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praisonaiagents.agent.query_rewriter_agent

Core SDK Query Rewriter Agent Module This module provides the QueryRewriterAgent class for transforming user queries to improve retrieval quality in RAG applications. Supported Rewriting Strategies:
  • BASIC: Simple rephrasing for clarity and keyword optimization
  • HYDE: Hypothetical Document Embeddings - generates a hypothetical answer
  • STEP_BACK: Generates higher-level concept questions for complex queries
  • SUB_QUERIES: Decomposes multi-part questions into focused sub-queries
  • MULTI_QUERY: Generates multiple paraphrased versions for ensemble retrieval
  • CONTEXTUAL: Uses conversation history to resolve references and context
Example: from praisonaiagents import QueryRewriterAgent, RewriteStrategy agent = QueryRewriterAgent()

Basic rewriting

result = agent.rewrite(“AI trends”) print(result.rewritten_queries)

HyDE for better semantic matching

result = agent.rewrite(“What is quantum computing?”, strategy=RewriteStrategy.HYDE) print(result.hypothetical_document)

Contextual with chat history

chat_history = [ {“role”: “user”, “content”: “Tell me about Python”}, {“role”: “assistant”, “content”: “Python is a programming language…”} ] result = agent.rewrite(“What about its performance?”, chat_history=chat_history)

With search tools for context-aware rewriting

from praisonaiagents.tools import internet_search agent = QueryRewriterAgent(tools=[internet_search]) result = agent.rewrite(“latest AI developments”) # Searches first, then rewrites

Overview

This module provides components for query_rewriter_agent.

Classes