modelx / src /graphs /vectorizationAgentGraph.py
nivakaran's picture
Upload folder using huggingface_hub
2473009 verified
"""
vectorizationAgentGraph.py - Vectorization Agent Graph for text-to-vector conversion
"""
from langgraph.graph import StateGraph, END
from src.states.vectorizationAgentState import VectorizationAgentState
from src.nodes.vectorizationAgentNode import VectorizationAgentNode
from src.llms.groqllm import GroqLLM
class VectorizationGraphBuilder:
def __init__(self, llm=None):
self.llm = llm or GroqLLM().get_llm()
def build_graph(self):
node = VectorizationAgentNode(self.llm)
graph = StateGraph(VectorizationAgentState)
graph.add_node("detect_languages", node.detect_languages)
graph.add_node("vectorize_texts", node.vectorize_texts)
graph.add_node("anomaly_detection", node.run_anomaly_detection)
graph.add_node("trending_detection", node.run_trending_detection)
graph.add_node("generate_expert_summary", node.generate_expert_summary)
graph.add_node("format_output", node.format_final_output)
graph.set_entry_point("detect_languages")
graph.add_edge("detect_languages", "vectorize_texts")
graph.add_edge("vectorize_texts", "anomaly_detection")
graph.add_edge("anomaly_detection", "trending_detection")
graph.add_edge("trending_detection", "generate_expert_summary")
graph.add_edge("generate_expert_summary", "format_output")
graph.add_edge("format_output", END)
return graph.compile()
llm = GroqLLM().get_llm()
graph = VectorizationGraphBuilder(llm).build_graph()