Browsing: Workflow

print(“\n########## 5. ANALYSIS ##########”) import numpy as np, pandas as pd def find_latest_report(): cands = [] for base in [os.path.expanduser(“~/.local/share/garak/garak_runs”), os.path.expanduser(“~/.cache/garak”), “.”]: cands += glob.glob(os.path.join(base, “**”,…

class SuperClaude: “”” Mimics what Claude Code does at session start: • reads Markdown behavior files for the active command/agent/modes, • concatenates them into one system…

entries = df.index[(df[“pos”].diff() == 1)] exits = df.index[(df[“pos”].diff() == -1)] fig, (ax1, ax2, ax3) = plt.subplots( 3, 1, figsize=(13, 10), sharex=True, gridspec_kw={“height_ratios”: [3, 1, 2]}, )…

— I wasn’t actively looking for Polars. I’ve been on a bit of a Pandas optimization journey lately. First, I wrote about why you should stop…

def cloakbrowser_tutorial_job(): results = { “basic_launch”: None, “advanced_context”: None, “storage_restore”: None, “persistent_profile”: None, “rendered_extraction”: None, “static_parsing”: None, “errors”: [], } print_section(“1. Basic CloakBrowser launch”) browser =…

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…

Hugging Face has released ml-intern, an open-source AI agent designed to automate end-to-end post-training workflows for large language models (LLMs). Built on the company’s smolagents framework,…

of those languages that can make you feel productive almost immediately. That is a big part of why it’s so popular. Moving from idea to working…

In this tutorial, we build a production-style Route Optimizer Agent for a logistics dispatch center using the latest LangChain agent APIs. We design a tool-driven workflow…

In this tutorial, we demonstrate how to move beyond static, code-heavy charts and build a genuinely interactive exploratory data analysis workflow directly using PyGWalker. We start…