import cognee
import os
import asyncio

async def analyze_document():
    # Configure Claude for document analysis
    os.environ["LLM_PROVIDER"] = "anthropic"
    os.environ["LLM_API_KEY"] = "your-anthropic-api-key"
    os.environ["LLM_MODEL"] = "claude-3-5-sonnet-20241022"
    
    # Analyze a research paper
    document = """
    Recent advances in transformer architectures have revolutionized 
    natural language processing. The attention mechanism allows models 
    to focus on relevant parts of the input, leading to better 
    understanding of context and relationships between concepts.
    """
    
    await cognee.add(document)
    await cognee.cognify()
    
    # Get detailed analysis
    analysis = await cognee.search(
        "What are the key innovations in transformer architectures?",
        query_type=SearchType.GRAPH_COMPLETION
    )
    
    print(analysis[0])

asyncio.run(analyze_document())

import cognee
import os
import asyncio

async def process_long_document():
    # Configure for long context processing
    os.environ["LLM_PROVIDER"] = "anthropic"
    os.environ["LLM_MODEL"] = "claude-3-5-sonnet-20241022"
    os.environ["LLM_MAX_TOKENS"] = "8000"
    
    # Process a long document (Claude handles up to 200k tokens)
    with open("long_research_paper.pdf", "r") as f:
        long_content = f.read()
    
    print(f"Processing document with {len(long_content)} characters...")
    
    await cognee.add(long_content)
    await cognee.cognify()
    
    # Get comprehensive insights
    insights = await cognee.search(
        "What are the main themes and conclusions?",
        query_type=SearchType.SUMMARIES
    )
    
    for insight in insights:
        print(f"Theme: {insight}")

asyncio.run(process_long_document())

import cognee
import asyncio
from anthropic import APIError, RateLimitError

async def robust_anthropic():
    try:
        await cognee.add("Your data here")
        await cognee.cognify()
        
        result = await cognee.search("Your query")
        return result
        
    except RateLimitError:
        print("Rate limit hit, waiting before retry...")
        await asyncio.sleep(60)
        return await robust_anthropic()
        
    except APIError as e:
        print(f"Anthropic API error: {e}")
        # Implement fallback logic
        
    except Exception as e:
        print(f"Unexpected error: {e}")

asyncio.run(robust_anthropic())