Modification of existing opensource project on langchain, with custom LLM on gradio and opensource vector DB (hyperdb)

I am looking for a freelancer who can make minor adjustments to an existing opensource project on langchain. The ideal candidate should be proficient in Python and have experience with custom LLM on gradio and opensource vector DB (hyperdb). The project has a specific deadline of within 1 week. The starting base implementation is here [login to view URL] The following changes are needed for this project 1. Instead of calling open AI, use another custom LLM based on Gradio (specific API and code can be provided. Adjustment to API can be discussed if needed) 2. Instead of calling pinecone for vector DB, use another custom vector DB (can store locally or remote server). Recommend to use hyperdb or other equivalent. [login to view URL] 3. Implement a thumbs up or down for chat replies, to indicate if response is good or not good. 4. Vector DB UI allows for upload of text files, be it py, xls, sql, text related content to be supported Additional context: 1. API to custom LLM currently look something like this from gradio_client import Client client = Client("[login to view URL]") result = [login to view URL]( "How to start a car dealer business? Give me in point forms", # str in 'Question/Instruction' Textbox component 0.1, # int | float (numeric value between 0.0 and 1.0) in 'Temperature' Slider component 1, # int | float (numeric value between 0.0 and 1) in 'Top-p (nucleus sampling)' Slider component 0, # int | float (numeric value between 0.0 and 200) in 'Top-k' Slider component 1532, # int | float (numeric value between 0 and 1664) in 'Maximum new tokens' Slider component api_name="/predict" ) print(result) 2. We need to be able to maintain conversation context in the chatbot and conversation history logged by sessions. 3. We need to provide a starter contextual prompt so that the chatbot can start the conversation with the context in mind, which in this case can be a particular mission/task to resolve or persona when replying the user in the chat bot 4. You can provide to me the corresponding [login to view URL] of the custom LLM, if you need to to be modified for the need for this project. The source code of that can also be provided.