Wine Collection Search
962 bottles catalogued
The Story
@prades_maxime had a large wine collection but no easy way to search and query it. He had CSV data with all the bottle information, but wanted a conversational interface to explore his cellar. The solution was elegant: import the CSV into Moltbot's knowledge base, enabling natural language queries like 'What should I pair with lamb tonight?' or 'Show me all my Burgundies from 2015.' Now his entire 962-bottle collection is accessible through chat.
"'What should I open with lamb tonight?' gets a proper answer. It's like having a sommelier in my pocket."
β @prades_maxime
π§ How It Works
CSV data is imported into Moltbot's persistent memory, with custom formatting for wine-related queries.
1. Data Preparation
Exported wine inventory to CSV with columns: name, vintage, region, varietal, price, rating, tasting notes.
Added metadata like drinkability window, food pairings, and storage location for richer queries.
2. Knowledge Base Import
Imported CSV into Moltbot's memory system using specialized wine knowledge formatting.
Moltbot indexed the data for fast retrieval and learned wine-specific terminology and concepts.
3. Natural Language Queries
Can now ask questions in plain English and get intelligent recommendations.
Supports complex queries: 'Best wines under $50 for a steak dinner' or 'What should I drink now from my collection?'
Tech Stack Used
π Results
π οΈ Moltbot Skills Used
Data Import
CSV to knowledge base
Natural Language
Conversational queries
Domain Knowledge
Wine-specific intelligence
Recommendations
Smart pairing suggestions
π‘ Tips for Implementation
Include as much metadata as possible in your CSV
Add personal tasting notes for better recommendations
Track which bottles you've enjoyed most
Update the database as you drink or acquire new wines
Consider adding photos of labels
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