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import streamlit as st
import os
import subprocess
import random
import string
from huggingface_hub import cached_download, hf_hub_url
from transformers import pipeline
import black
import pylint
# Define functions for each feature
# 1. Chat Interface
def chat_interface(input_text):
"""Handles user input in the chat interface.
Args:
input_text: User's input text.
Returns:
The chatbot's response.
"""
# Load the appropriate language model from Hugging Face
model_name = 'google/flan-t5-xl' # Choose a suitable model
model_url = hf_hub_url(repo_id=model_name, revision='main', filename='config.json')
model_path = cached_download(model_url)
generator = pipeline('text-generation', model=model_path)
# Generate chatbot response
response = generator(input_text, max_length=50, num_return_sequences=1, do_sample=True)[0]['generated_text']
return response
# 2. Terminal
def terminal_interface(command):
"""Executes commands in the terminal.
Args:
command: User's command.
Returns:
The terminal output.
"""
# Execute command
try:
process = subprocess.run(command.split(), capture_output=True, text=True)
output = process.stdout
except Exception as e:
output = f'Error: {e}'
return output
# 3. Code Editor
def code_editor_interface(code):
"""Provides code completion, formatting, and linting in the code editor.
Args:
code: User's code.
Returns:
Formatted and linted code.
"""
# Format code using black
try:
formatted_code = black.format_str(code, mode=black.FileMode())
except black.InvalidInput:
formatted_code = code # Keep original code if formatting fails
# Lint code using pylint
try:
pylint_output = pylint.run(formatted_code, output=None)
lint_results = pylint_output.linter.stats.get('global_note', 0)
lint_message = f"Pylint score: {lint_results:.2f}"
except Exception as e:
lint_message = f"Pylint error: {e}"
return formatted_code, lint_message
# 4. Workspace
def workspace_interface(project_name):
"""Manages projects, files, and resources in the workspace.
Args:
project_name: Name of the new project.
Returns:
Project creation status.
"""
# Create project directory
try:
os.makedirs(os.path.join('projects', project_name))
status = f'Project \"{project_name}\" created successfully.'
except FileExistsError:
status = f'Project \"{project_name}\" already exists.'
return status
# 5. AI-Infused Tools
# Define custom AI-powered tools using Hugging Face models
# Example: Text summarization tool
def summarize_text(text):
"""Summarizes a given text using a Hugging Face model.
Args:
text: Text to be summarized.
Returns:
Summarized text.
"""
summarizer = pipeline('summarization', model='facebook/bart-large-cnn')
summary = summarizer(text, max_length=100, min_length=30)[0]['summary_text']
return summary
# Streamlit App
st.title("CodeCraft: Your AI-Powered Development Toolkit")
# Chat Interface
st.header("Chat with CodeCraft")
chat_input = st.text_area("Enter your message:")
if st.button("Send"):
chat_response = chat_interface(chat_input)
st.write(f"CodeCraft: {chat_response}")
# Terminal Interface
st.header("Terminal")
terminal_input = st.text_input("Enter a command:")
if st.button("Run"):
terminal_output = terminal_interface(terminal_input)
st.code(terminal_output, language="bash")
# Code Editor Interface
st.header("Code Editor")
code_editor = st.text_area("Write your code:", language="python", height=300)
if st.button("Format & Lint"):
formatted_code, lint_message = code_editor_interface(code_editor)
st.code(formatted_code, language="python")
st.info(lint_message)
# Workspace Interface
st.header("Workspace")
project_name = st.text_input("Enter project name:")
if st.button("Create Project"):
workspace_status = workspace_interface(project_name)
st.success(workspace_status)
# AI-Infused Tools
st.header("AI-Powered Tools")
text_to_summarize = st.text_area("Enter text to summarize:")
if st.button("Summarize"):
summary = summarize_text(text_to_summarize)
st.write(f"Summary: {summary}") |