LusyChat positions itself as a chatbot designed for users who prefer conversations that feel less constrained by rules and more attentive to what is being said. Instead of rigid or repetitive responses, it aims to deliver interaction that adapts in real time, making it a suitable option for those interested in more open or spicy…
Starting a conversation with CraveU feels closer to an ongoing dialogue than a traditional request-based system, giving users room to discuss concepts, roleplay scenarios, or personal matters without repeated breaks. ⚡️ TRENDING CHATBOTS ⚡️ Candy AI Try Candy AI Unfiltered Chat with AI GirlsPhotos and voice messagesVideo Generation Promptchan Try Promptchan Your Dream AI Girlfriend…
DarLink is intended for users who treat AI image generation as an individual process of exploration rather than a structured design system. It emphasizes privacy, user control, and creative latitude, allowing adult-oriented visuals to be defined by input rather than platform restrictions. ⚡️ TRENDING IMAGE GENERATORS ⚡️ Candy AI Try Candy AI Unfiltered AI ImagesRealistic…
Engaging with the AI models in DarLink creates the impression of a flowing dialogue instead of a rigid input-output process, enabling exploration of ideas, roleplay elements, or personal topics with minimal disruption. ⚡️ TRENDING CHATBOTS ⚡️ Candy AI Try Candy AI Unfiltered Chat with AI GirlsPhotos and voice messagesVideo Generation Promptchan Try Promptchan Your Dream…
In this tutorial, we build an advanced, end-to-end multi-agent research workflow using the CAMEL framework. We design a coordinated society of agents, Planner, Researcher, Writer, Critic, and Finalizer, that collaboratively transform a high-level topic into a polished, evidence-grounded research brief. We securely integrate the OpenAI API, orchestrate agent interactions programmatically, and add lightweight persistent memory…
In this tutorial, we demonstrate how to design a contract-first agentic decision system using PydanticAI, treating structured schemas as non-negotiable governance contracts rather than optional output formats. We show how we define a strict decision model that encodes policy compliance, risk assessment, confidence calibration, and actionable next steps directly into the agent’s output schema. By…
NVIDIA AI research team released NitroGen, an open vision action foundation model for generalist gaming agents that learns to play commercial games directly from pixels and gamepad actions using internet video at scale. NitroGen is trained on 40,000 hours of gameplay across more than 1,000 games and comes with an open dataset, a universal simulator,…
Liquid AI has introduced LFM2-2.6B-Exp, an experimental checkpoint of its LFM2-2.6B language model that is trained with pure reinforcement learning on top of the existing LFM2 stack. The goal is simple, improve instruction following, knowledge tasks, and math for a small 3B class model that still targets on device and edge deployment. Where LFM2-2.6B-Exp Fits…
In this tutorial, we build an end-to-end, production-style agentic workflow using GraphBit that demonstrates how graph-structured execution, tool calling, and optional LLM-driven agents can coexist in a single system. We start by initializing and inspecting the GraphBit runtime, then define a realistic customer-support ticket domain with typed data structures and deterministic, offline-executable tools. We show…
Google has released FunctionGemma, a specialized version of the Gemma 3 270M model that is trained specifically for function calling and designed to run as an edge agent that maps natural language to executable API actions. But, What is FunctionGemma? FunctionGemma is a 270M parameter text only transformer based on Gemma 3 270M. It keeps…