Omni Flash

Nano Banana is the informal name for Google's Gemini 2.5 Flash Image generative AI model, used to create and edit images from text and image prompts. It supports applications such as product concepts, landscape visualizations, virtual staging, and promotional graphics.

Google's developer API for building applications with Gemini large language models. It provides access to models like Gemini 2.0 Flash and 2.5 Pro, and also supports Gemma open models. Developers use it for tasks such as custom model testing, retrieval, memory, and tool-calling systems.

The Gemini Interactions API is Google's unified API for calling Gemini models and specialized agents. It maintains server-side interaction state through interaction IDs and the `previous_interaction_id` parameter, while also supporting stateless requests. Each Interaction resource contains a chronological sequence of execution steps, including model thoughts, tool calls and results, and final output. The API supports text and multimodal generation, structured and strongly typed outputs, built-in and custom tools, tool orchestration, observable execution steps, background execution for long-running tasks, and chained image, video, and audio generation using shared context. Google documents it as generally available and recommends it for new Gemini API projects.

Finger Frame AI is a browser app and Python CLI pipeline by Sophia Yang that places an AI-generated world inside a two-hand finger-frame gesture. It sends an uploaded video to Gemini Omni Flash for video-to-video restyling using a selected style or custom prompt, with alignment instructions intended to preserve framing, facial positions, expressions, blinks, gaze, and motion. MediaPipe Hand Landmarker then tracks both hands and the finger-frame quadrilateral frame by frame; the tracking pipeline uses anatomical corner ordering, spread and area gates with hysteresis, teleport rejection, velocity-adaptive smoothing, dropout holding, and presence fading. The compositor reveals the restyled video through the tracked quadrilateral and adds a dashed outline with pulsing corner markers. The browser app exports MP4 where browser recording supports it and otherwise WebM. The CLI separates restyling and compositing into `stylize.py` and `composite.py`, accepts formats readable by FFmpeg or OpenCV, and can produce H.264 MP4 while retaining the original audio track when present. Users provide their own Gemini API key; the app keeps it in the browser and sends it only to Google's API. Generation is billed per video, and the app recommends keeping uploads under about 15 MB. A no-key placeholder mode runs the tracking, compositing, and export pipeline with a hue-shifted stand-in.

Gemini is Google's AI model and assistant accessible through gemini.google.com. It processes mixed media including video, audio, images, and text, and can convert recordings into SOPs, summarize meetings, extract decisions, and draft follow-up emails. In research and development contexts, it serves as an alternative LLM backend for tasks such as adversarial audits of requirements and resume evaluation.