main.py

from  langchain_ollama.llms import OllamaLLM
from langchain_core.prompts import ChatPromptTemplate
from faissdb import retriever

model = OllamaLLM(model="llama3.2")

template = """
You are an exeprt in answering questions about a pizza restaurant

Here are some relevant reviews: {reviews}

Here is the question to answer: {question}
"""
prompt = ChatPromptTemplate.from_template(template)
chain = prompt | model

while True:
    print("\n\n-------------------------------")
    question = input("Ask your question (q to quit): ")
    print("\n\n")
    if question == "q":
        break
    """ #chromadb vector retreiver
    reviews = retriever.invoke(question)
    result = chain.invoke({"reviews": reviews, "question": question})
    print(result)"""
    #with faiss 
    # Fetch relevant documents from FAISS retriever:
    docs = retriever.invoke(question)
    
    # Combine retrieved texts for prompt context
    reviews_text = "\n\n".join([doc.page_content for doc in docs]) or "No relevant reviews found."

    # Generate answer 
    result = chain.invoke({"reviews": reviews_text, "question": question})

    print("\nAnswer:\n", result)