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Browsing: build
How to Build a Fully Interactive Multi-Page NiceGUI Application with Real-Time Dashboard, CRUD Operations, File Upload, and Async Chat
import sys import subprocess subprocess.run([sys.executable, “-m”, “pip”, “install”, “-q”, “nicegui”], check=True) import threading, time, random, asyncio, base64, socket from datetime import datetime from nicegui import ui,…
class CalculatorSkill(Skill): def _define_metadata(self): return SkillMetadata( name=”calculator”, description=”Evaluate mathematical expressions. Supports arithmetic, powers, and ” “math functions: sqrt, abs, round, log, sin, cos, tan.”, category=SkillCategory.REASONING, tags=[“math”,…
Build a Multi-Agent AI Workflow for Biological Network Modeling, Protein Interactions, Metabolism, and Cell Signaling Simulation
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…
Voice assistants that engage in back-and-forth communication are something you’ve likely experienced. But a voice assistant that provides rational, uninterrupted exchanges via spoken dialogue? That’s what…
Step by Step Guide to Build a Complete PII Detection and Redaction Pipeline with OpenAI Privacy Filter
In this tutorial, we build a complete, production-style pipeline for detecting and redacting personally identifiable information using the OpenAI Privacy Filter. We begin by setting up…
Image by Editor # Introduction Python decorators can be incredibly useful in projects involving AI and machine learning system development. They excel at separating key logic…
(WORK_DIR / “judge.prompty”).write_text(“””— name: Judge model: api: chat configuration: type: openai connection: open_ai_connection model: gpt-4o-mini parameters: temperature: 0 max_tokens: 150 response_format: {type: json_object} inputs: question: {type:…
How to Build a Lightweight Vision-Language-Action-Inspired Embodied Agent with Latent World Modeling and Model Predictive Control
import random, numpy as np, torch, torch.nn as nn, torch.nn.functional as F import matplotlib.pyplot as plt from dataclasses import dataclass from typing import Tuple, Dict, List…
Enterprises building AI agents often require more than what managed foundation model (FM) services can provide. They need precise control over performance tuning, cost optimization at…
Build a Reinforcement Learning Powered Agent that Learns to Retrieve Relevant Long-Term Memories for Accurate LLM Question Answering
@dataclass class MemoryItem: memory_id: int topic: str entity: str slot: str value: str text: str def build_memory_bank() -> List[MemoryItem]: entities = [ { “entity”: “Astra”, “topic”:…
