chatbot_logic.py

from langchain_core.runnables import RunnableLambda, RunnablePassthrough
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.output_parsers import StrOutputParser
from langchain_huggingface import HuggingFaceEndpoint
import os

def create_chatbot_chain():
    """
    Creates a modular chatbot using LangChain Runnables
    """
    
    # Initialize Hugging Face LLM
    llm = HuggingFaceEndpoint(
        repo_id="mistralai/Mistral-7B-Instruct-v0.2",
        task="text-generation",
        max_new_tokens=512,
        temperature=0.7,
        token=os.getenv("HUGGINGFACEHUB_API_TOKEN")
    )
    
    # Define prompt template
    prompt = ChatPromptTemplate.from_messages([
        ("system", "You are a helpful AI assistant. You can answer questions, tell jokes, and have friendly conversations."),
        ("human", "{input}")
    ])
    
    # Create Runnable chain
    chain = (
        {"input": RunnablePassthrough()}
        | prompt
        | llm
        | StrOutputParser()
        | RunnableLambda(lambda x: {"output": x})
    )
    
    return chain