Update README.md

README.md

@@ -74,9 +74,45 @@ create_conversational_rag_chain: Creates a RAG chain for processing user questio
 Additional Notes
 
 
-The Lithuanian law documents might not be the latest versions.
+## Potential Improvements
+
+While the application functions effectively, there's room for future enhancements:
+
+####  Advanced Retrieval Techniques:
+Explore implementing more sophisticated retrieval methods beyond the current approach. This could involve techniques like self-corrective Retrieval-Augmented Generation (RAG), multi-vector RAG, or graph RAG, potentially leading to improved accuracy and more relevant results.
+####  Expanded Data Sources:
+Consider incorporating a wider range of data sources beyond the initial Lithuanian law documents. This could encompass legal databases, relevant news articles, or judicial opinions. If no pertinent information is found within these sources, the application could potentially resort to web searches for a broader perspective.
+####  GPU Acceleration:
+The application on a GPU to leverage its processing power. This could significantly reduce response times, enhancing user experience.
+####  Model Fine-tuning:
+Explore fine-tuning the Qwen2-0.5B model on specific legal datasets or domains. This could significantly bolster its understanding of Lithuanian legal terminology and nuances, leading to more accurate and insightful responses.
+####  Multi-agent Approach:
+Consider adopting a multi-agent approach. This could involve integrating additional tools and functionalities, such as data visualization tools or legal document summarization capabilities, to further enrich the user experience.
+
+
+
+## Benefits of Future Advancements
+
+####  Enhanced Accuracy:
+Advanced retrieval techniques could provide more precise and relevant results to user queries.
+####  Comprehensive Information Access: 
+Integrating additional data sources would broaden the information scope, offering users a more comprehensive picture.
+####  Faster Response Times:
+GPU implementation could significantly reduce processing times, leading to a more responsive application.
+####  Improved Legal Understanding:
+Fine-tuning the model would enhance its comprehension of Lithuanian legal concepts, leading to more accurate and informative responses.
+####  Richer User Experience: 
+A multi-agent approach could introduce new functionalities and data visualization tools, fostering a more interactive and informative experience.
+
+## Conclusion
+
+This application provides a valuable foundation for legal information access. By exploring the potential improvements outlined above, we can  continuously enhance its capabilities and user experience.
+
+
+
+
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-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference