Portkey AI: Unified Generative AI Platform

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Introduction

In today's rapidly evolving AI landscape, managing multiple AI models and providers can be challenging for developers. Portkey AI emerges as a powerful solution, offering a unified interface for integrating and managing over 250 AI models. This comprehensive guide will walk you through setting up Portkey AI and leveraging its powerful features for your applications.

What is Portkey AI?

Portkey AI serves as a comprehensive platform that streamlines AI integration for developers and organizations. Think of it as a universal remote control for AI services - one interface to manage them all. The platform offers:

• Access to 250+ AI models
• Advanced monitoring and logging capabilities
• Structured output handling
• Multi-provider support
• Cost and usage tracking

Getting Started with Portkey

Installation and Setup

First, let's install the necessary packages:

!pip install -qU portkey-ai openai portkey

Next, set up your API keys:

import os
from google.colab import userdata

os.environ['OPENAI_API_KEY'] = userdata.get('OPENAI_API_KEY')
os.environ['PORTKEY_API_KEY'] = userdata.get('PORTKEY_API_KEY')

Basic Integration

Here's how to set up the Portkey gateway with OpenAI:

from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

client = OpenAI(
    api_key=userdata.get('OPENAI_API_KEY'),
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        provider="openai",
        api_key=userdata.get('PORTKEY_API_KEY')
    )
)

Advanced Features

1. User Tracking

Portkey allows you to monitor individual user interactions and costs:

chat_complete = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "What is Portkey-AI?"}],
    user="shubham"
)

2. Structured Outputs

Portkey supports enforcing specific JSON schemas for model outputs:

from pydantic import BaseModel

class Step(BaseModel):
    explanation: str
    output: str

class MathReasoning(BaseModel):
    steps: list[Step]
    final_answer: str

completion = client.beta.chat.completions.parse(
    model="gpt-4o",
    messages=[
        {"role": "system", "content": "You are a helpful math tutor."},
        {"role": "user", "content": "how can I solve 8x + 7 = -23"}
    ],
    response_format=MathReasoning,
)

3. Multi-Provider Support

Anthropic Integration

client = OpenAI(
    api_key=userdata.get('ANTHROPIC_API_KEY'),
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        provider="anthropic",
        api_key=userdata.get("PORTKEY_API_KEY")
    ),
)

Mistral AI Integration

client = OpenAI(
    api_key=userdata.get('MISTRAL_API_KEY'),
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        provider="mistral-ai",
        api_key=userdata.get("PORTKEY_API_KEY")
    )
)

Best Practices and Tips

Logging and Monitoring

• Use the Portkey dashboard to monitor:
• Token usage
• Execution time
• Cost per request
• User-level analytics

Error Handling

Always implement proper error handling:

try:
    response = client.chat.completions.create(
        model="gpt-4o",
        messages=[{"role": "user", "content": "Hello"}]
    )
except Exception as e:
    print(f"Error: {e}")

Practical Applications

1. Customer Support Automation

Use Portkey to build a support system that can:

• Route queries to appropriate AI models
• Track user interactions
• Maintain conversation context
• Generate structured responses

2. Content Generation Pipeline

Create a content generation system that:

• Uses different models for different content types
• Ensures output consistency through schemas
• Tracks usage and costs per content piece

3. Data Analysis Workflow

Implement an analysis pipeline that:

• Processes data through multiple AI models
• Generates structured reports
• Maintains audit trails of all operations

Future Considerations

As AI technology evolves, Portkey is positioned to:

• Support new AI models and providers
• Enhance monitoring capabilities
• Improve cost optimization features
• Expand integration options

Conclusion

Portkey AI represents a significant step forward in making AI integration more accessible and manageable for developers. By providing a unified interface, robust monitoring tools, and support for multiple providers, it simplifies the complex landscape of AI service integration. Whether you're building a simple chatbot or a complex AI-powered application, Portkey offers the tools and features needed to succeed.

Remember to regularly check the official documentation and community resources as new features and capabilities are added to the platform. Happy coding!

Resources and Further Reading

• Portkey AI Documentation
• OpenAI API Reference
• Anthropic Claude Documentation
• Mistral AI Documentation

Community Resources

• Portkey AI GitHub Repository
• Build Fast With AI Portkey NoteBook

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