run_bots.py

"""
This is the main file used to run the bots in the Metaulus AI Competition.

It is run by workflows in the .github/workflows directory.
"""

import argparse
import asyncio
import logging
import os
from datetime import datetime
from enum import Enum
from typing import Literal

import dotenv
import pendulum
from pydantic import BaseModel

from forecasting_tools.ai_models.general_llm import GeneralLlm
from forecasting_tools.data_models.forecast_report import ForecastReport
from forecasting_tools.data_models.questions import MetaculusQuestion
from forecasting_tools.forecast_bots.forecast_bot import ForecastBot
from forecasting_tools.forecast_bots.official_bots.gpt_4_1_optimized_bot import (
    GPT41OptimizedBot,
)
from forecasting_tools.forecast_bots.official_bots.no_research_one_shot_bot import (
    NoResearchOneShotBot,
)
from forecasting_tools.forecast_bots.official_bots.research_only_bot_2025_fall import (
    FallResearchOnlyBot2025,
)
from forecasting_tools.forecast_bots.official_bots.uniform_probability_bot import (
    UniformProbabilityBot,
)
from forecasting_tools.forecast_bots.template_bot import TemplateBot
from forecasting_tools.helpers.metaculus_api import ApiFilter
from forecasting_tools.helpers.metaculus_client import MetaculusClient
from forecasting_tools.helpers.structure_output import DEFAULT_STRUCTURE_OUTPUT_MODEL

logger = logging.getLogger(__name__)
dotenv.load_dotenv()


default_for_skipping_questions = False
default_for_publish_to_metaculus = True
default_for_using_summary = False
default_num_forecasts_for_research_only_bot = 3
structure_output_model = DEFAULT_STRUCTURE_OUTPUT_MODEL
default_metaculus_client = MetaculusClient()
POST_IDS_TO_SKIP = [
    31653,  # https://www.metaculus.com/questions/31653/ is rejected by qwen3-max and is causing noisy workflow errors
    39009,  # https://www.metaculus.com/questions/39009/ is rejected since too many MC options
    41362,  # https://www.metaculus.com/questions/41362/ is rejected because common cause of errors (confusion on units?)
    42495,  # https://www.metaculus.com/questions/42495/ is rejected since too many MC options
    42557,  # https://www.metaculus.com/questions/42557/ is rejected since too many group question options that lower quality models fail at
    43310,  # https://www.metaculus.com/questions/43310/ is rejected since too many MC options
    40280,  # https://www.metaculus.com/questions/40280/ is rejected since noisy workflow errors
    39138,  # https://www.metaculus.com/questions/39138/ is rejected the best value is way out of bounds, and bots are constrained to not be able to make these forecasts
    42541,  # https://www.metaculus.com/questions/42541/ is rejected since too many MC options
    38420,  # https://www.metaculus.com/questions/38420/ is rejected since bots treat the 0.1-0.7 range as percent points (~43-56) and fail numeric validation
    27552,  # https://www.metaculus.com/questions/27552/ is rejected the best value is way out of bounds (date question closes 2026-12-31)
    7055,  # https://www.metaculus.com/questions/7055/ is rejected since bots treat the 0-1 range as percent points and fail numeric validation
    42727,  # https://www.metaculus.com/questions/42727/ is rejected since too many MC options
]
POST_IDS_TO_NOT_RAISE_ERRORS_FOR = [
    # 43335,  # https://www.metaculus.com/questions/43335/ is still forecasted but should not fail the workflow if it errors
]


class ScheduleConfig:
    regular_forecast_interval_days: int = (
        3  # Cup and other every-x-days tournaments. Was 2 until Sep 2026
    )
    main_site_check_interval_days: int = 2
    min_main_site_forecast_interval_days: int = 4

    _window_length_hrs = 2.5
    _US_morning_hour = 4  # 4am MT
    _US_afternoon_hour = 12  # 12pm MT
    UTC_morning_hour = _US_morning_hour + 7
    UTC_afternoon_hour = _US_afternoon_hour + 7

    default_max_main_site_questions_per_run = 30
    default_question_batch_size = 30
    main_site_months_ahead_to_check = 4

    @classmethod
    def is_interval_day(cls, interval_days: int, time: datetime | None = None) -> bool:
        time = time or pendulum.now(tz="UTC")
        value = time.day % interval_days == 0
        return value

    @classmethod
    def is_morning_window(cls, time: datetime | None = None) -> bool:
        time = time or pendulum.now(tz="UTC")
        hour = time.hour
        max_hour = cls.UTC_morning_hour + cls._window_length_hrs
        value = cls.UTC_morning_hour <= hour < max_hour
        return value

    @classmethod
    def is_afternoon_window(cls, time: datetime | None = None) -> bool:
        time = time or pendulum.now(tz="UTC")
        value = (
            cls.UTC_afternoon_hour
            <= time.hour
            < cls.UTC_afternoon_hour + cls._window_length_hrs
        )
        return value


class AllowedTourn(Enum):
    MINIBENCH = MetaculusClient.CURRENT_MINIBENCH_ID
    MAIN_AIB = MetaculusClient.CURRENT_AI_COMPETITION_ID
    MAIN_SITE = "main-site"
    METACULUS_CUP = MetaculusClient.CURRENT_METACULUS_CUP_ID
    # When representing a tournament, these should be valid slugs


class TournConfig:
    everything = [t for t in AllowedTourn]
    aib_only = [AllowedTourn.MAIN_AIB, AllowedTourn.MINIBENCH]
    main_site_tourns = [AllowedTourn.MAIN_SITE]
    aib_and_site = aib_only.copy() + main_site_tourns.copy()
    every_x_days_tourns = [AllowedTourn.METACULUS_CUP]
    experimental = []
    NONE = []

    forecasts_per_main_site_question: int = 5


class RunBotConfig(BaseModel):
    mode: str
    bot: ForecastBot | None
    estimated_cost_per_question: float | None
    tournaments: list[AllowedTourn]

    model_config = {"arbitrary_types_allowed": True}


async def configure_and_run_bot(
    mode: str,
    max_questions_for_run: int = ScheduleConfig.default_max_main_site_questions_per_run,
    batch_size: int = ScheduleConfig.default_question_batch_size,
) -> list[ForecastReport | BaseException]:
    base_url = os.getenv("METACULUS_API_BASE_URL")
    if base_url is None:
        raise ValueError(
            "METACULUS_API_BASE_URL environment variable is not set. "
            "Please set it in the environment variables."
            "This makes sure no workflows have forgotten to set it as an input variable."
        )
    if base_url == "":
        logger.warning(
            "METACULUS_API_BASE_URL environment variable is set to an empty string"
        )
    printable_base_url = " ".join(list(base_url))
    logger.info(f"Using Metaculus API base URL: {printable_base_url}")

    bot_config = get_default_bot_dict()[mode]
    questions = await get_questions_for_config(
        bot_config, max_questions=max_questions_for_run
    )
    logger.info(f"Running bot {mode} with {len(questions)} questions")
    bot = bot_config.bot

    assert isinstance(
        bot, ForecastBot
    ), f"Bot {mode} is not a ForecastBot, it is a {type(bot)}"
    logger.info(f"LLMs for bot are: {bot.make_llm_dict()}")
    all_reports = []
    batches = [
        questions[i : i + batch_size] for i in range(0, len(questions), batch_size)
    ]
    for batch in batches:
        reports = await bot.forecast_questions(batch, return_exceptions=True)
        all_reports.extend(reports)

    for i, question_report in enumerate(zip(questions, all_reports)):
        question, report = question_report
        if isinstance(report, BaseException) and "TimeoutError" in str(report):
            logger.warning(
                f"TimeoutError occurred for question {question.id_of_post}, retrying..."
            )
            new_report = await bot.forecast_question(question, return_exceptions=True)
            all_reports[i] = new_report

    bot.log_report_summary(all_reports, raise_errors=False)

    errors_to_raise = [
        report
        for question, report in zip(questions, all_reports)
        if isinstance(report, BaseException)
        and question.id_of_post not in POST_IDS_TO_NOT_RAISE_ERRORS_FOR
    ]
    if errors_to_raise:
        raise RuntimeError(
            f"{len(errors_to_raise)} errors occurred while forecasting: {errors_to_raise}"
        )

    return all_reports


async def get_questions_for_config(
    bot_config: RunBotConfig, max_questions: int
) -> list[MetaculusQuestion]:
    if max_questions < 1:
        raise ValueError(f"max questions ({max_questions}) must be at least 1")
    mode = bot_config.mode
    allowed_tournaments = list(set(bot_config.tournaments))
    return await get_questions_for_allowed_tournaments(
        allowed_tournaments, max_questions, mode
    )


async def get_questions_for_allowed_tournaments(
    allowed_tournaments: list[AllowedTourn],
    max_questions: int,
    mode: str | None,
) -> list[MetaculusQuestion]:
    if mode is None:
        mode = ""

    aib_tourns = [t for t in allowed_tournaments if t in TournConfig.aib_only]
    regularly_forecast_tourns = [
        t for t in allowed_tournaments if t in TournConfig.every_x_days_tourns
    ]
    main_site_tourns = [
        t for t in allowed_tournaments if t in TournConfig.main_site_tourns
    ]

    mode_parts = mode.split(
        "+"
    )  # Allow for adding specific tournaments via the mode name
    if len(mode_parts) > 1:
        suffix = mode_parts[1]
        assert suffix in [t.value for t in allowed_tournaments]

    main_site_override = (
        os.getenv("FORECAST_ON_MAIN_SITE_ALWAYS", "false").lower() == "true"
    )
    every_x_days_override = (
        os.getenv(
            "FORECAST_ON_REGULARLY_FORECASTED_TOURNAMENTS_ALWAYS", "false"
        ).lower()
        == "true"
    )  # env variables are for testing the workflow w/o waiting for the next interval day
    reforecast_aib_questions = False  # Manually change this if testing

    should_forecast_on_main_site = (
        ScheduleConfig.is_interval_day(ScheduleConfig.main_site_check_interval_days)
        and ScheduleConfig.is_afternoon_window()
    ) or main_site_override
    should_forecast_on__every_x_days__questions = (
        ScheduleConfig.is_interval_day(ScheduleConfig.regular_forecast_interval_days)
        and ScheduleConfig.is_morning_window()
    ) or every_x_days_override

    questions: list[MetaculusQuestion] = []
    for tournament in aib_tourns:
        questions.extend(_get_aib_questions(tournament, reforecast_aib_questions))

    if should_forecast_on__every_x_days__questions:
        questions.extend(_get__every_x_days__questions(regularly_forecast_tourns))

    if should_forecast_on_main_site:
        main_site_questions = await _get_questions_for_main_site(main_site_tourns)
        questions.extend(main_site_questions)

    not_skipped_questions = [
        q for q in questions if q.id_of_post not in POST_IDS_TO_SKIP
    ]
    questions_to_forecast = not_skipped_questions[:max_questions]
    logger.info(
        f"Questions to forecast: {len(questions_to_forecast)}. Possible questions that need forecasting: {len(not_skipped_questions)}"
    )
    return questions_to_forecast


def _get_aib_questions(
    tournament: AllowedTourn, reforecast_aib_questions: bool
) -> list[MetaculusQuestion]:
    aib_questions = default_metaculus_client.get_all_open_questions_from_tournament(
        tournament.value
    )
    filtered_questions = []
    already_forecasted_skip_count = 0
    for question in aib_questions:
        if reforecast_aib_questions or not question.already_forecasted:
            filtered_questions.append(question)
        else:
            already_forecasted_skip_count += 1
    logger.info(
        f"Skipping {already_forecasted_skip_count} already forecasted AIB questions from {tournament.name}"
    )
    return filtered_questions


def _get__every_x_days__questions(
    tournaments: list[AllowedTourn],
) -> list[MetaculusQuestion]:
    tournament_questions: list[MetaculusQuestion] = []
    for tournament in tournaments:
        tournament_questions += (
            default_metaculus_client.get_all_open_questions_from_tournament(
                tournament.value
            )
        )

    filtered_questions = []
    for question in tournament_questions:
        last_forecast_time = question.timestamp_of_my_last_forecast
        should_forecast = (
            last_forecast_time is None
            or last_forecast_time
            < pendulum.now(tz="UTC").subtract(
                days=ScheduleConfig.regular_forecast_interval_days
            )
        )
        if should_forecast:
            filtered_questions.append(question)
    return filtered_questions


async def _get_questions_for_main_site(
    main_site_tourns: list[AllowedTourn],
    months_ahead_to_check: int = ScheduleConfig.main_site_months_ahead_to_check,
) -> list[MetaculusQuestion]:
    site_questions: list[MetaculusQuestion] = []
    if AllowedTourn.MAIN_SITE in main_site_tourns:
        target_months_from_now = pendulum.now(tz="UTC").add(
            days=31 * months_ahead_to_check
        )
        site_questions += await default_metaculus_client.get_questions_matching_filter(
            ApiFilter(
                is_in_main_feed=True,
                allowed_statuses=["open"],
                group_question_mode="unpack_subquestions",
                scheduled_resolve_time_lt=target_months_from_now,
            ),
            num_questions=10_000,  # big enough to attempt to get everything available
            error_if_question_target_missed=False,
        )

    other_tourns = [t for t in main_site_tourns if t != AllowedTourn.MAIN_SITE]
    for tournament in other_tourns:
        site_questions += (
            default_metaculus_client.get_all_open_questions_from_tournament(
                tournament.value,
                group_question_mode="unpack_subquestions",
            )
        )

    filtered_questions = []
    for question in site_questions:
        last_forecast_time = question.timestamp_of_my_last_forecast
        assert question.close_time is not None
        assert question.open_time is not None
        open_lifetime = (
            question.close_time - question.open_time
        )  # Choose close time over scheduled resolution time so we can actually it the 5 forecasts in the open window
        forecast_every_x_days = round(
            max(
                (open_lifetime / TournConfig.forecasts_per_main_site_question).days,
                ScheduleConfig.min_main_site_forecast_interval_days,
            )
        )
        should_forecast = (
            last_forecast_time is None
            or last_forecast_time
            < pendulum.now(tz="UTC").subtract(days=forecast_every_x_days)
        )
        if should_forecast:
            filtered_questions.append(question)
    return filtered_questions


def create_bot(
    llm: GeneralLlm,
    researcher: str | GeneralLlm = "asknews/news-summaries",
    predictions_per_research_report: int | None = None,
    bot_type: Literal[
        "template", "gpt_4_1_optimized", "research_only", "no_research_one_shot"
    ] = "template",
) -> ForecastBot:
    default_summarizer = "openrouter/openai/gpt-4.1-mini"

    if bot_type == "no_research_one_shot":
        return NoResearchOneShotBot(
            research_reports_per_question=1,
            predictions_per_research_report=predictions_per_research_report or 1,
            use_research_summary_to_forecast=default_for_using_summary,
            publish_reports_to_metaculus=default_for_publish_to_metaculus,
            skip_previously_forecasted_questions=default_for_skipping_questions,
            llms={
                "default": llm,
                "summarizer": None,
                "researcher": "no_research",
                "parser": structure_output_model,
            },
            enable_summarize_research=False,
            extra_metadata_in_explanation=True,
        )

    if bot_type == "research_only":
        return FallResearchOnlyBot2025(
            research_reports_per_question=1,
            predictions_per_research_report=predictions_per_research_report
            or default_num_forecasts_for_research_only_bot,
            use_research_summary_to_forecast=default_for_using_summary,
            publish_reports_to_metaculus=default_for_publish_to_metaculus,
            skip_previously_forecasted_questions=default_for_skipping_questions,
            llms={
                "default": llm,
                "summarizer": None,
                "researcher": "no_research",
                "parser": structure_output_model,
            },
            enable_summarize_research=False,
            extra_metadata_in_explanation=True,
        )

    if bot_type == "template":
        bot_class = TemplateBot
    elif bot_type == "gpt_4_1_optimized":
        bot_class = GPT41OptimizedBot
    else:
        raise ValueError(f"Invalid bot type: {bot_type}")

    default_bot = bot_class(
        research_reports_per_question=1,
        predictions_per_research_report=predictions_per_research_report or 5,
        use_research_summary_to_forecast=default_for_using_summary,
        publish_reports_to_metaculus=default_for_publish_to_metaculus,
        skip_previously_forecasted_questions=default_for_skipping_questions,
        llms={
            "default": llm,
            "summarizer": default_summarizer,
            "researcher": researcher,
            "parser": structure_output_model,
        },
        extra_metadata_in_explanation=True,
    )
    return default_bot


def make_claude_thinking_settings(thinking_tokens: int, max_tokens: int) -> dict:
    return {
        "temperature": 1,
        "thinking": {
            "type": "enabled",
            "budget_tokens": thinking_tokens,
        },
        "max_tokens": max_tokens,
        "timeout": 160,
    }


def make_claude_adaptive_thinking_settings(
    effort: Literal["low", "medium", "high"], max_tokens: int
) -> dict:
    return {
        "temperature": 1,
        "thinking": {"type": "adaptive"},
        "output_config": {"effort": effort},
        "allowed_openai_params": ["output_config"],
        "max_tokens": max_tokens,
        "timeout": 160,
    }


def make_openrouter_provider_pin(*endpoint_slugs: str) -> dict:
    """
    OpenRouter serves open-weight models from many hosts at different quantizations, so an unpinned
    bot's quality shifts between runs. Pin to the lab's own endpoint, else the highest declared precision
    host (see https://openrouter.ai/api/v1/models/{model}/endpoints). Extra slugs are tried in order as
    backups, so only list hosts with the same precision.
    """
    return {
        "extra_body": {
            "provider": {
                "order": list(endpoint_slugs),
                "allow_fallbacks": False,
                "require_parameters": True,
            }
        }
    }


def get_default_bot_dict() -> dict[str, RunBotConfig]:  # NOSONAR
    """
    Each entry in the dict has a key which is the environment variable set in the project secrets, and also used in the Workflows that run the bots.

    Note that many of the workflow entries are commented out in order to disable them.
    An entry being marked "none" for tournaments will also be disabled.

    Anything that uses the "roughly" cost value (other than the original model the variable matches to)
    is estimated value and was not measured directly. These estimates were derived from Litellm's pricing functionality.
    Also, a lot of pricing is probably outdated. Unless otherwise stated, costs are "cost per question".

    Useful Links:
    OpenRouter reasoning control settings: https://openrouter.ai/docs/use-cases/reasoning-tokens#controlling-reasoning-tokens

    Comment last updated: 10/11/2025
    """
    default_temperature = 0.3

    roughly_gpt_4o_cost = 0.05
    roughly_gpt_4o_mini_cost = 0.005
    roughly_sonnet_3_5_cost = 0.10
    roughly_gemini_2_5_pro_preview_cost = 0.30  # TODO: Double check this
    roughly_deepseek_r1_cost = 0.039
    guess_at_search_cost = 0.015
    guess_at__research_only_bot__search_costs = (
        guess_at_search_cost * default_num_forecasts_for_research_only_bot
    )
    guess_at_deepseek_plus_search = roughly_deepseek_r1_cost + guess_at_search_cost
    guess_at_deepseek_v3_1_cost = roughly_deepseek_r1_cost / 2
    roughly_one_call_to_grok_4_llm = 0.084
    roughly_one_call_to_grok_4_5_llm = 0.15
    roughly_sonar_deep_research_cost_per_call = 1.35399 / 3
    roughly_opus_4_5_cost = 1.5

    sonnet_4_name = "anthropic/claude-sonnet-4-20250514"
    sonnet_4_5_name = "anthropic/claude-sonnet-4-5-20250929"
    gemini_2_5_pro = "openrouter/google/gemini-2.5-pro"  # Used to be gemini-2.5-pro-preview (though automatically switched to regular pro when preview was deprecated)
    gemini_default_timeout = 5 * 60
    deepnews_model = "asknews/deep-research/high-depth/claude-fable-5-1"  # Switched to claude-fable-5-1 Sep 8th 2026 once AskNews supported it. Switched to claude-fable-5 and added podcasts source Sep 5th 2026. Switched to opus 4.6 Feb 23rd. Switched to high depth Feb 16th 2026. Switched from claude-sonnet-4-20250514 to sonnet 4.5 in Nov 2025. Switched from high to medium depth on Jan 2nd, 2026

    roughly_sonnet_4_cost = 0.25190
    roughly_gpt_5_high_cost = 0.37868
    roughly_gpt_5_cost = 0.19971

    default_perplexity_settings: dict = {
        "web_search_options": {"search_context_size": "high"},
        "reasoning_effort": "high",
    }
    flex_price_settings: dict = {"service_tier": "flex"}
    claude_thinking_settings_16k: dict = make_claude_thinking_settings(
        thinking_tokens=16000, max_tokens=32000
    )
    claude_thinking_settings_32k: dict = make_claude_thinking_settings(
        thinking_tokens=32000, max_tokens=64000
    )
    claude_adaptive_thinking_settings_high: dict = (
        make_claude_adaptive_thinking_settings(effort="high", max_tokens=64000)
    )
    gpt_5_timeout = 15 * 60

    gemini_grounding_llm = GeneralLlm(
        model=gemini_2_5_pro,
        # generationConfig={
        #     "thinkingConfig": {
        #         "thinkingBudget": 0,
        #     },
        #     "responseMimeType": "text/plain",
        # }, # In Q2 had thinking turned off
        tools=[
            {"googleSearch": {}},
        ],
    )  # https://ai.google.dev/gemini-api/docs/google-search#rest
    default_research_comparison_forecast_llm = GeneralLlm(
        model="openrouter/deepseek/deepseek-r1",
        temperature=default_temperature,
        timeout=60 * 6,
        # pinned to provider Sept 25th 2026
        **make_openrouter_provider_pin("novita/fp8"),
    )
    grok_4_search_llm = GeneralLlm(
        model="xai/grok-4-latest",
        search_parameters={"mode": "auto"},
    )  # https://docs.x.ai/docs/guides/live-search
    sonnet_4_search_llm = GeneralLlm(
        model=sonnet_4_name,
        tools=[
            {
                "type": "web_search_20250305",
                "name": "web_search",
                "max_uses": 10,
            }
        ],
        **claude_thinking_settings_16k,
    )  # https://docs.anthropic.com/en/docs/agents-and-tools/tool-use/web-search-tool
    deepseek_r1_exa_online_llm = GeneralLlm(
        model="openrouter/deepseek/deepseek-r1:online",
        timeout=60 * 6,
        # pinned to provider Sept 25th 2026
        **make_openrouter_provider_pin("novita/fp8"),
    )
    o4_mini_deep_research_llm = GeneralLlm(
        model="openai/o4-mini-deep-research",
        responses_api=True,
        temperature=None,
        tools=[
            {"type": "web_search"},
            # {"type": "code_interpreter", "container": {"type": "auto", "file_ids": []}}, # TODO: Consider adding code interpreter
        ],
    )
    sonar_deep_research_llm = GeneralLlm(
        model="perplexity/sonar-deep-research",
        **default_perplexity_settings,
    )
    gpt_5_with_search = GeneralLlm(
        model="openai/gpt-5",
        responses_api=True,
        temperature=None,
        tools=[
            {"type": "web_search"},
            # {"type": "code_interpreter", "container": {"type": "auto", "file_ids": []}}, # TODO: Consider adding code interpreter
        ],
        **flex_price_settings,
    )

    kimi_k2_timeout = 5 * 60
    kimi_k2_basic_bot = {
        "estimated_cost_per_question": roughly_deepseek_r1_cost,
        "bot": create_bot(
            GeneralLlm(
                model="openrouter/moonshotai/kimi-k2",
                temperature=default_temperature,
                timeout=kimi_k2_timeout,
            ),
        ),
    }
    deepseek_r1_bot = {
        "estimated_cost_per_question": roughly_deepseek_r1_cost,
        "bot": create_bot(
            GeneralLlm(
                model="openrouter/deepseek/deepseek-r1",
                temperature=default_temperature,
                timeout=60 * 6,
                # pinned to provider Sept 25th 2026
                **make_openrouter_provider_pin("novita/fp8"),
            ),
        ),
    }
    deepseek_v3_1_bot = {
        "estimated_cost_per_question": guess_at_deepseek_v3_1_cost,
        "bot": create_bot(
            GeneralLlm(
                model="openrouter/deepseek/deepseek-chat-v3.1",
                temperature=default_temperature,
                # pinned to provider Sept 25th 2026
                **make_openrouter_provider_pin("coreweave/fp8"),
            ),
        ),
    }

    mode_base_bot_mapping = {
        ############################ Bots started in October 2026 ############################
        "METAC_NEMOTRON_3_5_SUPER_VL_HIGH": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost * 0.3,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/nvidia/nemotron-3.5-super-vl",
                    reasoning_effort="high",
                    temperature=default_temperature,
                    **make_openrouter_provider_pin("crusoe/bf16"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GEMINI_4_ARGON_HIGH": {
            "estimated_cost_per_question": roughly_gpt_5_high_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/google/gemini-4-argon",
                    reasoning_effort="high",
                    temperature=None,
                    timeout=gemini_default_timeout,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_MUSE_WONDER_HIGH": {
            "estimated_cost_per_question": roughly_gpt_5_high_cost * 2,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/meta/muse-wonder",
                    reasoning_effort="high",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_CLAUDE_HAIKU_5_5_HIGH": {
            "estimated_cost_per_question": roughly_opus_4_5_cost * 0.04,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="anthropic/claude-haiku-5-5",
                    **claude_adaptive_thinking_settings_high,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_MISTRAL_LARGE_4_HIGH": {
            "estimated_cost_per_question": roughly_gpt_5_high_cost * 0.21,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/mistralai/mistral-large-4-0",
                    reasoning_effort="high",
                    temperature=default_temperature,
                    **make_openrouter_provider_pin("mistral/zdr"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GPT_6_1_SOL_HIGH": {
            "estimated_cost_per_question": roughly_gpt_5_high_cost * 3,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-6.1-sol",
                    reasoning_effort="high",
                    temperature=None,
                    timeout=gpt_5_timeout,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_CLAUDE_SONNET_5_5_HIGH": {
            "estimated_cost_per_question": roughly_opus_4_5_cost * 0.8,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="anthropic/claude-sonnet-5-5",
                    **claude_adaptive_thinking_settings_high,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        ############################ Bots started in September 2026 ############################
        "METAC_GROK_4_7_HIGH": {
            "estimated_cost_per_question": 5 * roughly_one_call_to_grok_4_5_llm * 0.8,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/x-ai/grok-4.7",
                    reasoning_effort="high",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_CLAUDE_OPUS_5_5_HIGH": {
            "estimated_cost_per_question": roughly_opus_4_5_cost * 1.6,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="anthropic/claude-opus-5-5",
                    **claude_adaptive_thinking_settings_high,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GPT_6_ASTRA_HIGH": {
            "estimated_cost_per_question": roughly_gpt_5_high_cost * 5,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-6-astra",
                    reasoning_effort="high",
                    temperature=None,
                    timeout=gpt_5_timeout,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GPT_6_SOL_HIGH": {
            "estimated_cost_per_question": roughly_gpt_5_high_cost * 3,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-6-sol",
                    reasoning_effort="high",
                    temperature=None,
                    timeout=gpt_5_timeout,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GPT_6_LUNA_HIGH": {
            "estimated_cost_per_question": roughly_gpt_5_high_cost * 0.35,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-6-luna",
                    reasoning_effort="high",
                    temperature=None,
                    timeout=gpt_5_timeout,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GEMINI_3_8_FLASH": {
            "estimated_cost_per_question": roughly_opus_4_5_cost * 0.21,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/google/gemini-3.8-flash",
                    temperature=None,
                    timeout=gemini_default_timeout,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_MUSE_SPARK_1_3": {
            "estimated_cost_per_question": roughly_gpt_5_cost * 0.425,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/meta/muse-spark-1.3",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_CLAUDE_FABLE_5_1": {
            "estimated_cost_per_question": roughly_opus_4_5_cost * 2,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="anthropic/claude-fable-5-1",
                    temperature=None,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        ############################ Bots started in August 2026 ############################
        "METAC_QWEN_3_8_FLASH": {
            "estimated_cost_per_question": roughly_gpt_5_cost * 0.047,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/qwen/qwen3.8-flash",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GLM_5_3_FLASH": {
            "estimated_cost_per_question": roughly_gpt_5_cost * 0.05,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/z-ai/glm-5.3-flash",
                    temperature=default_temperature,
                    # pinned to provider Sept 25th 2026
                    **make_openrouter_provider_pin("z-ai/fp8"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GLM_5_3": {
            "estimated_cost_per_question": roughly_gpt_5_cost * 0.44,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/z-ai/glm-5.3",
                    temperature=default_temperature,
                    # pinned to provider Sept 25th 2026
                    **make_openrouter_provider_pin("z-ai/fp8"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GEMINI_3_7_FLASH": {
            "estimated_cost_per_question": roughly_opus_4_5_cost * 0.21,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/google/gemini-3.7-flash",
                    temperature=None,
                    timeout=gemini_default_timeout,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 23rd 2026: outpaced by Gemini 3.8 Flash
        },
        "METAC_GROK_4_6": {
            "estimated_cost_per_question": 5 * roughly_one_call_to_grok_4_5_llm,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/x-ai/grok-4.6",
                    temperature=default_temperature,
                    # pinned to provider Sept 25th 2026
                    # xai/zdr: standard-price xAI endpoint; plain "xai" also matches xAI's 2x-price priority endpoints
                    **make_openrouter_provider_pin("xai/zdr"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_NEMOTRON_3_5_LIGHTNING": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost * 0.1,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/nvidia/nemotron-3.5-lightning",
                    temperature=default_temperature,
                    # pinned to provider Sept 25th 2026
                    # CoreWeave over DeepInfra since DeepInfra's shared pool kept rate limiting on Sep 24th 2026
                    **make_openrouter_provider_pin("coreweave/bf16"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_MUSE_GLIMMER_30B": {
            "estimated_cost_per_question": roughly_gpt_5_cost * 0.15,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/meta/muse-glimmer-30b",
                    temperature=default_temperature,
                    # pinned to provider Sept 25th 2026
                    **make_openrouter_provider_pin("deepinfra/bf16"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_MUSE_SPARK_1_2": {
            "estimated_cost_per_question": roughly_gpt_5_cost * 0.425,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/meta/muse-spark-1.2",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 23rd 2026: outpaced by Muse Spark 1.3
        },
        "METAC_QWEN_3_8_MAX": {
            "estimated_cost_per_question": roughly_gpt_5_cost * 0.6,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/qwen/qwen3.8-max",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_INKLING_SMALL": {
            "estimated_cost_per_question": roughly_gpt_5_cost * 0.12,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/thinkingmachines/inkling-small",
                    temperature=default_temperature,
                    # pinned to provider Sept 25th 2026
                    **make_openrouter_provider_pin("deepinfra/fp8"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_DEEPSEEK_V4_FLASH": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost * 0.072,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/deepseek/deepseek-v4-flash-0731",
                    temperature=default_temperature,
                    timeout=5 * 60,
                    # pinned to provider Sept 25th 2026
                    # CoreWeave over DeepInfra since DeepInfra's shared pool kept rate limiting on Sep 24th 2026
                    **make_openrouter_provider_pin("coreweave/fp8"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        ############################ Bots started in July 2026 ############################
        "METAC_CLAUDE_OPUS_5": {
            "estimated_cost_per_question": roughly_opus_4_5_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="anthropic/claude-opus-5",
                    temperature=None,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 23rd 2026: outpaced by Opus 5.5
        },
        "METAC_GEMINI_3_6_FLASH": {
            "estimated_cost_per_question": roughly_opus_4_5_cost * 0.42,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/google/gemini-3.6-flash",
                    temperature=None,
                    timeout=gemini_default_timeout,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 5th 2026: outpaced by Gemini 3.7 Flash
        },
        "METAC_GEMINI_3_5_FLASH_LITE": {
            "estimated_cost_per_question": roughly_opus_4_5_cost * 0.14,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/google/gemini-3.5-flash-lite",
                    temperature=None,
                    timeout=gemini_default_timeout,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Oct 12th 2026
        },
        "METAC_INKLING": {
            "estimated_cost_per_question": roughly_gpt_5_cost * 0.405,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/thinkingmachines/inkling",
                    temperature=default_temperature,
                    # pinned to provider Sept 25th 2026
                    **make_openrouter_provider_pin("deepinfra/fp8"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_MUSE_SPARK_1_1": {
            "estimated_cost_per_question": roughly_gpt_5_cost * 0.425,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/meta/muse-spark-1.1",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 5th 2026: outpaced by Muse Spark 1.2
        },
        "METAC_KIMI_K3": {
            "estimated_cost_per_question": roughly_gpt_5_cost * 1.5,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/moonshotai/kimi-k3",
                    temperature=None,  # Moonshot's endpoint doesn't support temperature
                    timeout=kimi_k2_timeout,
                    # pinned to provider Sept 25th 2026
                    **make_openrouter_provider_pin("moonshotai/mxfp4"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GPT_5_6_LUNA": {
            "estimated_cost_per_question": roughly_gpt_5_cost * 0.6,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-5.6-luna",
                    temperature=None,
                    timeout=gpt_5_timeout,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 24th 2026: outpaced by GPT-6 Luna
        },
        "METAC_GPT_5_6_TERRA": {
            "estimated_cost_per_question": roughly_gpt_5_cost * 1.5,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-5.6-terra",
                    temperature=None,
                    timeout=gpt_5_timeout,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 24th 2026: outpaced by GPT-6 Sol
        },
        "METAC_GPT_5_6_SOL_HIGH": {
            "estimated_cost_per_question": roughly_gpt_5_high_cost * 3,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-5.6-sol",
                    reasoning_effort="high",
                    temperature=None,
                    timeout=gpt_5_timeout,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 23rd 2026: outpaced by GPT-6 Astra
        },
        "METAC_GROK_4_5_HIGH": {
            "estimated_cost_per_question": 5 * roughly_one_call_to_grok_4_5_llm,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/x-ai/grok-4.5",
                    reasoning_effort="high",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 5th 2026: outpaced by Grok 4.6
        },
        "METAC_CLAUDE_SONNET_5": {
            "estimated_cost_per_question": roughly_opus_4_5_cost * 1.5,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="anthropic/claude-sonnet-5",
                    temperature=None,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        ############################ No-research one-shot bots ############################
        "METAC_GPT_5_5_NO_RESEARCH_ONE_SHOT": {
            "estimated_cost_per_question": roughly_gpt_5_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-5.5",
                    temperature=None,
                    timeout=gpt_5_timeout,
                ),
                bot_type="no_research_one_shot",
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 5th 2026: expensive no-research one-shot experiment retired
        },
        "METAC_GEMINI_3_1_PRO_NO_RESEARCH_ONE_SHOT": {
            "estimated_cost_per_question": roughly_gemini_2_5_pro_preview_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/google/gemini-3.1-pro-preview",
                    temperature=default_temperature,
                    timeout=gemini_default_timeout,
                ),
                bot_type="no_research_one_shot",
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 5th 2026: expensive no-research one-shot experiment retired
        },
        "METAC_CLAUDE_FABLE_5_NO_RESEARCH_ONE_SHOT": {
            "estimated_cost_per_question": roughly_opus_4_5_cost * 2,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="anthropic/claude-fable-5",
                    temperature=None,
                ),
                bot_type="no_research_one_shot",
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 5th 2026: expensive no-research one-shot experiment retired
        },
        "METAC_GROK_4_3_NO_RESEARCH_ONE_SHOT": {
            "estimated_cost_per_question": 5 * roughly_one_call_to_grok_4_llm,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/x-ai/grok-4.3",
                    temperature=default_temperature,
                ),
                bot_type="no_research_one_shot",
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 5th 2026: expensive no-research one-shot experiment retired
        },
        ############################ Bots started in June 2026 ############################
        "METAC_OPENROUTER_FUSION_GENERAL_BUDGET": {
            "estimated_cost_per_question": roughly_opus_4_5_cost,  # Rough guess: budget panel of models + frontier judge + final answer
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/openrouter/fusion",
                    temperature=default_temperature,
                    timeout=20 * 60,
                    extra_body={
                        "plugins": [
                            {
                                "id": "fusion",
                                "preset": "general-budget",
                            }
                        ]
                    },
                ),
                researcher="no_research",  # Fusion does its own web research behind the API
                predictions_per_research_report=1,  # Fusion already aggregates a multi-model panel internally, so only run it once
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GLM_5_2": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/z-ai/glm-5.2",
                    temperature=default_temperature,
                    # pinned to provider Sept 25th 2026
                    **make_openrouter_provider_pin("z-ai/fp8"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_CLAUDE_FABLE_5_HIGH": {
            "estimated_cost_per_question": roughly_opus_4_5_cost * 2,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="anthropic/claude-fable-5",
                    **{
                        k: v
                        for k, v in claude_adaptive_thinking_settings_high.items()
                        if k != "temperature"
                    },
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 5th 2026: outpaced by Fable 5.1
        },
        "METAC_NEMOTRON_3_ULTRA": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/nvidia/nemotron-3-ultra-550b-a55b",
                    temperature=default_temperature,
                    timeout=kimi_k2_timeout,
                    # pinned to provider Sept 25th 2026
                    # Venice (only fp8 host) was down/unreliable on Sep 24th 2026 and DeepInfra's fp4 caps output at 16k tokens
                    **make_openrouter_provider_pin("baseten/fp4"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_QWEN_3_7_PLUS": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/qwen/qwen3.7-plus",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_MINIMAX_M3": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/minimax/minimax-m3",
                    temperature=default_temperature,
                    # pinned to provider Sept 25th 2026
                    **make_openrouter_provider_pin("minimax/fp8"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        ############################ Bots started in May 2026 ############################
        "METAC_GEMINI_3_5_FLASH": {
            "estimated_cost_per_question": roughly_opus_4_5_cost / 2,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/google/gemini-3.5-flash",
                    temperature=default_temperature,
                    timeout=gemini_default_timeout,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 5th 2026: outpaced by Gemini 3.7 Flash
        },
        "METAC_GPT_5_5_HIGH": {
            "estimated_cost_per_question": roughly_gpt_5_high_cost * 2,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-5.5",
                    reasoning_effort="high",
                    temperature=None,
                    timeout=gpt_5_timeout,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 5th 2026: outpaced by GPT 5.6 Sol
        },
        "METAC_GPT_5_5_INSTANT": {
            "estimated_cost_per_question": roughly_gpt_5_cost * 2,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-5.5",
                    reasoning_effort="minimal",
                    temperature=None,
                    timeout=gpt_5_timeout,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 5th 2026: outpaced by GPT 5.6 Luna
        },
        "METAC_GPT_5_4_HIGH": {
            "estimated_cost_per_question": roughly_gpt_5_high_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-5.4",
                    reasoning_effort="high",
                    temperature=default_temperature,
                    timeout=gpt_5_timeout,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 5th 2026: outpaced by GPT 5.6 Sol
        },
        "METAC_GEMINI_3_1_PRO_HIGH": {
            "estimated_cost_per_question": roughly_gemini_2_5_pro_preview_cost * 1.3,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/google/gemini-3.1-pro-preview",
                    reasoning_effort="high",
                    temperature=default_temperature,
                    timeout=gemini_default_timeout,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GEMINI_3_1_FLASH_LITE": {
            "estimated_cost_per_question": roughly_gpt_4o_mini_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/google/gemini-3.1-flash-lite",
                    temperature=default_temperature,
                    timeout=gemini_default_timeout,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_QWEN_3_6_PLUS": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/qwen/qwen3.6-plus",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GEMMA_4": {
            "estimated_cost_per_question": roughly_gpt_4o_mini_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/google/gemma-4-31b-it",
                    temperature=default_temperature,
                    # pinned to provider Sept 25th 2026
                    # using parasail for reliability despite having lower precision
                    **make_openrouter_provider_pin("parasail/fp8"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GLM_5_1": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/z-ai/glm-5.1",
                    temperature=default_temperature,
                    # pinned to provider Sept 25th 2026
                    **make_openrouter_provider_pin("z-ai/fp8"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_CLAUDE_OPUS_4_7_HIGH_32K": {
            "estimated_cost_per_question": roughly_opus_4_5_cost * 1.5,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="anthropic/claude-opus-4-7",
                    **claude_adaptive_thinking_settings_high,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 5th 2026: outpaced by Opus 5
        },
        "METAC_CLAUDE_OPUS_4_8_HIGH": {
            "estimated_cost_per_question": roughly_opus_4_5_cost * 1.5,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="anthropic/claude-opus-4-8",
                    **claude_adaptive_thinking_settings_high,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 5th 2026: outpaced by Opus 5
        },
        "METAC_KIMI_K2_6": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/moonshotai/kimi-k2.6",
                    temperature=None,  # Moonshot's endpoint doesn't support temperature
                    timeout=kimi_k2_timeout,
                    # pinned to provider Sept 25th 2026
                    **make_openrouter_provider_pin("moonshotai/int4"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_DEEPSEEK_V4_PRO_HIGH": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/deepseek/deepseek-v4-pro",
                    temperature=default_temperature,
                    reasoning={
                        "effort": "high",
                    },
                    timeout=5 * 60,
                    # pinned to provider Sept 25th 2026
                    **make_openrouter_provider_pin("novita/fp8"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GROK_4_3_HIGH": {
            "estimated_cost_per_question": 5 * roughly_one_call_to_grok_4_llm,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/x-ai/grok-4.3",
                    reasoning_effort="high",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 5th 2026: outpaced by Grok 4.6
        },
        "METAC_GROK_4_20": {
            "estimated_cost_per_question": 5 * roughly_one_call_to_grok_4_llm,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/x-ai/grok-4.20",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 5th 2026: outpaced by Grok 4.6
        },
        "METAC_GROK_4_20_MULTI_AGENT": {
            "estimated_cost_per_question": 10 * roughly_one_call_to_grok_4_llm,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/x-ai/grok-4.20-multi-agent",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 5th 2026: outpaced by Grok 4.6
        },
        ############################ Bots started in April 2026 ############################
        "METAC_CLAUDE_SONNET_4_6": {
            "estimated_cost_per_question": roughly_sonnet_4_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="anthropic/claude-sonnet-4-6",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Deprecated Sep 5th 2026: outpaced by Sonnet 5
        },
        "METAC_QWEN_3_5": {
            "estimated_cost_per_question": roughly_sonnet_3_5_cost / 2,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/qwen/qwen3.5-397b-a17b",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_GEMINI_3_1_PRO": {
            "estimated_cost_per_question": roughly_gemini_2_5_pro_preview_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/google/gemini-3.1-pro-preview",
                    temperature=default_temperature,
                    timeout=gemini_default_timeout,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GPT_5_5": {
            "estimated_cost_per_question": roughly_gpt_5_high_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-5.5",
                    temperature=None,
                    timeout=gpt_5_timeout,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_GPT_5_4": {
            "estimated_cost_per_question": roughly_gpt_5_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-5.4",
                    temperature=default_temperature,
                    timeout=gpt_5_timeout,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_GPT_5_4_MINI": {
            "estimated_cost_per_question": roughly_gpt_4o_mini_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-5.4-mini",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GPT_5_4_NANO": {
            "estimated_cost_per_question": roughly_gpt_4o_mini_cost / 2,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-5.4-nano",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        # "METAC_GPT_5_3": {} -> Not yet available in OpenAI API as of April 2026
        # "METAC_GPT_5_3_INSTANT": {} -> Not yet available in OpenAI API as of April 2026
        "METAC_MINIMAX_M2_7": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/minimax/minimax-m2.7",
                    temperature=default_temperature,
                    # pinned to provider Sept 25th 2026
                    **make_openrouter_provider_pin("minimax/fp8"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        ############################ Bots started in February 2026 ############################
        "METAC_CLAUDE_OPUS_4_6_HIGH_32K": {
            "estimated_cost_per_question": roughly_opus_4_5_cost * 1.3,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="anthropic/claude-opus-4-6",
                    **claude_thinking_settings_32k,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_CLAUDE_OPUS_4_6": {
            "estimated_cost_per_question": roughly_opus_4_5_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="anthropic/claude-opus-4-6",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_CLAUDE_HAIKU_4_5": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="anthropic/claude-haiku-4-5",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_QWEN3_MAX_THINKING": {
            "estimated_cost_per_question": roughly_sonnet_3_5_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/qwen/qwen3-max-thinking",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_MINIMAX_M2_5": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/minimax/minimax-m2.5",
                    temperature=default_temperature,
                    timeout=1 * 60,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Removed since it timed out the workflow a lot
        },
        "METAC_KIMI_K2_5_HIGH": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/moonshotai/kimi-k2.5",
                    temperature=default_temperature,
                    reasoning={
                        "effort": "high",
                    },
                    timeout=kimi_k2_timeout,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_GLM_5": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/z-ai/glm-5",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        ############################ Bots started in December 2025 ############################
        "METAC_CLAUDE_OPUS_4_5_HIGH_32K": {
            "estimated_cost_per_question": roughly_opus_4_5_cost * 1.3,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="anthropic/claude-opus-4-5",
                    **claude_thinking_settings_32k,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_CLAUDE_OPUS_4_5": {
            "estimated_cost_per_question": roughly_opus_4_5_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="anthropic/claude-opus-4-5",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_GPT_5_2_HIGH": {
            "estimated_cost_per_question": roughly_gpt_5_high_cost * 1.5,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-5.2",
                    reasoning_effort="high",
                    temperature=default_temperature,
                    timeout=gpt_5_timeout,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_GPT_5_2": {
            "estimated_cost_per_question": roughly_gpt_5_cost * 1.5,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-5.2",
                    temperature=default_temperature,
                    timeout=gpt_5_timeout,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_LLAMA_3_1_NEMOTRON_ULTRA_253B": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/nvidia/llama-3.1-nemotron-ultra-253b-v1",
                    temperature=0,  # 0 is recommended for this model in non-reasoning mode
                ),
            ),
            "tournaments": TournConfig.NONE,  # No longer available via OpenRouter as of Feb 25th, 2026
        },
        "METAC_GEMINI_3_FLASH": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost * 2,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/google/gemini-3-flash-preview",
                    temperature=default_temperature,
                    timeout=gemini_default_timeout,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_GLM_4_6": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/z-ai/glm-4.6",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_LLAMA_3_1_405B_INSTRUCT": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost * 3,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/meta-llama/llama-3.1-405b-instruct",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,  # Removed since low performance and non-negligible cost
        },
        ############################ Bots started in November 2025 ############################
        "METAC_KIMI_K2_HIGH": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/moonshotai/kimi-k2-thinking",
                    temperature=default_temperature,
                    timeout=kimi_k2_timeout,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_GPT_5_1_HIGH": {
            "estimated_cost_per_question": roughly_gpt_5_high_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-5.1",
                    reasoning_effort="high",
                    temperature=default_temperature,
                    timeout=gpt_5_timeout,
                    # **flex_price_settings,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_GPT_5_1": {
            "estimated_cost_per_question": roughly_gpt_5_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-5.1",
                    temperature=default_temperature,
                    timeout=gpt_5_timeout,
                    # **flex_price_settings,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        # "METAC_GEMINI_3_PRO_HIGH": {} # The default for regular gemini 3 pro is "high" so no need to make a separate version
        # "METAC_GEMINI_3_PRO": {
        #     "estimated_cost_per_question": roughly_gemini_2_5_pro_preview_cost * 1.3,
        #     "bot": create_bot(
        #         GeneralLlm(
        #             model="openrouter/google/gemini-3-pro-preview",
        #             reasoning_effort="high",  # This should be default (as of Nov 24th, 2025) even without specifying "high"
        #             temperature=1.0,
        #             timeout=gemini_default_timeout,
        #         ),
        #     ),
        #     "tournaments": TournConfig.aib_and_site,
        # },
        "METAC_GROK_4_1_FAST_HIGH": {
            "estimated_cost_per_question": guess_at_deepseek_v3_1_cost * 1.2,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="xai/grok-4-1-fast-reasoning-latest",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_GROK_4_1_FAST": {
            "estimated_cost_per_question": guess_at_deepseek_v3_1_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="xai/grok-4-1-fast-non-reasoning-latest",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        # "METAC_QWEN_3_MAX_HIGH": {} -> Accidentally made bot w/o realizing that qwen-3-max-thinking is just an upgrade to the base model (not a new parameter)
        # "METAC_DEEPSEEK_R1_CP_ENABLED": {}, # TODO: Make a framework for this bot
        ############################ Bots started in October 2025 ############################
        "METAC_CLAUDE_4_5_SONNET_HIGH": {
            "estimated_cost_per_question": roughly_sonnet_4_cost * 2,
            "bot": create_bot(
                llm=GeneralLlm(
                    model=sonnet_4_5_name,
                    **claude_thinking_settings_32k,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_CLAUDE_4_5_SONNET": {
            "estimated_cost_per_question": roughly_sonnet_4_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model=sonnet_4_5_name,
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_QWEN_3_MAX": {
            "estimated_cost_per_question": roughly_sonnet_3_5_cost / 2,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/qwen/qwen3-max",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_DEEPSEEK_3_2_REASONING": {
            "estimated_cost_per_question": guess_at_deepseek_v3_1_cost * 1.2,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/deepseek/deepseek-v3.2-exp",
                    temperature=default_temperature,
                    reasoning={
                        "enabled": True,
                    },
                    timeout=5 * 60,
                    # Provider history (unpinned mix of OpenRouter hosts before Sept 25th 2026):
                    # - Sept 25th 2026: pinned to novita/fp8
                    # - Sept 30th 2026: re-pinned to siliconflow/fp8 (novita/fp8 stopped serving this model)
                    **make_openrouter_provider_pin("siliconflow/fp8"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_DEEPSEEK_3_2": {
            "estimated_cost_per_question": guess_at_deepseek_v3_1_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/deepseek/deepseek-v3.2-exp",
                    temperature=default_temperature,
                    reasoning={
                        "enabled": False,
                    },
                    timeout=3 * 60,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_GROK_4_FAST_HIGH": {
            "estimated_cost_per_question": guess_at_deepseek_v3_1_cost * 1.2,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="xai/grok-4-fast-reasoning-latest",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_GROK_4_FAST": {
            "estimated_cost_per_question": guess_at_deepseek_v3_1_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="xai/grok-4-fast-non-reasoning-latest",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        ############################ Bots started in Fall 2025 ############################
        ### Regular Bots
        "METAC_GPT_5_HIGH": {
            "estimated_cost_per_question": roughly_gpt_5_high_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-5",
                    reasoning_effort="high",
                    temperature=default_temperature,
                    timeout=gpt_5_timeout,
                    # **flex_price_settings,
                ),
            ),
            "tournaments": TournConfig.NONE,  # NOTE: gpt-5 (gpt-5-2025-08-07) deprecated by OpenAI, API shutoff Dec 10, 2026
        },
        "METAC_GPT_5": {
            "estimated_cost_per_question": roughly_gpt_5_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-5",
                    temperature=default_temperature,
                    timeout=gpt_5_timeout,
                    # **flex_price_settings,
                ),
            ),
            "tournaments": TournConfig.NONE,  # NOTE: gpt-5 (gpt-5-2025-08-07) deprecated by OpenAI, API shutoff Dec 10, 2026
        },
        "METAC_GPT_5_MINI": {
            "estimated_cost_per_question": roughly_gpt_4o_mini_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-5-mini",
                    temperature=default_temperature,
                    **flex_price_settings,
                ),
            ),
            "tournaments": TournConfig.NONE,  # NOTE: gpt-5-mini (gpt-5-mini-2025-08-07) deprecated by OpenAI, API shutoff Dec 10, 2026
        },
        "METAC_GPT_5_NANO": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/gpt-5-nano",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,  # NOTE: gpt-5-nano (gpt-5-nano-2025-08-07) deprecated by OpenAI, API shutoff Dec 10, 2026
        },
        "METAC_CLAUDE_4_SONNET_HIGH_16K": {
            "estimated_cost_per_question": 0.33980,
            "bot": create_bot(
                llm=GeneralLlm(
                    model=sonnet_4_name,
                    **claude_thinking_settings_16k,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_CLAUDE_4_SONNET": {
            "estimated_cost_per_question": roughly_sonnet_4_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model=sonnet_4_name,
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_CLAUDE_4_1_OPUS_HIGH_16K": {
            "estimated_cost_per_question": 1.56,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="anthropic/claude-opus-4-1",
                    **claude_thinking_settings_16k,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_GROK_4": {
            "estimated_cost_per_question": 5 * roughly_one_call_to_grok_4_llm,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="xai/grok-4-latest",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_KIMI_K2": {
            **kimi_k2_basic_bot,
            "tournaments": TournConfig.NONE,
        },
        "METAC_KIMI_K2_VARIANCE_TEST": {
            **kimi_k2_basic_bot,
            "tournaments": TournConfig.NONE,
        },
        "METAC_DEEPSEEK_R1_VARIANCE_TEST": {
            **deepseek_r1_bot,
            "tournaments": TournConfig.aib_only,
        },  # See METAC_DEEPSEEK_R1_TOKEN below
        "METAC_GPT_OSS_120B": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/openai/gpt-oss-120b",
                    temperature=default_temperature,
                    # pinned to provider Sept 25th 2026
                    # two bf16 hosts since each alone rate-limited under 5-question bursts
                    **make_openrouter_provider_pin("akashml/bf16", "deepinfra/bf16"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_ZAI_GLM_4_5": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/z-ai/glm-4.5",
                    temperature=default_temperature,
                    reasoning={
                        "enabled": True,
                    },
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_DEEPSEEK_V3_1_REASONING": {
            "estimated_cost_per_question": guess_at_deepseek_v3_1_cost * 1.2,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openrouter/deepseek/deepseek-chat-v3.1",
                    temperature=default_temperature,
                    reasoning={
                        "enabled": True,
                    },
                    timeout=6 * 60,
                    # pinned to provider Sept 25th 2026
                    **make_openrouter_provider_pin("coreweave/fp8"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_DEEPSEEK_V3_1": {
            **deepseek_v3_1_bot,
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_DEEPSEEK_V3_1_VARIANCE_TEST_1": {
            **deepseek_v3_1_bot,
            "tournaments": TournConfig.aib_only,
        },
        "METAC_DEEPSEEK_V3_1_VARIANCE_TEST_2": {
            **deepseek_v3_1_bot,
            "tournaments": TournConfig.aib_only,
        },
        ### Research-Only Bots
        "METAC_O4_MINI_DEEP_RESEARCH": {
            "estimated_cost_per_question": 1.5,  # Top down calculation was 1.5, while bottom up was 0.64674
            "bot": create_bot(
                llm=o4_mini_deep_research_llm,
                bot_type="research_only",
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_O3_DEEP_RESEARCH": {
            "estimated_cost_per_question": roughly_sonnet_3_5_cost * 3
            + guess_at__research_only_bot__search_costs * 5,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="openai/o3-deep-research",
                    temperature=default_temperature,
                ),
                bot_type="research_only",
            ),
            "discontinued": True,
            "tournaments": TournConfig.NONE,
        },
        "METAC_SONAR_DEEP_RESEARCH": {
            "estimated_cost_per_question": 3
            * roughly_sonar_deep_research_cost_per_call,
            "bot": create_bot(
                llm=sonar_deep_research_llm,
                bot_type="research_only",
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_EXA_RESEARCH_PRO": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost
            + guess_at__research_only_bot__search_costs,
            "bot": create_bot(
                llm=GeneralLlm(
                    model="exa/exa-research-pro",
                    temperature=default_temperature,
                ),
                bot_type="research_only",
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_GEMINI_2_5_PRO_GROUNDING": {
            "estimated_cost_per_question": roughly_sonnet_3_5_cost
            + guess_at__research_only_bot__search_costs,
            "bot": create_bot(
                gemini_grounding_llm,
                bot_type="research_only",
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_ASKNEWS_DEEPNEWS": {
            "estimated_cost_per_question": 0,
            "bot": create_bot(
                llm=GeneralLlm(
                    model=deepnews_model,
                    temperature=default_temperature,
                ),
                bot_type="research_only",
            ),
            "tournaments": TournConfig.aib_only,
        },
        "METAC_GPT_5_SEARCH": {
            "estimated_cost_per_question": 1.17,
            "bot": create_bot(
                llm=gpt_5_with_search,
                bot_type="research_only",
            ),
            "tournaments": TournConfig.NONE,  # NOTE: gpt-5 (gpt-5-2025-08-07) deprecated by OpenAI, API shutoff Dec 10, 2026
        },
        "METAC_GROK_4_LIVE_SEARCH": {
            "estimated_cost_per_question": 3 * roughly_one_call_to_grok_4_llm,
            "bot": create_bot(
                llm=grok_4_search_llm,
                bot_type="research_only",
            ),
            "tournaments": TournConfig.NONE,  # Live search is now deprecated
        },
        "METAC_SONNET_4_SEARCH": {
            "estimated_cost_per_question": 1.53366,
            "bot": create_bot(
                llm=sonnet_4_search_llm,
                bot_type="research_only",
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_DEEPSEEK_R1_EXA_ONLINE_RESEARCH_ONLY": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost
            + guess_at__research_only_bot__search_costs,
            "bot": create_bot(
                llm=deepseek_r1_exa_online_llm,
                bot_type="research_only",
            ),
            "tournaments": TournConfig.aib_only,
        },
        ### DeepSeek Research Bots
        "METAC_DEEPSEEK_R1_PLUS_EXA_ONLINE": {
            "estimated_cost_per_question": guess_at_deepseek_plus_search,
            "bot": create_bot(
                llm=default_research_comparison_forecast_llm,
                researcher=deepseek_r1_exa_online_llm,
            ),
            "tournaments": TournConfig.aib_only,
        },
        "METAC_DEEPSEEK_R1_SONNET_4_SEARCH": {
            "estimated_cost_per_question": guess_at_deepseek_plus_search,
            "bot": create_bot(
                llm=default_research_comparison_forecast_llm,
                researcher=sonnet_4_search_llm,
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_DEEPSEEK_R1_XAI_LIVESEARCH": {
            "estimated_cost_per_question": guess_at_deepseek_plus_search
            + roughly_one_call_to_grok_4_llm,
            "bot": create_bot(
                llm=default_research_comparison_forecast_llm,
                researcher=grok_4_search_llm,
            ),
            "tournaments": TournConfig.NONE,  # Live search is now deprecated
        },
        "METAC_DEEPSEEK_R1_O4_MINI_DEEP_RESEARCH": {
            "estimated_cost_per_question": roughly_deepseek_r1_cost + 1.5 / 3,
            "bot": create_bot(
                llm=default_research_comparison_forecast_llm,
                researcher=o4_mini_deep_research_llm,
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_DEEPSEEK_R1_NO_RESEARCH": {
            "estimated_cost_per_question": guess_at_deepseek_plus_search,
            "bot": create_bot(
                llm=default_research_comparison_forecast_llm,
                researcher="no_research",
            ),
            "tournaments": TournConfig.aib_only,
        },
        ### Specialized Bots
        "METAC_GPT_4_1_OPTIMIZED_PROMPT": {
            "estimated_cost_per_question": 0.13871,
            "bot": create_bot(
                GeneralLlm(
                    model="openai/gpt-4.1",
                    temperature=default_temperature,
                    timeout=60 * 5,
                ),
                bot_type="gpt_4_1_optimized",
            ),
            "tournaments": TournConfig.aib_only,
        },
        "METAC_GPT_4_1_NANO_OPTIMIZED_PROMPT": {
            "estimated_cost_per_question": roughly_gpt_4o_mini_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="openai/gpt-4.1-nano",
                    temperature=default_temperature,
                    timeout=60 * 5,
                ),
                bot_type="gpt_4_1_optimized",
            ),
            "tournaments": TournConfig.aib_only,
        },
        "METAC_GROK_4_TOOLS": {
            "estimated_cost_per_question": None,
            "bot": None,
            "tournaments": TournConfig.NONE,
        },  # Don't have time to implement this, but this is a env variable that exists
        "METAC_GPT_5_HIGH_TOOLS": {
            "estimated_cost_per_question": None,
            "bot": None,
            "tournaments": TournConfig.NONE,
        },  # Don't have time to implement this, but this is a env variable that exists
        "METAC_SONNET_4_HIGH_TOOLS": {
            "estimated_cost_per_question": None,
            "bot": None,
            "tournaments": TournConfig.NONE,
        },  # Don't have time to implement this, but this is a env variable that exists
        ############################ Bots started in Q2 2025 ############################
        "METAC_GEMINI_2_5_PRO_GEMINI_2_5_PRO_GROUNDING": {
            "estimated_cost_per_question": 0.16,
            "bot": create_bot(
                GeneralLlm(
                    model=gemini_2_5_pro,
                    temperature=default_temperature,
                    timeout=gemini_default_timeout,
                ),
                researcher=gemini_grounding_llm,
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_GEMINI_2_5_PRO_SONAR_REASONING_PRO": {
            "estimated_cost_per_question": roughly_gemini_2_5_pro_preview_cost,
            "bot": create_bot(
                GeneralLlm(
                    model=gemini_2_5_pro,
                    temperature=default_temperature,
                    timeout=gemini_default_timeout,
                ),
                researcher=GeneralLlm(
                    model="perplexity/sonar-reasoning-pro",
                    **default_perplexity_settings,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_GEMINI_2_5_EXA_PRO": {
            "estimated_cost_per_question": roughly_gemini_2_5_pro_preview_cost,
            "bot": create_bot(
                GeneralLlm(
                    model=gemini_2_5_pro,
                    temperature=default_temperature,
                    timeout=gemini_default_timeout,
                ),
                researcher=GeneralLlm(
                    model="exa/exa"
                ),  # NOTE: Used to be exa-pro but that got deprecated
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_DEEPSEEK_R1_SONAR_PRO": {
            "estimated_cost_per_question": guess_at_deepseek_plus_search,
            "bot": create_bot(
                default_research_comparison_forecast_llm,
                researcher=GeneralLlm(
                    model="perplexity/sonar-pro",
                    **default_perplexity_settings,
                ),
            ),
            "tournaments": TournConfig.aib_only,
        },
        "METAC_DEEPSEEK_R1_SONAR": {
            "estimated_cost_per_question": guess_at_deepseek_plus_search,
            "bot": create_bot(
                default_research_comparison_forecast_llm,
                researcher=GeneralLlm(
                    model="perplexity/sonar",
                    **default_perplexity_settings,
                ),
            ),
            "tournaments": TournConfig.aib_only,
        },
        "METAC_DEEPSEEK_R1_SONAR_DEEP_RESEARCH": {
            "estimated_cost_per_question": guess_at_deepseek_plus_search
            + roughly_sonar_deep_research_cost_per_call,
            "bot": create_bot(
                default_research_comparison_forecast_llm,
                researcher=sonar_deep_research_llm,
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_DEEPSEEK_R1_SONAR_REASONING_PRO": {
            "estimated_cost_per_question": guess_at_deepseek_plus_search,
            "bot": create_bot(
                default_research_comparison_forecast_llm,
                researcher=GeneralLlm(
                    model="perplexity/sonar-reasoning-pro",
                    **default_perplexity_settings,
                ),
            ),
            "tournaments": TournConfig.aib_only,
        },
        "METAC_DEEPSEEK_R1_SONAR_REASONING": {
            "estimated_cost_per_question": guess_at_deepseek_plus_search,
            "bot": create_bot(
                default_research_comparison_forecast_llm,
                researcher=GeneralLlm(
                    model="perplexity/sonar-reasoning",
                    **default_perplexity_settings,
                ),
            ),
            "tournaments": TournConfig.NONE,  # sonar-reasoning is now deprecated
        },
        "METAC_ONLY_SONAR_REASONING_PRO": {
            "estimated_cost_per_question": guess_at_deepseek_plus_search,
            "bot": create_bot(
                GeneralLlm(
                    model="perplexity/sonar-reasoning-pro",
                    **default_perplexity_settings,
                ),
                researcher="None",
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_DEEPSEEK_R1_GPT_4O_SEARCH_PREVIEW": {
            "estimated_cost_per_question": guess_at_deepseek_plus_search,
            "bot": create_bot(
                default_research_comparison_forecast_llm,
                researcher=GeneralLlm(
                    model="openai/gpt-4o-search-preview", temperature=None
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_DEEPSEEK_R1_GEMINI_2_5_PRO_GROUNDING": {
            "estimated_cost_per_question": guess_at_deepseek_plus_search,
            "bot": create_bot(
                default_research_comparison_forecast_llm,
                researcher=gemini_grounding_llm,
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_DEEPSEEK_R1_EXA_SMART_SEARCHER": {
            "estimated_cost_per_question": guess_at_deepseek_plus_search,
            "bot": create_bot(
                default_research_comparison_forecast_llm,
                researcher="smart-searcher/openrouter/deepseek/deepseek-r1",
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_DEEPSEEK_R1_ASK_EXA_PRO": {
            "estimated_cost_per_question": guess_at_deepseek_plus_search,
            "bot": create_bot(
                default_research_comparison_forecast_llm,
                researcher=GeneralLlm(
                    model="exa/exa"
                ),  # Used to be "exa-pro" till this got deprecated
            ),
            "tournaments": TournConfig.aib_only,
        },
        "METAC_DEEPSEEK_R1_DEEPNEWS": {
            "estimated_cost_per_question": guess_at_deepseek_plus_search,
            "bot": create_bot(
                default_research_comparison_forecast_llm,
                researcher=deepnews_model,
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_O3_HIGH_TOKEN": {
            "estimated_cost_per_question": 0.16,
            "bot": create_bot(
                GeneralLlm(
                    model="o3",
                    temperature=1,
                    reasoning_effort="high",
                    timeout=60 * 8,
                    # **flex_price_settings,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_O3_TOKEN": {
            "estimated_cost_per_question": 0.16 * 0.8,
            "bot": create_bot(
                GeneralLlm(
                    model="o3",
                    temperature=1,
                    reasoning_effort="medium",
                    timeout=60 * 8,
                    # **flex_price_settings,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_O4_MINI_HIGH_TOKEN": {
            "estimated_cost_per_question": 0.07,
            "bot": create_bot(
                GeneralLlm(
                    model="o4-mini",
                    temperature=1,
                    reasoning_effort="high",
                    # **flex_price_settings,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_O4_MINI_TOKEN": {
            "estimated_cost_per_question": 0.043,
            "bot": create_bot(
                GeneralLlm(
                    model="o4-mini",
                    temperature=1,
                    reasoning_effort="medium",
                    # **flex_price_settings,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_4_1_TOKEN": {
            "estimated_cost_per_question": 0.07,
            "bot": create_bot(
                GeneralLlm(model="gpt-4.1", temperature=default_temperature),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_4_1_MINI_TOKEN": {
            "estimated_cost_per_question": 0.015,
            "bot": create_bot(
                GeneralLlm(
                    model="gpt-4.1-mini",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_4_1_NANO_TOKEN": {
            "estimated_cost_per_question": roughly_gpt_4o_mini_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="gpt-4.1-nano",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GEMINI_2_5_FLASH_PREVIEW_TOKEN": {
            "estimated_cost_per_question": 0.03,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/google/gemini-2.5-flash",  # NOTE: This was updated from "gemini/gemini-2.5-flash-preview-04-17" in Fall 2025
                    temperature=default_temperature,
                    timeout=gemini_default_timeout,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_O1_HIGH_TOKEN": {
            "estimated_cost_per_question": 1.18,
            "bot": create_bot(
                GeneralLlm(
                    model="o1",
                    temperature=default_temperature,
                    reasoning_effort="high",
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_O1_TOKEN": {
            "estimated_cost_per_question": 1.15,
            "bot": create_bot(
                GeneralLlm(
                    model="o1",
                    temperature=default_temperature,
                    reasoning_effort="medium",
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_O1_MINI_TOKEN": {
            "estimated_cost_per_question": roughly_gpt_4o_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="o1-mini",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_O3_MINI_HIGH_TOKEN": {
            "estimated_cost_per_question": roughly_gpt_4o_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="o3-mini",
                    temperature=default_temperature,
                    reasoning_effort="high",
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_O3_MINI_TOKEN": {
            "estimated_cost_per_question": roughly_gpt_4o_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="o3-mini",
                    temperature=default_temperature,
                    reasoning_effort="medium",
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_GPT_4O_TOKEN": {
            "estimated_cost_per_question": roughly_gpt_4o_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="gpt-4o-2024-08-06",  # NOTE: This bot used to be just "gpt-4o" in q2 2025 and before so changed between the 3 versions as the API Updated
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GPT_4O_MINI_TOKEN": {
            "estimated_cost_per_question": roughly_gpt_4o_mini_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="gpt-4o-mini",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GPT_3_5_TURBO_TOKEN": {
            "estimated_cost_per_question": roughly_gpt_4o_mini_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="gpt-3.5-turbo",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_CLAUDE_3_7_SONNET_LATEST_THINKING_TOKEN": {
            "estimated_cost_per_question": 0.37,
            "bot": create_bot(
                GeneralLlm(
                    model="anthropic/claude-3-7-sonnet-latest",  # NOSONAR
                    temperature=1,
                    thinking={
                        "type": "enabled",
                        "budget_tokens": 32000,
                    },
                    max_tokens=40000,
                    timeout=160,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_CLAUDE_3_7_SONNET_LATEST_TOKEN": {
            "estimated_cost_per_question": roughly_sonnet_3_5_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="anthropic/claude-3-7-sonnet-latest",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_CLAUDE_3_5_SONNET_LATEST_TOKEN": {
            "estimated_cost_per_question": roughly_sonnet_3_5_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="anthropic/claude-3-5-sonnet-latest",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,  # NOTE: No longer available (model deprecated by Anthropic)
        },
        "METAC_CLAUDE_3_5_SONNET_20240620_TOKEN": {
            "estimated_cost_per_question": roughly_sonnet_3_5_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="anthropic/claude-3-5-sonnet-20240620",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,  # NOTE: No longer available (model deprecated by Anthropic)
        },
        "METAC_GEMINI_2_5_PRO_PREVIEW_TOKEN": {
            "estimated_cost_per_question": roughly_gemini_2_5_pro_preview_cost,
            "bot": create_bot(
                GeneralLlm(
                    model=gemini_2_5_pro,  # NOTE: Switched from preview to regular pro mid Q2
                    temperature=default_temperature,
                    timeout=gemini_default_timeout,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_GEMINI_2_0_FLASH_TOKEN": {
            "estimated_cost_per_question": 0.05,
            "bot": create_bot(
                GeneralLlm(
                    model="gemini/gemini-2.0-flash-001",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_LLAMA_4_MAVERICK_17B_TOKEN": {
            "estimated_cost_per_question": roughly_gpt_4o_mini_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/meta-llama/llama-4-maverick",
                    temperature=default_temperature,
                    # Provider history (unpinned mix of OpenRouter hosts before Sept 25th 2026):
                    # - Sept 25th 2026: pinned to deepinfra/base (fp8)
                    # - Oct 10th 2026: re-pinned to parasail/fp8 (deepinfra/base stopped serving this model by Oct 4th, failing every call)
                    **make_openrouter_provider_pin("parasail/fp8"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_QWEN_2_5_MAX_TOKEN": {
            "estimated_cost_per_question": roughly_gpt_4o_mini_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/qwen/qwen-max",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_DEEPSEEK_R1_TOKEN": {
            **deepseek_r1_bot,
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_DEEPSEEK_V3_TOKEN": {
            "estimated_cost_per_question": roughly_gpt_4o_mini_cost,
            "bot": create_bot(
                GeneralLlm(
                    model="openrouter/deepseek/deepseek-chat",
                    temperature=default_temperature,
                    # pinned to provider Sept 25th 2026
                    # StreamLake doesn't declare its quantization, but the only other host is fp4
                    **make_openrouter_provider_pin("streamlake"),
                ),
            ),
            "tournaments": TournConfig.aib_and_site,
        },
        "METAC_GROK_3_LATEST_TOKEN": {
            "estimated_cost_per_question": 0.13,
            "bot": create_bot(
                GeneralLlm(
                    model="xai/grok-3-latest",
                    temperature=default_temperature,
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_GROK_3_MINI_LATEST_HIGH_TOKEN": {
            "estimated_cost_per_question": 0.10,
            "bot": create_bot(
                GeneralLlm(
                    model="xai/grok-3-mini-latest",
                    temperature=default_temperature,
                    reasoning_effort="high",
                ),
            ),
            "tournaments": TournConfig.NONE,
        },
        "METAC_UNIFORM_PROBABILITY_BOT_TOKEN": {
            "estimated_cost_per_question": 0.00,
            "bot": UniformProbabilityBot(
                use_research_summary_to_forecast=default_for_using_summary,
                publish_reports_to_metaculus=default_for_publish_to_metaculus,
                skip_previously_forecasted_questions=default_for_skipping_questions,
            ),
            "tournaments": TournConfig.aib_and_site,
        },
    }

    # Run basic validation/sanity checks on the bots
    modes = list(mode_base_bot_mapping.keys())
    bots: list[ForecastBot] = [mode_base_bot_mapping[key]["bot"] for key in modes]
    for mode, bot in zip(modes, bots):
        if "sonar" in mode.lower():
            researcher = bot.get_llm("researcher", "llm")
            if "only" in mode.lower():
                researcher = bot.get_llm("default", "llm")

            researcher_is_perplexity = researcher.model.startswith("perplexity/")
            forecaster_is_perplexity = bot.get_llm("default", "llm").model.startswith(
                "perplexity/"
            )

            assert researcher_is_perplexity or forecaster_is_perplexity
            if researcher_is_perplexity:
                assert (
                    researcher.litellm_kwargs["web_search_options"][
                        "search_context_size"
                    ]
                    == "high"
                ), f"Researcher {researcher.model} is perplexity but does not have high search context size for {mode}"
                assert (
                    researcher.litellm_kwargs["reasoning_effort"] == "high"
                ), f"Researcher {researcher.model} is not set to high reasoning effort for {mode}"
        elif "grounding" in mode.lower():
            researcher = bot.get_llm("researcher", "llm")
            forecaster = bot.get_llm("default", "llm")
            researcher_is_google = researcher.model.startswith(
                "gemini/"
            ) or researcher.model.startswith("openrouter/google/")
            forecaster_is_google = forecaster.model.startswith("openrouter/google/")
            assert researcher_is_google or forecaster_is_google
            if researcher_is_google:
                assert len(researcher.litellm_kwargs["tools"]) == 1
        elif "deepseek" in mode.lower():
            researcher = bot.get_llm("researcher", "llm")
            forecaster = bot.get_llm("default", "llm")
            researcher_is_deepseek = researcher.model.startswith("openrouter/deepseek/")
            forecaster_is_deepseek = forecaster.model.startswith("openrouter/deepseek/")
            assert researcher_is_deepseek or forecaster_is_deepseek

    mode_to_bot_config = {
        mode: RunBotConfig(**{**bot_config, "mode": mode})
        for mode, bot_config in mode_base_bot_mapping.items()
    }
    return mode_to_bot_config


if __name__ == "__main__":
    logging.basicConfig(
        level=logging.INFO,
        format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
    )

    # Suppress LiteLLM logging
    litellm_logger = logging.getLogger("LiteLLM")
    litellm_logger.setLevel(logging.WARNING)
    litellm_logger.propagate = False

    parser = argparse.ArgumentParser(
        description="Run a forecasting bot with the specified mode"
    )
    parser.add_argument(
        "mode",
        type=str,
        help="Bot mode to run",
    )

    args = parser.parse_args()
    token = args.mode

    asyncio.run(configure_and_run_bot(token))