This project presents a state-of-the-art chatbot designed to assist pet owners by providing reliable health care information. The bot is built upon the powerful LangChain and LLaMA 2 models, utilizing AWS SageMaker for robust deployment and MongoDB for efficient data handling.
- LangChain Integration: Crafting seamless conversational flows through advanced prompt engineering, ensuring precise user query understanding and response generation.
- LLaMA 2 Model: Utilizes the LLaMA 2 7B model from HuggingFace, offering comprehensive language understanding capabilities.
- Scalable Deployment: Hosting on AWS SageMaker to provide a responsive and scalable chatbot service.
- MongoDB Atlas: Employing MongoDB Atlas as a vector database, enhancing the chatbot's ability to fetch accurate and relevant pet health information quickly.
The chatbot includes a sophisticated data ingestion pipeline that leverages HuggingFace embeddings for document vectorization. This process allows the chatbot to retrieve the most pertinent information in response to user queries.
To get a local copy up and running, follow these simple steps:
- AWS account with SageMaker
- MongoDB Atlas account
- HuggingFace account
- Clone the repo
git clone [email protected]:ykj5060/Pet-Care-Web.git
- Install required packages
pip install -r requirements.txt