https://pypi.org/project/meddiscover/ Recent updates to the Python Package Index for meddiscover en https://pypi.org/project/meddiscover/0.1.6/ MedDiscover is an AI-powered tool designed to assist biomedical researchers by leveraging Retrieval-Augmented Generation (RAG) with fine-tuned LLMs on PubMed literature. It enables efficient document retrieval, knowledge extraction, and interactive querying from biomedical research papers, helping researchers find relevant insights quickly. The package supports both GPU-based embeddings (MedCPT) and CPU-friendly alternatives (GPT-4 embeddings), making it accessible for a wide range of users. vatsal1804@gmail.com Thu, 13 Mar 2025 08:12:17 GMT https://pypi.org/project/meddiscover/0.1.5/ MedDiscover is an AI-powered tool designed to assist biomedical researchers by leveraging Retrieval-Augmented Generation (RAG) with fine-tuned LLMs on PubMed literature. It enables efficient document retrieval, knowledge extraction, and interactive querying from biomedical research papers, helping researchers find relevant insights quickly. The package supports both GPU-based embeddings (MedCPT) and CPU-friendly alternatives (GPT-4 embeddings), making it accessible for a wide range of users. vatsal1804@gmail.com Thu, 13 Mar 2025 08:05:38 GMT https://pypi.org/project/meddiscover/0.1.4/ MedDiscover is an AI-powered tool designed to assist biomedical researchers by leveraging Retrieval-Augmented Generation (RAG) with fine-tuned LLMs on PubMed literature. It enables efficient document retrieval, knowledge extraction, and interactive querying from biomedical research papers, helping researchers find relevant insights quickly. The package supports both GPU-based embeddings (MedCPT) and CPU-friendly alternatives (GPT-4 embeddings), making it accessible for a wide range of users. vatsal1804@gmail.com Thu, 13 Mar 2025 07:48:08 GMT https://pypi.org/project/meddiscover/0.1.3/ MedDiscover is an AI-powered tool designed to assist biomedical researchers by leveraging Retrieval-Augmented Generation (RAG) with fine-tuned LLMs on PubMed literature. It enables efficient document retrieval, knowledge extraction, and interactive querying from biomedical research papers, helping researchers find relevant insights quickly. The package supports both GPU-based embeddings (MedCPT) and CPU-friendly alternatives (GPT-4 embeddings), making it accessible for a wide range of users. vatsal1804@gmail.com Thu, 13 Mar 2025 07:42:54 GMT https://pypi.org/project/meddiscover/0.1.2/ MedDiscover is an AI-powered tool designed to assist biomedical researchers by leveraging Retrieval-Augmented Generation (RAG) with fine-tuned LLMs on PubMed literature. It enables efficient document retrieval, knowledge extraction, and interactive querying from biomedical research papers, helping researchers find relevant insights quickly. The package supports both GPU-based embeddings (MedCPT) and CPU-friendly alternatives (GPT-4 embeddings), making it accessible for a wide range of users. vatsal1804@gmail.com Thu, 13 Mar 2025 07:34:54 GMT https://pypi.org/project/meddiscover/0.1.1/ Med-Discover is an AI-powered tool designed to assist biomedical researchers by leveraging Retrieval-Augmented Generation (RAG) with fine-tuned LLMs on PubMed literature. It enables efficient document retrieval, knowledge extraction, and interactive querying from biomedical research papers, helping researchers find relevant insights quickly. The package supports both GPU-based embeddings (MedCPT) and CPU-friendly alternatives (GPT-4 embeddings), making it accessible for a wide range of users. vatsal1804@gmail.com Thu, 13 Mar 2025 07:19:28 GMT https://pypi.org/project/meddiscover/0.1.0/ MedDiscover is an AI-powered tool designed to assist biomedical researchers by leveraging Retrieval-Augmented Generation (RAG) with fine-tuned LLMs on PubMed literature. It enables efficient document retrieval, knowledge extraction, and interactive querying from biomedical research papers, helping researchers find relevant insights quickly. The package supports both GPU-based embeddings (MedCPT) and CPU-friendly alternatives (GPT-4 embeddings), making it accessible for a wide range of users. vatsal1804@gmail.com Wed, 12 Mar 2025 13:20:19 GMT