Properties

Version: 6.0.0

Overview

Properties are EDDI's primary mechanism for storing and retrieving state within and across conversations. They are key-value pairs that can be set by agent configuration, extracted from API responses, or written by LLM tools — and they're accessible in every template (system prompts, HTTP call bodies, output templates, property instructions).

Properties are the glue that connects the pipeline's processing steps with persistent user state. Understanding how they work is essential for building stateful agents.

Key Concepts

What Properties Are

A property has:

• Name (key): The identifier used to access the property (e.g., preferred_language, company_name)

• Value: Can be a String, Integer, Float, Map, List, or Boolean

• Scope: How long the property lives

• Visibility (v6): Who can see the property

Property vs Context vs Memory

Mechanism	Source	Lifetime	Access Pattern
Properties	Agent-set (via PropertySetter, LLM tools)	Configurable (step → longTerm)	{properties.key.valueString}
Context	Your application (passed per request)	Per request	{context.key}
Memory	Pipeline (each task writes data)	Per step (current turn's data)	{memory.current.key}

Use properties when the agent needs to remember something. Use context when your application injects something. Use memory when you need data from the current or previous pipeline step.

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Scopes

Properties support four scopes that control their lifetime:

Scope	Lifetime	Persistence	Use Case
step	Current conversation turn only	Not persisted	Temporary data needed only for this response
conversation	Entire conversation session	Persisted in conversation memory	User preferences within a session, extracted entities
longTerm	Across conversations	Persisted in user property store	User profile data, preferences that should survive between sessions
secret	Across conversations (encrypted)	Persisted via SecretsVault	API keys, tokens, sensitive credentials

Choosing the Right Scope

Is this data only needed for the current response?
  → step

Will the user need this data later in the same conversation?
  → conversation

Should this data persist when the user starts a new conversation?
  → longTerm

Is this sensitive data (API keys, tokens)?
  → secret

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Visibility (v6)

Properties also have a visibility dimension that controls which agents can see them:

Visibility	Who sees it	Use Case
self (default)	Only the owning agent	Agent-specific preferences, internal state
group	All agents in the same group conversation	Shared context in multi-agent orchestration
global	All agents for this user	Cross-agent user preferences (e.g., language, timezone)

Visibility is orthogonal to scope — a property can be longTerm + self (persists across sessions, visible only to the owning agent) or longTerm + global (persists and visible to all agents).

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Setting Properties

Via PropertySetter Configuration (JSON)

The PropertySetter task (ai.labs.property) sets properties based on triggered actions:

{
  "setOnActions": ["greet_user"],
  "propertyInstructions": [
    {
      "name": "greeted",
      "valueString": "true",
      "scope": "conversation"
    },
    {
      "name": "preferred_language",
      "valueString": "{context.language}",
      "scope": "longTerm",
      "visibility": "global"
    }
  ]
}

When the greet_user action fires:

1. greeted is set to "true" for this conversation session

2. preferred_language is set from the input context and persisted across all conversations and agents

Via Pre/Post Request Instructions

Properties can be set before or after any lifecycle task (HTTP calls, LLM calls):

{
  "preRequest": {
    "propertyInstructions": [
      {
        "name": "requestTimestamp",
        "valueString": "{uuidUtils:generateUUID()}",
        "scope": "step"
      }
    ]
  },
  "postResponse": {
    "propertyInstructions": [
      {
        "name": "lastApiResponse",
        "fromObjectPath": "httpCalls.weatherApi",
        "scope": "conversation"
      }
    ]
  }
}

Via LLM Tools (Agent-Driven)

When enableMemoryTools is enabled in the agent configuration, the LLM can set properties using built-in memory tools:

Agent: "I'll remember that you prefer dark mode."
→ Tool call: rememberFact(key="ui_preference", value="dark_mode", category="preference", visibility="self")

See Persistent User Memory for full details on the LLM memory tools, visibility scoping, and Dream consolidation.

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Accessing Properties in Templates

Properties are available in all templates via the properties namespace:

In Output Templates

Hello {properties.userName.valueString}! Your preferred language is {properties.preferred_language.valueString}.

In System Prompts (LLM)

You are a helpful assistant. The user's name is {properties.userName.valueString}.
They prefer {properties.preferred_language.valueString} responses.

In HTTP Call Bodies

{
  "userId": "{properties.userId.valueString}",
  "language": "{properties.preferred_language.valueString}"
}

Property Value Accessors

Accessor	Type	Example
.valueString	String value	{properties.name.valueString}
.valueInt	Integer value	{properties.age.valueInt}
.valueFloat	Float value	{properties.score.valueFloat}
.valueObject	Object/Map	{properties.profile.valueObject.email}
.valueList	List	{#for item in properties.tags.valueList}...{/for}
.valueBoolean	Boolean	{#if properties.isPremium.valueBoolean}...{/if}

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Property Lifecycle

Properties are managed by Conversation.java at session boundaries — NOT by pipeline tasks.

1. Conversation Init

Conversation.init()
  └─→ loadUserProperties()
      └─→ IPropertiesHandler.getUserMemoryStore()
      └─→ IUserMemoryStore.getVisibleEntries(userId, agentId, groupIds, recallOrder, maxEntries)
      └─→ Entries converted to Property objects with scope=longTerm
      └─→ Loaded into conversationProperties
      └─→ Available as {properties.key} in all templates

Recall order (most_recent or most_accessed) and max entries come from the agent's UserMemoryConfig if configured, otherwise sensible defaults (1000 entries, most recent).

2. Pipeline Execution

LifecycleManager runs pipeline
  └─→ PropertySetterTask sets properties based on actions
      └─→ scope=step (cleared after this turn)
      └─→ scope=conversation (lives for the session)
      └─→ scope=longTerm (persisted across conversations)
      └─→ scope=secret (auto-vaulted via SecretsVault)

3. Conversation Teardown

Conversation.postConversationLifecycleTasks()
  └─→ storePropertiesPermanently()
      └─→ All longTerm properties saved via IUserMemoryStore.upsert()
      └─→ Visibility applied at persistence boundary:
          - Explicit visibility on property → used as-is
          - No visibility set → defaults to agent's defaultVisibility (or `global`)

Key insight: Persistent state is a session concern handled at init/teardown — NOT in the pipeline. This means properties "just work" without any task ordering dependencies.

Storage: In v6, all persistent properties are stored in the unified usermemories collection (MongoDB) or usermemories table (PostgreSQL). The legacy properties collection has been removed. See Persistent User Memory for the full unified memory model.

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Secret Properties

Properties with scope=secret are automatically handled by the SecretsVault:

1. During pipeline execution, the secret value is available in memory normally

2. At teardown, the value is encrypted and stored in SecretsVault

3. The in-memory property value is scrubbed (replaced with a vault reference)

4. On next conversation init, the value is loaded from the vault and decrypted

{
  "name": "api_token",
  "valueString": "sk-abc123...",
  "scope": "secret"
}

See Secrets Vault for full documentation.

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Best Practices

1. Use Appropriate Scopes

// ❌ Don't persist temporary data
{"name": "tempResult", "scope": "longTerm"}

// ✅ Use step scope for temporary data
{"name": "tempResult", "scope": "step"}

2. Use fromObjectPath for Extraction

Instead of storing entire API responses, extract only what you need:

{
  "name": "temperature",
  "fromObjectPath": "httpCalls.weatherApi.current.temperature",
  "scope": "conversation"
}

3. Use Visibility for Multi-Agent Scenarios

// Agent-specific memory
{"name": "internal_state", "scope": "longTerm", "visibility": "self"}

// Shared within group conversation
{"name": "group_context", "scope": "longTerm", "visibility": "group"}

// Cross-agent user preference
{"name": "language", "scope": "longTerm", "visibility": "global"}

4. Naming Conventions

• Use snake_case for property names

• Use descriptive, specific names (user_preferred_timezone not tz)

• Prefix agent-specific properties with the agent's domain (support_ticket_id, onboarding_step)

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Related Documentation

• Conversation Memory - How memory flows through the pipeline

• Secrets Vault - Encrypted property storage

• Passing Context Information - External data injection

• Output Templating - Using properties in templates

• LLM Integration - Using properties in LLM prompts

• HTTP Calls - Using properties in API requests