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Learning stores use predefined schemas by default. Extend them with custom fields to capture domain-specific information.

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Extending User Profile

The default UserProfile includes name and preferred_name. Add fields for your domain: 
from dataclasses import dataclass, field
from typing import Optional
from agno.learn.schemas import UserProfile

@dataclass
class CustomerProfile(UserProfile):
    company: Optional[str] = field(
        default=None,
        metadata={"description": "Company or organization"}
    )
    plan_tier: Optional[str] = field(
        default=None,
        metadata={"description": "Subscription tier: free | pro | enterprise"}
    )
    role: Optional[str] = field(
        default=None,
        metadata={"description": "Job title or role"}
    )
    timezone: Optional[str] = field(
        default=None,
        metadata={"description": "User's timezone"}
    )
Use the custom schema: 
from agno.learn import LearningMachine, UserProfileConfig

agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    db=db,
    learning=LearningMachine(
        user_profile=UserProfileConfig(schema=CustomerProfile),
    ),
)

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Field Guidelines

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Use Metadata Descriptions

The metadata={"description": ...} tells the LLM what to extract: 
# Good: Clear description guides extraction
role: Optional[str] = field(
    default=None,
    metadata={"description": "Job title like 'Data Scientist' or 'Engineering Manager'"}
)

# Less effective: No description
role: Optional[str] = None

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Use Optional Fields

All custom fields should be Optional with defaults: 
# Good
company: Optional[str] = field(default=None, metadata={...})

# Bad: Required field will fail if not extracted
company: str

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Document Constrained Values

For fields with known options, list them in the description: 
plan_tier: Optional[str] = field(
    default=None,
    metadata={"description": "Subscription tier: free | pro | enterprise"}
)

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Domain Examples

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SaaS Support

@dataclass
class SupportProfile(UserProfile):
    company: Optional[str] = field(
        default=None,
        metadata={"description": "Company name"}
    )
    plan: Optional[str] = field(
        default=None,
        metadata={"description": "Plan: starter | professional | enterprise"}
    )
    account_id: Optional[str] = field(
        default=None,
        metadata={"description": "Account or customer ID"}
    )
    primary_use_case: Optional[str] = field(
        default=None,
        metadata={"description": "Main use case or workflow"}
    )

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Developer Tools

@dataclass
class DeveloperProfile(UserProfile):
    primary_language: Optional[str] = field(
        default=None,
        metadata={"description": "Primary language: python | javascript | go | rust"}
    )
    framework: Optional[str] = field(
        default=None,
        metadata={"description": "Primary framework: react | django | fastapi"}
    )
    experience_years: Optional[int] = field(
        default=None,
        metadata={"description": "Years of programming experience"}
    )
    editor: Optional[str] = field(
        default=None,
        metadata={"description": "Editor: vscode | neovim | intellij"}
    )

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Extending Other Schemas

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Entity Memory

from agno.learn.schemas import EntityMemory

@dataclass
class CompanyEntity(EntityMemory):
    industry: Optional[str] = field(
        default=None,
        metadata={"description": "Industry: fintech | healthcare | saas"}
    )
    funding_stage: Optional[str] = field(
        default=None,
        metadata={"description": "Stage: seed | series_a | series_b | public"}
    )
    employee_count: Optional[int] = field(
        default=None,
        metadata={"description": "Number of employees"}
    )

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Learned Knowledge

from agno.learn.schemas import LearnedKnowledge

@dataclass
class TechnicalInsight(LearnedKnowledge):
    applicable_languages: Optional[List[str]] = field(
        default=None,
        metadata={"description": "Languages this applies to"}
    )
    performance_impact: Optional[str] = field(
        default=None,
        metadata={"description": "Performance impact: high | medium | low"}
    )
    complexity: Optional[str] = field(
        default=None,
        metadata={"description": "Complexity: simple | moderate | complex"}
    )

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Full Example

from dataclasses import dataclass, field
from typing import Optional
from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.learn import LearningMachine, UserProfileConfig
from agno.learn.schemas import UserProfile
from agno.models.openai import OpenAIResponses

@dataclass
class EnterpriseProfile(UserProfile):
    company: Optional[str] = field(
        default=None,
        metadata={"description": "Company name"}
    )
    department: Optional[str] = field(
        default=None,
        metadata={"description": "Department: engineering | sales | marketing"}
    )
    role: Optional[str] = field(
        default=None,
        metadata={"description": "Job title"}
    )
    region: Optional[str] = field(
        default=None,
        metadata={"description": "Region: NA | EMEA | APAC"}
    )

agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    db=PostgresDb(db_url="postgresql+psycopg://ai:ai@localhost:5532/ai"),
    learning=LearningMachine(
        user_profile=UserProfileConfig(schema=EnterpriseProfile),
    ),
)

# Custom fields extracted automatically
agent.print_response(
    "Hi, I'm Sarah Chen, VP of Engineering at Acme Corp. We're the EMEA team.",
    user_id="sarah@acme.com",
)