import asyncio
import logging
from datetime import datetime
from typing import TYPE_CHECKING, List, Optional

from jinja2 import Template, TemplateSyntaxError
from pydantic import BaseModel, Field, field_validator

# Forward referencing to avoid circular import with Agent -> Memory -> Agent
if TYPE_CHECKING:
    pass

from openai.types.beta.function_tool import FunctionTool as OpenAITool

from letta.constants import CORE_MEMORY_BLOCK_CHAR_LIMIT
from letta.otel.tracing import trace_method
from letta.schemas.block import Block, FileBlock
from letta.schemas.message import Message


class ContextWindowOverview(BaseModel):
    """
    Overview of the context window, including the number of messages and tokens.
    """

    # top-level information
    context_window_size_max: int = Field(..., description="The maximum amount of tokens the context window can hold.")
    context_window_size_current: int = Field(..., description="The current number of tokens in the context window.")

    # context window breakdown (in messages)
    # (technically not in the context window, but useful to know)
    num_messages: int = Field(..., description="The number of messages in the context window.")
    num_archival_memory: int = Field(..., description="The number of messages in the archival memory.")
    num_recall_memory: int = Field(..., description="The number of messages in the recall memory.")
    num_tokens_external_memory_summary: int = Field(
        ..., description="The number of tokens in the external memory summary (archival + recall metadata)."
    )
    external_memory_summary: str = Field(
        ..., description="The metadata summary of the external memory sources (archival + recall metadata)."
    )

    # context window breakdown (in tokens)
    # this should all add up to context_window_size_current

    num_tokens_system: int = Field(..., description="The number of tokens in the system prompt.")
    system_prompt: str = Field(..., description="The content of the system prompt.")

    num_tokens_core_memory: int = Field(..., description="The number of tokens in the core memory.")
    core_memory: str = Field(..., description="The content of the core memory.")

    num_tokens_summary_memory: int = Field(..., description="The number of tokens in the summary memory.")
    summary_memory: Optional[str] = Field(None, description="The content of the summary memory.")

    num_tokens_functions_definitions: int = Field(..., description="The number of tokens in the functions definitions.")
    functions_definitions: Optional[List[OpenAITool]] = Field(..., description="The content of the functions definitions.")

    num_tokens_messages: int = Field(..., description="The number of tokens in the messages list.")
    # TODO make list of messages?
    # messages: List[dict] = Field(..., description="The messages in the context window.")
    messages: List[Message] = Field(..., description="The messages in the context window.")


class Memory(BaseModel, validate_assignment=True):
    """

    Represents the in-context memory (i.e. Core memory) of the agent. This includes both the `Block` objects (labelled by sections), as well as tools to edit the blocks.

    """

    # Memory.block contains the list of memory blocks in the core memory
    blocks: List[Block] = Field(..., description="Memory blocks contained in the agent's in-context memory")
    file_blocks: List[FileBlock] = Field(
        default_factory=list, description="Special blocks representing the agent's in-context memory of an attached file"
    )

    @field_validator("file_blocks")
    @classmethod
    def validate_file_blocks_no_duplicates(cls, v: List[Block]) -> List[Block]:
        """Validate that file_blocks don't contain duplicate labels, log warnings and remove duplicates."""
        if not v:
            return v

        seen_labels = set()
        unique_blocks = []
        duplicate_labels = []

        for block in v:
            if block.label in seen_labels:
                duplicate_labels.append(block.label)
            else:
                seen_labels.add(block.label)
                unique_blocks.append(block)

        if duplicate_labels:
            logger = logging.getLogger(__name__)
            logger.warning(f"Duplicate block labels found in file_blocks: {duplicate_labels}. Removing duplicates.")

        return unique_blocks

    # Memory.template is a Jinja2 template for compiling memory module into a prompt string.
    prompt_template: str = Field(
        default="{% for block in blocks %}"
        "<{{ block.label }}>\n"
        "<metadata>"
        'read_only="{{ block.read_only}}" chars_current="{{ block.value|length }}" chars_limit="{{ block.limit }}"'
        "</metadata>"
        "<value>"
        "{{ block.value }}\n"
        "</value>"
        "</{{ block.label }}>\n"
        "{% if not loop.last %}\n{% endif %}"
        "{% endfor %}",
        description="Jinja2 template for compiling memory blocks into a prompt string",
    )

    def get_prompt_template(self) -> str:
        """Return the current Jinja2 template string."""
        return str(self.prompt_template)

    @trace_method
    def set_prompt_template(self, prompt_template: str):
        """
        Set a new Jinja2 template string.
        Validates the template syntax and compatibility with current memory structure.
        """
        try:
            # Validate Jinja2 syntax
            Template(prompt_template)

            # Validate compatibility with current memory structure
            Template(prompt_template).render(blocks=self.blocks, file_blocks=self.file_blocks, sources=[], max_files_open=None)

            # If we get here, the template is valid and compatible
            self.prompt_template = prompt_template
        except TemplateSyntaxError as e:
            raise ValueError(f"Invalid Jinja2 template syntax: {str(e)}")
        except Exception as e:
            raise ValueError(f"Prompt template is not compatible with current memory structure: {str(e)}")

    @trace_method
    async def set_prompt_template_async(self, prompt_template: str):
        """
        Async version of set_prompt_template that doesn't block the event loop.
        """
        try:
            # Validate Jinja2 syntax with async enabled
            Template(prompt_template)

            # Validate compatibility with current memory structure - use async rendering
            template = Template(prompt_template)
            await asyncio.to_thread(template.render, blocks=self.blocks, file_blocks=self.file_blocks, sources=[], max_files_open=None)

            # If we get here, the template is valid and compatible
            self.prompt_template = prompt_template
        except TemplateSyntaxError as e:
            raise ValueError(f"Invalid Jinja2 template syntax: {str(e)}")
        except Exception as e:
            raise ValueError(f"Prompt template is not compatible with current memory structure: {str(e)}")

    @trace_method
    def compile(self, tool_usage_rules=None, sources=None, max_files_open=None) -> str:
        """Generate a string representation of the memory in-context using the Jinja2 template"""
        try:
            template = Template(self.prompt_template)
            return template.render(
                blocks=self.blocks,
                file_blocks=self.file_blocks,
                tool_usage_rules=tool_usage_rules,
                sources=sources,
                max_files_open=max_files_open,
            )
        except TemplateSyntaxError as e:
            raise ValueError(f"Invalid Jinja2 template syntax: {str(e)}")
        except Exception as e:
            raise ValueError(f"Prompt template is not compatible with current memory structure: {str(e)}")

    @trace_method
    async def compile_async(self, tool_usage_rules=None, sources=None, max_files_open=None) -> str:
        """Async version of compile that doesn't block the event loop"""
        try:
            template = Template(self.prompt_template, enable_async=True)
            return await template.render_async(
                blocks=self.blocks,
                file_blocks=self.file_blocks,
                tool_usage_rules=tool_usage_rules,
                sources=sources,
                max_files_open=max_files_open,
            )
        except TemplateSyntaxError as e:
            raise ValueError(f"Invalid Jinja2 template syntax: {str(e)}")
        except Exception as e:
            raise ValueError(f"Prompt template is not compatible with current memory structure: {str(e)}")

    @trace_method
    async def compile_in_thread_async(self, tool_usage_rules=None, sources=None, max_files_open=None) -> str:
        """Compile the memory in a thread"""
        return await asyncio.to_thread(self.compile, tool_usage_rules=tool_usage_rules, sources=sources, max_files_open=max_files_open)

    def list_block_labels(self) -> List[str]:
        """Return a list of the block names held inside the memory object"""
        # return list(self.memory.keys())
        return [block.label for block in self.blocks]

    # TODO: these should actually be label, not name
    def get_block(self, label: str) -> Block:
        """Correct way to index into the memory.memory field, returns a Block"""
        keys = []
        for block in self.blocks:
            if block.label == label:
                return block
            keys.append(block.label)
        raise KeyError(f"Block field {label} does not exist (available sections = {', '.join(keys)})")

    def get_blocks(self) -> List[Block]:
        """Return a list of the blocks held inside the memory object"""
        # return list(self.memory.values())
        return self.blocks

    def set_block(self, block: Block):
        """Set a block in the memory object"""
        for i, b in enumerate(self.blocks):
            if b.label == block.label:
                self.blocks[i] = block
                return
        self.blocks.append(block)

    def update_block_value(self, label: str, value: str):
        """Update the value of a block"""
        if not isinstance(value, str):
            raise ValueError("Provided value must be a string")

        for block in self.blocks:
            if block.label == label:
                block.value = value
                return
        raise ValueError(f"Block with label {label} does not exist")


# TODO: ideally this is refactored into ChatMemory and the subclasses are given more specific names.
class BasicBlockMemory(Memory):
    """
    BasicBlockMemory is a basic implemention of the Memory class, which takes in a list of blocks and links them to the memory object. These are editable by the agent via the core memory functions.

    Attributes:
        memory (Dict[str, Block]): Mapping from memory block section to memory block.

    Methods:
        core_memory_append: Append to the contents of core memory.
        core_memory_replace: Replace the contents of core memory.
    """

    def __init__(self, blocks: List[Block] = []):
        """
        Initialize the BasicBlockMemory object with a list of pre-defined blocks.

        Args:
            blocks (List[Block]): List of blocks to be linked to the memory object.
        """
        super().__init__(blocks=blocks)

    def core_memory_append(agent_state: "AgentState", label: str, content: str) -> Optional[str]:  # type: ignore
        """
        Append to the contents of core memory.

        Args:
            label (str): Section of the memory to be edited.
            content (str): Content to write to the memory. All unicode (including emojis) are supported.

        Returns:
            Optional[str]: None is always returned as this function does not produce a response.
        """
        current_value = str(agent_state.memory.get_block(label).value)
        new_value = current_value + "\n" + str(content)
        agent_state.memory.update_block_value(label=label, value=new_value)
        return None

    def core_memory_replace(agent_state: "AgentState", label: str, old_content: str, new_content: str) -> Optional[str]:  # type: ignore
        """
        Replace the contents of core memory. To delete memories, use an empty string for new_content.

        Args:
            label (str): Section of the memory to be edited.
            old_content (str): String to replace. Must be an exact match.
            new_content (str): Content to write to the memory. All unicode (including emojis) are supported.

        Returns:
            Optional[str]: None is always returned as this function does not produce a response.
        """
        current_value = str(agent_state.memory.get_block(label).value)
        if old_content not in current_value:
            raise ValueError(f"Old content '{old_content}' not found in memory block '{label}'")
        new_value = current_value.replace(str(old_content), str(new_content))
        agent_state.memory.update_block_value(label=label, value=new_value)
        return None


class ChatMemory(BasicBlockMemory):
    """
    ChatMemory initializes a BaseChatMemory with two default blocks, `human` and `persona`.
    """

    def __init__(self, persona: str, human: str, limit: int = CORE_MEMORY_BLOCK_CHAR_LIMIT):
        """
        Initialize the ChatMemory object with a persona and human string.

        Args:
            persona (str): The starter value for the persona block.
            human (str): The starter value for the human block.
            limit (int): The character limit for each block.
        """
        # TODO: Should these be CreateBlocks?
        super().__init__(blocks=[Block(value=persona, limit=limit, label="persona"), Block(value=human, limit=limit, label="human")])


class UpdateMemory(BaseModel):
    """Update the memory of the agent"""


class ArchivalMemorySummary(BaseModel):
    size: int = Field(..., description="Number of rows in archival memory")


class RecallMemorySummary(BaseModel):
    size: int = Field(..., description="Number of rows in recall memory")


class CreateArchivalMemory(BaseModel):
    text: str = Field(..., description="Text to write to archival memory.")
    tags: Optional[List[str]] = Field(None, description="Optional list of tags to attach to the memory.")
    created_at: Optional[datetime] = Field(None, description="Optional timestamp for the memory (defaults to current UTC time).")


class ArchivalMemorySearchResult(BaseModel):
    timestamp: str = Field(..., description="Timestamp of when the memory was created, formatted in agent's timezone")
    content: str = Field(..., description="Text content of the archival memory passage")
    tags: List[str] = Field(default_factory=list, description="List of tags associated with this memory")


class ArchivalMemorySearchResponse(BaseModel):
    results: List[ArchivalMemorySearchResult] = Field(..., description="List of search results matching the query")
    count: int = Field(..., description="Total number of results returned")