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---
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title: Response schema
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description: Understanding the search API response structure
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---
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The search API returns different response structures depending on the search mode and result type.
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## Response structure
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```json
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{
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"results": [...],
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"timing": 245,
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"total": 10
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}
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```
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### Top-level fields
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<ResponseField name="results" type="array">
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Array of search results. Can contain memory results, chunk results, or both (in hybrid mode).
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</ResponseField>
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<ResponseField name="timing" type="number">
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Search execution time in milliseconds.
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</ResponseField>
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<ResponseField name="total" type="number">
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Total number of results returned.
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</ResponseField>
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## Result types
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In hybrid search mode, results can be either memory results or chunk results. Each type has a different structure.
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### Memory result
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Memory results contain the `memory` field and represent structured memory entries.
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```json
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{
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"id": "mem_abc123",
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"memory": "John prefers machine learning over traditional programming",
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"metadata": {
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"category": "preferences",
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"confidence": 0.95
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},
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"updatedAt": "2024-01-15T10:30:00Z",
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"version": 2,
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"rootMemoryId": "mem_root456",
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"similarity": 0.92,
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"context": {
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"parents": [...],
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"children": [...]
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},
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"documents": [...],
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"chunks": [...]
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}
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```
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<ResponseField name="id" type="string">
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Unique identifier for the memory entry.
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</ResponseField>
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<ResponseField name="memory" type="string">
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The memory content. **Only present in memory results.**
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</ResponseField>
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<ResponseField name="metadata" type="object | null">
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Custom metadata associated with the memory.
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</ResponseField>
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<ResponseField name="updatedAt" type="string">
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ISO 8601 timestamp of when the memory was last updated.
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</ResponseField>
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<ResponseField name="version" type="number">
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Version number of the memory (increments with updates).
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</ResponseField>
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<ResponseField name="rootMemoryId" type="string | null">
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ID of the root memory if this memory is part of a memory chain.
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</ResponseField>
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<ResponseField name="similarity" type="number">
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Similarity score between 0 and 1 (higher is more similar).
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</ResponseField>
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<ResponseField name="context" type="object">
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Related memories (parents and children) if `include.relatedMemories` is true.
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```json
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{
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"parents": [
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{
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"id": "mem_parent123",
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"memory": "Parent memory content",
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"relation": "updates"
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}
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],
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"children": [
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{
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"id": "mem_child456",
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"memory": "Child memory content",
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"relation": "extends"
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}
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]
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}
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```
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</ResponseField>
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<ResponseField name="documents" type="array">
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Associated documents if `include.documents` is true. See [Document schema](#document-schema).
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</ResponseField>
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<ResponseField name="chunks" type="array">
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Top 5 relevant document chunks if `include.chunks` is true. See [Chunk schema](#chunk-schema).
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</ResponseField>
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### Chunk result
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Chunk results contain the `chunk` field and represent raw document content. **Only returned in hybrid search mode.**
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```json
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{
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"id": "chunk_xyz789",
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"chunk": "This is a chunk of content from a document about machine learning preferences...",
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"metadata": {
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"source": "document_123.pdf",
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"page": 5
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},
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"updatedAt": "2024-01-15T10:30:00Z",
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"similarity": 0.88,
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"version": 1,
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"context": {
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"parents": [],
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"children": []
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},
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"documents": [
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{
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"id": "doc_123",
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"title": "Machine Learning Guide",
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"type": "pdf",
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"createdAt": "2024-01-10T08:00:00Z",
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"updatedAt": "2024-01-15T10:30:00Z"
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}
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],
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"chunks": []
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}
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```
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<ResponseField name="id" type="string">
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Unique identifier for the chunk.
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</ResponseField>
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<ResponseField name="chunk" type="string">
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The chunk content. **Only present in chunk results.**
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</ResponseField>
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<ResponseField name="metadata" type="object | null">
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Metadata from the parent document.
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</ResponseField>
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<ResponseField name="updatedAt" type="string">
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ISO 8601 timestamp of when the document was last updated.
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</ResponseField>
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<ResponseField name="similarity" type="number">
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Similarity score between 0 and 1 (higher is more similar).
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</ResponseField>
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<ResponseField name="version" type="number">
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Always 1 for chunk results.
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</ResponseField>
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<ResponseField name="context" type="object">
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Always empty for chunk results (chunks don't have parent/child relationships).
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</ResponseField>
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<ResponseField name="documents" type="array">
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Array containing the parent document. Always includes exactly one document.
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</ResponseField>
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<ResponseField name="chunks" type="array">
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Always empty for chunk results.
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</ResponseField>
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## Nested schemas
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### Document schema
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```json
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{
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"id": "doc_123",
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"title": "Machine Learning Guide",
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"type": "pdf",
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"metadata": {
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"author": "John Doe",
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"tags": ["ml", "ai"]
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},
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"summary": "A comprehensive guide to machine learning...",
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"createdAt": "2024-01-10T08:00:00Z",
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"updatedAt": "2024-01-15T10:30:00Z"
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}
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```
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<ResponseField name="id" type="string">
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Document identifier (custom ID if provided, otherwise internal ID).
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</ResponseField>
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<ResponseField name="title" type="string">
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Document title (if `include.documents` is true).
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</ResponseField>
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<ResponseField name="type" type="string">
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Document type (e.g., "pdf", "txt", "html").
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</ResponseField>
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<ResponseField name="metadata" type="object | null">
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Document metadata (if `include.documents` is true).
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</ResponseField>
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<ResponseField name="summary" type="string | null">
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Document summary (if `include.summaries` is true).
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</ResponseField>
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<ResponseField name="createdAt" type="string">
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ISO 8601 timestamp of document creation.
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</ResponseField>
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<ResponseField name="updatedAt" type="string">
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ISO 8601 timestamp of last document update.
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</ResponseField>
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### Chunk schema
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```json
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{
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"content": "This is a chunk of content from the document...",
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"score": 0.89,
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"position": 3,
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"documentId": "doc_123"
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}
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```
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<ResponseField name="content" type="string">
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The chunk content.
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</ResponseField>
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<ResponseField name="score" type="number">
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Similarity score for this chunk (0-1).
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</ResponseField>
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<ResponseField name="position" type="number">
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Position of the chunk within the document (0-indexed).
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</ResponseField>
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<ResponseField name="documentId" type="string">
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ID of the parent document.
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</ResponseField>
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## Distinguishing result types
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To determine if a result is a memory or chunk:
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```javascript
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if (result.memory) {
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// This is a memory result
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console.log("Memory:", result.memory);
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} else if (result.chunk) {
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// This is a chunk result
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console.log("Chunk:", result.chunk);
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}
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```
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## Example responses
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### Memories mode response
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```json
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{
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"results": [
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{
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"id": "mem_abc123",
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"memory": "John prefers machine learning over traditional programming",
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"metadata": {
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"category": "preferences"
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},
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"updatedAt": "2024-01-15T10:30:00Z",
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"version": 2,
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"rootMemoryId": null,
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"similarity": 0.92
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}
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],
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"timing": 145,
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"total": 1
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}
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```
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### Hybrid mode response
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```json
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{
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"results": [
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{
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"id": "mem_abc123",
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"memory": "John prefers machine learning over traditional programming",
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"metadata": {
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"category": "preferences"
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},
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"updatedAt": "2024-01-15T10:30:00Z",
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"version": 2,
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"rootMemoryId": null,
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"similarity": 0.92,
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"context": {
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"parents": [],
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"children": []
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},
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"documents": [],
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"chunks": []
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},
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{
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"id": "chunk_xyz789",
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"chunk": "Machine learning is a subset of artificial intelligence...",
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"metadata": {
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"source": "ml_guide.pdf"
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},
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"updatedAt": "2024-01-14T09:00:00Z",
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"similarity": 0.88,
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"version": 1,
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"context": {
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"parents": [],
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"children": []
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},
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"documents": [
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{
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"id": "doc_123",
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"title": "Machine Learning Guide",
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"type": "pdf",
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"createdAt": "2024-01-10T08:00:00Z",
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"updatedAt": "2024-01-14T09:00:00Z"
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}
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],
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"chunks": []
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}
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],
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"timing": 245,
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"total": 2
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}
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```
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## Notes
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- In hybrid mode, results are sorted by similarity score regardless of type
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- Chunk results that are already associated with memory results are automatically deduplicated
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- The `context` field is always empty for chunk results
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- The `documents` array for chunk results always contains exactly one document (the parent)
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- Memory results can have multiple associated documents if the memory references multiple sources
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