Query API

Find relevant memories and generate answers.

Query Memories

Find memories relevant to a context using intelligent retrieval.

POST /v1/query

Request Body

Field	Type	Required	Default	Description
context	string	Yes	-	Query context/question
max_memories	int	No	20	Max results (1-100)
relevance_threshold	float	No	0.5	Min score (0-1)
include_metadata	bool	No	true	Include metadata
space_id	string	No	null	Filter to specific space
query_rewrite	bool	No	false	Expand query for better recall
hybrid_search	bool	No	false	Combine keyword and semantic matching
temporal_boost	float	No	null	Boost recent memories (0-1)

Example

curl -X POST https://api.memory.tensorheart.com/v1/query \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "context": "What programming languages does the user know?",
    "max_memories": 5,
    "relevance_threshold": 0.6,
    "space_id": "skills",
    "query_rewrite": true
  }'

Response

{
  "success": true,
  "data": {
    "memories": [
      {
        "id": "mem_abc123",
        "text": "User is proficient in Python and JavaScript",
        "relevance_score": 0.92,
        "metadata": {"category": "skills"}
      }
    ],
    "query_context": "What programming languages does the user know?"
  }
}

---

Query with Answer

Find memories and generate an AI answer.

POST /v1/query/answer

Request Body

Field	Type	Required	Default	Description
context	string	Yes	-	Question to answer
max_memories	int	No	20	Max memories to consider
relevance_threshold	float	No	0.5	Min relevance
prompt_template	string	No	null	Custom prompt

Example

curl -X POST https://api.memory.tensorheart.com/v1/query/answer \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "context": "What industry does the user work in?"
  }'

Response

{
  "success": true,
  "data": {
    "answer": "Based on the stored memories, the user works in the technology industry as a data scientist.",
    "memories_used": [...]
  }
}

---

Extract Memories

Extract memories from a conversation or document.

POST /v1/query/extract

Request Body

Field	Type	Required	Description
content	string	Yes	Content to extract from
content_type	string	No	Type: conversation, document, notes
metadata	object	No	Metadata for extracted memories

Example

curl -X POST https://api.memory.tensorheart.com/v1/query/extract \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "content": "User: Hi, I am John and I work at Google.\nAssistant: Nice to meet you!",
    "content_type": "conversation"
  }'

Response

{
  "success": true,
  "data": {
    "extracted_count": 2,
    "memory_ids": ["mem_new1", "mem_new2"]
  }
}