haive.agents.rag.self_route.agent

Self-Route RAG Agents.

from typing import Any Implementation of self-routing RAG with dynamic strategy selection and iterative planning. Uses structured output models for complex routing decisions and preprocessing.

Classes

IterativePlan	Iterative processing plan with loop structure.
IterativePlannerAgent	Agent that creates iterative processing plans.
QueryAnalysis	Structured analysis of query for routing decisions.
QueryAnalyzerAgent	Agent that performs structured query analysis for routing.
QueryComplexity	Query complexity levels for routing decisions.
RoutingDecision	Final routing decision with execution plan.
RoutingDecisionAgent	Agent that makes final routing decisions.
RoutingStrategy	Available routing strategies.
SelfRouteRAGAgent	Complete Self-Route RAG agent with structured analysis and iterative planning.

Functions

create_self_route_rag_agent(documents[, llm_config, ...])	Create a Self-Route RAG agent.
get_self_route_rag_io_schema()	Get I/O schema for Self-Route RAG agents.

Module Contents

class haive.agents.rag.self_route.agent.IterativePlan(/, **data)

Bases: pydantic.BaseModel

Iterative processing plan with loop structure.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

data (Any)

class haive.agents.rag.self_route.agent.IterativePlannerAgent

Bases: haive.agents.base.agent.Agent

Agent that creates iterative processing plans.

build_graph()

Build iterative planning graph.

Return type:

haive.core.graph.state_graph.base_graph2.BaseGraph

class haive.agents.rag.self_route.agent.QueryAnalysis(/, **data)

Bases: pydantic.BaseModel

Structured analysis of query for routing decisions.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

data (Any)

class haive.agents.rag.self_route.agent.QueryAnalyzerAgent

Bases: haive.agents.base.agent.Agent

Agent that performs structured query analysis for routing.

build_graph()

Build query analysis graph.

Return type:

haive.core.graph.state_graph.base_graph2.BaseGraph

class haive.agents.rag.self_route.agent.QueryComplexity

Bases: str, enum.Enum

Query complexity levels for routing decisions.

Initialize self. See help(type(self)) for accurate signature.

class haive.agents.rag.self_route.agent.RoutingDecision(/, **data)

Bases: pydantic.BaseModel

Final routing decision with execution plan.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

data (Any)

class haive.agents.rag.self_route.agent.RoutingDecisionAgent

Bases: haive.agents.base.agent.Agent

Agent that makes final routing decisions.

build_graph()

Build routing decision graph.

Return type:

haive.core.graph.state_graph.base_graph2.BaseGraph

class haive.agents.rag.self_route.agent.RoutingStrategy

Bases: str, enum.Enum

Available routing strategies.

Initialize self. See help(type(self)) for accurate signature.

class haive.agents.rag.self_route.agent.SelfRouteRAGAgent

Bases: haive.agents.multi.base.SequentialAgent

Complete Self-Route RAG agent with structured analysis and iterative planning.

classmethod from_documents(documents, llm_config=None, analysis_depth='comprehensive', max_iterations=3, enable_fallback=True, **kwargs)

Create Self-Route RAG agent from documents.

Parameters:

• documents (list[langchain_core.documents.Document]) – Documents to index

• llm_config (haive.core.models.llm.base.LLMConfig | None) – LLM configuration

• analysis_depth (str) – Depth of query analysis

• max_iterations (int) – Maximum iterations for planning

• enable_fallback (bool) – Whether to enable fallback routing

• **kwargs – Additional arguments

Returns:

SelfRouteRAGAgent instance

haive.agents.rag.self_route.agent.create_self_route_rag_agent(documents, llm_config=None, routing_mode='adaptive', **kwargs)

Create a Self-Route RAG agent.

Parameters:

• documents (list[langchain_core.documents.Document]) – Documents for retrieval

• llm_config (haive.core.models.llm.base.LLMConfig | None) – LLM configuration

• routing_mode (str) – Routing mode (“conservative”, “adaptive”, “aggressive”)

• **kwargs – Additional arguments

Returns:

Configured Self-Route RAG agent

Return type:

SelfRouteRAGAgent

haive.agents.rag.self_route.agent.get_self_route_rag_io_schema()

Get I/O schema for Self-Route RAG agents.

Return type:

dict[str, list[str]]