next

logs/access.log

@@ -1824,3 +1824,14 @@
 2025-11-14 15:21:39,030 | INFO | access_logger | app.py:20 | Response status: 200
 2025-11-14 15:34:22,638 | INFO | access_logger | app.py:18 | Request: POST http://127.0.0.1:8000/api/analytics-chatbot
 2025-11-14 15:34:30,193 | INFO | access_logger | app.py:20 | Response status: 200
+2025-11-17 12:34:36,598 | INFO | access_logger | app.py:18 | Request: GET http://127.0.0.1:8000/
+2025-11-17 12:34:36,599 | INFO | access_logger | app.py:20 | Response status: 200
+2025-11-17 12:34:37,112 | INFO | access_logger | app.py:18 | Request: GET http://127.0.0.1:8000/favicon.ico
+2025-11-17 12:34:37,113 | INFO | access_logger | app.py:20 | Response status: 404
+2025-11-17 12:34:40,115 | INFO | access_logger | app.py:18 | Request: GET http://127.0.0.1:8000/docs
+2025-11-17 12:34:40,115 | INFO | access_logger | app.py:20 | Response status: 200
+2025-11-17 12:34:40,269 | INFO | access_logger | app.py:18 | Request: GET http://127.0.0.1:8000/openapi.json
+2025-11-17 12:34:40,276 | INFO | access_logger | app.py:20 | Response status: 200
+2025-11-17 12:35:00,599 | INFO | access_logger | app.py:18 | Request: POST http://127.0.0.1:8000/api/analytics-chatbot
+2025-11-17 12:35:24,309 | INFO | access_logger | app.py:20 | Response status: 200
+2025-11-17 12:36:00,652 | INFO | access_logger | app.py:18 | Request: POST http://127.0.0.1:8000/api/analytics-chatbot

src/genai/analytics_chatbot/agent.py

@@ -30,8 +30,8 @@ class ChatbotAgent:
         graph_builder.add_edge(START, "fetch_last_message")
         graph_builder.add_edge("fetch_last_message", 'retrieve_api_endpoints')
         graph_builder.add_edge("retrieve_api_endpoints", 'retrieve_exact_endpoint')
-        graph_builder.add_edge("retrieve_exact_endpoint", 'check_query_type')
-        graph_builder.add_edge("check_query_type", 'fetch_parameters')
+        graph_builder.add_edge("retrieve_exact_endpoint", 'fetch_parameters')
+        # graph_builder.add_edge("check_query_type", 'fetch_parameters')
         graph_builder.add_edge("fetch_parameters", 'fetch_data')
         graph_builder.add_edge("fetch_data", END)
         graph_builder.add_edge("backup_response", END)

src/genai/analytics_chatbot/utils/nodes.py

@@ -111,17 +111,18 @@ class FetchParametersNode:
                 result = self.llm.with_structured_output(ParameterFormatter, method='function_calling').invoke(messages)
                 parameters_values = {k: (process_query(v) if isinstance(v, str) else v) for k, v in result.parameters_values.items()}
                             
-                if 'single_influencer_query' in state['query_type']:
-                    print('The parameter values:', parameters_values)
-                    return {
-                        'parameters_values':parameters_values
-                    }
-                elif 'aggregate_query' in state['query_type']:
-                    parameters_values['influencer_username'] = ['divyadhakal_','munachiya','mydarlingfood','_its.me.muskan_']
-                    print('The parameter values:', parameters_values)
-                    return{
-                        'parameters_values': parameters_values
-                    }
+                # if 'single_influencer_query' in state['query_type']:
+                #     print('The parameter values:', parameters_values)
+                #     return {
+                #         'parameters_values':parameters_values
+                #     }
+                # elif 'aggregate_query' in state['query_type']:
+                #     parameters_values['influencer_username'] = ['divyadhakal_','munachiya','mydarlingfood','_its.me.muskan_']
+                #     print('The parameter values:', parameters_values)
+                #     return{
+                #         'parameters_values': parameters_values
+                #     }
+                return {'parameters_values': parameters_values}
         except Exception as e:
             print('Error occoured:', e)
             return {'error_message': str(e)}
@@ -148,6 +149,7 @@ class FetchDataNode:
 
     def run(self, state:State):
         try:
+            state['query_type']='single_influencer_query'
 
             print('Entered to fetch data')
             url = f'''{self.base_url}{state['endpoint']}'''
@@ -165,22 +167,22 @@ class FetchDataNode:
                 print('Data from api:', response)
                 return {'response':response.json()}
             
-            elif 'aggregate_query' in state['query_type']:
-                print('Entered to aggregrated query execution')
-                print(state['parameters_values'])
-                params = state["parameters_values"]
-                if "influencer_username" in params and isinstance(params["influencer_username"], list):
-                    results = {}
-
-                    # Iterate through each influencer username
-                    for username in params["influencer_username"]:
-                        current_params = params.copy()
-                        current_params["influencer_username"] = username
-
-                        response = requests.get(url, params=current_params, headers=self.headers)
-                        results[username] = response.json()  # Store influencer-wise response
-                    print('Data from api:', response)
-                    return {"response": results}
+            # elif 'aggregate_query' in state['query_type']:
+            #     print('Entered to aggregrated query execution')
+            #     print(state['parameters_values'])
+            #     params = state["parameters_values"]
+            #     if "influencer_username" in params and isinstance(params["influencer_username"], list):
+            #         results = {}
+
+            #         # Iterate through each influencer username
+            #         for username in params["influencer_username"]:
+            #             current_params = params.copy()
+            #             current_params["influencer_username"] = username
+
+            #             response = requests.get(url, params=current_params, headers=self.headers)
+            #             results[username] = response.json()  # Store influencer-wise response
+            #         print('Data from api:', response)
+            #         return {"response": results}
             
 
         except Exception as e: