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| # agents/router_agent.py | |
| import re | |
| from .academic_agent import AcademicAgent | |
| from .drug_info_agent import DrugInfoAgent | |
| from .mnemonic_agent import MnemonicAgent | |
| from .quiz_agent import QuizAgent | |
| from .viva_agent import VivaAgent | |
| class RouterAgent: | |
| def __init__(self, gemini_model=None): | |
| """ | |
| Initializes the router and all specialist agents. | |
| """ | |
| self.academic_agent = AcademicAgent(gemini_model) | |
| self.drug_info_agent = DrugInfoAgent(gemini_model) | |
| self.mnemonic_agent = MnemonicAgent(gemini_model) | |
| self.quiz_agent = QuizAgent(gemini_model) | |
| self.viva_agent = VivaAgent(gemini_model) | |
| def route_query(self, query: str, file_context: str, viva_state: dict, chat_history: list): | |
| """ | |
| Determines the user's intent and routes the query with all necessary | |
| context to the correct specialist agent. | |
| """ | |
| query_lower = query.lower() | |
| # --- Intent Detection Logic --- | |
| # 1. Viva Agent (High priority for session commands) | |
| if viva_state and viva_state.get('active'): | |
| return self.viva_agent.process_query(query, file_context, viva_state) | |
| if any(cmd in query_lower for cmd in ["viva", "interview", "start viva"]): | |
| return self.viva_agent.process_query(query, file_context, viva_state) | |
| # 2. Mnemonic Agent | |
| if any(cmd in query_lower for cmd in ["mnemonic", "memory aid", "remember"]): | |
| return self.mnemonic_agent.process_query(query, file_context, chat_history) | |
| # 3. Quiz Agent | |
| if any(cmd in query_lower for cmd in ["quiz", "test me", "flashcard"]): | |
| return self.quiz_agent.process_query(query, file_context, chat_history) | |
| # 4. Drug Info Agent | |
| drug_keywords = ["drug", "medicine", "medication", "side effect", "dosage"] | |
| specific_drugs = r'\b(paracetamol|ibuprofen|metformin|aspirin|amoxicillin)\b' | |
| if any(cmd in query_lower for cmd in drug_keywords) or re.search(specific_drugs, query_lower): | |
| return self.drug_info_agent.process_query(query, file_context, chat_history) | |
| # 5. Default to Academic Agent for general queries | |
| return self.academic_agent.process_query(query, file_context, chat_history) |