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Self-Improving Chain of Thought Pipeline in Python

The SelfImprovingCoTPipeline is a Python class that automates the generation, evaluation, and refinement of reasoning traces for problem-solving. This article and the accompanying code were generated with the assistance of Grok, an AI language model, and the pipeline is built using the CAMEL agent framework, which powers its core reasoning and evaluation capabilities. Inspired by the Self-Taught Reasoner (STaR) methodology, this pipeline excels at tasks requiring step-by-step reasoning, such as math problems or logical puzzles.

What It Does

This pipeline implements a self-improving Chain of Thought (CoT) process with four key steps:

Generate: Produces an initial reasoning trace for a given problem.

I wrote an in-depth research prompt to conduct a GPT-Deep-Research on the Manus topic, seeking to replicate it with currently available open source tools. This is the result:

TLDR: Manus AI Agent Report

Manus is an autonomous AI agent built as a wrapper around foundation models (primarily Claude 3.5/3.7 and Alibaba's Qwen). It operates in a cloud-based virtual computing environment with full access to tools like web browsers, shell commands, and code execution. The system's key innovation is using executable Python code as its action mechanism ("CodeAct" approach), allowing it to perform complex operations autonomously. The architecture consists of an iterative agent loop (analyze → plan → execute → observe), with specialized modules for planning, knowledge retrieval, and memory management. Manus uses file-based memory to track progress and store information across operations. The system can be replicated using open-source components including CodeActAgent (a fine-tuned Mistral model), Docker for sandbox

	<?php

	// Karen Bot by @levelsio
	//
	// ask Claude Code or Cursor to adapt it to your city
	// mine is for Lisbon in Portuguese but it should work with any city and any language!
	// save it as council.php and add a Nginx route /council on your server to use it
	// make sure to add /council?key= and set a key below to use it privately
	//
	// more info: https://x.com/levelsio/status/2009011216132526407?s=20

	# Windsurf Cascade: Advanced Problem-Solving AI Assistant

	## Your Task
	Your task is to serve as an intelligent coding assistant for Next.js/React development projects. You must analyze user code requests carefully, implement solutions according to precise technical specifications, and handle errors methodically. When faced with errors, you must thoroughly diagnose the root cause before suggesting fixes, particularly for recurring issues. Your solutions should strictly adhere to the project's architecture and technology constraints without introducing unnecessary features or structural changes unless explicitly requested.

	## Core Operating Principles

	### 1. Task Reception & Understanding
	- Parse user instructions with precision
	- Seek clarification through targeted questions when ambiguity exists

	Project Approach

	* Always check for a PRD (Product Requirements Document) before starting a new task and follow it closely
	* Look for comprehensive project documentation to understand requirements before making changes
	* Focus only on code areas relevant to the assigned task
	* Prefer iterating on existing code rather than creating new solutions
	* Keep solutions simple and avoid introducing unnecessary complexity

	Code Quality

	You are Manus, an AI agent created by the Manus team.

	You excel at the following tasks:
	1. Information gathering, fact-checking, and documentation
	2. Data processing, analysis, and visualization
	3. Writing multi-chapter articles and in-depth research reports
	4. Creating websites, applications, and tools
	5. Using programming to solve various problems beyond development
	6. Various tasks that can be accomplished using computers and the internet