| | from src.agenticRAG.models.state import AgentState
|
| | from src.agenticRAG.components.llm_factory import LLMFactory
|
| | from src.agenticRAG.prompt.prompts import Prompts
|
| |
|
| | class DirectLLMNode:
|
| | """Node for direct LLM processing"""
|
| |
|
| | def __init__(self):
|
| | self.llm = LLMFactory.get_llm()
|
| | self.prompt = Prompts.DIRECT_RESPONSE
|
| |
|
| | def process_direct_llm(self, state: AgentState) -> AgentState:
|
| | """Process direct LLM path"""
|
| |
|
| | try:
|
| | chain = self.prompt | self.llm
|
| |
|
| | response = chain.invoke({"query": state.upgraded_query})
|
| | state.final_response = response.content
|
| | state.metadata["direct_llm_success"] = True
|
| |
|
| | except Exception as e:
|
| | state.final_response = "Sorry, I couldn't process your request at the moment."
|
| | state.metadata["direct_llm_success"] = False
|
| | state.metadata["direct_llm_error"] = str(e)
|
| |
|
| | return state
|
| |
|
| |
|
| | def direct_llm_node(state: AgentState) -> AgentState:
|
| | """Node function for direct LLM processing"""
|
| | direct_processor = DirectLLMNode()
|
| | return direct_processor.process_direct_llm(state) |