update Readme layout

README.md

@@ -17,9 +17,11 @@ models:
 short_description: Ask any questions to the Audit reports
 license: apache-2.0
 ---
-
+### Technical Documentation of the system in accordance with EU AI Act.
 System Name: Audit Assistant
+
 Provider / Supplier: GIZ Data Service Center
+
 As of: July 2025
 
 
@@ -28,49 +30,47 @@ Audit Assistant is an AI-powered tool for exploring and understanding Uganda's a
 
 
 2. Model's Used 
-Generative LLM
--   Model Name: [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct)
--	Model Source API: [Nebius AI](https://studio.nebius.com/)
 
-Retriever/Embedding
--   Model Name: [BAAI/bge-m3](https://huggingface.co/BAAI/bge-m3)
--   Model Source: Local Instance 
+    Generative LLM
+    -   Model Name: [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct)
+    -	Model Source API: [Nebius AI](https://studio.nebius.com/)
 
-Re-ranker:
--   Model Name: [BAAI/bge-reranker-v2-m3](https://huggingface.co/BAAI/bge-reranker-v2-m3)
--   Model Source: Local Instance
+    Retriever/Embedding
+    -   Model Name: [BAAI/bge-m3](https://huggingface.co/BAAI/bge-m3)
+    -   Model Source: Local Instance 
 
+    Re-ranker:
+    -   Model Name: [BAAI/bge-reranker-v2-m3](https://huggingface.co/BAAI/bge-reranker-v2-m3)
+    -   Model Source: Local Instance
 
-
-3. Model Training Data
+3. Model Training Data:
 All the models mentioned above are being consumed, without any fine-tuning or trianing being performed by the developer team fo audit assistant tool. And hence there os no training data had been sued by the development team of Audit Assistant tool.
 
 
 4. Knowledge Base (Retrieval Component)
-•	Data Sources: Public, non-personal audit reports relased by [**Office of the Auditor General (OAG) of Uganda**](https://www.oag.go.ug/welcome)
-•	Embedding Model: [BAAI/bge-m3](https://huggingface.co/BAAI/bge-m3)
-•	Embedding Dimension: 1024
-•	Vector Database: Qdrant (via API)
-•	Framework: Langchain (custom RAG pipeline)
-•	Top-k: 5 relevant text segments per query
+
+    -   Data Sources: Public, non-personal audit reports relased by [**Office of the Auditor General (OAG) of Uganda**](https://www.oag.go.ug/welcome)
+    -   Embedding Model: [BAAI/bge-m3](https://huggingface.co/BAAI/bge-m3)
+    -   Embedding Dimension: 1024
+    -   Vector Database: Qdrant (via API)
+    -   Framework: Langchain (custom RAG pipeline)
+    -   Top-k: 5 relevant text segments per query
 
 5. System Limitations and Non-Purposes
-•	The system does not make autonomous decisions.
-•	No processing of personal data except for the usage statistics as mentioned in Disclaimer.
-•	Results are intended for orientation only – not for legal or political advice.
+    -	The system does not make autonomous decisions.
+    -	No processing of personal data except for the usage statistics as mentioned in Disclaimer.
+    -	Results are intended for orientation only – not for legal or political advice.
 
 6. Transparency Towards Users
-•	The user interface clearly indicates the use of a generative AI model.
-•	An explanation of the RAG method is included.
-•	Feedback mechanism available (via https://huggingface.co/spaces/GIZ/audit_assistant/discussions/new).
+    -	The user interface clearly indicates the use of a generative AI model.
+    -	An explanation of the RAG method is included.
+    -   We collect usage statistics as detailed in Disclaimer tab of the app along with the explicit display in the user interface of the tool.
+    -	Feedback mechanism available (via https://huggingface.co/spaces/GIZ/audit_assistant/discussions/new).
 
 7. Monitoring, Feedback, and Incident Reporting
-•	User can provide feedback via UI by giving (Thumbs-up or down to AI-Generated answer). alternatively for more detailed feedback please use https://huggingface.co/spaces/GIZ/audit_assistant/discussions/new to report any issue.
-•	Technical development is carried out by the GIZ Data Service Center.
-•	No automated bias detection – but low risk due to content restrictions.
-
+    -	User can provide feedback via UI by giving (Thumbs-up or down to AI-Generated answer). alternatively for more detailed feedback please use https://huggingface.co/spaces/GIZ/audit_assistant/discussions/new to report any issue.
+    -	Technical development is carried out by the GIZ Data Service Center.
+    -	No automated bias detection – but low risk due to content restrictions.
 
-8. Contact
-For any questions, please contact via https://huggingface.co/spaces/GIZ/audit_assistant/discussions/new or send us email to dataservicecenter@giz.de
 
-Check out the configuration reference at: https://huggingface.co/docs/hub/spaces-config-reference
+8. Contact: For any questions, please contact via https://huggingface.co/spaces/GIZ/audit_assistant/discussions/new or send us email to dataservicecenter@giz.de

app.py

@@ -692,7 +692,7 @@ with gr.Blocks(title="Audit Q&A", css= "style.css", theme=theme,elem_id = "main-
                         - Usage statistics such as session duration and device type.
                     We process this data based on our legitimate interest in continually enhancing the quality, security, and usability of the Audit Q&A assistant
                 - By using this chatbot, you agree to these terms and acknowledge that you are solely responsible for any reliance on or actions taken based on its responses.
-                - User can read more about the technical information about the tool in [Readme](https://huggingface.co/spaces/GIZ/audit_assistant/blob/main/README.md) of this tool.
+                - User can read more about the technical information about the tool in [**Readme**](https://huggingface.co/spaces/GIZ/audit_assistant/blob/main/README.md) of this tool.
                 - **This is just a prototype and being tested and worked upon, so its not perfect and may sometimes give irrelevant answers**. If you are not satisfied with the answer, please ask a more specific question or report your feedback to help us improve the system.
                 """)