User Analysis Memory

Learn about users and build comprehensive profiles

Overview

User Analysis Memory extracts user traits from conversations and builds persistent profiles. This enables personalization across sessions and adaptive agent behavior.

Save vs Load

Flag	Purpose
user_analysis_memory	Save: Analyze conversations and persist user profiles
load_user_analysis_memory	Load: Inject user profile into subsequent runs (defaults to user_analysis_memory)

Basic Usage

from upsonic import Agent, Task
from upsonic.storage.memory import Memory
from upsonic.storage.sqlite import SqliteStorage

storage = SqliteStorage(db_file="users.db")

memory = Memory(
    storage=storage,
    session_id="session_001",
    user_id="user_abc",
    user_analysis_memory=True,
    model="anthropic/claude-sonnet-4-5"
)

agent = Agent("anthropic/claude-sonnet-4-5", memory=memory)

result1 = agent.do(Task("I'm a data scientist with 5 years of ML experience"))
result2 = agent.do(Task("What do you know about me?"))
print(result2)  # "You're a data scientist with 5 years of ML experience"

Standalone Usage

User analysis memory works without full session memory. The agent saves and loads user profiles independently:

from upsonic import Agent, Task
from upsonic.storage.memory import Memory
from upsonic.storage.sqlite import SqliteStorage

storage = SqliteStorage(db_file="profiles.db")

memory = Memory(
    storage=storage,
    session_id="session_001",
    user_id="user_abc",
    full_session_memory=False,     # No raw history
    user_analysis_memory=True,     # Save user profile
    model="anthropic/claude-sonnet-4-5"
)

agent = Agent("anthropic/claude-sonnet-4-5", memory=memory)

result1 = agent.do(Task("I'm Alice, a Python developer who prefers dark mode"))
result2 = agent.do(Task("What do you know about me?"))
print(result2)  # Recalls user profile without raw history

Custom Profile Schema

Define specific fields to track:

from pydantic import BaseModel, Field
from typing import Optional, List
from upsonic import Agent, Task
from upsonic.storage.memory import Memory
from upsonic.storage.sqlite import SqliteStorage

class DeveloperProfile(BaseModel):
    name: Optional[str] = Field(None, description="Developer name")
    languages: Optional[List[str]] = Field(None, description="Programming languages")
    experience_years: Optional[int] = Field(None, description="Years of experience")
    preferred_editor: Optional[str] = Field(None, description="Preferred code editor")

storage = SqliteStorage(db_file="developers.db")

memory = Memory(
    storage=storage,
    session_id="session_001",
    user_id="dev_123",
    user_analysis_memory=True,
    user_profile_schema=DeveloperProfile,
    model="anthropic/claude-sonnet-4-5"
)

agent = Agent("anthropic/claude-sonnet-4-5", memory=memory)

result = agent.do(Task("I'm Alice, I use Python and Go, been coding for 8 years, love VS Code"))
print(result)

Dynamic Profile Generation

Let the agent discover and create custom fields:

from upsonic import Agent, Task
from upsonic.storage.memory import Memory
from upsonic.storage.sqlite import SqliteStorage

storage = SqliteStorage(db_file="dynamic.db")

memory = Memory(
    storage=storage,
    session_id="session_001",
    user_id="user_456",
    user_analysis_memory=True,
    dynamic_user_profile=True,  # Agent creates custom fields
    model="anthropic/claude-sonnet-4-5"
)

agent = Agent("anthropic/claude-sonnet-4-5", memory=memory)

result = agent.do(Task("I prefer concise answers, work night shifts, and love hiking"))
print(result)  # Agent adapts to learned preferences

Cross-Session Persistence

User profiles persist across sessions:

from upsonic import Agent, Task
from upsonic.storage.memory import Memory
from upsonic.storage.sqlite import SqliteStorage

storage = SqliteStorage(db_file="profiles.db")

# Session 1: Learn about user
memory1 = Memory(
    storage=storage,
    session_id="session_001",
    user_id="customer_789",
    user_analysis_memory=True,
    model="anthropic/claude-sonnet-4-5"
)
agent1 = Agent("anthropic/claude-sonnet-4-5", memory=memory1)
agent1.do(Task("I'm John, I run a small bakery in Seattle"))

# Session 2: New session, same user - profile is loaded
memory2 = Memory(
    storage=storage,
    session_id="session_002",  # Different session
    user_id="customer_789",     # Same user
    user_analysis_memory=True,
    model="anthropic/claude-sonnet-4-5"
)
agent2 = Agent("anthropic/claude-sonnet-4-5", memory=memory2)
result = agent2.do(Task("Remind me what you know about me"))
print(result)  # "You're John, you run a bakery in Seattle"

Save-Only Mode

Save profiles for analytics without injecting them into the agent’s context:

from upsonic import Agent, Task
from upsonic.storage.memory import Memory
from upsonic.storage.sqlite import SqliteStorage

storage = SqliteStorage(db_file="analytics.db")

memory = Memory(
    storage=storage,
    session_id="session_001",
    user_id="user_789",
    user_analysis_memory=True,          # Save profiles
    load_user_analysis_memory=False,    # Don't inject into context
    model="anthropic/claude-sonnet-4-5"
)

agent = Agent("anthropic/claude-sonnet-4-5", memory=memory)
result = agent.do(Task("I also speak Spanish and French"))
print(result)

Update Modes

Mode	Behavior
'update'	Merge new traits with existing profile (default)
'replace'	Replace entire profile with new traits

from upsonic import Agent, Task
from upsonic.storage.memory import Memory
from upsonic.storage.sqlite import SqliteStorage

storage = SqliteStorage(db_file="modes.db")

memory = Memory(
    storage=storage,
    session_id="session_001",
    user_id="user_123",
    user_analysis_memory=True,
    user_memory_mode='update',
    model="anthropic/claude-sonnet-4-5"
)

agent = Agent("anthropic/claude-sonnet-4-5", memory=memory)
result = agent.do(Task("I also speak Spanish and French"))
print(result)

Parameters

Parameter	Type	Default	Description
user_analysis_memory	bool	False	Save user profiles
load_user_analysis_memory	bool | None	None	Inject profiles into runs (defaults to user_analysis_memory)
user_id	str	auto-generated	User identifier
model	str | Model	(required)	Model for trait extraction
user_profile_schema	BaseModel | None	None	Custom profile schema
dynamic_user_profile	bool	False	Auto-generate profile fields
user_memory_mode	Literal['update', 'replace']	'update'	Profile update strategy