Investigate natural langugage processing shcemes private LLM development using LLMs. Our aims are to explore the state-of-the-art natural language processing algorithms using LLMs for achieving effective long-term memory and private systems(LLM/RAG) and improving performance as in:
1. Motivation
- Needs for contextual information
2. Research goal and issue
- Goal : Develop a mechanism to provide contextual information
- Issue
3. Approach
- Develop a pipeline for injecting contextual information
- Scenarios
4. Result on scenario1
- Retrieve restaurant information near the user's current GPS coordinates using a map API, and filter this information based on the user's specific query
- Scroll 15 restaurant based on current location
- Distance is derived based on User's GPS coordinates between restuarant location
- Use hte Maps API to search for nearby restaurant information and convert their data into contextual data to enhance the responsiveness of your LLM model
- Context information is crucial for improving the accuracy and relevance of language model responses
- The utilization of context information is necessary for answering difficult questions, such as understanding the specific food a user wnats to better meet their needs
- To prevent hallucinations from unclear details, responses should more effectively utilize exact restaurant information such as distance, address, and restaurant category.
