Skill: xsir0/google-gemini-media (version 1.0.1)

--- name: google-gemini-media description: Use the Gemini API (Nano Banana image generation, Veo video, Gemini TTS speech and audio understanding) to deliver end-to-end multimodal media workflows and code templates for "generation + understanding". license: MIT --- # Gemini Multimodal Media (Image/Video/Speech) Skill ## 1. Goals and scope This Skill consolidates six Gemini API capabilities into reusable workflows and implementation templates: - Image generation (Nano Banana: text-to-image, image editing, multi-turn iteration) - Image understanding (caption/VQA/classification/comparison, multi-image prompts; supports inline and Files API) - Video generation (Veo 3.1: text-to-video, aspect ratio/resolution control, reference-image guidance, first/last frames, video extension, native audio) - Video understanding (upload/inline/YouTube URL; summaries, Q&A, timestamped evidence) - Speech generation (Gemini native TTS: single-speaker and multi-speaker; controllable style/accent/pace/tone) - Audio understanding (upload/inline; description, transcription, time-range transcription, token counting) > Convention: This Skill follows the official Google Gen AI SDK (Node.js/REST) as the main line; currently only Node.js/REST examples are provided. If your project already wraps other languages or frameworks, map this Skill's request structure, model selection, and I/O spec to your wrapper layer. --- ## 2. Quick routing (decide which capability to use) 1) **Do you need to produce images?** - Need to generate images from scratch or edit based on an image -> use **Nano Banana image generation** (see Section 5) 2) **Do you need to understand images?** - Need recognition, description, Q&A, comparison, or info extraction -> use **Image understanding** (see Section 6) 3) **Do you need to produce video?** - Need to generate an 8-second video (optionally with native audio) -> use **Veo 3.1 video generation** (see Section 7) 4) **Do you need to understand video?** - Need summaries/Q&A/segment extraction with timestamps -> use **Video understanding** (see Section 8) 5) **Do you need to read text aloud?** - Need controllable narration, podcast/audiobook style, etc. -> use **Speech generation (TTS)** (see Section 9) 6) **Do you need to understand audio?** - Need audio descriptions, transcription, time-range transcription, token counting -> use **Audio understanding** (see Section 10) --- ## 3. Unified engineering constraints and I/O spec (must read) ### 3.0 Prerequisites (dependencies and tools) - Node.js 18+ (match your project version) - Install SDK (example): ```bash npm install @google/genai ``` - REST examples only need `curl`; if you need to parse image Base64, install `jq` (optional). ### 3.1 Authentication and environment variables - Put your API key in `GEMINI_API_KEY` - REST requests use `x-goog-[REDACTED_SECRET]` ### 3.2 Two file input modes: Inline vs Files API **Inline (embedded bytes/Base64)** - Pros: shorter call chain, good for small files. - Key constraint: total request size (text prompt + system instructions + embedded bytes) typically has a ~20MB ceiling. **Files API (upload then reference)** - Pros: good for large files, reusing the same file, or multi-turn conversations. - Typical flow: 1. `files.upload(...)` (SDK) or `POST /upload/v1beta/files` (REST resumable) 2. Use `file_data` / `file_uri` in `generateContent` > Engineering suggestion: implement `ensure_file_uri()` so that when a file exceeds a threshold (for example 10-15MB warning) or is reused, you automatically route through the Files API. ### 3.3 Unified handling of binary media outputs - **Images**: usually returned as `inline_data` (Base64) in response parts; in the SDK use `part.as_image()` or decode Base64 and save as PNG/JPG. - **Speech (TTS)**: usually returns **PCM** bytes (Base64); save as `.pcm` or wrap into `.wav` (commonly 24kHz, 16-bit, mono). - **Video (Veo)**: long-running async task; poll the operation; download the file (or use the returned URI). --- ## 4. Model selection matrix (choose by scenario) > Important: model names, versions, limits, and quotas can change over time. Verify against official docs before use. Last updated: 2026-01-22. ### 4.1 Image generation (Nano Banana) - **gemini-2.5-flash-image**: optimized for speed/throughput; good for frequent, low-latency generation/editing. - **gemini-3-pro-image-preview**: stronger instruction following and high-fidelity text rendering; better for professional assets and complex edits. ### 4.2 General image/video/audio understanding - Docs use `gemini-3-flash-preview` for image, video, and audio understanding (choose stronger models as needed for quality/cost). ### 4.3 Video generation (Veo) - Example model: `veo-3.1-generate-preview` (generates 8-second video and can natively generate audio). ### 4.4 Speech generation (TTS) - Example model: `gemini-2.5-flash-preview-tts` (native TTS, currently in preview). --- ## 5. Image generation (Nano Banana) ### 5.1 Text-to-Image **SDK (Node.js) minimal template** ```js import { GoogleGenAI } from "@google/genai"; import * as fs from "node:fs"; const ai = new GoogleGenAI({ [REDACTED_SECRET] }); const response = await ai.models.generateContent({ model: "gemini-2.5-flash-image", contents: "Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme", }); const parts = response.candidates?.[0]?.content?.parts ?? []; for (const part of parts) { if (part.text) console.log(part.text); if (part.inlineData?.data) { fs.writeFileSync("out.png", Buffer.from(part.inlineData.data, "base64")); } } ``` **REST (with imageConfig) minimal template** ```bash curl -s -X POST "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image:generateContent" -H "x-goog-[REDACTED_SECRET]" -H "Content-Type: application/json" -d '{ "contents":[{"parts":[{"text":"Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme"}]}], "generationConfig": {"imageConfig": {"aspectRatio":"16:9"}} }' ``` **REST image parsing (Base64 decode)** ```bash curl -s -X POST "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image:generateContent" \ -H "x-goog-[REDACTED_SECRET]" \ -H "Content-Type: application/json" \ -d '{"contents":[{"parts":[{"text":"A minimal studio product shot of a nano banana"}]}]}' \ | jq -r '.candidates[0].content.parts[] | select(.inline_data) | .inline_data.data' \ | base64 --decode > out.png # macOS can use: base64 -D > out.png ``` ### 5.2 Text-and-Image-to-Image Use case: given an image, **add/remove/modify elements**, change style, color grading, etc. **SDK (Node.js) minimal template** ```js import { GoogleGenAI } from "@google/genai"; import * as fs from "node:fs"; const ai = new GoogleGenAI({ [REDACTED_SECRET] }); const prompt = "Add a nano banana on the table, keep lighting consistent, cinematic tone."; const imageBase64 = fs.readFileSync("input.png").toString("base64"); const response = await ai.models.generateContent({ model: "gemini-2.5-flash-image", contents: [ { text: prompt }, { inlineData: { mimeType: "image/png", data: imageBase64 } }, ], }); const parts = response.candidates?.[0]?.content?.parts ?? []; for (const part of parts) { if (part.inlineData?.data) { fs.writeFileSync("edited.png", Buffer.from(part.inlineData.data, "base64")); } } ``` ### 5.3 Multi-turn image iteration (Multi-turn editing) Best practice: use chat for continuous iteration (for example: generate first, then "only edit a specific region/element", then "make variants in the same style"). To output mixed "text + image" results, set `response_modalities` to `["TEXT", "IMAGE"]`. ### 5.4 ImageConfig You can set in `generationConfig.imageConfig` or the SDK config: - `aspectRatio`: e.g. `16:9`, `1:1`. - `imageSize`: e.g. `2K`, `4K` (higher resolution is usually slower/more expensive and model support can vary). --- ## 6. Image understanding (Image Understanding) ### 6.1 Two ways to provide input images - **Inline image data**: suitable for small files (total request size < 20MB). - **Files API upload**: better for large files or reuse across multiple requests. ### 6.2 Inline images (Node.js) minimal template ```js import { GoogleGenAI } from "@google/genai"; import * as fs from "node:fs"; const ai = new GoogleGenAI({ [REDACTED_SECRET] }); const imageBase64 = fs.readFileSync("image.jpg").toString("base64"); const response = await ai.models.generateContent({ model: "gemini-3-flash-preview", contents: [ { inlineData: { mimeType: "image/jpeg", data: imageBase64 } }, { text: "Caption this image, and list any visible brands." }, ], }); console.log(response.text); ``` ### 6.3 Upload and reference with Files API (Node.js) minimal template ```js import { GoogleGenAI, createPartFromUri, createUserContent } from "@google/genai"; const ai = new GoogleGenAI({ [REDACTED_SECRET] }); const uploaded = await ai.files.upload({ file: "image.jpg" }); const response = await ai.models.generateContent({ model: "gemini-3-flash-preview", contents: createUserContent([ createPartFromUri(uploaded.uri, uploaded.mimeType), "Caption this image.", ]), }); console.log(response.text); ``` ### 6.4 Multi-image prompts Append multiple images as multiple `Part` entries in the same `contents`; you can mix uploaded references and inline bytes. --- ## 7. Video generation (Veo 3.1) ### 7.1 Core features (must know) - Generates **8-second** high-fidelity video, optionally 720p / 1080p / 4k, and supports native audio generation (dialogue, ambience, SFX). - Supports: - Aspect ratio (16:9 / 9:16) - Video extension (extend a generated video; typically limited to 720p) - First/last frame control (frame-specific) - Up to 3 reference images (image-based direction) ### 7.2 SDK (Node.js) minimal template: async polling + download ```js import { GoogleGenAI } from "@google/genai"; const ai = new GoogleGenAI({ [REDACTED_SECRET] }); const prompt = "A cinematic shot of a cat astronaut walking on the moon. Include subtle wind ambience."; let operation = await ai.models.generateVideos({ model: "veo-3.1-generate-preview", prompt, config: { resolution: "1080p" }, }); while (!operation.done) { await new Promise((resolve) => setTimeout(resolve, 10_000)); operation = await ai.operations.getVideosOperation({ operation }); } const video = operation.response?.generatedVideos?.[0]?.video; if (!video) throw new Error("No video returned"); await ai.files.download({ file: video, downloadPath: "out.mp4" }); ``` ### 7.3 REST minimal template: predictLongRunning + poll + download Key point: Veo REST uses `:predictLongRunning` to return an operation name, then poll `GET /v1beta/{operation_name}`; once done, download from the video URI in the response. ### 7.4 Common controls (recommend a unified wrapper) - `aspectRatio`: `"16:9"` or `"9:16"` - `resolution`: `"720p" | "1080p" | "4k"` (higher resolutions are usually slower/more expensive) - When writing prompts: put dialogue in quotes; explicitly call out SFX and ambience; use cinematography language (camera position, movement, composition, lens effects, mood). - Negative constraints: if the API supports a negative prompt field, use it; otherwise list elements you do not want to see. ### 7.5 Important limits (engineering fallback needed) - Latency can vary from seconds to minutes; implement timeouts and retries. - Generated videos are only retained on the server for a limited time (download promptly). - Outputs include a SynthID watermark. **Polling fallback (with timeout/backoff) pseudocode** ```js const deadline = Date.now() + 300_000; // 5 min let sleepMs = 2000; while (!operation.done && Date.now() < deadline) { await new Promise((resolve) => setTimeout(resolve, sleepMs)); sleepMs = Math.min(Math.floor(sleepMs * 1.5), 15_000); operation = await ai.operations.getVideosOperation({ operation }); } if (!operation.done) throw new Error("video generation timed out"); ``` --- ## 8. Video understanding (Video Understanding) ### 8.1 Video input options - **Files API upload**: recommended when file > 100MB, video length > ~1 minute, or you need reuse. - **Inline video data**: for smaller files. - **Direct YouTube URL**: can analyze public videos. ### 8.2 Files API (Node.js) minimal template ```js import { GoogleGenAI, createPartFromUri, createUserContent } from "@google/genai"; const ai = new GoogleGenAI({ [REDACTED_SECRET] }); const uploaded = await ai.files.upload({ file: "sample.mp4" }); const response = await ai.models.generateContent({ model: "gemini-3-flash-preview", contents: createUserContent([ createPartFromUri(uploaded.uri, uploaded.mimeType), "Summarize this video. Provide timestamps for key events.", ]), }); console.log(response.text); ``` ### 8.3 Timestamp prompting strategy - Ask for segmented bullets with "(mm:ss)" timestamps. - Require "evidence with specific time ranges" and include downstream structured extraction (JSON) in the same prompt if needed. --- ## 9. Speech generation (Text-to-Speech, TTS) ### 9.1 Positioning - Native TTS: for "precise reading + controllable style" (podcasts, audiobooks, ad voiceover, etc.). - Distinguish from the Live API: Live API is more interactive and non-structured audio/multimodal conversation; TTS is focused on controlled narration. ### 9.2 Single-speaker TTS (Node.js) minimal template ```js import { GoogleGenAI } from "@google/genai"; import * as fs from "node:fs"; const ai = new GoogleGenAI({ [REDACTED_SECRET] }); const response = await ai.models.generateContent({ model: "gemini-2.5-flash-preview-tts", contents: [{ parts: [{ text: "Say cheerfully: Have a wonderful day!" }] }], config: { responseModalities: ["AUDIO"], speechConfig: { voiceConfig: { prebuiltVoiceConfig: { voiceName: "Kore" }, }, }, }, }); const data = response.candidates?.[0]?.content?.parts?.[0]?.inlineData?.data ?? ""; if (!data) throw new Error("No audio returned"); fs.writeFileSync("out.pcm", Buffer.from(data, "base64")); ``` ### 9.3 Multi-speaker TTS (max 2 speakers) Requirements: - Use `multiSpeakerVoiceConfig` - Each speaker name must match the dialogue labels in the prompt (e.g., Joe/Jane). ### 9.4 Voice options and language - `voice_name` supports 30 prebuilt voices (for example Zephyr, Puck, Charon, Kore, etc.). - The model can auto-detect input language and supports 24 languages (see docs for the list). ### 9.5 "Director notes" (strongly recommended for high-quality voice) Provide controllable directions for style, pace, accent, etc., but avoid over-constraining. --- ## 10. Audio understanding (Audio Understanding) ### 10.1 Typical tasks - Describe audio content (including non-speech like birds, alarms, etc.) - Generate transcripts - Transcribe specific time ranges - Count tokens (for cost estimates/segmentation) ### 10.2 Files API (Node.js) minimal template ```js import { GoogleGenAI, createPartFromUri, createUserContent } from "@google/genai"; const ai = new GoogleGenAI({ [REDACTED_SECRET] }); const uploaded = await ai.files.upload({ file: "sample.mp3" }); const response = await ai.models.generateContent({ model: "gemini-3-flash-preview", contents: createUserContent([ "Describe this audio clip.", createPartFromUri(uploaded.uri, uploaded.mimeType), ]), }); console.log(response.text); ``` ### 10.3 Key limits and engineering tips - Supports common formats: WAV/MP3/AIFF/AAC/OGG/FLAC. - Audio tokenization: about 32 tokens/second (about 1920 tokens per minute; values may change). - Total audio length per prompt is capped at 9.5 hours; multi-channel audio is downmixed; audio is resampled (see docs for exact parameters). - If total request size exceeds 20MB, you must use the Files API. --- ## 11. End-to-end examples (composition) ### Example A: Image generation -> validation via understanding 1) Generate product images with Nano Banana (require negative space, consistent lighting). 2) Use image understanding for self-check: verify text clarity, brand spelling, and unsafe elements. 3) If not satisfied, feed the generated image into text+image editing and iterate. ### Example B: Video generation -> video understanding -> narration script 1) Generate an 8-second shot with Veo (include dialogue or SFX). 2) Download and save (respect retention window). 3) Upload video to video understanding to produce a storyboard + timestamps + narration copy (then feed to TTS). ### Example C: Audio understanding -> time-range transcription -> TTS redub 1) Upload meeting audio and transcribe full content. 2) Transcribe or summarize specific time ranges. 3) Use TTS to generate a "broadcast" version of the summary. --- ## 12. Compliance and risk (must follow) - Ensure you have the necessary rights to upload images/video/audio; do not generate infringing, deceptive, harassing, or harmful content. - Generated images and videos include SynthID watermarking; videos may also have regional/person-based generation constraints. - Production systems must implement timeouts, retries, failure fallbacks, and human review/post-processing for generated content. --- ## 13. Quick reference (Checklist) - [ ] Pick the right model: image generation (Flash Image / Pro Image Preview), video generation (Veo 3.1), TTS (Gemini 2.5 TTS), understanding (Gemini Flash/Pro). - [ ] Pick the right input mode: inline for small files; Files API for large/reuse. - [ ] Parse binary outputs correctly: image/audio via inline_data decode; video via operation polling + download. - [ ] For video generation: set aspectRatio / resolution, and download promptly (avoid expiration). - [ ] For TTS: set response_modalities=["AUDIO"]; max 2 speakers; speaker names must match prompt. - [ ] For audio understanding: countTokens when needed; segment long audio or use Files API.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)