Renaming the app at places

.env.example

@@ -1,7 +1,7 @@
 # --- HF Spaces Deployment Settings ---
 
 # --- Application Settings ---
-APP_NAME=AI Universal Knowledge Ingestion System
+APP_NAME=QuerySphere
 APP_VERSION=1.0.0
 PORT=7860
 HOST=0.0.0.0

README.md

@@ -46,7 +46,7 @@ A MVP grade Retrieval-Augmented Generation (RAG) system that enables organizatio
 
 ## 🎯 Overview
 
-The AI Universal Knowledge Ingestion System addresses a critical enterprise pain point: **information silos that cost organizations 20% of employee productivity**. Unlike existing solutions (Humata AI, ChatPDF, NotebookLM) that charge $49/user/month and rely on expensive cloud LLM APIs, this system offers:
+The QuerySphere addresses a critical enterprise pain point: **information silos that cost organizations 20% of employee productivity**. Unlike existing solutions (Humata AI, ChatPDF, NotebookLM) that charge $49/user/month and rely on expensive cloud LLM APIs, this system offers:
 
 ### **Core Value Propositions**
 

app.py

@@ -955,7 +955,7 @@ async def lifespan(app: FastAPI):
     # Register atexit cleanup
     atexit.register(_atexit_cleanup)
 
-    logger.info("Starting AI Universal Knowledge Ingestion System...")
+    logger.info("Starting QuerySphere ...")
     
     try:
         # Initialize application state
@@ -999,8 +999,8 @@ async def lifespan(app: FastAPI):
 
 
 # Create FastAPI application
-app = FastAPI(title       = "AI Universal Knowledge Ingestion System",
-              description = "Enterprise RAG Platform with Multi-Source Ingestion",
+app = FastAPI(title       = "QuerySphere",
+              description = "Enterprise RAG Platform with Multi-Source & Multi-Format Document Ingestion Support",
               version     = "1.0.0",
               lifespan    = lifespan,
              )

config/settings.py

@@ -20,7 +20,7 @@ class Settings(BaseSettings):
     IS_HF_SPACE                   : bool                                                     = Field(default = os.getenv("SPACE_ID") is not None, description = "Running in HF Space")
     
     # Application Settings
-    APP_NAME                      : str                                                      = "AI Universal Knowledge Ingestion System"
+    APP_NAME                      : str                                                      = "QuerySphere"
     APP_VERSION                   : str                                                      = "1.0.0"
     DEBUG                         : bool                                                     = Field(default = False, description = "Enable debug mode")
     HOST                          : str                                                      = Field(default = "0.0.0.0", description = "API host")

docs/API.md

@@ -1,7 +1,7 @@
-# AI Universal Knowledge Ingestion System - API Documentation
+# QuerySphere - API Documentation
 
 ## Overview
-The AI Universal Knowledge Ingestion System is a production-grade RAG (Retrieval-Augmented Generation) platform that enables organizations to unlock knowledge from multiple document sources while maintaining complete data privacy and eliminating API costs.
+The QuerySphere is a MVP level RAG (Retrieval-Augmented Generation) platform that enables organizations to unlock knowledge from multiple document sources while maintaining complete data privacy and eliminating API costs.
 
 **Base URL:** http://localhost:8000 (or your deployed domain)
 

docs/ARCHITECTURE.md

@@ -1,4 +1,4 @@
-# AI Universal Knowledge Ingestion System - Technical Architecture Document
+# QuerySphere - Technical Architecture Document
 
 ## 1. System Overview
 
@@ -845,7 +845,7 @@ def check_rate_limit(request: Request, limit: int = 100):
 
 ## Conclusion
 
-This architecture document provides a comprehensive technical blueprint for the AI Universal Knowledge Ingestion System. The modular design, clear separation of concerns, and production-ready considerations make this system suitable for enterprise deployment while maintaining flexibility for future enhancements.
+This architecture document provides a comprehensive technical blueprint for the QuerySphere system. The modular design, clear separation of concerns, and production-ready considerations make this system suitable for enterprise deployment while maintaining flexibility for future enhancements.
 
 ### Key Architectural Strengths
 
@@ -879,4 +879,4 @@ Author: Satyaki Mitra
 
 ---
 
-> This document is part of the AI Universal Knowledge Ingestion System technical documentation suite.
+> This document is part of the QuerySphere technical documentation suite.