Migrating from v0.x to v1.0.0

# Update to the latest version
pip install --upgrade mem0ai

from mem0 import Memory

# These parameters are no longer supported
m = Memory()
result = m.add(
    "I love pizza",
    user_id="alice",
    version="v1.0"         # ❌ REMOVED
)

from mem0 import Memory

# Clean, simplified API
m = Memory()
result = m.add(
    "I love pizza",
    user_id="alice"
    # version parameter removed
)

config = {
    "vector_store": {
        "provider": "qdrant",
        "config": {
            "host": "localhost",
            "port": 6333
        }
    },
    "version": "v1.0"  # ❌ No longer supported
}

m = Memory.from_config(config)

config = {
    "vector_store": {
        "provider": "qdrant",
        "config": {
            "host": "localhost",
            "port": 6333
        }
    },
    "version": "v1.1"  # ✅ v1.1 is the minimum supported version
}

m = Memory.from_config(config)

# Response could be a list or dict depending on version
result = m.add("I love coffee", user_id="alice")

if isinstance(result, list):
    # Handle list format
    for item in result:
        print(item["memory"])
else:
    # Handle dict format
    print(result["results"])

# Response is always a standardized dict with "results" key
result = m.add("I love coffee", user_id="alice")

# Always access via "results" key
for item in result["results"]:
    print(item["memory"])

# Basic search
results = m.search("What do I like?", user_id="alice")

# With filters
results = m.search(
    "What do I like?",
    user_id="alice",
    filters={"category": "food"}
)

# Same basic search API
results = m.search("What do I like?", user_id="alice")

# Enhanced filtering with operators (optional upgrade)
results = m.search(
    "What do I like?",
    user_id="alice",
    filters={
        "AND": [
            {"category": "food"},
            {"rating": {"gte": 8}}
        ]
    }
)

# New: Reranking support (optional)
results = m.search(
    "What do I like?",
    user_id="alice",
    rerank=True  # Requires reranker configuration
)

from mem0 import MemoryClient

client = MemoryClient(api_key="your-key")

# Had to explicitly set async_mode
result = client.add("I enjoy hiking", user_id="alice", async_mode=True)

from mem0 import MemoryClient

client = MemoryClient(api_key="your-key")

# async_mode now defaults to True (best performance)
result = client.add("I enjoy hiking", user_id="alice")

# You can still override if needed for synchronous processing
result = client.add("I enjoy hiking", user_id="alice", async_mode=False)

config = {
    "vector_store": {
        "provider": "qdrant",
        "config": {
            "host": "localhost",
            "port": 6333
        }
    },
    "llm": {
        "provider": "openai",
        "config": {
            "model": "gpt-3.5-turbo",
            "api_key": "your-key"
        }
    },
    "version": "v1.0"
}

config = {
    "vector_store": {
        "provider": "qdrant",
        "config": {
            "host": "localhost",
            "port": 6333
        }
    },
    "llm": {
        "provider": "openai",
        "config": {
            "model": "gpt-3.5-turbo",
            "api_key": "your-key"
        }
    },
    "version": "v1.1",  # Minimum supported version

    # New optional features
    "reranker": {
        "provider": "cohere",
        "config": {
            "model": "rerank-english-v3.0",
            "api_key": "your-cohere-key"
        }
    }
}

# Take advantage of new features
config = {
    "vector_store": {
        "provider": "qdrant",
        "config": {
            "host": "localhost",
            "port": 6333
        }
    },
    "llm": {
        "provider": "openai",
        "config": {
            "model": "gpt-4",
            "api_key": "your-key"
        }
    },
    "embedder": {
        "provider": "openai",
        "config": {
            "model": "text-embedding-3-small",
            "api_key": "your-key"
        }
    },
    "reranker": {
        "provider": "sentence_transformer",
        "config": {
            "model": "cross-encoder/ms-marco-MiniLM-L-6-v2"
        }
    },
    "version": "v1.1"
}

try:
    result = m.add("memory", user_id="alice", version="v1.0")
except Exception as e:
    print(f"Error: {e}")

try:
    result = m.add("memory", user_id="alice")
except ValueError as e:
    if "v1.0 API format is no longer supported" in str(e):
        print("Please upgrade your code to use v1.1+ format")
    else:
        print(f"Error: {e}")
except Exception as e:
    print(f"Unexpected error: {e}")

def test_basic_functionality():
    m = Memory()

    # Test add
    result = m.add("I love testing", user_id="test_user")
    assert "results" in result
    assert len(result["results"]) > 0

    # Test search
    search_results = m.search("testing", user_id="test_user")
    assert "results" in search_results

    # Test get_all
    all_memories = m.get_all(user_id="test_user")
    assert "results" in all_memories

    print("✅ Basic functionality test passed")

test_basic_functionality()

def test_enhanced_features():
    config = {
        "reranker": {
            "provider": "sentence_transformer",
            "config": {
                "model": "cross-encoder/ms-marco-MiniLM-L-6-v2"
            }
        }
    }

    m = Memory.from_config(config)

    # Test reranking
    m.add("I love advanced features", user_id="test_user")
    results = m.search("features", user_id="test_user", rerank=True)
    assert "results" in results

    # Test enhanced filtering
    results = m.search(
        "features",
        user_id="test_user",
        filters={"user_id": {"eq": "test_user"}}
    )
    assert "results" in results

    print("✅ Enhanced features test passed")

test_enhanced_features()

ValueError: The v1.0 API format is no longer supported in mem0ai 1.0.0+

# Remove version parameters or set to v1.1+
config = {
    # ... other config
    "version": "v1.1"  # or remove entirely for default
}

KeyError: 'results'

# Always access response via "results" key
result = m.add("memory", user_id="alice")
memories = result["results"]  # Not result directly

TypeError: add() got an unexpected keyword argument 'output_format'

# Remove deprecated parameters
result = m.add(
    "memory",
    user_id="alice"
    # Remove: version
)

# Downgrade to last v0.x version
pip install mem0ai==0.1.20  # Replace with your last working version

# Test both versions side by side
import mem0_v0  # Your old version
import mem0     # New version

def compare_results(query, user_id):
    old_results = mem0_v0.search(query, user_id=user_id)
    new_results = mem0.search(query, user_id=user_id)

    print("Old format:", old_results)
    print("New format:", new_results["results"])

# Sequential operations
result1 = m.add("memory 1", user_id="alice")
result2 = m.add("memory 2", user_id="alice")
result3 = m.search("query", user_id="alice")

# Better async performance
async def batch_operations():
    async_memory = AsyncMemory()

    # Concurrent operations
    results = await asyncio.gather(
        async_memory.add("memory 1", user_id="alice"),
        async_memory.add("memory 2", user_id="alice"),
        async_memory.search("query", user_id="alice")
    )
    return results