v1
/
Store Message

Papr Memory API (1.0.0)

API for managing personal memory items with authentication and user-specific data.

Authentication

This API supports three authentication methods:

  • API Key: Include your API key in the X-API-Key header
    X-API-Key: <your-api-key>
  • Session Token: Include your session token in the X-Session-Token header
    X-Session-Token: <your-session-token>
  • Bearer Token: Include your OAuth2 token from Auth0 in the Authorization header
    Authorization: Bearer <token>

All endpoints require one of these authentication methods.

Download OpenAPI description
arazzo.json
arazzo.yaml
Languages
Servers
Production server
http://memory.papr.ai/

v1

Operations

Delete User Schema V1

Request

Delete a schema.

Soft deletes the schema by marking it as archived. The schema data and associated graph nodes/relationships are preserved for data integrity. User must have write access to the schema.

Path
schema_idstring(Schema Id)required
curl -i -X DELETE \
  'http://memory.papr.ai/v1/schemas/{schema_id}' \
  -H 'X-API-Key: YOUR_API_KEY_HERE'

Responses

Schema deleted successfully

Bodyapplication/json
any
Response
application/json
null

Store Message

Request

Store a chat message and queue it for AI analysis and memory creation.

Authentication Required: Bearer token, API key, or session token

Processing Control:

  • Set process_messages: true (default) to enable full AI analysis and memory creation
  • Set process_messages: false to store messages only without processing into memories

Processing Flow (when process_messages=true):

  1. Message is immediately stored in PostMessage class
  2. Background processing analyzes the message for memory-worthiness
  3. If worthy, creates a memory with appropriate role-based categorization
  4. Links the message to the created memory

Role-Based Categories:

  • User messages: preference, task, goal, facts, context
  • Assistant messages: skills, learning

Session Management:

  • sessionId is required to group related messages
  • Use the same sessionId for an entire conversation
  • Optional title: Set a human-readable title for the conversation (e.g., "Q4 Planning Session")
  • Retrieve conversation history using GET /messages/sessions/{sessionId}
Bodyapplication/jsonrequired
contentContent (string) or Array of Content (objects)(Content)required

The content of the chat message - can be a simple string or structured content objects

Any of:

The content of the chat message - can be a simple string or structured content objects

string(Content)

The content of the chat message - can be a simple string or structured content objects

rolestring(MessageRole)required

Role of the message sender (user or assistant)

Enum"user""assistant"
sessionIdstring(Sessionid)required

Session ID to group related messages in a conversation

titleTitle (string) or Title (null)(Title)

Optional title for the conversation session. Sets the Chat.title in Parse Server for easy identification.

Any of:

Optional title for the conversation session. Sets the Chat.title in Parse Server for easy identification.

string(Title)

Optional title for the conversation session. Sets the Chat.title in Parse Server for easy identification.

metadataMemoryMetadata (object) or null

Optional metadata for the message (topics, location, etc.)

Any of:

Optional metadata for the message (topics, location, etc.)

contextArray of Context (objects) or Context (null)(Context)

Optional context for the message (conversation history or relevant context)

Any of:

Optional context for the message (conversation history or relevant context)

relationships_jsonArray of Relationships Json (objects) or Relationships Json (null)(Relationships Json)

Optional array of relationships for Graph DB (Neo4j)

Any of:

Optional array of relationships for Graph DB (Neo4j)

process_messagesboolean(Process Messages)

Whether to process messages into memories (true) or just store them (false). Default is true.

Default true
memory_policyMemoryPolicy (object) or null

Unified policy for graph generation and OMO safety. Use mode='auto' (LLM extraction), 'manual' (exact nodes), or 'hybrid' (LLM with constraints). Includes consent, risk, and ACL settings.

Any of:

Unified policy for graph generation and OMO safety. Use mode='auto' (LLM extraction), 'manual' (exact nodes), or 'hybrid' (LLM with constraints). Includes consent, risk, and ACL settings.

organization_idOrganization Id (string) or Organization Id (null)(Organization Id)

Optional organization ID for multi-tenant message scoping

Any of:

Optional organization ID for multi-tenant message scoping

string(Organization Id)

Optional organization ID for multi-tenant message scoping

namespace_idNamespace Id (string) or Namespace Id (null)(Namespace Id)

Optional namespace ID for multi-tenant message scoping

Any of:

Optional namespace ID for multi-tenant message scoping

string(Namespace Id)

Optional namespace ID for multi-tenant message scoping

graph_generationGraphGeneration (object) or nullDeprecated

DEPRECATED: Use 'memory_policy' instead. Legacy graph generation configuration.

Any of:
Deprecated

DEPRECATED: Use 'memory_policy' instead. Legacy graph generation configuration.

curl -i -X POST \
  http://memory.papr.ai/v1/messages \
  -H 'Content-Type: application/json' \
  -H 'X-API-Key: YOUR_API_KEY_HERE' \
  -d '{
    "content": "Can you help me plan the Q4 product roadmap?",
    "metadata": {
      "location": "Office",
      "topics": [
        "product",
        "planning",
        "roadmap"
      ]
    },
    "process_messages": true,
    "role": "user",
    "sessionId": "session_123",
    "title": "Q4 Product Planning"
  }'

Responses

Message stored and queued for processing

Bodyapplication/json
objectIdstring(Objectid)required

Parse Server objectId of the stored message

Example: "msg_abc123"
sessionIdstring(Sessionid)required

Session ID of the conversation

Example: "session_123"
rolestring(MessageRole)required

Role of the message sender

Enum"user""assistant"
Example: "user"
contentContent (string) or Array of Content (objects)(Content)required

Content of the message - can be a simple string or structured content objects

Example: "Can you help me plan the Q4 product roadmap?"
Any of:

Content of the message - can be a simple string or structured content objects

string(Content)

Content of the message - can be a simple string or structured content objects

createdAtstring(date-time)(Createdat)required

When the message was created

Example: "2024-01-15T10:30:00Z"
processing_statusstring(Processing Status)

Status of background processing (queued, analyzing, completed, failed)

Default "queued"
Example: "queued"
Response
application/json
{
  "content": "Can you help me plan the Q4 product roadmap?",
  "createdAt": "2024-01-15T10:30:00Z",
  "objectId": "msg_abc123",
  "processing_status": "queued",
  "role": "user",
  "sessionId": "session_123"
}

Get Session History

Request

Retrieve message history for a specific conversation session.

Authentication Required: Bearer token, API key, or session token

Pagination:

  • Use limit and skip parameters for pagination
  • Messages are returned in chronological order (oldest first)
  • total_count indicates total messages in the session

Summaries (if available):

  • Returns hierarchical conversation summaries (short/medium/long-term)
  • Includes context_for_llm field with pre-compressed context
  • Summaries are automatically generated every 15 messages
  • Use /sessions/{session_id}/compress endpoint to retrieve on-demand

Access Control:

  • Only returns messages for the authenticated user
  • Workspace scoping is applied if available
Path
session_idstring(Session Id)required
Query
limitinteger(Limit)[ 1 .. 100 ]

Maximum number of messages to return

Default 50
skipinteger(Skip)>= 0

Number of messages to skip for pagination

Default 0
curl -i -X GET \
  'http://memory.papr.ai/v1/messages/sessions/{session_id}?limit=50&skip=0' \
  -H 'X-API-Key: YOUR_API_KEY_HERE'

Responses

Message history retrieved

Bodyapplication/json
sessionIdstring(Sessionid)required

Session ID of the conversation

Example: "session_123"
messagesArray of objects(Messages)required

List of messages in chronological order

Example: [{"content":"Can you help me plan the Q4 product roadmap?","createdAt":"2024-01-15T10:30:00Z","objectId":"msg_abc123","processing_status":"completed","role":"user","sessionId":"session_123"},{"content":"I'd be happy to help you plan your Q4 roadmap. Let's start by identifying your key objectives.","createdAt":"2024-01-15T10:31:00Z","objectId":"msg_def456","processing_status":"completed","role":"assistant","sessionId":"session_123"}]
messages[].​objectIdstring(Objectid)required

Parse Server objectId of the stored message

Example: "msg_abc123"
messages[].​sessionIdstring(Sessionid)required

Session ID of the conversation

Example: "session_123"
messages[].​rolestring(MessageRole)required

Role of the message sender

Enum"user""assistant"
Example: "user"
messages[].​contentContent (string) or Array of Content (objects)(Content)required

Content of the message - can be a simple string or structured content objects

Example: "Can you help me plan the Q4 product roadmap?"
Any of:

Content of the message - can be a simple string or structured content objects

string(Content)

Content of the message - can be a simple string or structured content objects

messages[].​createdAtstring(date-time)(Createdat)required

When the message was created

Example: "2024-01-15T10:30:00Z"
messages[].​processing_statusstring(Processing Status)

Status of background processing (queued, analyzing, completed, failed)

Default "queued"
Example: "queued"
total_countinteger(Total Count)required

Total number of messages in the session

Example: 2
summariesConversationSummaryResponse (object) or null

Hierarchical conversation summaries for context compression

Example: {"long_term":"Product planning and strategy conversation","medium_term":"Ongoing product planning discussion for Q4","short_term":"User requested help planning Q4 product roadmap","topics":["product","roadmap","planning","Q4"]}
Any of:

Hierarchical conversation summaries for context compression

context_for_llmContext For Llm (string) or Context For Llm (null)(Context For Llm)

Pre-formatted compressed context ready for LLM consumption (summaries + recent messages)

Example: "FULL SESSION: Product planning and strategy conversation\nRECENT (last ~100): Ongoing product planning discussion for Q4\nCURRENT (last 15): User requested help planning Q4 product roadmap"
Any of:

Pre-formatted compressed context ready for LLM consumption (summaries + recent messages)

string(Context For Llm)

Pre-formatted compressed context ready for LLM consumption (summaries + recent messages)

Response
application/json
{
  "context_for_llm": "FULL SESSION: Product planning and strategy conversation\nRECENT (last ~100): Ongoing product planning discussion for Q4\nCURRENT (last 15): User requested help planning Q4 product roadmap",
  "messages": [
    { … },
    { … }
  ],
  "sessionId": "session_123",
  "summaries": {
    "long_term": "Product planning and strategy conversation",
    "medium_term": "Ongoing product planning discussion for Q4",
    "short_term": "User requested help planning Q4 product roadmap",
    "topics": [ … ]
  },
  "total_count": 2
}

Memory

Operations

User

Operations

Feedback

Operations

Schema Management

Operations

Messages

Operations

omo

Operations

Sync

Operations

Telemetry

Operations

Document

Operations

GraphQL

Operations

Authentication

Operations