Quickstart (v0.x)

pip install mem0ai==0.1.20  # Last stable v0.x version

from mem0 import Memory
import os

# Set your OpenAI API key
os.environ["OPENAI_API_KEY"] = "your-api-key"

# Initialize memory
m = Memory()

# Add a simple memory
result = m.add("I love pizza and prefer thin crust", user_id="alice")
print(result)

[
    {
        "id": "mem_123",
        "memory": "User loves pizza and prefers thin crust",
        "event": "ADD"
    }
]

# Search for relevant memories
results = m.search("What food does alice like?", user_id="alice")
print(results)

[
    {
        "id": "mem_123",
        "memory": "User loves pizza and prefers thin crust",
        "score": 0.95,
        "user_id": "alice"
    }
]

# Get all memories for a user
all_memories = m.get_all(user_id="alice")
print(all_memories)

config = {
    "vector_store": {
        "provider": "qdrant",
        "config": {
            "host": "localhost",
            "port": 6333
        }
    },
    "llm": {
        "provider": "openai",
        "config": {
            "model": "gpt-3.5-turbo",
            "api_key": "your-api-key"
        }
    },
    "version": "v1.0"  # Supported in v0.x
}

m = Memory.from_config(config)

# v0.x supports output_format parameter
result = m.add(
    "I love hiking",
    user_id="alice",
    output_format="v1.0"  # Available in v0.x
)

# v0.x supports version configuration
config = {
    "version": "v1.0"  # Explicit version setting
}

# v0.x: Async is optional
result = m.add(
    "memory content",
    user_id="alice",
    async_mode=False  # Synchronous by default
)

result = m.add("I love coffee", user_id="alice", output_format="v1.0")
# Returns: [{"id": "...", "memory": "...", "event": "ADD"}]

result = m.add("I love coffee", user_id="alice", output_format="v1.1")
# Returns: {"results": [{"id": "...", "memory": "...", "event": "ADD"}]}

from mem0 import Memory

m = Memory()

# Learn user preferences
m.add("I prefer morning meetings and dislike late evening calls", user_id="john")
m.add("I'm vegetarian and allergic to nuts", user_id="john")

# Query for personalized responses
schedule_pref = m.search("when does john prefer meetings?", user_id="john")
food_pref = m.search("what food restrictions does john have?", user_id="john")

print("Schedule:", schedule_pref[0]["memory"])
print("Food:", food_pref[0]["memory"])

# Track customer interactions
m.add("Customer reported login issues with Safari browser", user_id="customer_123")
m.add("Resolved login issue by clearing browser cache", user_id="customer_123")

# Later interaction
history = m.search("previous issues", user_id="customer_123")
print("Previous context:", history)