dfd

apis/reddit_apis.py

@@ -0,0 +1,42 @@
+from fastapi import  HTTPException
+from models.reddit_models import AnalysisRequest
+from reddit.reddit_functions import getRedditData
+from reddit.reddit_gemini import getKeywords
+from reddit.reddit_pain_point_analysis import pain_point_analysis
+from reddit.reddit_utils import services_names
+from reddit.reddit_search_scrapper import getCompetitorAnalysisData
+from fastapi import HTTPException
+
+# main method for user end
+async def analyzeData(index:int,inputData:AnalysisRequest):
+    try:
+        keywords = getKeywords(user_query=inputData.user_query)
+       
+        result = await getRedditData(user_query=keywords['query'], search_keywords=keywords['top_3_combinations'])
+       
+        getServices(
+            index=index,
+            analysis_list=inputData.analysis_names,
+            user_query=keywords['query'],
+            fileName=result['fileName'],
+            uniqueFileId=result['fileUniqueId']
+        )
+    except Exception as e:
+        print("Failed to run analyzeData ", e)
+        raise HTTPException(status_code=500, detail=str(f"Failed to run analyzeData : {e}"))
+
+def getServices(index, analysis_list, user_query=None, fileName=None, uniqueFileId=None):
+   # Pain point + Competitor Analysis
+    if services_names[0] in analysis_list and services_names[1] in analysis_list:
+        result=pain_point_analysis(user_query=user_query,fileName=fileName,uniqueFileId=uniqueFileId)
+       
+        competitor_result  = getCompetitorAnalysisData(user_query=user_query,fileName=fileName)
+       
+    # Pain point analysis only
+    elif services_names[0] in analysis_list:
+        result=pain_point_analysis(user_query=user_query,fileName=fileName,uniqueFileId=uniqueFileId)
+    
+    # Competitor analysis only
+    elif services_names[1] in analysis_list:
+        competitor_result  = getCompetitorAnalysisData(user_query=user_query,fileName=fileName)
+       

app.py

@@ -1,7 +1,7 @@
-from collections import deque
 import os
-from fastapi import APIRouter, FastAPI, HTTPException
+from fastapi import  FastAPI, HTTPException
 from fastapi.middleware.cors import CORSMiddleware
+from apis.reddit_apis import analyzeData
 from models.reddit_models import AnalysisRequest, RedditPostDataModel
 from reddit.reddit_functions import getRedditData
 from reddit.reddit_gemini import getKeywords
@@ -9,7 +9,6 @@ from reddit.load_env import api_key
 import google.generativeai as genai
 from datetime import datetime
 from reddit.reddit_pain_point_analysis import pain_point_analysis
-from reddit.reddit_utils import services_names
 from reddit.reddit_search_scrapper import getCompetitorAnalysisData
 from utils import time_execution
 import asyncio
@@ -202,55 +201,7 @@ def getCompetitorAnalysis(user_query: str, fileName: str,isSolo=True):
 
 
 
-# main method for user end
-async def analyzeData(index:int,inputData:AnalysisRequest):
-    try:
-        keywords = getKeywords(user_query=inputData.user_query)
-        config.user_df.loc[index,'gemini_input'] = str({
-            'query': keywords['query'],
-            'top_3_combinations': keywords['top_3_combinations']
-        })
-        result = await getRedditData(user_query=keywords['query'], search_keywords=keywords['top_3_combinations'])
-        config.user_df.loc[index,'file_with_sentiment'] = str({
-            'reddit_data': result['reddit_data'],
-            'sentiment_data':result['sentiment_data']
-        })
-        getServices(
-            index=index,
-            analysis_list=inputData.analysis_names,
-            user_query=keywords['query'],
-            fileName=result['fileName'],
-            uniqueFileId=result['fileUniqueId']
-        )
-    except Exception as e:
-        print("Failed to run analyzeData ", e)
-        raise HTTPException(status_code=500, detail=str(f"Failed to run analyzeData : {e}"))
 
-def getServices(index, analysis_list, user_query=None, fileName=None, uniqueFileId=None):
-   # Pain point + Competitor Analysis
-    if services_names[0] in analysis_list and services_names[1] in analysis_list:
-        result=pain_point_analysis(user_query=user_query,fileName=fileName,uniqueFileId=uniqueFileId)
-        config.user_df.loc[index,'pain_point_analysis'] = str({
-            'e_time': result[2],
-        })
-        competitor_result  = getCompetitorAnalysisData(user_query=user_query,fileName=fileName)
-        config.user_df.loc[index,'competitor_analysis'] = str({
-            "no_of_competitors": len(competitor_result['all_competitor_data']),
-            'e_time': competitor_result['e_time'],
-        })
-    # Pain point analysis only
-    elif services_names[0] in analysis_list:
-        result=pain_point_analysis(user_query=user_query,fileName=fileName,uniqueFileId=uniqueFileId)
-        config.user_df.loc[index,'pain_point_analysis'] = str({
-            'e_time': result[2],
-        })
-    # Competitor analysis only
-    elif services_names[1] in analysis_list:
-        competitor_result  = getCompetitorAnalysisData(user_query=user_query,fileName=fileName)
-        config.user_df.loc[index,'competitor_analysis'] = str({
-            "no_of_competitors": len(competitor_result['all_competitor_data']),
-            'e_time': competitor_result['e_time'],
-        })
 
 # if __name__ == "__main__":
 #     import uvicorn

venv/pyvenv.cfg

@@ -2,4 +2,4 @@ home = C:\Users\HP\AppData\Local\Microsoft\WindowsApps\PythonSoftwareFoundation.
 include-system-site-packages = false
 version = 3.11.9
 executable = C:\Users\HP\AppData\Local\Microsoft\WindowsApps\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\python.exe
-command = C:\Users\HP\AppData\Local\Microsoft\WindowsApps\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\python.exe -m venv D:\work2\nextAnalytics\venv
+command = C:\Users\HP\AppData\Local\Microsoft\WindowsApps\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\python.exe -m venv D:\work\nextAnalytics\venv