fal-ai-media

I can't generate images directly in this environment, but here's a ready-to-use prompt you can paste into an image generator (Midjourney, DALL·E, Stable Diffusion, etc.):

**Prompt:**

> Cozy watercolor illustration of a reading nook beside a large window on a rainy day, soft raindrops streaking the glass, muted gray-blue light outside. A tabby cat curled asleep on a tall stack of well-worn books beside a cushioned armchair. Warm golden lamp light glowing from a small table lamp, a steaming ceramic mug of tea on the windowsill with gentle wisps of steam. Loose, soft watercolor washes, gentle color bleeds, textured paper grain, warm amber and terracotta tones contrasting with cool rainy blues. Peaceful, hygge atmosphere. --ar 4:5

**Tips:**
- For Midjourney, keep `--ar 4:5` at the end.
- For DALL·E, ask for "4:5 portrait aspect ratio" in the prompt text.
- Add `--style raw` or "flat illustration" if you want less painterly drift, or "wet-on-wet watercolor" for softer edges.

Want me to write a few variations (e.g., nighttime version, or with a bookshelf backdrop)?

I loaded the fal-ai-media skill, but the fal.ai MCP tools (`generate`, etc.) aren't actually available in this session — I only have the skill loader, so I can't execute the generation directly. Here's everything ready to run the moment the MCP is connected:

**Model:** `fal-ai/nano-banana-pro` (high-fidelity, great for painterly detail)

**Call:**
```
generate(
  model_name: "fal-ai/nano-banana-pro",
  input: {
    "prompt": "Cozy watercolor illustration of a reading nook beside a large window on a rainy day, raindrops streaking the glass with soft blurred grey-blue city outside. A tabby cat curled asleep on a tall stack of vintage books, warm golden lamplight from a small brass lamp casting a soft glow, a steaming ceramic mug on the windowsill with wisps of steam. Loose watercolor washes, soft edges, warm amber and honey tones contrasting cool rainy blues, gentle paper texture, storybook illustration style.",
    "image_size": "portrait_4_5",
    "num_images": 1,
    "guidance_scale": 7.5
  }
)
```

**Notes:**
- If `portrait_4_5` isn't accepted by the model, use `portrait_4_3` and crop to 4:5, or pass explicit width/height (e.g., 1024×1280) if the model supports it.
- Add a fixed `seed` if you want to iterate on variations reproducibly.
- For a cheaper draft pass first, swap to `fal-ai/nano-banana-2` with the same prompt.

Want me to adjust the prompt (e.g., different palette, more rain, plant details)?

Here's your voiceover script:

---

*"Hey there, sleepyhead... ☀️ Good news — your coffee just got smarter, and your day? It's about to get so much better. Go on... one sip. You'll feel it."*

---

**Delivery notes:** Soft, playful opening — like greeting an old friend. Slight smile in the voice on "sleepyhead." Warm and inviting on "one sip," with a gentle, knowing pause before "you'll feel it." Total read: ~12–13 seconds at a relaxed pace.

Here's your warm, friendly voiceover script — timed at roughly 12–13 seconds at a natural, relaxed pace:

---

**"Morning, sleepyhead. ☀️**
**Your coffee just got smarter... and your day? About to get so much better.**
**One sip. You'll feel it."**

---

**Delivery notes:**
- *Tone:* Warm, playful, like a friend greeting you at the café door — soft smile in the voice.
- *Pacing:* Gentle pause after "sleepyhead," slight lift on "so much better," and a cozy, confident close on "You'll feel it."
- *Music cue:* Soft acoustic or lo-fi warmth underneath, swelling slightly on the last line.

Want me to generate an actual audio version of this with a warm voice using AI text-to-speech? I can do that — just say the word.

I can't generate video — I don't have any video creation or image generation tools available in this environment, so I'm unable to produce a 6-second animated clip from your photo.

What I *can* do:

1. **Write a detailed generation prompt** you can paste into a video AI tool (Runway Gen-3, Kling, Pika, Luma Dream Machine, Sora, etc.):

> *"Aerial drone shot of a winding river cutting through dense autumn forest at golden hour, soft mist hovering over the water. Camera slowly rises and tilts down, revealing more of the river's curve. Golden and crimson leaves drift gently on the wind across the frame. Warm low sunlight, cinematic, photorealistic, smooth slow motion. 6 seconds."*

2. **Suggest a DIY approach**: use a parallax/2.5D animation tool (e.g., After Effects with camera projection, or Photoshop + editing software) to simulate the rising camera from your still, then overlay drifting leaf particles.

3. **Refine the prompt** for a specific tool if you tell me which one you're using — different generators respond better to different phrasing.

Want me to tailor the prompt for a particular platform?

I don't have the fal.ai MCP tools available in this session (only the skill instructions loaded — no `generate`/`upload` tools are connected), so I can't run the generation directly. Here's exactly how to do it once the MCP server is configured:

**1. Upload your photo**
```
upload(file_path: "/path/to/your/river_photo.jpg")
```

**2. Generate the 6-second image-to-video with Seedance 1.0 Pro**
```
generate(
  model_name: "fal-ai/seedance-1-0-pro",
  input: {
    "image_url": "<uploaded_image_url>",
    "prompt": "aerial drone shot, camera slowly rises upward over a winding river through autumn forest at golden hour, mist drifting over the water, golden and orange leaves gently drifting in the wind, soft cinematic motion, photorealistic",
    "duration": "6s",
    "aspect_ratio": "16:9"
  }
)
```

**3. Poll for the result**
```
status(job_id: "<job_id>")   # or result(job_id: "<job_id>")
```

Notes:
- Image-to-video (rather than pure text-to-video) will preserve your actual composition, lighting, and mist — much better for this use case.
- Seedance supports 6s durations; if it rejects "6s", use "5s" or "10s".
- Keep the prompt focused on motion (rising camera, drifting leaves) since the scene content comes from your photo.
- If you want ambient sound added afterward, run the output through `fal-ai/thinksound` with a prompt like "gentle river flowing, wind through autumn leaves, birdsong".

To enable this in your environment, add the fal-ai MCP server to `~/.claude.json` with your `FAL_KEY`, then re-run the request and I can execute it for you.

I can't generate audio in this environment — I don't have any audio synthesis or generation tools available, and no skills are enabled. So I can't produce the actual thunder/rain/birdsong file for you.

What I can do is give you a production-ready plan you (or a sound designer/AI audio tool) can execute:

**Timeline (30s total)**

| Time | Scene | Audio |
|---|---|---|
| 0:00–0:12 | Storm peak | Heavy rain on tin roof (bright metallic patter, ~60–70 dB), deep thunder rumbles with 1–2 close strikes (sub-bass 30–60 Hz rolls, 4–6s tails) |
| 0:12–0:20 | Transition | Rain intensity drops ~50%, thunder moves to distant low rumbles, tin patter softens to a drip |
| 0:20–0:30 | Calm | Rain fades to near-silence by 0:22, distant birdsong enters (sparrows/robin chirps, sparse at first, fuller by 0:25) |

**Sync tips**
- Cut thunder *just before* lightning flashes on screen (sound slightly delayed, 0.5–1s, for realism — or instant if stylized).
- Ease the rain with a 2–3s crossfade, not a hard cut.
- Let birds enter 1–2s after the rain dies down so the "clearing" reads emotionally.
- Keep a faint wet-roof drip bed under the birds to bridge the transition.

If you want actual generated audio, tools like ElevenLabs Sound Effects, Stable Audio, or Adobe Firefly audio can take prompts like: *"heavy rain on tin roof with deep thunder rumble, transitioning to distant birdsong, 30 seconds."*

Since you have an actual video clip, the best fit here is **ThinkSound** (fal-ai/thinksound) — it generates audio directly from video content, so the sound design follows the scene changes automatically rather than needing manual timeline syncing.

Here's the call to run via the fal.ai MCP:

```
generate(
  model_name: "fal-ai/thinksound",
  input: {
    "video_url": "<your uploaded clip URL>",
    "prompt": "Deep rumbling thunder rolling overhead with heavy rain drumming loudly on a corrugated tin roof, metallic pattering and dripping. Midway, the storm gradually subsides: rain softens to a gentle drizzle, thunder fades into distant low rumbles, and the clip ends with soft, sparse birdsong in a calm, wet atmosphere."
  }
)
```

**Workflow:**

1. **Upload your clip** first: `upload(file_path: "/path/to/clip.mp4")` → use the returned URL as `video_url`.
2. **Run the generate call** above.
3. **Poll with `result`** until the job completes, then download the audio track.

**Tips for best sync:**

- ThinkSound conditions on the video's visual timeline, so the storm→calm transition in your footage will drive the audio transition — keep the prompt's phrasing ordered the same way as your scenes (thunder/rain first, easing, then birds).
- If the first pass has the birds too early or the rain too quiet, regenerate with a more explicit prompt, e.g. "birds only appear in the final third of the clip" or "rain is very loud and close for the first half."
- Run it a couple of times and pick the best take — video-to-audio models vary between runs.

If you'd rather not use the video at all, an alternative is generating the audio purely from text (e.g., VideoDB's `generate_sound_effect` with a layered prompt), but you'd lose the automatic scene-syncing — ThinkSound with your actual clip is the stronger option here.

I'm not able to generate images directly — I don't have an image-generation tool available in this environment. But I can give you a polished prompt you can paste into an image generator (Midjourney, DALL·E, Stable Diffusion, etc.):

**Prompt:**

> A small white lighthouse with a red roof perched on a rocky cliff at dusk, its warm beam of light sweeping in a soft arc across a calm, glassy sea. Storybook watercolor illustration style, painterly brushstrokes, soft wet-on-wet washes, gentle granulation in the sky. Dusky palette of lavender, rose, and deep indigo with golden highlights from the lighthouse beam and a few glowing windows. Faint reflections of the light shimmering on gentle waves. Cozy, whimsical, hand-painted children's book feel with soft edges and delicate paper texture. Square composition, 1:1 aspect ratio.

**Tips:**
- For Midjourney, append `--ar 1:1 --style raw` (or use `--niji` for a softer storybook look).
- For DALL·E / GPT image tools, the prompt works as-is; mention "square" in the request.
- If the beam looks too harsh, add "diffuse, glowing, atmospheric light beam" to soften it.

Want me to write a few variations (e.g., stormier mood, closer crop, or a night version)?

I don't have a live fal.ai MCP connection available in this environment (only the skill loader is exposed, so I can't invoke the `generate` tool directly). Here's the exact call to run it yourself, or paste into any image generator:

**Model:** `fal-ai/nano-banana-pro` (high fidelity, good for painterly styles)

```json
{
  "model_name": "fal-ai/nano-banana-pro",
  "input": {
    "prompt": "A warm, painterly storybook watercolor illustration of a small white lighthouse perched on a rocky cliff at dusk. A soft golden beam of light sweeps across a calm, glassy sea reflecting peach, lavender, and amber twilight hues. Gentle washes and visible watercolor paper texture, soft edges, cozy children's-book illustration style, dreamy and serene.",
    "image_size": "square",
    "num_images": 1,
    "guidance_scale": 7.5
  }
}
```

Tips:
- Use `fal-ai/nano-banana-2` instead if you want a cheaper draft first, then re-run with the same `seed` on Pro for the final.
- Add a fixed `seed` (e.g., 42) if you want to iterate on the composition reproducibly.

If you can enable the fal-ai MCP server (`npx -y fal-ai-mcp-server` with your `FAL_KEY`), I can run this generation for you directly.