supermemory/apps/docs/search/response-schema.mdx

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---
title: "Response Schema"
description: "Complete response structure for all search endpoints with scoring details"
---
## Document Search Response (POST `/v3/search`)
Response from `client.search.documents()` and `client.search.execute()`:
```json
{
"results": [
{
"documentId": "doc_abc123",
"title": "Machine Learning Fundamentals",
"type": "pdf",
"score": 0.89,
"chunks": [
{
"content": "Machine learning is a subset of artificial intelligence...",
"score": 0.95,
"isRelevant": true
}
],
"metadata": {
"category": "education",
"author": "Dr. Smith",
"difficulty": "beginner"
},
"createdAt": "2024-01-15T10:30:00Z",
"updatedAt": "2024-01-20T14:45:00Z"
}
],
"timing": 187,
"total": 1
}
```
### Document Result Fields
<ResponseField name="documentId" type="string">
Unique identifier for the document containing the matching chunks.
</ResponseField>
<ResponseField name="title" type="string | null">
Document title if available. May be null for documents without titles.
</ResponseField>
<ResponseField name="type" type="string | null">
Document type (e.g., "pdf", "text", "webpage", "notion_doc"). May be null if not specified.
</ResponseField>
<ResponseField name="score" type="number" range="0-1">
**Overall document relevance score**. Combines semantic similarity, keyword matching, and metadata relevance.
- **0.9-1.0**: Extremely relevant
- **0.7-0.9**: Highly relevant
- **0.5-0.7**: Moderately relevant
- **0.3-0.5**: Somewhat relevant
- **0.0-0.3**: Marginally relevant
</ResponseField>
<ResponseField name="chunks" type="Array<Chunk>">
Array of matching text chunks from the document. Each chunk represents a portion of the document that matched your query.
<ResponseField name="chunks[].content" type="string">
The actual text content of the matching chunk. May include context from surrounding chunks unless `onlyMatchingChunks=true`.
</ResponseField>
<ResponseField name="chunks[].score" type="number" range="0-1">
**Chunk-specific similarity score**. How well this specific chunk matches your query.
</ResponseField>
<ResponseField name="chunks[].isRelevant" type="boolean">
Whether this chunk passed the `chunkThreshold`. `true` means the chunk is above the threshold, `false` means it's included for context only.
</ResponseField>
</ResponseField>
<ResponseField name="metadata" type="object | null">
Document metadata as key-value pairs. Structure depends on what was stored with the document.
```json
{
"category": "tutorial",
"language": "python",
"difficulty": "intermediate",
"tags": "web-development,backend"
}
```
</ResponseField>
<ResponseField name="createdAt" type="string">
ISO 8601 timestamp when the document was created.
</ResponseField>
<ResponseField name="updatedAt" type="string">
ISO 8601 timestamp when the document was last updated.
</ResponseField>
<ResponseField name="content" type="string | null" optional>
**Full document content**. Only included when `includeFullDocs=true`. Can be very large.
<Warning>
Full document content can make responses extremely large. Use with appropriate limits and only when necessary.
</Warning>
</ResponseField>
<ResponseField name="summary" type="string | null" optional>
**AI-generated document summary**. Only included when `includeSummary=true`. Provides a concise overview of the document.
</ResponseField>
## Memory Search Response
Response from `client.search.memories()`:
When `searchMode="memories"` (default), all results are memory entries:
```json
{
"results": [
{
"id": "mem_xyz789",
"memory": "Complete memory content about quantum computing applications...",
"similarity": 0.87,
"metadata": {
"category": "research",
"topic": "quantum-computing"
},
"updatedAt": "2024-01-18T09:15:00Z",
"version": 3,
"context": {
"parents": [
{
"memory": "Earlier discussion about quantum theory basics...",
"relation": "extends",
"version": 2,
"updatedAt": "2024-01-17T16:30:00Z"
}
],
"children": [
{
"memory": "Follow-up questions about quantum algorithms...",
"relation": "derives",
"version": 4,
"updatedAt": "2024-01-19T11:20:00Z"
}
]
},
"documents": [
{
"id": "doc_quantum_paper",
"title": "Quantum Computing Applications",
"type": "pdf",
"createdAt": "2024-01-10T08:00:00Z"
}
]
}
],
"timing": 156,
"total": 1
}
```
When `searchMode="hybrid"`, results can contain both memory entries and document chunks. **Memory results have a `memory` key, chunk results have a `chunk` key:**
```json
{
"results": [
{
"id": "mem_xyz789",
"memory": "Complete memory content about quantum computing applications...",
"similarity": 0.87,
"metadata": {
"category": "research",
"topic": "quantum-computing"
},
"updatedAt": "2024-01-18T09:15:00Z",
"version": 3,
"context": {
"parents": [],
"children": []
},
"documents": [
{
"id": "doc_quantum_paper",
"title": "Quantum Computing Applications",
"type": "pdf",
"createdAt": "2024-01-10T08:00:00Z",
"updatedAt": "2024-01-10T08:00:00Z"
}
]
},
{
"id": "chunk_abc123",
"chunk": "This is a chunk of content from a document about quantum computing...",
"similarity": 0.82,
"metadata": {
"category": "research",
"source": "document"
},
"updatedAt": "2024-01-15T10:30:00Z",
"version": 1,
"context": {
"parents": [],
"children": []
},
"documents": [
{
"id": "doc_quantum_research",
"title": "Quantum Computing Research Paper",
"type": "pdf",
"metadata": {
"author": "Dr. Smith"
},
"createdAt": "2024-01-15T10:30:00Z",
"updatedAt": "2024-01-15T10:30:00Z"
}
]
}
],
"timing": 198,
"total": 2
}
```
<Note>
**Distinguishing Memory vs Chunk Results:**
In hybrid mode, check which key exists on the result object:
- **Memory results**: Have a `memory` key (no `chunk` key)
- **Chunk results**: Have a `chunk` key (no `memory` key)
```typescript
// TypeScript example
results.results.forEach(result => {
if ('memory' in result) {
// This is a memory result
console.log('Memory:', result.memory);
} else if ('chunk' in result) {
// This is a chunk result
console.log('Chunk:', result.chunk);
}
});
```
</Note>
### Memory Result Fields
<ResponseField name="id" type="string">
Unique identifier for the memory entry or chunk ID. In hybrid mode, can be either a memory ID (e.g., `mem_xyz789`) or a chunk ID (e.g., `chunk_abc123`).
</ResponseField>
<ResponseField name="memory" type="string" optional>
**Complete memory content**. Only present for memory results (when `searchMode="memories"` or when a memory result is returned in hybrid mode). This field is not present for chunk results.
</ResponseField>
<ResponseField name="chunk" type="string" optional>
**Chunk content from a document**. Only present for chunk results when `searchMode="hybrid"`. This field is not present for memory results. Contains the actual text content from the document chunk.
</ResponseField>
<ResponseField name="similarity" type="number" range="0-1">
**Similarity score** between your query and this memory. Higher scores indicate better matches.
- **0.9-1.0**: Extremely similar
- **0.8-0.9**: Very similar
- **0.7-0.8**: Similar
- **0.6-0.7**: Somewhat similar
- **0.5-0.6**: Marginally similar
</ResponseField>
<ResponseField name="metadata" type="object | null">
Memory metadata as key-value pairs. Structure depends on what was stored with the memory.
</ResponseField>
<ResponseField name="updatedAt" type="string">
ISO 8601 timestamp when the memory was last updated.
</ResponseField>
<ResponseField name="version" type="number | null" optional>
Version number of this memory entry. Used for tracking memory evolution and relationships. For chunk results, this is typically `1`.
</ResponseField>
<ResponseField name="rootMemoryId" type="string | null" optional>
Root memory ID for memory entries. Only present for memory results. Always `null` for chunk results.
</ResponseField>
<ResponseField name="context" type="object" optional>
**Contextual memory relationships**. Only included when `include.relatedMemories=true`.
<ResponseField name="context.parents" type="Array<ContextMemory>" optional>
Array of parent memories that this memory extends or derives from.
</ResponseField>
<ResponseField name="context.children" type="Array<ContextMemory>" optional>
Array of child memories that extend or derive from this memory.
</ResponseField>
### Context Memory Structure
<ResponseField name="memory" type="string">
Content of the related memory.
</ResponseField>
<ResponseField name="relation" type="string">
Relationship type: `"updates"`, `"extends"`, or `"derives"`.
- **updates**: This memory updates/replaces the related memory
- **extends**: This memory builds upon the related memory
- **derives**: This memory is derived from the related memory
</ResponseField>
<ResponseField name="version" type="number | null">
Relative version distance:
- **Negative values** for parents (-1 = direct parent, -2 = grandparent)
- **Positive values** for children (+1 = direct child, +2 = grandchild)
</ResponseField>
<ResponseField name="updatedAt" type="string">
When the related memory was last updated.
</ResponseField>
<ResponseField name="metadata" type="object | null" optional>
Metadata of the related memory.
</ResponseField>
</ResponseField>
<ResponseField name="documents" type="Array<Document>" optional>
**Associated documents**. Only included when `include.documents=true`.
<ResponseField name="documents[].id" type="string">
Document identifier.
</ResponseField>
<ResponseField name="documents[].title" type="string">
Document title.
</ResponseField>
<ResponseField name="documents[].type" type="string">
Document type.
</ResponseField>
<ResponseField name="documents[].metadata" type="object">
Document metadata.
</ResponseField>
<ResponseField name="documents[].createdAt" type="string">
Document creation timestamp.
</ResponseField>
<ResponseField name="documents[].updatedAt" type="string">
Document update timestamp.
</ResponseField>
</ResponseField>