Documentation
Learn how to integrate FineTune Studio into your applications
Quick Start
Create an Account
Sign up for a free account to get started.
Create a Model
Go to the Models page and create your first custom AI model with a system prompt.
Generate API Key
Create an API key from the API Keys page to authenticate your requests.
Make Your First Request
Use the API to send messages to your custom model.
Base URL
https://finetune-studio.onrender.comAuthentication
All API requests require authentication using your API key. Include it in the Authorization header:
Authorization: Bearer YOUR_API_KEYAPI Endpoints
/api/chat/completionsSend a message to your custom AI model and receive a response.
Request Body:
{
"model_name": "string", // Your model name (e.g., "customer-support-bot")
"messages": [
{
"role": "user", // "user" or "assistant"
"content": "string" // Message content
}
],
"stream": false // Optional: Enable streaming
}Response:
{
"id": "string",
"choices": [
{
"message": {
"role": "assistant",
"content": "AI response here"
}
}
],
"usage": {
"total_tokens": 150
}
}Code Examples
cURL
curl -X POST https://finetune-studio.onrender.com/api/chat/completions \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model_name": "your-model-name",
"messages": [
{
"role": "user",
"content": "Hello, how can you help me?"
}
]
}'Python
import requests
url = "https://finetune-studio.onrender.com/api/chat/completions"
headers = {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
}
data = {
"model_name": "your-model-name",
"messages": [
{"role": "user", "content": "Hello, how can you help me?"}
]
}
response = requests.post(url, headers=headers, json=data)
print(response.json())JavaScript (Fetch)
const url = 'https://finetune-studio.onrender.com/api/chat/completions';
const response = await fetch(url, {
method: 'POST',
headers: {
'Authorization': 'Bearer YOUR_API_KEY',
'Content-Type': 'application/json'
},
body: JSON.stringify({
model_name: 'your-model-name',
messages: [
{ role: 'user', content: 'Hello, how can you help me?' }
]
})
});
const data = await response.json();
console.log(data);Node.js (Axios)
const axios = require('axios');
const url = 'https://finetune-studio.onrender.com/api/chat/completions';
const response = await axios.post(
url,
{
model_name: 'your-model-name',
messages: [
{ role: 'user', content: 'Hello, how can you help me?' }
]
},
{
headers: {
'Authorization': 'Bearer YOUR_API_KEY',
'Content-Type': 'application/json'
}
}
);
console.log(response.data);Best Practices
Keep API Keys Secure
Never expose your API keys in client-side code or public repositories.
Use Environment Variables
Store API keys in environment variables, not in your code.
Handle Errors Gracefully
Always implement proper error handling for API requests.
Monitor Usage
Check your analytics dashboard regularly to track API usage and costs.
RAG - Custom Knowledge Base
Give your AI models custom knowledge by uploading documents. The system uses Retrieval Augmented Generation (RAG) to automatically find and use relevant information from your uploaded files.
Supported File Types
Documents, manuals, reports
📝 TXT
Plain text, documentation
📊 CSV
Data tables, spreadsheets
How It Works
Upload Documents
Edit your model and upload PDF, TXT, or CSV files with your custom knowledge
Automatic Processing
Documents are split into chunks and converted to vector embeddings
Smart Retrieval
When users chat, relevant context is automatically retrieved and used
💡 Use Cases: Customer support FAQs, product documentation, API references, company policies, technical manuals, knowledge bases, and more!
Rate Limits
Starter Plan
₹0
5K requests/month
Pro Plan
₹5,999
1M requests/month
Enterprise
Unlimited
custom limits
Need Help?
If you have questions or need assistance, we're here to help!