Browsing: Pipelines

This week, Anthropic released Claude Science. It is an app for scientists, available in beta. It runs on Anthropic’s existing Claude models, not a new model.…

base_g = ( graphistry .bind(source=”src”, destination=”dst”, node=”id”) .edges(edges_df) .nodes(nodes_df) .bind( edge=”edge_id”, edge_title=”edge_title”, edge_label=”edge_label”, edge_weight=”event_count”, edge_size=”edge_size”, point_title=”point_title”, point_label=”label”, point_color=”node_color”, point_size=”node_size”, point_x=”x”, point_y=”y” ) .settings(url_params={“play”: 0, “info”: “true”})…

Today, Mistral AI released OCR 4, its latest document-understanding model. This new release adds bounding boxes, block classification, and inline confidence scores alongside extracted text. It…

TL;DR don’t just pause your agents. They ruin your data structure if you swap models without changing the payload. A basic fallback router shows a 100%…

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…

JetBrains released Mellum2, open-sourcing the weights under the Apache 2.0 license. The first version of Mellum was a completion-focused 4B dense model. Mellum2 is its successor:…

banner(“1) logger.configure(): handlers + custom level + extra + patcher”) mem = MemorySink() logger.configure( handlers=[ {“sink”: sys.stderr, “format”: console_formatter, “level”: “DEBUG”, “colorize”: True, “backtrace”: True, “diagnose”:…

print(“\n” + “=”*70 + “\n SECTION 6 — NetworkX analytics\n” + “=”*70) def kg_to_networkx(graph): G = nx.MultiDiGraph() for e in graph.entities: G.add_node(e) for s, p, o…

us three weeks to ship a single data pipeline. Today, an analyst with zero Python experience does it in a day. Here’s how we got there.…

consumer = huey.create_consumer( workers=4, worker_type=WORKER_THREAD, periodic=True, initial_delay=0.1, backoff=1.15, max_delay=2.0, scheduler_interval=1, check_worker_health=True, health_check_interval=10, flush_locks=False, ) consumer_thread = threading.Thread(target=consumer.run, daemon=True) consumer_thread.start() print(“Consumer started (threaded).”) print(“\nEnqueue basics…”) r1 =…