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docs: clarify Chain-of-Thought vs ReAct in Unit 1 thoughts section #563
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…arly define Chain-of-Thought (CoT), distinguish it from ReAct, and correct prior conflation. Added comparison table and revised example placement for accuracy.
The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update. |
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Thanks for the contribution!
I appreciate the concerns you've raised and agree that adding more context is valuable. However, I noticed that the new addition appears at the bottom of the previous content, resulting in a lot of duplicated text.
Could we clean that up to avoid repetition?
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Thank you for the review.
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Thanks for the changes
Hi @sergiopaniego, I’ve applied the newline formatting to both blocks to ensure proper MDX rendering, as you suggested. The updated version should now display correctly in the docs. Let me know if there’s anything else you’d like me to adjust. |
This PR addresses issue #525, which noted that the “Thought” section in Unit 1 previously conflated Chain-of-Thought (CoT) with ReAct.
What’s Fixed:
• Clearly defined Chain-of-Thought (CoT) as a separate prompting strategy.
• Clarified ReAct as an extension of CoT that includes external actions and observations.
• Moved the image and explanation of ReAct to the appropriate context.
• Added a comparison table showing CoT vs ReAct in terms of behavior and use cases.
• Updated explanatory on how modern LLMs like DeepSeek R1 and OpenAI’s o1 handle structured internal reasoning.
Outcome:
The revised section now:
• Accurately reflects the original academic papers (Kojima et al. for CoT, Yao et al. for ReAct),
• Eliminates confusion between the two methods, and
• Supports students with a more pedagogically sound and technically correct explanation.