Introduction
AI Elements
AI Elements is a component library and custom registry built on top of shadcn/ui to help you build AI-native applications faster. It provides pre-built components like conversations, messages and more.
You can install it with:
npx ai-elements@latest
Here are some basic examples of what you can achieve using components from AI Elements.
Components
Actions
Hello, how are you?
I am fine, thank you!
Artifact
Dijkstra's Algorithm Implementation
Updated 1 minute ago
1# Dijkstra's Algorithm implementation
2import heapq
3
4def dijkstra(graph, start):
5 distances = {node: float('inf') for node in graph}
6 distances[start] = 0
7 heap = [(0, start)]
8 visited = set()
9
10 while heap:
11 current_distance, current_node = heapq.heappop(heap)
12 if current_node in visited:
13 continue
14 visited.add(current_node)
15
16 for neighbor, weight in graph[current_node].items():
17 distance = current_distance + weight
18 if distance < distances[neighbor]:
19 distances[neighbor] = distance
20 heapq.heappush(heap, (distance, neighbor))
21
22 return distances
23
24# Example graph
25 graph = {
26 'A': {'B': 1, 'C': 4},
27 'B': {'A': 1, 'C': 2, 'D': 5},
28 'C': {'A': 4, 'B': 2, 'D': 1},
29 'D': {'B': 5, 'C': 1}
30}
31
32print(dijkstra(graph, 'A'))1# Dijkstra's Algorithm implementation
2import heapq
3
4def dijkstra(graph, start):
5 distances = {node: float('inf') for node in graph}
6 distances[start] = 0
7 heap = [(0, start)]
8 visited = set()
9
10 while heap:
11 current_distance, current_node = heapq.heappop(heap)
12 if current_node in visited:
13 continue
14 visited.add(current_node)
15
16 for neighbor, weight in graph[current_node].items():
17 distance = current_distance + weight
18 if distance < distances[neighbor]:
19 distances[neighbor] = distance
20 heapq.heappush(heap, (distance, neighbor))
21
22 return distances
23
24# Example graph
25 graph = {
26 'A': {'B': 1, 'C': 4},
27 'B': {'A': 1, 'C': 2, 'D': 5},
28 'C': {'A': 4, 'B': 2, 'D': 1},
29 'D': {'B': 5, 'C': 1}
30}
31
32print(dijkstra(graph, 'A'))Branch
What are the key strategies for optimizing React performance?
HaHere's the first response to your question. This approach focuses on performance optimization.
AIChain of Thought
Code Block
function MyComponent(props) {
return (
<div>
<h1>Hello, {props.name}!</h1>
<p>This is an example React component.</p>
</div>
);
}function MyComponent(props) {
return (
<div>
<h1>Hello, {props.name}!</h1>
<p>This is an example React component.</p>
</div>
);
}Context
Conversation
Start a conversation
Messages will appear here as the conversation progresses.
Image
Loader
Message
Hello, how are you?
HaOpen In Chat
Prompt Input
Reasoning
Response
Sources
Suggestion
Task
Tool
Web Preview
Inline Citation
According to recent studies, artificial intelligence has shown remarkable progress in natural language processing. The technology continues to evolve rapidly, with new breakthroughs being announced regularlyexample.com +5.
View the source code for all components on GitHub.
