# OpenAI tool calling with history
# Uses a sample function
import yaml
import gradio as gr
import json
import os
from openai import OpenAI
from dotenv import load_dotenv

load_dotenv()
openai_api_key = os.getenv("OPENAI_API_KEY")

with open('character_config.yaml', 'r') as f:
    char_config = yaml.safe_load(f)

client = OpenAI(api_key=openai_api_key)

# Constants
HISTORY_FILE = char_config['history_file']
MODEL = char_config['model']

SYSTEM_PROMPT = [
    {
        "role": "system",
        "content": char_config['presets']['default']['system_prompt']
    }
]

# Load/save chat history
def load_history():
    if os.path.exists(HISTORY_FILE):
        with open(HISTORY_FILE, "r") as f:
            return json.load(f)
    return SYSTEM_PROMPT.copy()

def save_history(history):
    with open(HISTORY_FILE, "w") as f:
        json.dump(history, f, indent=2)

def get_riko_response_no_tool(messages):
    # Call OpenAI with system prompt + history using the classic Chat API
    response = client.chat.completions.create(
        model=MODEL,
        messages=messages,
        temperature=1,
        top_p=1,
        max_tokens=2048, # Changed from max_output_tokens
        stream=False
    )
    # The classic API returns the text directly here:
    return response.choices[0].message.content

def llm_response(user_input):
    messages = load_history()

    # Append user message to memory (clean text format)
    messages.append({
        "role": "user",
        "content": user_input
    })

    riko_test_response = get_riko_response_no_tool(messages)

    # append assistant message to regular response
    messages.append({
        "role": "assistant",
        "content": riko_test_response
    })

    save_history(messages)
    return riko_test_response

# respond with Long-term memory
def llm_response_with_memory(user_input, context_memory):
    messages = load_history()

    # Safely modify the system prompt (assumes it's always first)
    if messages and messages[0]['role'] == 'system':
        base_content = char_config['presets']['default']['system_prompt']
        messages[0]['content'] = f"{base_content}\n\nThe following memories may or may not be relevent information from past conversations. If it is not relevent to this conversation, ignore it:\n{context_memory}"
    else:
        # Fallback in case system prompt is missing for some reason
        messages.insert(0, {
            "role": "system",
            "content": f"{char_config['presets']['default']['system_prompt']}\n\n[Memory]\n{context_memory}"
        })

    # Append user message to memory (clean text format)
    messages.append({
        "role": "user",
        "content": user_input
    })

    riko_test_response = get_riko_response_no_tool(messages)

    # append assistant message to regular response
    messages.append({
        "role": "assistant",
        "content": riko_test_response
    })

    save_history(messages)
    return riko_test_response

if __name__ == "__main__":
    print('running main')
    # Fixed the test call so it passes a valid message array instead of a raw string
    test_messages = [{"role": "user", "content": "hi riko"}]
    response = get_riko_response_no_tool(test_messages)
    print(response)