encountered an issue with the AI News Writer feature. The system successfully generates a news report (as indicated by the success message), but the actual content is not displayed in the UI.
Steps to Reproduce:
Open Alwrity and navigate to AI Writers.
Select Write News Reports.
Enter keywords (e.g., Upcoming AI Trends in 2025).
Select an origin country (e.g., India) and language (e.g., English).
Click Generate News Report.
Changes Made:
Configured logging similar to openai_text_gen.py.
Added retry mechanism using tenacity similar to both openai_text_gen.py and gemini_pro_text.py.
Adapted the API call to use DeepSeek's reasoning.create method.
Handled streaming of responses and error logging.
Function Definitions:
fetch_arxiv_data: Fetches arXiv data based on a query.
create_dataframe: Creates a DataFrame from the provided data.
get_arxiv_main_content: Returns the main content of an arXiv paper.
download_image: Downloads an image from a URL.
scrape_images_from_arxiv: Scrapes images from an arXiv page.
arxiv_bibtex: Generates the BibTeX entry for an arXiv paper.
extract_arxiv_ids_from_line: Extracts arXiv IDs from a given line of text.
read_written_ids: Reads already written arXiv IDs from a file.
append_id_to_file: Appends a single arXiv ID to a file.
Step 2: Suggest Code Improvements
Code Duplication:
Combine Similar Functions: Functions such as fetch_arxiv_data and create_dataframe can be combined or refactored to reduce redundancy.
Reuse Code: Ensure common functionality is abstracted into reusable functions.
Performance and Optimization:
Optimize API Calls: Ensure the arXiv API calls are optimized and handle rate limits.
Efficient Data Handling: Use more efficient data handling techniques, such as batch processing for large datasets.
Coding Standards and Best Practices:
Add Docstrings: Ensure all functions have detailed docstrings explaining their purpose, arguments, and return values.
Error Handling: Improve error handling to provide more informative error messages and handle different types of errors separately.
Logging: Use a consistent logging strategy to log important events and errors.
Code Structure: Group related functions into classes or modules for better organization and maintainability.
PEP 8 Compliance: Ensure the code follows PEP 8 standards for Python code style.
Code Improvements:
Error Handling:
Improve error messages to be more informative.
Log errors for debugging purposes.
Code Readability:
Add docstrings and comments to explain the purpose of functions and complex code blocks.
Use consistent formatting and naming conventions.
Modularization:
Split large functions into smaller, reusable functions.
Group related functions together.
Optimization:
Use caching where possible to reduce redundant operations.
Optimize data processing steps for better performance.
User Experience Improvements:
User Feedback:
Provide immediate feedback on actions (e.g., loading spinners, success, and error messages).
Use placeholders and help text to guide users on what inputs are expected.
Interactive Elements:
Use more interactive elements like sliders, date pickers, and multi-selects to enhance the user interface.
User-Friendly Interface: The Streamlit interface is intuitive, allowing users to easily input text and get readability scores.
Comprehensive Analysis: The tool covers a wide range of readability metrics, providing detailed insights into the text's readability.
Actionable Tips: Each readability score is accompanied by actionable tips, helping users improve their content based on the analysis.
Additional Insights: The inclusion of additional metrics like reading time, syllable count, and word count provides a thorough analysis of the text.
Suggested Improvements:
Error Handling:
Add error handling for cases where the text input might be empty or too short for certain readability metrics.
Code Modularization:
Refactor the code to encapsulate readability calculations and markdown generation into separate functions. This will make the code more modular and easier to maintain.
Performance Optimization:
Optimize the readability calculation by avoiding redundant calculations if the text hasn't changed.
Code Readability:
Add docstrings and comments to explain the purpose of functions and complex code blocks.
Ensure consistent formatting and adherence to PEP8 standards.
Code Improvements:
Error Handling:
Improve error messages to be more informative.
Log errors for debugging purposes.
Code Readability:
Add docstrings and comments to explain the purpose of functions and complex code blocks.
Modularization:
Split large functions into smaller, reusable functions.
Group related functions together.
Input Validation:
Ensure user inputs are validated to prevent errors later in the code.
User Experience Improvements:
User Feedback:
Provide immediate feedback on actions (e.g., loading spinners, success, and error messages).
Use placeholders and help text to guide users on what inputs are expected.
Interactive Elements:
Use more interactive elements like sliders, date pickers, and multi-selects to enhance the user interface.
Add Type Hints: Improve code readability and help with static type checking by adding type hints.
Modular Logging Setup: Move the logging setup to a separate function for better modularity.
Error Handling Improvements: Add more specific error handling and informative logging.
Environment Variable Loading: Ensure environment variables are loaded only once and not inside functions.
Check for API Key Validity: Add a check to validate the Tinyfy API key before using it.
Optimize Image Saving: Use a temporary file to avoid saving directly to the filesystem.
