Fix: chat_history addition

agents/drug_info_agent.py

@@ -2,57 +2,83 @@
 """
 Drug Information Agent - Handles drug-related queries using Generative AI.
 """
+# agents/drug_info_agent.py
+
 import re
 from .agent_helpers import format_history_for_prompt
+
 class DrugInfoAgent:
     def __init__(self, gemini_model=None):
         """
         Initializes the agent with the Gemini model.
-
-        Args:
-            gemini_model: An instance of the Gemini model client.
         """
         self.model = gemini_model
 
-def process_query(self, query: str, file_context: str = "", chat_history: list = None):
+    def _extract_drug_name(self, query: str) -> str:
+        """
+        A simple helper to extract the drug name from the user's query.
+        This is a crucial step for this agent's reliability.
+        """
+        # Remove common phrases and get the potential drug name
+        query_lower = query.lower()
+        patterns = [
+            "what are the side effects of", "tell me about", "information on", 
+            "info on", "about the drug", "what is", "about"
+        ]
+        
+        cleaned_query = query_lower
+        for p in patterns:
+            cleaned_query = cleaned_query.replace(p, "")
+        
+        # A simple assumption: the first significant word is the drug name.
+        # This can be improved with more advanced NLP in the future.
+        match = re.search(r'\b[a-zA-Z0-9]+\b', cleaned_query)
+        if match:
+            return match.group(0).title()
+        return ""
+
+    def process_query(self, query: str, file_context: str = "", chat_history: list = None):
         """
         Processes a query to retrieve information about a specific drug.
-
-        Args:
-            query (str): The user's full query (e.g., "Tell me about Metformin").
-            file_context (str): Optional context from uploaded files.
-            chat_history (list): The history of the conversation.
-
-        Returns:
-            dict: A dictionary containing the response message and agent metadata.
         """
         if not self.model:
             return {'message': "💊 The pharmacy database is offline! The Gemini API key is missing.", 'agent_used': 'drug_info', 'status': 'error_no_api_key'}
 
+        # --- RESTORED LOGIC ---
+        drug_name = self._extract_drug_name(query)
+        if not drug_name:
+             # If the history also doesn't provide context, ask the user.
+            if "drug" not in str(chat_history).lower():
+                return {
+                    'message': "Please tell me which drug you want to know about! For example, try 'info on Paracetamol'.",
+                    'agent_used': 'drug_info',
+                    'status': 'error_no_topic'
+                }
+        
         history_for_prompt = format_history_for_prompt(chat_history)
         
-        prompt = f"""You are a cautious AI Pharmacist Tutor like Chanakya  providing educational information.
+        prompt = f"""You are a cautious AI Pharmacist Tutor providing educational information like ancient india's Chanakya.
 
 **CRITICAL SAFETY INSTRUCTION:** START EVERY RESPONSE with this disclaimer: "⚠️ **Disclaimer:** This information is for educational purposes ONLY and is not a substitute for professional medical advice."
 
-Your reasoning process must be:
-1. Analyze the CONVERSATION HISTORY and the CURRENT QUESTION to identify the drug being discussed.
-2. Provide a structured summary for that drug. If the user asks a follow-up (e.g., "what about its side effects?"), answer that specific question in the context of the drug already being discussed.
+Your reasoning process is:
+1. Analyze the CONVERSATION HISTORY and CURRENT QUESTION to identify the specific drug being discussed. The primary drug to focus on is: **{drug_name}**.
+2. If the user asks a follow-up (e.g., "what about its dosage forms?"), answer that specific question in the context of the drug.
+3. Provide a structured summary.
 
 CONVERSATION HISTORY:
 {history_for_prompt}
 CURRENT QUESTION:
 User: {query}
 
-Provide a structured summary including: Therapeutic Class, MOA, Indications, Side Effects, and Warnings. DO NOT provide specific dosages.
+Provide a structured summary for the drug **{drug_name}** including: Therapeutic Class, Mechanism of Action (MOA), Indications, Side Effects, and Warnings. DO NOT provide specific dosages.
 """
         try:
             response = self.model.generate_content(prompt)
             return {'message': response.text, 'agent_used': 'drug_info', 'status': 'success'}
         except Exception as e:
             print(f"Drug Info Agent Error: {e}")
-            return {'message': f"Sorry, I couldn't access the drug database. Error: {e}", 'agent_used': 'drug_info', 'status': 'error_api_call'}
-
+            return {'message': f"Sorry, I couldn't access the drug database. An error occurred.", 'agent_used': 'drug_info', 'status': 'error_api_call'}
 #     def process_query(self, query: str, file_context: str = "", chat_history: list = None):
 #         """
 #         Processes a query to retrieve information about a specific drug.