What it does
This platform utilizes advanced semantic search algorithms to analyze and retrieve relevant data from this diverse content repository. After processing the input prompt, the system performs a semantic search to fetch pertinent content, which is then used as references for the language model to enhance the accuracy and relevance of its outputs.
The platform is designed to handle inputs across a diverse formats including images, YouTube links, and pdf files. For videos, it fetches metadata through the YouTube API, which is then effectively summarized using a LLM to provide concise and relevant content overviews. Similarly, the system is equipped to summarize content from images, ensuring a comprehensive and versatile user experience that accommodates various types of media.
Additionally, the platform incorporates the capability to generate images using the Stable Diffusion algorithm, further enriching the user interaction experience by providing visual content generation based on textual prompts. The system stores generated images in Pinata (IPFS) and also maintains a comprehensive chat history, enabling seamless continuity in interactions and the ability to reference previous conversations when needed.
How we built it
NextJS Langchain LangGraph Pinata Huggingface API Ollama LLM Mistal embeddings Postgres Firebase
Built With
- api
- embeddings
- huggingface
- langchain
- langgraph
- llm
- mistal
- nextjs
- ollama
- pinata
- postgresql
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