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47 lines
1.5 KiB
Python
47 lines
1.5 KiB
Python
from langgraph.graph import StateGraph
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from .configuration import Configuration
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from .nodes import (
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generate_further_questions,
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handle_qna_workflow,
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reformulate_user_query,
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)
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from .state import State
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def build_graph():
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"""
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Build and return the LangGraph workflow.
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This function constructs the researcher agent graph for Q&A workflow.
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The workflow follows a simple path:
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1. Reformulate user query based on chat history
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2. Handle QNA workflow (fetch documents and generate answer)
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3. Generate follow-up questions
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Returns:
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A compiled LangGraph workflow
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"""
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# Define a new graph with state class
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workflow = StateGraph(State, config_schema=Configuration)
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# Add nodes to the graph
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workflow.add_node("reformulate_user_query", reformulate_user_query)
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workflow.add_node("handle_qna_workflow", handle_qna_workflow)
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workflow.add_node("generate_further_questions", generate_further_questions)
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# Define the edges - simple linear flow for QNA
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workflow.add_edge("__start__", "reformulate_user_query")
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workflow.add_edge("reformulate_user_query", "handle_qna_workflow")
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workflow.add_edge("handle_qna_workflow", "generate_further_questions")
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workflow.add_edge("generate_further_questions", "__end__")
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# Compile the workflow into an executable graph
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graph = workflow.compile()
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graph.name = "Surfsense Researcher" # This defines the custom name in LangSmith
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return graph
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# Compile the graph once when the module is loaded
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graph = build_graph()
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