chatbot-rag 0.1.5

ChatBot with Retrieval Augmented Generation

ChatBot-RAG

A powerful chatbot implementation using Retrieval Augmented Generation (RAG) to provide context-aware responses based on your data.

Features

• 🔍 Retrieval Augmented Generation: Enhances LLM responses with relevant context from your data
• 🧠 Ollama Support: Run models locally with Ollama for privacy and customization
• 🔗 LangChain Integration: Built on the powerful LangChain framework for advanced chains and pipelines

Installation

pip install chatbot-rag

Requirements

• Python 3.12
• Ollama (for local model hosting)

Quick Start

from chatbot_rag.chat import Chatbot 
from chatbot_rag.RAG import RAG

# Use a specific Ollama model
rag = RAG(path="./data/")
rag()
bot = Chatbot(name="llama3")

# Query with specific parameters
question = "Summarize my recent research on climate change"
context  = rag._search_context(question,k=5)
response = bot(context,question)
print(response)

License

This project is licensed under the Apache 2.0 License - see the LICENSE file for details.