Skip to main content

​
Quick Start Guide

You’ll need a Nebula API key before starting. Get one at trynebula.ai
Get up and running with Nebula in minutes.

​
Prerequisites

  • Python 3.8+ or Node.js 16+
  • A Nebula account at trynebula.ai

​
1. Install

# Python
pip install nebula-client

# Node.js
npm install @nebula-ai/sdk

# Go
go get github.com/nebula-ai/nebula-client-go

​
2. Initialize Client

from nebula import Nebula

# With API key
nebula = Nebula(api_key="your-api-key-here")

# Or set NEBULA_API_KEY environment variable
# nebula = Nebula()

from nebula import Nebula

nebula = Nebula(api_key="your-api-key-here")

# Create a collection
collection = nebula.create_collection(name="my_notes", description="Personal notes")

# Store a memory
memory_id = nebula.store_memory({
    "collection_id": collection.id,
    "content": "Machine learning is transforming healthcare",
    "metadata": {"topic": "AI", "importance": "high"}
})

# Search memories
results = nebula.search(
    query="machine learning healthcare",
    collection_ids=[collection.id],
    limit=5
)

for result in results:
    print(f"Score: {result.score:.2f}")
    print(f"Content: {result.content}")

​
What You’ll Get Back

When you store a memory, Nebula returns the memory ID: 
# Returns the memory ID
memory_id = "eng_abc123def456"
When you search, you get a list of relevant results with scores: 
# Search results structure
[
  {
    "memory_id": "eng_abc123def456",
    "content": "Machine learning is transforming healthcare",
    "score": 0.95,
    "metadata": {"topic": "AI", "importance": "high"},
    "created_at": "2024-01-15T10:30:00Z"
  },
  {
    "memory_id": "eng_xyz789ghi012",
    "content": "AI models improve diagnostic accuracy",
    "score": 0.87,
    "metadata": {"topic": "AI", "importance": "high"},
    "created_at": "2024-01-14T09:15:00Z"
  }
]
Scores range from 0-1, with higher scores indicating better semantic matches to your query.

​
Next Steps

​
Need Help?