agents.rag.adaptive_tools.agent¶

Adaptive RAG with Tools Integration Agents.

from typing import Any Implementation of adaptive RAG with tool integration and ReAct patterns. Includes Google Search integration, tool selection, and dynamic routing based on query needs.

Classes¶

`AdaptiveToolsRAGAgent`	Complete Adaptive RAG agent with tools integration and ReAct patterns.
`AdaptiveToolsResult`	Complete result from adaptive tools RAG.
`QueryNeed`	Query need categories for tool selection.
`SearchIntegrationAgent`	Agent that integrates external search tools.
`SearchResult`	Results from search tools.
`ToolSelection`	Tool selection analysis and recommendations.
`ToolSelectionAgent`	Agent that selects optimal tools based on query analysis.
`ToolType`	Available tool types for adaptive RAG.

Functions¶

`create_adaptive_synthesis_callable`(llm_config)	Create callable function for adaptive synthesis.
`create_adaptive_tools_rag_agent`(documents[, ...])	Create an Adaptive Tools RAG agent.
`create_google_search_callable`(llm_config)	Create callable function for Google search integration.
`create_tool_selector_callable`(llm_config)	Create callable function for tool selection.
`get_adaptive_tools_rag_io_schema`()	Get I/O schema for Adaptive Tools RAG agents.

Module Contents¶

class agents.rag.adaptive_tools.agent.AdaptiveToolsRAGAgent(config)¶

Bases: haive.agents.multi.base.SequentialAgent

Complete Adaptive RAG agent with tools integration and ReAct patterns.

Init .

Parameters:: config (SequentialAgentConfig) – [TODO: Add description]

classmethod from_documents(documents, llm_config=None, enable_google_search=True, enable_local_retrieval=True, **kwargs)¶

Create Adaptive Tools RAG agent from documents.

Parameters:

documents (list[langchain_core.documents.Document]) – Documents to index for local retrieval
llm_config (haive.core.models.llm.base.LLMConfig | None) – LLM configuration
enable_google_search (bool) – Whether to enable Google Search integration
enable_local_retrieval (bool) – Whether to enable local document retrieval
**kwargs – Additional arguments

Returns:

AdaptiveToolsRAGAgent instance

class agents.rag.adaptive_tools.agent.AdaptiveToolsResult(/, **data)¶

Bases: pydantic.BaseModel

Complete result from adaptive tools RAG.

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 agents.rag.adaptive_tools.agent.QueryNeed¶

Bases: str, enum.Enum

Query need categories for tool selection.

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

class agents.rag.adaptive_tools.agent.SearchIntegrationAgent¶

Bases: haive.agents.base.agent.Agent

Agent that integrates external search tools.

build_graph()¶

Build search integration graph.

Return type:: haive.core.graph.state_graph.base_graph2.BaseGraph

class agents.rag.adaptive_tools.agent.SearchResult(/, **data)¶

Bases: pydantic.BaseModel

Results from search tools.

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 agents.rag.adaptive_tools.agent.ToolSelection(/, **data)¶

Bases: pydantic.BaseModel

Tool selection analysis and recommendations.

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 agents.rag.adaptive_tools.agent.ToolSelectionAgent¶

Bases: haive.agents.base.agent.Agent

Agent that selects optimal tools based on query analysis.

build_graph()¶

Build tool selection graph.

Return type:: haive.core.graph.state_graph.base_graph2.BaseGraph

class agents.rag.adaptive_tools.agent.ToolType¶

Bases: str, enum.Enum

Available tool types for adaptive RAG.

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

agents.rag.adaptive_tools.agent.create_adaptive_synthesis_callable(llm_config)¶

Create callable function for adaptive synthesis.

Parameters:: llm_config (haive.core.models.llm.base.LLMConfig)

agents.rag.adaptive_tools.agent.create_adaptive_tools_rag_agent(documents, llm_config=None, tools_mode='full', **kwargs)¶

Create an Adaptive Tools RAG agent.

Parameters:

documents (list[langchain_core.documents.Document]) – Documents for local retrieval
llm_config (haive.core.models.llm.base.LLMConfig | None) – LLM configuration
tools_mode (str) – Tools mode (“full”, “search_only”, “local_only”)
**kwargs – Additional arguments

Returns:

Configured Adaptive Tools RAG agent

Return type:

AdaptiveToolsRAGAgent

agents.rag.adaptive_tools.agent.create_google_search_callable(llm_config)¶

Create callable function for Google search integration.

Parameters:: llm_config (haive.core.models.llm.base.LLMConfig)

agents.rag.adaptive_tools.agent.create_tool_selector_callable(llm_config)¶

Create callable function for tool selection.

Parameters:: llm_config (haive.core.models.llm.base.LLMConfig)

agents.rag.adaptive_tools.agent.get_adaptive_tools_rag_io_schema()¶

Get I/O schema for Adaptive Tools RAG agents.

Return type:: dict[str, list[str]]