discordbot/cogs/rule34_cog.py

import discord
from discord.ext import commands, tasks
from discord import app_commands
import typing  # Need this for Optional
import logging
import re  # For _get_response_text, if copied

# Google Generative AI Imports (using Vertex AI backend)
from google import genai
from google.genai import types
from google.api_core import exceptions as google_exceptions

# Import project configuration for Vertex AI
from gurt.config import PROJECT_ID, LOCATION
from gurt.api import get_genai_client_for_model

from .gelbooru_watcher_base_cog import GelbooruWatcherBaseCog

# Setup logger for this cog
log = logging.getLogger(__name__)

# Define standard safety settings using google.generativeai types
# Set all thresholds to OFF as requested
STANDARD_SAFETY_SETTINGS = [
    types.SafetySetting(
        category=types.HarmCategory.HARM_CATEGORY_HATE_SPEECH, threshold="BLOCK_NONE"
    ),
    types.SafetySetting(
        category=types.HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT,
        threshold="BLOCK_NONE",
    ),
    types.SafetySetting(
        category=types.HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT,
        threshold="BLOCK_NONE",
    ),
    types.SafetySetting(
        category=types.HarmCategory.HARM_CATEGORY_HARASSMENT, threshold="BLOCK_NONE"
    ),
]


# --- Helper Function to Safely Extract Text (copied from teto_cog.py) ---
def _get_response_text(
    response: typing.Optional[types.GenerateContentResponse],
) -> typing.Optional[str]:
    """
    Safely extracts the text content from the first text part of a GenerateContentResponse.
    Handles potential errors and lack of text parts gracefully.
    """
    if not response:
        # log.debug("[_get_response_text] Received None response object.")
        return None

    if hasattr(response, "text") and response.text:
        # log.debug("[_get_response_text] Found text directly in response.text attribute.")
        return response.text

    if not response.candidates:
        # log.debug(f"[_get_response_text] Response object has no candidates. Response: {response}")
        return None

    try:
        candidate = response.candidates[0]
        if not hasattr(candidate, "content") or not candidate.content:
            # log.debug(f"[_get_response_text] Candidate 0 has no 'content'. Candidate: {candidate}")
            return None
        if not hasattr(candidate.content, "parts") or not candidate.content.parts:
            # log.debug(f"[_get_response_text] Candidate 0 content has no 'parts' or parts list is empty. types.Content: {candidate.content}")
            return None

        for i, part in enumerate(candidate.content.parts):
            if hasattr(part, "text") and part.text is not None:
                if isinstance(part.text, str) and part.text.strip():
                    # log.debug(f"[_get_response_text] Found non-empty text in part {i}.")
                    return part.text
                else:
                    # log.debug(f"[_get_response_text] types.Part {i} has 'text' attribute, but it's empty or not a string: {part.text!r}")
                    pass  # Continue searching
        # log.debug(f"[_get_response_text] No usable text part found in candidate 0 after iterating through all parts.")
        return None

    except (AttributeError, IndexError, TypeError) as e:
        # log.warning(f"[_get_response_text] Error accessing response structure: {type(e).__name__}: {e}")
        # log.debug(f"Problematic response object: {response}")
        return None
    except Exception as e:
        # log.error(f"[_get_response_text] Unexpected error extracting text: {e}")
        # log.debug(f"Response object during error: {response}")
        return None


class Rule34Cog(GelbooruWatcherBaseCog):  # Removed name="Rule34"
    # Define the command group specific to this cog
    r34watch = app_commands.Group(
        name="r34watch", description="Manage Rule34 tag watchers for new posts."
    )

    def __init__(self, bot: commands.Bot):
        super().__init__(
            bot=bot,
            cog_name="Rule34",
            api_base_url="https://api.rule34.xxx/index.php",
            default_tags="kasane_teto breast_milk",  # Example default, will be overridden if tags are required
            is_nsfw_site=True,
            command_group_name="r34watch",  # For potential use in base class messages
            main_command_name="rule34",  # For potential use in base class messages
            post_url_template="https://rule34.xxx/index.php?page=post&s=view&id={}",
        )
        # Initialize Google GenAI Client for Vertex AI
        try:
            if PROJECT_ID and LOCATION:
                self.genai_client = genai.Client(
                    vertexai=True,
                    project=PROJECT_ID,
                    location=LOCATION,
                )
                log.info(
                    f"Rule34Cog: Google GenAI Client initialized for Vertex AI project '{PROJECT_ID}' in location '{LOCATION}'."
                )
            else:
                self.genai_client = None
                log.warning(
                    "Rule34Cog: PROJECT_ID or LOCATION not found in config. Google GenAI Client not initialized."
                )
        except Exception as e:
            self.genai_client = None
            log.error(
                f"Rule34Cog: Error initializing Google GenAI Client for Vertex AI: {e}"
            )

        self.tag_transformer_model = (
            "gemini-2.0-flash-lite-001"  # Hardcoded as per request
        )
        # The __init__ in base class handles session creation and task starting.

    async def _transform_tags_ai(self, user_tags: str) -> typing.Optional[str]:
        """Transforms user-provided tags into rule34-style tags using AI."""
        if not self.genai_client:
            log.warning(
                "Rule34Cog: GenAI client not initialized, cannot transform tags."
            )
            return None
        if not user_tags:
            return ""  # Return empty if no tags provided to transform

        system_prompt_text = (
            "You are an AI assistant specialized in transforming user-provided text into tags suitable for rule34.xxx. "
            "Your task is to convert natural language input into a space-separated list of tags, where multi-word concepts are joined by underscores. "
            "For example, if the user provides 'hatsune miku blue hair', you should output 'hatsune_miku blue_hair'. "
            "Ambigious character names typically have the series their from appended, like 'astolfo_(fate)'. Typically only applies if the character lacks a last name, unless the full name is also ambiguous (for example, 'jane_doe'). Therefore 'hatsune_miku' for example would remain as is. "
            "In a case where the user provides a character name like 'ame chan' for example, it should actually be 'ame-chan'. "
            "If the user puts no/without in front of a tag, for example 'no inflation', change it to '-inflation' (hyphen denoting tag exclusion). "
            "If the input is already in rule34 format, return it unchanged. "
            "Some specific cases to handle: 'needy streamer overload' should be transformed to 'needy_girl_overdose'. If the user puts '-ai_generated' in their input, remove it, as its automatically added later. If the user puts 'teto', it should be 'kasane_teto'. "
            "Only output the transformed tags. Do NOT add any other text, explanations, or greetings. "
        )

        prompt_parts = [
            types.Part(text=system_prompt_text),
            types.Part(text=f'User input: "{user_tags}"'),
            types.Part(text="Transformed tags:"),
        ]
        contents_for_api = [types.Content(role="user", parts=prompt_parts)]

        generation_config = types.GenerateContentConfig(
            temperature=0.2,  # Low temperature for more deterministic output
            max_output_tokens=256,
            safety_settings=STANDARD_SAFETY_SETTINGS,
        )

        try:
            log.debug(
                f"Rule34Cog: Sending to Vertex AI for tag transformation. Model: {self.tag_transformer_model}, Input: '{user_tags}'"
            )
            client = get_genai_client_for_model(self.tag_transformer_model)
            response = await client.aio.models.generate_content(
                model=f"publishers/google/models/{self.tag_transformer_model}",
                contents=contents_for_api,
                config=generation_config,
            )
            transformed_tags = _get_response_text(response)
            if transformed_tags:
                log.info(
                    f"Rule34Cog: Tags transformed: '{user_tags}' -> '{transformed_tags.strip()}'"
                )
                return transformed_tags.strip()
            else:
                log.warning(
                    f"Rule34Cog: AI tag transformation returned empty for input: '{user_tags}'. Response: {response}"
                )
                return None
        except google_exceptions.GoogleAPICallError as e:
            log.error(
                f"Rule34Cog: Vertex AI API call failed for tag transformation: {e}"
            )
            return None
        except Exception as e:
            log.error(f"Rule34Cog: Unexpected error during AI tag transformation: {e}")
            return None

    # --- Prefix Command ---
    @commands.command(name="rule34")
    async def rule34_prefix(self, ctx: commands.Context, *, tags: str):
        """Search for images on Rule34 with the provided tags."""
        if not tags:  # Should not happen due to 'tags: str' but as a safeguard
            await ctx.reply("Please provide tags to search for.")
            return

        loading_msg = await ctx.reply(
            f"Transforming tags and fetching data from {self.cog_name}, please wait..."
        )

        transformed_tags = await self._transform_tags_ai(tags)
        if transformed_tags is None:  # AI transformation failed
            await loading_msg.edit(
                content=f"Sorry, I couldn't transform the tags using AI. Please try again or use rule34-formatted tags directly. Original tags: `{tags}`"
            )
            return
        if not transformed_tags:  # AI returned empty
            await loading_msg.edit(
                content=f"Sorry, the AI couldn't understand the tags provided: `{tags}`. Please try rephrasing."
            )
            return

        final_tags = f"{transformed_tags} -ai_generated"
        log.info(
            f"Rule34Cog (Prefix): Using final tags: '{final_tags}' from original: '{tags}'"
        )

        response = await self._fetch_posts_logic(
            "prefix_internal", final_tags, hidden=False
        )

        if isinstance(response, tuple):
            content, all_results = response
            view = self.GelbooruButtons(
                self, final_tags, all_results, hidden=False
            )  # Pass final_tags to buttons
            await loading_msg.edit(content=content, view=view)
        elif isinstance(response, str):  # Error
            await loading_msg.edit(content=response, view=None)

    # --- Slash Command ---
    @app_commands.command(
        name="rule34", description="Get random image from Rule34 with specified tags"
    )
    @app_commands.describe(
        tags="The tags to search for (e.g., 'hatsune miku rating:safe')",  # Updated example
        hidden="Set to True to make the response visible only to you (default: False)",
    )
    async def rule34_slash(
        self, interaction: discord.Interaction, tags: str, hidden: bool = False
    ):
        """Slash command version of rule34."""
        await interaction.response.defer(thinking=True, ephemeral=hidden)

        transformed_tags = await self._transform_tags_ai(tags)
        if transformed_tags is None:
            await interaction.followup.send(
                f"Sorry, I couldn't transform the tags using AI. Please try again or use rule34-formatted tags directly. Original tags: `{tags}`",
                ephemeral=True,
            )
            return
        if not transformed_tags:
            await interaction.followup.send(
                f"Sorry, the AI couldn't understand the tags provided: `{tags}`. Please try rephrasing.",
                ephemeral=True,
            )
            return

        final_tags = f"{transformed_tags} -ai_generated"
        log.info(
            f"Rule34Cog (Slash): Using final tags: '{final_tags}' from original: '{tags}'"
        )

        # _slash_command_logic calls _fetch_posts_logic, which checks if already deferred
        await self._slash_command_logic(interaction, final_tags, hidden)

    # --- New Browse Command ---
    @app_commands.command(
        name="rule34browse", description="Browse Rule34 results with navigation buttons"
    )
    @app_commands.describe(
        tags="The tags to search for (e.g., 'hatsune miku rating:safe')",  # Updated example
        hidden="Set to True to make the response visible only to you (default: False)",
    )
    async def rule34_browse_slash(
        self, interaction: discord.Interaction, tags: str, hidden: bool = False
    ):
        """Browse Rule34 results with navigation buttons."""
        await interaction.response.defer(thinking=True, ephemeral=hidden)

        transformed_tags = await self._transform_tags_ai(tags)
        if transformed_tags is None:
            await interaction.followup.send(
                f"Sorry, I couldn't transform the tags using AI. Please try again or use rule34-formatted tags directly. Original tags: `{tags}`",
                ephemeral=True,
            )
            return
        if not transformed_tags:
            await interaction.followup.send(
                f"Sorry, the AI couldn't understand the tags provided: `{tags}`. Please try rephrasing.",
                ephemeral=True,
            )
            return

        final_tags = f"{transformed_tags} -ai_generated"
        log.info(
            f"Rule34Cog (Browse): Using final tags: '{final_tags}' from original: '{tags}'"
        )

        # _browse_slash_command_logic calls _fetch_posts_logic, which checks if already deferred
        await self._browse_slash_command_logic(interaction, final_tags, hidden)

    # --- r34watch slash command group ---
    # All subcommands will call the corresponding _watch_..._logic methods from the base class.

    @r34watch.command(
        name="add",
        description="Watch for new Rule34 posts with specific tags in a channel or thread.",
    )
    @app_commands.describe(
        tags="The tags to search for (e.g., 'kasane_teto rating:safe').",
        channel="The parent channel for the subscription. Must be a Forum Channel if using forum mode.",
        thread_target="Optional: Name or ID of a thread within the channel (for TextChannels only).",
        post_title="Optional: Title for a new forum post if 'channel' is a Forum Channel.",
    )
    @app_commands.checks.has_permissions(manage_guild=True)
    async def r34watch_add(
        self,
        interaction: discord.Interaction,
        tags: str,
        channel: typing.Union[discord.TextChannel, discord.ForumChannel],
        thread_target: typing.Optional[str] = None,
        post_title: typing.Optional[str] = None,
    ):
        await interaction.response.defer(
            ephemeral=True
        )  # Defer here before calling base logic
        final_tags = f"{tags} -ai_generated"
        log.info(
            f"Rule34Cog (Watch Add): Using final tags for watch: '{final_tags}' from original: '{tags}'"
        )
        await self._watch_add_logic(
            interaction, final_tags, channel, thread_target, post_title
        )

    @r34watch.command(
        name="request",
        description="Request a new Rule34 tag watch (requires moderator approval).",
    )
    @app_commands.describe(
        tags="The tags you want to watch.",
        forum_channel="The Forum Channel where a new post for this watch should be created.",
        post_title="Optional: A title for the new forum post (defaults to tags).",
    )
    async def r34watch_request(
        self,
        interaction: discord.Interaction,
        tags: str,
        forum_channel: discord.ForumChannel,
        post_title: typing.Optional[str] = None,
    ):
        await interaction.response.defer(ephemeral=True)
        final_tags = f"{tags} -ai_generated"
        log.info(
            f"Rule34Cog (Watch Request): Using final tags for watch request: '{final_tags}' from original: '{tags}'"
        )
        await self._watch_request_logic(
            interaction, final_tags, forum_channel, post_title
        )

    @r34watch.command(
        name="pending_list", description="Lists all pending Rule34 watch requests."
    )
    @app_commands.checks.has_permissions(manage_guild=True)
    async def r34watch_pending_list(self, interaction: discord.Interaction):
        # No defer needed if _watch_pending_list_logic handles it or is quick
        await self._watch_pending_list_logic(interaction)

    @r34watch.command(
        name="approve_request", description="Approves a pending Rule34 watch request."
    )
    @app_commands.describe(request_id="The ID of the request to approve.")
    @app_commands.checks.has_permissions(manage_guild=True)
    async def r34watch_approve_request(
        self, interaction: discord.Interaction, request_id: str
    ):
        await interaction.response.defer(ephemeral=True)
        await self._watch_approve_request_logic(interaction, request_id)

    @r34watch.command(
        name="reject_request", description="Rejects a pending Rule34 watch request."
    )
    @app_commands.describe(
        request_id="The ID of the request to reject.",
        reason="Optional reason for rejection.",
    )
    @app_commands.checks.has_permissions(manage_guild=True)
    async def r34watch_reject_request(
        self,
        interaction: discord.Interaction,
        request_id: str,
        reason: typing.Optional[str] = None,
    ):
        await interaction.response.defer(ephemeral=True)
        await self._watch_reject_request_logic(interaction, request_id, reason)

    @r34watch.command(
        name="list", description="List active Rule34 tag watches for this server."
    )
    @app_commands.checks.has_permissions(manage_guild=True)
    async def r34watch_list(self, interaction: discord.Interaction):
        # No defer needed if _watch_list_logic handles it or is quick
        await self._watch_list_logic(interaction)

    @r34watch.command(
        name="remove",
        description="Stop watching for new Rule34 posts using a subscription ID.",
    )
    @app_commands.describe(
        subscription_id="The ID of the subscription to remove (get from 'list' command)."
    )
    @app_commands.checks.has_permissions(manage_guild=True)
    async def r34watch_remove(
        self, interaction: discord.Interaction, subscription_id: str
    ):
        # No defer needed if _watch_remove_logic handles it or is quick
        await self._watch_remove_logic(interaction, subscription_id)

    @r34watch.command(
        name="send_test",
        description="Send a test new Rule34 post message using a subscription ID.",
    )
    @app_commands.describe(subscription_id="The ID of the subscription to test.")
    @app_commands.checks.has_permissions(manage_guild=True)
    async def r34watch_send_test(
        self, interaction: discord.Interaction, subscription_id: str
    ):
        await self._watch_test_message_logic(interaction, subscription_id)

    @app_commands.command(
        name="rule34debug_transform",
        description="Debug command to test AI tag transformation.",
    )
    @app_commands.describe(
        tags="The tags to test transformation for (e.g., 'hatsune miku')"
    )
    async def rule34debug_transform(self, interaction: discord.Interaction, tags: str):
        await interaction.response.defer(ephemeral=True, thinking=True)

        transformed_tags = await self._transform_tags_ai(tags)

        if transformed_tags is None:
            response_content = (
                f"AI transformation failed for tags: `{tags}`. Check logs for details."
            )
        elif not transformed_tags:
            response_content = (
                f"AI returned empty for tags: `{tags}`. Please try rephrasing."
            )
        else:
            response_content = (
                f"Original tags: `{tags}`\n" f"Transformed tags: `{transformed_tags}`"
            )

        await interaction.followup.send(response_content, ephemeral=True)


async def setup(bot: commands.Bot):
    await bot.add_cog(Rule34Cog(bot))
    log.info("Rule34Cog (refactored) added to bot.")