Updated analytics

.github/workflows/main.yaml

@@ -1,62 +0,0 @@
-name: FastAPI CI + Docker
-
-on:
-  push:
-    branches: [main]
-  pull_request:
-    branches: [main]
-
-jobs:
-  build-test-and-dockerize:
-    runs-on: ubuntu-latest
-
-    env:
-      HUGGINGFACEHUB_ACCESS_TOKEN: ${{ secrets.HUGGINGFACEHUB_ACCESS_TOKEN }}
-      GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }}
-      GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
-      OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
-      ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
-
-    steps:
-    - name: Checkout code
-      uses: actions/checkout@v3
-
-    - name: Set up Python
-      uses: actions/setup-python@v4
-      with:
-        python-version: '3.13'
-
-    - name: Install dependencies
-      run: |
-        python -m pip install --upgrade pip
-        pip install -r requirements.txt
-        pip install pytest
-        pip install langgraph==0.6.4
-
-    # - name: Run tests
-    #   run: pytest
-
-    - name: Set up Docker Buildx
-      uses: docker/setup-buildx-action@v3
-
-    - name: Log in to Docker Hub
-      uses: docker/login-action@v3
-      with:
-        username: ${{ secrets.DOCKER_USERNAME }}
-        password: ${{ secrets.DOCKER_PASSWORD }}
-
-    - name: Build and Push Docker image
-      uses: docker/build-push-action@v5
-      with:
-        context: .
-        push: false
-        tags: subash024/rt-genai-app:latest
-        build-args: |
-          HUGGINGFACEHUB_ACCESS_TOKEN=${{ secrets.HUGGINGFACEHUB_ACCESS_TOKEN }}
-          GROQ_API_KEY=${{ secrets.GROQ_API_KEY }}
-          GOOGLE_API_KEY=${{ secrets.GOOGLE_API_KEY }}
-          OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY }}
-          ANTHROPIC_API_KEY=${{ secrets.ANTHROPIC_API_KEY }}
-
-
-

.gitignore

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

logs/access.log

@@ -1247,3 +1247,37 @@
 2025-10-09 15:08:33,444 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/orchestration
 2025-10-09 16:48:18,312 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/show-analytics
 2025-10-09 16:48:20,028 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-10 13:19:42,360 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/
+2025-10-10 13:19:42,361 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-10 13:19:42,846 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/favicon.ico
+2025-10-10 13:19:42,848 | INFO | access_logger | app.py:21 | Response status: 404
+2025-10-10 13:19:45,626 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/docs
+2025-10-10 13:19:45,627 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-10 13:19:45,750 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/openapi.json
+2025-10-10 13:19:45,758 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-10 13:19:58,201 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=I%20want%20to%20compare%20the%20analytics%20of%20divya%20dhakal%20and%20muna%20chiya%20in%20weekly%20basis
+2025-10-10 13:20:10,214 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-10 13:20:35,163 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=I%20want%20to%20compare%20the%20analytics%20of%20divya%20dhakal%20and%20muna%20chiya%20in%20weekly%20basis
+2025-10-10 13:20:40,837 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-10 13:30:44,690 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=I%20want%20to%20compare%20the%20analytics%20of%20divya%20dhakal%20and%20muna%20chiya%20in%20weekly%20basis
+2025-10-10 13:30:56,753 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-10 13:32:12,738 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=I%20want%20to%20compare%20the%20analytics%20of%20divya%20dhakal%20and%20muna%20chiya%20in%20weekly%20basis
+2025-10-10 13:32:30,841 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-10 13:54:13,642 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=I%20want%20to%20compare%20the%20analytics%20of%20divya%20dhakal%20and%20muna%20chiya%20in%20weekly%20basis
+2025-10-10 13:54:23,393 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-10 13:58:25,240 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=I%20want%20to%20compare%20the%20analytics%20of%20divya%20dhakal%20and%20muna%20chiya%20in%20weekly%20basis
+2025-10-10 13:58:48,010 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-10 14:00:29,327 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=no%20i%20want%20monthly
+2025-10-10 14:00:32,974 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-10 14:05:34,316 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=I%20want%20to%20compare%20the%20analytics%20of%20divya%20dhakal%20and%20muna%20chiya%20in%20weekly%20basis
+2025-10-10 14:06:32,897 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-10 14:14:43,239 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=I%20want%20to%20compare%20the%20analytics%20of%20divya%20dhakal%20and%20muna%20chiya%20in%20weekly%20basis
+2025-10-10 14:14:57,116 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-10 14:15:18,176 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=now%20i%20want%20monthly
+2025-10-10 14:17:14,812 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-10 15:11:11,583 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=I%20want%20to%20compare%20the%20analytics%20of%20divya%20dhakal%20and%20muna%20chiya%20in%20weekly%20basis
+2025-10-10 15:12:47,152 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-10 15:13:11,651 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=i%20want%20monthly
+2025-10-10 15:13:23,414 | INFO | access_logger | app.py:21 | Response status: 200
+2025-10-10 15:14:29,401 | INFO | access_logger | app.py:19 | Request: GET http://127.0.0.1:8000/api/analytics-chatbot?msg=i%20want%20monthly%20not%20weekly
+2025-10-10 15:15:31,389 | INFO | access_logger | app.py:21 | Response status: 200

src/genai/analytics_chatbot/utils/nodes.py

@@ -1,8 +1,8 @@
 import requests
 from langchain_core.messages import SystemMessage , HumanMessage , FunctionMessage
 from .state import State
-from .schemas import ResponseFormatter , InfluencerNames
-from .prompts import chatbot_prompt , get_inf_name_prompt
+from .schemas import ResponseFormatter , CompareBodyFormatter
+from .prompts import chatbot_prompt , get_body_prompt
 from .utils import generate_api_knowledge
 from src.genai.utils.models_loader import llm_gpt
 
@@ -15,6 +15,7 @@ class ChatbotNode:
         # state['messages'][-1].content = process_query(state['messages'][-1].content)
         template = chatbot_prompt()
         knowledge_base = generate_api_knowledge('https://reveltrends.vercel.app')
+        print('The knowledge base is:', knowledge_base)
         messages = [SystemMessage(content=template), 
                     FunctionMessage(name='analytics_chatbot',content=str(knowledge_base)),
                     ] + state["messages"]
@@ -47,12 +48,15 @@ class FetchDataNode:
             response = requests.get(url, params=state['parameters'],headers=self.headers)
         elif state['endpoint'] == '/api/v1/compare/':
             print('Condition satisfied')
-            messages = [SystemMessage(content=get_inf_name_prompt()), 
-            HumanMessage(content=f'''The dictionary of parameters is: {state['parameters']}''')]
-            response=llm_gpt.with_structured_output(InfluencerNames).invoke(messages)
+            human_messages = [msg.content for msg in state['messages'] if isinstance(msg, HumanMessage)]
+            print('Human messages:', human_messages)
+            messages = [SystemMessage(content=get_body_prompt()), 
+            HumanMessage(content=str(state['messages']))]
+            response=llm_gpt.with_structured_output(CompareBodyFormatter , method='function_calling').invoke(messages)
+            print('INF names response:', response)
             payload = {
             "usernames": response.names,
-            "freq": state['parameters']['frequency']          
+            "freq": response.frequency          
              }
             
             print('The payload is:',payload)

src/genai/analytics_chatbot/utils/prompts.py

@@ -41,8 +41,27 @@ Expected output:
 Your response must always follow this exact JSON format.
 """
 
-def get_inf_name_prompt():
-    return'''You are given with a dictionary called parameters.
-Your task is to just extract the names of influencers from as it is from the values of that dictionary.
-Extract the names in the form of list. 
+def get_body_prompt():
+    return '''You are given a user query  for comparing influencers.
+
+Your task:
+1. Extract all influencer names in the form of list.
+   - The names should be returned exactly as they appear.
+
+2. Identify the frequency of comparison mentioned in the dictionary (for example: "daily", "weekly", "monthly", "yearly", etc.).
+Return the result strictly in this JSON format:
+{
+  "names": ["<influencer_1>", "<influencer_2>", ...],
+  "frequency": "<frequency_value>"
+}
+
+Example:
+If the query is :"I want to compare the analytics of divyadhakal_ and munachiya in weekly basis", then 
+
+Then the expected output is:
+{
+  "names": ["divyadhakal_", "munachiya"],
+  "frequency": "weekly"
+}
 '''
+

src/genai/analytics_chatbot/utils/schemas.py

@@ -1,9 +1,14 @@
 from pydantic import BaseModel, Field
+from typing import Optional , Dict , Any
 
 class ResponseFormatter(BaseModel):
     endpoint: str = Field(description='Return the exact endpoint from the knowledge base of endpoints.')
     method: str = Field(description='Return the exact request type from the knowledge base of endpoints. GET or POST ')
-    parameters: dict = Field(description='Return the dictionary of parameters to pass to the endpoint.')
+    parameters: Optional[Dict[str, Optional[Any]]] = Field(
+    None,
+    description="Return the dictionary of parameters to pass to the endpoint. Each parameter value can be None if not specified."
+    )
 
-class InfluencerNames(BaseModel):
-    names: list
+class CompareBodyFormatter(BaseModel):
+    names: list
+    frequency: str