Add async support (#2492)
Co-authored-by: Deshraj Yadav <deshrajdry@gmail.com>
This commit is contained in:
@@ -73,6 +73,7 @@
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"group": "Features",
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"icon": "wrench",
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"pages": [
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"open-source/features/async-memory",
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"features/openai_compatibility",
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"features/custom-fact-extraction-prompt",
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"features/custom-update-memory-prompt",
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169
docs/open-source/features/async-memory.mdx
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169
docs/open-source/features/async-memory.mdx
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@@ -0,0 +1,169 @@
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---
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title: Async Memory
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description: 'Asynchronous memory for Mem0'
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icon: "bolt"
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iconType: "solid"
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---
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## AsyncMemory
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The `AsyncMemory` class is a direct asynchronous interface to Mem0'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 Mem0 directly into your codebase.
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### Initialization
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To use `AsyncMemory`, import it from the `mem0.memory` module:
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```python Python
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import asyncio
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from mem0 import AsyncMemory
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# Initialize with default configuration
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memory = AsyncMemory()
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# Or initialize with custom configuration
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from mem0.configs.base import MemoryConfig
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custom_config = MemoryConfig(
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# Your custom configuration here
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)
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memory = AsyncMemory(config=custom_config)
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```
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### Key Features
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1. **Non-blocking Operations** - All memory operations use `asyncio` to avoid blocking the event loop
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2. **Concurrent Processing** - Parallel execution of vector store and graph operations
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3. **Efficient Resource Utilization** - Better handling of I/O bound operations
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4. **Compatible with Async Frameworks** - Seamless integration with FastAPI, aiohttp, and other async frameworks
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### Methods
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All methods in `AsyncMemory` have the same parameters as the synchronous `Memory` class but are designed to be used with `async/await`.
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#### Create memories
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Add a new memory asynchronously:
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```python Python
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await memory.add(
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messages=[
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{"role": "user", "content": "I'm travelling to SF"},
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{"role": "assistant", "content": "That's great to hear!"}
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],
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user_id="alice"
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)
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```
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#### Retrieve memories
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Retrieve memories related to a query:
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```python Python
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await memory.search(
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query="Where am I travelling?",
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user_id="alice"
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)
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```
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#### List memories
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List all memories for a `user_id`, `agent_id`, or `run_id`:
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```python Python
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await memory.get_all(user_id="alice")
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```
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#### Get specific memory
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Retrieve a specific memory by its ID:
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```python Python
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await memory.get(memory_id="memory-id-here")
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```
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#### Update memory
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Update an existing memory by ID:
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```python Python
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await memory.update(
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memory_id="memory-id-here",
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data="I'm travelling to Seattle"
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)
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```
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#### Delete memory
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Delete a specific memory by ID:
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```python Python
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await memory.delete(memory_id="memory-id-here")
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```
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#### Delete all memories
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Delete all memories for a specific user, agent, or run:
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```python Python
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await memory.delete_all(user_id="alice")
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```
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Note: At least one filter (user_id, agent_id, or run_id) is required when using delete_all.
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#### Memory History
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Get the history of changes for a specific memory:
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```python Python
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await memory.history(memory_id="memory-id-here")
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```
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### Example: Concurrent Usage with Other APIs
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`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:
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```python Python
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import asyncio
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from openai import AsyncOpenAI
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from mem0 import AsyncMemory
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async_openai_client = AsyncOpenAI()
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async_memory = AsyncMemory()
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async def chat_with_memories(message: str, user_id: str = "default_user") -> str:
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# Retrieve relevant memories
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search_result = await async_memory.search(query=message, user_id=user_id, limit=3)
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relevant_memories = search_result["results"]
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memories_str = "\n".join(f"- {entry['memory']}" for entry in relevant_memories)
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# Generate Assistant response
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system_prompt = f"You are a helpful AI. Answer the question based on query and memories.\nUser Memories:\n{memories_str}"
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messages = [{"role": "system", "content": system_prompt}, {"role": "user", "content": message}]
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response = await async_openai_client.chat.completions.create(model="gpt-4o-mini", messages=messages)
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assistant_response = response.choices[0].message.content
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# Create new memories from the conversation
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messages.append({"role": "assistant", "content": assistant_response})
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await async_memory.add(messages, user_id=user_id)
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return assistant_response
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async def async_main():
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print("Chat with AI (type 'exit' to quit)")
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while True:
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user_input = input("You: ").strip()
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if user_input.lower() == 'exit':
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print("Goodbye!")
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break
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response = await chat_with_memories(user_input)
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print(f"AI: {response}")
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def main():
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asyncio.run(async_main())
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if __name__ == "__main__":
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main()
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```
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If you have any questions or need further assistance, please don't hesitate to reach out:
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<Snippet file="get-help.mdx" />
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@@ -28,6 +28,16 @@ from mem0 import Memory
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os.environ["OPENAI_API_KEY"] = "your-api-key"
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m = Memory()
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```
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</Tab>
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<Tab title="Async">
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```python
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import os
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from mem0 import AsyncMemory
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os.environ["OPENAI_API_KEY"] = "your-api-key"
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m = AsyncMemory()
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```
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</Tab>
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<Tab title="Advanced">
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