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Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
DeepInfer: High-performance, large-scale inference framework for DeepSeek models
20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.
🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
the LLM vulnerability scanner
Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.
Autonomous multi-agent framework to optimize scientific software
MCP server for spatial transcriptomics analysis through natural language interfaces.
Prompt-injection firewall for LLM applications — 33 input detectors, 9 output scanners, federated ed25519-signed threat-intel feed. Apache 2.0, 1040 tests, F1 96.0% with 0% false positives. Docker, GitHub Action, LangChain/LlamaIndex/CrewAI integrations.
Pipeline de ingestão e busca semântica de documentos para RAG — com rate limiting, circuit breaker e fila resiliente.