from constants import MAX_TOKENS , TEMPERATURE
import os
import requests
import google.generativeai as genai
from dotenv import load_dotenv
load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
genai.configure(api_key=GOOGLE_API_KEY)
model = genai.GenerativeModel('gemini-1.5-flash')

def contruct_prompt(system_prompt:str , user_prompt:str , conversation_history)->str:
    final_prompt = f"""{system_prompt} \n \n
    You strictly follow the instructions given above.\n
    You will also be provided a user query below.\n
    {user_prompt}
    Below is the conversation_history.\n
    {conversation_history}
    Based on the instrcutions given to you and the user query and conversation history understand all of them and give accurate responses.
    """
    return final_prompt 

def get_llm_response(system_prompt, user_prompt, conversation_history):
    generation_config = genai.types.GenerationConfig(
        max_output_tokens=2500,
        temperature=0.0,
    )
    prompt_to_llm = contruct_prompt(system_prompt, user_prompt, conversation_history)
    response = model.generate_content(prompt_to_llm,generation_config=generation_config ,stream=True)
    response.resolve()
    return response.text

# def get_llm_response(system_prompt, user_prompt, conversation_history) -> str:
#     url = "https://api.openai.com/v1/chat/completions"
#     prompt_to_llm = contruct_prompt(system_prompt, user_prompt, conversation_history)
#     headers = {
#         "Content-Type": "application/json",
#         "Authorization": f"Bearer {os.getenv('OPENAI_API_KEY')}",
#         "OpenAI-Organization": os.getenv('ORG_ID')
#     }

#     data = {
#         "model": "gpt-4o-mini",
#         "max_tokens": MAX_TOKENS,
#         "messages": [{"role": "user", "content": f"{prompt_to_llm}"}],
#         "temperature": TEMPERATURE
#     }
#     try:
#         response = requests.post(url, headers=headers, json=data)
#         output = response.json()
#     except Exception as e:
#         print(f"Error Occurred {e}")
#         return f"Error Occurred {e}"

#     return output['choices'][0]['message']['content']