Skill UI

Expert guidance for fine-tuning LLMs with Axolotl, covering YAML configs, LoRA/QLoRA/DPO variants, multimodal support, and practical troubleshooting patterns for development and training workflows.

This SDK provides programmatic access to Azure AI Content Understanding, enabling the extraction of structured and semantic content from diverse multimodal sources. It supports analyzing documents (PDF, etc.), images, audio, and video files. Users can leverage prebuilt analyzers (like invoice or document search) or create custom analyzers with specific field schemas for advanced RAG and automated workflow implementations.

This SDK provides programmatic access to Azure AI Content Understanding, enabling the extraction of structured and semantic content from diverse multimodal sources. It supports analyzing documents (PDF, etc.), images, audio, and video files. Users can leverage prebuilt analyzers (like invoice or document search) or create custom analyzers with specific field schemas for advanced RAG and automated workflow implementations.

A comprehensive TypeScript client for the Azure Document Intelligence REST API. This SDK allows developers to programmatically extract structured data, text, and tables from various document types, including PDFs and images. It supports using prebuilt models (like invoices, receipts, and IDs) and building custom models for specialized document processing workflows.

A comprehensive TypeScript client for the Azure Document Intelligence REST API. This SDK allows developers to programmatically extract structured data, text, and tables from various document types, including PDFs and images. It supports using prebuilt models (like invoices, receipts, and IDs) and building custom models for specialized document processing workflows.

This is a high-level Software Development Kit (SDK) designed for managing the full lifecycle of AI projects within Azure AI Foundry. Built for Java, it provides robust client interfaces for core AI operations, including managing connections to Azure resources, uploading and managing datasets, creating and updating search indexes, running model evaluations, and handling deployments. It streamlines complex AI workflow orchestration.

This is a high-level Software Development Kit (SDK) designed for managing the full lifecycle of AI projects within Azure AI Foundry. Built for Java, it provides robust client interfaces for core AI operations, including managing connections to Azure resources, uploading and managing datasets, creating and updating search indexes, running model evaluations, and handling deployments. It streamlines complex AI workflow orchestration.

Automate Bannerbear operations through the Composio Rube MCP toolkit by discovering up-to-date tools, ensuring active connections, and executing schema-compliant operations with memory-aware multi-tool calls.

Automated guidance for batch request handler tasks inside API integration workflows, covering best practices, code generation, webhook patterns, and validations when dealing with third-party APIs.

Use Composio’s Botpress toolkit through Rube MCP to orchestrate Botpress workflows: always search tools for the latest schemas, confirm the Botpress connection, then execute discovered operations via RUBE_MULTI_EXECUTE_TOOL with schema-compliant inputs.

Automate Botsonic operations through Composio’s toolkit by routing every workflow via the Rube MCP endpoints, emphasizing tool discovery, connection validation, and schema-compliant executions before running multi-step plans.

Automate Breezy HR workflows through Composio’s Breezy HR toolkit via the Rube MCP interface, covering discovery, connection checks, and execution while always querying current schemas before running tools.