56 lines
2.5 KiB
Markdown
56 lines
2.5 KiB
Markdown
# Seasoned
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[](https://jenkins.wrigglyt.xyz/job/Seasoned/)
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In progress link: https://seasoned.ddns.net/
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The Pitch:
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Seasoned is a high-performance, private digital cookbook that bridges the gap between web discovery and kitchen execution. By combining the multimodal power of Gemini 3.1 Flash Lite with a secure, self-hosted PostgreSQL backbone, Seasoned allows users to instantly "distill" messy recipe blogs and food photos into a standardized, searchable, and shareable library they truly own.
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Target Audience:
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The Modern Minimalist: Cooks who want an ad-free, recipe experience.
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The Legacy Keeper: Families digitizing handwritten recipes into a clean digital format.
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The Privacy Enthusiast: Users who want the power of AI without storing their personal data in a massive cloud.
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The Hybrid Tech Stack:
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| Components | Technology |
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| :--- | :--- |
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| **Hosting** | Private Server (Dockerized on home hardware) |
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| **CI/CD** | Jenkins server |
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| **Frontend** | Nuxt 4 + Vuetify + CSS |
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| **Backend** | Dotnet |
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| **Database** | Postgres + pgvector |
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| **Intelligence** | Gemini 3.1 Flash Lite |
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| **Storage** | Local File System |
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Technical Requirements:
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1. AI & Multimodal Intelligence
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Multimodal Extraction: Uses Gemini 3.1 Flash Lite to accept image/jpeg inputs and return a strictly validated JSON Schema containing title, ingredients, and steps.
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Semantic Search: Implement pgvector in the local database. Recipes will be converted into "embeddings" (via Gemini) to allow users to search for "Comfort food for a rainy day" instead of just keyword matches.
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2. Full-Stack Architecture (Nuxt 4)
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Directory Structure: Adherence to the new app/ directory standard for better IDE performance and separation of concerns.
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Responsive Design: A UI that adapts perfectly to a tablet propped up on a kitchen counter.
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3. Data & Storage
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Relational Schema: A PostgreSQL database to manage Users, Recipes, Tags, and Shares.
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Private Media Pipeline: A custom upload handler that saves images to a local Docker volume, served via a secured static asset route.
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Use Cases:
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Photo-to-Recipe: User snaps a picture of a magazine page; Gemini extracts the text; the user saves it to their Postgres DB.
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Semantic Discovery: User searches for "High protein dinner with lime" and the app uses vector similarity to find the best match.
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Ad-Free Web Scraping: User pastes a blog URL; the server fetches the content, and Gemini strips out the ads and life stories. |