clara-flow-sdk
Advanced tools
Modern JavaScript SDK for executing Clara AI agent workflows with zero configuration
Modern JavaScript SDK for executing Clara AI agent workflows with zero configuration
npm install clara-flow-sdk
import { ClaraFlowRunner } from 'clara-flow-sdk';
const runner = new ClaraFlowRunner();
const result = await runner.execute(workflow, { input: 'Hello World!' });
console.log(result);
import { ClaraFlowRunner } from 'clara-flow-sdk';
// Create a simple workflow
const textWorkflow = {
nodes: [
{
id: 'input-1',
type: 'input',
name: 'User Input',
data: { value: 'Hello' },
outputs: [{ id: 'output', name: 'Output' }]
},
{
id: 'process-1',
type: 'static-text',
name: 'Add Greeting',
data: { text: 'Welcome: ' },
inputs: [{ id: 'input', name: 'Input' }],
outputs: [{ id: 'output', name: 'Output' }]
},
{
id: 'combine-1',
type: 'combine-text',
name: 'Combine',
data: { separator: '' },
inputs: [
{ id: 'text1', name: 'Text1' },
{ id: 'text2', name: 'Text2' }
],
outputs: [{ id: 'output', name: 'Output' }]
},
{
id: 'output-1',
type: 'output',
name: 'Final Result',
inputs: [{ id: 'input', name: 'Input' }]
}
],
connections: [
{ sourceNodeId: 'process-1', sourcePortId: 'output', targetNodeId: 'combine-1', targetPortId: 'text1' },
{ sourceNodeId: 'input-1', sourcePortId: 'output', targetNodeId: 'combine-1', targetPortId: 'text2' },
{ sourceNodeId: 'combine-1', sourcePortId: 'output', targetNodeId: 'output-1', targetPortId: 'input' }
]
};
// Execute workflow
const runner = new ClaraFlowRunner();
const result = await runner.execute(textWorkflow, { 'input-1': 'Clara!' });
console.log(result); // { "output-1": { "output": "Welcome: Clara!" } }
const jsonWorkflow = {
nodes: [
{
id: 'data-input',
type: 'input',
name: 'JSON Data',
data: { value: '{"user": {"name": "Alice", "profile": {"age": 30, "city": "NYC"}}}' },
outputs: [{ id: 'output', name: 'Output' }]
},
{
id: 'parse-name',
type: 'json-parse',
name: 'Extract Name',
data: { field: 'user.name' },
inputs: [{ id: 'input', name: 'JSON' }],
outputs: [{ id: 'output', name: 'Output' }]
},
{
id: 'parse-city',
type: 'json-parse',
name: 'Extract City',
data: { field: 'user.profile.city' },
inputs: [{ id: 'input', name: 'JSON' }],
outputs: [{ id: 'output', name: 'Output' }]
},
{
id: 'result',
type: 'output',
name: 'User Info',
inputs: [{ id: 'input', name: 'Input' }]
}
],
connections: [
{ sourceNodeId: 'data-input', sourcePortId: 'output', targetNodeId: 'parse-name', targetPortId: 'input' },
{ sourceNodeId: 'parse-name', sourcePortId: 'output', targetNodeId: 'result', targetPortId: 'input' }
]
};
const result = await runner.execute(jsonWorkflow);
console.log(result); // Extracted: "Alice"
const runner = new ClaraFlowRunner();
// Register a custom node
runner.registerCustomNode({
type: 'email-validator',
name: 'Email Validator',
executionCode: `
function execute(inputs, properties, context) {
const email = inputs.email || '';
const emailRegex = /^[^\\s@]+@[^\\s@]+\\.[^\\s@]+$/;
const isValid = emailRegex.test(email);
context.log('Validating email: ' + email);
return {
output: isValid,
email: email,
status: isValid ? 'valid' : 'invalid'
};
}
`
});
// Use custom node in workflow
const emailWorkflow = {
nodes: [
{
id: 'email-input',
type: 'input',
name: 'Email',
data: { value: 'user@example.com' },
outputs: [{ id: 'output', name: 'Output' }]
},
{
id: 'validator',
type: 'email-validator',
name: 'Validate Email',
inputs: [{ id: 'email', name: 'Email' }],
outputs: [{ id: 'output', name: 'Valid' }]
},
{
id: 'result',
type: 'output',
name: 'Validation Result',
inputs: [{ id: 'input', name: 'Input' }]
}
],
connections: [
{ sourceNodeId: 'email-input', sourcePortId: 'output', targetNodeId: 'validator', targetPortId: 'email' },
{ sourceNodeId: 'validator', sourcePortId: 'output', targetNodeId: 'result', targetPortId: 'input' }
]
};
const result = await runner.execute(emailWorkflow);
console.log(result); // Email validation result
const aiWorkflow = {
nodes: [
{
id: 'prompt',
type: 'input',
name: 'User Prompt',
data: { value: 'Explain quantum computing in simple terms' },
outputs: [{ id: 'output', name: 'Output' }]
},
{
id: 'ai-chat',
type: 'llm',
name: 'AI Assistant',
data: {
apiKey: process.env.OPENAI_API_KEY,
model: 'gpt-3.5-turbo',
temperature: 0.7
},
inputs: [
{ id: 'user', name: 'User Message' },
{ id: 'system', name: 'System Message' }
],
outputs: [{ id: 'output', name: 'Response' }]
},
{
id: 'response',
type: 'output',
name: 'AI Response',
inputs: [{ id: 'input', name: 'Input' }]
}
],
connections: [
{ sourceNodeId: 'prompt', sourcePortId: 'output', targetNodeId: 'ai-chat', targetPortId: 'user' },
{ sourceNodeId: 'ai-chat', sourcePortId: 'output', targetNodeId: 'response', targetPortId: 'input' }
]
};
const result = await runner.execute(aiWorkflow);
console.log(result['response'].output); // AI explanation
<!DOCTYPE html>
<html>
<head>
<title>Clara Flow SDK Demo</title>
</head>
<body>
<script src="https://unpkg.com/clara-flow-sdk@2.0.0/dist/clara-flow-sdk.umd.min.js"></script>
<script>
const runner = new ClaraFlowSDK.ClaraFlowRunner();
const simpleFlow = {
nodes: [
{ id: 'in', type: 'input', data: { value: 'Hello Browser!' }, outputs: [{ id: 'output' }] },
{ id: 'out', type: 'output', inputs: [{ id: 'input' }] }
],
connections: [
{ sourceNodeId: 'in', sourcePortId: 'output', targetNodeId: 'out', targetPortId: 'input' }
]
};
runner.execute(simpleFlow).then(result => {
console.log('Result:', result);
});
</script>
</body>
</html>
<input type="file" id="workflow-file" accept=".json">
<button onclick="runWorkflow()">Run Workflow</button>
<script>
async function runWorkflow() {
const fileInput = document.getElementById('workflow-file');
const file = fileInput.files[0];
if (file) {
const workflow = await ClaraFlowSDK.BrowserUtils.loadFlowFromFile(file);
const runner = new ClaraFlowSDK.ClaraFlowRunner();
const result = await runner.execute(workflow);
console.log('Workflow result:', result);
}
}
</script>
| Node Type | Description | Example Use Case |
|---|---|---|
input | Accept user input | Form data, parameters |
output | Display results | Final output, responses |
static-text | Fixed text content | Templates, prompts |
combine-text | Merge text inputs | String concatenation |
json-parse | Parse JSON data | API response processing |
if-else | Conditional logic | Decision making |
llm | AI language model | Chat, text generation |
structured-llm | Structured AI output | JSON generation |
api-request | HTTP requests | External API calls |
const runner = new ClaraFlowRunner({
enableLogging: true, // Enable console logging
timeout: 30000, // Execution timeout (ms)
logLevel: 'info', // Log level: 'info', 'warn', 'error'
maxRetries: 3 // Max retry attempts
});
Import workflows directly from Clara Studio:
// Export from Clara Studio as "SDK Enhanced" format
const studioExport = {
format: 'clara-sdk',
version: '1.0.0',
flow: { /* workflow definition */ },
customNodes: [ /* custom node definitions */ ]
};
// Execute directly
const result = await runner.execute(studioExport, inputs);
try {
const result = await runner.execute(workflow, inputs);
console.log('Success:', result);
} catch (error) {
console.error('Workflow failed:', error.message);
// Get detailed logs
const logs = runner.getLogs();
console.log('Execution logs:', logs);
}
const runner = new ClaraFlowRunner({ enableLogging: true });
// Execute workflow
await runner.execute(workflow);
// Get execution logs
const logs = runner.getLogs();
logs.forEach(log => {
console.log(`[${log.level}] ${log.message}`, log.data);
});
// Clear logs
runner.clearLogs();
The SDK is designed to work seamlessly with server deployment:
// Future server integration
import express from 'express';
import { ClaraFlowRunner } from 'clara-flow-sdk';
const app = express();
const runner = new ClaraFlowRunner();
app.post('/execute', async (req, res) => {
try {
const { workflow, inputs } = req.body;
const result = await runner.execute(workflow, inputs);
res.json({ success: true, result });
} catch (error) {
res.status(500).json({ success: false, error: error.message });
}
});
import { ClaraFlowRunner, BrowserUtils } from 'clara-flow-sdk';
interface WorkflowResult {
[key: string]: any;
}
const runner: ClaraFlowRunner = new ClaraFlowRunner({
enableLogging: true,
timeout: 30000
});
const result: WorkflowResult = await runner.execute(workflow, inputs);
git checkout -b feature/amazing-feature)git commit -m 'Add amazing feature')git push origin feature/amazing-feature)This project is licensed under the MIT License - see the LICENSE file for details.
Made with ❤️ by the Clara Team
FAQs
Modern JavaScript SDK for executing Clara AI agent workflows with zero configuration
The npm package clara-flow-sdk receives a total of 45 weekly downloads. As such, clara-flow-sdk popularity was classified as not popular.
We found that clara-flow-sdk demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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