Please create GenAi chatbot in python with all given context also i have image data that can be feed as input. Title: Development of a Domain$-$Specific Chatbot Using Advanced NLP Techniques$(,$ Retrieval$-$Augmented Generation $($RAG$)$ Framework, and Vector Databases for Procter & Gamble $($P&G$)$

Product Overview: Procter & Gamble $($P&G$)$ is a global leader in consumer goods, offering a diverse portfolio of products that cater to a wide range of needs across households worldwide. With a strongcommitment to innovation and quality, P&G$\text{'}$s products are designed to enhance everydaylife, providing consumers with reliable solutions for personal care, health, hygiene, and homecare.

Introduction to Procter & Gamble Procter & Gamble, commonly known as P&G$,$ has a rich history of over $180$ years, founded in $1837$ by William Procter and James Gamble. Thecompany's mission is to improve the lives of consumers through its trusted brands, which

have become household names across the globe. P&G$\text{'}$s success is driven by itscommitment to understanding consumer needs and delivering high$-$quality products that offer convenience, value, and performance.Categories of P&G Products P&G$\text{'}$s product portfolio is categorized into severalsegments, each tailored to address specific consumer needs. These categories include:

Beauty & Personal Care

Health & Well$-$being

Fabric & Home Care

Baby, Feminine, and Family Care

Each category is supported by well$-$known brands that have earned the trust of millions ofconsumers.Beauty & Personal Care Products P&G$\text{'}$s Beauty & Personal Care segment offers a wide range of products designed to enhance personal appearance and hygiene. Key brands include:Olay: Renowned for its skincare products, Olay provides solutions for anti$-$aging,moisturizing, and overall skin health. Its Regenerist line is particularly popular for itsadvanced anti$-$aging benefits.Pantene: A leading hair care brand, Pantene offers shampoos, conditioners, andstyling products that cater to various hair types. The brand's Pro$-$V formula is known for its ability to nourish and strengthe

Objective: The goal of this project is to design and develop a domain$-$specific Generative AI chatbot that can provide detailed product knowledge and information to users, particularly for a company in the consumer goods industry like P&G$.$ The chatbot will leverage advanced NLP techniques, including various transformer models and a Retrieval$-$Augmented Generation $($RAG$)$ framework, to enhance its ability to understand and respond to user queries accurately. The project should be fully implemented in Python, and all code, documentation, and dependencies should be properly maintained to ensure the solution works effectively.

Scope:

Data Input and Knowledge Base Setup:

Input: The chatbot will use PDF$,$ text, and image data, which will be stored locally in a knowledge base. This data will be stored in a vector database such as Faiss or ChromaDB for fast information retrieval.

Data Processing: The project will involve extracting and processing data from these documents to ensure that they can be efficiently queried by the chatbot.

Model Selection and Fine$-$Tuning:

LLMs: The project will explore the use of various large language models $($LLMs$)$ such as Gemini, GPT$,$ Mistral, and Claude. These models will be evaluated for their ability to handle multimodal data $($text$,$ image$)$ and will undergo hyperparameter tuning.

Embedding Models: An embedding model will be selected and fine$-$tuned using the Hugging Face API to enhance the chatbot's contextual understanding.

Frameworks and Development Environment:

Frameworks: The project will utilize frameworks like LangChain and LlamaIndex for implementing the chatbot and managing the RAG framework.

Prompt Engineering: Chain of Thought prompting will be employed to improve the chatbot's reasoning and response generation capabilities.

Performance Evaluation:

Metrics: The chatbot's performance will be evaluated using a range of metrics, including completeness, coherence, relevance, semantic similarity, correctness, context precision, and context recall

Deployment: The final solution will be deployed using Streamlit, providing an interactive interface for users to engage with the chatbot.

Documentation and Code Requirements:

Code Documentation: The project must include comprehensive documentation covering the development process, code explanations, and usage instructions. The documentation should also include a step$-$by$-$step guide on setting up the environment and running the chatbot.

Working Code: All code must be thoroughly tested to ensure it works as expected. The solution should be implemented entirely in Python, without relying on GPT for assistance.

Requirements.txt: A requirements.txt file should be included, listing all Python packages and dependencies required to run the project. This will ensure that anyone replicating the work can set up the environment without issues.