Skill detail
ai-podcast
Generates multi-person talking head podcast videos from scratch using AI, covering character creation, TTS, avatar animation, and video stitching.
Inspect before use
Read the source instructions and check the requirements before you install this skill.
SKILL.md
The saved excerpt is a snapshot from when this skill was listed. The external source remains the complete and most current version.
---
name: ai-podcast
description: "Generate multi-person talking head podcast videos from scratch using AI — character creation, TTS, avatar animation, and video stitching. Use when the user wants to create a podcast, talking head video, or multi-speaker conversation video."
allowed-tools: Bash, Read, Write, Agent, Glob, Grep
---
## AI Podcast Generator
Create multi-person talking head podcast videos using the inference.sh pipeline: portrait generation → TTS audio → avatar video → merge. Supports real humans (via Phota), 3D mascots, illustrated characters, and mixed casts.
Use when the user wants to create a podcast, talking head video, demo reel, promotional conversation, or any multi-speaker video content.
### Pipeline Overview
```
Characters (images) → TTS (audio per turn) → Avatar (video per turn) → Merge (final video)
```
### Process
#### Step 1: Character Creation
Choose the right tool per character type:
| Character Type | Tool | Notes |
|---------------|------|-------|
| **Real human (new)** | `pruna/p-image` | 16:9, `prompt_upsampling: true`. Quick, no training needed, but identity won't be consistent across multiple generations. |
| **Real human (consistent ID)** | `phota/generate` with `[[profile_id]]` | Consistent identity across all shots. Requires a trained Phota profile first (see below). |
| **Brand mascot / logo character** | `google/gemini-3-pro-image-preview` | Pass logo + character sheet as reference images |
| **Illustrated / stylized** | `google/gemini-3-pro-image-preview` | Pass style reference as input image |
**Training a Phota identity (optional but recommended for humans):**
If you need a real human character with consistent identity across multiple angles and shots, train a Phota profile first:
```bash
infsh app run phota/train --input '{
"images": ["url1.jpg", "url2.jpg", ...],
"wait": true
}' --save profile.json
```
- Requires 30-50 face images of the subject
- Training takes a few minutes with `wait: true`
- Returns a `profile_id` you then use in `phota/generate` as `[[profile_id]]` in prompts
- The profile is reusable forever — train once, generate unlimited shots
If you don't need cross-shot consistency (e.g. single-speaker video, one angle only), `pruna/p-image` is simpler and cheaper.
**Character sheets first, podcast frames second:**
1. Generate a character sheet (plain white background, multiple angles) for each character
2. Then place characters into the podcast studio setting using the sheet as reference
**For branded characters (logo on clothing):**
1. Generate the character with a plain version of the garment
2. Use `phota/edit` with the logo as a second reference image to add the logo
3. Always pass the logo image alongside character references when generating new angles
#### Step 2: Alternate Angles
Generate at least 2 angles per character for visual variety:
| Angle | When to use |
|-------|-------------|
| **Front/medium** | Establishing shots, opening, closing |
| **Close-up** | Reactions, emotional moments, punchy lines |
For close-ups, prompt for "tight framing, chest up, shallow depth of field" — not "turned to the side" (which just makes them look away).
**Identity consistency rules:**
- For real humans with a Phota profile: use `phota/generate` or `phota/edit` for new angles — Gemini does not preserve facial identity and will produce a different person
- For real humans without a Phota profile: try to generate all needed angles in one go with `pruna/p-image`, or consider training a Phota profile if you need many shots
- For mascots/illustrations: Gemini 3 Pro is fine, pass the established frame as reference
**Framing rule:** Use tight framing on individual speakers. Wide shots with multiple seats show empty chairs when only one person is on screen.
#### Step 3: QA Frames
Before proceeding, visually inspect all frames for:
- Extra people in the background
- Multiple microphones (should be single mic per shot)
- Wrong or distorted logos
- InconsistentRead the full source on GitHub (opens external page)