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API Services

AI API interfaces for developers to integrate into your applications.

đŸŽ¯ What Are API Services?

API services provide programming interfaces that allow you to integrate AI capabilities into your own applications, websites, or tools.

Suitable For:

  • Developers
  • Technical teams
  • Production environment deployment
  • Automation needs

🌟 Recommended Services

Free Forever, High Quota

Google AI Studio API

  • Quota: 15M tokens/day
  • Features: Gemini series, OpenAI compatible
  • Rating: ⭐⭐⭐⭐⭐

Groq API

  • Quota: 14,400 times/day
  • Features: 800+ tokens/s ultra-fast
  • Rating: ⭐⭐⭐⭐⭐

Rich Model Selection

OpenRouter API

  • Quota: 50-1,000 times/day
  • Features: 47+ free models, OpenAI compatible
  • Rating: ⭐⭐⭐⭐⭐

Ultra-low Price

DeepSeek API

  • Quota: ÂĨ5 trial (7 days)
  • Features: 97% cheaper than GPT-4, top Chinese performance
  • Rating: ⭐⭐⭐⭐⭐

RAG Expert

Cohere API

  • Quota: 1,000-10,000 times/month
  • Features: Embed + Rerank, RAG optimized
  • Rating: ⭐⭐⭐⭐⭐

Enterprise-grade

Vertex AI API

  • Quota: $300 trial (90 days)
  • Features: 2M context, complete MLOps
  • Rating: ⭐⭐⭐⭐ (Enterprise choice)

📊 Detailed Comparison

By Free Quota

API Free Type Daily/Monthly Quota Rate Limit OpenAI Compatible
Google AI Studio Free Forever 15M tokens/day 1,500 req/day ❌
Groq Free Forever 14,400 req/day 30 req/min ✅
OpenRouter Free Forever 50-1,000 req/day 20 req/min ✅
DeepSeek Trial Credits ÂĨ5 (7 days) By usage ✅
Cohere Trial Credits 1,000-10,000/month 10-1000 req/min ❌
Vertex AI Trial Credits $300 (90 days) Configurable ❌

By Key Features

API Inference Speed Chinese Performance Context Special Features
Google AI Studio Fast Excellent 2M Multimodal, high quota
Groq 🏆 Ultra-fast Good 128K Speed champion
OpenRouter Fast Varies by model Varies 🏆 47+ models
DeepSeek Fast 🏆 Top-tier 64K Ultra-low price, chain-of-thought
Cohere Fast Excellent 128K 🏆 RAG, Embed
Vertex AI Fast Excellent 🏆 2M Enterprise-grade

đŸŽ¯ Selection Guide

I Need High Free Quota

→ Google AI Studio API - 15M tokens/day

I Need Ultra-fast Inference Speed

→ Groq API - 800+ tokens/s

I Need OpenAI Compatibility

→ Groq API → OpenRouter API → DeepSeek API

I Need to Try Multiple Models

→ OpenRouter API - 47+ models

I Need Chinese Optimization

→ DeepSeek API - Top Chinese performance

I Need RAG Features

→ Cohere API - Embed + Rerank

I Need Ultra-long Context

→ Google AI Studio API - 2M → Vertex AI API - 2M

I Need Enterprise Deployment

→ Vertex AI API - Complete MLOps

💡 Development Suggestions

Quick Start

  1. Choose the Right API

    • Personal projects: Google AI Studio or Groq
    • Enterprise projects: Vertex AI
    • Multi-model testing: OpenRouter
    • Chinese applications: DeepSeek
    • RAG applications: Cohere

  2. Get API Keys

    • Register according to provider documentation
    • Save API keys

  3. Install SDK

    # OpenAI compatible
pip install openai

# Or use official SDKs
pip install google-cloud-aiplatform
pip install groq
pip install cohere

  4. Write Code

    • Refer to each API’s documentation
    • Start with simple examples
    • Gradually add features

Best Practices

  1. Securely Manage API Keys

    import os
from dotenv import load_dotenv

load_dotenv()
api_key = os.getenv('API_KEY')

  2. Implement Error Handling and Retries

    import time

def call_with_retry(func, max_retries=3):
    for i in range(max_retries):
        try:
            return func()
        except Exception as e:
            if i < max_retries - 1:
                time.sleep(2 ** i)
            else:
                raise

  3. Monitor Usage

    • Regularly check quotas
    • Set usage alerts
    • Log API calls

  4. Optimize Costs

    • Use caching
    • Batch processing
    • Choose appropriate models

📚 Learning Resources

Documentation

  • Each API has detailed documentation
  • Includes quick start guides
  • Provides code examples
  • Best practice guidelines

Code Examples

See complete examples in each API documentation:

  • Basic conversations
  • Streaming output
  • Multimodal input
  • Function calling
  • RAG applications

🔗 Related Resources

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