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Ariav Asulin

Schemas

Section titled “Schemas”

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Pydantic models for API requests and responses.

Location

Section titled “Location”
  • Main schemas: src/youlab_server/server/schemas.py
  • Strategy schemas: src/youlab_server/server/strategy/schemas.py

Agent Schemas

Section titled “Agent Schemas”

CreateAgentRequest

Section titled “CreateAgentRequest”
class CreateAgentRequest(BaseModel):
    user_id: str
    agent_type: str = "tutor"
    user_name: str | None = None

AgentResponse

Section titled “AgentResponse”
class AgentResponse(BaseModel):
    agent_id: str
    user_id: str
    agent_type: str
    agent_name: str
    created_at: datetime | int | None = None

AgentListResponse

Section titled “AgentListResponse”
class AgentListResponse(BaseModel):
    agents: list[AgentResponse]

Chat Schemas

Section titled “Chat Schemas”

ChatRequest

Section titled “ChatRequest”
class ChatRequest(BaseModel):
    agent_id: str
    message: str
    chat_id: str | None = None
    chat_title: str | None = None

ChatResponse

Section titled “ChatResponse”
class ChatResponse(BaseModel):
    response: str
    agent_id: str

StreamChatRequest

Section titled “StreamChatRequest”
class StreamChatRequest(BaseModel):
    agent_id: str
    message: str
    chat_id: str | None = None
    chat_title: str | None = None
    enable_thinking: bool = True

Health Schemas

Section titled “Health Schemas”

HealthResponse

Section titled “HealthResponse”
class HealthResponse(BaseModel):
    status: str
    letta_connected: bool
    honcho_connected: bool = False
    version: str = "0.1.0"

Strategy Schemas

Section titled “Strategy Schemas”

UploadDocumentRequest

Section titled “UploadDocumentRequest”
class UploadDocumentRequest(BaseModel):
    content: str
    tags: list[str] = Field(default_factory=list)

UploadDocumentResponse

Section titled “UploadDocumentResponse”
class UploadDocumentResponse(BaseModel):
    success: bool

AskRequest

Section titled “AskRequest”
class AskRequest(BaseModel):
    question: str

AskResponse

Section titled “AskResponse”
class AskResponse(BaseModel):
    response: str

SearchDocumentsResponse

Section titled “SearchDocumentsResponse”
class SearchDocumentsResponse(BaseModel):
    documents: list[str]

HealthResponse (Strategy)

Section titled “HealthResponse (Strategy)”
class HealthResponse(BaseModel):
    status: str
    agent_exists: bool

Memory Schemas

Section titled “Memory Schemas”

PersonaBlock

Section titled “PersonaBlock”
class PersonaBlock(BaseModel):
    name: str = "Assistant"
    role: str
    capabilities: list[str] = Field(default_factory=list)
    tone: str = "professional"
    verbosity: str = "concise"
    constraints: list[str] = Field(default_factory=list)
    expertise: list[str] = Field(default_factory=list)

HumanBlock

Section titled “HumanBlock”
class HumanBlock(BaseModel):
    name: str | None = None
    role: str | None = None
    current_task: str | None = None
    session_state: SessionState = SessionState.IDLE
    preferences: list[str] = Field(default_factory=list)
    context_notes: list[str] = Field(default_factory=list)
    facts: list[str] = Field(default_factory=list)

SessionState

Section titled “SessionState”
class SessionState(str, Enum):
    IDLE = "idle"
    ACTIVE_TASK = "active_task"
    WAITING_INPUT = "waiting_input"
    THINKING = "thinking"
    ERROR_RECOVERY = "error_recovery"

Template Schemas

Section titled “Template Schemas”

AgentTemplate

Section titled “AgentTemplate”
class AgentTemplate(BaseModel):
    type_id: str
    display_name: str
    description: str = ""
    persona: PersonaBlock
    human: HumanBlock = Field(default_factory=HumanBlock)

Metrics Schemas

Section titled “Metrics Schemas”

ContextMetrics

Section titled “ContextMetrics”
@dataclass
class ContextMetrics:
    persona_chars: int
    human_chars: int
    persona_max: int
    human_max: int


    @property
    def persona_usage(self) -> float
    @property
    def human_usage(self) -> float
    @property
    def total_usage(self) -> float

LLMMetrics

Section titled “LLMMetrics”
@dataclass
class LLMMetrics:
    prompt_tokens: int = 0
    completion_tokens: int = 0
    total_tokens: int = 0
    latency_ms: float = 0
    model: str = ""
Section titled “Related Pages”