TypeScript SDK Integration

1import { Cognitora } from '@cognitora/sdk';
2
3const client = new Cognitora({
4  apiKey: process.env.COGNITORA_API_KEY!,
5  baseURL: 'https://api.cognitora.dev'
6});
7
8class CodeInterpreter {
9  private sessionId: string | null = null;
10
11  async createSession() {
12    const sessionResponse = await client.codeInterpreter.createSession({
13      language: 'python',
14      timeout_minutes: 30
15    });
16
17    this.sessionId = sessionResponse.data.session_id;
18    return this.sessionId;
19  }
20
21  async execute(code: string, language: 'python' | 'javascript' | 'bash' = 'python') {
22    if (!this.sessionId) {
23      await this.createSession();
24    }
25
26    try {
27      const result = await client.codeInterpreter.execute({
28        code,
29        language,
30        session_id: this.sessionId!
31      });
32
33      return {
34        success: result.data.status === 'completed',
35        outputs: result.data.outputs,
36        execution_time: result.data.execution_time_ms,
37        session_id: this.sessionId
38      };
39    } catch (error) {
40      return {
41        success: false,
42        error: error instanceof Error ? error.message : 'Unknown error',
43        session_id: this.sessionId
44      };
45    }
46  }
47
48  async executeCompute(image: string, command: string[], options: {
49    cpu_cores?: number;
50    memory_mb?: number;
51    max_cost_credits?: number;
52    storage_gb?: number;
53  } = {}) {
54    try {
55      const execution = await client.compute.createExecution({
56        image,
57        command,
58        cpu_cores: options.cpu_cores || 1.0,
59        memory_mb: options.memory_mb || 512,
60        max_cost_credits: options.max_cost_credits || 10,
61        storage_gb: options.storage_gb || 5
62      });
63
64      return {
65        execution_id: execution.id,
66        status: execution.status,
67        image: execution.image,
68        command: execution.command
69      };
70    } catch (error) {
71      return {
72        success: false,
73        error: error instanceof Error ? error.message : 'Unknown error'
74      };
75    }
76  }
77
78  async uploadFiles(files: Array<{ name: string; content: string; encoding?: string }>) {
79    if (!this.sessionId) {
80      await this.createSession();
81    }
82
83    try {
84      const result = await client.codeInterpreter.runWithFiles(
85        'print("Files uploaded successfully")',
86        files.map(f => ({ name: f.name, content: f.content, encoding: f.encoding || 'string' })),
87        'python',
88        this.sessionId!
89      );
90
91      return {
92        success: result.data.status === 'completed',
93        outputs: result.data.outputs
94      };
95    } catch (error) {
96      return {
97        success: false,
98        error: error instanceof Error ? error.message : 'Unknown error'
99      };
100    }
101  }
102
103  async cleanup() {
104    if (this.sessionId) {
105      await client.codeInterpreter.deleteSession(this.sessionId);
106      this.sessionId = null;
107    }
108  }
109}
110
111// Example usage
112async function main() {
113  const interpreter = new CodeInterpreter();
114  
115  try {
116    // Execute Python code with persistent variables
117    await interpreter.execute('x = 42');
118    await interpreter.execute('y = "Hello World"');
119    
120    // Use variables from previous execution
121    const result = await interpreter.execute('print(f"{y}! The answer is {x}")');
122    console.log('Session result:', result);
123    
124    // Execute containerized workload
125    const computeResult = await interpreter.executeCompute(
126      'docker.io/library/python:3.11-slim',
127      ['python', '-c', 'print("Hello from container!")'],
128      { cpu_cores: 1.0, memory_mb: 512, max_cost_credits: 10 }
129    );
130    console.log('Compute result:', computeResult);
131    
132    // Upload and process files
133    await interpreter.uploadFiles([
134      { name: 'data.csv', content: 'name,age\nJohn,25\nJane,30' }
135    ]);
136    
137    await interpreter.execute(`
138import pandas as pd
139df = pd.read_csv('data.csv')
140print(df.describe())
141    `);
142    
143  } finally {
144    await interpreter.cleanup();
145  }
146}
147
148main().catch(console.error);