GSAM - GenericSuite App Maker

Key Features: * Answer question with LLM inference, using Meta Llama models, Together.ai, HuggingFace, Groq, Ollama, Nvidia NIMs, and OpenAI. * Image Generation: using HuggingFace and the Flux or OpenAI Dall-E models. * Video Generation: using Rhymes AI Allegro model. * Galleries to show the generated images and videos. * Ability to change the Provider and Model used for all the LLM Inferences, image and video generations. * Suggestions to generate App ideas, and the hability to customize the suggestion generation prompt. * Code Generation: suggest the JSON configuration files and Langchain Tools Python code from an App description to be used with the GenericSuite library. * Use LlamaIndex to generate code and JSON files using vectorized data instead of send all the attachments to the LLM. * Store each user interaction (question, answer, image, video, code) in a MongoDB database, and retrieve it later. * Database Management: import and export data from MongoDB to JSON files. * Prompt Engineering: there's an option to allow the prompts/questions optimization to take more advantage from the Model's capabilities. * Naming: generate name ideas for the App. * App Structure: generate the App description and database table structures. * App Presentation: generate PowerPoint presentation for the App, including the content, speaker notes, and image generation prompts. Technology Used: * Meta Llama models: Llama 3.2 3B, Llama 3.1 8B, 70B, and 405B * Together.ai * Huggingface Inference API * Flux.1 image generation model * Rhymes Allegro video generation model * LlamaIndex framework. * StreamLit * MongoDB Atlas * Python 3.10