Most Easy Way to Implement RAG with AI Model

 This video is a simple hands-on tutorial to show how to implement RAG with your own files locally by using Cohere Comand R+ model.

Code:

#pip install cohere

import cohere

import os

api_key = os.getenv('COHERE_API_KEY')

co = cohere.Client(api_key)

def read_file(filename):

    try:

        with open(filename, 'r') as file:

            content = file.read()

        return content

    except FileNotFoundError:

        print(f"{filename} not found in the current directory.")

        return None

   

def generate_rag_response_with_citations(query, documents):

    response = co.chat(

        model="command-r",

        message=query,

        documents=documents

    )  

    # Extracting text and citations from the response

    response_text = response.text

    citations = response.citations

    return response_text, citations

filename1 = 'file1.txt'

file_content1 = read_file(filename1)

filename2 = 'file2.txt'

file_content2 = read_file(filename2)

documents = [

    { "title": "Whois", "text": file_content1},

    { "title": "Location", "text": file_content2}

]

#query = "Where Fahd Mirza lives?"

query = "Who is Fahd Mirza?"

text,citation=generate_rag_response_with_citations(query,documents)

print(text)

print(citation)