@bernierllc/ai-provider-anthropic

Anthropic Claude API adapter implementing the unified AI provider interface from @bernierllc/ai-provider-core.

Features

• All Claude 3 Models: Full support for Opus, Sonnet, and Haiku
• Streaming: Async generator-based streaming completions
• Vision Analysis: Image analysis with all Claude 3 models
• Extended Context: Support for 200K token context windows
• Cost Estimation: Accurate cost calculation with model-specific pricing
• TypeScript: Full type safety with strict mode
• Error Handling: Comprehensive error handling with retry support

Installation

npm install @bernierllc/ai-provider-anthropic

Basic Usage

import { AnthropicProvider } from '@bernierllc/ai-provider-anthropic';

const provider = new AnthropicProvider({
  providerName: 'anthropic',
  apiKey: process.env.ANTHROPIC_API_KEY!,
  defaultModel: 'claude-3-opus-20240229'
});

// Generate completion
const response = await provider.complete({
  messages: [
    { role: 'system', content: 'You are a helpful assistant.' },
    { role: 'user', content: 'Explain TypeScript generics in simple terms.' }
  ],
  maxTokens: 500,
  temperature: 0.7
});

if (response.success) {
  console.log(response.content);
  console.log(`Tokens used: ${response.usage?.totalTokens}`);
}

API Reference

Constructor

new AnthropicProvider(config: AnthropicProviderConfig)

Config Options:

• providerName: Must be 'anthropic'
• apiKey: Anthropic API key (required)
• defaultModel: Default model to use (optional, defaults to claude-3-opus-20240229)
• baseURL: Custom API base URL (optional)
• timeout: Request timeout in milliseconds (optional, defaults to 60000)
• maxRetries: Maximum number of retries (optional, defaults to 3)

Methods

complete(request: CompletionRequest): Promise<CompletionResponse>

Generate a text completion.

const response = await provider.complete({
  messages: [
    { role: 'user', content: 'Hello!' }
  ],
  maxTokens: 100,
  temperature: 0.7
});

streamComplete(request: CompletionRequest): AsyncGenerator<StreamChunk>

Generate a streaming text completion.

for await (const chunk of provider.streamComplete({
  messages: [
    { role: 'user', content: 'Write a short poem about coding' }
  ]
})) {
  process.stdout.write(chunk.delta);

  if (chunk.finishReason) {
    console.log(`\n\nFinished: ${chunk.finishReason}`);
  }
}

analyzeImage(imageData, prompt, model?, maxTokens?, temperature?): Promise<CompletionResponse>

Analyze an image using Claude's vision capabilities.

const imageBuffer = fs.readFileSync('diagram.png');

const analysis = await provider.analyzeImage(
  imageBuffer,
  'Describe this architecture diagram in detail',
  'claude-3-opus-20240229'
);

if (analysis.success) {
  console.log(analysis.content);
}

extendedContextCompletion(request): Promise<CompletionResponse>

Process requests with extended context (200K tokens).

const longDocument = fs.readFileSync('very-long-document.txt', 'utf-8');

const response = await provider.extendedContextCompletion({
  messages: [
    { role: 'user', content: `Summarize this document:\n\n${longDocument}` }
  ],
  enableExtendedContext: true
});

estimateCost(request: CompletionRequest): CostEstimate

Estimate the cost of a request before sending it.

const cost = provider.estimateCost({
  messages: [{ role: 'user', content: 'Hello world!' }],
  model: 'claude-3-opus-20240229',
  maxTokens: 100
});

console.log(`Estimated cost: $${cost.estimatedCostUSD.toFixed(4)}`);

getAvailableModels(): Promise<ModelInfo[]>

Get information about all available Claude models.

const models = await provider.getAvailableModels();

models.forEach(model => {
  console.log(`${model.name}: ${model.contextWindow} tokens`);
});

checkHealth(): Promise<HealthStatus>

Check if the Anthropic API is available.

const health = await provider.checkHealth();

if (health.status === 'healthy') {
  console.log(`API is healthy (latency: ${health.latency}ms)`);
}

Available Models

All models support:

• Text completion
• Streaming
• Vision analysis
• Extended context (200K tokens)

Error Handling

The provider returns structured error responses:

const response = await provider.complete({
  messages: [{ role: 'user', content: 'Test' }]
});

if (!response.success) {
  console.error('Error:', response.error);
}

Limitations

Embeddings

Anthropic does not provide an embeddings API. Use @bernierllc/ai-provider-openai for embeddings:

const embeddingResponse = await provider.generateEmbeddings({
  input: 'test text'
});

// Returns: { success: false, error: 'Anthropic does not provide an embeddings API...' }

Content Moderation

Claude has built-in safety features (Constitutional AI), so no separate moderation API is needed:

const moderation = await provider.moderate('content');

// Always returns: { success: true, flagged: false, ... }

Integration Status

• Logger: ✅ Integrated - Uses @bernierllc/logger for error logging
• Docs-Suite: ✅ Ready - Full TypeDoc/JSDoc documentation
• NeverHub: ⚠️ Optional - Can integrate for monitoring and metrics

Advanced Usage

Model Comparison

const models = await provider.getAvailableModels();

models.forEach(model => {
  console.log(`${model.name}:`);
  console.log(`  Context: ${model.contextWindow.toLocaleString()} tokens`);
  console.log(`  Capabilities: ${model.capabilities.join(', ')}`);
  if (model.pricing) {
    console.log(`  Input: $${model.pricing.inputPricePerToken * 1000000}/M tokens`);
    console.log(`  Output: $${model.pricing.outputPricePerToken * 1000000}/M tokens`);
  }
});

Complex Reasoning Task

// Claude excels at complex reasoning and analysis
const response = await provider.complete({
  messages: [
    {
      role: 'user',
      content: `Analyze this code architecture and suggest improvements:

[Large codebase content...]

Consider: scalability, maintainability, security, performance`
    }
  ],
  model: 'claude-3-opus-20240229',
  maxTokens: 4096,
  temperature: 0.3 // Lower temperature for analytical tasks
});

Vision with Multiple Images

// Analyze multiple images in sequence
const images = ['image1.png', 'image2.png', 'image3.png'];

for (const imagePath of images) {
  const imageBuffer = fs.readFileSync(imagePath);

  const analysis = await provider.analyzeImage(
    imageBuffer,
    'What do you see in this image?'
  );

  console.log(`${imagePath}: ${analysis.content}`);
}

TypeScript Types

import type {
  AnthropicProviderConfig,
  AnthropicVisionRequest,
  AnthropicExtendedContextRequest
} from '@bernierllc/ai-provider-anthropic';

import type {
  CompletionRequest,
  CompletionResponse,
  StreamChunk,
  ModelInfo,
  HealthStatus,
  CostEstimate
} from '@bernierllc/ai-provider-core';

License

Copyright (c) 2025 Bernier LLC. All rights reserved.

See Also

• @bernierllc/ai-provider-core - Abstract provider interface
• @bernierllc/ai-provider-openai - OpenAI provider implementation
• @bernierllc/retry-policy - Retry logic used by this package
• @bernierllc/logger - Logging used by this package