feat: Enhance memory system with isolated memory configuration (#2597)

* feat: support defining any memory in an isolated way

This change makes it easier to use a specific memory type without unintentionally enabling all others.

Previously, setting memory=True would implicitly configure all available memories (like LTM and STM), which might not be ideal in all cases. For example, when building a chatbot that only needs an external memory, users were forced to also configure LTM and STM — which rely on default OpenAPI embeddings — even if they weren’t needed.

With this update, users can now define a single memory in isolation, making the configuration process simpler and more flexible.

* feat: add tests to ensure we are able to use contextual memory by set individual memories

* docs: enhance memory documentation

* feat: warn when long-term memory is defined but entity memory is not
This commit is contained in:
Lucas Gomide
2025-04-14 16:48:48 -03:00
committed by GitHub
parent 88455cd52c
commit 9dffd42e6d
17 changed files with 5018 additions and 1528 deletions

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@@ -145,6 +145,7 @@ from crewai.memory import LongTermMemory
# Simple memory configuration
crew = Crew(memory=True) # Uses default storage locations
```
Note that External Memory wont be defined when `memory=True` is set, as we cant infer which external memory would be suitable for your case
### Custom Storage Configuration
```python
@@ -278,15 +279,19 @@ crew = Crew(
### Using External Memory
External Memory is a powerful feature that allows you to integrate external memory systems with your CrewAI applications. This is particularly useful when you want to use specialized memory providers or maintain memory across different applications.
Since its an external memory, were not able to add a default value to it - unlike with Long Term and Short Term memory.
#### Basic Usage with Mem0
The most common way to use External Memory is with Mem0 as the provider:
```python
import os
from crewai import Agent, Crew, Process, Task
from crewai.memory.external.external_memory import ExternalMemory
os.environ["MEM0_API_KEY"] = "YOUR-API-KEY"
agent = Agent(
role="You are a helpful assistant",
goal="Plan a vacation for the user",
@@ -304,7 +309,6 @@ crew = Crew(
tasks=[task],
verbose=True,
process=Process.sequential,
memory=True,
external_memory=ExternalMemory(
embedder_config={"provider": "mem0", "config": {"user_id": "U-123"}} # you can provide an entire Mem0 configuration
),
@@ -363,7 +367,6 @@ crew = Crew(
tasks=[task],
verbose=True,
process=Process.sequential,
memory=True,
external_memory=external_memory,
)