import base64
import json
import re
from typing import Dict

import requests

from mm_agents.gpt_4v_prompt_action import SYS_PROMPT as SYS_PROMPT_ACTION
from mm_agents.gpt_4v_prompt_code import SYS_PROMPT as SYS_PROMPT_CODE


# Function to encode the image
def encode_image(image_path):
    with open(image_path, "rb") as image_file:
        return base64.b64encode(image_file.read()).decode('utf-8')


def parse_actions_from_string(input_string):
    # Search for a JSON string within the input string
    actions = []
    matches = re.findall(r'```json\s+(.*?)\s+```', input_string, re.DOTALL)
    if matches:
        # Assuming there's only one match, parse the JSON string into a dictionary
        try:
            for match in matches:
                action_dict = json.loads(match)
                actions.append(action_dict)
            return actions
        except json.JSONDecodeError as e:
            return f"Failed to parse JSON: {e}"
    else:
        matches = re.findall(r'```\s+(.*?)\s+```', input_string, re.DOTALL)
        if matches:
            # Assuming there's only one match, parse the JSON string into a dictionary
            try:
                for match in matches:
                    action_dict = json.loads(match)
                    actions.append(action_dict)
                return actions
            except json.JSONDecodeError as e:
                return f"Failed to parse JSON: {e}"
        else:
            try:
                action_dict = json.loads(input_string)
                return [action_dict]
            except json.JSONDecodeError as e:
                raise ValueError("Invalid response format: " + input_string)


def parse_code_from_string(input_string):
    # This regular expression will match both ```code``` and ```python code```
    # and capture the `code` part. It uses a non-greedy match for the content inside.
    pattern = r"```(?:\w+\s+)?(.*?)```"
    # Find all non-overlapping matches in the string
    matches = re.findall(pattern, input_string, re.DOTALL)

    # The regex above captures the content inside the triple backticks.
    # The `re.DOTALL` flag allows the dot `.` to match newline characters as well,
    # so the code inside backticks can span multiple lines.

    # matches now contains all the captured code snippets
    return matches


class GPT4v_Agent:
    def __init__(self, api_key, model="gpt-4-vision-preview", max_tokens=300, action_space="computer_13"):
        self.model = model
        self.max_tokens = max_tokens
        self.action_space = action_space

        self.headers = {
            "Content-Type": "application/json",
            "Authorization": f"Bearer {api_key}"
        }

        self.trajectory = [
            {
                "role": "system",
                "content": [
                    {
                        "type": "text",
                        "text": {
                            "computer_13": SYS_PROMPT_ACTION,
                            "pyautogui": SYS_PROMPT_CODE
                        }[action_space]
                    },
                ]
            }
        ]

    def predict(self, obs: Dict):
        """
        Predict the next action(s) based on the current observation.
        """
        base64_image = encode_image(obs["screenshot"])
        self.trajectory.append({
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "To accomplish the task '{}' and given the current screenshot, what's the next step?".format(
                        obs["instruction"])
                },
                {
                    "type": "image_url",
                    "image_url": {
                        "url": f"data:image/jpeg;base64,{base64_image}"
                    }
                }
            ]
        })

        traj_to_show = []
        for i in range(len(self.trajectory)):
            traj_to_show.append(self.trajectory[i]["content"][0]["text"])
            if len(self.trajectory[i]["content"]) > 1:
                traj_to_show.append("screenshot_obs")

        print("Trajectory:", traj_to_show)

        payload = {
            "model": self.model,
            "messages": self.trajectory,
            "max_tokens": self.max_tokens
        }
        response = requests.post("https://api.openai.com/v1/chat/completions", headers=self.headers, json=payload)

        try:
            actions = self.parse_actions(response.json()['choices'][0]['message']['content'])
        except:
            # todo: add error handling
            print("Failed to parse action from response:", response.json()['choices'][0]['message']['content'])
            actions = None

        return actions

    def parse_actions(self, response: str):
        # response example
        """
        ```json
        {
          "action_type": "CLICK",
          "click_type": "RIGHT"
        }
        ```
        """

        # parse from the response
        if self.action_space == "computer_13":
            actions = parse_actions_from_string(response)
        elif self.action_space == "pyautogui":
            actions = parse_code_from_string(response)

        # add action into the trajectory
        self.trajectory.append({
            "role": "assistant",
            "content": [
                {
                    "type": "text",
                    "text": response
                },
            ]
        })

        return actions