.fetchall()])
 64 |     conn.close()
 65 |     return unique_thread_ids
 66 | 
 67 | 
 68 | def create_documents_db():
 69 |     pass
 70 | 
 71 | 
 72 | def get_uploaded_doc_names():
 73 |     pass
 74 | 
 75 | 
 76 | def add_user_to_db(email, password):
 77 |     conn = sqlite3.connect('MASTER.db')
 78 |     cursor = conn.cursor()
 79 |     insert_query = """
 80 |         INSERT INTO Users (email, password)
 81 |         VALUES (?, ?)
 82 |     """
 83 |     cursor.execute(insert_query, (email, password))
 84 |     conn.commit()
 85 |     conn.close()
 86 | 
 87 | 
 88 | def authenticate_user(email, password):
 89 |     conn = sqlite3.connect('MASTER.db')
 90 |     cursor = conn.cursor()
 91 |     select_query = """
 92 |         SELECT * FROM Users WHERE email = ? AND password = ?
 93 |     """
 94 |     cursor.execute(select_query, (email, password))
 95 |     user = cursor.fetchone()
 96 |     conn.close()
 97 |     if user:
 98 |         return True
 99 |     else:
100 |         return False


--------------------------------------------------------------------------------
/AppV7/htmlTemplates.py:
--------------------------------------------------------------------------------
 1 | css = '''
 2 | <style>
 3 | .chat-message {
 4 |     padding: 1.5rem; border-radius: 0.5rem; margin-bottom: 1rem; display: flex
 5 | }
 6 | .chat-message.user {
 7 |     background-color: #2b313e
 8 | }
 9 | .chat-message.bot {
10 |     background-color: #475063
11 | }
12 | .chat-message .avatar {
13 |   width: 12%;
14 | }
15 | .chat-message .avatar img {
16 |   max-width: 60px;
17 |   max-height: 60px;
18 |   border-radius: 50%;
19 |   object-fit: cover;
20 | }
21 | .chat-message .message {
22 |   width: 90%;
23 |   padding: 0 .35rem;
24 |   color: #fff;
25 | }
26 | '''
27 | 
28 | bot_template = '''
29 | <div class="chat-message bot">
30 |     <div class="avatar">
31 |         <img src="https://www.sideshow.com/storage/product-images/2171/c-3po_star-wars_square.jpg">
32 |     </div>
33 |     <div class="message">{{MSG}}</div>
34 | </div>
35 | '''
36 | 
37 | user_template = '''
38 | <div class="chat-message user">
39 |     <div class="avatar">
40 |         <img src="https://resizing.flixster.com/ocuc8yjm8Fu5UK5Ze8lbdp58m9Y=/300x300/v2/https://flxt.tmsimg.com/assets/p11759522_i_h9_aa.jpg">
41 |     </div>    
42 |     <div class="message">{{MSG}}</div>
43 | </div>
44 | '''
45 | 


--------------------------------------------------------------------------------
/AppV7/main.py:
--------------------------------------------------------------------------------
  1 | import os
  2 | import re
  3 | from PIL import Image
  4 | from dotenv import load_dotenv
  5 | from PyPDF2 import PdfReader
  6 | import sqlite3
  7 | import streamlit as st
  8 | from werkzeug.utils import secure_filename
  9 | import openai
 10 | from langchain.text_splitter import CharacterTextSplitter
 11 | from langchain.llms import OpenAI
 12 | from langchain.memory import ConversationBufferMemory
 13 | from langchain.prompts import PromptTemplate
 14 | from langchain.embeddings import OpenAIEmbeddings
 15 | from langchain.vectorstores import FAISS
 16 | from langchain.chains import LLMChain, ConversationalRetrievalChain, RetrievalQA
 17 | from langchain.chat_models import ChatOpenAI
 18 | from htmlTemplates import css, bot_template, user_template
 19 | from db_functions import create_users_db, create_messages_db, create_documents_db, write_to_messages_db, get_all_thread_messages, \
 20 |     get_unique_thread_ids, get_uploaded_doc_names, add_user_to_db, authenticate_user
 21 | from prompts import CHAT_TEMPLATE, INITIAL_TEMPLATE
 22 | from prompts import CORRECTION_CONTEXT, COMPLETION_CONTEXT, OPTIMIZATION_CONTEXT, GENERAL_ASSISTANT_CONTEXT, \
 23 |     GENERATION_CONTEXT, COMMENTING_CONTEXT, EXPLANATION_CONTEXT, LEETCODE_CONTEXT, SHORTENING_CONTEXT
 24 | 
 25 | 
 26 | # TODO: Create Password Encryption Function
 27 | 
 28 | 
 29 | # TODO: Create Password Deryption Function
 30 | 
 31 | 
 32 | def page_config():
 33 |     st.set_page_config(page_title="GPT-4 Coding Asssistant", page_icon="computer")
 34 |     st.write(css, unsafe_allow_html=True)
 35 | 
 36 | 
 37 | def init_ses_states():
 38 |     default_values = {
 39 |         'chat_history': [],
 40 |         'initial_input': "",
 41 |         'initial_context': "",
 42 |         'scenario_context': "",
 43 |         'thread_id': "",
 44 |         'docs_processed': False,
 45 |         'docs_chain': None,
 46 |         'user_authenticated': False,
 47 |         'uploaded_docs': None,
 48 |         'current_user_id': None
 49 |     }
 50 |     for key, value in default_values.items():
 51 |         st.session_state.setdefault(key, value)
 52 | # Get Current Users User ID
 53 | 
 54 | 
 55 | def page_title_header():
 56 |     top_image = Image.open('trippyPattern.png')
 57 |     st.image(top_image)
 58 |     st.title("GPT-4 Coding Assistant")
 59 |     st.caption("Powered by OpenAI, LangChain, Streamlit")
 60 | 
 61 | 
 62 | def get_pdf_text(pdf_docs):
 63 |     text = ""
 64 |     for pdf in pdf_docs:
 65 |         pdf_reader = PdfReader(pdf)
 66 |         for page in pdf_reader.pages:
 67 |             text += page.extract_text()
 68 |     return text
 69 | 
 70 | 
 71 | def get_text_chunks(text):
 72 |     text_splitter = CharacterTextSplitter(
 73 |         separator="\n",
 74 |         chunk_size=1000,
 75 |         chunk_overlap=200,
 76 |         length_function=len
 77 |     )
 78 |     chunks = text_splitter.split_text(text)
 79 |     return chunks
 80 | 
 81 | 
 82 | def get_vectorstore(text_chunks):
 83 |     embeddings = OpenAIEmbeddings()
 84 |     vectorstore = FAISS.from_texts(texts=text_chunks, embedding=embeddings)
 85 |     return vectorstore
 86 | 
 87 | 
 88 | def create_retrieval_chain(vectorstore):
 89 |     llm = ChatOpenAI(temperature=temperature, model_name=model)
 90 |     memory = ConversationBufferMemory(memory_key='chat_history', return_messages=True)
 91 |     conversation_chain = ConversationalRetrievalChain.from_llm(
 92 |         llm=llm,
 93 |         retriever=vectorstore.as_retriever(),
 94 |         memory=memory
 95 |     )
 96 |     return conversation_chain
 97 | 
 98 | 
 99 | def create_llm_chain(prompt_template):
100 |     memory = ConversationBufferMemory(input_key="input", memory_key="chat_history", )
101 |     llm = OpenAI(temperature=temperature, model_name=model)
102 |     return LLMChain(llm=llm, prompt=prompt_template, memory=memory)
103 | 
104 | 
105 | def approve_password(password):
106 |     if len(password) >= 8 and re.search(r"(?=.*[a-z])(?=.*[A-Z])(?=.*[0-9])(?=.*[_@$#!?&*%])", password):
107 |         return True
108 |     return False
109 |     
110 | 
111 | def approve_email(email):
112 |     email_regex = '^[a-zA-Z0-9]+[\._]?[a-zA-Z0-9]+[@]\w+[.]\w{2,3}$'
113 |     if re.search(email_regex, email):
114 |         return True
115 |     else:
116 |         return False
117 | 
118 | 
119 | def user_authentication_tab():
120 |     with st.expander("User Authentication", expanded=True):
121 |         login_tab, create_account_tab = st.tabs(["Login", "Create Account"])
122 | 
123 |         with login_tab:
124 |             email = st.text_input("Email:") 
125 |             password = st.text_input("Password:", type='password')
126 |             if st.button("Login"):
127 |                 if authenticate_user(email=email,password=password):
128 |                     st.session_state.user_authenticated = True
129 |                 else:
130 |                     st.caption('Incorrect Username or Password.')
131 | 
132 |             if st.session_state.user_authenticated:
133 |                 st.caption("User Authenticated")
134 | 
135 |         with create_account_tab:
136 |             new_email = st.text_input("New Email:")
137 |             new_password = st.text_input("New Password:", type='password')
138 |             confirm_password = st.text_input("Confirm Password:", type='password')
139 |             if st.button("Create Account"):
140 |                 if not approve_email(new_email):
141 |                     st.caption("Invalid Email")
142 |                     return
143 |                 if not approve_password(new_password):
144 |                     st.caption("Invalid Password")
145 |                     return
146 |                 if new_password != confirm_password:
147 |                     st.caption("Passwords do not match")
148 |                     return
149 |                 add_user_to_db(email=new_email, password=new_password)
150 |                 st.caption(f"{new_email} Successfully Added")
151 | 
152 | 
153 | def sidebar():
154 |     global language, scenario, temperature, model, scenario_context, libraries, pdf_docs, uploaded_docs
155 |     languages = sorted(['Python', 'GoLang','TypeScript', 'JavaScript', 'Java', 'C', 'C++', 'C#', 'R', 'SQL'])
156 |     python_libs = sorted(['SQLite','PyGame','Seaborn',"Pandas",'Numpy','Scipy','Scikit-Learn','PyTorch','TensorFlow','Streamlit','Flask','FastAPI'])
157 |     scenarios = ['General Assistant', 'Code Correction', 'Code Completion', 'Code Commenting', 'Code Optimization', 
158 |                  'Code Shortener','Code Generation', 'Code Explanation', 'LeetCode Solver']
159 |     scenario_context_map = {
160 |         "Code Correction": CORRECTION_CONTEXT,
161 |         "Code Completion": COMPLETION_CONTEXT,
162 |         "Code Optimization": OPTIMIZATION_CONTEXT,
163 |         "General Assistant": GENERAL_ASSISTANT_CONTEXT,
164 |         "Code Generation": GENERATION_CONTEXT,
165 |         "Code Commenting": COMMENTING_CONTEXT,
166 |         "Code Explanation": EXPLANATION_CONTEXT,
167 |         "LeetCode Solver": LEETCODE_CONTEXT,
168 |         "Code Shortener": SHORTENING_CONTEXT,
169 |     }
170 | 
171 |     with st.sidebar:
172 |         user_authentication_tab()
173 |         if st.session_state.user_authenticated:
174 |             with st.expander(label="Settings",expanded=True):
175 |                 coding_settings_tab, chatbot_settings_tab = st.tabs(['Coding','ChatBot'])
176 |                 with coding_settings_tab:
177 |                     language = st.selectbox(label="Language", options=languages)
178 |                     if language == "Python":
179 |                         libraries = st.multiselect(label="Libraries",options=python_libs)
180 |                         if not libraries:
181 |                             libraries = ""
182 |                     else:
183 |                         libraries=""
184 |                     scenario = st.selectbox(label="Scenario", options=scenarios, index=0)
185 |                     scenario_context = scenario_context_map.get(scenario, "")
186 |             
187 |                 with chatbot_settings_tab:
188 |                     model = st.selectbox("Language Model", options=['gpt-4-0613','gpt-4','gpt-3.5-turbo'])
189 |                     temperature = st.slider(label="Temperature", min_value=0.0, max_value=1.0, value=0.5)
190 |             
191 |             with st.expander(label="Embed Documents",expanded=True):
192 |                 pdf_docs = st.file_uploader("Upload Docs Here",type=['PDF'],accept_multiple_files=True)
193 |                 if pdf_docs:
194 |                     if st.button("Process Docs"):
195 |                         st.session_state.uploaded_docs = pdf_docs
196 |                         raw_text = get_pdf_text(pdf_docs)
197 |                         text_chunks = get_text_chunks(raw_text)
198 |                         vectorstore = get_vectorstore(text_chunks)
199 |                         initial_llm_chain = create_retrieval_chain(vectorstore=vectorstore)
200 |                         st.session_state.docs_chain = initial_llm_chain
201 |                         st.session_state.docs_processed = True
202 |                 else:
203 |                     st.session_state.docs_processed = False
204 |                 if st.session_state.docs_processed:
205 |                     st.write("Docs Succesfully Processed:")
206 |                     for i, pdf in enumerate(st.session_state.uploaded_docs):
207 |                         st.caption(f"{i+1}. {str(secure_filename(pdf.name))}")
208 |             
209 |             with st.expander("Previous Chats", expanded=True):
210 |                 selected_thread_id = st.selectbox(label="Previous Thread IDs", options=get_unique_thread_ids(), index=0)
211 |                 if st.button("Render Chat"):
212 |                     st.session_state.thread_id = selected_thread_id
213 |                     st.session_state.chat_history = get_all_thread_messages(selected_thread_id)
214 |                     st.experimental_rerun()
215 | 
216 |         else:
217 |             st.write("Login for additional features")
218 | 
219 | 
220 | def display_convo():
221 |     with st.container():
222 |         for i, message in enumerate(reversed(st.session_state.chat_history)):
223 |             if i % 2 == 0:
224 |                 st.markdown(bot_template.replace("{{MSG}}", message), unsafe_allow_html=True)
225 |             else:
226 |                 st.markdown(user_template.replace("{{MSG}}", message), unsafe_allow_html=True)
227 | 
228 | 
229 | def handle_initial_submit():
230 |     global code_input, code_context
231 |     initial_template = PromptTemplate(
232 |         input_variables=['input','language','scenario','scenario_context','code_context','libraries'],
233 |         template= INITIAL_TEMPLATE
234 |     )
235 |     if pdf_docs and st.session_state.docs_processed:
236 |         initial_llm_chain =st.session_state.docs_chain
237 |     else:
238 |         initial_llm_chain = create_llm_chain(prompt_template=initial_template)
239 |     code_input = st.text_area(label=f"User Code", height=200)
240 |     code_context = st.text_area(label="Additional Context", height=60)
241 |     if (st.button(f'Submit Initial Input') and (code_input or code_context)):
242 |         with st.spinner('Generating Response...'):
243 |             if st.session_state.docs_processed:
244 |                 llm_input = initial_template.format(input=code_input,
245 |                                                 code_context=code_context, 
246 |                                                 language=language, 
247 |                                                 scenario=scenario,
248 |                                                 scenario_context=scenario_context,
249 |                                                 libraries=libraries)
250 |                 initial_response = initial_llm_chain({'question':llm_input})['answer']
251 |             else: 
252 |                 initial_response = initial_llm_chain.run(input=code_input,
253 |                                                         code_context=code_context, 
254 |                                                         language=language, 
255 |                                                         scenario=scenario,
256 |                                                         scenario_context=scenario_context,
257 |                                                         libraries=libraries)
258 |         st.session_state.update({
259 |             'initial_input': code_input,
260 |             'initial_context': code_context,
261 |             'chat_history': [f"USER: CODE CONTEXT:{code_context} CODE INPUT: {code_input}", f"AI: {initial_response}"],
262 |         })
263 |         st.session_state.thread_id = (code_context+code_input)[:40]
264 |         write_to_messages_db(thread_id=st.session_state.thread_id, 
265 |                              role='USER',
266 |                              message=f"USER: CODE CONTEXT:{code_context} CODE INPUT: {code_input}"
267 |                             )
268 |         write_to_messages_db(thread_id=st.session_state.thread_id, 
269 |                              role='AI',
270 |                              message=f"AI: {initial_response}"
271 |                             )
272 | 
273 | 
274 | def handle_user_message():
275 |     chat_template = PromptTemplate(
276 |         input_variables=['input','language','scenario','scenario_context','chat_history','libraries','code_input','code_context','most_recent_ai_message'],
277 |         template=CHAT_TEMPLATE
278 |     )
279 |     if st.session_state.docs_processed:
280 |         chat_llm_chain = st.session_state.docs_chain
281 |     else:
282 |         chat_llm_chain = create_llm_chain(prompt_template=chat_template)
283 |     if st.session_state.chat_history:
284 |         user_message = st.text_area("Further Questions for Coding AI?", key="user_input", height=60)
285 |         if st.button("Submit Message") and user_message:
286 |             with st.spinner('Generating Response...'):
287 |                 most_recent_ai_message = st.session_state.chat_history[-1]
288 |                 if st.session_state.docs_processed:
289 |                     chat_input = chat_template.format(input=user_message, 
290 |                                                     language=language, 
291 |                                                     scenario=scenario,
292 |                                                     scenario_context=scenario_context,
293 |                                                     libraries=libraries,
294 |                                                     code_input=st.session_state.initial_input,
295 |                                                     code_context=st.session_state.initial_context,
296 |                                                     most_recent_ai_message=most_recent_ai_message)
297 |                     chat_response = chat_llm_chain({'question':chat_input})['answer']
298 |                 else:
299 |                     chat_response = chat_llm_chain.run(input=user_message,
300 |                                                         language=language, 
301 |                                                         scenario=scenario,
302 |                                                         scenario_context=scenario_context,
303 |                                                         chat_history=st.session_state.chat_history,
304 |                                                         libraries=libraries,
305 |                                                         code_input=st.session_state.initial_input,
306 |                                                         code_context=st.session_state.initial_context,
307 |                                                         most_recent_ai_message=most_recent_ai_message)
308 |                 st.session_state['chat_history'].append(f"USER: {user_message}")
309 |                 st.session_state['chat_history'].append(f"AI: {chat_response}")
310 |                 write_to_messages_db(thread_id=st.session_state.thread_id, 
311 |                              role='USER',
312 |                              message=f"USER: {user_message}"
313 |                             )
314 |                 write_to_messages_db(thread_id=st.session_state.thread_id, 
315 |                              role='AI',
316 |                              message=f"AI: {chat_response}"
317 |                             )
318 | 
319 | 
320 | def display_file_code(filename):
321 |     with open(filename, "r") as file:
322 |         with st.expander(filename, expanded=False):
323 |             st.code(file.read(), language='python')
324 | 
325 | 
326 | def display_all_code():
327 |     st.subheader("GitHub Link")
328 |     st.write("https://github.com/petermartens98/GPT4-Programming-Assistant")
329 |     st.subheader("Source Code")
330 |     files = ["main.py", "db_functions.py", "htmlTemplates.py", "prompts.py", "requirements.txt"]
331 |     for file in files:
332 |         display_file_code(file)
333 | 
334 | 
335 | def main():
336 |     page_config()
337 |     create_users_db()
338 |     create_messages_db()
339 |     init_ses_states()
340 |     page_title_header()
341 |     sidebar()
342 |     if st.session_state.user_authenticated:
343 |         if st.session_state.docs_processed:
344 |             deploy_tab, code_tab, docs_tab = st.tabs(['Deployment','Source Code','Doc Analysis'])
345 |             with docs_tab:
346 |                 st.caption("Coming Soon")
347 |                 for pdf in st.session_state.uploaded_docs:
348 |                     st.caption("hi")
349 |         else:
350 |             deploy_tab, code_tab = st.tabs(['Deployment','Source Code'])
351 |         with deploy_tab:
352 |             handle_initial_submit()
353 |             handle_user_message()
354 |             display_convo()
355 |         with code_tab: 
356 |             display_all_code()
357 |     else:
358 |         st.write("Login to use application")
359 | 
360 | 
361 | if __name__ == '__main__':
362 |     load_dotenv()
363 |     main()
364 | 
365 | 


--------------------------------------------------------------------------------
/AppV7/prompts.py:
--------------------------------------------------------------------------------
  1 | INITIAL_TEMPLATE = '''
  2 |     You are a GPT-4 AI Coding Assistant specializing in the "{language}" programming language.
  3 |     \nAlso consider these additional {language} librarieS: {libraries}
  4 |     \nAlthough your main language is {language}, you should draw inspiration from all possible sources.
  5 |     \nYou should come off as helpful, confindent, multifunctional, and welcoming.
  6 |     \nThe user has specified the mode to "{scenario}"
  7 |     \n{scenario} SCENARIO CONTEXT: {scenario_context}
  8 |     \nUSER {language} CODE INPUT: 
  9 |     \n{input}
 10 |     \nADDITIONAL CONTEXT FROM USER: {code_context}
 11 |     \nBefore returning your response be sure its the best and most optimal solution.
 12 |     \nAfter your coding response, be sure to end your chat response by asking user if they need any further assistance
 13 |     \n\nAI {language} GPT4 CHATBOT RESPONSE HERE:\n
 14 | '''
 15 | 
 16 | 
 17 | CHAT_TEMPLATE = '''
 18 |     You are a GPT-4 AI Coding Assistant specializing in the "{language}" programming language.
 19 |     \nAlso consider these additional {language} libraries: {libraries}
 20 |     \nYou should come off as helpful, confindent, multifunctional, and welcoming.
 21 |     \nThe user has specified the mode to "Code {scenario}"
 22 |     \n{scenario} SCENARIO CONTEXT: {scenario_context}
 23 |     \nUSER {language} CODE INPUT: 
 24 |     \n{code_input}
 25 |     \nADDITIONAL CONTEXT FROM USER: {code_context}
 26 |     \nCHAT HISTORY:
 27 |     \n{chat_history}
 28 |     \n MOST RECENT AI MESSAGE {most_recent_ai_message}
 29 |     \n USER QUESTION: {input}
 30 |     \n Be sure to end your response by asking user if they need any further assistance
 31 |     \n\nAI {language} GPT4 CHATBOT RESPONSE HERE:\n
 32 | '''
 33 | 
 34 | 
 35 | # Scenario Contexts
 36 | 
 37 | GENERAL_ASSISTANT_CONTEXT = '''
 38 | General Assistant Mode: You are an all purpose coding assistant for the "{language}" programming language.
 39 | '''
 40 | 
 41 | CORRECTION_CONTEXT = '''
 42 | Correction Mode: Correct the "{language}" code the user submitted.
 43 | \nIdentify and rectify any errors while maintaining the intended functionality of the code.
 44 | \nAnalyze and optimize user syntax
 45 | \nAdd or remove any code necessary to fix and corrext the user code
 46 | \nAlso provide an explanation for how you corrected the code and how you implemented such a correction.
 47 | '''
 48 | 
 49 | COMPLETION_CONTEXT = '''
 50 | Completion Mode: Complete the "{language}" code the user submitted.
 51 | \nThe Code may either be partially complete or have comments for what the user wants you to implement/complete.
 52 | \nAlso provide an explanation for how you completed the code and how you implemented such a completion.
 53 | '''
 54 | 
 55 | ALTERATION_CONTEXT = '''
 56 | 
 57 | '''
 58 | 
 59 | OPTIMIZATION_CONTEXT = '''
 60 | Optimization Mode: Enhance the "{language}" code provided by the user for optimal performance.
 61 | \nAnalyze the code thoroughly and apply optimizations to maximize efficiency.
 62 | \nAlso keep in mind, code readability and maintainability.
 63 | \nPlease document the optimizations made, explaining the rationale and how it contributes to code optimization.
 64 | '''
 65 | 
 66 | SHORTENING_CONTEXT = '''
 67 | Shortening Mode: Shorten the user's {language} code as much as possible, use as few characters and as fews lines
 68 | as possible.
 69 | '''
 70 | 
 71 | GENERATION_CONTEXT = '''
 72 | Generation Mode: Generate {language} code based on the user input.
 73 | '''
 74 | 
 75 | COMMENTING_CONTEXT = '''
 76 | Commenting Mode: Add comments to the {language} code provided by the user.
 77 | '''
 78 | 
 79 | EXPLANATION_CONTEXT = '''
 80 | Explanation Mode: Explain the {language} code provided by the user.
 81 | '''
 82 | 
 83 | LEETCODE_CONTEXT = '''
 84 | LeetCode Solver Mode: You have been provided with a LeetCode problem in {language} by the user.
 85 | \nCarefully analyze the problem statement.
 86 | \nMake sure to thoroughly understand the problem requirements and constraints.
 87 | \nConsider any edge cases that may arise and handle them appropriately
 88 | \nEfficiency and correctness are crucial in solving LeetCode problems. Therefore, strive to optimize your 
 89 | solution by considering time and space complexities. Your goal is to produce a solution that is both accurate and efficient.
 90 | \nConsider multiple solutions to the problem and go with the most optimal solution
 91 | \nAfter you come up with a solution, be sure to shorten and optimize
 92 | \nNow proceed to solve the user-submitted LeetCode problem.
 93 | '''
 94 | 
 95 | DAN_PROMPT = '''
 96 | coming soon
 97 | '''
 98 | 
 99 | # Incorrect code generator prompt
100 | 
101 | # Multiple Choice Solver and Generator


--------------------------------------------------------------------------------
/AppV7/requirements.txt:
--------------------------------------------------------------------------------
  1 | aiohttp==3.8.4
  2 | aiosignal==1.3.1
  3 | altair==5.0.1
  4 | async-timeout==4.0.2
  5 | attrs==23.1.0
  6 | beautifulsoup4==4.12.2
  7 | blinker==1.6.2
  8 | cachetools==5.3.1
  9 | certifi==2023.5.7
 10 | charset-normalizer==3.1.0
 11 | click==8.1.4
 12 | colorama==0.4.6
 13 | contourpy==1.1.0
 14 | cycler==0.11.0
 15 | dataclasses-json==0.5.9
 16 | decorator==5.1.1
 17 | faiss-cpu==1.7.4
 18 | Faker==18.13.0
 19 | favicon==0.7.0
 20 | fonttools==4.40.0
 21 | frozenlist==1.3.3
 22 | gitdb==4.0.10
 23 | GitPython==3.1.31
 24 | greenlet==2.0.2
 25 | htbuilder==0.6.1
 26 | idna==3.4
 27 | importlib-metadata==6.7.0
 28 | Jinja2==3.1.2
 29 | jsonschema==4.18.0
 30 | jsonschema-specifications==2023.6.1
 31 | kiwisolver==1.4.4
 32 | langchain==0.0.226
 33 | langchainplus-sdk==0.0.20
 34 | lxml==4.9.3
 35 | Markdown==3.4.3
 36 | markdown-it-py==3.0.0
 37 | markdownlit==0.0.7
 38 | MarkupSafe==2.1.3
 39 | marshmallow==3.19.0
 40 | marshmallow-enum==1.5.1
 41 | matplotlib==3.7.2
 42 | mdurl==0.1.2
 43 | more-itertools==9.1.0
 44 | multidict==6.0.4
 45 | mypy-extensions==1.0.0
 46 | numexpr==2.8.4
 47 | numpy==1.25.0
 48 | openai==0.27.8
 49 | openapi-schema-pydantic==1.2.4
 50 | packaging==23.1
 51 | pandas==2.0.3
 52 | Pillow==9.5.0
 53 | protobuf==4.23.4
 54 | pyarrow==12.0.1
 55 | pydantic==1.10.11
 56 | pydeck==0.8.1b0
 57 | Pygments==2.15.1
 58 | pymdown-extensions==10.0.1
 59 | Pympler==1.0.1
 60 | pyparsing==3.0.9
 61 | PyPDF2==3.0.1
 62 | python-dateutil==2.8.2
 63 | python-dotenv==1.0.0
 64 | pytz==2023.3
 65 | pytz-deprecation-shim==0.1.0.post0
 66 | PyYAML==6.0
 67 | referencing==0.29.1
 68 | regex==2023.6.3
 69 | requests==2.31.0
 70 | rich==13.4.2
 71 | rpds-py==0.8.8
 72 | six==1.16.0
 73 | smmap==5.0.0
 74 | soupsieve==2.4.1
 75 | SQLAlchemy==2.0.18
 76 | st-annotated-text==4.0.0
 77 | streamlit==1.24.0
 78 | streamlit-camera-input-live==0.2.0
 79 | streamlit-card==0.0.61
 80 | streamlit-embedcode==0.1.2
 81 | streamlit-extras==0.2.7
 82 | streamlit-faker==0.0.2
 83 | streamlit-image-coordinates==0.1.5
 84 | streamlit-keyup==0.2.0
 85 | streamlit-toggle-switch==1.0.2
 86 | streamlit-vertical-slider==1.0.2
 87 | tenacity==8.2.2
 88 | tiktoken==0.4.0
 89 | toml==0.10.2
 90 | toolz==0.12.0
 91 | tornado==6.3.2
 92 | tqdm==4.65.0
 93 | typing-inspect==0.9.0
 94 | typing_extensions==4.7.1
 95 | tzdata==2023.3
 96 | tzlocal==4.3.1
 97 | urllib3==2.0.3
 98 | validators==0.20.0
 99 | watchdog==3.0.0
100 | Werkzeug==2.3.6
101 | yarl==1.9.2
102 | zipp==3.15.0
103 | 


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/AppV7/trippyPattern.png:
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https://raw.githubusercontent.com/Luis96920/GPT4-Programming-Assistant/34e61ffd199e7401d345adb165fdebb55077bbb9/AppV7/trippyPattern.png


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/README.md:
--------------------------------------------------------------------------------
 1 |  # GPT4-Coding-Assistant-Web-App
 2 | ### Description
 3 | Python Streamlit web app utilizing OpenAI (GPT-4) and LangChain language modeling tools. Application includes an SQLite database for login/authentication and message storage for later retrieval. Users can also upload and embed their own PDF documents for chatbot reference. The user can then interact with a GPT-4 chatbot intended for the user's specified programming language, code input, context, scenario, LLM temperature, and chat history.
 4 | 
 5 | ### Supported Scenarios
 6 | 1. General Assistant
 7 | 2. Code Correction
 8 | 3. Code Completion
 9 | 4. Code Commenting
10 | 5. Code Optimization
11 | 6. Code Shortening
12 | 7. Code Generation
13 | 8. Code Explanation
14 | 9. LeetCode Solver
15 | 
16 | ### Supported Programming Languages
17 | 1. Python
18 | 2. TypeScripts
19 | 3. JavaScript
20 | 4. Java
21 | 5. Golang
22 | 6. C
23 | 7. C++
24 | 8. C#
25 | 9. R
26 | 10. SQL
27 | 
28 | ### Supported Large Language Models
29 | 1. GPT-4
30 | 2. GPT-4-0613
31 | 3. GPT-3.5-Turbo
32 | 
33 | ## V7
34 | ### V7 Improvements
35 | 1. Added User Login and Authentication System (SQLite)
36 | 2. Save User Messages (SQLite)
37 | 3. View and Revive Previous Chats
38 | ### V7 Screenshot
39 | ![image](https://github.com/petermartens98/GPT4-Programming-Assistant/assets/87671757/2467d134-cf1a-46a9-9ed6-4deb57a426de)
40 | 
41 | 
42 | ## V6
43 | ### V6 Improvements
44 | 1. Allow users to upload and embed multiple documents
45 | 2. Allow users to specify a desired library within their specified programming language
46 | 3. Allow users to specify their desired large language model
47 | ### V6 Example Screenshot
48 | ![image](https://github.com/petermartens98/GPT4-Programming-Assistant/assets/87671757/688eb70b-e84e-4dcc-9f68-a05ca414d665)
49 | 
50 | 
51 | ## V5
52 | ### Improvements
53 | ### 1. Added support for SQL
54 |    ![image](https://github.com/petermartens98/GPT4-Programming-Assistant/assets/87671757/a46515b5-20a2-41ef-8330-dbdb46ccae79)
55 | 
56 | ### 2. Added Code Shortening Mode
57 |  ![image](https://github.com/petermartens98/GPT4-Programming-Assistant/assets/87671757/f9f4380e-411c-48d5-ada6-366d56f30c57)
58 | 
59 | ### 3. Added Leet Code Solver 
60 | ![image](https://github.com/petermartens98/GPT4-Programming-Assistant/assets/87671757/07d6ff64-2f71-4687-82d3-d84f297b3eb0)
61 | 
62 | ### 4. Added Code to display source code
63 | ![image](https://github.com/petermartens98/GPT4-Programming-Assistant/assets/87671757/5ebb8827-0d01-418a-b650-bff087e95478)
64 | 
65 | ## V4
66 | Improved code modularity
67 | 
68 | ## V3
69 | ### V3 General Assistant Screenshot:
70 | ![image](https://github.com/petermartens98/GPT4-Programming-Assistant/assets/87671757/6e35f3cf-fa60-47cb-b6f8-533dbf89072c)
71 | 
72 | ### V3 Code Completion Screenshot:
73 | ![image](https://github.com/petermartens98/GPT4-Programming-Assistant/assets/87671757/9c4fa802-468f-4899-b2c2-bc5bc7b05ef9)
74 | 
75 | ### V3 Code Correction Screenshot: 
76 | ![image](https://github.com/petermartens98/GPT4-Programming-Assistant/assets/87671757/1ffe61e2-2f73-4a47-b11c-8aee0b9f0b8c)
77 | 
78 | ### V3 Code Commenting Screenshot:
79 | ![image](https://github.com/petermartens98/GPT4-Programming-Assistant/assets/87671757/701eb2c6-8321-4c43-b06f-0df728c03858)
80 | 
81 | ### V3 Code Optimization Screenshot:
82 | ![image](https://github.com/petermartens98/GPT4-Programming-Assistant/assets/87671757/bf796215-328d-41b7-919b-62f669ed4e61)
83 | 
84 | ### V3 Code Explanation Screenshot:
85 | ![image](https://github.com/petermartens98/GPT4-Programming-Assistant/assets/87671757/f5ace256-8a75-4a10-a6c6-07d93f579535)
86 | 
87 | ## V2
88 | ### V2 Code Completion Screenshot
89 | ![image](https://github.com/petermartens98/GPT4-Coding-Assistant-Web-App/assets/87671757/f6b251e8-c989-480b-9e1e-c5a041b7ebab)
90 | 
91 | ### V2 Code Correction Screenshot
92 | ![image](https://github.com/petermartens98/GPT4-Coding-Assistant-Web-App/assets/87671757/98ac7b0a-df63-42b1-8ec4-d57bd24b1711)
93 | 
94 | ## V1
95 | ### V1 Code Correction Screenshot
96 | ![image](https://github.com/petermartens98/GPT4-Coding-Assistant-Web-App/assets/87671757/0a09df8d-f457-4d9c-842e-8dc8e757ad96)
97 | 


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