LLMs-Pharmaceutical

ChemicalQDevice innovates new LLM/LLM agent pharmaceutical industry applications regarding cancer drug cost containment, clinical decision support, cancer signaling pathways, bioprocess engineering, biosynthesis, characterization, or drug synthesis. OpenAI, Anthropic, Gemini, or xAI direct chat proprietary software are utilized to generate LLM reports and propose detailed solutions. AI governance is employed with relevant software implementations, model bias amplification mitigation, and generation traceability analyses.

PAIML MCP Agent Toolkit (PMAT) is a zero-configuration AI context generation system with extreme quality enforcement and Toyota Way standards. It allows users to analyze any codebase instantly through CLI, MCP, or HTTP interfaces. The toolkit provides features such as technical debt analysis, advanced monitoring, metrics aggregation, performance profiling, bottleneck detection, alert system, multi-format export, storage flexibility, and more. It also offers AI-powered intelligence for smart recommendations, polyglot analysis, repository showcase, and integration points. PMAT enforces quality standards like complexity ≤20, zero SATD comments, test coverage >80%, no lint warnings, and synchronized documentation with commits. The toolkit follows Toyota Way development principles for iterative improvement, direct AST traversal, automated quality gates, and zero SATD policy.

MCP Context Forge is a powerful tool for generating context-aware data for machine learning models. It provides functionalities to create diverse datasets with contextual information, enhancing the performance of AI algorithms. The tool supports various data formats and allows users to customize the context generation process easily. With MCP Context Forge, users can efficiently prepare training data for tasks requiring contextual understanding, such as sentiment analysis, recommendation systems, and natural language processing.

GPT-Vis is a tool designed for GPTs, generative AI, and LLM projects. It provides components such as LLM Protocol for conversational interaction, LLM Component for application development, and LLM access for knowledge base and model solutions. The tool aims to facilitate rapid integration into AI applications by offering a visual protocol, built-in components, and chart recommendations for LLM.

pdr_ai_v2 is a Python library for implementing machine learning algorithms and models. It provides a wide range of tools and functionalities for data preprocessing, model training, evaluation, and deployment. The library is designed to be user-friendly and efficient, making it suitable for both beginners and experienced data scientists. With pdr_ai_v2, users can easily build and deploy machine learning models for various applications, such as classification, regression, clustering, and more.

GrowthHacking-Notes is a repository containing detailed notes, strategies, and resources related to growth hacking. It provides valuable insights and tips for individuals and businesses looking to accelerate their growth through innovative marketing techniques and data-driven strategies. The repository covers various topics such as user acquisition, retention, conversion optimization, and more, making it a comprehensive resource for anyone interested in growth hacking.

TuyaOpen is an open source AI+IoT development framework supporting cross-chip platforms and operating systems. It provides core functionalities for AI+IoT development, including pairing, activation, control, and upgrading. The SDK offers robust security and compliance capabilities, meeting data compliance requirements globally. TuyaOpen enables the development of AI+IoT products that can leverage the Tuya APP ecosystem and cloud services. It continues to expand with more cloud platform integration features and capabilities like voice, video, and facial recognition.

HolmesGPT is an open-source DevOps assistant powered by OpenAI or any tool-calling LLM of your choice. It helps in troubleshooting Kubernetes, incident response, ticket management, automated investigation, and runbook automation in plain English. The tool connects to existing observability data, is compliance-friendly, provides transparent results, supports extensible data sources, runbook automation, and integrates with existing workflows. Users can install HolmesGPT using Brew, prebuilt Docker container, Python Poetry, or Docker. The tool requires an API key for functioning and supports OpenAI, Azure AI, and self-hosted LLMs.

Dranet is a Python library for analyzing and visualizing data from neural networks. It provides tools for interpreting model predictions, understanding feature importance, and evaluating model performance. With Dranet, users can gain insights into how neural networks make decisions and improve model transparency and interpretability.

Cloudflare Agents is a framework for building intelligent, stateful agents that persist, think, and evolve at the edge of the network. It allows for maintaining persistent state and memory, real-time communication, processing and learning from interactions, autonomous operation at global scale, and hibernating when idle. The project is actively evolving with focus on core agent framework, WebSocket communication, HTTP endpoints, React integration, and basic AI chat capabilities. Future developments include advanced memory systems, WebRTC for audio/video, email integration, evaluation framework, enhanced observability, and self-hosting guide.

GPTQModel is an easy-to-use LLM quantization and inference toolkit based on the GPTQ algorithm. It provides support for weight-only quantization and offers features such as dynamic per layer/module flexible quantization, sharding support, and auto-heal quantization errors. The toolkit aims to ensure inference compatibility with HF Transformers, vLLM, and SGLang. It offers various model supports, faster quant inference, better quality quants, and security features like hash check of model weights. GPTQModel also focuses on faster quantization, improved quant quality as measured by PPL, and backports bug fixes from AutoGPTQ.

Authed is an identity and authentication system designed for AI agents, providing unique identities, secure agent-to-agent authentication, and dynamic access policies. It eliminates the need for static credentials and human intervention in authentication workflows. The protocol is developer-first, open-source, and scalable, enabling AI agents to interact securely across different ecosystems and organizations.

The Alignment Handbook provides robust training recipes for continuing pretraining and aligning language models with human and AI preferences. It includes techniques such as continued pretraining, supervised fine-tuning, reward modeling, rejection sampling, and direct preference optimization (DPO). The handbook aims to fill the gap in public resources on training these models, collecting data, and measuring metrics for optimal downstream performance.

The Atomic Agents framework is a modular and extensible tool designed for creating powerful applications. It leverages Pydantic for data validation and serialization. The framework follows the principles of Atomic Design, providing small and single-purpose components that can be combined. It integrates with Instructor for AI agent architecture and supports various APIs like Cohere, Anthropic, and Gemini. The tool includes documentation, examples, and testing features to ensure smooth development and usage.

Dyad is a lightweight Python library for analyzing dyadic data, which involves pairs of individuals and their interactions. It provides functions for computing various network metrics, visualizing network structures, and conducting statistical analyses on dyadic data. Dyad is designed to be user-friendly and efficient, making it suitable for researchers and practitioners working with relational data in fields such as social network analysis, communication studies, and psychology.

HexStrike AI is an advanced AI-powered penetration testing MCP framework with 150+ security tools and 12+ autonomous AI agents. It features a multi-agent architecture with intelligent decision-making, vulnerability intelligence, and modern visual engine. The platform allows for AI agent connection, intelligent analysis, autonomous execution, real-time adaptation, and advanced reporting. HexStrike AI offers a streamlined installation process, Docker container support, 250+ specialized AI agents/tools, native desktop client, advanced web automation, memory optimization, enhanced error handling, and bypassing limitations.

ChemicalQDevice innovates new LLM/LLM agent pharmaceutical industry applications regarding cancer drug cost containment, clinical decision support, cancer signaling pathways, bioprocess engineering, biosynthesis, characterization, or drug synthesis. OpenAI, Anthropic, Gemini, or xAI direct chat proprietary software are utilized to generate LLM reports and propose detailed solutions. AI governance is employed with relevant software implementations, model bias amplification mitigation, and generation traceability analyses.

The AI Fairness 360 toolkit is an open-source library designed to detect and mitigate bias in machine learning models. It provides a comprehensive set of metrics, explanations, and algorithms for bias mitigation in various domains such as finance, healthcare, and education. The toolkit supports multiple bias mitigation algorithms and fairness metrics, and is available in both Python and R. Users can leverage the toolkit to ensure fairness in AI applications and contribute to its development for extensibility.

HuatuoGPT-o1 is a medical language model designed for advanced medical reasoning. It can identify mistakes, explore alternative strategies, and refine answers. The model leverages verifiable medical problems and a specialized medical verifier to guide complex reasoning trajectories and enhance reasoning through reinforcement learning. The repository provides access to models, data, and code for HuatuoGPT-o1, allowing users to deploy the model for medical reasoning tasks.

**Prompt flow** is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.

DeepEval is a simple-to-use, open-source LLM evaluation framework specialized for unit testing LLM outputs. It incorporates various metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., and runs locally on your machine for evaluation. It provides a wide range of ready-to-use evaluation metrics, allows for creating custom metrics, integrates with any CI/CD environment, and enables benchmarking LLMs on popular benchmarks. DeepEval is designed for evaluating RAG and fine-tuning applications, helping users optimize hyperparameters, prevent prompt drifting, and transition from OpenAI to hosting their own Llama2 with confidence.

MegaDetector is an AI model that identifies animals, people, and vehicles in camera trap images (which also makes it useful for eliminating blank images). This model is trained on several million images from a variety of ecosystems. MegaDetector is just one of many tools that aims to make conservation biologists more efficient with AI. If you want to learn about other ways to use AI to accelerate camera trap workflows, check out our of the field, affectionately titled "Everything I know about machine learning and camera traps".

LeapfrogAI is a self-hosted AI platform designed to be deployed in air-gapped resource-constrained environments. It brings sophisticated AI solutions to these environments by hosting all the necessary components of an AI stack, including vector databases, model backends, API, and UI. LeapfrogAI's API closely matches that of OpenAI, allowing tools built for OpenAI/ChatGPT to function seamlessly with a LeapfrogAI backend. It provides several backends for various use cases, including llama-cpp-python, whisper, text-embeddings, and vllm. LeapfrogAI leverages Chainguard's apko to harden base python images, ensuring the latest supported Python versions are used by the other components of the stack. The LeapfrogAI SDK provides a standard set of protobuffs and python utilities for implementing backends and gRPC. LeapfrogAI offers UI options for common use-cases like chat, summarization, and transcription. It can be deployed and run locally via UDS and Kubernetes, built out using Zarf packages. LeapfrogAI is supported by a community of users and contributors, including Defense Unicorns, Beast Code, Chainguard, Exovera, Hypergiant, Pulze, SOSi, United States Navy, United States Air Force, and United States Space Force.

This Docker image for LLaVA (Large Language and Vision Assistant) provides a convenient way to run LLaVA locally or on RunPod. LLaVA is a powerful AI tool that combines natural language processing and computer vision capabilities. With this Docker image, you can easily access LLaVA's functionalities for various tasks, including image captioning, visual question answering, text summarization, and more. The image comes pre-installed with LLaVA v1.2.0, Torch 2.1.2, xformers 0.0.23.post1, and other necessary dependencies. You can customize the model used by setting the MODEL environment variable. The image also includes a Jupyter Lab environment for interactive development and exploration. Overall, this Docker image offers a comprehensive and user-friendly platform for leveraging LLaVA's capabilities.

The 'carrot' repository on GitHub provides a list of free and user-friendly ChatGPT mirror sites for easy access. The repository includes sponsored sites offering various GPT models and services. Users can find and share sites, report errors, and access stable and recommended sites for ChatGPT usage. The repository also includes a detailed list of ChatGPT sites, their features, and accessibility options, making it a valuable resource for ChatGPT users seeking free and unlimited GPT services.

TrustLLM is a comprehensive study of trustworthiness in LLMs, including principles for different dimensions of trustworthiness, established benchmark, evaluation, and analysis of trustworthiness for mainstream LLMs, and discussion of open challenges and future directions. Specifically, we first propose a set of principles for trustworthy LLMs that span eight different dimensions. Based on these principles, we further establish a benchmark across six dimensions including truthfulness, safety, fairness, robustness, privacy, and machine ethics. We then present a study evaluating 16 mainstream LLMs in TrustLLM, consisting of over 30 datasets. The document explains how to use the trustllm python package to help you assess the performance of your LLM in trustworthiness more quickly. For more details about TrustLLM, please refer to project website.

AI-YinMei is an AI virtual anchor Vtuber development tool (N card version). It supports fastgpt knowledge base chat dialogue, a complete set of solutions for LLM large language models: [fastgpt] + [one-api] + [Xinference], supports docking bilibili live broadcast barrage reply and entering live broadcast welcome speech, supports Microsoft edge-tts speech synthesis, supports Bert-VITS2 speech synthesis, supports GPT-SoVITS speech synthesis, supports expression control Vtuber Studio, supports painting stable-diffusion-webui output OBS live broadcast room, supports painting picture pornography public-NSFW-y-distinguish, supports search and image search service duckduckgo (requires magic Internet access), supports image search service Baidu image search (no magic Internet access), supports AI reply chat box [html plug-in], supports AI singing Auto-Convert-Music, supports playlist [html plug-in], supports dancing function, supports expression video playback, supports head touching action, supports gift smashing action, supports singing automatic start dancing function, chat and singing automatic cycle swing action, supports multi scene switching, background music switching, day and night automatic switching scene, supports open singing and painting, let AI automatically judge the content.