Update

main.py

@@ -156,99 +156,44 @@ class HealthcareChatbot:
         # UNIFIED ROUTER CHAIN - Handles both intent classification AND API routing
         self.router_prompt_template = PromptTemplate(
                 template="""
-            You are an advanced AI routing system designed to analyze user queries and determine whether they require direct conversational responses or specific API endpoint actions. Your primary responsibility is to deeply understand user intent and accurately match it against available API capabilities.
+            You are a routing system that determines if a user query matches any available API endpoint.
 
-            ## Core Responsibilities
-            1. Analyze user queries with precision to understand the underlying intent and requirements
-            2. Cross-reference user needs against available API endpoint documentation
-            3. Make intelligent routing decisions based on exact capability matching
-            4. Provide detailed reasoning for all routing decisions to ensure transparency and auditability
-
-            ## Available API Endpoints Documentation
+            ## Available API Endpoints
             {endpoints_documentation}
 
-            ## Current Query Context
-            - User Query: "{user_query}"
-            - Detected Language: {detected_language}
-            - Extracted Keywords: {extracted_keywords}
-            - Sentiment Analysis: {sentiment_analysis}
-
-            ## Decision Framework
-
-            ### Phase 1: Deep Query Understanding
-            Analyze the user query to identify:
-            - Primary action or information request
-            - Specific entities mentioned (dates, specializations, personal data)
-            - Intent indicators (verbs like book, cancel, update, retrieve)
-            - Data requirements (what information is needed or being provided)
-
-            ### Phase 2: Endpoint Capability Matching
-            For each endpoint in the documentation:
-            - Review the endpoint description and purpose
-            - Evaluate if the user's request aligns with the endpoint's functionality
-            - Consider the HTTP method requirements (GET for retrieval, POST for creation, etc.)
-            - Assess parameter compatibility with extracted user data
-
-            ### Phase 3: Routing Decision Logic
-            
-            **IMPORTANT: Default to API_ACTION when there's ANY potential endpoint match**
-            
-            **API_ACTION Classification (PRIMARY):**
-            - User mentions ANY action that could relate to healthcare operations
-            - ANY request for information that might exist in the system
-            - Keywords indicating medical services, appointments, records, or healthcare data
-            - Even vague requests that could be interpreted as needing API data
-            - When user asks about anything related to their health, medical history, or healthcare services
-            - Any mention of booking, scheduling, checking, updating, or retrieving information
-
-            **CONVERSATION Classification (SECONDARY - Use ONLY when certain):**
-            - Pure greetings with no follow-up request (just "hello", "hi")
-            - Thank you messages with no additional requests
-            - Questions ONLY about the bot's capabilities with no data needs
-            - Completely unrelated topics (weather, sports, general knowledge)
-            - Clear goodbye messages with no pending requests
-
-            ### Phase 4: Technical Implementation
-            When API_ACTION is determined:
-            1. Select the most appropriate endpoint based on functionality match
-            2. Determine correct HTTP method from endpoint specifications
-            3. Extract available parameters from user query
-            4. Identify any missing required parameters for proper error handling
-            5. Ensure all parameter names and formats match endpoint documentation exactly
-
-            ## Confidence Assessment
-            Rate your confidence (0.0-1.0) based on:
-            - BIAS TOWARD API_ACTION: Start with 0.7 confidence for any healthcare-related query
-            - Increase confidence when specific actions or data requests are mentioned
-            - Only reduce confidence below 0.5 for pure conversational elements
-            - Healthcare context should maintain high confidence for API_ACTION
-
-            ## Required Output Format
+            ## User Query
+            "{user_query}"
+
+            ## Simple Decision Process
+
+            **Step 1: Check Endpoint Match**
+            - Read each endpoint description in the documentation
+            - Check if the user query aligns with ANY endpoint's purpose/description
+            - If YES → intent = "API_ACTION"
+            - If NO → intent = "CONVERSATION"
+
+            **Step 2: Extract Details (only if API_ACTION)**
+            - Select the matching endpoint
+            - Extract parameters from user query
+            - List missing required parameters
+
+            ## Output Format
             {{
                 "intent": "CONVERSATION|API_ACTION",
                 "confidence": 0.0-1.0,
-                "reasoning": "Comprehensive explanation of analysis process, endpoint matching logic, and decision rationale",
-                "endpoint": "/exact/endpoint/path/from/documentation",
-                "method": "GET|POST|PUT|PATCH|DELETE",
-                "params": {{
-                    "parameter_name": "extracted_value"
-                }},
-                "missing_required": ["list_of_missing_required_parameters"]
+                "reasoning": "Brief explanation of whether query matches any endpoint description",
+                "endpoint": "/endpoint/path/or/null",
+                "method": "HTTP_METHOD/or/null",
+                "params": {{}},
+                "missing_required": []
             }}
 
-            ## Quality Assurance Rules
-            - **CRITICAL**: Favor API_ACTION over CONVERSATION when in doubt
-            - Never fabricate endpoints not present in the documentation
-            - When multiple endpoints could match, select the most appropriate one
-            - If unsure about parameters, still route to API_ACTION and list missing parameters
-            - Only use CONVERSATION for clearly non-actionable queries
-            - Healthcare-related queries should almost always be API_ACTION
-
-            Analyze the provided query using this comprehensive framework and respond with the specified JSON format.
+            Analyze the query against the endpoint descriptions and respond with the JSON format.
             """,
                 input_variables=["user_query", "detected_language", "extracted_keywords", 
                                 "sentiment_analysis", "endpoints_documentation"]
             )
+
         # CONVERSATION CHAIN - Handles conversational responses
         self.conversation_template = PromptTemplate(
             template="""