docs: add comprehensive project docs (architecture, progress, configuration, troubleshooting)
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* **Key Takeaways (Bullet list)**
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* **Actionable Verdict**
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3. **Read/Skip State**: Mark videos as **Read** or **Skip** to clear them from your pending queue, allowing you to only keep track of what's unread.
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4. **View Full Transcript**: Expand the accordion at the bottom of the digest to read the raw transcripts if needed.
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4. **View Full Transcript**: Expand the accordion at the bottom of the digest to read the raw transcripts if needed.
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5. **Agent Queue**: Save videos with notes to a queue for Hermes agents to process (create skills, open issues, etc.)
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---
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## 📚 Documentation
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Comprehensive documentation for this project is available in the `docs/` folder:
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- **[Architecture](docs/architecture.md)** - System overview, components, API endpoints, database schema
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- **[Progress](docs/progress.md)** - Session history, completed tasks, planned features, metrics
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- **[Configuration](docs/configuration.md)** - Environment variables, API tokens, database, Authelia, Caddy setup
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- **[Troubleshooting](docs/troubleshooting.md)** - Common issues, recovery procedures, monitoring
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---
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## 🚀 Setup Instructions
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### 1. Extract your YouTube browser cookies
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Since YouTube restricts subscription feeds to logged-in users, you need to export your logged-in cookies so `yt-dlp` can request the feed on your behalf:
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1. Install a browser extension like **Get cookies.txt LOCALLY** (Chrome/Edge) or **cookies.txt** (Firefox).
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2. Open YouTube in your browser and ensure you are logged in to your account.
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3. Click the extension icon and export the cookies for `youtube.com` as a Netscape-formatted text file.
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4. Create a folder named `config` in your project root, rename the exported file to `cookies.txt`, and save it inside:
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```text
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t-youtube/config/cookies.txt
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```
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### 2. Configure Environment Variables
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Create a `.env` file in the root directory:
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```env
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# Optional: Override the fallback OpenAI / Anthropic key
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OPENAI_API_KEY=sk-Kq5...rOlx
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```
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### 3. Build & Deploy using Docker Compose
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Run the following command to build the multi-stage image (compiles frontend static assets using Node, then packages backend with Python) and start the container:
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```bash
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docker compose up -d --build
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```
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The server will boot up and listen on port `8000`.
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