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Supermemory API Reference overview
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docs/supermemory-research/raw/05-api-reference.md
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Supermemory API Reference
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Supermemory API Reference
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docs/supermemory-research/raw/05-api-reference
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# Supermemory API Reference
Source: https://supermemory.ai/docs/api-reference
## Base URL
`https://api.supermemory.ai`
## Authentication
Bearer token (HTTP bearer scheme). API keys prefixed with `sm_`.
## POST /v3/documents
### Purpose
Ingest documents with flexible content types (text, URLs, files, images, videos) and optional metadata.
### Request Body
**Required:**
- `content` (string): The content to process -- can be a website URL, PDF, image, or video
**Optional Parameters:**
- `containerTag`: Organize documents with a tag (max 100 chars; alphanumeric with hyphens, underscores, dots)
- `entityContext`: Guide memory extraction (max 1,500 chars)
- `customId`: Custom document identifier (max 100 chars)
- `metadata`: Key-value pairs (strings, numbers, booleans, or string arrays)
- `taskType`: Choose "memory" (full context layer, default) or "superrag" (managed RAG service)
- `filepath`: File path information for filesystem integration
- `filterByMetadata`: Filter related memories by metadata criteria during ingestion
- `dreaming`: Processing mode -- "dynamic" (default, batches related documents) or "instant" (processes immediately)
### Response
**Success (200):**
```json
{
"id": "string",
"status": "string"
}
```
**Errors:**
- 401: Unauthorized (missing/invalid bearer token)
- 500: Internal server error
## Additional API Operations
### Memory Operations
- Create memories directly
- Update and version memory entries
- Soft-delete memories ("forgetting")
- Search across indexed content
### Document Operations
- Add single or batch documents
- Upload files for processing
- Update document metadata
- Delete by ID or custom identifiers
- Track processing status
- Access document chunks and presigned URLs
### Profile Operations
- Retrieve user profiles
- Get static + dynamic context
- Query with threshold filtering
### Search Operations
- Semantic search with metadata filtering
- Hybrid search (RAG + memory)
- Low-latency retrieval for conversational AI
## SDK Usage
### JavaScript/TypeScript
```javascript
import { Supermemory } from "supermemory";
const client = new Supermemory({ apiKey: "sm_..." });
// Add memory
await client.add({
content: "User prefers functional patterns",
containerTag: "user_123",
});
// Retrieve profile
const { profile, searchResults } = await client.profile({
containerTag: "user_123",
q: "programming style?",
});
// Hybrid search
const results = await client.search.memories({
q: "how to deploy?",
containerTag: "user_123",
searchMode: "hybrid",
});
```
### Python
```python
from supermemory import Supermemory
client = Supermemory(api_key="sm_...")
client.add(content="User prefers functional patterns", container_tag="user_123")
profile = client.profile(container_tag="user_123", q="programming style?")
```
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