import ollama
import re


def detect_language(text):

    arabic_pattern = re.compile(r'[\u0600-\u06FF]')

    if arabic_pattern.search(text):
        return "Arabic"

    return "English"


def generate_final_answer(
    question,
    result,
    metadata=None
):

    language = detect_language(question)

    system_prompt = f"""
You are a professional Data Analysis Assistant.

Rules:
- Answer only based on the dataset uploaded 
- The user's language is {language}.
- ALWAYS answer in {language}.
- Never switch languages.
- Explain results naturally.
- Keep answers concise.
- Do not mention Python code.
- Do not mention calculations.
- Do not explain your reasoning.
- Round long decimal numbers to 3 decimal places.
- If the result is a dictionary, explain it naturally.
- If the result is a list, summarize it naturally.
- If the result is a table, describe it naturally.
"""

    user_prompt = f"""
Question:
{question}

Analysis Result:
{result}

Generate a natural answer for the user.
"""

    response = ollama.chat(
        model="qwen2.5:3b",    # qwen2:7b 
        messages=[
            {
                "role": "system",
                "content": system_prompt
            },
            {
                "role": "user",
                "content": user_prompt
            }
        ]
    )

    return response["message"]["content"]