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927c050 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 | """Node functions for the multi-agent graph."""
import logging
from typing import Optional
from langchain_core.messages import SystemMessage, HumanMessage
from langchain_core.runnables import RunnableConfig
from langgraph.store.base import BaseStore
from langgraph.types import interrupt
from src.state import State
from src.models import UserInput, UserProfile
from src.agents.prompts import (
generate_music_assistant_prompt,
STRUCTURED_EXTRACTION_PROMPT,
VERIFICATION_PROMPT,
CREATE_MEMORY_PROMPT,
)
from src.db.database import get_engine, normalize_phone
logger = logging.getLogger(__name__)
def get_customer_id_from_identifier(identifier: str) -> Optional[int]:
if not identifier or not identifier.strip():
return None
identifier = identifier.strip()
engine = get_engine()
try:
from sqlalchemy import text
if "@" in identifier:
with engine.connect() as conn:
result = conn.execute(
text("SELECT CustomerId FROM Customer WHERE LOWER(Email) = LOWER(:email)"),
{"email": identifier},
)
row = result.fetchone()
if row:
return int(row[0])
if identifier.isdigit():
with engine.connect() as conn:
result = conn.execute(
text("SELECT CustomerId FROM Customer WHERE CustomerId = :cid"),
{"cid": int(identifier)},
)
row = result.fetchone()
if row:
return int(row[0])
normalized_input = normalize_phone(identifier)
if normalized_input and len(normalized_input) >= 5:
with engine.connect() as conn:
result = conn.execute(text("SELECT CustomerId, Phone FROM Customer WHERE Phone IS NOT NULL"))
for row in result:
db_phone_normalized = normalize_phone(str(row[1]))
if db_phone_normalized == normalized_input:
return int(row[0])
except Exception as e:
logger.error(f"Error looking up customer by identifier '{identifier}': {e}")
return None
def format_user_memory(user_data: dict) -> str:
try:
profile = user_data.get("memory")
if profile and hasattr(profile, "music_preferences") and profile.music_preferences:
return f"Music Preferences: {', '.join(profile.music_preferences)}"
except Exception as e:
logger.error(f"Error formatting user memory: {e}")
return ""
def create_music_assistant_node(llm, music_tools):
llm_with_tools = llm.bind_tools(music_tools)
def music_assistant(state: State, config: RunnableConfig):
memory = state.get("loaded_memory", "None") or "None"
prompt = generate_music_assistant_prompt(memory)
messages = [SystemMessage(content=prompt)]
if state.get("customer_id"):
messages.append(
SystemMessage(content=f"The current verified customer ID is: {state['customer_id']}")
)
messages.extend(state["messages"])
logger.info(f"Music assistant invoked with {len(state['messages'])} conversation messages")
response = llm_with_tools.invoke(messages)
return {"messages": [response]}
return music_assistant
def should_continue(state: State, config: RunnableConfig) -> str:
messages = state["messages"]
last_message = messages[-1]
if not last_message.tool_calls:
return "end"
return "continue"
def should_interrupt(state: State, config: RunnableConfig) -> str:
if state.get("customer_id") is not None:
return "continue"
return "interrupt"
def create_verify_info_node(llm):
structured_llm = llm.with_structured_output(schema=UserInput)
def verify_info(state: State, config: RunnableConfig):
if state.get("customer_id") is not None:
logger.info(f"Customer already verified: {state['customer_id']}")
return {}
user_input = state["messages"][-1]
logger.info(f"Verification attempt with message: {getattr(user_input, 'content', '')[:100]}")
try:
parsed_info = structured_llm.invoke(
[SystemMessage(content=STRUCTURED_EXTRACTION_PROMPT)] + [user_input]
)
identifier = parsed_info.identifier
logger.info(f"Extracted identifier: '{identifier}'")
except Exception as e:
logger.error(f"Error parsing user input for verification: {e}")
identifier = ""
customer_id = None
if identifier:
customer_id = get_customer_id_from_identifier(identifier)
logger.info(f"DB lookup result: customer_id={customer_id}")
if customer_id is not None:
intent_message = SystemMessage(
content=(
f"Customer verified successfully. "
f"The verified customer_id is {customer_id}. "
f"Use this customer_id for all invoice and purchase lookups."
)
)
return {
"customer_id": str(customer_id),
"messages": [intent_message],
}
else:
response = llm.invoke(
[SystemMessage(content=VERIFICATION_PROMPT)] + state["messages"]
)
return {"messages": [response]}
return verify_info
def human_input(state: State, config: RunnableConfig):
user_input = interrupt("Please provide input.")
return {"messages": [HumanMessage(content=user_input)]}
def load_memory(state: State, config: RunnableConfig, store: BaseStore):
user_id = str(state.get("customer_id", ""))
if not user_id:
return {"loaded_memory": ""}
namespace = ("memory_profile", user_id)
try:
existing_memory = store.get(namespace, "user_memory")
if existing_memory and existing_memory.value:
formatted = format_user_memory(existing_memory.value)
logger.info(f"Loaded memory for customer {user_id}: {formatted}")
return {"loaded_memory": formatted}
except Exception as e:
logger.error(f"Error loading memory for user {user_id}: {e}")
return {"loaded_memory": ""}
def create_memory_node(llm):
def create_memory(state: State, config: RunnableConfig, store: BaseStore):
user_id = str(state.get("customer_id", ""))
if not user_id:
return {}
namespace = ("memory_profile", user_id)
try:
existing_preferences = []
existing_memory = store.get(namespace, "user_memory")
formatted_memory = ""
if existing_memory and existing_memory.value:
mem_dict = existing_memory.value
profile = mem_dict.get("memory")
if profile and hasattr(profile, "music_preferences"):
existing_preferences = list(profile.music_preferences or [])
formatted_memory = f"Music Preferences: {', '.join(existing_preferences)}"
recent_messages = state["messages"][-10:]
conversation_summary = "\n".join(
f"{getattr(msg, 'type', 'unknown')}: {getattr(msg, 'content', '')}"
for msg in recent_messages
if getattr(msg, "content", "")
)
formatted_prompt = CREATE_MEMORY_PROMPT.format(
conversation=conversation_summary,
memory_profile=formatted_memory or "Empty, no existing profile",
)
updated_memory = llm.with_structured_output(UserProfile).invoke(
[SystemMessage(content=formatted_prompt)]
)
new_prefs = updated_memory.music_preferences or []
if not new_prefs and existing_preferences:
logger.info(f"Memory unchanged for customer {user_id} (preserving existing preferences)")
return {}
merged_prefs = list(set(existing_preferences + new_prefs))
updated_memory.music_preferences = merged_prefs
updated_memory.customer_id = user_id
store.put(namespace, "user_memory", {"memory": updated_memory})
logger.info(f"Memory updated for customer {user_id}: {merged_prefs}")
except Exception as e:
logger.error(f"Error creating/updating memory for user {user_id}: {e}")
return create_memory
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