> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mem0.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Advanced Retrieval

> Advanced memory search with intelligent reranking for precise results

## What is Advanced Retrieval?

Advanced Retrieval gives you precise control over how memories are found and ranked. While basic search uses semantic similarity, these advanced options help you find exactly what you need, when you need it.

## Search Enhancement Options

### Reranking

Reorders results using deep semantic understanding to put the most relevant memories first.

<Tabs>
  <Tab title="When to Use">
    * Need the most relevant result at the top
    * Result order is critical for your application
    * Want consistent quality across different queries
    * Building user-facing features where accuracy matters
  </Tab>

  <Tab title="How it Works">
    ```python Python theme={null}
    # Get the most relevant travel plans first
    results = client.search(
        query="What are my upcoming travel plans?",
        rerank=True,
        filters={"user_id": "user123"},
    )

    # Before reranking:        After reranking:
    # 1. "Went to Paris"   →   1. "Tokyo trip next month"
    # 2. "Tokyo trip next" →   2. "Need to book hotel in Tokyo"  
    # 3. "Need hotel"      →   3. "Went to Paris last year"
    ```
  </Tab>

  <Tab title="Performance">
    * **Latency**: 150-200ms additional
    * **Accuracy**: Significantly improved
    * **Ordering**: Much more relevant
    * **Best for**: Top-N precision, user-facing results
  </Tab>
</Tabs>

## Real-World Use Cases

<Tabs>
  <Tab title="Personal AI Assistant">
    ```python Python theme={null}
    # Smart home assistant finding device preferences
    results = client.search(
        query="How do I like my bedroom temperature?",
        rerank=True,           # Get most recent preferences first
        filters={"user_id": "user123"},
    )

    # Finds: "Keep bedroom at 68°F", "Too cold last night at 65°F", etc.
    ```
  </Tab>

  <Tab title="Customer Support">
    ```python Python theme={null}
    # Find specific product issues with high precision
    results = client.search(
        query="Problems with premium subscription billing",
        filters={"user_id": "customer456"},
    )

    # Returns only relevant billing problems, not general questions
    ```
  </Tab>

  <Tab title="Healthcare AI">
    ```python Python theme={null}
    # Critical medical information needs perfect accuracy
    results = client.search(
        query="Patient allergies and contraindications",
        rerank=True,            # Most important info first
        filters={"user_id": "patient789"},
    )

    # Ensures critical allergy info appears first
    ```
  </Tab>

  <Tab title="Learning Platform">
    ```python Python theme={null}
    # Find learning progress for specific topics
    results = client.search(
        query="Python programming progress and difficulties",
        rerank=True,           # Recent progress first
        filters={"user_id": "student123"},
    )

    # Gets comprehensive view of Python learning journey
    ```
  </Tab>
</Tabs>

## Choosing the Right Configuration

### Recommended Configurations

<CodeGroup>
  ```python Python theme={null}
  # Basic search - good for exploration
  def quick_search(query, user_id):
      return client.search(
          query=query,
          filters={"user_id": user_id},
      )

  # Reranked search - good for most applications
  def standard_search(query, user_id):
      return client.search(
          query=query,
          rerank=True,
          filters={"user_id": user_id},
      )

  # Reranked search - good for critical applications
  def precise_search(query, user_id):
      return client.search(
          query=query,
          rerank=True,
          filters={"user_id": user_id},
      )
  ```

  ```javascript JavaScript theme={null}
  // Basic search - good for exploration
  function quickSearch(query, userId) {
      return client.search(query, {
          filters: { user_id: userId },
      });
  }

  // Reranked search - good for most applications
  function standardSearch(query, userId) {
      return client.search(query, {
          filters: { user_id: userId },
          rerank: true,
      });
  }

  // Reranked search - good for critical applications
  function preciseSearch(query, userId) {
      return client.search(query, {
          filters: { user_id: userId },
          rerank: true,
      });
  }
  ```
</CodeGroup>

## Best Practices

### Do

* Start simple with basic search and measure impact before enabling reranking
* Use reranking when the top result quality matters most
* Monitor latency and adjust based on your application's needs
* Handle empty results gracefully

### Don't

* Enable reranking by default without measuring necessity
* Ignore latency impact in real-time applications
* Use advanced retrieval for simple, fast lookup scenarios

## Performance Guidelines

### Latency Expectations

```python Python theme={null}
# Performance monitoring example
import time

start_time = time.time()
results = client.search(
    query="user preferences",
    rerank=True,         # +150ms
    filters={"user_id": "user123"},
)
latency = time.time() - start_time
print(f"Search completed in {latency:.2f}s")
```

### Optimization Tips

1. **Cache frequent queries** to avoid repeated advanced processing
2. **Use session-specific search** with `run_id` to reduce search space
3. **Implement fallback logic** when search returns empty results
4. **Monitor and alert** on search latency patterns

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