Update langgraph_pipeline.py

langgraph_pipeline.py

@@ -1,200 +1,197 @@
-from langgraph.graph import StateGraph, END
-from typing import Literal
-from data import debug_print
-from langchain_core.messages import  AIMessage
-from langgraph.prebuilt import ToolNode,tools_condition
-from nodes.agent import agent_node,TOOLS
-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()
+from langgraph.graph import StateGraph, END
+from data import debug_print
+from nodes.agent import agent_node,TOOLS
+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()