docs: new algorithm migration guides + memory evaluation (#4811)

Co-authored-by: kartik-mem0 <kartik.labhshetwar@mem0.ai>
Co-authored-by: Saket Aryan <saketaryan2002@gmail.com>
This commit is contained in:
Chaithanya Kumar
2026-04-16 17:13:13 +05:30
committed by GitHub
parent 50db9e428d
commit 30469aec17
69 changed files with 2054 additions and 2066 deletions
+18 -14
View File
@@ -56,7 +56,7 @@ Search converts your natural language question into a vector embedding, then fin
client.search("What are Alice's hobbies?", filters={"user_id": "alice"})
# OSS
m.search("What are Alice's hobbies?", user_id="alice")
m.search("What are Alice's hobbies?", filters={"user_id": "alice"})
```
<Tip>
@@ -74,7 +74,7 @@ m.search("What are Alice's hobbies?", user_id="alice")
| Capability | Mem0 Platform | Mem0 OSS |
| --- | --- | --- |
| **user_id usage** | In `filters={"user_id": "alice"}` for search/get_all | As parameter `user_id="alice"` for all operations |
| **Entity IDs on search / get_all** | Inside `filters={"user_id": "alice"}` | Inside `filters={"user_id": "alice"}` (aligned with Platform in v3 — top-level kwargs raise `ValueError`) |
| **Filter syntax** | Logical operators (`AND`, `OR`, comparisons) with field-level access | Basic field filters, extend via Python hooks |
| **Reranking** | Toggle `rerank=True` with managed reranker catalog | Requires configuring local or third-party rerankers |
| **Thresholds** | Request-level configuration (`threshold`, `top_k`) | Controlled via SDK parameters |
@@ -125,14 +125,13 @@ from mem0 import Memory
m = Memory()
# Simple search
related_memories = m.search("Should I drink coffee or tea?", user_id="alice")
# Simple search — entity IDs go in `filters`
related_memories = m.search("Should I drink coffee or tea?", filters={"user_id": "alice"})
# Search with filters
# Search with additional metadata filters (combine entity + metadata in the same dict)
memories = m.search(
"food preferences",
user_id="alice",
filters={"categories": {"contains": "diet"}}
filters={"user_id": "alice", "categories": {"contains": "diet"}},
)
```
@@ -141,13 +140,14 @@ import { Memory } from 'mem0ai/oss';
const memory = new Memory();
// Simple search
const relatedMemories = memory.search("Should I drink coffee or tea?", { userId: "alice" });
// Simple search — entity IDs go inside `filters`
const relatedMemories = memory.search("Should I drink coffee or tea?", {
filters: { userId: "alice" },
});
// Search with filters (if supported)
// Combine entity + metadata filters in the same filters object
const memories = memory.search("food preferences", {
userId: "alice",
filters: { categories: { contains: "diet" } }
filters: { userId: "alice", categories: { contains: "diet" } },
});
```
</CodeGroup>
@@ -176,8 +176,12 @@ client.search("query", filters={
*OSS:*
```python
# Get memories from a specific agent session
m.search("query", user_id="alice", agent_id="chatbot", run_id="session-123")
# Get memories from a specific agent session — entity IDs combined in filters
m.search("query", filters={
"user_id": "alice",
"agent_id": "chatbot",
"run_id": "session-123",
})
```
**Filter by Date Range:**