Anthropic Integration

import os
from graphiti_core import Graphiti
from graphiti_core.llm_client.anthropic_client import AnthropicClient
from graphiti_core.llm_client.config import LLMConfig

# Create Anthropic LLM client
llm_client = AnthropicClient(
    config=LLMConfig(
        api_key=os.environ["ANTHROPIC_API_KEY"],
        model="claude-haiku-4-5-latest",
        temperature=0.7,
        max_tokens=8192
    )
)

# Initialize Graphiti
graphiti = Graphiti(
    "bolt://localhost:7687",
    "neo4j",
    "password",
    llm_client=llm_client
)

llm_client = AnthropicClient(
    config=LLMConfig(
        model="claude-sonnet-4-5-latest",        # Primary model
        small_model="claude-haiku-4-5-latest",   # Small model
    )
)

# Graphiti automatically:
# 1. Defines a tool with your Pydantic schema
# 2. Forces tool use via tool_choice
# 3. Extracts structured data from tool arguments
# 4. Falls back to JSON extraction if needed

import asyncio
import os
from datetime import datetime, timezone
from graphiti_core import Graphiti
from graphiti_core.llm_client.anthropic_client import AnthropicClient
from graphiti_core.llm_client.config import LLMConfig
from graphiti_core.nodes import EpisodeType

async def main():
    # Configure Anthropic LLM
    llm_client = AnthropicClient(
        config=LLMConfig(
            api_key=os.environ["ANTHROPIC_API_KEY"],
            model="claude-haiku-4-5-latest",
            temperature=0.7
        ),
        max_tokens=16384  # Override default
    )
    
    # Initialize Graphiti
    graphiti = Graphiti(
        "bolt://localhost:7687",
        "neo4j",
        "password",
        llm_client=llm_client
    )
    
    try:
        # Add an episode
        await graphiti.add_episode(
            name="AI Research 1",
            episode_body="Anthropic released Claude 4.5, featuring extended context and reasoning.",
            source=EpisodeType.text,
            reference_time=datetime.now(timezone.utc)
        )
        
        # Search the graph
        results = await graphiti.search("What are Claude 4.5's capabilities?")
        for result in results:
            print(f"Fact: {result.fact}")
    
    finally:
        await graphiti.close()

if __name__ == "__main__":
    asyncio.run(main())

# Token usage is logged automatically
# Check your application logs for:
# - Input tokens
# - Output tokens
# - Total token usage per prompt