https://github.com/soumyadeepbose/jessup-cellar-rag-app
Jessup's Helper is a Retrieval Based Chatbot that uses a pre-trained Llama3-8b model to generate responses to user input. Groq has been used for a near instant inference because of the high token speed, and Google Gen AI Studio API has been used to get the embeddings. The model uses a PDF file for information retrieval based responses.
https://github.com/soumyadeepbose/jessup-cellar-rag-app
chatbot genai genai-chatbot groq groq-api llama llama3 llm rag
Last synced: 6 months ago
JSON representation
Jessup's Helper is a Retrieval Based Chatbot that uses a pre-trained Llama3-8b model to generate responses to user input. Groq has been used for a near instant inference because of the high token speed, and Google Gen AI Studio API has been used to get the embeddings. The model uses a PDF file for information retrieval based responses.
- Host: GitHub
- URL: https://github.com/soumyadeepbose/jessup-cellar-rag-app
- Owner: soumyadeepbose
- License: mit
- Created: 2024-07-19T21:33:18.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-07-23T21:49:52.000Z (about 1 year ago)
- Last Synced: 2025-04-08T09:06:32.452Z (6 months ago)
- Topics: chatbot, genai, genai-chatbot, groq, groq-api, llama, llama3, llm, rag
- Language: Python
- Homepage: https://jessup-cellar.streamlit.app/
- Size: 296 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
Awesome Lists containing this project
README
# Jessup's Helper 🤖
Jessup's Helper is a Retrieval Based Chatbot that uses a pre-trained Llama3-8b model to generate responses to user input. Groq has been used for a near instant inference because of the high token speed, and Google Gen AI Studio API has been used to get the embeddings. The model uses a PDF file for information retrieval and generation of responses based on the context. The PDF file can be found in the 'pdfs' folder.
## Live Demo
The project is hosted on Streamlit and can be accessed [here](https://jessup-cellar.streamlit.app/).
## Getting Started
These instructions will guide you through getting a copy of the project up and running on your local machine for development and testing purposes.
### Prerequisites
First of, you will need to clone the repository to your local machine. You can do this by running the following command in your terminal:
```bash
git clone https://github.com/soumyadeepbose/Jessup-Cellar-RAG-App.git
```
Next, you will need to install the required packages. You can do this by running the following command in your terminal:
```bash
pip install -r requirements.txt
```
### Setting up the Environment Variables
You will need to set up the environment variables. For this, you need to create a `.env` file in the root directory of the project. The `.env` file should contain the following environment variables:
- `GOOGLE_API_KEY`: This is the API key for the Google Gen AI Studio API. You can get this by following the instructions [here](https://ai.google.dev/aistudio).
- `GROQ_API_KEY`: This is the API key for the Groq API. You can get this by following the instructions [here](https://groq.com/).
### Running the App
Now to run the app, you will need to run the following command in your terminal:
```bash
streamlit run app.py
```
## Author
- [Soumyadeep Bose 😊](https://www.linkedin.com/in/soumyadeepbose)