How to use LlamaIndex with Claude

pip install anthropic llama-index

import os
from anthropic import Anthropic
from llama_index import GPTVectorStoreIndex, SimpleDirectoryReader, LLMPredictor, PromptHelper

# Initialize Anthropic client
client = Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"])

# Define a wrapper class to adapt Anthropic client to LlamaIndex's LLMPredictor interface
class ClaudeLLM:
    def __init__(self, client, model="claude-3-5-sonnet-20241022", max_tokens=1024):
        self.client = client
        self.model = model
        self.max_tokens = max_tokens

    def __call__(self, prompt: str) -> str:
        response = self.client.messages.create(
            model=self.model,
            max_tokens=self.max_tokens,
            system="You are a helpful assistant.",
            messages=[{"role": "user", "content": prompt}]
        )
        return response.content

# Instantiate the LLM predictor with Claude
llm_predictor = LLMPredictor(llm=ClaudeLLM(client))

# Load documents from a directory (replace 'data' with your folder)
loader = SimpleDirectoryReader('data')
documents = loader.load_data()

# Create the index
index = GPTVectorStoreIndex(documents, llm_predictor=llm_predictor)

# Query the index
query = "What is the main topic of the documents?"
response = index.query(query)
print("Response:", response.response)