Implemented caching'

.gitignore

@@ -6,4 +6,5 @@ logs
 delete_pycache.py
 docker_file_for_actions.txt
 vercel.json
-.github/workflows/actions_cicd.txt
+.github/workflows/actions_cicd.txt
+check.py

api/routers/analytics_chatbot.py

@@ -1,7 +1,10 @@
 import ast
+import os
 import json
+import hashlib
 import logging
 from fastapi import APIRouter
+from redis import Redis
 from fastapi.responses import StreamingResponse
 from api.stored_data import stored_data
 from src.genai.analytics_chatbot.agent import ChatbotAgent
@@ -10,20 +13,39 @@ from api.schemas.analytics_chatbot import UserMessage
 
 app_logger = logging.getLogger("app_logger")
 error_logger = logging.getLogger("error_logger")
+password=os.environ['REDIS_PASSWORD']
+host = os.environ['REDIS_HOST']
+port = os.environ['REDIS_PORT']
+print('password:', password)
 
 router = APIRouter()
 agent=ChatbotAgent()
-graph = agent.chatbot_graph()  
+graph = agent.chatbot_graph() 
+redis_client = Redis(host=host, port=port, db=0, decode_responses=True, username="default",password=password) 
 
 @router.get("/analytics-chatbot")
 def get_analytics(msg:str):
     # user_query=process_query(msg)
+    cache_key = f"analytics:{hashlib.md5(msg.encode()).hexdigest()}"
+    
+    cached_response = redis_client.get(cache_key)
+    if cached_response:
+        print("Cache hit")
+        return json.loads(cached_response)
+    
     config={"configurable": {"thread_id": "analytics-chatbot-thread"},"run_name":"analytics-chatbot"}
     result=graph.invoke({'messages':msg},config=config)
+    print('Final Result:', result)
+    response_to_cache = {}
     if result.get('backup_data') is not None:
-        return {'backup_response': result['backup_data']}
+        response_to_cache = {'backup_response': result['backup_data']}
     else:
-        return {
+        response_to_cache = {
             'response': result['response'],
             'endpoint': result['endpoint']
         }
+
+    # Save to Redis with TTL (e.g., 1 hour)
+    redis_client.set(cache_key, json.dumps(response_to_cache), ex=3600)  # ex=seconds
+
+    return response_to_cache

app.py

@@ -1,13 +1,12 @@
 from fastapi import FastAPI, Request
 from logger_config import setup_loggers
 import logging
-from api.routers import orchestration, context_analysis, ideation , human_idea_refining , brainstorm , generate_final_story , generate_image, show_analytics, analytics_chatbot
+from api.routers import orchestration, context_analysis, ideation , brainstorm , generate_final_story , generate_image, show_analytics, analytics_chatbot
 
 setup_loggers()
 app = FastAPI()
 
 
-# Get loggers
 app_logger = logging.getLogger("app_logger")
 error_logger = logging.getLogger("error_logger")
 access_logger = logging.getLogger("access_logger")

logs/access.log

@@ -1509,3 +1509,31 @@
 2025-10-17 13:54:02,382 | INFO | access_logger | app.py:21 | Response status: 200
 2025-10-17 13:54:26,472 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=i%20want%20the%20analytics%20of%20last%2010%20days%20of%20muna%20chiya
 2025-10-17 13:54:36,464 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-17 15:46:54,304 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=i%20want%20the%20analytics%20of%20last%2010%20days%20of%20muna%20chiya
+2025-10-17 15:47:04,686 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-17 15:47:10,111 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=i%20want%20the%20analytics%20of%20last%2010%20days%20of%20muna%20chiya
+2025-10-17 15:47:16,471 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-17 15:49:07,624 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=i%20want%20the%20analytics%20of%20last%2010%20days%20of%20muna%20chiya
+2025-10-17 15:49:12,250 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-17 15:49:16,022 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=i%20want%20the%20analytics%20of%20last%2010%20days%20of%20muna%20chiya
+2025-10-17 15:49:21,139 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-17 15:51:43,342 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=i%20want%20the%20analytics%20of%20last%2010%20days%20of%20muna%20chiya
+2025-10-17 15:51:47,715 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-17 15:51:51,793 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=i%20want%20the%20analytics%20of%20last%2010%20days%20of%20muna%20chiya
+2025-10-17 15:51:56,726 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-17 16:00:44,222 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=i%20want%20the%20analytics%20of%20last%2010%20days%20of%20muna%20chiya
+2025-10-17 16:00:55,100 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-17 16:00:59,383 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=i%20want%20the%20analytics%20of%20last%2010%20days%20of%20muna%20chiya
+2025-10-17 16:01:04,084 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-17 16:03:18,574 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=i%20want%20the%20analytics%20of%20last%2010%20days%20of%20muna%20chiya
+2025-10-17 16:05:48,001 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=i%20want%20the%20analytics%20of%20last%2010%20days%20of%20muna%20chiya
+2025-10-17 16:05:52,416 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-17 16:06:13,136 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=i%20want%20the%20analytics%20of%20last%2010%20days%20of%20muna%20chiya
+2025-10-17 16:06:17,871 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-26 15:27:54,555 | INFO | access_logger | app.py:18 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=I%20want%20sentiment%20distribution%20of%20divya%20dhakal
+2025-10-26 15:34:02,449 | INFO | access_logger | app.py:18 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=I%20want%20sentiment%20distribution%20of%20divya%20dhakal
+2025-10-26 15:34:21,305 | INFO | access_logger | app.py:20 | Response status: 200
+2025-10-26 15:34:25,929 | INFO | access_logger | app.py:18 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=I%20want%20sentiment%20distribution%20of%20divya%20dhakal
+2025-10-26 15:34:26,248 | INFO | access_logger | app.py:20 | Response status: 200
+2025-10-26 15:41:29,547 | INFO | access_logger | app.py:18 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=I%20want%20sentiment%20distribution%20of%20divya%20dhakal
+2025-10-26 15:41:32,818 | INFO | access_logger | app.py:20 | Response status: 200

requirements.txt

@@ -1,26 +1,26 @@
 langgraph==0.6.5
-langsmith 
-langchain_groq
+langsmith==0.4.16
+langchain_groq==0.3.7
 pydantic==2.11.7
-datasets 
-faiss-cpu
-dotenv
-fastapi
-uvicorn
-numpy 
+datasets==4.0.0
+faiss-cpu==1.12.0
+dotenv==0.9.9
+fastapi==0.116.1
+uvicorn==0.36.0
+numpy==2.3.2
 pandas
-langchain_huggingface
-python-multipart
-langmem
-streamlit
-requests
-langchain_openai
-nltk
-scikit-learn
-pandas
-langchain-community
-tiktoken
-langchain-anthropic
-pytest
-langchain_google_genai
+langchain_huggingface==0.3.1
+python-multipart==0.0.20
+langmem==0.0.29
+streamlit==1.48.1
+requests==2.32.5
+langchain_openai==0.3.31
+nltk==3.9.1
+scikit-learn==1.7.1
+langchain-community==0.3.27
+tiktoken==0.11.0
+langchain-anthropic==0.3.19
+pytest==8.4.1
+langchain_google_genai==2.1.9
 mangum
+redis==7.0.0

src/genai/analytics_chatbot/agent.py

@@ -3,18 +3,25 @@ from langgraph.checkpoint.memory import MemorySaver
 from .utils.state import State
 from .utils.nodes import FetchDataNode , FetchLastMessage , RetrievePossibleEndpoints , FetchParametersNode , RetrieveExactEndpoint, BackupRetrievalNode, RoutingNode
 
+fetch_last_message_node = FetchLastMessage()
+retrieve_api_endpoints_node = RetrievePossibleEndpoints()
+retrieve_exact_endpoint_node = RetrieveExactEndpoint()
+fetch_parameters_node = FetchParametersNode()
+fetch_data_node = FetchDataNode()
+backup_response_node = BackupRetrievalNode()
+
 class ChatbotAgent:
     def __init__(self):
         self.memory = MemorySaver()
 
     def chatbot_graph(self):
         graph_builder= StateGraph(State)
-        graph_builder.add_node("fetch_last_message", FetchLastMessage().run)
-        graph_builder.add_node("retrieve_api_endpoints", RetrievePossibleEndpoints().run)
-        graph_builder.add_node("retrieve_exact_endpoint", RetrieveExactEndpoint().run)
-        graph_builder.add_node("fetch_parameters", FetchParametersNode().run)
-        graph_builder.add_node("fetch_data", FetchDataNode().run)
-        graph_builder.add_node("backup_response", BackupRetrievalNode().run)
+        graph_builder.add_node("fetch_last_message", fetch_last_message_node.run)
+        graph_builder.add_node("retrieve_api_endpoints", retrieve_api_endpoints_node.run)
+        graph_builder.add_node("retrieve_exact_endpoint", retrieve_exact_endpoint_node.run)
+        graph_builder.add_node("fetch_parameters", fetch_parameters_node.run)
+        graph_builder.add_node("fetch_data", fetch_data_node.run)
+        graph_builder.add_node("backup_response", backup_response_node.run)
         
         graph_builder.add_edge(START, "fetch_last_message")
         graph_builder.add_edge("fetch_last_message", 'retrieve_api_endpoints')

src/genai/analytics_chatbot/utils/nodes.py

@@ -35,6 +35,7 @@ class RetrievePossibleEndpoints:
         self.results = []
 
     def run(self,state:State):
+        print('Gone to retrieve possible endpoints')
         query_embedding = np.array(embedding_model.embed_query(state['latest_message'])).reshape(1, -1).astype('float32')
         distances, indices = self.index.search(query_embedding, 3)
         for idx in indices[0]:
@@ -51,6 +52,7 @@ class RetrieveExactEndpoint:
         self.llm = llm_gpt
     
     def run(self,state:State):
+        print('Gone to retrieve exact endpoint')
         messages = [SystemMessage(content=fetch_endpoint_prompt),
                     FunctionMessage(name='possible_endpoints',content=f'''The possible endpoints are: {state['possible_endpoints']}'''),
                     HumanMessage(content=f'''The user query is: {state['latest_message']}''')]

src/genai/utils/models_loader.py

@@ -23,7 +23,8 @@ llm_groq = ChatGroq(model="llama-3.3-70b-versatile",temperature=0)
 llm_gpt_small = ChatOpenAI(model="gpt-3.5-turbo",temperature=0.3)
 llm_gpt = ChatOpenAI(model="gpt-3.5-turbo",temperature=0.3)
 llm_gpt_high = ChatOpenAI(model="gpt-5-nano",temperature=0.5)
-encoding_model = tiktoken.encoding_for_model('gpt-4o-mini')
+# encoding_model = tiktoken.encoding_for_model('gpt-4o-mini')
+encoding_model = 'demo'
 
 
 captioning_model = "meta-llama/llama-4-scout-17b-16e-instruct"