spiceai/cookbook/client-sdk/spice.js-sdk-sample/README.md

Spice.js SDK Sample

Works with v1.0+

Use @spiceai/spice (opens in a new tab) from Node.js to query taxi_trips.

What This Sample Includes

index.js: Main sample with multiple analytics queries.
index_cloud.mjs: Minimal cloud-only query (show tables;).

Prerequisites

Node.js 20+
npm
Spice CLI (opens in a new tab) for local mode

Quick Start

git clone https://github.com/spiceai/cookbook.git
cd cookbook/client-sdk/spice.js-sdk-sample
npm install

git clone https://github.com/spiceai/cookbook.git
cd cookbook/client-sdk/spice.js-sdk-sample
npm install

Run with Local Spice Runtime

Start Spice runtime in one terminal:

spice run

spice run

Run the Node sample in another terminal:

npm start

npm start

index.js runs against your local runtime by default.

Run with Spice.ai Cloud

Set your API key for the commands in this README:

export SPICE_API_KEY="your_api_key"

export SPICE_API_KEY="your_api_key"

index.js reads SPICE_API_KEY (from the environment or a .env file) and connects to Spice.ai Cloud instead of the local runtime when it is set - no code edit needed:

npm start

npm start

index_cloud.mjs is a minimal cloud-only snippet and keeps an inline API key placeholder by design. It does not read the environment, so replace its API_KEY placeholder with the key itself rather than with ${SPICE_API_KEY}, then run:

node index_cloud.mjs

node index_cloud.mjs

Example Output

The application prints output similar to:

Spice.js initialized
  Platform: Node.js v24.9.0 darwin arm64
  Transport: Arrow Flight -> HTTP
  Endpoint: http://127.0.0.1:8090
  Flight URL: 127.0.0.1:50051
NYC Taxi Trips Data Analysis

Connected to: Local Spice Runtime
Tip: Set SPICE_API_KEY in .env to use Spice.ai Cloud

Querying taxi_trips dataset...

============================================================

Query 1: Top 10 Most Expensive Taxi Trips

Using .sql() - Apache Arrow Flight (gRPC) for high performance

Found 10 trips:

1. $5000.00 - 0 miles - 0 passenger(s)
2. $5000.00 - 0 miles - 0 passenger(s)
3. $2500.00 - 0 miles - 0 passenger(s)
4. $2500.00 - 0 miles - 0 passenger(s)
5. $2500.00 - 0 miles - 0 passenger(s)
6. $2225.30 - 31.95 miles - 1 passenger(s)
7. $1617.50 - 233.25 miles - 1 passenger(s)
8. $1000.00 - 0 miles - 0 passenger(s)
9. $940.93 - 142.62 miles - 1 passenger(s)
10. $900.00 - 157.25 miles - 1 passenger(s)

Execution time: 27.59ms

============================================================

Query 2: Trip Statistics Summary

Statistics from sample:
  - Total trips analyzed: 2964624
  - Average fare: $26.8
  - Average distance: 3.65 miles
  - Average tip: $3.34
  - Highest fare: $5000
  - Lowest fare: $-900

Execution time: 9.25ms

============================================================

Query 3: Top 10 Popular Pickup Locations

Most popular pickup locations:

1. Location ID 132:
  145240 trips | Avg fare: $76.58 | Avg distance: 15.49 miles
2. Location ID 161:
  143471 trips | Avg fare: $23.48 | Avg distance: 2.56 miles
3. Location ID 237:
  142708 trips | Avg fare: $19.45 | Avg distance: 1.7 miles
4. Location ID 236:
  136465 trips | Avg fare: $20 | Avg distance: 1.85 miles
5. Location ID 162:
  106717 trips | Avg fare: $22.88 | Avg distance: 2.23 miles
6. Location ID 230:
  106324 trips | Avg fare: $26.27 | Avg distance: 2.91 miles
7. Location ID 186:
  104523 trips | Avg fare: $23.64 | Avg distance: 2.27 miles
8. Location ID 142:
  104080 trips | Avg fare: $21 | Avg distance: 2.09 miles
9. Location ID 138:
  89533 trips | Avg fare: $65.01 | Avg distance: 9.59 miles
10. Location ID 239:
  88474 trips | Avg fare: $20.93 | Avg distance: 2.26 miles

Execution time: 9.00ms

============================================================

Query 4: Payment Type Distribution

Using .sqlJson() - HTTP transport for simpler integration

Payment type breakdown:

1. Credit card (Type 1):
  2,319,046 trips | Avg amount: $28.26 | Avg tip: $4.17
2. Cash (Type 2):
  439,191 trips | Avg amount: $22.88 | Avg tip: $0
3. Dispute (Type 4):
  46,628 trips | Avg amount: $1.77 | Avg tip: $0.04
4. No charge (Type 3):
  19,597 trips | Avg amount: $8.76 | Avg tip: $0.01

Execution time: 17.14ms

============================================================

Query 5: Parametrized Query - Trips by Distance Range

Using .sql() with parameters for safe, dynamic queries

Trips with distance between 5 and 10 miles:

1. 5.99 miles - $313.74 total - $99.99 tip - 4 passenger(s)
2. 5.84 miles - $311.00 total - $15.00 tip - 1 passenger(s)
3. 7.47 miles - $307.75 total - $15.00 tip - 2 passenger(s)
4. 7.93 miles - $297.75 total - $0.00 tip - 1 passenger(s)
5. 7.18 miles - $282.75 total - $5.00 tip - 1 passenger(s)

Execution time: 8.91ms

Parameters used: $1=5, $2=10, $3=5

============================================================

Method Comparison:

.sql() - Uses Apache Arrow Flight (gRPC)
  - Higher performance and efficiency
  - Better for large datasets and high-throughput applications
  - Returns Arrow Tables (columnar format)
  - Supports parametrized queries ($1, $2, ... placeholders)
  - Works in true Node.js runtimes (local Node.js, Lambda)

.sqlJson() - Uses HTTP
  - Simpler integration, works everywhere HTTP does
  - Better for smaller queries and web applications
  - Returns plain JavaScript objects (easier to work with)
  - Works in browsers, Vercel, Netlify, and sandbox environments

============================================================

Analysis complete!

Spice.js initialized
  Platform: Node.js v24.9.0 darwin arm64
  Transport: Arrow Flight -> HTTP
  Endpoint: http://127.0.0.1:8090
  Flight URL: 127.0.0.1:50051
NYC Taxi Trips Data Analysis

Connected to: Local Spice Runtime
Tip: Set SPICE_API_KEY in .env to use Spice.ai Cloud

Querying taxi_trips dataset...

============================================================

Query 1: Top 10 Most Expensive Taxi Trips

Using .sql() - Apache Arrow Flight (gRPC) for high performance

Found 10 trips:

1. $5000.00 - 0 miles - 0 passenger(s)
2. $5000.00 - 0 miles - 0 passenger(s)
3. $2500.00 - 0 miles - 0 passenger(s)
4. $2500.00 - 0 miles - 0 passenger(s)
5. $2500.00 - 0 miles - 0 passenger(s)
6. $2225.30 - 31.95 miles - 1 passenger(s)
7. $1617.50 - 233.25 miles - 1 passenger(s)
8. $1000.00 - 0 miles - 0 passenger(s)
9. $940.93 - 142.62 miles - 1 passenger(s)
10. $900.00 - 157.25 miles - 1 passenger(s)

Execution time: 27.59ms

============================================================

Query 2: Trip Statistics Summary

Statistics from sample:
  - Total trips analyzed: 2964624
  - Average fare: $26.8
  - Average distance: 3.65 miles
  - Average tip: $3.34
  - Highest fare: $5000
  - Lowest fare: $-900

Execution time: 9.25ms

============================================================

Query 3: Top 10 Popular Pickup Locations

Most popular pickup locations:

1. Location ID 132:
  145240 trips | Avg fare: $76.58 | Avg distance: 15.49 miles
2. Location ID 161:
  143471 trips | Avg fare: $23.48 | Avg distance: 2.56 miles
3. Location ID 237:
  142708 trips | Avg fare: $19.45 | Avg distance: 1.7 miles
4. Location ID 236:
  136465 trips | Avg fare: $20 | Avg distance: 1.85 miles
5. Location ID 162:
  106717 trips | Avg fare: $22.88 | Avg distance: 2.23 miles
6. Location ID 230:
  106324 trips | Avg fare: $26.27 | Avg distance: 2.91 miles
7. Location ID 186:
  104523 trips | Avg fare: $23.64 | Avg distance: 2.27 miles
8. Location ID 142:
  104080 trips | Avg fare: $21 | Avg distance: 2.09 miles
9. Location ID 138:
  89533 trips | Avg fare: $65.01 | Avg distance: 9.59 miles
10. Location ID 239:
  88474 trips | Avg fare: $20.93 | Avg distance: 2.26 miles

Execution time: 9.00ms

============================================================

Query 4: Payment Type Distribution

Using .sqlJson() - HTTP transport for simpler integration

Payment type breakdown:

1. Credit card (Type 1):
  2,319,046 trips | Avg amount: $28.26 | Avg tip: $4.17
2. Cash (Type 2):
  439,191 trips | Avg amount: $22.88 | Avg tip: $0
3. Dispute (Type 4):
  46,628 trips | Avg amount: $1.77 | Avg tip: $0.04
4. No charge (Type 3):
  19,597 trips | Avg amount: $8.76 | Avg tip: $0.01

Execution time: 17.14ms

============================================================

Query 5: Parametrized Query - Trips by Distance Range

Using .sql() with parameters for safe, dynamic queries

Trips with distance between 5 and 10 miles:

1. 5.99 miles - $313.74 total - $99.99 tip - 4 passenger(s)
2. 5.84 miles - $311.00 total - $15.00 tip - 1 passenger(s)
3. 7.47 miles - $307.75 total - $15.00 tip - 2 passenger(s)
4. 7.93 miles - $297.75 total - $0.00 tip - 1 passenger(s)
5. 7.18 miles - $282.75 total - $5.00 tip - 1 passenger(s)

Execution time: 8.91ms

Parameters used: $1=5, $2=10, $3=5

============================================================

Method Comparison:

.sql() - Uses Apache Arrow Flight (gRPC)
  - Higher performance and efficiency
  - Better for large datasets and high-throughput applications
  - Returns Arrow Tables (columnar format)
  - Supports parametrized queries ($1, $2, ... placeholders)
  - Works in true Node.js runtimes (local Node.js, Lambda)

.sqlJson() - Uses HTTP
  - Simpler integration, works everywhere HTTP does
  - Better for smaller queries and web applications
  - Returns plain JavaScript objects (easier to work with)
  - Works in browsers, Vercel, Netlify, and sandbox environments

============================================================

Analysis complete!

Optional: Minimal Cloud-Only Script

node index_cloud.mjs

node index_cloud.mjs

Expected output is a table list from show tables;.

Advanced and More

Features

Dual mode support: local Spice runtime and Spice.ai Cloud.
Uses both .sql() and .sqlJson() query methods.
Includes five analytics query examples over taxi_trips.

Detailed Cloud Setup

Create a free account at spice.ai (opens in a new tab).
Create a Spice.ai Cloud app.
Deploy this sample's spicepod.yaml to your Cloud app.
Set SPICE_API_KEY, then replace the API key placeholder in index_cloud.mjs with that value.
Run node index_cloud.mjs.

Code Examples

Connect to Spice:

const { SpiceClient } = require("@spiceai/spice");

// Cloud
const spiceCloud = new SpiceClient({ apiKey: process.env.SPICE_API_KEY });

// Local (default localhost runtime)
const spiceLocal = new SpiceClient();

const { SpiceClient } = require("@spiceai/spice");

// Cloud
const spiceCloud = new SpiceClient({ apiKey: process.env.SPICE_API_KEY });

// Local (default localhost runtime)
const spiceLocal = new SpiceClient();

Query with .sql() (Arrow Flight / gRPC):

const result = await spice.sql("SELECT * FROM taxi_trips LIMIT 10");
const rows = result.toArray();

const result = await spice.sql("SELECT * FROM taxi_trips LIMIT 10");
const rows = result.toArray();

Query with .sqlJson() (HTTP):

const result = await spice.sqlJson("SELECT * FROM taxi_trips LIMIT 10");
const rows = result.data;

const result = await spice.sqlJson("SELECT * FROM taxi_trips LIMIT 10");
const rows = result.data;

About the Dataset

This sample uses the NYC taxi_trips dataset.

Local mode: dataset is defined in spicepod.yaml and loads with spice run.
Cloud mode: deploy spicepod.yaml to your Cloud app before running queries.

Links

spiceai/cookbook/client-sdk/spice.js-sdk-sample/README.md

Spice.js SDK Sample

Works with v1.0+

Use @spiceai/spice (opens in a new tab) from Node.js to query taxi_trips.

What This Sample Includes

index.js: Main sample with multiple analytics queries.
index_cloud.mjs: Minimal cloud-only query (show tables;).

Prerequisites

Node.js 20+
npm
Spice CLI (opens in a new tab) for local mode

Quick Start

git clone https://github.com/spiceai/cookbook.git
cd cookbook/client-sdk/spice.js-sdk-sample
npm install

git clone https://github.com/spiceai/cookbook.git
cd cookbook/client-sdk/spice.js-sdk-sample
npm install

Run with Local Spice Runtime

Start Spice runtime in one terminal:

spice run

spice run

Run the Node sample in another terminal:

npm start

npm start

index.js runs against your local runtime by default.

Run with Spice.ai Cloud

Set your API key for the commands in this README:

export SPICE_API_KEY="your_api_key"

export SPICE_API_KEY="your_api_key"

index.js reads SPICE_API_KEY (from the environment or a .env file) and connects to Spice.ai Cloud instead of the local runtime when it is set - no code edit needed:

npm start

npm start

node index_cloud.mjs

node index_cloud.mjs

Example Output

The application prints output similar to:

Spice.js initialized
  Platform: Node.js v24.9.0 darwin arm64
  Transport: Arrow Flight -> HTTP
  Endpoint: http://127.0.0.1:8090
  Flight URL: 127.0.0.1:50051
NYC Taxi Trips Data Analysis

Connected to: Local Spice Runtime
Tip: Set SPICE_API_KEY in .env to use Spice.ai Cloud

Querying taxi_trips dataset...

============================================================

Query 1: Top 10 Most Expensive Taxi Trips

Using .sql() - Apache Arrow Flight (gRPC) for high performance

Found 10 trips:

1. $5000.00 - 0 miles - 0 passenger(s)
2. $5000.00 - 0 miles - 0 passenger(s)
3. $2500.00 - 0 miles - 0 passenger(s)
4. $2500.00 - 0 miles - 0 passenger(s)
5. $2500.00 - 0 miles - 0 passenger(s)
6. $2225.30 - 31.95 miles - 1 passenger(s)
7. $1617.50 - 233.25 miles - 1 passenger(s)
8. $1000.00 - 0 miles - 0 passenger(s)
9. $940.93 - 142.62 miles - 1 passenger(s)
10. $900.00 - 157.25 miles - 1 passenger(s)

Execution time: 27.59ms

============================================================

Query 2: Trip Statistics Summary

Statistics from sample:
  - Total trips analyzed: 2964624
  - Average fare: $26.8
  - Average distance: 3.65 miles
  - Average tip: $3.34
  - Highest fare: $5000
  - Lowest fare: $-900

Execution time: 9.25ms

============================================================

Query 3: Top 10 Popular Pickup Locations

Most popular pickup locations:

1. Location ID 132:
  145240 trips | Avg fare: $76.58 | Avg distance: 15.49 miles
2. Location ID 161:
  143471 trips | Avg fare: $23.48 | Avg distance: 2.56 miles
3. Location ID 237:
  142708 trips | Avg fare: $19.45 | Avg distance: 1.7 miles
4. Location ID 236:
  136465 trips | Avg fare: $20 | Avg distance: 1.85 miles
5. Location ID 162:
  106717 trips | Avg fare: $22.88 | Avg distance: 2.23 miles
6. Location ID 230:
  106324 trips | Avg fare: $26.27 | Avg distance: 2.91 miles
7. Location ID 186:
  104523 trips | Avg fare: $23.64 | Avg distance: 2.27 miles
8. Location ID 142:
  104080 trips | Avg fare: $21 | Avg distance: 2.09 miles
9. Location ID 138:
  89533 trips | Avg fare: $65.01 | Avg distance: 9.59 miles
10. Location ID 239:
  88474 trips | Avg fare: $20.93 | Avg distance: 2.26 miles

Execution time: 9.00ms

============================================================

Query 4: Payment Type Distribution

Using .sqlJson() - HTTP transport for simpler integration

Payment type breakdown:

1. Credit card (Type 1):
  2,319,046 trips | Avg amount: $28.26 | Avg tip: $4.17
2. Cash (Type 2):
  439,191 trips | Avg amount: $22.88 | Avg tip: $0
3. Dispute (Type 4):
  46,628 trips | Avg amount: $1.77 | Avg tip: $0.04
4. No charge (Type 3):
  19,597 trips | Avg amount: $8.76 | Avg tip: $0.01

Execution time: 17.14ms

============================================================

Query 5: Parametrized Query - Trips by Distance Range

Using .sql() with parameters for safe, dynamic queries

Trips with distance between 5 and 10 miles:

1. 5.99 miles - $313.74 total - $99.99 tip - 4 passenger(s)
2. 5.84 miles - $311.00 total - $15.00 tip - 1 passenger(s)
3. 7.47 miles - $307.75 total - $15.00 tip - 2 passenger(s)
4. 7.93 miles - $297.75 total - $0.00 tip - 1 passenger(s)
5. 7.18 miles - $282.75 total - $5.00 tip - 1 passenger(s)

Execution time: 8.91ms

Parameters used: $1=5, $2=10, $3=5

============================================================

Method Comparison:

.sql() - Uses Apache Arrow Flight (gRPC)
  - Higher performance and efficiency
  - Better for large datasets and high-throughput applications
  - Returns Arrow Tables (columnar format)
  - Supports parametrized queries ($1, $2, ... placeholders)
  - Works in true Node.js runtimes (local Node.js, Lambda)

.sqlJson() - Uses HTTP
  - Simpler integration, works everywhere HTTP does
  - Better for smaller queries and web applications
  - Returns plain JavaScript objects (easier to work with)
  - Works in browsers, Vercel, Netlify, and sandbox environments

============================================================

Analysis complete!

Spice.js initialized
  Platform: Node.js v24.9.0 darwin arm64
  Transport: Arrow Flight -> HTTP
  Endpoint: http://127.0.0.1:8090
  Flight URL: 127.0.0.1:50051
NYC Taxi Trips Data Analysis

Connected to: Local Spice Runtime
Tip: Set SPICE_API_KEY in .env to use Spice.ai Cloud

Querying taxi_trips dataset...

============================================================

Query 1: Top 10 Most Expensive Taxi Trips

Using .sql() - Apache Arrow Flight (gRPC) for high performance

Found 10 trips:

1. $5000.00 - 0 miles - 0 passenger(s)
2. $5000.00 - 0 miles - 0 passenger(s)
3. $2500.00 - 0 miles - 0 passenger(s)
4. $2500.00 - 0 miles - 0 passenger(s)
5. $2500.00 - 0 miles - 0 passenger(s)
6. $2225.30 - 31.95 miles - 1 passenger(s)
7. $1617.50 - 233.25 miles - 1 passenger(s)
8. $1000.00 - 0 miles - 0 passenger(s)
9. $940.93 - 142.62 miles - 1 passenger(s)
10. $900.00 - 157.25 miles - 1 passenger(s)

Execution time: 27.59ms

============================================================

Query 2: Trip Statistics Summary

Statistics from sample:
  - Total trips analyzed: 2964624
  - Average fare: $26.8
  - Average distance: 3.65 miles
  - Average tip: $3.34
  - Highest fare: $5000
  - Lowest fare: $-900

Execution time: 9.25ms

============================================================

Query 3: Top 10 Popular Pickup Locations

Most popular pickup locations:

1. Location ID 132:
  145240 trips | Avg fare: $76.58 | Avg distance: 15.49 miles
2. Location ID 161:
  143471 trips | Avg fare: $23.48 | Avg distance: 2.56 miles
3. Location ID 237:
  142708 trips | Avg fare: $19.45 | Avg distance: 1.7 miles
4. Location ID 236:
  136465 trips | Avg fare: $20 | Avg distance: 1.85 miles
5. Location ID 162:
  106717 trips | Avg fare: $22.88 | Avg distance: 2.23 miles
6. Location ID 230:
  106324 trips | Avg fare: $26.27 | Avg distance: 2.91 miles
7. Location ID 186:
  104523 trips | Avg fare: $23.64 | Avg distance: 2.27 miles
8. Location ID 142:
  104080 trips | Avg fare: $21 | Avg distance: 2.09 miles
9. Location ID 138:
  89533 trips | Avg fare: $65.01 | Avg distance: 9.59 miles
10. Location ID 239:
  88474 trips | Avg fare: $20.93 | Avg distance: 2.26 miles

Execution time: 9.00ms

============================================================

Query 4: Payment Type Distribution

Using .sqlJson() - HTTP transport for simpler integration

Payment type breakdown:

1. Credit card (Type 1):
  2,319,046 trips | Avg amount: $28.26 | Avg tip: $4.17
2. Cash (Type 2):
  439,191 trips | Avg amount: $22.88 | Avg tip: $0
3. Dispute (Type 4):
  46,628 trips | Avg amount: $1.77 | Avg tip: $0.04
4. No charge (Type 3):
  19,597 trips | Avg amount: $8.76 | Avg tip: $0.01

Execution time: 17.14ms

============================================================

Query 5: Parametrized Query - Trips by Distance Range

Using .sql() with parameters for safe, dynamic queries

Trips with distance between 5 and 10 miles:

1. 5.99 miles - $313.74 total - $99.99 tip - 4 passenger(s)
2. 5.84 miles - $311.00 total - $15.00 tip - 1 passenger(s)
3. 7.47 miles - $307.75 total - $15.00 tip - 2 passenger(s)
4. 7.93 miles - $297.75 total - $0.00 tip - 1 passenger(s)
5. 7.18 miles - $282.75 total - $5.00 tip - 1 passenger(s)

Execution time: 8.91ms

Parameters used: $1=5, $2=10, $3=5

============================================================

Method Comparison:

.sql() - Uses Apache Arrow Flight (gRPC)
  - Higher performance and efficiency
  - Better for large datasets and high-throughput applications
  - Returns Arrow Tables (columnar format)
  - Supports parametrized queries ($1, $2, ... placeholders)
  - Works in true Node.js runtimes (local Node.js, Lambda)

.sqlJson() - Uses HTTP
  - Simpler integration, works everywhere HTTP does
  - Better for smaller queries and web applications
  - Returns plain JavaScript objects (easier to work with)
  - Works in browsers, Vercel, Netlify, and sandbox environments

============================================================

Analysis complete!

Optional: Minimal Cloud-Only Script

node index_cloud.mjs

node index_cloud.mjs

Expected output is a table list from show tables;.

Advanced and More

Features

Dual mode support: local Spice runtime and Spice.ai Cloud.
Uses both .sql() and .sqlJson() query methods.
Includes five analytics query examples over taxi_trips.

Detailed Cloud Setup

Create a free account at spice.ai (opens in a new tab).
Create a Spice.ai Cloud app.
Deploy this sample's spicepod.yaml to your Cloud app.
Set SPICE_API_KEY, then replace the API key placeholder in index_cloud.mjs with that value.
Run node index_cloud.mjs.

Code Examples

Connect to Spice:

const { SpiceClient } = require("@spiceai/spice");

// Cloud
const spiceCloud = new SpiceClient({ apiKey: process.env.SPICE_API_KEY });

// Local (default localhost runtime)
const spiceLocal = new SpiceClient();

const { SpiceClient } = require("@spiceai/spice");

// Cloud
const spiceCloud = new SpiceClient({ apiKey: process.env.SPICE_API_KEY });

// Local (default localhost runtime)
const spiceLocal = new SpiceClient();

Query with .sql() (Arrow Flight / gRPC):

const result = await spice.sql("SELECT * FROM taxi_trips LIMIT 10");
const rows = result.toArray();

const result = await spice.sql("SELECT * FROM taxi_trips LIMIT 10");
const rows = result.toArray();

Query with .sqlJson() (HTTP):

const result = await spice.sqlJson("SELECT * FROM taxi_trips LIMIT 10");
const rows = result.data;

const result = await spice.sqlJson("SELECT * FROM taxi_trips LIMIT 10");
const rows = result.data;

About the Dataset

This sample uses the NYC taxi_trips dataset.

Local mode: dataset is defined in spicepod.yaml and loads with spice run.
Cloud mode: deploy spicepod.yaml to your Cloud app before running queries.

No models configured

Spice.js SDK Sample

What This Sample Includes

Prerequisites

Quick Start

Run with Local Spice Runtime

Run with Spice.ai Cloud

Example Output

Optional: Minimal Cloud-Only Script

Advanced and More

Features

Detailed Cloud Setup

Code Examples

About the Dataset

Links

No models configured

Spice.js SDK Sample

What This Sample Includes

Prerequisites

Quick Start

Run with Local Spice Runtime

Run with Spice.ai Cloud

Example Output

Optional: Minimal Cloud-Only Script

Advanced and More

Features

Detailed Cloud Setup

Code Examples

About the Dataset

Links