The article also highlights how Graphlit can ingest additional background information from various sources, such as websites or related documents, which will be incorporated into the platform's conversation responses. The author concludes by stating that Graphlit offers an automated approach to content workflows for creators of podcasts or YouTube video content, integrating any publicly hosted Language Learning Model (LLM) for summary generation and interactive chatbots over content.
Key takeaways:
- Graphlit is a platform that can unlock knowledge contained in unstructured data, such as podcasts, by automating content workflows and generating summaries, headlines, social media posts, timestamped chapters, and follow-up questions.
- Graphlit uses OpenAI GPT-4 Turbo model for content generation and can process content asynchronously, allowing for efficient content management.
- Graphlit can also create interactive chatbots for podcasts, allowing listeners to ask questions and get more information about the episodes. This is done using the Retrieval Augmented Generation (RAG) pattern and Large Language Models (LLMs).
- Graphlit supports chatbot conversations across all media types, not just web pages and audio, and can ingest additional background information from various sources to provide richer conversation responses.