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feat(video): add Gemini Omni Flash provider with conversational editing
Add gemini_omni_video, a native Gemini API provider wrapping gemini-omni-flash-preview via the Interactions API. Text-to-video, image/reference-to-video with <FIRST_FRAME>/<IMAGE_REF_N> prompt tags, and stateful edit_video turns via previous_interaction_id — the only provider in the fleet that can refine a clip without regenerating it. Reuses the existing GOOGLE_API_KEY / GEMINI_API_KEY, so one Google key now unlocks images, TTS, and video. - New Layer 3 skill .agents/skills/gemini-omni (prompting, edit-loop rules, tag/timecode syntax, preview limits) sourced from official Google docs; linked via agent_skills and the AGENT_GUIDE Layer 3 map - ai-video-gen gains the Gemini API gateway row + editing pointer - veo_video/sora_video fallback lists and video_selector agent_skills reference the new provider; quality_score 0.85 with rationale - Contract tests: registry discovery, selector routing, status from env keys, uri + inline delivery, edit turns, typed image parts, store=false editability, cost clamp
This commit is contained in:
calesthio
@@ -1,7 +1,7 @@
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---
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name: ai-video-gen
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description: |
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Generate AI videos from text prompts using multiple provider gateways. Use when: (1) Generating videos from text descriptions, (2) Creating AI-generated video clips for content production, (3) Image-to-video generation with a reference image, (4) Choosing between video generation providers (VEO, Kling, Sora, Runway, Seedance, MiniMax). Supports two gateways: HeyGen API and fal.ai API.
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Generate AI videos from text prompts using multiple provider gateways. Use when: (1) Generating videos from text descriptions, (2) Creating AI-generated video clips for content production, (3) Image-to-video generation with a reference image, (4) Choosing between video generation providers (VEO, Kling, Sora, Runway, Seedance, MiniMax, Gemini Omni). Supports gateways: HeyGen API, fal.ai API, and the Gemini API (Gemini Omni Flash).
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allowed-tools: mcp__heygen__*
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metadata:
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openclaw:
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@@ -9,6 +9,8 @@ metadata:
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env_any:
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- HEYGEN_API_KEY
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- FAL_KEY
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- GEMINI_API_KEY
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- GOOGLE_API_KEY
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---
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# Video Generation (Multi-Gateway)
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@@ -19,6 +21,9 @@ Generate AI videos from text prompts. Supports multiple providers via two API ga
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|---------|-------------|-----------|------|
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| **fal.ai** | `FAL_KEY` | **Seedance 2.0** (standard + fast), Kling v3/v2.1, MiniMax, VEO | `seedance_video`, `kling_video`, `minimax_video`, `veo_video` |
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| **HeyGen** | `HEYGEN_API_KEY` | VEO 3.1, Kling Pro, Sora v2, Runway Gen-4, Seedance Pro / Lite (1.x) | `heygen_video` |
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| **Gemini API** | `GEMINI_API_KEY` / `GOOGLE_API_KEY` | Gemini Omni Flash (generation + conversational editing) | `gemini_omni_video` |
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**Iterative editing — Gemini Omni.** When the brief calls for *refining an existing clip* (add/remove objects, restyle, change lighting or on-screen text) rather than regenerating, Gemini Omni Flash is the only provider in the fleet with stateful multi-turn editing. See Layer 3 `gemini-omni` for the authoritative prompting guide (reference-image tags, timecode syntax, edit-prompt rules) before writing any prompt for it.
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**Preferred premium default — Seedance 2.0.** When any premium gateway is configured (`FAL_KEY` → `seedance_video`, or HeyGen's Video Agent / Avatar Shots path), Seedance 2.0 is the preferred default for cinematic, trailer, and high-fidelity clip work. It is the only model in the fleet with **single-pass native synchronized audio, multi-shot generation, director-level camera control, and lip-sync from quoted dialogue**, and it ranks #1 on Artificial Analysis Elo as of early 2026. Switch off it only when the user has a specific reason (budget, provider preference, stylistic fit like VEO for photoreal landscape or Kling for specific anime look). See Layer 3 `seedance-2-0` for the authoritative prompting and parameter guide.
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113
.agents/skills/gemini-omni/SKILL.md
Normal file
113
.agents/skills/gemini-omni/SKILL.md
Normal file
@@ -0,0 +1,113 @@
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---
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name: gemini-omni
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description: |
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Generate and conversationally edit short videos with Google Gemini Omni Flash (`gemini-omni-flash-preview`). Use when: (1) iterating on a clip with natural-language edits instead of regenerating ("make the phone invisible, keep everything else the same"), (2) generating 3-10s 720p clips with synthesized audio, rendered on-screen text, or timecoded beats, (3) binding reference images to roles with <FIRST_FRAME>/<IMAGE_REF_N> prompt tags, (4) editing an existing uploaded video. Accessed via the `gemini_omni_video` tool using the project's GEMINI_API_KEY/GOOGLE_API_KEY — the same key as Imagen and Google TTS.
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allowed-tools: Bash, Read, Write
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metadata:
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openclaw:
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requires:
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env_any:
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- GEMINI_API_KEY
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- GOOGLE_API_KEY
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---
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# Gemini Omni Flash (Google DeepMind)
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Gemini Omni is Google DeepMind's video generation **and editing** model family, announced at I/O 2026. The first model, **Gemini Omni Flash** (`gemini-omni-flash-preview`, developer access since June 30, 2026), generates 3-10 second clips at 720p/24fps with synthesized audio via the Gemini **Interactions API**. Its differentiator in the OpenMontage fleet is **stateful conversational editing**: each generation returns an `interaction_id`, and a follow-up call with `previous_interaction_id` edits that video in place — no other wrapped provider can refine a clip without regenerating it.
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OpenMontage wraps it as `gemini_omni_video` (native Gemini API, no gateway). It shares `GOOGLE_API_KEY`/`GEMINI_API_KEY` with `google_imagen` and `google_tts` — one key, three capabilities. Paid tier only: ~$0.10 per second of output video (billed as 5,792 output tokens/sec at $17.50/1M).
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## When to pick it (and when not)
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| Use it for | Prefer another provider for |
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|---|---|
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| Iterative refinement — generate, review, then edit the same clip in layers | One-shot cinematic hero clips (→ Seedance 2.0, see `seedance-2-0`) |
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| Editing an existing/uploaded clip (restyle, add/remove objects, change text) | Clips longer than 10s or above 720p |
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| On-screen rendered text and word-by-word text beats | Seed-reproducible generations (no seed support) |
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| Reference-image-bound subjects/styles via prompt tags | First/last-frame interpolation (→ `veo_video`) |
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| Timecode-scheduled multi-beat clips from one prompt | Non-English narration (English only fully supported) |
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Route through `video_selector` for generation operations. **Editing (`edit_video`) is a direct-tool operation** — call `gemini_omni_video` from the registry, because the multi-turn interaction state lives outside the selector's model.
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## Generation prompting
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Describe **scene + camera + lighting + motion + audio**. Official example:
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> Continuous, unbroken handheld shot of a fluffy tabby cat sitting on a sunny windowsill, looking out into a leafy garden. The cat's tail twitches slowly, and its ears rotate slightly toward ambient noises. Sunbeams illuminate dust motes in the air.
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- **Force a single shot** explicitly: "In a single continuous shot," / "No scene cuts." Otherwise the model may cut between scenes.
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- **Negatives go in prose** — there is no `negative_prompt` parameter: "No dialogue," "No extra sound effects."
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- **No sampler controls**: system instructions, temperature, top_p, and seeds are all unsupported. The prompt is the only lever.
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- **Meta-prompt for quality**: "Consider micro-detail, expression and timing to create a very rich, detailed but entirely natural scene."
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### Timecode syntax
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Schedule beats with bracketed ranges or natural language — this maps directly onto OpenMontage scene-plan timings:
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```
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[0-3s] A person is walking [3-6s] They stop and turn around
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```
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> "After 3 seconds, a woman enters the scene." / "At 5s the chorus starts in the background audio."
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### Audio and on-screen text
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Audio is synthesized automatically; direct it in the prompt: "Include calm background music," "The audio is a low tinny radio broadcast in the background." Rendered text works and can be timed:
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> One word on the screen at a time: 'did, you, know, that, Omni, can, do, awesome, text?' Each word appears for 1s.
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## Reference images (`<FIRST_FRAME>` / `<IMAGE_REF_N>` tags)
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Pass local images via `reference_image_paths` (they are sent in order), then bind them to roles **inside the prompt** with tags. `<IMAGE_REF_N>` indexes from 0 in the order supplied:
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```
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in the style of <IMAGE_REF_0> a woman <IMAGE_REF_1> is walking
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```
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```
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[0-3s] A studio fashion sequence. Starting with woman <IMAGE_REF_0>, she is
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holding <IMAGE_REF_1> [3-6s] Then we see the man <IMAGE_REF_2> holding <IMAGE_REF_3>
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```
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- `<FIRST_FRAME>` makes an image the opening frame: `<FIRST_FRAME> a woman is walking`.
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- Use high-resolution images; describe the intended motion specifically rather than "make it move."
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- Say what each image *is* (product / character / style / background reference) — the model decides usage from context.
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## Conversational editing (the differentiator)
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**Editing prompts are the opposite of generation prompts: short and surgical.** Overly descriptive edit prompts cause unintended changes.
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1. Generate the base clip (subject + scene + motion). The tool returns `interaction_id` in its result data.
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2. Pass it back as `previous_interaction_id` with `operation="edit_video"` and describe **only the delta**.
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3. Append **"Keep everything else the same."** to pin unmentioned elements.
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4. Refine in layers — one turn for lighting, one for camera, one for action, one for audio.
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Official good/bad pairs:
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| Avoid | Instead |
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|---|---|
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| "In the video of the man sitting on the sofa, please add a small black cat..." | "Add a cat that jumps onto his lap, he begins to pet it. Keep everything else the same." |
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| "Please remove the cell phone... and fill in the background so it looks like..." | "Make the phone invisible. Keep everything else the same." |
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Other working edit prompts: "Make this video anime" / "Put a fashionable hat on this person" / "Change the lighting to be more dramatic" / "Change the text on the sign to say 'Omni Flash'".
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**Gotcha — `store`:** editing via `previous_interaction_id` only works if the *prior* call kept the interaction server-side (`store` defaults to true in `gemini_omni_video`). Set `store=false` only for one-shot generations you will never edit.
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**Editing uploaded videos:** pass `input_video_path` instead of `previous_interaction_id`; the tool uploads it via the Files API. Unavailable in the EEA, Switzerland, and the UK (editing *generated* videos works everywhere).
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## Hard limitations (preview)
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- Output: 3-10s, 720p, 24fps, MP4 with audio; aspect ratio `16:9` or `9:16`. All output carries an invisible SynthID watermark.
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- No seed, negative prompt, temperature, top_p, or system instructions.
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- No video extension or first/last-frame interpolation; no voice editing.
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- Audio reference inputs unsupported. Video references ≤3s are accepted by the schema but **not processed correctly** — don't rely on them.
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- Multi-video prompting unsupported; may degrade output.
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- English fully supported; other languages untested.
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- Images of minors (EEA/CH/UK) and certain recognizable people are blocked for upload/editing.
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## Sources
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- Generation & editing guide: https://ai.google.dev/gemini-api/docs/omni
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- Model card: https://ai.google.dev/gemini-api/docs/models/gemini-omni-flash
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- Pricing: https://ai.google.dev/gemini-api/docs/pricing
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- Announcement: https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-omni/
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@@ -1,7 +1,7 @@
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---
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name: ai-video-gen
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description: |
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Generate AI videos from text prompts using multiple provider gateways. Use when: (1) Generating videos from text descriptions, (2) Creating AI-generated video clips for content production, (3) Image-to-video generation with a reference image, (4) Choosing between video generation providers (VEO, Kling, Sora, Runway, Seedance, MiniMax). Supports two gateways: HeyGen API and fal.ai API.
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Generate AI videos from text prompts using multiple provider gateways. Use when: (1) Generating videos from text descriptions, (2) Creating AI-generated video clips for content production, (3) Image-to-video generation with a reference image, (4) Choosing between video generation providers (VEO, Kling, Sora, Runway, Seedance, MiniMax, Gemini Omni). Supports gateways: HeyGen API, fal.ai API, and the Gemini API (Gemini Omni Flash).
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allowed-tools: mcp__heygen__*
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metadata:
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openclaw:
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@@ -9,6 +9,8 @@ metadata:
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env_any:
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- HEYGEN_API_KEY
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- FAL_KEY
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- GEMINI_API_KEY
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- GOOGLE_API_KEY
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---
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# Video Generation (Multi-Gateway)
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@@ -19,6 +21,9 @@ Generate AI videos from text prompts. Supports multiple providers via two API ga
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|---------|-------------|-----------|------|
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| **fal.ai** | `FAL_KEY` | **Seedance 2.0** (standard + fast), Kling v3/v2.1, MiniMax, VEO | `seedance_video`, `kling_video`, `minimax_video`, `veo_video` |
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| **HeyGen** | `HEYGEN_API_KEY` | VEO 3.1, Kling Pro, Sora v2, Runway Gen-4, Seedance Pro / Lite (1.x) | `heygen_video` |
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| **Gemini API** | `GEMINI_API_KEY` / `GOOGLE_API_KEY` | Gemini Omni Flash (generation + conversational editing) | `gemini_omni_video` |
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**Iterative editing — Gemini Omni.** When the brief calls for *refining an existing clip* (add/remove objects, restyle, change lighting or on-screen text) rather than regenerating, Gemini Omni Flash is the only provider in the fleet with stateful multi-turn editing. See Layer 3 `gemini-omni` for the authoritative prompting guide (reference-image tags, timecode syntax, edit-prompt rules) before writing any prompt for it.
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**Preferred premium default — Seedance 2.0.** When any premium gateway is configured (`FAL_KEY` → `seedance_video`, or HeyGen's Video Agent / Avatar Shots path), Seedance 2.0 is the preferred default for cinematic, trailer, and high-fidelity clip work. It is the only model in the fleet with **single-pass native synchronized audio, multi-shot generation, director-level camera control, and lip-sync from quoted dialogue**, and it ranks #1 on Artificial Analysis Elo as of early 2026. Switch off it only when the user has a specific reason (budget, provider preference, stylistic fit like VEO for photoreal landscape or Kling for specific anime look). See Layer 3 `seedance-2-0` for the authoritative prompting and parameter guide.
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@@ -16,9 +16,11 @@ HIGGSFIELD_API_KEY= # Higgsfield Cloud key (higgsfield_video). Pair wit
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HIGGSFIELD_API_SECRET= # or use the combined HIGGSFIELD_KEY="<key>:<secret>" form instead.
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# HIGGSFIELD_KEY= # Combined key:secret — set this INSTEAD of the _KEY/_SECRET pair if you prefer.
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# --- Google (one key unlocks image gen + TTS) ---
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GOOGLE_API_KEY= # Google Imagen images, Google Cloud TTS (700+ voices, 50+ languages)
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# --- Google (one key unlocks image gen + TTS + video) ---
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GOOGLE_API_KEY= # Google Imagen images, Google Cloud TTS (700+ voices, 50+ languages),
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# Gemini Omni video (generation + conversational editing, paid tier)
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# Get one at https://aistudio.google.com/apikey
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# GEMINI_API_KEY= # Alias for GOOGLE_API_KEY (takes precedence when both are set)
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# Alternative to the API key: service-account JSON auth.
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# TTS uses Cloud Text-to-Speech; Imagen routes to Vertex AI.
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GOOGLE_APPLICATION_CREDENTIALS= # path to a service-account JSON key file
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@@ -676,7 +676,7 @@ The `.agents/skills/` directory is large. When you're not coming in through a to
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| **Animation knowledge (generic)** | `gsap-core`, `gsap-timeline`, `gsap-plugins` (SplitText / MorphSVG / DrawSVG / MotionPath / Flip / CustomEase), `gsap-utils`, `gsap-react`, `gsap-performance`, `gsap-scrolltrigger`, `gsap-frameworks`, `framer-motion` (Disney 12 principles), `lottie-bodymovin` (Lottie export) |
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| **Character animation** | `character-rigging`, `svg-character-animation`, `pose-library-design`, `canvas-procedural-animation`, `character-animation-qa` |
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| **Image generation** | `bfl-api`, `flux-best-practices` |
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| **Video generation** | `seedance-2-0` (preferred premium default — cinematic, trailer, multi-shot, synced audio, lip-sync), `ai-video-gen`, `ltx2` |
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| **Video generation** | `seedance-2-0` (preferred premium default — cinematic, trailer, multi-shot, synced audio, lip-sync), `gemini-omni` (conversational video editing, reference tags, timecoded beats), `ai-video-gen`, `ltx2` |
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| **Audio** | `elevenlabs`, `music`, `sound-effects`, `acestep`, `text-to-speech`, `setup-api-key` |
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| **Avatar / lip-sync** | `avatar-video`, `heygen`, `create-video`, `faceswap`, `video-translate`, `speech-to-text`, `agents` |
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| **Capture** | `playwright-recording` (browser flows), `ffmpeg` (post) |
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244
tests/tools/test_gemini_omni_video.py
Normal file
244
tests/tools/test_gemini_omni_video.py
Normal file
@@ -0,0 +1,244 @@
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"""Regression coverage for first-class Gemini Omni provider discovery and execution."""
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from __future__ import annotations
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import base64
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import json
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import sys
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import types
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from pathlib import Path
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import pytest
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from tools.base_tool import ToolStatus
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class FakeResponse:
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def __init__(self, json_data=None, content=b"", ok=True, status_code=200, headers=None, text=""):
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self._json = json_data
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self.content = content
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self.ok = ok
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self.status_code = status_code
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self.headers = headers or {}
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self.text = text or (json.dumps(json_data) if json_data is not None else "")
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def json(self):
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return self._json
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def raise_for_status(self):
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if not self.ok:
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raise RuntimeError(f"HTTP {self.status_code}")
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def _install_fake_requests(monkeypatch, post_responses, get_responses):
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"""Inject a fake requests module; returns the recorded calls."""
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calls = {"post": [], "get": []}
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fake = types.ModuleType("requests")
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def fake_post(url, headers=None, json=None, data=None, timeout=None, params=None):
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calls["post"].append({"url": url, "headers": headers, "json": json, "data": data})
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return post_responses.pop(0)
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def fake_get(url, headers=None, timeout=None, params=None):
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calls["get"].append({"url": url, "headers": headers, "params": params})
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return get_responses.pop(0)
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fake.post = fake_post
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fake.get = fake_get
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monkeypatch.setitem(sys.modules, "requests", fake)
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return calls
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@pytest.fixture()
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def gemini_env(monkeypatch):
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monkeypatch.delenv("GOOGLE_API_KEY", raising=False)
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monkeypatch.setenv("GEMINI_API_KEY", "test-gemini-key")
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def test_gemini_omni_is_discovered_as_video_provider():
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from tools.tool_registry import ToolRegistry
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registry = ToolRegistry()
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registry.discover()
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tool = registry.get("gemini_omni_video")
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assert tool is not None
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assert tool.provider == "gemini_omni"
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assert tool.capability == "video_generation"
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# Ranking + selector-filter contract: without these the scorer buries the
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# editing capability and the selector drops it from image_to_video routing.
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assert tool.quality_score == 0.85
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assert tool.supports["image_to_video"] is True
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assert tool.supports["reference_to_video"] is True
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assert tool.supports["conversational_editing"] is True
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assert "gemini-omni" in tool.agent_skills
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def test_gemini_omni_is_routed_by_video_selector():
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from tools.video.video_selector import VideoSelector
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provider_names = [t.name for t in VideoSelector()._providers()]
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assert "gemini_omni_video" in provider_names
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def test_gemini_omni_status_tracks_google_api_keys(monkeypatch):
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from tools.video.gemini_omni_video import GeminiOmniVideo
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monkeypatch.delenv("GEMINI_API_KEY", raising=False)
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monkeypatch.delenv("GOOGLE_API_KEY", raising=False)
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assert GeminiOmniVideo().get_status() == ToolStatus.UNAVAILABLE
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monkeypatch.setenv("GOOGLE_API_KEY", "test-google-key")
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assert GeminiOmniVideo().get_status() == ToolStatus.AVAILABLE
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def test_gemini_omni_cost_estimate_clamps_duration_hint(gemini_env):
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from tools.video.gemini_omni_video import GeminiOmniVideo
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tool = GeminiOmniVideo()
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assert tool.estimate_cost({"prompt": "x"}) == pytest.approx(0.80)
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assert tool.estimate_cost({"prompt": "x", "duration": "5s"}) == pytest.approx(0.50)
|
||||
assert tool.estimate_cost({"prompt": "x", "duration": "30"}) == pytest.approx(1.00)
|
||||
|
||||
|
||||
def test_gemini_omni_text_to_video_via_uri_delivery(monkeypatch, tmp_path, gemini_env):
|
||||
from tools.video.gemini_omni_video import GeminiOmniVideo
|
||||
|
||||
calls = _install_fake_requests(
|
||||
monkeypatch,
|
||||
post_responses=[
|
||||
FakeResponse({"id": "int_123", "output_video": {"uri": "files/vid-123"}}),
|
||||
],
|
||||
get_responses=[
|
||||
FakeResponse({"state": "ACTIVE"}),
|
||||
FakeResponse(content=b"fake omni mp4"),
|
||||
],
|
||||
)
|
||||
|
||||
output_path = tmp_path / "clip.mp4"
|
||||
result = GeminiOmniVideo().execute(
|
||||
{
|
||||
"prompt": "A marble rolling on a track, single continuous shot.",
|
||||
"aspect_ratio": "9:16",
|
||||
"output_path": str(output_path),
|
||||
}
|
||||
)
|
||||
|
||||
assert result.success, result.error
|
||||
assert output_path.read_bytes() == b"fake omni mp4"
|
||||
assert result.data["interaction_id"] == "int_123"
|
||||
assert result.data["editable"] is True
|
||||
|
||||
payload = calls["post"][0]["json"]
|
||||
assert payload["model"] == "gemini-omni-flash-preview"
|
||||
assert payload["input"] == "A marble rolling on a track, single continuous shot."
|
||||
assert payload["response_format"] == {"type": "video", "aspect_ratio": "9:16", "delivery": "uri"}
|
||||
assert calls["post"][0]["headers"]["x-goog-api-key"] == "test-gemini-key"
|
||||
assert calls["get"][1]["url"].endswith("files/vid-123:download")
|
||||
assert calls["get"][1]["params"] == {"alt": "media"}
|
||||
|
||||
|
||||
def test_gemini_omni_inline_data_response_is_handled(monkeypatch, tmp_path, gemini_env):
|
||||
from tools.video.gemini_omni_video import GeminiOmniVideo
|
||||
|
||||
inline = base64.b64encode(b"inline mp4").decode("ascii")
|
||||
calls = _install_fake_requests(
|
||||
monkeypatch,
|
||||
post_responses=[FakeResponse({"id": "int_9", "output_video": {"data": inline}})],
|
||||
get_responses=[],
|
||||
)
|
||||
|
||||
output_path = tmp_path / "inline.mp4"
|
||||
result = GeminiOmniVideo().execute({"prompt": "A sunset.", "output_path": str(output_path)})
|
||||
|
||||
assert result.success, result.error
|
||||
assert output_path.read_bytes() == b"inline mp4"
|
||||
assert calls["get"] == []
|
||||
|
||||
|
||||
def test_gemini_omni_edit_turn_sends_previous_interaction_id(monkeypatch, tmp_path, gemini_env):
|
||||
from tools.video.gemini_omni_video import GeminiOmniVideo
|
||||
|
||||
inline = base64.b64encode(b"edited mp4").decode("ascii")
|
||||
calls = _install_fake_requests(
|
||||
monkeypatch,
|
||||
post_responses=[FakeResponse({"id": "int_2", "output_video": {"data": inline}})],
|
||||
get_responses=[],
|
||||
)
|
||||
|
||||
result = GeminiOmniVideo().execute(
|
||||
{
|
||||
"prompt": "Make the violin invisible. Keep everything else the same.",
|
||||
"operation": "edit_video",
|
||||
"previous_interaction_id": "int_1",
|
||||
"output_path": str(tmp_path / "edit.mp4"),
|
||||
}
|
||||
)
|
||||
|
||||
assert result.success, result.error
|
||||
assert calls["post"][0]["json"]["previous_interaction_id"] == "int_1"
|
||||
|
||||
|
||||
def test_gemini_omni_edit_without_source_is_rejected(gemini_env):
|
||||
from tools.video.gemini_omni_video import GeminiOmniVideo
|
||||
|
||||
result = GeminiOmniVideo().execute({"prompt": "Make it anime", "operation": "edit_video"})
|
||||
assert not result.success
|
||||
assert "previous_interaction_id" in result.error
|
||||
|
||||
|
||||
def test_gemini_omni_image_to_video_sends_typed_parts(monkeypatch, tmp_path, gemini_env):
|
||||
from tools.video.gemini_omni_video import GeminiOmniVideo
|
||||
|
||||
ref = tmp_path / "cat.png"
|
||||
ref.write_bytes(b"png bytes")
|
||||
inline = base64.b64encode(b"cat mp4").decode("ascii")
|
||||
calls = _install_fake_requests(
|
||||
monkeypatch,
|
||||
post_responses=[FakeResponse({"id": "int_3", "output_video": {"data": inline}})],
|
||||
get_responses=[],
|
||||
)
|
||||
|
||||
result = GeminiOmniVideo().execute(
|
||||
{
|
||||
"prompt": "A cat <IMAGE_REF_0> playfully batting at yarn.",
|
||||
"operation": "image_to_video",
|
||||
"reference_image_path": str(ref),
|
||||
"output_path": str(tmp_path / "cat.mp4"),
|
||||
}
|
||||
)
|
||||
|
||||
assert result.success, result.error
|
||||
parts = calls["post"][0]["json"]["input"]
|
||||
assert parts[0]["type"] == "image"
|
||||
assert parts[0]["mime_type"] == "image/png"
|
||||
assert parts[0]["data"] == base64.b64encode(b"png bytes").decode("ascii")
|
||||
assert parts[-1] == {"type": "text", "text": "A cat <IMAGE_REF_0> playfully batting at yarn."}
|
||||
|
||||
|
||||
def test_gemini_omni_image_to_video_requires_reference(gemini_env):
|
||||
from tools.video.gemini_omni_video import GeminiOmniVideo
|
||||
|
||||
result = GeminiOmniVideo().execute({"prompt": "x", "operation": "image_to_video"})
|
||||
assert not result.success
|
||||
assert "reference_image_path" in result.error
|
||||
|
||||
|
||||
def test_gemini_omni_store_false_marks_result_not_editable(monkeypatch, tmp_path, gemini_env):
|
||||
from tools.video.gemini_omni_video import GeminiOmniVideo
|
||||
|
||||
inline = base64.b64encode(b"oneshot mp4").decode("ascii")
|
||||
calls = _install_fake_requests(
|
||||
monkeypatch,
|
||||
post_responses=[FakeResponse({"id": "int_4", "output_video": {"data": inline}})],
|
||||
get_responses=[],
|
||||
)
|
||||
|
||||
result = GeminiOmniVideo().execute(
|
||||
{"prompt": "A sunset.", "store": False, "output_path": str(tmp_path / "s.mp4")}
|
||||
)
|
||||
|
||||
assert result.success, result.error
|
||||
assert result.data["editable"] is False
|
||||
assert calls["post"][0]["json"]["store"] is False
|
||||
437
tools/video/gemini_omni_video.py
Normal file
437
tools/video/gemini_omni_video.py
Normal file
@@ -0,0 +1,437 @@
|
||||
"""Google Gemini Omni Flash video generation and conversational editing.
|
||||
|
||||
Calls the Gemini Interactions API (``POST /v1beta/interactions``) directly with
|
||||
the project's Google API key — the same key that unlocks Imagen images and
|
||||
Cloud TTS. Gemini Omni Flash generates 3-10 second 720p/24fps clips with
|
||||
synthesized audio, and is the only provider in the fleet with stateful
|
||||
conversational editing: pass ``previous_interaction_id`` and describe only the
|
||||
delta ("Make the violin invisible. Keep everything else the same.").
|
||||
|
||||
Reference images bind to roles via inline prompt tags (``<FIRST_FRAME>``,
|
||||
``<IMAGE_REF_N>``) and beats can be scheduled with timecode syntax
|
||||
(``[0-3s] ... [3-6s] ...``). See the Layer 3 skill ``gemini-omni`` for the
|
||||
authoritative prompting guide — read it before writing prompts.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import base64
|
||||
import mimetypes
|
||||
import os
|
||||
import time
|
||||
from pathlib import Path
|
||||
from typing import Any
|
||||
|
||||
from tools.base_tool import (
|
||||
BaseTool,
|
||||
Determinism,
|
||||
ExecutionMode,
|
||||
ResourceProfile,
|
||||
RetryPolicy,
|
||||
ToolResult,
|
||||
ToolRuntime,
|
||||
ToolStability,
|
||||
ToolStatus,
|
||||
ToolTier,
|
||||
)
|
||||
|
||||
_BASE_URL = "https://generativelanguage.googleapis.com/v1beta"
|
||||
_UPLOAD_URL = "https://generativelanguage.googleapis.com/upload/v1beta/files"
|
||||
_DEFAULT_MODEL = "gemini-omni-flash-preview"
|
||||
# Billed at 5,792 output tokens per second of 720p video, $17.50/1M tokens
|
||||
# (ai.google.dev/gemini-api/docs/pricing) — effectively ~$0.10 per second.
|
||||
_COST_PER_SECOND = 0.10
|
||||
_DEFAULT_DURATION_SECONDS = 8
|
||||
_POLL_INTERVAL_SECONDS = 5
|
||||
_MAX_POLL_SECONDS = 900
|
||||
|
||||
|
||||
class GeminiOmniVideo(BaseTool):
|
||||
name = "gemini_omni_video"
|
||||
version = "0.1.0"
|
||||
tier = ToolTier.GENERATE
|
||||
capability = "video_generation"
|
||||
provider = "gemini_omni"
|
||||
stability = ToolStability.EXPERIMENTAL
|
||||
execution_mode = ExecutionMode.SYNC
|
||||
determinism = Determinism.STOCHASTIC
|
||||
runtime = ToolRuntime.API
|
||||
|
||||
dependencies = []
|
||||
install_instructions = (
|
||||
"Set GEMINI_API_KEY or GOOGLE_API_KEY to a Google AI Studio API key.\n"
|
||||
" Get one at https://aistudio.google.com/apikey\n"
|
||||
" Gemini Omni Flash is paid-tier only (no free tier); ~$0.10 per second of video."
|
||||
)
|
||||
agent_skills = ["gemini-omni", "ai-video-gen"]
|
||||
|
||||
capabilities = ["text_to_video", "image_to_video", "reference_to_video", "edit_video"]
|
||||
supports = {
|
||||
"text_to_video": True,
|
||||
"image_to_video": True,
|
||||
"reference_to_video": True,
|
||||
"edit_video": True,
|
||||
"conversational_editing": True,
|
||||
"native_audio": True,
|
||||
"text_rendering": True,
|
||||
"timecode_control": True,
|
||||
# Preview limitations — no sampler controls of any kind.
|
||||
"seed": False,
|
||||
"negative_prompt": False,
|
||||
"first_last_frame_to_video": False,
|
||||
}
|
||||
best_for = [
|
||||
"iterative natural-language video editing (edit a clip without regenerating it)",
|
||||
"reference-image-driven clips via <FIRST_FRAME>/<IMAGE_REF_N> prompt tags",
|
||||
"fast 3-10s clips with synced audio, rendered text, and timecoded beats from one Google key",
|
||||
]
|
||||
not_good_for = [
|
||||
"clips longer than 10 seconds or above 720p",
|
||||
"seed-reproducible output or negative-prompt control",
|
||||
"offline generation",
|
||||
]
|
||||
fallback_tools = ["veo_video", "sora_video", "kling_video", "minimax_video"]
|
||||
# Conversational editing + native audio are unique in the fleet, but preview
|
||||
# output is capped at 720p/10s — below seedance (0.95) and grok/runway (0.9)
|
||||
# on raw generation fidelity. Without a quality_score the scorer would only
|
||||
# count supports/stability flags and bury the editing capability entirely.
|
||||
# See lib/scoring.py.
|
||||
quality_score = 0.85
|
||||
|
||||
input_schema = {
|
||||
"type": "object",
|
||||
"required": ["prompt"],
|
||||
"properties": {
|
||||
"prompt": {
|
||||
"type": "string",
|
||||
"description": (
|
||||
"Video description, or for edit_video the change to apply. "
|
||||
"Supports <FIRST_FRAME>/<IMAGE_REF_N> tags and [0-3s] timecodes — "
|
||||
"see the gemini-omni skill."
|
||||
),
|
||||
},
|
||||
"operation": {
|
||||
"type": "string",
|
||||
"enum": ["text_to_video", "image_to_video", "reference_to_video", "edit_video"],
|
||||
"default": "text_to_video",
|
||||
},
|
||||
"aspect_ratio": {
|
||||
"type": "string",
|
||||
"enum": ["16:9", "9:16"],
|
||||
"default": "16:9",
|
||||
},
|
||||
"duration": {
|
||||
"type": "string",
|
||||
"description": (
|
||||
"Duration hint in seconds (3-10). The model chooses the actual length; "
|
||||
"this only shapes the prompt-independent cost estimate."
|
||||
),
|
||||
},
|
||||
"reference_image_path": {
|
||||
"type": "string",
|
||||
"description": "Local reference image (jpg/png) for image_to_video.",
|
||||
},
|
||||
"reference_image_paths": {
|
||||
"type": "array",
|
||||
"items": {"type": "string"},
|
||||
"description": "Local reference images, bound in the prompt as <IMAGE_REF_0>, <IMAGE_REF_1>, ...",
|
||||
},
|
||||
"previous_interaction_id": {
|
||||
"type": "string",
|
||||
"description": (
|
||||
"Interaction id from a prior gemini_omni_video result — edits that video "
|
||||
"in place (edit_video). Requires the prior call to have used store=true."
|
||||
),
|
||||
},
|
||||
"input_video_path": {
|
||||
"type": "string",
|
||||
"description": (
|
||||
"Local video to edit (edit_video). Uploaded via the Files API. "
|
||||
"Editing uploaded videos is unavailable in the EEA, Switzerland, and the UK."
|
||||
),
|
||||
},
|
||||
"store": {
|
||||
"type": "boolean",
|
||||
"default": True,
|
||||
"description": (
|
||||
"Keep the interaction server-side so the result can be edited in later turns "
|
||||
"via previous_interaction_id. Set false only for one-shot generations."
|
||||
),
|
||||
},
|
||||
"output_path": {"type": "string"},
|
||||
},
|
||||
}
|
||||
|
||||
resource_profile = ResourceProfile(
|
||||
cpu_cores=1, ram_mb=512, vram_mb=0, disk_mb=500, network_required=True
|
||||
)
|
||||
retry_policy = RetryPolicy(max_retries=1, retryable_errors=["rate_limit", "timeout"])
|
||||
idempotency_key_fields = ["prompt", "operation", "aspect_ratio", "previous_interaction_id"]
|
||||
side_effects = [
|
||||
"writes video file to output_path",
|
||||
"calls the Gemini Interactions API",
|
||||
"stores the interaction server-side when store=true (enables later edits)",
|
||||
]
|
||||
user_visible_verification = [
|
||||
"Watch generated clip for visual quality, motion, and prompt adherence",
|
||||
"Listen for synthesized audio quality and any requested dialogue/music",
|
||||
"After an edit turn, confirm unmentioned elements were preserved",
|
||||
]
|
||||
|
||||
@staticmethod
|
||||
def _get_api_key() -> str | None:
|
||||
return os.environ.get("GEMINI_API_KEY") or os.environ.get("GOOGLE_API_KEY")
|
||||
|
||||
def get_status(self) -> ToolStatus:
|
||||
if self._get_api_key():
|
||||
return ToolStatus.AVAILABLE
|
||||
return ToolStatus.UNAVAILABLE
|
||||
|
||||
@staticmethod
|
||||
def _duration_hint(inputs: dict[str, Any]) -> int:
|
||||
raw = str(inputs.get("duration") or _DEFAULT_DURATION_SECONDS).strip().lower()
|
||||
raw = raw[:-1] if raw.endswith("s") else raw
|
||||
try:
|
||||
seconds = int(float(raw))
|
||||
except ValueError:
|
||||
seconds = _DEFAULT_DURATION_SECONDS
|
||||
return max(3, min(10, seconds))
|
||||
|
||||
def estimate_cost(self, inputs: dict[str, Any]) -> float:
|
||||
return _COST_PER_SECOND * self._duration_hint(inputs)
|
||||
|
||||
def estimate_runtime(self, inputs: dict[str, Any]) -> float:
|
||||
return 180.0
|
||||
|
||||
@staticmethod
|
||||
def _image_part(path_str: str) -> dict[str, Any]:
|
||||
path = Path(path_str)
|
||||
if not path.exists():
|
||||
raise FileNotFoundError(f"Reference image not found: {path}")
|
||||
mime_type, _ = mimetypes.guess_type(path.name)
|
||||
if not mime_type or not mime_type.startswith("image/"):
|
||||
mime_type = "image/png"
|
||||
return {
|
||||
"type": "image",
|
||||
"data": base64.b64encode(path.read_bytes()).decode("ascii"),
|
||||
"mime_type": mime_type,
|
||||
}
|
||||
|
||||
def _upload_video_file(self, requests_mod: Any, api_key: str, path_str: str) -> str:
|
||||
"""Upload a local video via the Files API (resumable) and return its URI."""
|
||||
path = Path(path_str)
|
||||
if not path.exists():
|
||||
raise FileNotFoundError(f"Input video not found: {path}")
|
||||
mime_type, _ = mimetypes.guess_type(path.name)
|
||||
if not mime_type or not mime_type.startswith("video/"):
|
||||
mime_type = "video/mp4"
|
||||
video_bytes = path.read_bytes()
|
||||
|
||||
start_resp = requests_mod.post(
|
||||
_UPLOAD_URL,
|
||||
headers={
|
||||
"x-goog-api-key": api_key,
|
||||
"X-Goog-Upload-Protocol": "resumable",
|
||||
"X-Goog-Upload-Command": "start",
|
||||
"X-Goog-Upload-Header-Content-Length": str(len(video_bytes)),
|
||||
"X-Goog-Upload-Header-Content-Type": mime_type,
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
json={"file": {"display_name": path.name}},
|
||||
timeout=30,
|
||||
)
|
||||
start_resp.raise_for_status()
|
||||
upload_url = start_resp.headers.get("X-Goog-Upload-URL")
|
||||
if not upload_url:
|
||||
raise RuntimeError("Files API did not return an upload URL")
|
||||
|
||||
upload_resp = requests_mod.post(
|
||||
upload_url,
|
||||
headers={
|
||||
"X-Goog-Upload-Command": "upload, finalize",
|
||||
"X-Goog-Upload-Offset": "0",
|
||||
"Content-Length": str(len(video_bytes)),
|
||||
},
|
||||
data=video_bytes,
|
||||
timeout=300,
|
||||
)
|
||||
upload_resp.raise_for_status()
|
||||
file_info = upload_resp.json().get("file", {})
|
||||
|
||||
# Wait until the uploaded video is processed before referencing it.
|
||||
deadline = time.time() + _MAX_POLL_SECONDS
|
||||
while str(file_info.get("state", "")).upper() == "PROCESSING":
|
||||
if time.time() > deadline:
|
||||
raise TimeoutError("Uploaded video did not finish processing in time")
|
||||
time.sleep(_POLL_INTERVAL_SECONDS)
|
||||
status_resp = requests_mod.get(
|
||||
f"{_BASE_URL}/{file_info.get('name')}",
|
||||
headers={"x-goog-api-key": api_key},
|
||||
timeout=15,
|
||||
)
|
||||
status_resp.raise_for_status()
|
||||
file_info = status_resp.json()
|
||||
if str(file_info.get("state", "")).upper() == "FAILED":
|
||||
raise RuntimeError("Files API failed to process the uploaded video")
|
||||
|
||||
uri = file_info.get("uri")
|
||||
if not uri:
|
||||
raise RuntimeError(f"Files API response missing uri: {file_info}")
|
||||
return uri
|
||||
|
||||
@staticmethod
|
||||
def _extract_output_video(data: dict[str, Any]) -> dict[str, Any] | None:
|
||||
"""Find the output video payload ({'data': b64} or {'uri': files/...})."""
|
||||
for key in ("output_video", "outputVideo"):
|
||||
video = data.get(key)
|
||||
if isinstance(video, dict) and (video.get("data") or video.get("uri")):
|
||||
return video
|
||||
# REST responses may also carry the video inside steps[].content[].
|
||||
for step in data.get("steps") or []:
|
||||
for item in step.get("content") or []:
|
||||
if isinstance(item, dict) and (item.get("data") or item.get("uri")):
|
||||
if "video" in str(item.get("type", "")).lower() or item.get("mime_type", "").startswith("video/"):
|
||||
return item
|
||||
if item.get("data") or str(item.get("uri", "")).startswith("files/"):
|
||||
return item
|
||||
return None
|
||||
|
||||
def _download_via_uri(self, requests_mod: Any, api_key: str, uri: str) -> bytes:
|
||||
"""Poll a Files API entry until ACTIVE, then download its bytes."""
|
||||
file_id = uri.rstrip("/").split("/")[-1]
|
||||
headers = {"x-goog-api-key": api_key}
|
||||
deadline = time.time() + _MAX_POLL_SECONDS
|
||||
while True:
|
||||
status_resp = requests_mod.get(
|
||||
f"{_BASE_URL}/files/{file_id}", headers=headers, timeout=15
|
||||
)
|
||||
status_resp.raise_for_status()
|
||||
state = str(status_resp.json().get("state", "")).upper()
|
||||
if state == "ACTIVE":
|
||||
break
|
||||
if state == "FAILED":
|
||||
raise RuntimeError("Gemini Omni video generation failed during processing")
|
||||
if time.time() > deadline:
|
||||
raise TimeoutError("Timed out waiting for Gemini Omni video to become ACTIVE")
|
||||
time.sleep(_POLL_INTERVAL_SECONDS)
|
||||
|
||||
download_resp = requests_mod.get(
|
||||
f"{_BASE_URL}/files/{file_id}:download",
|
||||
params={"alt": "media"},
|
||||
headers=headers,
|
||||
timeout=300,
|
||||
)
|
||||
download_resp.raise_for_status()
|
||||
return download_resp.content
|
||||
|
||||
def execute(self, inputs: dict[str, Any]) -> ToolResult:
|
||||
api_key = self._get_api_key()
|
||||
if not api_key:
|
||||
return ToolResult(
|
||||
success=False,
|
||||
error="GEMINI_API_KEY / GOOGLE_API_KEY not set. " + self.install_instructions,
|
||||
)
|
||||
|
||||
import requests
|
||||
|
||||
start = time.time()
|
||||
operation = inputs.get("operation", "text_to_video")
|
||||
prompt = str(inputs["prompt"]).strip()
|
||||
aspect_ratio = inputs.get("aspect_ratio", "16:9")
|
||||
previous_interaction_id = inputs.get("previous_interaction_id")
|
||||
|
||||
if operation == "edit_video" and not previous_interaction_id and not inputs.get("input_video_path"):
|
||||
return ToolResult(
|
||||
success=False,
|
||||
error="edit_video requires previous_interaction_id (edit a generated clip) or input_video_path (edit an uploaded clip)",
|
||||
)
|
||||
|
||||
reference_paths = list(inputs.get("reference_image_paths") or [])
|
||||
if inputs.get("reference_image_path"):
|
||||
reference_paths.insert(0, inputs["reference_image_path"])
|
||||
if operation in {"image_to_video", "reference_to_video"} and not reference_paths:
|
||||
return ToolResult(
|
||||
success=False,
|
||||
error=f"{operation} requires reference_image_path or reference_image_paths",
|
||||
)
|
||||
|
||||
try:
|
||||
parts: list[dict[str, Any]] = [self._image_part(p) for p in reference_paths]
|
||||
if inputs.get("input_video_path"):
|
||||
video_uri = self._upload_video_file(requests, api_key, inputs["input_video_path"])
|
||||
parts.append({"type": "document", "uri": video_uri})
|
||||
except Exception as e:
|
||||
return ToolResult(success=False, error=f"Gemini Omni input preparation failed: {e}")
|
||||
|
||||
payload: dict[str, Any] = {
|
||||
"model": _DEFAULT_MODEL,
|
||||
# Plain string for text-only turns (the documented minimal form),
|
||||
# typed parts when images or an uploaded video ride along.
|
||||
"input": prompt if not parts else parts + [{"type": "text", "text": prompt}],
|
||||
# uri delivery avoids the ~4MB inline-payload ceiling; inline data in
|
||||
# the response is still handled below if the API returns it anyway.
|
||||
"response_format": {
|
||||
"type": "video",
|
||||
"aspect_ratio": aspect_ratio,
|
||||
"delivery": "uri",
|
||||
},
|
||||
}
|
||||
if previous_interaction_id:
|
||||
payload["previous_interaction_id"] = previous_interaction_id
|
||||
if inputs.get("store") is False:
|
||||
payload["store"] = False
|
||||
|
||||
try:
|
||||
resp = requests.post(
|
||||
f"{_BASE_URL}/interactions",
|
||||
headers={"x-goog-api-key": api_key, "Content-Type": "application/json"},
|
||||
json=payload,
|
||||
timeout=600,
|
||||
)
|
||||
if not resp.ok:
|
||||
detail = resp.text[:1000]
|
||||
return ToolResult(
|
||||
success=False,
|
||||
error=f"Gemini Omni interaction failed ({resp.status_code}): {detail}",
|
||||
)
|
||||
data = resp.json()
|
||||
|
||||
interaction_id = data.get("id")
|
||||
video = self._extract_output_video(data)
|
||||
if not video:
|
||||
return ToolResult(
|
||||
success=False,
|
||||
error=f"Gemini Omni response did not include an output video: {str(data)[:1000]}",
|
||||
)
|
||||
|
||||
if video.get("data"):
|
||||
video_bytes = base64.b64decode(video["data"])
|
||||
else:
|
||||
video_bytes = self._download_via_uri(requests, api_key, str(video["uri"]))
|
||||
|
||||
output_path = Path(inputs.get("output_path", "gemini_omni_output.mp4"))
|
||||
output_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
output_path.write_bytes(video_bytes)
|
||||
except Exception as e:
|
||||
return ToolResult(success=False, error=f"Gemini Omni video generation failed: {e}")
|
||||
|
||||
editable = inputs.get("store") is not False
|
||||
return ToolResult(
|
||||
success=True,
|
||||
data={
|
||||
"provider": self.provider,
|
||||
"model": _DEFAULT_MODEL,
|
||||
"prompt": prompt,
|
||||
"operation": operation,
|
||||
"output": str(output_path),
|
||||
"aspect_ratio": aspect_ratio,
|
||||
"has_audio": True,
|
||||
# Feed this back as previous_interaction_id to edit this clip.
|
||||
"interaction_id": interaction_id,
|
||||
"editable": editable,
|
||||
},
|
||||
artifacts=[str(output_path)],
|
||||
cost_usd=self.estimate_cost(inputs),
|
||||
duration_seconds=round(time.time() - start, 2),
|
||||
model=_DEFAULT_MODEL,
|
||||
)
|
||||
@@ -65,7 +65,7 @@ class SoraVideo(BaseTool):
|
||||
"4, 8, or 12 second social-video clips that OpenMontage can stitch and compose",
|
||||
]
|
||||
not_good_for = ["offline generation", "long continuous scenes", "projects without Sora API access"]
|
||||
fallback_tools = ["veo_video", "seedance_video", "kling_video", "minimax_video"]
|
||||
fallback_tools = ["veo_video", "gemini_omni_video", "seedance_video", "kling_video", "minimax_video"]
|
||||
|
||||
input_schema = {
|
||||
"type": "object",
|
||||
|
||||
@@ -62,7 +62,7 @@ class VeoVideo(BaseTool):
|
||||
"ambient sound and music generation built in",
|
||||
]
|
||||
not_good_for = ["budget projects", "offline generation", "quick iteration"]
|
||||
fallback_tools = ["kling_video", "minimax_video", "wan_video"]
|
||||
fallback_tools = ["gemini_omni_video", "kling_video", "minimax_video", "wan_video"]
|
||||
|
||||
input_schema = {
|
||||
"type": "object",
|
||||
|
||||
@@ -20,7 +20,7 @@ class VideoSelector(BaseTool):
|
||||
provider = "selector"
|
||||
stability = ToolStability.BETA
|
||||
runtime = ToolRuntime.HYBRID
|
||||
agent_skills = ["ai-video-gen", "create-video", "ltx2"]
|
||||
agent_skills = ["ai-video-gen", "create-video", "ltx2", "gemini-omni"]
|
||||
|
||||
# Operations that REQUIRE motion: an image-only tool (image_selector) is not
|
||||
# an acceptable last-resort fallback for these, so fallback_tools_for() drops it.
|
||||
|
||||
Reference in New Issue
Block a user