AI & Machine Learning Skills

Helps with AI, data modeling as part of building AI and machine learning applications workflows.

Searches local files using Google Gemini's capabilities to find relevant information based on your prompts.

Helps with LLMs, pipeline automation as part of building AI and machine learning applications workflows.

Leverage OpenAI Assistants directly within your workflows for advanced conversation, task delegation, and intelligent automation.

Helps with LLMs, patterns as part of building AI and machine learning applications workflows.

Helps with OpenAI, MCP tools as part of building AI and machine learning applications workflows.

Provides LLMs guidance and assistance for building AI and machine learning applications.

Helps with image processing, code generation as part of building AI and machine learning applications workflows.

Helps with AI, data modeling, web development as part of building AI and machine learning applications workflows.

This skill optimizes AI prompts for better responses by refining instructions and techniques – crucial for maximizing model performance.

Implement robust Retrieval Augmented Generation (RAG) pipelines using langchain4j patterns for enhanced AI knowledge access.

Crafts highly effective prompts for large language models, boosting output quality and streamlining AI workflows for optimal results.

Transcribes audio into text using OpenAI's Whisper model, enabling voice command processing and content analysis.

Optimizes prompts for better AI responses by suggesting refinements and variations to improve clarity & effectiveness.

Gemini provides creative text generation – ideal for brainstorming content, crafting stories, and exploring diverse writing styles efficiently.

Retrieval-Augmented Generation (RAG) enhances LLMs by retrieving relevant context from external data sources, boosting accuracy and knowledge.

The Rag Engineer skill automatically constructs high-quality retrieval augmented generation (RAG) pipelines for seamless knowledge integration and improved AI responses.

Seedance Prompt En generates diverse and creative prompts based on a given seed, boosting brainstorming & content generation efficiency.

This Rag implementation facilitates Retrieval-Augmented Generation by providing a structured framework for integrating external knowledge into AI responses, boosting accuracy and context.

Provides AI guidance and assistance for building AI and machine learning applications.

Generates high-quality embeddings using GrepAI and Ollama for semantic search, similarity analysis, and knowledge graph construction.

Provides LLMs guidance and assistance for building AI and machine learning applications.

Generate images from text prompts using Google's Gemini model, offering creative visuals based on your descriptions.

Provides constructive, detailed feedback on written work, mimicking a helpful peer review process using jezweb's Gemini model.