Browsing: MultiAgent

A humorous-but-real tour of SwarmKV — KV-snapshot fan-out, copy-on-fork host buffers, and how to make a two-agent analytical pipeline ~1.95× faster (and the second branch’s activation…

are the talk of the town. We see them everywhere, even being used for the simplest of tasks on our phones. They are convenient, fast, and…

Building a structured dataset from the web is still a pipeline problem. You identify a data source, write or configure a scraper, design a schema, handle…

AI Agents When building an AI agent, the design choice matters. A single agent may be enough for straightforward tasks, while more complex workflows may need…

class CellSignalingSimulationAgent: def run(self, df_signal: pd.DataFrame) -> AgentResult: peak_receptor = float(df_signal[“receptor_active”].max()) peak_kinase = float(df_signal[“kinase_active”].max()) peak_tf = float(df_signal[“tf_active”].max()) t_receptor = float(df_signal.loc[df_signal[“receptor_active”].idxmax(), “time”]) t_kinase = float(df_signal.loc[df_signal[“kinase_active”].idxmax(), “time”]) t_tf…

In this tutorial, we implement an advanced agentic AI system using the CAMEL framework, orchestrating multiple specialized agents to collaboratively solve a complex task. We design…

In this tutorial, we build an advanced, production-ready agentic system using SmolAgents and demonstrate how modern, lightweight AI agents can reason, execute code, dynamically manage tools,…

def describe_dataset(dataset_name: str, tool_context: ToolContext) -> dict: print(f”📊 Describing dataset: {dataset_name}”) df = DATA_STORE.get_dataset(dataset_name) if df is None: return {“status”: “error”, “message”: f”Dataset ‘{dataset_name}’ not found”}…

Writing a research paper is brutal. Even after the experiments are done, a researcher still faces weeks of translating messy lab notes, scattered results tables, and…

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…