use codex_protocol::config_types::ReasoningSummary;use codex_protocol::openai_models::ConfigShellToolType;use codex_protocol::openai_models::ModelInfo;use codex_protocol::openai_models::ModelInstructionsVariables;use codex_protocol::openai_models::ModelMessages;use codex_protocol::openai_models::ModelVisibility;use codex_protocol::openai_models::TruncationMode;use codex_protocol::openai_models::TruncationPolicyConfig;use codex_protocol::openai_models::WebSearchToolType;use codex_protocol::openai_models::default_input_modalities;use crate::config::ModelsManagerConfig;use codex_utils_output_truncation::approx_bytes_for_tokens;use tracing::warn;pub const BASE_INSTRUCTIONS: &str = include_str!("../prompt.md");const DEFAULT_PERSONALITY_HEADER: &str = "You are Codex, a coding agent based on GPT-5. You and the user share the same workspace and collaborate to achieve the user's goals.";const LOCAL_FRIENDLY_TEMPLATE: &str =    "You optimize for team morale and being a supportive teammate as much as code quality.";const LOCAL_PRAGMATIC_TEMPLATE: &str = "You are a deeply pragmatic, effective software engineer.";const PERSONALITY_PLACEHOLDER: &str = "{{ personality }}";pub fn with_config_overrides(mut model: ModelInfo, config: &ModelsManagerConfig) -> ModelInfo {    if let Some(supports_reasoning_summaries) = config.model_supports_reasoning_summaries        && supports_reasoning_summaries    {        model.supports_reasoning_summaries = true;    }    if let Some(context_window) = config.model_context_window {        model.context_window = Some(            model                .max_context_window                .map_or(context_window, |max_context_window| {                    context_window.min(max_context_window)                }),        );    }    if let Some(auto_compact_token_limit) = config.model_auto_compact_token_limit {        model.auto_compact_token_limit = Some(auto_compact_token_limit);    }    if let Some(token_limit) = config.tool_output_token_limit {        model.truncation_policy = match model.truncation_policy.mode {            TruncationMode::Bytes => {                let byte_limit =                    i64::try_from(approx_bytes_for_tokens(token_limit)).unwrap_or(i64::MAX);                TruncationPolicyConfig::bytes(byte_limit)            }            TruncationMode::Tokens => {                let limit = i64::try_from(token_limit).unwrap_or(i64::MAX);                TruncationPolicyConfig::tokens(limit)            }        };    }    if let Some(base_instructions) = &config.base_instructions {        model.base_instructions = base_instructions.clone();        model.model_messages = None;    } else if !config.personality_enabled {        model.model_messages = None;    }    model}/// Build a minimal fallback model descriptor for missing/unknown slugs.pub fn model_info_from_slug(slug: &str) -> ModelInfo {    warn!("Unknown model {slug} is used. This will use fallback model metadata.");    ModelInfo {        slug: slug.to_string(),        display_name: slug.to_string(),        description: None,        default_reasoning_level: None,        supported_reasoning_levels: Vec::new(),        shell_type: ConfigShellToolType::Default,        visibility: ModelVisibility::None,        supported_in_api: true,        priority: 99,        additional_speed_tiers: Vec::new(),        service_tiers: Vec::new(),        default_service_tier: None,        availability_nux: None,        upgrade: None,        base_instructions: BASE_INSTRUCTIONS.to_string(),        model_messages: local_personality_messages_for_slug(slug),        supports_reasoning_summaries: false,        default_reasoning_summary: ReasoningSummary::Auto,        support_verbosity: false,        default_verbosity: None,        apply_patch_tool_type: None,        web_search_tool_type: WebSearchToolType::Text,        truncation_policy: TruncationPolicyConfig::bytes(/*limit*/ 10_000),        supports_parallel_tool_calls: false,        supports_image_detail_original: false,        context_window: Some(272_000),        max_context_window: Some(272_000),        auto_compact_token_limit: None,        comp_hash: None,        effective_context_window_percent: 95,        experimental_supported_tools: Vec::new(),        input_modalities: default_input_modalities(),        used_fallback_model_metadata: true, // this is the fallback model metadata        supports_search_tool: false,        use_responses_lite: false,        auto_review_model_override: None,        tool_mode: None,        multi_agent_version: None,    }}fn local_personality_messages_for_slug(slug: &str) -> Option<ModelMessages> {    match slug {        "gpt-5.2-codex" | "exp-codex-personality" => Some(ModelMessages {            instructions_template: Some(format!(                "{DEFAULT_PERSONALITY_HEADER}\n\n{PERSONALITY_PLACEHOLDER}\n\n{BASE_INSTRUCTIONS}"            )),            instructions_variables: Some(ModelInstructionsVariables {                personality_default: Some(String::new()),                personality_friendly: Some(LOCAL_FRIENDLY_TEMPLATE.to_string()),                personality_pragmatic: Some(LOCAL_PRAGMATIC_TEMPLATE.to_string()),            }),        }),        _ => None,    }}#[cfg(test)]#[path = "model_info_tests.rs"]mod tests;