Delete components

components/__init__.py

@@ -1,7 +0,0 @@
-# components/__init__.py
-from .home import HomePage
-from .refactor_page import RefactorPage
-from .style_page import StylePage
-from .test_page import TestPage
-from .optimize_page import OptimizePage
-from .documentation_page import DocumentationPage

components/database_page.py

@@ -1,18 +0,0 @@
-# components/database_page.py
-import streamlit as st
-import sqlite3
-
-def show_database_page(chat):
-    st.title("Database Interaction")
-    st.write("This page interacts with a SQLite database.")
-
-    def execute_query(query):
-        conn = sqlite3.connect("test.db")
-        result = conn.execute(query)
-        return result.fetchall()
-
-    database_query = st.text_input("Enter the SQLite query:", "SELECT * FROM users;")
-
-    if st.button("Execute Query"):
-        result = execute_query(database_query)
-        st.write(result)

components/documentation_page.py

@@ -1,22 +0,0 @@
-# components/code_documentation_page.py
-import streamlit as st
-from langchain.prompts.chat import SystemMessagePromptTemplate, HumanMessagePromptTemplate
-from langchain.chains import LLMChain
-from langchain.llms import OpenAI
-
-def show_doc_page(chat):
-    st.title("Code Documentation Generator")
-    st.write("This page generates documentation for a given code snippet.")
-
-    code_snippet = st.text_area("Enter the code snippet:", height=200)
-
-    if st.button("Generate Documentation"):
-        # Implement the functionality for generating documentation
-        system_message_prompt = SystemMessagePromptTemplate.from_template("Generate documentation for the provided code snippet.")
-        human_message_prompt = HumanMessagePromptTemplate.from_template("Code snippet:\n{code_snippet}")
-        chat_prompt = SystemMessagePromptTemplate.from_prompt_template(system_message_prompt)
-        chat_prompt.add_message(human_message_prompt)
-        llm = OpenAI(temperature=0.5)
-        chain = LLMChain(llm=llm, prompt=chat_prompt)
-        result = chain.run(code_snippet=code_snippet)
-        st.write(result)

components/home.py

@@ -1,11 +0,0 @@
-import streamlit as st
-
-def show_home_page():
-    st.title("Welcome to CodeCraft GPT!")
-    st.write("This is the home page.")
-
-    st.markdown("""
-    CodeCraft GPT is an all-in-one platform designed for AI/ML developers.
-    It offers a set of mini-apps for code documentation, optimization, refactoring,
-    style checking, testing, language translation, and database interaction.
-    """)

components/lang_page.py

@@ -1,14 +0,0 @@
-import streamlit as st
-from langchain.chat_models import ChatOpenAI
-
-def show_lang_page(chat):
-    st.title("Language Translation")
-    st.write("This page translates code snippets between programming languages.")
-
-    source_language = st.selectbox("Select the source language:", LANGUAGES)
-    target_language = st.selectbox("Select the target language:", LANGUAGES)
-    code_snippet = st.text_area("Enter the code snippet:", height=200)
-
-    if st.button("Translate Code"):
-        # Implement the functionality for translating code
-        pass

components/optimization_page.py

@@ -1,31 +0,0 @@
-# components/code_optimization_page.py
-import streamlit as st
-from langchain.prompts.chat import (
-    ChatPromptTemplate,
-    HumanMessagePromptTemplate,
-    SystemMessagePromptTemplate)
-from langchain.chat_models import ChatOpenAI
-from data.optimization_prompt import OPTIMIZATION_PROMPT
-
-def show_optimize_page(chat):
-    # Request a code snippet for optimization
-    st.subheader("Request Code Snippet for Optimization")
-    user_code = st.text_area("Enter the code snippet:", "def factorial(n):\n\treturn 1 if n < 2 else n * factorial(n - 1)", height=200)
-
-    if st.button("Optimize Code"):
-        # Create a prompt for optimization
-        optimization_prompt = ChatPromptTemplate.from_template(OPTIMIZATION_PROMPT)
-
-        # Create a message template for the user's code
-        human_message_prompt = HumanMessagePromptTemplate.from_template("{code_snippet}")
-
-        # Combine the system and user message templates
-        chat_prompt = ChatPromptTemplate.from_messages([optimization_prompt, human_message_prompt])
-
-        # Run the optimization chat chain
-        optimization_chain = LLMChain(llm=chat, prompt=chat_prompt)
-        optimized_code = optimization_chain.run(code_snippet=user_code)
-
-        # Display the optimized code
-        st.subheader("Optimized Code")
-        st.text_area("", optimized_code, height=200)

components/refactor_page.py

@@ -1,12 +0,0 @@
-import streamlit as st
-from langchain.chat_models import ChatOpenAI
-
-def show_refactor_page(chat):
-    st.title("Code Refactoring")
-    st.write("This page refactors a given code snippet.")
-
-    code_snippet = st.text_area("Enter the code snippet:", height=200)
-
-    if st.button("Refactor Code"):
-        # Implement the functionality for refactoring code
-        pass

components/style_page.py

@@ -1,12 +0,0 @@
-import streamlit as st
-from langchain.chat_models import ChatOpenAI
-
-def show_style_page(chat):
-    st.title("Code Style Checker")
-    st.write("This page checks the style of a given code snippet.")
-
-    code_snippet = st.text_area("Enter the code snippet:", height=200)
-
-    if st.button("Check Style"):
-        # Implement the functionality for checking code style
-        pass

components/test_page.py

@@ -1,12 +0,0 @@
-import streamlit as st
-from langchain.chat_models import ChatOpenAI
-
-def show_test_page(chat):
-    st.title("Code Testing")
-    st.write("This page generates tests for a given code snippet.")
-
-    code_snippet = st.text_area("Enter the code snippet:", height=200)
-
-    if st.button("Generate Tests"):
-        # Implement the functionality for generating tests
-        pass