This n8n workflow creates an advanced, real-time question-answering system using Retrieval-Augmented Generation (RAG) techniques integrated with Telegram and WordPress. It automatically handles user inquiries, processes data, and manages AI-driven responses, making it ideal for interactive customer support, content retrieval, or knowledge base management.
The workflow begins with a Telegram trigger to listen for incoming messages. Based on the message content, it uses a switch node to determine the type of request—whether it’s audio, text, or images—and processes each accordingly. Audio files received via Telegram are sent to OpenAI for transcription, while text or image requests are handled by specified OpenAI or image-processing nodes.
The processed data is then used to generate responses from OpenAI’s language models or an AI agent, which can contextually interact with a user. To enhance data retrieval, the system employs Pinecone vector stores for embedding and storing textual data, enabling efficient similarity searches.
Furthermore, the workflow integrates with Google Docs for document management, schedules automatic runs, and maintains an interactive chat history with a buffer memory node. Sticky notes are employed for manual annotations or debugging purposes, helping users track and adjust different steps.
This setup is particularly useful for businesses seeking to automate customer support, build intelligent FAQ bots, or create interactive content assistants within WordPress sites, ensuring quick, accurate, and scalable AI-powered interactions.
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