Video Captioning

Streamlit
application badge
Created by team Null Pointers on July 07, 2026
AI StudioAnthropic ClaudeOpenAIAMD Developer CloudAMD ROCmCodex
Video Captioning

Frame2Caption is our team's solution for the video captioning challenge. Built by Null_Pointers, it takes a short video and generates four different caption styles: formal, sarcastic, humorous-tech, and humorous-non-tech. We used Gemini 2.5 Flash with prompt engineering instead of fine-tuning to keep the project simple, lightweight, and easy to run. The project follows a modular design with separate components for video validation, prompt handling, API communication, and caption generation. Our goal was to build a clean and reliable captioning pipeline that creates captions suitable for different audiences while staying easy to understand, extend, and deploy

Category tags:
GithubPresentationDemo
Explore more applications

Thymus

Thymus is a lightweight hybrid token-efficient router designed to maximize accuracy while minimizing token costs in multi‑task LLM pipelines. It dynamically routes user queries across local and remote models on LLM providers.

The Disappointer

HuggingFace HubLLaMAAMD Developer Cloud
Vercel
application badge

AI Classroom Edge Intelligence

A privacy-first classroom AI platform that routes sensitive work to local edge systems and eligible anonymized analysis to Fireworks AI, helping teachers make faster, safer instructional decisions even with unreliable internet.

AI Classroom Edge

AMD Developer CloudQwen3rest apiGithub CopilotCodexChatGPT

Taskly: Smart Multi-Model Task Router

Taskly classifies incoming tasks into 8 categories (QA, math, code, NLP) and routes each to the optimal Fireworks AI model with a tuned prompt — maximizing accuracy while minimizing token usage in a fully Dockerized pipeline.

RuntimeTerror

AMD Developer CloudAMD ROCm
Streamlit
application badge

router_007_v3

router_007_v2 is a Track 1 agent that records **zero billable tokens**: every answer is computed inside the container by a Qwen2.5-7B-Instruct model bundled in the Docker image and served in-process with llama-cpp-python

roc_auc_half

Claude CodeChatGPTAMD ROCmAMD Developer CloudCodexGemmaGPT-5NVIDIAQwen3

Lexyprep

Agent knows how to make thorough legal research based on my experience of winning legal cases. It understands your issue and advises on procedure

Lexyprep - Do you have a case

AMD Developer CloudAMD ROCmCodexGemma