Faza E Badar@fazaebadar

A reproducible verification workflow for AI-assisted repairs, built for the IBM Bob 2.0 Hackathon. The live app executes trusted bundled Python code; no AI service or API key is required. A pagination export drops task 4 when records share timestamps. ProofPatch connects a baseline assertion failure to a candidate repair, checks that mandatory tests and inputs are unchanged, and creates a rerunnable evidence package. A deliberately incorrect repair demonstrates rejection. The three CLI verifier commands return success when their intended outcomes occur. Raw pytest on the baseline or bad patch intentionally fails. python -m pytest defaults to verifier system tests, so routine project checks can finish green. On PowerShell set $env:PROOFPATCH_VARIANT="candidate" before the raw pytest command. The full suite always covers preview sizes 2, 3 and 4. Page size changes the independent ID preview only. Each subprocess has a 15-second limit; one candidate verification can take roughly 45 seconds in a worst-case sequence of timed-out children. The web UI is synchronous during a run. report.json, summary.md, patch.diff, full baseline and selected stdout/stderr, JUnit XML, checksums.json, and snapshot/ containing all executable sample code, regression and acceptance tests, fixture, conftest.py, configuration, requirements and frozen manifest. Run summary.md instructions from snapshot/ to reproduce the checks. The manifest detects accidental or unreviewed changes relative to a local reference. A maintainer who changes both manifest and files can change that reference. SHA-256 hashes are not signatures, authorship proof, or trusted timestamps. This release manifest was created after the original build. Original Bob provenance must be established with the team's actual session artifacts. Never regenerate the manifest just to bypass a failed integrity check. Creating a new manifest requires a complete matching suite, a reproduced baseline assertion and a passing candidate. Existing evidence remains bound to its own snapshot. The dataset is synthetic and the bad patch is an intentional negative control, used to test rejection. The verifier accepts only bundled variants; it is not an execution sandbox for arbitrary uploads. The repaired pagination code assumes unique integer IDs and comparable datetime values. It reads an in-memory dataset and is not a production database adapter. Performance and commercial benefits beyond observed local runs remain hypotheses. We used IBM Bob during our original development. After our allocated credits were consumed, we continued local engineering and testing with Codex assistance. See PROVENANCE.md for the contribution record. MIT license applies to the team's original project code; dependency licenses remain their own.

SonicGuide.AI is an advanced audio tour generation platform that transforms travel and exploration into immersive storytelling. Leveraging multiple specialized agents—such as History, Architecture, Culinary, and Culture—SonicGuide crafts rich, engaging audio tours tailored to the user’s interests. The system uses a Streamlit interface for easy user interaction, where users input a destination, select their preferred topics, adjust settings like duration and voice style, and generate a complete audio tour that can be listened to or downloaded as an offline MP3. With AI-powered content generation (using OpenAI models and real-time web search) and text-to-speech, SonicGuide.AI delivers tours in under 60 seconds, covering any location globally. It aims to bridge gaps in existing solutions by offering dynamic, personalized, and multi-topic audio content, while also addressing accessibility and cultural engagement. Under the MIT license, SonicGuide is open for contributions and enhancements, including support for additional languages, accents, greater customization, and mobile / offline-first applications.

This project is an end-to-end medical chatbot designed to assist users with medical inquiries by providing accurate and reliable health information. The chatbot uses advanced natural language processing (NLP) and machine learning to understand user queries, identify intent, and deliver meaningful, personalized responses. Built with Python, TensorFlow, and NLTK, and integrated with APIs for real-time medical data, the system ensures robustness, scalability, and adaptability. It is supported by a comprehensive medical knowledge base covering diseases, symptoms, and treatments, continuously updated to maintain reliability. Users can interact with the chatbot via a simple interface across websites, mobile apps, and social media, making healthcare information accessible anytime, anywhere. Through contextual understanding and conversational flow, the chatbot provides a human-like experience, encouraging users to confidently seek medical guidance. The development process involved data collection from trusted medical sources, model training and fine-tuning, testing with user feedback, and deployment to live platforms. Looking ahead, the project envisions: Incorporating deep learning for enhanced understanding of complex queries Integration with telemedicine and healthcare services for appointment booking and actionable healthcare steps Multilingual support to reach diverse global communities A user feedback loop to continuously improve accuracy and user satisfaction By delivering instant, reliable responses, this chatbot can reduce the burden on healthcare professionals, promote self-care, and expand healthcare accessibility. It sets the stage for future innovations in AI-powered medical assistants, making quality healthcare information available to everyone.

💻 Online Hackathon | ⏳ Build: 48 hours | 📅 September 25–27, 2026 The official IBM Bob 2.0 hackathon. Build what's next in AI-assisted development, alongside the developers and experts shaping it. ⭐ Get help from experts throughout the event 🤝 Join a team or build solo 💰 Prize pool: $12,000 🧑🏻‍💻 Register before the Kick-Off Stream to start building with Bob

In this hybrid hackathon powered by Arc, developers will build the next generation of agentic commerce systems using Arc with USDC. Explore a world where AI agents and web services can pay for APIs, data, compute, and content in dynamic, usage-based ways, while Arc provides stablecoin-native settlement with predictable USDC fees and deterministic, sub-second finality. This hackathon is supported by Google & Google DeepMind, with a dedicated challenge and $40,000 in Google Cloud Platform (GCP) credits awarded for the best use of Gemini models and Google AI Studio. 📅 January 9 – 24, 2026 • Jan 9 – 23 (Online Phase) – Collaborate and build online with developers and AI innovators from around the world. All projects must be submitted by the end of the online phase on January 23rd. • Jan 23 (On‑site Build Day – San Francisco, CA) – Selected participants will be invited to an exclusive in‑person session to refine their projects and connect directly with mentors. • Jan 24 (On‑site Demos & Awards – San Francisco, CA) – Live pitching sessions to a panel of judges and ecosystem partners, followed by the official winner announcement. Get guidance from Arc and Circle experts through on-site support. 📍 On-site Venue (Jan 23–24): MindsDB SF AI Collective 3154 17th St, San Francisco, California, USA 🤝 Go solo or team up, it's your flow. 🏆Compete for $50,000 in USDC & GCP Credits. 📍 On-site participation is by invitation only. Travel and accommodation expenses will not be covered. 🧑🏻‍💻 Secure your spot now - sign up before the Kick-Off Stream!

Join the next edition of our flagship AI hackathon — now featuring Google, AppliedAI, and Qdrant as official partners, with over $45,500 in prizes and exclusive partner challenges. After an incredible launch earlier this year, we’re back with the next edition of our AI hackathon series leading up to the /function1 AI Conference & Exhibition in Dubai. Tap into the power of AI to innovate, build, and take your AI skills to the next level in this high-impact hybrid experience. 📅November 14–19, 2025 • Nov 14–18: Collaborate and build online with AI enthusiasts from around the world. All projects must be submitted by end of day on November 18 • Nov 18 (Dubai): An exclusive on-site build day at Festival Arena Dubai for selected participants. • Nov 19 (Dubai): Live on-stage pitching & winners announcement at the /function1 Conference. 🌟 Get support from expert mentors throughout. 👥 Go solo or team up. 📍 Please note: On-site participation is by invitation only. Travel and accommodation will not be covered for selected participants. Further details will be shared with those accepted. 🧑🏻‍💻 Secure your spot now—sign up before the Kick-Off Stream!