import json
import time
import tiktoken

class OpenaiStreamOutputer:
    """
    Create chat completion - OpenAI API Documentation
    * https://platform.openai.com/docs/api-reference/chat/create
    """

    def __init__(self):
        current_time = int(time.time())
        self.default_data = {
            "id": "chatcmpl-hugginface",
            "object": "chat.completion.chunk",
            "created": current_time,
            "model": "hugginface",
            "system_fingerprint": "fp_44709d6fcb",
            "choices": [],
            "usage": {
                "prompt_tokens": 0,
                "completion_tokens": 0,
                "total_tokens": 0
            }
        }

    def data_to_string(self, data={}, content_type=""):
        data_str = f"{json.dumps(data)}"
        return data_str

    def output(self, content=None, content_type="Completions", tokens_count=0) -> str:
        data = self.default_data.copy()
        if content_type == "Role":
            data["choices"] = [
                {
                    "index": 0,
                    "message": {
                        "role": "assistant",
                        "content": content,
                    },
                    "logprobs": None,
                    "finish_reason": "stop"
                }
            ]
        elif content_type in [
            "Completions",
            "InternalSearchQuery",
            "InternalSearchResult",
            "SuggestedResponses",
        ]:
            if content_type in ["InternalSearchQuery", "InternalSearchResult"]:
                content += "\n"
            data["choices"] = [
                {
                    "index": 0,
                    "message": {
                        "role": "user",
                        "content": content,
                    },
                    "logprobs": None,
                    "finish_reason": None,
                }
            ]
        elif content_type == "Finished":
            data["choices"] = [
                {
                    "index": 0,
                    "message": {
                        "role": "assistant",
                        "content": content,
                    },
                    "logprobs": None,
                    "finish_reason": "stop",
                }
            ]
        else:
            data["choices"] = [
                {
                    "index": 0,
                    "message": {
                        "role": "assistant",
                        "content": content,
                    },
                    "logprobs": None,
                    "finish_reason": None,
                }
            ]

        # Update token counts
        tokens_used = len(content.split())
        self.token_manager.add_tokens(tokens_used)  # hypothetical method
        data["usage"]["prompt_tokens"] += tokens_count
        data["usage"]["completion_tokens"] += tokens_used
        data["usage"]["total_tokens"] = self.token_manager.get_total_tokens()  # hypothetical method

        return self.data_to_string(data, content_type)