Content creation for YouTube requires engaging titles and well-structured scripts to capture audience interest. This publication presents the YouTube GPT Creator, a Streamlit-based web application that automates the generation of YouTube video titles and scripts using OpenAI's GPT model. Additionally, the system leverages Wikipedia API for research enrichment, enhancing the factual accuracy of the generated content. This project integrates LangChain for prompt structuring and memory handling, OpenAI API for AI-powered text generation, Wikipedia API to fetch real-world data, and Streamlit for an intuitive web interface. By the end of this publication, readers will understand how AI-powered tools can streamline YouTube content creation, saving time and improving quality.

The YouTube GPT Creator follows a structured pipeline, starting with user input, where a topic is entered into the Streamlit interface. The application then generates an engaging YouTube title using OpenAI's API before retrieving relevant content from Wikipedia to enhance script accuracy. Finally, based on the generated title and Wikipedia research, the AI produces a structured YouTube video script. The content is displayed in an interactive interface with options to view past history. The tech stack includes Python as the programming language, while the key libraries include Streamlit for the web application, LangChain for managing prompts, OpenAI API for text generation, Wikipedia API for factual data retrieval, and ConversationBufferMemory to retain prompt history.

The implementation begins with title generation, where the system uses a predefined prompt template to request a catchy video title from OpenAI. For example, a template instructs OpenAI to generate an engaging title based on a given topic. Once the title is generated, the system queries Wikipedia for additional context using the Wikipedia API Wrapper. This retrieved data ensures that the AI-generated script incorporates factual insights. The next step is script generation, where the OpenAI model takes both the generated title and Wikipedia research to create a detailed script. The structured prompt instructs OpenAI to produce a script while leveraging Wikipedia insights. Finally, all outputs are displayed using Streamlit, allowing users to interact with the results, expand sections to view history, and refine their prompts as needed.

For a sample topic such as "Artificial Intelligence in 2025", the system generated a title: "The Future of AI in 2025: What's Next?". The corresponding script included an introduction discussing advancements in AI, potential industry impacts, and predictions for the near future. Performance testing showed that title and script generation took under 5 seconds, making the system efficient. Additionally, the integration of Wikipedia enhanced the factual accuracy of generated scripts. The Streamlit interface proved to be user-friendly, allowing easy access to generated content and previous results. However, certain limitations were identified. The system currently relies heavily on Wikipedia, which may not always provide the most updated or comprehensive information. Future improvements could involve incorporating alternative sources like the Google Search API. Additionally, the application does not yet support AI-generated thumbnails, which could enhance video engagement. Another potential improvement is SEO optimization, where AI could suggest relevant keywords and hashtags for better video ranking on YouTube.