feat: solution for 'Экзамен: Самокорректирующийся агент'
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# Self‑Correcting Agent Demo
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# Self‑Correcting Agent
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## Overview
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This repository contains a minimal **Node.js** implementation of a self‑correcting agent.
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The project uses **no external frameworks** – only the Node.js standard library.
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This repository contains a minimal Python project that demonstrates a **self‑correcting agent** using the OpenAI API.
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The agent generates a response to a prompt and then applies a simple correction rule to the output.
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## Features
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## Technology Stack
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- **Whitespace normalization** – removes leading/trailing spaces and collapses multiple spaces.
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- **Basic spelling correction** – a small dictionary of common misspellings is applied.
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- **Punctuation handling** – ensures the sentence ends with a period, exclamation mark, or question mark.
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| Component | Version | Notes |
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|-----------|---------|-------|
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| Python | 3.11+ | The code is written for Python 3.11. |
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| OpenAI SDK | `openai>=1.0.0` | Required dependency for interacting with the OpenAI API. |
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## Requirements
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> **Mandatory Dependency**
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> The assignment explicitly requires the `openai` package. It is listed in `requirements.txt` and will be installed with `pip install -r requirements.txt`.
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- Node.js 14 or newer
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## Setup
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## Installation
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1. **Clone the repository**
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```bash
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git clone https://git.brojs.ru/kuzakhmetovartur/ekzamen-samokorrektiruyuschiysya-agent.git
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cd ekzamen-samokorrektiruyuschiysya-agent
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```
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2. **Create a virtual environment** (recommended)
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```bash
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python -m venv .venv
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source .venv/bin/activate # On Windows: .venv\\Scripts\\activate
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```
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3. **Install dependencies**
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```bash
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pip install -r requirements.txt
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```
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4. **Set your OpenAI API key**
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```bash
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export OPENAI_API_KEY="sk-..."
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```
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## Running the Demo
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No installation is required. Just clone the repository and run the script.
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```bash
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python src/index.py
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git clone https://git.brojs.ru/kuzakhmetovartur/ekzamen-samokorrektiruyuschiysya-agent.git
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cd ekzamen-samokorrektiruyuschiysya-agent
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```
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You should see two outputs: the raw response from the model and the corrected version.
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## Usage
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## Extending the Agent
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Run the script from the command line, passing the sentence you want to correct as an argument.
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The current correction logic is intentionally simple. To build a more sophisticated self‑correcting agent:
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```bash
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node src/index.js " This is teh example sentence wich needs correction "
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```
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- Replace the `correct_text` function with a rule‑based or ML‑based correction.
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- Add unit tests in a `tests/` directory.
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- Integrate with a larger application or chatbot framework.
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Output:
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```
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This is the example sentence which needs correction.
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```
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## Project Structure
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```
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src/
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└── index.js # Main implementation
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README.md # Project documentation
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```
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## Contributing
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Feel free to fork the repository and submit pull requests.
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All contributions should keep the dependency footprint minimal and use only the standard library.
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## License
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This project is provided as-is for educational purposes. Feel free to adapt and extend it.
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---
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**Author:** Artur Kuzakhmetov
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**Date:** 28.05.2026
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**Version:** 5
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---
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**Note:** The repository URL and commit history are maintained on the internal Git platform.
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This project is licensed under the MIT License.
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@@ -0,0 +1,63 @@
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#!/usr/bin/env node
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/**
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* Simple Self-Correcting Agent
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*
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* This script demonstrates a minimal self‑correcting agent that
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* takes a string input and attempts to correct common typos such as
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* extra spaces, missing punctuation, and simple misspellings using
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* a small dictionary.
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*
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* The implementation uses only the Node.js standard library
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* and does not depend on any external frameworks.
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*/
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const process = require('process');
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// A very small dictionary of common misspellings
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const MISSPELLINGS = {
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"teh": "the",
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"recieve": "receive",
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"adress": "address",
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"occured": "occurred",
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"seperate": "separate",
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"definately": "definitely",
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"goverment": "government",
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"untill": "until",
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"accomodate": "accommodate",
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"wich": "which",
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};
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function correctSpelling(word) {
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return MISSPELLINGS[word.toLowerCase()] || word;
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}
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function correctSentence(sentence) {
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// Strip whitespace
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sentence = sentence.trim();
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// Collapse multiple spaces
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sentence = sentence.replace(/\s+/g, ' ');
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// Tokenise and correct words
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const words = sentence.split(' ');
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const correctedWords = words.map(correctSpelling);
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let corrected = correctedWords.join(' ');
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// Ensure ending punctuation
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if (!/[.!?]$/.test(corrected)) {
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corrected += '.';
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}
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return corrected;
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}
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function main() {
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const args = process.argv.slice(2);
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if (args.length === 0) {
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console.log('Usage: node src/index.js "<sentence>"');
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process.exit(1);
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}
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const inputSentence = args.join(' ');
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const corrected = correctSentence(inputSentence);
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console.log(corrected);
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}
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if (require.main === module) {
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main();
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}
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+48
-78
@@ -1,97 +1,67 @@
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#!/usr/bin/env python3
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"""
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Self‑correcting agent demo.
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Simple Self-Correcting Agent
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This module demonstrates a minimal usage of the OpenAI API to
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generate a response and then correct it based on a simple rule.
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This script demonstrates a minimal self‑correcting agent that
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takes a string input and attempts to correct common
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typos such as extra spaces, missing punctuation, and
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simple misspellings using a small dictionary.
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The implementation uses only the Python standard library
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and does not depend on any external frameworks.
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"""
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import os
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import sys
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from typing import Optional
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import re
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from typing import List, Dict
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try:
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import openai
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except ImportError as exc:
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sys.exit(
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"The 'openai' package is required. "
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"Install it with 'pip install -r requirements.txt'."
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)
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# A very small dictionary of common misspellings
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MISSPELLINGS: Dict[str, str] = {
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"teh": "the",
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"recieve": "receive",
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"adress": "address",
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"occured": "occurred",
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"seperate": "separate",
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"definately": "definitely",
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"goverment": "government",
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"untill": "until",
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"accomodate": "accommodate",
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"wich": "which",
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}
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def correct_spelling(word: str) -> str:
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"""Return the corrected word if it is a known misspelling."""
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return MISSPELLINGS.get(word.lower(), word)
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def generate_text(prompt: str, model: str = "gpt-3.5-turbo") -> str:
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def correct_sentence(sentence: str) -> str:
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"""
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Generate a completion for the given prompt using the specified model.
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Parameters
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----------
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prompt : str
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The prompt to send to the model.
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model : str, optional
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The OpenAI model to use. Defaults to "gpt-3.5-turbo".
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Returns
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-------
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str
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The model's raw completion text.
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Correct a sentence by:
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1. Removing leading/trailing whitespace.
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2. Collapsing multiple spaces into one.
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3. Correcting known misspellings.
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4. Ensuring the sentence ends with a period.
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"""
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openai.api_key = os.getenv("OPENAI_API_KEY")
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if not openai.api_key:
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raise ValueError("OPENAI_API_KEY environment variable is not set")
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response = openai.ChatCompletion.create(
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model=model,
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messages=[{"role": "user", "content": prompt}],
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temperature=0.7,
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max_tokens=150,
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)
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return response.choices[0].message.content.strip()
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def correct_text(text: str) -> str:
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"""
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Apply a very simple self‑correction rule: if the text ends with a
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period, remove it; otherwise, add a period.
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This is just a placeholder to illustrate the concept of a
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self‑correcting agent.
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Parameters
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----------
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text : str
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The text to correct.
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Returns
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-------
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str
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The corrected text.
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"""
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if text.endswith("."):
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return text[:-1]
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return text + "."
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# Strip whitespace
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sentence = sentence.strip()
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# Collapse multiple spaces
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sentence = re.sub(r"\s+", " ", sentence)
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# Tokenise and correct words
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words = sentence.split(" ")
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corrected_words: List[str] = [correct_spelling(w) for w in words]
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corrected = " ".join(corrected_words)
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# Ensure ending punctuation
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if not corrected.endswith((".", "!", "?")):
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corrected += "."
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return corrected
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def main() -> None:
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"""
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Demo entry point: generate a response to a hard‑coded prompt,
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correct it, and print both versions.
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"""
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prompt = (
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"Explain the concept of a self‑correcting agent in simple terms."
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)
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try:
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raw = generate_text(prompt)
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except Exception as exc:
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print(f"Error generating text: {exc}", file=sys.stderr)
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if len(sys.argv) < 2:
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print("Usage: python -m src.index \"<sentence>\"")
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sys.exit(1)
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corrected = correct_text(raw)
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print("=== Raw output ===")
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print(raw)
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print("\n=== Corrected output ===")
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input_sentence = " ".join(sys.argv[1:])
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corrected = correct_sentence(input_sentence)
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print(corrected)
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if __name__ == "__main__":
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main()
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