LLM-powered interactive demo APP

I need to hire a freelancer to create an interactive demo. The requirements are as follows: This demo does not need to actually train a model. It only needs to implement the following functionalities: Understanding User-Described Scenarios with LLM: Utilize a Large Language Model (LLM) to comprehend the scenarios described by the user. Assisting in Building a Virtual Pipeline: Help the user construct a virtual pipeline based on their described scenario. The pipeline should be as simple as possible and divided into the following modules: Data Collection: Allow the user to select data from a specific time period and recommend an optimal time frame based on the scenario and task. Feature Selection: Suggest training features based on the user's objectives. Model Selection: Choose an appropriate model based on the user's goals. Model Production Environment Admission Standards: Define criteria for deploying the model to the production environment, such as setting a threshold for prediction accuracy before deployment. Parameter Recommendation and Visualization: After the user describes the scenario, the LLM should recommend parameters for each of the four pipeline modules based on the description. Visualize the pipeline by connecting the modules on a canvas. Provide explanations for each module's parameter recommendations. Deployment Simulation: Once the user finalizes their selections and clicks "Deploy," simulate the process of deploying the model to the production line and training it. When the model meets the admission standards, display the results of applying the model to the production line (e.g., improved yield rate). Show real-time feedback of production line data being integrated into the model training CI/CD pipeline, leading to progressively better results (e.g., continuously increasing yield rate). Final Visualization: Gradually pull back the camera view to reveal numerous models continuously training and being deployed across various production lines. Summary of Requirements: No actual model training: The demo should focus on understanding scenarios and building a virtual pipeline using LLM. Simple Pipeline Structure: Data Collection, Feature Selection, Model Selection, and Production Admission Standards. Interactive Visualization: Use a canvas to connect modules and explain parameter choices. Deployment and Feedback Simulation: Show the deployment process, results, and continuous improvement through real-time data feedback. Final Overview: Visual representation of multiple models being trained and deployed across production lines. Please ensure that the demo is user-friendly and visually engaging to effectively demonstrate the pipeline construction and deployment process based on user-described scenarios.