​
Container Tag

Container tag is an identifier for your end users, to group memories together.. This can be:
  • A user using your product
  • An organization using a SaaS
A project ID, or even a dynamic one like user_project_etc We recommend using single containerTag in all API requests. The graph is built on top of the Container Tags. For example, each user / tag in your supermemory account will have one single graph built for them. 
curl https://api.supermemory.ai/v3/search \
  --request POST \
  --header 'Content-Type: application/json' \
  --header 'Authorization: Bearer SUPERMEMORY_API_KEY' \
  --data '{
    "q": "machine learning",
    "containerTags": ["user_123"]
  }'

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Metadata

Sometimes, you might want to add metadata and do advanced filtering based on it. Using metadata filtering, you can search based on:
  • AND and OR conditions
  • String matching
  • Numeric matching
  • Date matching
  • Time range queries
curl https://api.supermemory.ai/v3/search \
  --request POST \
  --header 'Content-Type: application/json' \
  --header 'Authorization: Bearer SUPERMEMORY_API_KEY' \
  --data '{
    "q": "machine learning",
    "filters": {
        "AND": [
            {
                "key": "category",
                "value": "technology",
                "negate": false
            },
            {
                "filterType": "numeric",
                "key": "readingTime",
                "value": "5",
                "negate": false,
                "numericOperator": "<="
            }
        ]
    }
}'

​
Document

You can also find chunks within a specific, large document. This can be particularly useful for extremely large documents like Books, Podcasts, etc. 
curl https://api.supermemory.ai/v3/search \
  --request POST \
  --header 'Content-Type: application/json' \
  --header 'Authorization: Bearer SUPERMEMORY_API_KEY' \
  --data '{
    "q": "machine learning",
    "docId": "doc_123"
  }'