RAG Bank Chatbot

A chatbot designed to assist with Sparkassen documents using Redis and Ollama for efficient data retrieval and language processing.

Features

⚠️ Note that this chatbot is a prototype and says a lot of nonsensical things. That's maybe because we use a rather small model, for it to run locally on a laptop.

Nonetheless, it has all the following features:

• Document Ingestion: Automatically downloads, converts, and indexes Sparkassen documents.
• Vector Search: Utilizes Redis for fast and relevant document retrieval based on user queries.
• Interactive Chat: Engages users in natural language conversations.
• Dockerized Setup: Easily deployable using Docker Compose for seamless environment management.

Prerequisites

• Docker: Ensure Docker is installed on your Linux system. Install Docker
• Docker Compose: Make sure Docker Compose is installed. Install Docker Compose

Installation

1. Clone the Repository:

   git clone https://github.com/yourusername/sparkassen-chatbot.git
   cd sparkassen-chatbot

2. Start the Chatbot:

   Simply run the following command to build and start the chatbot:

   docker compose run -it llm_rag

   ⚠️ It may take some time for this command to finish, without there being a whole lot of console logging.

   This command will:

   • Build the necessary Docker images.
   • Start the Ollama and Redis services.
   • Download the Llama3.2:1b from Ollama.
   • Ingest Sparkasse documents into Redis.
   • Launch the chatbot in interactive mode.

3. (Optional) Langsmith tracking:

   If you want to use Langsmith to track your conversations, add a file named secrets.env to the base directory and enter LANGCHAIN_API_KEY=<your-key>.

Usage

Once the chatbot is running, you can interact with it directly in your terminal:

============================================================
🏦 Willkommen bei Ihrem Sparkassen-Assistenten!
Ich kann Ihnen Fragen zu Sparkassen-Dokumenten beantworten.
Sie können jederzeit 'exit' eingeben, um zu beenden.
============================================================

➤ Hi

[Chatbot Response...]

➤ exit

Auf Wiedersehen! 👋

• Ask Questions: Type your queries related to Sparkassen documents.
• Exit: Type exit, quit, or q to terminate the session.