| --- |
| title: Podify - AI Podcast Generator |
| emoji: 🎙️ |
| colorFrom: indigo |
| colorTo: purple |
| sdk: gradio |
| sdk_version: 5.27.0 |
| app_file: app.py |
| python_version: "3.10" |
| hardware: zero-a10g |
| suggested_hardware: zero-a10g |
| pinned: false |
| short_description: Research a topic and turn it into a voiced podcast |
| tags: |
| - build-small-hackathon |
| - backyard ai |
| - off the grid |
| - off-brand |
| - field notes |
| --- |
| |
|  |
|
|
| # 🎙️ Podify — AI Podcast Generator |
|
|
| Turn any topic into a finished, voiced podcast in two phases: |
|
|
| 1. **Content** — research agents (LangGraph) use a HuggingFace-hosted LLM plus live |
| DuckDuckGo web search to research the topic and write a speaker-tagged script. |
| 2. **Audio** — the self-hosted **Fish Audio / OpenAudio S1-mini** model speaks the |
| script, with selectable preset voices and zero-shot **voice cloning** from an |
| uploaded clip or a live mic recording. |
|
|
| Everything runs inside this single Gradio Space; the TTS model runs on **ZeroGPU**. |
|
|
| ## Architecture |
|
|
| ``` |
| Topic ─▶ LangGraph: plan ─▶ DDG search ─▶ outline ─▶ write ─▶ Script |
| Script ─▶ Fish Audio S1-mini (@spaces.GPU): per-line synth ─▶ stitched podcast WAV |
| ``` |
|
|
| - `app.py` — Gradio Blocks UI (two tabs) wiring both phases. |
| - `research/` — `llm.py` (HF Inference client), `search.py` (DuckDuckGo), `graph.py` |
| (LangGraph research graph). |
| - `tts/` — `engine.py` (model load + GPU synthesis + multi-speaker stitching), |
| `voices.py` (preset voice registry). |
|
|
| ## Configuration |
|
|
| Set these as **Space secrets / variables** (Settings → Variables and secrets): |
|
|
| | Name | Required | Purpose | |
| |-------------|----------|----------------------------------------------------------------| |
| | `HF_TOKEN` | ✅ | LLM inference (Inference Providers) + model download. | |
| | `LLM_MODEL` | optional | Override the content LLM (default `Qwen/Qwen2.5-14B-Instruct`, <32B). | |
| | `TTS_MODEL_REPO` | optional | Override the TTS model repo (default `fishaudio/openaudio-s1-mini`). | |
|
|
| **ZeroGPU** requires a HuggingFace **PRO** account on the Space owner. |
|
|
| ## Run locally |
|
|
| ```bash |
| pip install -r requirements.txt |
| export HF_TOKEN=hf_xxx # PowerShell: $env:HF_TOKEN="hf_xxx" |
| python app.py |
| ``` |
|
|
| Phase 1 (research + script) runs on CPU. Phase 2 (TTS) needs a GPU and the |
| `fish-speech` package; on CPU-only machines the UI loads but synthesis is disabled. |
|
|
| ## Deploy to a Space |
|
|
| ```bash |
| huggingface-cli login |
| huggingface-cli upload <user>/podify . --repo-type=space |
| # or: git push to the Space remote (preset .wav files tracked via Git LFS) |
| ``` |
|
|
| ## Credits / assets |
|
|
| - **Voice samples** (`tts/voices/`): derived from [CMU ARCTIC](http://festvox.org/cmu_arctic/) |
| (free for research and commercial use). Rebuild with `scripts/build_voice_samples.py`. |
| - **Background-music loops** (`tts/music_loops/`): [FreePD](https://freepd.com/) by Kevin |
| MacLeod — 100% public domain (CC0). Rebuild with `scripts/build_music_loops.py`. |
| A procedural numpy fallback in `tts/music.py` is used if the loops are absent. |
|
|
| #backyard-ai |
| Blog: |
| Social Media Post: |
| Demo: |
