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----
-title: "Searching Memories"
-description: "Learn how to search for and retrieve content from supermemory"
----
-
-<Accordion title="Best Practices" defaultOpen icon="sparkles">
-1. **Query Formulation**:
-   - Use natural language queries
-   - Include relevant keywords
-   - Be specific but not too verbose
-
-2. **Filtering**:
-   - Use metadata filters for precision
-   - Combine multiple filters when needed
-   - Use appropriate thresholds
-
-3. **Performance**:
-   - Set appropriate result limits
-   - Use specific document/chunk filters
-   - Consider response timing
-     </Accordion>
-
-## Basic Search
-
-To search through your memories, send a POST request to `/search`:
-
-<CodeGroup>
-
-```bash cURL
-curl https://api.supermemory.ai/v3/search?q=machine+learning+concepts&limit=10 \
-  --request GET \
-  --header 'Authorization: Bearer SUPERMEMORY_API_KEY'
-```
-
-```typescript Typescript
-await client.search.execute({
-  q: "machine learning concepts",
-  limit: 10,
-});
-```
-
-```python Python
-client.search.execute(
-    q="machine learning concepts",
-    limit=10
-)
-```
-
-</CodeGroup>
-
-The API will return relevant matches with their similarity scores:
-
-```json
-{
-  "results": [
-    {
-      "documentId": "doc_xyz789",
-      "chunks": [
-        {
-          "content": "Machine learning is a subset of artificial intelligence...",
-          "isRelevant": true,
-          "score": 0.85
-        }
-      ],
-      "score": 0.95,
-      "metadata": {
-        "source": "web",
-        "category": "technology"
-      },
-      "title": "Introduction to Machine Learning"
-    }
-  ],
-  "total": 1,
-  "timing": 123.45
-}
-```
-
-## Search Parameters
-
-```json
-{
-  "q": "search query", // Required: Search query string
-  "limit": 10, // Optional: Max results (default: 10)
-  "documentThreshold": 0.5, // Optional: Min document score (0-1)
-  "chunkThreshold": 0.5, // Optional: Min chunk score (0-1)
-  "onlyMatchingChunks": false, // Optional: Skip context chunks
-  "docId": "doc_id", // Optional: Search in specific doc
-  "userId": "user_123", // Optional: Search in user's space
-  "includeSummary": false, // Optional: Include doc summaries
-  "filters": {
-    // Optional: Metadata filters
-    "AND": [
-      {
-        "key": "category",
-        "value": "technology"
-      }
-    ]
-  },
-  "categoriesFilter": [
-    // Optional: Category filters
-    "technology",
-    "science"
-  ]
-}
-```
-
-## Search Response
-
-The search response includes:
-
-```json
-{
-  "results": [
-    {
-      "documentId": "string", // Document ID
-      "chunks": [
-        {
-          // Matching chunks
-          "content": "string", // Chunk content
-          "isRelevant": true, // Is directly relevant
-          "score": 0.95 // Similarity score
-        }
-      ],
-      "score": 0.95, // Document score
-      "metadata": {}, // Document metadata
-      "title": "string", // Document title
-      "createdAt": "string", // Creation date
-      "updatedAt": "string" // Last update date
-    }
-  ],
-  "total": 1, // Total results
-  "timing": 123.45 // Search time (ms)
-}
-```
-
-## Next Steps
-
-Explore more advanced features in our [API Reference](/api-reference/search-memories/search-memories).