Browsing: workflows

In this tutorial, we build a complete AgentScope workflow from the ground up and run everything in Colab. We start by wiring OpenAI through AgentScope and…

In the field of vision-language models (VLMs), the ability to bridge the gap between visual perception and logical code execution has traditionally faced a performance trade-off.…

Hugging Face has officially released TRL (Transformer Reinforcement Learning) v1.0, marking a pivotal transition for the library from a research-oriented repository to a stable, production-ready framework.…

In this tutorial, we build and explore the CAI Cybersecurity AI Framework step by step in Colab using an OpenAI-compatible model. We begin by setting up…

like OpenAI’s GPT-5.4 and Anthropic’s Opus 4.6 have demonstrated outstanding capabilities in executing long-running agentic tasks. As a result, we see an increased use of LLM…

Agentalent.ai lets companies hire AI agents to handle defined business functionsEnterprises can evaluate agent profiles before selecting them for specific operational rolesAgents undergo authentication, authorization, and…

Finance leaders are automating their complex workflows by actively adopting powerful new multimodal AI frameworks.Extracting text from unstructured documents presents a frequent headache for developers. Historically,…

import asyncio import json import io import contextlib import re from dataclasses import dataclass from typing import Callable, Awaitable import nest_asyncio nest_asyncio.apply() TOOL_DEFINITIONS = [ {…

In the current landscape of Retrieval-Augmented Generation (RAG), the primary bottleneck for developers is no longer the large language model (LLM) itself, but the data ingestion…

angles = np.linspace(0.0, 2.0 * np.pi, n_particles, endpoint=False, dtype=np.float32) px0_np = 0.4 * np.cos(angles).astype(np.float32) py0_np = (0.7 + 0.15 * np.sin(angles)).astype(np.float32) vx0_np = (-0.8 * np.sin(angles)).astype(np.float32)…