Find community members with relevant expertise using vector search
This skill enables Claude to find and recommend MLAI community members based on their expertise, interests, and what they're working on.
Parse the user's query to identify the specific expertise areas they're looking for.
Common patterns to recognize:
Use the vector_search function to find users with matching expertise.
The search uses cosine similarity on embeddings stored in the user_expertise table.
SELECT u.id, u.name, u.slack_id, e.topic, e.relationship,
1 - (e.embedding <=> $query_embedding) as similarity
FROM users u
JOIN user_expertise e ON u.id = e.user_id
WHERE 1 - (e.embedding <=> $query_embedding) > 0.7
ORDER BY similarity DESC
LIMIT 5;
Generate a warm, friendly response suggesting the matched users.
Include for each user:
G'day! Looking for folks in AI research, eh? Here are some legends who might help:
• **@sam** - Expert in machine learning and neural networks
• **@jane** - Currently working on computer vision projects
• **@bob** - Interested in deep learning applications
Feel free to reach out to them! 🦘
Hmm, I couldn't find anyone specifically matching "quantum computing" in our community yet.
A few things we could try:
• Broaden the search - maybe "physics" or "advanced computing"?
• Post in #introductions asking if anyone's into this space
• Check out our upcoming events - might meet someone there!
Want me to try a different search? 🤔
If the database search fails: