from google import genai
import os
import logging
import json
import requests
from datetime import datetime

# Configure logging
log_directory = os.getenv("LOG_DIR", "logs")
os.makedirs(log_directory, exist_ok=True)
log_file = os.path.join(
    log_directory, f"llm_calls_{datetime.now().strftime('%Y%m%d')}.log"
)

# Set up logger
logger = logging.getLogger("llm_logger")
logger.setLevel(logging.INFO)
logger.propagate = False  # Prevent propagation to root logger
file_handler = logging.FileHandler(log_file, encoding='utf-8')
file_handler.setFormatter(
    logging.Formatter("%(asctime)s - %(levelname)s - %(message)s")
)
logger.addHandler(file_handler)

# Simple cache configuration
cache_file = "llm_cache.json"

def call_llm(prompt, use_cache: bool = True) -> str:
    """
    Call an LLM provider based on environment variables.
    Environment variables:
    - LLM_PROVIDER: "OLLAMA" or "XAI"
    - <provider>_MODEL: Model name (e.g., OLLAMA_MODEL, XAI_MODEL)
    - <provider>_BASE_URL: Base URL without endpoint (e.g., OLLAMA_BASE_URL, XAI_BASE_URL)
    - <provider>_API_KEY: API key (e.g., OLLAMA_API_KEY, XAI_API_KEY; optional for providers that don't require it)
    The endpoint /v1/chat/completions will be appended to the base URL.
    """
    logger.info(f"PROMPT: {prompt}") # log the prompt

    # Read the provider from environment variable
    provider = os.environ.get("LLM_PROVIDER")
    if not provider:
        raise ValueError("LLM_PROVIDER environment variable is required")

    # Construct the names of the other environment variables
    model_var = f"{provider}_MODEL"
    base_url_var = f"{provider}_BASE_URL"
    api_key_var = f"{provider}_API_KEY"

    # Read the provider-specific variables
    model = os.environ.get(model_var)
    base_url = os.environ.get(base_url_var)
    api_key = os.environ.get(api_key_var, "")  # API key is optional, default to empty string

    # Validate required variables
    if not model:
        raise ValueError(f"{model_var} environment variable is required")
    if not base_url:
        raise ValueError(f"{base_url_var} environment variable is required")

    # Append the endpoint to the base URL
    url = f"{base_url}/v1/chat/completions"

    # Configure headers and payload based on provider
    headers = {
        "Content-Type": "application/json",
    }
    if api_key:  # Only add Authorization header if API key is provided
        headers["Authorization"] = f"Bearer {api_key}"

    payload = {
        "model": model,
        "messages": [{"role": "user", "content": prompt}],
        "temperature": 0.7,
    }

    try:
        response = requests.post(url, headers=headers, json=payload)
        response_json = response.json() # Log the response
        logger.info("RESPONSE:\n%s", json.dumps(response_json, indent=2))
        #logger.info(f"RESPONSE: {response.json()}")
        response.raise_for_status()
        return response.json()["choices"][0]["message"]["content"]
    except requests.exceptions.HTTPError as e:
        error_message = f"HTTP error occurred: {e}"
        try:
            error_details = response.json().get("error", "No additional details")
            error_message += f" (Details: {error_details})"
        except:
            pass
        raise Exception(error_message)
    except requests.exceptions.ConnectionError:
        raise Exception(f"Failed to connect to {provider} API. Check your network connection.")
    except requests.exceptions.Timeout:
        raise Exception(f"Request to {provider} API timed out.")
    except requests.exceptions.RequestException as e:
        raise Exception(f"An error occurred while making the request to {provider}: {e}")
    except ValueError:
        raise Exception(f"Failed to parse response as JSON from {provider}. The server might have returned an invalid response.")

if __name__ == "__main__":
    test_prompt = "Hello, how are you?"

    # First call - should hit the API
    print("Making call...")
    response1 = call_llm(test_prompt, use_cache=False)
    print(f"Response: {response1}")