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from langgraph.graph import StateGraph, END
from data import debug_print
from nodes.agent import agent_node
from nodes.intent import oos_handler_node,general_info_handler_node,intent_classifier_node,CreditCardState
from nodes.format import format_output_node
from nodes.compare import compare_node_fn
from nodes.chat import router_node,tool_node,expert_agent_node
from recommender.graph_retrieval import neo4j_error_handler_node,neo4j_retrieval_node
from recommender.vectordb import query_refiner_node
from recommender.vectordb_retrieval import ranked_card_retrieval_node
# Main Graph flow
graph = StateGraph(CreditCardState)
graph.add_node("intent_classifier", intent_classifier_node)
graph.add_node("general_info_handler", general_info_handler_node)
graph.add_node("oos_handler", oos_handler_node)
graph.add_node("query_refiner", query_refiner_node)
graph.add_node("neo4j_retriever", neo4j_retrieval_node)
graph.add_node("neo4j_error_handler", neo4j_error_handler_node)
graph.add_node("ranked_card_retrieval", ranked_card_retrieval_node)
graph.add_node("agent", agent_node)
graph.add_node("format_output", format_output_node)
graph.set_entry_point("intent_classifier")
def route_after_intent_classification(state: CreditCardState):
intent = state["intent"]
debug_print("ROUTE", f"Intent classification routing with intent: '{intent}'")
if intent == "credit-card-recommendation":
return "query_refiner"
elif intent == "general-credit-related":
return "general_info_handler"
else:
return "oos_handler"
def route_after_format_output(state: CreditCardState):
if state.get("trigger_compare", False):
return "compare_node"
elif state.get("trigger_chat", False):
return "chat_node"
else:
return END
graph.add_conditional_edges(
"intent_classifier",
route_after_intent_classification,
{
"query_refiner": "query_refiner",
"general_info_handler": "general_info_handler",
"oos_handler": "oos_handler",
},
)
graph.add_edge("general_info_handler", END)
graph.add_edge("oos_handler", END)
graph.add_edge("query_refiner", "neo4j_retriever")
def route_after_neo4j_retriever(state: CreditCardState):
debug_print("ROUTE", f"neo4j_error: {state.get('neo4j_error')}")
if state.get("neo4j_error", False):
return "neo4j_error_handler"
else:
return "ranked_card_retrieval"
graph.add_conditional_edges(
"neo4j_retriever",
route_after_neo4j_retriever,
{
"neo4j_error_handler": "neo4j_error_handler",
"ranked_card_retrieval": "ranked_card_retrieval",
},
)
graph.add_edge("neo4j_error_handler", END)
graph.add_edge("ranked_card_retrieval", "agent")
graph.add_edge("agent", "format_output")
graph.add_edge("format_output",END)
app = graph.compile()
# invoking function
async def run_langgraph_pipeline(
query: str,
preferences: str,
query_intent: bool,
include_cobranded: bool,
use_eligibility: bool = False,
age=None,
income=None,
cibil=None,
min_joining_fee=None,
max_joining_fee=None,
min_annual_fee=None,
max_annual_fee=None
):
debug_print("PIPELINE", f"Starting pipeline with query: '{query}'")
debug_print("PIPELINE", f"Preferences: '{preferences}'")
debug_print("PIPELINE", f"Query intent: {query_intent}, Include cobranded: {include_cobranded}")
debug_print("PIPELINE", f"Eligibility: {use_eligibility}, Age: {age}, Income: {income}, CIBIL: {cibil}")
debug_print("PIPELINE", f"Join fee: {min_joining_fee}-{max_joining_fee}, Annual fee: {min_annual_fee}-{max_annual_fee}")
inputs = {
"query": query,
"preferences": preferences,
"query_intent": query_intent,
"include_cobranded": include_cobranded,
"use_eligibility": use_eligibility,
"age": age,
"income": income,
"cibil": cibil,
"min_joining_fee": min_joining_fee,
"max_joining_fee": max_joining_fee,
"min_annual_fee": min_annual_fee,
"max_annual_fee": max_annual_fee,
"agent_outcome": None,
"messages": [],
"trigger_chat": False,
"trigger_compare": False,
"selected_cards": [],
"user_message": "",
}
debug_print("PIPELINE", f"Invoking LangGraph app")
result = await app.ainvoke(inputs)
debug_print("PIPELINE", f"LangGraph execution complete")
card_lookup = result.get("card_lookup", {})
for name, desc in card_lookup.items():
debug_print("PIPELINE_CARD_LOOKUP", f"{name} -> Description length: {len(desc) if isinstance(desc, str) else 'N/A'}")
debug_print("PIPELINE", f"Pipeline complete, returning results")
return (
result.get("top_card", "No top card found"),
result.get("top_card_description", []),
result.get("card_rows", []),
result.get("card_names", []),
result.get("card_lookup", {}),
result.get("card_links", [])
)
#utility graph for chat and compare features
def passthrough_node(state: CreditCardState) -> CreditCardState:
return state
def utility_router(state: CreditCardState):
if state.get("trigger_compare", False):
return "compare_node"
elif state.get("trigger_chat", False):
return "chat_agent"
else:
raise ValueError("No trigger flag set for utility graph.")
def should_call_tool(state: CreditCardState):
if state['router_decision'].decision == "call_tool":
return "call_tool"
else:
return "answer_question"
utility_graph = StateGraph(CreditCardState)
utility_graph.add_node("router", passthrough_node)
utility_graph.add_node("compare_node", compare_node_fn)
utility_graph.add_node("chat_router", router_node)
utility_graph.add_node("call_tool", tool_node)
utility_graph.add_node("answer_question", expert_agent_node)
utility_graph.set_entry_point("router")
utility_graph.add_conditional_edges(
"router",
utility_router,
{
"compare_node": "compare_node",
"chat_agent": "chat_router",
},
)
utility_graph.add_conditional_edges(
"chat_router",
should_call_tool,
{
"call_tool": "call_tool",
"answer_question": "answer_question",
}
)
utility_graph.add_edge("call_tool", "answer_question")
utility_graph.add_edge("answer_question", END)
utility_graph.add_edge("compare_node", END)
utility_app = utility_graph.compile()
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