CalcCracker/singleLLM.py at main · tomrudyk/CalcCracker · GitHub

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# {
# Using VirtualchatbotTest memory
# (venv) python3 -m venv chatbotTest
# (venv) source chatbotTest/bin/activate
# (chatbotTest) (venv)
# }


import json
from langchain_core.prompts import ChatPromptTemplate

from langchain_ollama import ChatOllama
from langchain_core.output_parsers import StrOutputParser


templateChat="""
You are given a sentence in Hebrew.
The text may contain incorrect syntax.
Return the correct way to say the same sentence.

Here is the text:
{text_no_nikud}

Answer:
"""
modelLlama3_8_Normal = ChatOllama(model="llama3.1:8b")
## Notice - OllamaLLM is !NOT! ChatOllama (used in the start)
promptChat = ChatPromptTemplate.from_template(templateChat)
chatAI = promptChat | modelLlama3_8_Normal | StrOutputParser()


def handle_conv():
    history=""
    print("Welcome to Chat, type exit to quit.")
    while True:
        userInput = input("Input: ")
        if userInput.lower() =="exit":
            break

        result = chatAI.invoke({"text_no_nikud":userInput})

        print("AI: ", result)
        history = history + f"\nUser: {userInput}\nAI: {result}"


handle_conv()