#
#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
#
#  Licensed under the Apache License, Version 2.0 (the "License");
#  you may not use this file except in compliance with the License.
#  You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
#  Unless required by applicable law or agreed to in writing, software
#  distributed under the License is distributed on an "AS IS" BASIS,
#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#  See the License for the specific language governing permissions and
#  limitations under the License.
#

import functools
import inspect
import json
import logging
import os
import time
from copy import deepcopy
from functools import wraps
from typing import Any

import requests
import trio
from quart import (
    Response,
    jsonify,
    request
)

from peewee import OperationalError

from common.constants import ActiveEnum
from api.db.db_models import APIToken
from api.utils.json_encode import CustomJSONEncoder
from common.mcp_tool_call_conn import MCPToolCallSession, close_multiple_mcp_toolcall_sessions
from api.db.services.tenant_llm_service import LLMFactoriesService
from common.connection_utils import timeout
from common.constants import RetCode
from common import settings

requests.models.complexjson.dumps = functools.partial(json.dumps, cls=CustomJSONEncoder)


async def _coerce_request_data() -> dict:
    """Fetch JSON body with sane defaults; fallback to form data."""
    payload: Any = None
    last_error: Exception | None = None

    try:
        payload = await request.get_json(force=True, silent=True)
    except Exception as e:
        last_error = e
        payload = None

    if payload is None:
        try:
            form = await request.form
            payload = form.to_dict()
        except Exception as e:
            last_error = e
            payload = None

    if payload is None:
        if last_error is not None:
            raise last_error
        raise ValueError("No JSON body or form data found in request.")

    if isinstance(payload, dict):
        return payload or {}

    if isinstance(payload, str):
        raise AttributeError("'str' object has no attribute 'get'")

    raise TypeError(f"Unsupported request payload type: {type(payload)!r}")

async def get_request_json():
    return await _coerce_request_data()

def serialize_for_json(obj):
    """
    Recursively serialize objects to make them JSON serializable.
    Handles ModelMetaclass and other non-serializable objects.
    """
    if hasattr(obj, "__dict__"):
        # For objects with __dict__, try to serialize their attributes
        try:
            return {key: serialize_for_json(value) for key, value in obj.__dict__.items() if not key.startswith("_")}
        except (AttributeError, TypeError):
            return str(obj)
    elif hasattr(obj, "__name__"):
        # For classes and metaclasses, return their name
        return f"<{obj.__module__}.{obj.__name__}>" if hasattr(obj, "__module__") else f"<{obj.__name__}>"
    elif isinstance(obj, (list, tuple)):
        return [serialize_for_json(item) for item in obj]
    elif isinstance(obj, dict):
        return {key: serialize_for_json(value) for key, value in obj.items()}
    elif isinstance(obj, (str, int, float, bool)) or obj is None:
        return obj
    else:
        # Fallback: convert to string representation
        return str(obj)


def get_data_error_result(code=RetCode.DATA_ERROR, message="Sorry! Data missing!"):
    logging.exception(Exception(message))
    result_dict = {"code": code, "message": message}
    response = {}
    for key, value in result_dict.items():
        if value is None and key != "code":
            continue
        else:
            response[key] = value
    return jsonify(response)


def server_error_response(e):
    # Quart invokes this handler outside the original except block, so we must pass exc_info manually.
    logging.error("Unhandled exception during request", exc_info=(type(e), e, e.__traceback__))
    try:
        msg = repr(e).lower()
        if getattr(e, "code", None) == 401 or ("unauthorized" in msg) or ("401" in msg):
            return get_json_result(code=RetCode.UNAUTHORIZED, message=repr(e))
    except Exception as ex:
        logging.warning(f"error checking authorization: {ex}")

    if len(e.args) > 1:
        try:
            serialized_data = serialize_for_json(e.args[1])
            return get_json_result(code=RetCode.EXCEPTION_ERROR, message=repr(e.args[0]), data=serialized_data)
        except Exception:
            return get_json_result(code=RetCode.EXCEPTION_ERROR, message=repr(e.args[0]), data=None)
    if repr(e).find("index_not_found_exception") >= 0:
        return get_json_result(code=RetCode.EXCEPTION_ERROR, message="No chunk found, please upload file and parse it.")

    return get_json_result(code=RetCode.EXCEPTION_ERROR, message=repr(e))


def validate_request(*args, **kwargs):
    def process_args(input_arguments):
        no_arguments = []
        error_arguments = []
        for arg in args:
            if arg not in input_arguments:
                no_arguments.append(arg)
        for k, v in kwargs.items():
            config_value = input_arguments.get(k, None)
            if config_value is None:
                no_arguments.append(k)
            elif isinstance(v, (tuple, list)):
                if config_value not in v:
                    error_arguments.append((k, set(v)))
            elif config_value != v:
                error_arguments.append((k, v))
        if no_arguments or error_arguments:
            error_string = ""
            if no_arguments:
                error_string += "required argument are missing: {}; ".format(",".join(no_arguments))
            if error_arguments:
                error_string += "required argument values: {}".format(",".join(["{}={}".format(a[0], a[1]) for a in error_arguments]))
            return error_string

    def wrapper(func):
        @wraps(func)
        async def decorated_function(*_args, **_kwargs):
            errs = process_args(await _coerce_request_data())
            if errs:
                return get_json_result(code=RetCode.ARGUMENT_ERROR, message=errs)
            if inspect.iscoroutinefunction(func):
                return await func(*_args, **_kwargs)
            return func(*_args, **_kwargs)

        return decorated_function

    return wrapper


def not_allowed_parameters(*params):
    def decorator(func):
        async def wrapper(*args, **kwargs):
            input_arguments = await _coerce_request_data()
            for param in params:
                if param in input_arguments:
                    return get_json_result(code=RetCode.ARGUMENT_ERROR, message=f"Parameter {param} isn't allowed")
            if inspect.iscoroutinefunction(func):
                return await func(*args, **kwargs)
            return func(*args, **kwargs)
        return wrapper

    return decorator


def active_required(func):
    @wraps(func)
    async def wrapper(*args, **kwargs):
        from api.db.services import UserService
        from api.apps import current_user

        user_id = current_user.id
        usr = UserService.filter_by_id(user_id)
        # check is_active
        if not usr or not usr.is_active == ActiveEnum.ACTIVE.value:
            return get_json_result(code=RetCode.FORBIDDEN, message="User isn't active, please activate first.")
        if inspect.iscoroutinefunction(func):
            return await func(*args, **kwargs)
        return func(*args, **kwargs)

    return wrapper


def get_json_result(code: RetCode = RetCode.SUCCESS, message="success", data=None):
    response = {"code": code, "message": message, "data": data}
    return jsonify(response)


def apikey_required(func):
    @wraps(func)
    async def decorated_function(*args, **kwargs):
        token = request.headers.get("Authorization").split()[1]
        objs = APIToken.query(token=token)
        if not objs:
            return build_error_result(message="API-KEY is invalid!", code=RetCode.FORBIDDEN)
        kwargs["tenant_id"] = objs[0].tenant_id
        if inspect.iscoroutinefunction(func):
            return await func(*args, **kwargs)

        return func(*args, **kwargs)

    return decorated_function


def build_error_result(code=RetCode.FORBIDDEN, message="success"):
    response = {"code": code, "message": message}
    response = jsonify(response)
    response.status_code = code
    return response


def construct_json_result(code: RetCode = RetCode.SUCCESS, message="success", data=None):
    if data is None:
        return jsonify({"code": code, "message": message})
    else:
        return jsonify({"code": code, "message": message, "data": data})


def token_required(func):
    def get_tenant_id(**kwargs):
        if os.environ.get("DISABLE_SDK"):
            return False, get_json_result(data=False, message="`Authorization` can't be empty")
        authorization_str = request.headers.get("Authorization")
        if not authorization_str:
            return False, get_json_result(data=False, message="`Authorization` can't be empty")
        authorization_list = authorization_str.split()
        if len(authorization_list) < 2:
            return False, get_json_result(data=False, message="Please check your authorization format.")
        token = authorization_list[1]
        objs = APIToken.query(token=token)
        if not objs:
            return False, get_json_result(data=False, message="Authentication error: API key is invalid!", code=RetCode.AUTHENTICATION_ERROR)
        kwargs["tenant_id"] = objs[0].tenant_id
        return True, kwargs

    @wraps(func)
    def decorated_function(*args, **kwargs):
        e, kwargs = get_tenant_id(**kwargs)
        if not e:
            return kwargs
        return func(*args, **kwargs)

    @wraps(func)
    async def adecorated_function(*args, **kwargs):
        e, kwargs = get_tenant_id(**kwargs)
        if not e:
            return kwargs
        return await func(*args, **kwargs)

    if inspect.iscoroutinefunction(func):
        return adecorated_function
    return decorated_function


def get_result(code=RetCode.SUCCESS, message="", data=None, total=None):
    """
    Standard API response format:
    {
        "code": 0,
        "data": [...],        # List or object, backward compatible
        "total": 47,          # Optional field for pagination
        "message": "..."      # Error or status message
    }
    """
    response = {"code": code}

    if code == RetCode.SUCCESS:
        if data is not None:
            response["data"] = data
        if total is not None:
            response["total_datasets"] = total
    else:
        response["message"] = message or "Error"

    return jsonify(response)


def get_error_data_result(
    message="Sorry! Data missing!",
    code=RetCode.DATA_ERROR,
):
    result_dict = {"code": code, "message": message}
    response = {}
    for key, value in result_dict.items():
        if value is None and key != "code":
            continue
        else:
            response[key] = value
    return jsonify(response)


def get_error_argument_result(message="Invalid arguments"):
    return get_result(code=RetCode.ARGUMENT_ERROR, message=message)


def get_error_permission_result(message="Permission error"):
    return get_result(code=RetCode.PERMISSION_ERROR, message=message)


def get_error_operating_result(message="Operating error"):
    return get_result(code=RetCode.OPERATING_ERROR, message=message)


def generate_confirmation_token():
    import secrets

    return "ragflow-" + secrets.token_urlsafe(32)


def get_parser_config(chunk_method, parser_config):
    if not chunk_method:
        chunk_method = "naive"

    # Define default configurations for each chunking method
    base_defaults = {
        "table_context_size": 0,
        "image_context_size": 0,
    }
    key_mapping = {
        "naive": {
            "layout_recognize": "DeepDOC",
            "chunk_token_num": 512,
            "delimiter": "\n",
            "auto_keywords": 0,
            "auto_questions": 0,
            "html4excel": False,
            "topn_tags": 3,
            "raptor": {
                "use_raptor": True,
                "prompt": "Please summarize the following paragraphs. Be careful with the numbers, do not make things up. Paragraphs as following:\n      {cluster_content}\nThe above is the content you need to summarize.",
                "max_token": 256,
                "threshold": 0.1,
                "max_cluster": 64,
                "random_seed": 0,
            },
            "graphrag": {
                "use_graphrag": True,
                "entity_types": [
                    "organization",
                    "person",
                    "geo",
                    "event",
                    "category",
                ],
                "method": "light",
            },
        },
        "qa": {"raptor": {"use_raptor": False}, "graphrag": {"use_graphrag": False}},
        "tag": None,
        "resume": None,
        "manual": {"raptor": {"use_raptor": False}, "graphrag": {"use_graphrag": False}},
        "table": None,
        "paper": {"raptor": {"use_raptor": False}, "graphrag": {"use_graphrag": False}},
        "book": {"raptor": {"use_raptor": False}, "graphrag": {"use_graphrag": False}},
        "laws": {"raptor": {"use_raptor": False}, "graphrag": {"use_graphrag": False}},
        "presentation": {"raptor": {"use_raptor": False}, "graphrag": {"use_graphrag": False}},
        "one": None,
        "knowledge_graph": {
            "chunk_token_num": 8192,
            "delimiter": r"\n",
            "entity_types": ["organization", "person", "location", "event", "time"],
            "raptor": {"use_raptor": False},
            "graphrag": {"use_graphrag": False},
        },
        "email": None,
        "picture": None,
    }

    default_config = key_mapping[chunk_method]

    # If no parser_config provided, return default merged with base defaults
    if not parser_config:
        if default_config is None:
            return deep_merge(base_defaults, {})
        return deep_merge(base_defaults, default_config)

    # If parser_config is provided, merge with defaults to ensure required fields exist
    if default_config is None:
        return deep_merge(base_defaults, parser_config)

    # Ensure raptor and graphrag fields have default values if not provided
    merged_config = deep_merge(base_defaults, default_config)
    merged_config = deep_merge(merged_config, parser_config)

    return merged_config


def get_data_openai(id=None, created=None, model=None, prompt_tokens=0, completion_tokens=0, content=None, finish_reason=None, object="chat.completion", param=None, stream=False):
    total_tokens = prompt_tokens + completion_tokens

    if stream:
        return {
            "id": f"{id}",
            "object": "chat.completion.chunk",
            "model": model,
            "choices": [
                {
                    "delta": {"content": content},
                    "finish_reason": finish_reason,
                    "index": 0,
                }
            ],
        }

    return {
        "id": f"{id}",
        "object": object,
        "created": int(time.time()) if created else None,
        "model": model,
        "param": param,
        "usage": {
            "prompt_tokens": prompt_tokens,
            "completion_tokens": completion_tokens,
            "total_tokens": total_tokens,
            "completion_tokens_details": {
                "reasoning_tokens": 0,
                "accepted_prediction_tokens": 0,
                "rejected_prediction_tokens": 0,
            },
        },
        "choices": [
            {
                "message": {"role": "assistant", "content": content},
                "logprobs": None,
                "finish_reason": finish_reason,
                "index": 0,
            }
        ],
    }


def check_duplicate_ids(ids, id_type="item"):
    """
    Check for duplicate IDs in a list and return unique IDs and error messages.

    Args:
        ids (list): List of IDs to check for duplicates
        id_type (str): Type of ID for error messages (e.g., 'document', 'dataset', 'chunk')

    Returns:
        tuple: (unique_ids, error_messages)
            - unique_ids (list): List of unique IDs
            - error_messages (list): List of error messages for duplicate IDs
    """
    id_count = {}
    duplicate_messages = []

    # Count occurrences of each ID
    for id_value in ids:
        id_count[id_value] = id_count.get(id_value, 0) + 1

    # Check for duplicates
    for id_value, count in id_count.items():
        if count > 1:
            duplicate_messages.append(f"Duplicate {id_type} ids: {id_value}")

    # Return unique IDs and error messages
    return list(set(ids)), duplicate_messages


def verify_embedding_availability(embd_id: str, tenant_id: str) -> tuple[bool, Response | None]:
    from api.db.services.llm_service import LLMService
    from api.db.services.tenant_llm_service import TenantLLMService

    """
    Verifies availability of an embedding model for a specific tenant.

    Performs comprehensive verification through:
    1. Identifier Parsing: Decomposes embd_id into name and factory components
    2. System Verification: Checks model registration in LLMService
    3. Tenant Authorization: Validates tenant-specific model assignments
    4. Built-in Model Check: Confirms inclusion in predefined system models

    Args:
        embd_id (str): Unique identifier for the embedding model in format "model_name@factory"
        tenant_id (str): Tenant identifier for access control

    Returns:
        tuple[bool, Response | None]:
        - First element (bool):
            - True: Model is available and authorized
            - False: Validation failed
        - Second element contains:
            - None on success
            - Error detail dict on failure

    Raises:
        ValueError: When model identifier format is invalid
        OperationalError: When database connection fails (auto-handled)

    Examples:
        >>> verify_embedding_availability("text-embedding@openai", "tenant_123")
        (True, None)

        >>> verify_embedding_availability("invalid_model", "tenant_123")
        (False, {'code': 101, 'message': "Unsupported model: <invalid_model>"})
    """
    try:
        llm_name, llm_factory = TenantLLMService.split_model_name_and_factory(embd_id)
        in_llm_service = bool(LLMService.query(llm_name=llm_name, fid=llm_factory, model_type="embedding"))

        tenant_llms = TenantLLMService.get_my_llms(tenant_id=tenant_id)
        is_tenant_model = any(llm["llm_name"] == llm_name and llm["llm_factory"] == llm_factory and llm["model_type"] == "embedding" for llm in tenant_llms)

        is_builtin_model = llm_factory == "Builtin"
        if not (is_builtin_model or is_tenant_model or in_llm_service):
            return False, get_error_argument_result(f"Unsupported model: <{embd_id}>")

        if not (is_builtin_model or is_tenant_model):
            return False, get_error_argument_result(f"Unauthorized model: <{embd_id}>")
    except OperationalError as e:
        logging.exception(e)
        return False, get_error_data_result(message="Database operation failed")

    return True, None


def deep_merge(default: dict, custom: dict) -> dict:
    """
    Recursively merges two dictionaries with priority given to `custom` values.

    Creates a deep copy of the `default` dictionary and iteratively merges nested
    dictionaries using a stack-based approach. Non-dict values in `custom` will
    completely override corresponding entries in `default`.

    Args:
        default (dict): Base dictionary containing default values.
        custom (dict): Dictionary containing overriding values.

    Returns:
        dict: New merged dictionary combining values from both inputs.

    Example:
        >>> from copy import deepcopy
        >>> default = {"a": 1, "nested": {"x": 10, "y": 20}}
        >>> custom = {"b": 2, "nested": {"y": 99, "z": 30}}
        >>> deep_merge(default, custom)
        {'a': 1, 'b': 2, 'nested': {'x': 10, 'y': 99, 'z': 30}}

        >>> deep_merge({"config": {"mode": "auto"}}, {"config": "manual"})
        {'config': 'manual'}

    Notes:
        1. Merge priority is always given to `custom` values at all nesting levels
        2. Non-dict values (e.g. list, str) in `custom` will replace entire values
           in `default`, even if the original value was a dictionary
        3. Time complexity: O(N) where N is total key-value pairs in `custom`
        4. Recommended for configuration merging and nested data updates
    """
    merged = deepcopy(default)
    stack = [(merged, custom)]

    while stack:
        base_dict, override_dict = stack.pop()

        for key, val in override_dict.items():
            if key in base_dict and isinstance(val, dict) and isinstance(base_dict[key], dict):
                stack.append((base_dict[key], val))
            else:
                base_dict[key] = val

    return merged


def remap_dictionary_keys(source_data: dict, key_aliases: dict = None) -> dict:
    """
    Transform dictionary keys using a configurable mapping schema.

    Args:
        source_data: Original dictionary to process
        key_aliases: Custom key transformation rules (Optional)
            When provided, overrides default key mapping
            Format: {<original_key>: <new_key>, ...}

    Returns:
        dict: New dictionary with transformed keys preserving original values

    Example:
        >>> input_data = {"old_key": "value", "another_field": 42}
        >>> remap_dictionary_keys(input_data, {"old_key": "new_key"})
        {'new_key': 'value', 'another_field': 42}
    """
    DEFAULT_KEY_MAP = {
        "chunk_num": "chunk_count",
        "doc_num": "document_count",
        "parser_id": "chunk_method",
        "embd_id": "embedding_model",
    }

    transformed_data = {}
    mapping = key_aliases or DEFAULT_KEY_MAP

    for original_key, value in source_data.items():
        mapped_key = mapping.get(original_key, original_key)
        transformed_data[mapped_key] = value

    return transformed_data


def group_by(list_of_dict, key):
    res = {}
    for item in list_of_dict:
        if item[key] in res.keys():
            res[item[key]].append(item)
        else:
            res[item[key]] = [item]
    return res


def get_mcp_tools(mcp_servers: list, timeout: float | int = 10) -> tuple[dict, str]:
    results = {}
    tool_call_sessions = []
    try:
        for mcp_server in mcp_servers:
            server_key = mcp_server.id

            cached_tools = mcp_server.variables.get("tools", {})

            tool_call_session = MCPToolCallSession(mcp_server, mcp_server.variables)
            tool_call_sessions.append(tool_call_session)

            try:
                tools = tool_call_session.get_tools(timeout)
            except Exception:
                tools = []

            results[server_key] = []
            for tool in tools:
                tool_dict = tool.model_dump()
                cached_tool = cached_tools.get(tool_dict["name"], {})

                tool_dict["enabled"] = cached_tool.get("enabled", True)
                results[server_key].append(tool_dict)

        # PERF: blocking call to close sessions — consider moving to background thread or task queue
        close_multiple_mcp_toolcall_sessions(tool_call_sessions)
        return results, ""
    except Exception as e:
        return {}, str(e)


async def is_strong_enough(chat_model, embedding_model):
    count = settings.STRONG_TEST_COUNT
    if not chat_model or not embedding_model:
        return
    if isinstance(count, int) and count <= 0:
        return

    @timeout(60, 2)
    async def _is_strong_enough():
        nonlocal chat_model, embedding_model
        if embedding_model:
            with trio.fail_after(10):
                _ = await trio.to_thread.run_sync(lambda: embedding_model.encode(["Are you strong enough!?"]))
        if chat_model:
            with trio.fail_after(30):
                res = await trio.to_thread.run_sync(lambda: chat_model.chat("Nothing special.", [{"role": "user", "content": "Are you strong enough!?"}], {}))
            if res.find("**ERROR**") >= 0:
                raise Exception(res)

    # Pressure test for GraphRAG task
    async with trio.open_nursery() as nursery:
        for _ in range(count):
            nursery.start_soon(_is_strong_enough)


def get_allowed_llm_factories() -> list:
    factories = list(LLMFactoriesService.get_all(reverse=True, order_by="rank"))
    if settings.ALLOWED_LLM_FACTORIES is None:
        return factories

    return [factory for factory in factories if factory.name in settings.ALLOWED_LLM_FACTORIES]