AI-POWERED SEARCH AND CONTEXTUAL COMMENT AUTOMATION
AI & Machine Learning
Developed an AI-powered automation system that discovers relevant web pages through Bing and DuckDuckGo, detects available comment forms, evaluates page relevance using Large Language Models (LLMs), and generates context-aware comments based on the actual page content.
PROJECT OVERVIEW
The goal was to automate the complete workflow of finding relevant articles, verifying that comments are supported, analyzing content with AI, and generating unique comments for suitable pages.
Instead of relying only on keyword matching, the system performs semantic analysis to determine whether a page is actually relevant before generating any content.
WORKFLOW
• Search Bing and DuckDuckGo using configurable keywords.
• Collect and normalize search result URLs.
• Remove duplicates and previously processed pages.
• Load each page and extract article content.
• Detect whether a comment form is available.
• Skip pages without comment functionality.
• Send page content to an AI model for semantic analysis.
• Evaluate topic relevance and confidence.
• Generate a unique context-aware comment for approved pages.
• Save results and processing history.
AI RELEVANCE ANALYSIS
The AI evaluates:
• Main topic of the page.
• Semantic similarity to the target topic.
• Context and intended audience.
• Whether mentioning the target resource would be natural.
• Language detection.
• Confidence score.
• Reason for the decision.
• Recommended comment angle.
The AI returns structured JSON responses, making the workflow predictable and easy to integrate with other automation systems.
COMMENT FORM DETECTION
Before sending a page to the AI, the system checks whether comments are actually supported.
Detected elements include:
• WordPress comment forms.
• Custom HTML comment forms.
• Textarea and input fields.
• Author, email and website fields.
• Submit buttons.
• Hidden form parameters.
• Closed comments.
• Authentication requirements.
This optimization significantly reduces unnecessary AI requests by processing only pages where interaction is possible.
KEY FEATURES
• Bing & DuckDuckGo search automation.
• Keyword-based page discovery.
• URL normalization and deduplication.
• HTML parsing and content extraction.
• Comment form detection.
• AI-powered semantic relevance analysis.
• Context-aware AI comment generation.
• Multilingual content support.
• Prompt customization.
• Structured JSON outputs.
• Multithreaded processing.
• Proxy support.
• Retry and timeout handling.
• Processing history.
• SQLite database.
• CSV export.
• Detailed logging.
TECHNOLOGY
Python, LLM APIs, Prompt Engineering, HTTP Requests, HTML Parsing, SQLite, JSON, Multithreading, Semantic Analysis, Web Automation.
RESULT
The system automates the entire pipeline—from search engine discovery to AI-assisted relevance analysis and contextual comment generation. By combining traditional web automation with LLM-based semantic understanding, it delivers significantly more accurate results than keyword filtering alone while reducing manual research and improving scalability.
For confidentiality reasons, production prompts, customer data, target resources, and search keywords are not included.
PROJECT OVERVIEW
The goal was to automate the complete workflow of finding relevant articles, verifying that comments are supported, analyzing content with AI, and generating unique comments for suitable pages.
Instead of relying only on keyword matching, the system performs semantic analysis to determine whether a page is actually relevant before generating any content.
WORKFLOW
• Search Bing and DuckDuckGo using configurable keywords.
• Collect and normalize search result URLs.
• Remove duplicates and previously processed pages.
• Load each page and extract article content.
• Detect whether a comment form is available.
• Skip pages without comment functionality.
• Send page content to an AI model for semantic analysis.
• Evaluate topic relevance and confidence.
• Generate a unique context-aware comment for approved pages.
• Save results and processing history.
AI RELEVANCE ANALYSIS
The AI evaluates:
• Main topic of the page.
• Semantic similarity to the target topic.
• Context and intended audience.
• Whether mentioning the target resource would be natural.
• Language detection.
• Confidence score.
• Reason for the decision.
• Recommended comment angle.
The AI returns structured JSON responses, making the workflow predictable and easy to integrate with other automation systems.
COMMENT FORM DETECTION
Before sending a page to the AI, the system checks whether comments are actually supported.
Detected elements include:
• WordPress comment forms.
• Custom HTML comment forms.
• Textarea and input fields.
• Author, email and website fields.
• Submit buttons.
• Hidden form parameters.
• Closed comments.
• Authentication requirements.
This optimization significantly reduces unnecessary AI requests by processing only pages where interaction is possible.
KEY FEATURES
• Bing & DuckDuckGo search automation.
• Keyword-based page discovery.
• URL normalization and deduplication.
• HTML parsing and content extraction.
• Comment form detection.
• AI-powered semantic relevance analysis.
• Context-aware AI comment generation.
• Multilingual content support.
• Prompt customization.
• Structured JSON outputs.
• Multithreaded processing.
• Proxy support.
• Retry and timeout handling.
• Processing history.
• SQLite database.
• CSV export.
• Detailed logging.
TECHNOLOGY
Python, LLM APIs, Prompt Engineering, HTTP Requests, HTML Parsing, SQLite, JSON, Multithreading, Semantic Analysis, Web Automation.
RESULT
The system automates the entire pipeline—from search engine discovery to AI-assisted relevance analysis and contextual comment generation. By combining traditional web automation with LLM-based semantic understanding, it delivers significantly more accurate results than keyword filtering alone while reducing manual research and improving scalability.
For confidentiality reasons, production prompts, customer data, target resources, and search keywords are not included.