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Feedback Mechanism

docs/platform/features/feedback-mechanism.mdx

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Mem0's Feedback Mechanism allows you to provide feedback on the memories generated by your application. This feedback is used to improve the accuracy of the memories and search results.

How it works

The feedback mechanism is a simple API that allows you to provide feedback on the memories generated by your application. The feedback is stored in the database and used to improve the accuracy of the memories and search results. Over time, Mem0 continuously learns from this feedback, refining its memory generation and search capabilities for better performance.

Give Feedback

You can give feedback on a memory by calling the feedback method on the Mem0 client.

<CodeGroup>
python
from mem0 import MemoryClient

client = MemoryClient(api_key="your_api_key")

client.feedback(memory_id="your-memory-id", feedback="NEGATIVE", feedback_reason="I don't like this memory because it is not relevant.")
javascript
import MemoryClient from 'mem0ai';

const client = new MemoryClient({ apiKey: 'your-api-key'});

client.feedback({
    memory_id: "your-memory-id", 
    feedback: "NEGATIVE", 
    feedback_reason: "I don't like this memory because it is not relevant."
})
</CodeGroup>

Feedback Types

The feedback parameter can be one of the following values:

  • POSITIVE: The memory is useful.
  • NEGATIVE: The memory is not useful.
  • VERY_NEGATIVE: The memory is not useful at all.

Parameters

The feedback method accepts these parameters:

ParameterTypeRequiredDescription
memory_idstringYesThe ID of the memory to give feedback on
feedbackstringNoType of feedback: POSITIVE, NEGATIVE, or VERY_NEGATIVE
feedback_reasonstringNoOptional explanation for the feedback
<Note> Pass `None` or `null` to the `feedback` and `feedback_reason` parameters to remove existing feedback for a memory. </Note>

Bulk Feedback Operations

For applications with high volumes of feedback, you can provide feedback on multiple memories at once:

<CodeGroup>
python
from mem0 import MemoryClient

client = MemoryClient(api_key="your_api_key")

# Bulk feedback example
feedback_data = [
    {
        "memory_id": "memory-1", 
        "feedback": "POSITIVE", 
        "feedback_reason": "Accurately captured the user's preference"
    },
    {
        "memory_id": "memory-2", 
        "feedback": "NEGATIVE", 
        "feedback_reason": "Contains outdated information"
    }
]

for item in feedback_data:
    client.feedback(**item)
javascript
import MemoryClient from 'mem0ai';

const client = new MemoryClient({ apiKey: 'your-api-key'});

// Bulk feedback example
const feedbackData = [
    {
        memory_id: "memory-1", 
        feedback: "POSITIVE", 
        feedback_reason: "Accurately captured the user's preference"
    },
    {
        memory_id: "memory-2", 
        feedback: "NEGATIVE", 
        feedback_reason: "Contains outdated information"
    }
];

for (const item of feedbackData) {
    await client.feedback(item);
}
</CodeGroup>

Best Practices

When to Provide Feedback

  • Immediately after memory retrieval when you can assess relevance
  • During user interactions when users explicitly indicate satisfaction or dissatisfaction
  • Through automated evaluation using your application's success metrics

Effective Feedback Reasons

Provide specific, actionable feedback reasons:

Good examples:

  • "Contains outdated contact information"
  • "Accurately captured the user's dietary restrictions"
  • "Irrelevant to the current conversation context"

Avoid vague reasons:

  • "Bad memory"
  • "Wrong"
  • "Not good"

Feedback Strategy

  1. Be consistent: Apply the same criteria across similar memories
  2. Be specific: Detailed reasons help improve the system faster
  3. Monitor patterns: Regular feedback analysis helps identify improvement areas

Error Handling

Handle potential errors when submitting feedback:

<CodeGroup>
python
from mem0 import MemoryClient
from mem0.exceptions import MemoryError, ValidationError

client = MemoryClient(api_key="your_api_key")

try:
    client.feedback(
        memory_id="memory-123", 
        feedback="POSITIVE", 
        feedback_reason="Helpful context for user query"
    )
    print("Feedback submitted successfully")
except ValidationError:
    print("memory_id is not a valid UUID")
except MemoryError as e:
    print(f"memory_id was not found or not accessible ({e.error_code})")
javascript
import MemoryClient from 'mem0ai';

const client = new MemoryClient({ apiKey: 'your-api-key'});

try {
    await client.feedback({
        memory_id: "memory-123", 
        feedback: "POSITIVE", 
        feedback_reason: "Helpful context for user query"
    });
    console.log("Feedback submitted successfully");
} catch (error) {
    if (error.errorCode === "HTTP_400") {
        console.log("memory_id is not a valid UUID");
    } else if (error.errorCode === "HTTP_500") {
        console.log("Server error - the memory_id may not exist or be inaccessible, or it may be transient; retry if it persists");
    } else {
        console.log(`Unexpected error: ${error.message}`);
    }
}
</CodeGroup>

Handling an unknown or malformed memory_id

  • A malformed memory_id (not a valid UUID) returns a clean 400 with {"error": "Invalid memory_id"}.
  • A well-formed but non-existent memory_id (or one that doesn't belong to your org or project) currently returns a 500 Internal Server Error instead of a 404. This is a server-side bug being tracked in MEM-5745. A 5xx can also be a transient server error, so don't treat it as a definitive "not found"; to avoid the case entirely, only call feedback with a memory_id you just read from a get_all or search response.

Feedback Analytics

Track the impact of your feedback by monitoring memory performance over time. Consider implementing:

  • Feedback completion rates: What percentage of memories receive feedback
  • Feedback distribution: Balance of positive vs. negative feedback
  • Memory quality trends: How accuracy improves with feedback volume
  • User satisfaction metrics: Correlation between feedback and user experience