Ahmad Ali@Ahmad_A1i

Code Compass – AI-Powered Open-Source Contribution Helper Code Compass makes open-source contribution easier by helping developers understand complex codebases, visualize dependencies, and find actionable contribution opportunities. Core Problem New developers struggle with large, unfamiliar repositories and lack clear starting points. Code Compass bridges this gap with AI-driven insights and interactive visualization. Key Features ✅ AI-Powered Analysis – GPT-5-based repository summarization, code explanations, and intelligent Q&A. ✅ Visual Knowledge Graphs – Interactive dependency maps using NetworkX + PyVis for files, classes, and functions. ✅ Smart Contribution Guidance – Detects TODOs, missing tests, and suggests beginner-friendly GitHub issues. ✅ Multi-Language Support – Handles Python, JavaScript, TypeScript, HTML, CSS, and config files. How It Works Repo Ingestion – Clone any GitHub repo via API. Graph Mapping – Build a knowledge graph of imports, function calls, and file relationships. AI Insight Layer – GPT-5 answers natural language questions, explains architecture, and recommends contributions. Interactive Exploration – Filter graphs, view file summaries, and discover improvement areas. Tech Stack Frontend: Streamlit, PyVis Backend: FastAPI, Python AI & NLP: GPT-5 (via AIML), Google Generative AI embeddings, FAISS for semantic search Visualization: NetworkX, Plotly Integration: GitHub API (PyGithub) Why It’s Innovative Unlike basic code search tools, Code Compass combines graph visualization, AI-driven explanations, and predictive contribution detection. It not only answers “what” and “where” but also explains “why” and “how”, empowering newcomers to contribute confidently. One-Line Summary: Code Compass transforms codebases into interactive, explainable maps, making open-source projects accessible to everyone.

ChatCinema is a multifaceted Streamlit application that combines a sophisticated movie information chatbot with advanced data processing and generation capabilities. The project integrates various cutting-edge technologies to create a versatile platform for movie enthusiasts, data scientists, and AI researchers. At its core, ChatCinema features a highly interactive movie chatbot. This chatbot utilizes a CSV file ('Hydra-Movie-Scrape.csv') as its primary data source, containing a wealth of information about various movies. To enable efficient and relevant movie retrieval, the application employs the 'all-MiniLM-L6-v2' sentence transformer model to generate embeddings for movie summaries. These embeddings are then used in conjunction with cosine similarity calculations to find the most relevant movie based on user queries. The chatbot's natural language processing capabilities are powered by the Groq API, specifically using the 'llama3-8b-8192' model. This integration allows for dynamic and context-aware responses to user inquiries. When a user inputs a movie-related query, the system retrieves the most similar movie from its database and uses this information as context for generating a response. The output includes comprehensive movie details such as title, year, summary, genres, IMDB ID, YouTube trailer link, rating, movie poster URL, director, writers, and cast information. Additionally, the chatbot generates relevant dialogues or additional information about the movie using the AI model. A key feature of ChatCinema is its ability to maintain and manage chat history. The application stores conversation logs in Streamlit's session state, allowing for a continuous and contextual chat experience. Users have the option to download their chat history, which is provided as an encrypted CSV file for enhanced privacy and security.

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