​
AsyncMemory

The AsyncMemory class is a direct asynchronous interface to Zentry’s in-process memory operations. Unlike the memory, which interacts with an API, AsyncMemory works directly with the underlying storage systems. This makes it ideal for applications where you want to embed Zentry directly into your codebase.

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Initialization

To use AsyncMemory, import it from the zentry.memory module:
Python
import asyncio
from zentry import AsyncMemory

# Initialize with default configuration
memory = AsyncMemory()

# Or initialize with custom configuration
from zentry.configs.base import MemoryConfig
custom_config = MemoryConfig(
    # Your custom configuration here
)
memory = AsyncMemory(config=custom_config)

​
Key Features

  1. Non-blocking Operations - All memory operations use asyncio to avoid blocking the event loop
  2. Concurrent Processing - Parallel execution of vector store and graph operations
  3. Efficient Resource Utilization - Better handling of I/O bound operations
  4. Compatible with Async Frameworks - Seamless integration with FastAPI, aiohttp, and other async frameworks

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Methods

All methods in AsyncMemory have the same parameters as the synchronous Memory class but are designed to be used with async/await.

​
Create memories

Add a new memory asynchronously:
Python
await memory.add(
    messages=[
        {"role": "user", "content": "I'm travelling to SF"},
        {"role": "assistant", "content": "That's great to hear!"}
    ],
    user_id="alice"
)

​
Retrieve memories

Retrieve memories related to a query:
Python
await memory.search(
    query="Where am I travelling?",
    user_id="alice"
)

​
List memories

List all memories for a user_id, agent_id, or run_id:
Python
await memory.get_all(user_id="alice")

​
Get specific memory

Retrieve a specific memory by its ID:
Python
await memory.get(memory_id="memory-id-here")

​
Update memory

Update an existing memory by ID:
Python
await memory.update(
    memory_id="memory-id-here",
    data="I'm travelling to Seattle"
)

​
Delete memory

Delete a specific memory by ID:
Python
await memory.delete(memory_id="memory-id-here")

​
Delete all memories

Delete all memories for a specific user, agent, or run:
Python
await memory.delete_all(user_id="alice")
Note: At least one filter (user_id, agent_id, or run_id) is required when using delete_all.

​
Memory History

Get the history of changes for a specific memory:
Python
await memory.history(memory_id="memory-id-here")

​
Example: Concurrent Usage with Other APIs

AsyncMemory can be effectively combined with other async operations. Here’s an example showing how to use it alongside OpenAI API calls in separate threads:
Python
import asyncio
from openai import AsyncOpenAI
from zentry import AsyncMemory

async_openai_client = AsyncOpenAI()
async_memory = AsyncMemory()

async def chat_with_memories(message: str, user_id: str = "default_user") -> str:
    # Retrieve relevant memories
    search_result = await async_memory.search(query=message, user_id=user_id, limit=3)
    relevant_memories = search_result["results"]
    memories_str = "\n".join(f"- {entry['memory']}" for entry in relevant_memories)
    
    # Generate Assistant response
    system_prompt = f"You are a helpful AI. Answer the question based on query and memories.\nUser Memories:\n{memories_str}"
    messages = [{"role": "system", "content": system_prompt}, {"role": "user", "content": message}]
    response = await async_openai_client.chat.completions.create(model="gpt-4o-mini", messages=messages)
    assistant_response = response.choices[0].message.content

    # Create new memories from the conversation
    messages.append({"role": "assistant", "content": assistant_response})
    await async_memory.add(messages, user_id=user_id)

    return assistant_response

async def async_main():
    print("Chat with AI (type 'exit' to quit)")
    while True:
        user_input = input("You: ").strip()
        if user_input.lower() == 'exit':
            print("Goodbye!")
            break
        response = await chat_with_memories(user_input)
        print(f"AI: {response}")

def main():
    asyncio.run(async_main())

if __name__ == "__main__":
    main()
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