| title | image | emoji | colorFrom | colorTo | sdk | pinned | license |
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PharmAssistAI |
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PharmAssistAI revolutionizes how pharmacy professionals and students approach learning and research related to FDA-approved drugs. By integrating modern information retrieval technologies with Large Language Models (LLMs), PharmAssistAI optimizes the research and learning workflow, making it less time-consuming and more efficient.
- Comprehensive Data Access: Directly tap into the FDA drug labels dataset, with plans to incorporate the FDA adverse reactions dataset for a fuller data spectrum.
- Dynamic Retrieval: Utilize the Retrieval-Augmented Generation (RAG) technique for dynamic, real-time data retrieval.
- Intelligent Summaries: Leverage LLMs to generate insightful summaries and contextual answers.
- Interactive Learning: Engage with AI-generated related questions to deepen understanding and knowledge retention.
- Research Linkage: Automatically fetch and link relevant academic papers from PubMed, enhancing the depth of available information and supporting academic research.
- Real-Time Feedback with LangSmith: Use LangSmith to incorporate real-time feedback and custom evaluations. This system ensures that the AI's responses are not only accurate but also contextually aware and user-focused.
- Custom Evaluators for Enhanced Accuracy: Deploy custom evaluators like PharmAssistEvaluator to ensure responses meet high standards of relevance, safety, and perception as human-generated versus AI-generated.
- Query Input: Pharmacists type in their questions directly.
- Data Retrieval: Relevant data is fetched from comprehensive datasets, including automated searches of PubMed for related academic papers.
- Data Presentation: Data is displayed in an easily digestible format.
- Summary Generation: Summaries of the data are created using GenAI
- Question Suggestion: Suggest related questions to encourage further exploration.
Experience our app live on Hugging Face:
Home Screen
Demo Screen
Explore the effectiveness and interaction tracking of LangSmith in PharmAssistAI through these detailed screenshots:
Overview of Real-Time Evaluations
Detailed Feedback Example
Interaction Metrics Dashboard
- Integrate and index the complete FDA Drug Labeling and Adverse Events datasets.
- Refine the user interface for enhanced interaction and accessibility.
- Develop AI-driven educational tools like flashcards and study guides for mechanism of action.
- Enhance the retrieval system to include more open-source and advanced embedding models for better precision and efficiency.
Simply enter your question about any FDA-approved drug in our chat interface, and PharmAssistAI will provide you with detailed information, summaries, and follow-up questions to help expand your research and understanding.
We value your input and invite you to help us enhance PharmAssistAI:
- 🐛 Report an issue on GitHub for technical issues or feature suggestions.
- 📧 Contact us at raj.k.stats@gmail.com for direct support or inquiries.