Anthropic SDK

The Anthropic SDK provides official Python and TypeScript clients for interacting with Claude models. Edgee’s OpenAI-compatible API works seamlessly with the Anthropic SDK, allowing you to leverage the SDK’s features while gaining access to Edgee’s up to 50% cost reduction through token compression, unified gateway, automatic failover, and full observability.

Installation

Python
TypeScript

pip install anthropic

npm install @anthropic-ai/sdk

Basic Usage

Python
TypeScript

import os
from anthropic import Anthropic

# Initialize client with Edgee endpoint
client = Anthropic(
    base_url="https://api.edgee.ai",
    api_key=os.environ.get("EDGEE_API_KEY"),
)

# Send a message
message = client.messages.create(
    model="claude-sonnet-4.5",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "What is the capital of France?"}
    ]
)

print(message.content)

# Access token usage
print(f"Input tokens: {message.usage.input_tokens}")
print(f"Output tokens: {message.usage.output_tokens}")

import Anthropic from '@anthropic-ai/sdk';

// Initialize client with Edgee endpoint
const client = new Anthropic({
  baseURL: 'https://api.edgee.ai',
  apiKey: process.env.EDGEE_API_KEY,
});

// Send a message
const message = await client.messages.create({
  model: 'claude-sonnet-4.5',
  max_tokens: 1024,
  messages: [
    { role: 'user', content: 'What is the capital of France?' }
  ]
});

console.log(message.content);

// Access token usage
console.log(`Input tokens: ${message.usage.input_tokens}`);
console.log(`Output tokens: ${message.usage.output_tokens}`);

Streaming Responses

Stream responses for real-time token delivery:

Python
TypeScript

from anthropic import Anthropic

client = Anthropic(
    base_url="https://api.edgee.ai",
    api_key=os.environ.get("EDGEE_API_KEY"),
)

# Stream messages
with client.messages.stream(
    model="claude-sonnet-4.5",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Write a short poem about coding"}
    ]
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  baseURL: 'https://api.edgee.ai',
  apiKey: process.env.EDGEE_API_KEY,
});

// Stream messages
const stream = await client.messages.create({
  model: 'claude-sonnet-4.5',
  max_tokens: 1024,
  messages: [
    { role: 'user', content: 'Write a short poem about coding' }
  ],
  stream: true,
});

for await (const event of stream) {
  if (event.type === 'content_block_delta'
      && event.delta.type === 'text_delta') {
    process.stdout.write(event.delta.text);
  }
}

Token Usage Tracking

Access standard Anthropic token usage metrics in every response:

Python
TypeScript

from anthropic import Anthropic

client = Anthropic(
    base_url="https://api.edgee.ai",
    api_key=os.environ.get("EDGEE_API_KEY"),
)

message = client.messages.create(
    model="claude-sonnet-4.5",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Analyze this long document..."}]
)

print(message.content)
print(f"Input tokens: {message.usage.input_tokens}")
print(f"Output tokens: {message.usage.output_tokens}")

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  baseURL: 'https://api.edgee.ai',
  apiKey: process.env.EDGEE_API_KEY,
});

const message = await client.messages.create({
  model: 'claude-sonnet-4.5',
  max_tokens: 1024,
  messages: [{ role: 'user', content: 'Analyze this long document...' }]
});

console.log(message.content);
console.log(`Input tokens: ${message.usage.input_tokens}`);
console.log(`Output tokens: ${message.usage.output_tokens}`);

When compression is enabled, input_tokens reflects the compressed token count. View detailed compression metrics in the Edgee dashboard.

Compression & Tags via Headers

When using the Anthropic SDK with Edgee, you can control token compression and add tags using HTTP headers:

Enabling Compression

Python
TypeScript

from anthropic import Anthropic

client = Anthropic(
    base_url="https://api.edgee.ai",
    api_key=os.environ.get("EDGEE_API_KEY"),
    default_headers={
        "x-edgee-enable-compression": "true",
        "x-edgee-compression-rate": "0.8",  # Target 80% compression (0.0-1.0)
    }
)

# All requests will use compression with 80% target rate
message = client.messages.create(
    model="claude-sonnet-4.5",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Analyze this document..."}]
)

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  baseURL: 'https://api.edgee.ai',
  apiKey: process.env.EDGEE_API_KEY,
  defaultHeaders: {
    'x-edgee-enable-compression': 'true',
    'x-edgee-compression-rate': '0.8',  // Target 80% compression (0.0-1.0)
  }
});

// All requests will use compression
const message = await client.messages.create({
  model: 'claude-sonnet-4.5',
  max_tokens: 1024,
  messages: [{ role: 'user', content: 'Analyze this document...' }]
});

Adding Tags for Analytics

Combine compression with tags to track requests in your dashboard:

Python
TypeScript

from anthropic import Anthropic

client = Anthropic(
    base_url="https://api.edgee.ai",
    api_key=os.environ.get("EDGEE_API_KEY"),
    default_headers={
        "x-edgee-enable-compression": "true",
        "x-edgee-compression-rate": "0.8",
        "x-edgee-tags": "production,anthropic-sdk,user-123"
    }
)

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  baseURL: 'https://api.edgee.ai',
  apiKey: process.env.EDGEE_API_KEY,
  defaultHeaders: {
    'x-edgee-enable-compression': 'true',
    'x-edgee-compression-rate': '0.8',
    'x-edgee-tags': 'production,anthropic-sdk,user-123'
  }
});

Available Headers:

Header	Type	Description
`x-edgee-enable-compression`	`"true"` or `"false"`	Enable token compression for requests (overrides console settings)
`x-edgee-compression-rate`	`string`	Target compression rate (0.0-1.0, default 0.75)
`x-edgee-tags`	`string`	Comma-separated tags for analytics and filtering

You can also enable compression organization-wide or per API key in the Edgee console. Headers override console settings for specific requests.

Multi-Provider Access

With Edgee, you can access models from multiple providers using the same Anthropic SDK client and compare costs across providers:

Python
TypeScript

from anthropic import Anthropic

client = Anthropic(
    base_url="https://api.edgee.ai",
    api_key=os.environ.get("EDGEE_API_KEY"),
)

# Use Claude
claude_response = client.messages.create(
    model="claude-sonnet-4.5",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello!"}]
)

# Use GPT-4 through the same client
gpt_response = client.messages.create(
    model="gpt-4o",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello!"}]
)

# Use Mistral
mistral_response = client.messages.create(
    model="mistral-large",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello!"}]
)

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  baseURL: 'https://api.edgee.ai/',
  apiKey: process.env.EDGEE_API_KEY,
});

// Use Claude
const claudeResponse = await client.messages.create({
  model: 'claude-sonnet-4.5',
  max_tokens: 1024,
  messages: [{ role: 'user', content: 'Hello!' }]
});

// Use GPT-4 through the same client
const gptResponse = await client.messages.create({
  model: 'gpt-4o',
  max_tokens: 1024,
  messages: [{ role: 'user', content: 'Hello!' }]
});

// Use Mistral
const mistralResponse = await client.messages.create({
  model: 'mistral-large',
  max_tokens: 1024,
  messages: [{ role: 'user', content: 'Hello!' }]
});

Function Calling (Tools)

Use Claude’s tool calling with Edgee:

Python
TypeScript

from anthropic import Anthropic

client = Anthropic(
    base_url="https://api.edgee.ai",
    api_key=os.environ.get("EDGEE_API_KEY"),
)

# Define a tool
tools = [
    {
        "name": "get_weather",
        "description": "Get the current weather in a given location",
        "input_schema": {
            "type": "object",
            "properties": {
                "location": {
                    "type": "string",
                    "description": "The city and state, e.g. San Francisco, CA"
                }
            },
            "required": ["location"]
        }
    }
]

# Send message with tools
message = client.messages.create(
    model="claude-sonnet-4.5",
    max_tokens=1024,
    tools=tools,
    messages=[
        {"role": "user", "content": "What's the weather like in Paris?"}
    ]
)

print(message.content)

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  baseURL: 'https://api.edgee.ai',
  apiKey: process.env.EDGEE_API_KEY,
});

// Define a tool
const tools = [
  {
    name: 'get_weather',
    description: 'Get the current weather in a given location',
    input_schema: {
      type: 'object',
      properties: {
        location: {
          type: 'string',
          description: 'The city and state, e.g. San Francisco, CA'
        }
      },
      required: ['location']
    }
  }
];

// Send message with tools
const message = await client.messages.create({
  model: 'claude-sonnet-4.5',
  max_tokens: 1024,
  tools: tools,
  messages: [
    { role: 'user', content: "What's the weather like in Paris?" }
  ]
});

console.log(message.content);

Error Handling and Retries

The Anthropic SDK includes built-in retry logic, which works seamlessly with Edgee’s automatic failover:

Python
TypeScript

from anthropic import Anthropic, APIError

client = Anthropic(
    base_url="https://api.edgee.ai",
    api_key=os.environ.get("EDGEE_API_KEY"),
    max_retries=3,  # SDK will retry up to 3 times
)

try:
    message = client.messages.create(
        model="claude-sonnet-4.5",
        max_tokens=1024,
        messages=[{"role": "user", "content": "Hello!"}]
    )
    print(message.content)
except APIError as e:
    print(f"API Error: {e}")

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  baseURL: 'https://api.edgee.ai',
  apiKey: process.env.EDGEE_API_KEY,
  maxRetries: 3,  // SDK will retry up to 3 times
});

try {
  const message = await client.messages.create({
    model: 'claude-sonnet-4.5',
    max_tokens: 1024,
    messages: [{ role: 'user', content: 'Hello!' }]
  });
  console.log(message.content);
} catch (error) {
  console.error('API Error:', error);
}

Authentication

Edgee uses standard Bearer token authentication. Set your API key as an environment variable:

export EDGEE_API_KEY="sk-edgee-..."

Or in your .env file:

EDGEE_API_KEY=sk-edgee-...

The SDK automatically formats the authentication header as:

Authorization: Bearer {api_key}

Benefits of Using Anthropic SDK with Edgee

Up to 50% Cost Reduction

Automatic token compression on every request reduces input tokens by up to 50% while preserving output quality.

Multi-Provider Cost Comparison

Compare costs across Claude, GPT-4, Mistral, and 200+ models. Track compression savings per provider.

Automatic Failover

If Claude is rate-limited or unavailable, Edgee automatically routes to backup models without code changes.

Full Observability

Monitor latency, token usage, compression ratios, error rates, and costs for all requests in one dashboard.

Complete Example

Here’s a complete application example:

Python
TypeScript

#!/usr/bin/env python3
import os
from anthropic import Anthropic

def main():
    # Initialize client
    client = Anthropic(
        base_url="https://api.edgee.ai",
        api_key=os.environ.get("EDGEE_API_KEY"),
        default_headers={
            "x-edgee-tags": "production,chat-app"
        }
    )

    # Chat loop
    conversation = []
    print("Chat with Claude (type 'quit' to exit)")

    while True:
        user_input = input("\nYou: ")
        if user_input.lower() == 'quit':
            break

        conversation.append({
            "role": "user",
            "content": user_input
        })

        # Stream response
        print("\nClaude: ", end="", flush=True)
        with client.messages.stream(
            model="claude-sonnet-4.5",
            max_tokens=1024,
            messages=conversation
        ) as stream:
            assistant_message = ""
            for text in stream.text_stream:
                print(text, end="", flush=True)
                assistant_message += text

        conversation.append({
            "role": "assistant",
            "content": assistant_message
        })

if __name__ == "__main__":
    main()

import Anthropic from '@anthropic-ai/sdk';
import * as readline from 'readline';

async function main() {
  // Initialize client
  const client = new Anthropic({
    baseURL: 'https://api.edgee.ai',
    apiKey: process.env.EDGEE_API_KEY,
    defaultHeaders: {
      'x-edgee-tags': 'production,chat-app'
    }
  });

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout
  });

  const conversation: Array<{ role: string; content: string }> = [];

  console.log("Chat with Claude (type 'quit' to exit)");

  const chat = () => {
    rl.question('\nYou: ', async (input) => {
      if (input.toLowerCase() === 'quit') {
        rl.close();
        return;
      }

      conversation.push({
        role: 'user',
        content: input
      });

      process.stdout.write('\nClaude: ');

      const stream = await client.messages.create({
        model: 'claude-sonnet-4.5',
        max_tokens: 1024,
        messages: conversation,
        stream: true,
      });

      let assistantMessage = '';
      for await (const event of stream) {
        if (event.type === 'content_block_delta'
            && event.delta.type === 'text_delta') {
          process.stdout.write(event.delta.text);
          assistantMessage += event.delta.text;
        }
      }

      conversation.push({
        role: 'assistant',
        content: assistantMessage
      });

      chat();
    });
  };

  chat();
}

main();

Next Steps

Explore Anthropic SDK documentation for advanced features
Check out Edgee’s routing capabilities for intelligent model selection
Set up observability to monitor your applications
Configure privacy controls to manage data retention

Introduction

Quickstart

Features

Integrations

Installation

Basic Usage

Streaming Responses

Token Usage Tracking

Compression & Tags via Headers

Enabling Compression

Adding Tags for Analytics

Multi-Provider Access

Function Calling (Tools)

Error Handling and Retries

Authentication

Benefits of Using Anthropic SDK with Edgee

Up to 50% Cost Reduction

Multi-Provider Cost Comparison

Automatic Failover

Full Observability

Complete Example

Next Steps

Introduction

Quickstart

Features

Integrations

​Installation

​Basic Usage

​Streaming Responses

​Token Usage Tracking

​Compression & Tags via Headers

​Enabling Compression

​Adding Tags for Analytics

​Multi-Provider Access

​Function Calling (Tools)

​Error Handling and Retries

​Authentication

​Benefits of Using Anthropic SDK with Edgee

Up to 50% Cost Reduction

Multi-Provider Cost Comparison

Automatic Failover

Full Observability

​Complete Example

​Next Steps

Installation

Basic Usage

Streaming Responses

Token Usage Tracking

Compression & Tags via Headers

Enabling Compression

Adding Tags for Analytics

Multi-Provider Access

Function Calling (Tools)

Error Handling and Retries

Authentication

Benefits of Using Anthropic SDK with Edgee

Complete Example

Next Steps