#pip install -U langchain-ollama

from langchain_core.prompts import ChatPromptTemplate
#from langchain_community.chat_models import ChatOllama
from langchain_ollama import ChatOllama

# --- 4. LLM & RAG Chain ---
print("---STEP 4---")
count = 0

with open('queries_all.txt', 'r', encoding='utf-8') as f:
    for line in f:
        query = line.strip()

        prompt = ChatPromptTemplate.from_messages([
            ("system", ""),
            ("user", "{question}")
        ])

        llm = ChatOllama(
            model="deepseek-r1:70b",
            temperature=0.1,
            base_url="http://195.130.94.63:11434"
        )

        chain = prompt | llm
        response = chain.invoke({"question": query})

        with open('responses_all_ollama_model_deepseek-r1-70b_wo_rag.txt', 'a', encoding='utf-8') as file:
            count += 1
            file.write("Prompt " + str(count) + " :\n" +
                "Question: " + str(query) +
                "\n\nAnwer:\n" +
                str(response.content) + "\n\n")
            print(count)