Anthropic LangChain Integration

Modify the API base and add the Helicone-Auth header

const llm = new ChatAnthropic({
  modelName: "claude-2",
  anthropicApiKey: "ANTHROPIC_API_KEY",
  clientOptions: {
    baseURL: "https://anthropic.helicone.ai",
    defaultHeaders: {
      "Helicone-Auth": `Bearer ${HELICONE_API_KEY}`,
    },
  },
});

anthropic = ChatAnthropic(
  temperature=0.9,
  model="claude-2",
  anthropic_api_url="https://anthropic.helicone.ai",
  anthropic_api_key="ANTHROPIC_API_KEY",
  model_kwargs={
    "extra_headers":{
      "Helicone-Auth": f"Bearer {HELICONE_API_KEY}"
    }
  }
)

Using AnthropicMultiModal with Helicone

Enhance your integration by using AnthropicMultiModal with Helicone to process images and generate text descriptions. Follow the code below to add this functionality to your application.

import os
from llama_index.multi_modal_llms.anthropic import AnthropicMultiModal
from llama_index.core.multi_modal_llms.generic_utils import load_image_urls

# Initialize the AnthropicMultiModal class with your Anthropic API key
anthropic_mm_llm = AnthropicMultiModal(
    max_tokens=300,
    default_headers={
        "Helicone-Auth": f"Bearer {os.environ['HELICONE_API_KEY']}",
    },
    api_key="<your Anthropic API key>",
    api_base="https://anthropic.helicone.ai",
)

# Provide image URLs
image_urls = ["https://example.com/image1.png"]

# Load image URLs into documents
image_url_documents = load_image_urls(image_urls)

# Generate a response based on the images
response = anthropic_mm_llm.complete(
    prompt="Describe the images as alternative text",
    image_documents=image_url_documents,
)

print(response)

Getting Started

AI Gateway

Observability & Analytics

Prompt Management

Legacy Integrations

References

Using AnthropicMultiModal with Helicone

​Using AnthropicMultiModal with Helicone

Using AnthropicMultiModal with Helicone