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Overview

The Anthropic provider gives you access to Claude models with advanced reasoning capabilities through adaptive and manual thinking modes.

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Installation

npm install @core-ai/anthropic

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createAnthropic()

Create an Anthropic provider instance. 
import { createAnthropic } from '@core-ai/anthropic';

const anthropic = createAnthropic({
  apiKey: process.env.ANTHROPIC_API_KEY,
  defaultMaxTokens: 4096 // optional
});

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Options

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apiKey
string
Your Anthropic API key. Defaults to ANTHROPIC_API_KEY environment variable.
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baseURL
string
Custom base URL for API requests. Useful for proxies or custom endpoints.
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defaultMaxTokens
number
default:"4096"
Default maximum tokens for completions. Can be overridden per request.
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client
Anthropic
Provide your own configured Anthropic client instance.

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Returns

AnthropicProvider - Provider instance with methods to create models.

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Provider Methods

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chatModel()

Create a chat model instance. 
const model = anthropic.chatModel('claude-opus-4-6');
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modelId
string
required
Model identifier. See Supported Models below.

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Supported Models

Latest generation with adaptive thinking mode.
  • claude-opus-4-6 - Most capable, supports max effort
  • claude-sonnet-4-6 - Balanced performance and speed
Previous generation with manual thinking budget control.
  • claude-opus-4-5 - High capability
  • claude-sonnet-4-5 - Efficient reasoning
  • claude-haiku-4-5 - Fast and lightweight
Earlier Claude models with manual thinking.
  • claude-opus-4-1 - Enhanced reasoning
  • claude-opus-4 - Strong performance
  • claude-sonnet-4 - Balanced model
  • claude-sonnet-3-7 - Previous generation

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Capabilities

FeatureSupport
Chat Completion✓
Streaming✓
Function Calling✓
Vision✓
Reasoning Effort✓
Embeddings✗
Image Generation✗

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Thinking Modes

Claude models use two different thinking modes:

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Adaptive Thinking

Used by Claude 4.6 models. The model automatically determines thinking depth based on the effort level. 
const result = await generateText({
  model: anthropic.chatModel('claude-opus-4-6'),
  prompt: 'Solve this complex problem...',
  reasoning: {
    effort: 'high' // 'low' | 'medium' | 'high' | 'max'
  }
});
Only claude-opus-4-6 supports 'max' effort level.

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Manual Thinking Budget

Used by Claude 4.5 and earlier. You control the thinking token budget:
  • minimal → 1,024 tokens
  • low → 2,048 tokens
  • medium → 8,192 tokens
  • high → 32,768 tokens
  • max → 65,536 tokens
const result = await generateText({
  model: anthropic.chatModel('claude-opus-4-5'),
  prompt: 'Complex reasoning task...',
  reasoning: {
    effort: 'high' // Allocates 32,768 thinking tokens
  }
});

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Examples

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Basic Chat

import { createAnthropic } from '@core-ai/anthropic';
import { generateText } from '@core-ai/core-ai';

const anthropic = createAnthropic({
  apiKey: process.env.ANTHROPIC_API_KEY
});

const result = await generateText({
  model: anthropic.chatModel('claude-opus-4-6'),
  prompt: 'Explain the theory of relativity'
});

console.log(result.text);

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Extended Thinking

const result = await generateText({
  model: anthropic.chatModel('claude-opus-4-6'),
  prompt: `
    Analyze this complex dataset and provide insights:
    [Large dataset here]
  `,
  reasoning: {
    effort: 'max' // Maximum reasoning effort
  },
  maxTokens: 8192
});

// Access thinking process if available
if (result.reasoning) {
  console.log('Thinking tokens:', result.reasoning.thinkingTokens);
}

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Streaming with Thinking

import { streamText } from '@core-ai/core-ai';

const stream = await streamText({
  model: anthropic.chatModel('claude-sonnet-4-6'),
  prompt: 'Write a detailed analysis of...',
  reasoning: {
    effort: 'high'
  }
});

for await (const chunk of stream) {
  if (chunk.type === 'thinking') {
    console.log('Thinking:', chunk.text);
  } else if (chunk.type === 'text') {
    console.log('Output:', chunk.text);
  }
}

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Function Calling

import { generateText, tool } from '@core-ai/core-ai';
import { z } from 'zod';

const result = await generateText({
  model: anthropic.chatModel('claude-opus-4-6'),
  prompt: 'What is the weather in San Francisco?',
  tools: {
    getWeather: tool({
      description: 'Get weather for a location',
      parameters: z.object({
        location: z.string()
      }),
      execute: async ({ location }) => {
        return { temp: 72, condition: 'sunny' };
      }
    })
  }
});

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Vision

const result = await generateText({
  model: anthropic.chatModel('claude-opus-4-6'),
  messages: [
    {
      role: 'user',
      content: [
        { type: 'text', text: 'What is in this image?' },
        {
          type: 'image',
          image: 'https://example.com/image.jpg'
        }
      ]
    }
  ]
});

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Custom Max Tokens

const anthropic = createAnthropic({
  apiKey: process.env.ANTHROPIC_API_KEY,
  defaultMaxTokens: 8192 // Higher default for all requests
});

// Or override per request
const result = await generateText({
  model: anthropic.chatModel('claude-opus-4-6'),
  prompt: 'Long response...',
  maxTokens: 16000
});

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Error Handling

import { APIError } from '@core-ai/core-ai';

try {
  const result = await generateText({
    model: anthropic.chatModel('claude-opus-4-6'),
    prompt: 'Hello!'
  });
} catch (error) {
  if (error instanceof APIError) {
    console.error('Anthropic API error:', error.message);
    console.error('Status:', error.statusCode);
  }
}

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Best Practices

  • Use Claude 4.6 (adaptive) for most use cases - it’s more efficient
  • Use Claude 4.5 (manual) when you need precise control over thinking budget
  • low - Simple questions, quick responses
  • medium - Standard reasoning tasks
  • high - Complex analysis, multi-step reasoning
  • max - Most challenging problems (Opus 4-6 only)
  • Set defaultMaxTokens based on your typical use case
  • Remember thinking tokens count toward your usage
  • Use streaming to show progress for long responses

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