GenAI Processors provides a library of reusable, configurable processors to build end-to-end generative AI workflows. Developers can ingest documents, break them into semantic chunks, generate embeddings, store and query vectors, apply retrieval strategies, and dynamically construct prompts for large language model calls. Its plug-and-play design allows easy extension of custom processing steps, seamless integration with Google Cloud services or external vector stores, and orchestration of complex RAG pipelines for tasks such as question answering, summarization, and knowledge retrieval.

Split Prompt is a specialized tool designed to handle long prompts by splitting them into smaller, ChatGPT-compatible chunks. Catering to extensive texts, it precisely divides them using token-counting methods, ensuring minimal segments for optimized processing. This tool simplifies the interaction with ChatGPT, removing the constraints of character limits, thus enabling more seamless and efficient usage of the AI model for detailed and expanded textual inputs.

BulkCorrector is a cutting-edge tool designed to streamline the process of bulk text corrections. By automating text segmentation and flawlessly reassembling documents, it offers a seamless editing experience. Ideal for professional writers, editors, and anyone dealing with large volumes of text, BulkCorrector allows for significant time savings and improved accuracy, making it an indispensable part of your writing arsenal.

Content Summarizer with AI Agents orchestrates a sequence of specialized AI agents to streamline content summarization workflows. A FetchAgent retrieves text from URLs or local files, while a PreprocessingAgent cleans and segments content. A SummarizationAgent generates concise summaries for each segment using GPT models, and a FeedbackAgent iteratively refines the output for coherence and relevance. The tool supports customization of summary length and tone, handles long documents through chunking, and produces final summaries in plain text or JSON formats. It requires a valid OpenAI API key and runs in a standard Python environment.