139 lines
4.0 KiB
Plaintext
139 lines
4.0 KiB
Plaintext
---
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title: Jan API Integration for Developers
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description: Learn to build applications using Jan's local server API
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video:
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type: video
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link: https://www.youtube.com/watch?v=L_jWHffIx5E
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duration: 420
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---
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import { List } from 'starlight-videos/components';
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# Jan API Integration for Developers
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Ready to build applications powered by Jan? In this advanced course, you'll learn how to integrate Jan's local server API into your own applications, enabling you to create AI-powered tools and services.
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## What You'll Learn
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- Understanding Jan's OpenAI-compatible API
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- Setting up the local server for development
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- Making your first API calls
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- Authentication and security considerations
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- Building a simple AI-powered application
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- Best practices for production deployment
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## Prerequisites
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<List title="Developer Requirements" variant="caution" icon="warning">
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- Jan installed and working properly
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- Downloaded at least one model
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- Local server enabled in Jan settings
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- Basic programming knowledge (any language)
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- Understanding of REST APIs and HTTP requests
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- Familiarity with JSON data format
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</List>
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## Course Outline
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### 1. API Overview
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- Jan's local server architecture
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- OpenAI compatibility layer
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- Available endpoints and methods
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- Rate limiting and resource management
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### 2. Development Setup
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- Enabling the local server
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- Configuring ports and security
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- Testing connectivity with curl
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- Using API testing tools like Postman
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### 3. Core API Operations
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- Chat completions endpoint
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- Streaming responses
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- Model management
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- System monitoring
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### 4. Building Your First App
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We'll build a simple chat application that demonstrates:
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- Connecting to Jan's API
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- Sending messages and receiving responses
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- Handling streaming responses
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- Error handling and reconnection logic
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### 5. Advanced Integration Patterns
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- Async/await patterns for better performance
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- Caching strategies for repeated queries
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- Integration with popular frameworks (Express.js, FastAPI, etc.)
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- WebSocket integration for real-time apps
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## Code Examples
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### Basic Python Integration
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```python
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import requests
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import json
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def chat_with_jan(message):
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url = "http://localhost:1337/v1/chat/completions"
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headers = {"Content-Type": "application/json"}
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data = {
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"model": "your-model-name",
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"messages": [{"role": "user", "content": message}]
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}
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response = requests.post(url, headers=headers, json=data)
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return response.json()
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```
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### JavaScript/Node.js Example
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```javascript
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const axios = require('axios');
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async function chatWithJan(message) {
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const response = await axios.post('http://localhost:1337/v1/chat/completions', {
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model: 'your-model-name',
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messages: [{ role: 'user', content: message }]
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});
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return response.data.choices[0].message.content;
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}
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```
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## Security Considerations
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- Keeping API endpoints local and secure
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- Managing API keys and authentication
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- Rate limiting to prevent abuse
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- Monitoring resource usage
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- Backup and recovery strategies
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## Real-World Applications
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Examples of what you can build:
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- **Customer Service Bots**: Automated support using your data
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- **Content Generation Tools**: AI-powered writing assistants
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- **Code Analysis Tools**: Automated code review and suggestions
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- **Personal Assistants**: Custom AI helpers for specific tasks
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## Production Deployment
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- Scaling considerations for multiple users
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- Load balancing strategies
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- Monitoring and logging
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- Error handling and fallback mechanisms
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- Performance optimization techniques
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## Next Steps
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After completing this course, consider exploring:
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- **Custom Model Integration**: Adding your own fine-tuned models
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- **Multi-Modal Applications**: Integrating with vision and audio models
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- **Enterprise Scaling**: Deploying Jan for team use
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## Resources
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- [Jan API Documentation](https://jan.ai/api-reference)
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- [Example Applications GitHub Repository](https://github.com/menloresearch/jan-examples)
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- [Community Discord](https://discord.gg/qSwXFx6Krr) for developer support
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Ready to start building? Watch the video above and follow along with the code examples! |