docs: changed the images path in readme file

Author: Avijit-Microsoft

README.md

@@ -15,19 +15,19 @@ Analysts working with large volumes of conversational data can use this solution
 </div>
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-<h2><img src="./docs/Images/ReadMe/solution-overview.png" width="48" />
+<h2><img src="./documents/Images/ReadMe/solution-overview.png" width="48" />
 Solution overview
 </h2>
 
 Leverages Azure AI Content Understanding, Azure AI Search, Azure OpenAI Service, Semantic Kernel, Azure SQL Database, and Cosmos DB to process large volumes of conversational data. Audio and text inputs are analyzed through event-driven pipelines to extract and vectorize key information, orchestrate intelligent responses, and power an interactive web front-end for exploring insights using natural language.
 
 ### Solution architecture
-|![image](./docs/Images/ReadMe/solution-architecture.png)|
+|![image](./documents/Images/ReadMe/solution-architecture.png)|
 |---|
 
 ### Additional resources
 
-[Technical Architecture](./docs/TechnicalArchitecture.md)
+[Technical Architecture](./documents/TechnicalArchitecture.md)
 
 <br/>
 
@@ -55,14 +55,14 @@ Summarized conversations, topic generation, and key phrase extraction support fa
 
 
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-<h2><img src="./docs/Images/ReadMe/quick-deploy.png" width="48" />
+<h2><img src="./documents/Images/ReadMe/quick-deploy.png" width="48" />
 Quick deploy
 </h2>
 
 ### How to install or deploy
 Follow the quick deploy steps on the deployment guide to deploy this solution to your own Azure subscription.
 
-[Click here to launch the deployment guide](./docs/DeploymentGuide.md)
+[Click here to launch the deployment guide](./documents/DeploymentGuide.md)
 <br/><br/>
 
 
@@ -114,12 +114,12 @@ _Note: This is not meant to outline all costs as selected SKUs, scaled use, cust
 either by deleting the resource group in the Portal or running `azd down`.
 
 <br /><br />
-<h2><img src="./docs/Images/ReadMe/business-scenario.png" width="48" />
+<h2><img src="./documents/Images/ReadMe/business-scenario.png" width="48" />
 Business scenario
 </h2>
 
 
-|![image](./docs/Images/ReadMe/ui.png)|
+|![image](./documents/Images/ReadMe/ui.png)|
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@@ -152,7 +152,7 @@ Clear, contextual insights empower employees to take meaningful action based on
 
 <br /><br />
 
-<h2><img src="./docs/Images/ReadMe/supporting-documentation.png" width="48" />
+<h2><img src="./documents/Images/ReadMe/supporting-documentation.png" width="48" />
 Supporting documentation
 </h2>
 

docs/workshop/docs/workshop/Challenge-1/Code_Walkthrough/02_Frontend.md

@@ -5,7 +5,7 @@
 
 The frontend is a **React-based web interface** that allows users to explore insights from conversations, interact with an AI-powered chatbot, and view dynamic visualizations.
 
-![image](../../../../../docs/Images/ReadMe/ui.png)
+![image](../../../../../../documents/Images/ReadMe/ui.png)
 
 ### Features
 

docs/workshop/docs/workshop/Challenge-1/Solution_Overview.md

@@ -2,7 +2,7 @@
 <!-- ## Overview -->
 The Conversation Knowledge Mining Solution Accelerator is a robust application designed to extract actionable insights from conversational data. It leverages Azure AI services and provides an interactive user interface for querying and visualizing data. The solution is built with a modular architecture, combining a React-based frontend, a FastAPI backend, and Azure services for data processing and storage.
 
-![image](../../../../docs/Images/ReadMe/solution-architecture.png)
+![image](../../../../../documents/Images/ReadMe/solution-architecture.png)
 
 The solution extracts insights from call audio files or transcripts and enables users to interact with the data via a chatbot and dynamic charts:
 

documents/TechnicalArchitecture.md

@@ -2,7 +2,7 @@
 
 This section outlines the components and interactions that power the conversational insights platform. The architecture ingests call transcripts and audio files, applies AI services for enrichment and structuring, and surfaces insights via an interactive web experience.
 
-![image](./images/readme/solution-architecture.png)
+![image](./Images/ReadMe/solution-architecture.png)
 
 ### Call Audio Files / Call Transcripts  
 Raw audio and text-based transcripts are the primary input into the system. These files are uploaded and stored for downstream processing.