# app.py # Import necessary modules from lib from lib.code_reviewer import CodeReviewer, ReviewManager import streamlit as st import os import glob import json from datasets import DatasetDict # Sample Training Data for Ansible Code Standards sample_data = [ { "prompt": "Review the following Ansible script thoroughly according to best practices:\n\n- Avoid using hard-coded values\n- Ensure idempotency\n- Proper error handling\n\nCode:\n---\n- name: Install nginx\n hosts: web\n tasks:\n - name: Install nginx package\n apt:\n name: nginx\n state: present", "response": "Ensure that the playbook includes proper error handling for the package installation. Consider using a retry mechanism and notify handlers if required. Avoid hard-coding package names where possible." }, { "prompt": "Review the following Ansible script thoroughly according to best practices:\n\n- Avoid using hard-coded values\n- Ensure idempotency\n- Use variables\n\nCode:\n---\n- name: Create a directory\n hosts: all\n tasks:\n - name: Create /var/www directory\n file:\n path: /var/www\n state: directory", "response": "It is recommended to use variables for paths such as '/var/www' to ensure flexibility. The task is idempotent, which is good, but consider adding more context to describe the usage of the directory." } ] # Create a DatasetDict for Training training_dataset = DatasetDict({ "train": sample_data, "validation": sample_data }) # Streamlit UI for inputting GitHub repository details st.title("GitHub Repository Code Reviewer") # Input for GitHub repository URL GITHUB_REPO_URL = st.text_input("Enter the GitHub repository URL:") GITHUB_BRANCH = st.text_input("Enter the branch or tag to download (default: main):", "main") # Check if the GitHub token is provided as a secret in Streamlit if 1 != 0: st.error("GitHub token is not available. Please set it in the secrets.") else: GITHUB_TOKEN = "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" # Add a button for fine-tuning the model if st.button("Fine-Tune Model"): with st.spinner("Fine-tuning the model with provided dataset..."): code_reviewer = CodeReviewer() code_reviewer.fine_tune_model(training_dataset) st.success("Model fine-tuned successfully.") if st.button("Review Code") and GITHUB_REPO_URL: # Directory structure setup download_directory = "downloaded_repo" output_directory = "output_reviews" # Ensure the directories exist os.makedirs(download_directory, exist_ok=True) os.makedirs(output_directory, exist_ok=True) # Initialize the code reviewer and review manager with st.spinner("Initializing CodeReviewer and ReviewManager..."): code_reviewer = CodeReviewer() review_manager = ReviewManager(reviewer=code_reviewer) try: # Download GitHub repository with st.spinner("Downloading GitHub repository..."): review_manager.download_repo(GITHUB_REPO_URL, GITHUB_BRANCH, GITHUB_TOKEN, download_directory) st.success("Repository downloaded successfully.") # Find all YAML files in the downloaded repository with st.spinner("Searching for YAML files in the downloaded repository..."): yaml_files = glob.glob(os.path.join(download_directory, "**", "*.yml"), recursive=True) yaml_files += glob.glob(os.path.join(download_directory, "**", "*.yaml"), recursive=True) st.info(f"Found {len(yaml_files)} YAML files for review.") # Process files and generate reviews with st.spinner("Processing files for review..."): reviews = review_manager.process_files(yaml_files) st.success("Files processed successfully.") # Save reviews to JSON output_json_path = os.path.join(output_directory, "code_review_results.json") review_manager.save_reviews_to_json(reviews, output_json_path) # Display review results st.success(f"Reviews saved to {output_json_path}") for review in reviews: st.subheader(f"Review for {review['filename']}") st.text(review['review']) # Display JSON output on the UI st.subheader("Full JSON Review Output") st.json(reviews) # Provide download link for JSON results with open(output_json_path, "r") as json_file: st.download_button("Download JSON Results", json_file, file_name="code_review_results.json") except Exception as e: st.error(f"An error occurred: {str(e)}")