import os
import requests
import json
from dotenv import load_dotenv

# 🔐 Load token dari .env file (optional, aman buat deploy)
load_dotenv()
HF_TOKEN = os.getenv("HF_TOKEN")

# 🎭 Modifier untuk gaya bahasa (tone)
def apply_tone(prompt, tone):
    tone_instructions = {
        "Formal": "Jawab dengan gaya bahasa formal dan sopan.",
        "Casual": "Jawab dengan gaya santai dan mudah dimengerti.",
        "Humorous": "Jawab dengan gaya lucu dan menghibur.",
        "Professional": "Jawab dengan gaya profesional dan ringkas.",
        "Sarcastic": "Jawab dengan gaya sarkastik tapi tetap informatif."
    }
    instruction = tone_instructions.get(tone, "")
    return f"{instruction}\n\n{prompt}"

# 🌐 Modifier untuk bahasa respon
def apply_language(prompt, language):
    if language == "Indonesia":
        return f"Jawab pertanyaan berikut dalam bahasa Indonesia:\n\n{prompt}"
    elif language == "English":
        return f"Answer the following question in English:\n\n{prompt}"
    elif language == "Chinese":
        return f"请用中文回答以下问题：\n\n{prompt}"
    else:
        return prompt

# 🧾 Modifier untuk format respon
def apply_format(prompt, response_format):
    format_instructions = {
        "Text": "",  # default
        "Bullet Points": "Jawab dalam bentuk poin-poin yang jelas dan terstruktur.",
        "Code": "Jawab dalam format kode atau blok teknis jika memungkinkan."
    }
    instruction = format_instructions.get(response_format, "")
    return f"{instruction}\n\n{prompt}" if instruction else prompt

# 🧠 Query Hugging Face Inference API
def query_huggingface(prompt, model="mistralai/Mistral-7B-Instruct-v0.2", temperature=0.7, max_tokens=500):
    try:
        headers = {
            "Authorization": f"Bearer {HF_TOKEN}",
            "Content-Type": "application/json"
        }
        payload = {
            "inputs": prompt,
            "parameters": {
                "temperature": temperature,
                "max_new_tokens": max_tokens
            }
        }
        response = requests.post(
            f"https://api-inference.huggingface.co/models/{model}",
            headers=headers,
            json=payload
        )
        response.raise_for_status()
        result = response.json()
        if isinstance(result, list):
            return result[0].get("generated_text", "")
        elif isinstance(result, dict) and "generated_text" in result:
            return result["generated_text"]
        else:
            return json.dumps(result)
    except Exception as e:
        return f"⚠️ Error from Hugging Face: {str(e)}"

# 🧠 Query OpenAI backend (DISABLED)
# import openai
# openai.api_key = os.getenv("OPENAI_API_KEY")

# def query_openai(prompt, model="gpt-3.5-turbo", temperature=0.7, max_tokens=500):
#     try:
#         response = openai.ChatCompletion.create(
#             model=model,
#             messages=[{"role": "user", "content": prompt}],
#             temperature=temperature,
#             max_tokens=max_tokens
#         )
#         return response.choices[0].message.content
#     except Exception as e:
#         return f"⚠️ Error from OpenAI: {str(e)}"

# 🔀 Dispatcher untuk backend
def get_response(prompt, backend="HuggingFace", model="mistralai/Mistral-7B-Instruct-v0.2", temperature=0.7, max_tokens=500):
    if backend == "HuggingFace":
        return query_huggingface(prompt, model, temperature, max_tokens)
    # elif backend == "OpenAI":
    #     return query_openai(prompt, model, temperature, max_tokens)
    else:
        return "❌ Backend tidak dikenali."