Artifact

The Artifact component provides a structured container for displaying generated content like code, documents, or other outputs with built-in header actions.

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'))

Installation

npx ai-elements@latest add artifact

Usage

import {
  Artifact,
  ArtifactAction,
  ArtifactActions,
  ArtifactContent,
  ArtifactDescription,
  ArtifactHeader,
  ArtifactTitle,
} from '@/components/ai-elements/artifact';

<Artifact>
  <ArtifactHeader>
    <div>
      <ArtifactTitle>Dijkstra's Algorithm Implementation</ArtifactTitle>
      <ArtifactDescription>Updated 1 minute ago</ArtifactDescription>
    </div>
    <ArtifactActions>
      <ArtifactAction icon={CopyIcon} label="Copy" tooltip="Copy to clipboard" />
    </ArtifactActions>
  </ArtifactHeader>
  <ArtifactContent>
    {/* Your content here */}
  </ArtifactContent>
</Artifact>

Features

Structured container with header and content areas
Built-in header with title and description support
Flexible action buttons with tooltips
Customizable styling for all subcomponents
Support for close buttons and action groups
Clean, modern design with border and shadow
Responsive layout that adapts to content
TypeScript support with proper type definitions
Composable architecture for maximum flexibility

Examples

With Code Display

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'))