wiremux 0.11.9

//! Item-centered IR and LossReport.

use std::collections::BTreeMap;

/// Protocol-neutral conversation. Hosts convert to/from their own types.
///
/// Build with [`IrRequest::new`]. Extra fields stay at their defaults.
///
/// ```
/// use wiremux::{IrItem, IrPart, IrRequest};
/// let req = IrRequest::new(
///     "gpt-4",
///     vec![IrItem::User {
///         parts: vec![IrPart::Text("Hi".into())],
///     }],
/// );
/// assert_eq!(req.model, "gpt-4");
/// assert!(req.tools.is_empty());
/// ```
#[derive(Clone, Debug, PartialEq)]
#[non_exhaustive]
pub struct IrRequest {
    pub model: String,
    pub items: Vec<IrItem>,
    pub tools: Vec<IrTool>,
    pub sampling: IrSampling,
}

impl IrRequest {
    /// Request with `model` and `items`. Tools and sampling are empty/default.
    ///
    /// Pass a string slice (`"gpt-4o"`). Do not write `model.into()`:
    /// hosts that also depend on `bytes` or `reqwest` see `E0283`.
    #[must_use]
    pub fn new(model: impl AsRef<str>, items: Vec<IrItem>) -> Self {
        Self {
            model: model.as_ref().to_owned(),
            items,
            tools: Vec::new(),
            sampling: IrSampling::default(),
        }
    }

    /// Set tools. For hosts that cannot use a struct literal.
    #[must_use]
    pub fn with_tools(mut self, tools: Vec<IrTool>) -> Self {
        self.tools = tools;
        self
    }

    /// Set sampling. For hosts that cannot use a struct literal.
    #[must_use]
    pub fn with_sampling(mut self, sampling: IrSampling) -> Self {
        self.sampling = sampling;
        self
    }
}

impl Default for IrRequest {
    fn default() -> Self {
        Self::new(String::new(), Vec::new())
    }
}

#[derive(Clone, Debug, Default, PartialEq)]
#[non_exhaustive]
pub struct IrSampling {
    pub temperature: Option<f32>,
    pub top_p: Option<f32>,
    /// Messages `top_k`. Gemini `generationConfig.topK`.
    /// Chat Completions, Responses, and Converse drop.
    pub top_k: Option<u32>,
    /// Host max output tokens.
    ///
    /// Chat Completions encode may write `max_completion_tokens` and omit
    /// temperature (`LossReport`) for o1/o3/o4/gpt-5; decode accepts either key.
    /// Chat omits logprobs for gpt-5, gpt-5-mini, and gpt-5-nano, and for
    /// gpt-5.1 and gpt-5.2 unless reasoning effort is none. Responses does
    /// the same for temperature, top_p, and top_logprobs.
    pub max_tokens: Option<u32>,
    /// Chat omits stop for o3 and o4-mini.
    pub stop: Vec<String>,
    pub tool_choice: IrToolChoice,
    pub parallel_tool_calls: Option<bool>,
    /// Chat Completions and Responses `store`. Gemini emits request-root
    /// `store`. Messages drops.
    pub store: Option<bool>,
    pub previous_response_id: Option<String>,
    pub cache: IrCache,
    /// Client asked for SSE. Grok TUI always sets this.
    pub stream: Option<bool>,
    /// Gemini `thinkingConfig.includeThoughts`; Messages `thinking.type`;
    /// Responses `reasoning.summary` (`auto` when true). Chat Completions drops.
    pub include_thoughts: Option<bool>,
    /// Gemini `thinkingConfig.thinkingBudget` (decode and encode).
    /// Messages encode emits this as `thinking.budget_tokens` when
    /// `max_reasoning_tokens` is unset. Messages decode leaves this `None`
    /// and writes `budget_tokens` into `max_reasoning_tokens`.
    pub thinking_budget: Option<u32>,
    /// Dialect effort string (`low`, `high`, `xhigh`). Not a host enum.
    /// Gemini encode emits `thinkingConfig.thinkingLevel` (lowercase;
    /// `xhigh` / `x-high` degrade to `high`). Converse encode emits
    /// `outputConfig.effort` (`low`/`medium`/`high`/`xhigh`/`max`;
    /// `x-high` degrades to `xhigh`).
    pub reasoning_effort: Option<String>,
    /// Host cap on reasoning tokens.
    ///
    /// Messages decode writes `thinking.budget_tokens` here
    /// (`thinking_budget` stays `None`). Messages encode emits this as
    /// `thinking.budget_tokens`. Gemini encode emits it as
    /// `thinkingConfig.thinkingBudget` when `thinking_budget` is unset.
    /// Chat Completions and Responses have no emit slot.
    pub max_reasoning_tokens: Option<u32>,
    /// JSON schema for structured output when the dialect has a slot.
    pub json_schema: Option<serde_json::Value>,
    /// Optional schema name (Responses `text.format.name` / Chat json_schema.name /
    /// Converse `outputConfig.textFormat.structure.jsonSchema.name`).
    pub json_schema_name: Option<String>,
    /// Chat `response_format.json_schema.description`, Responses
    /// `text.format.description`, and Converse
    /// `outputConfig.textFormat.structure.jsonSchema.description`.
    /// Gemini and Messages drop when set.
    pub json_schema_description: Option<String>,
    /// Chat Completions `response_format.json_schema.strict`.
    /// Other dests drop when `Some`.
    pub json_schema_strict: Option<bool>,
    /// Unconstrained JSON object mode (Chat `response_format.type=json_object`,
    /// Responses `text.format.type=json_object`, Gemini `responseMimeType=
    /// application/json` without a schema). `json_schema` wins when both are set.
    pub json_object: Option<bool>,
    /// Responses `include`. Empty by default. Encode writes this list and
    /// omits the field when it is empty. It does not add
    /// `reasoning.encrypted_content`. Other dests drop a non-empty list.
    pub include: Vec<String>,
    /// OpenAI / Codex `prompt_cache_key`. Chat Completions and Responses
    /// emit it. Messages and Gemini drop.
    pub prompt_cache_key: Option<String>,
    /// Chat Completions and Responses `prompt_cache_retention`
    /// (`24h` / `in_memory`). Distinct from Messages `IrCache.retention`.
    /// Gemini, Messages, and Converse drop.
    pub prompt_cache_retention: Option<String>,
    /// Chat / Responses `prompt_cache_options.mode` (`implicit` / `explicit`).
    pub prompt_cache_mode: Option<String>,
    /// Chat / Responses `prompt_cache_options.ttl` (`30m`). Distinct from Messages IrCache.retention.
    pub prompt_cache_ttl: Option<String>,
    /// Chat / Responses `top_logprobs` (0-20).
    pub top_logprobs: Option<u32>,
    /// Chat / Responses `moderation.model`.
    pub moderation_model: Option<String>,
    /// Chat / Responses `moderation.policy.input.mode` (`score` / `block`).
    pub moderation_input: Option<String>,
    /// Chat / Responses `moderation.policy.output.mode`.
    pub moderation_output: Option<String>,
    /// Chat / Responses `stream_options.include_obfuscation`.
    pub include_obfuscation: Option<bool>,
    /// Chat Completions and Responses `user`. Messages, Gemini, and
    /// Converse drop.
    pub user: Option<String>,
    /// Chat Completions `verbosity` and Responses `text.verbosity`
    /// (`low` / `medium` / `high`). Gemini, Messages, and Converse drop.
    pub verbosity: Option<String>,
    /// Chat Completions and Responses `safety_identifier`.
    /// Distinct from `user`. Gemini, Messages, and Converse drop.
    pub safety_identifier: Option<String>,
    /// Chat Completions and Responses `metadata` string map.
    /// Messages `metadata.user_id` stays on `user`. Gemini and Converse drop.
    pub metadata: BTreeMap<String, String>,
    /// Chat Completions `frequency_penalty`. Gemini `generationConfig.frequencyPenalty`.
    /// Messages, Responses, and Converse drop.
    pub frequency_penalty: Option<f32>,
    /// Chat Completions `presence_penalty`. Gemini `generationConfig.presencePenalty`.
    /// Messages, Responses, and Converse drop.
    pub presence_penalty: Option<f32>,
    /// Chat Completions `seed`. Gemini `generationConfig.seed`.
    /// Messages, Responses, and Converse drop.
    pub seed: Option<i64>,
    /// Chat Completions `n`. Gemini `generationConfig.candidateCount`.
    /// Messages, Responses, and Converse drop.
    pub n: Option<u32>,
    /// OpenAI / Codex `service_tier` (`flex`, `priority`, `auto`).
    /// Chat Completions and Responses emit it. Converse emits
    /// `serviceTier.type` (`flex` / `priority` / `reserved` /
    /// `default`; `auto` degrades to `default`). Gemini emits
    /// request-root `serviceTier` (`flex` / `priority` / `standard`;
    /// `default` / `auto` degrade to `standard`). Messages drops.
    pub service_tier: Option<String>,
    /// Dest Chat `modalities` (`text` / `audio`). Dest Gemini
    /// `generationConfig.responseModalities` (`TEXT` / `AUDIO` / `IMAGE`).
    /// Dest Messages, dest Responses, and dest Converse drop.
    /// Dest Chat drops `image`.
    pub output_modalities: Vec<String>,
    /// Dest Chat `audio.voice` (string or object `id`). Dest Gemini
    /// `generationConfig.speechConfig.voiceConfig.prebuiltVoiceConfig.voiceName`.
    /// Dest Messages, dest Responses, and dest Converse drop.
    pub audio_voice: Option<String>,
    /// Dest Chat `audio.format`. Dest Gemini speechConfig has no format
    /// (Chat encode defaults to `wav` when emitting `audio`). Dest
    /// Messages, dest Responses, and dest Converse drop.
    pub audio_format: Option<String>,
    /// Dest Chat `logprobs` boolean. Dest Gemini
    /// `generationConfig.responseLogprobs`. Distinct from `top_logprobs`.
    /// Dest Messages, dest Responses, and dest Converse drop.
    pub logprobs: Option<bool>,
    /// Dest Chat `logit_bias` token-id to bias (-100..100). Dest Responses,
    /// dest Gemini, dest Messages, and dest Converse drop.
    pub logit_bias: BTreeMap<String, f64>,
    /// Dest Chat `prediction` object (`type` + `content`). Dest Responses,
    /// dest Gemini, dest Messages, and dest Converse drop.
    pub prediction: Option<serde_json::Value>,
    /// Dest Chat `web_search_options` object. Dest Responses, dest Gemini,
    /// dest Messages, and dest Converse drop.
    pub web_search_options: Option<serde_json::Value>,
    /// Messages request `inference_geo`. Chat, Responses, Gemini, and Converse drop.
    pub inference_geo: Option<String>,
    /// Converse `performanceConfig.latency` (`standard` or `optimized`).
    /// Chat, Messages, Responses, and Gemini drop.
    pub performance_latency: Option<String>,
    /// Messages request `diagnostics.previous_message_id`. Chat, Responses, Gemini, and Converse drop.
    pub previous_message_id: Option<String>,
    /// Converse `additionalModelResponseFieldPaths`.
    /// Chat, Messages, Responses, and Gemini drop.
    pub response_field_paths: Vec<String>,
    /// Converse `additionalModelRequestFields`.
    /// Chat, Messages, Responses, and Gemini drop.
    pub additional_request_fields: Option<serde_json::Value>,
    /// Converse `promptVariables`.
    /// Chat, Messages, Responses, and Gemini drop.
    pub prompt_variables: Option<serde_json::Value>,
    /// Converse `guardrailConfig`.
    /// Chat, Messages, Responses, and Gemini drop.
    pub guardrail: Option<serde_json::Value>,
    /// Messages request `container` (string id or object). Null and other
    /// types decode as absent. Chat, Responses, Gemini, and Converse drop.
    pub container: Option<serde_json::Value>,
    /// Messages request `context_management` object. Chat, Responses,
    /// Gemini, and Converse drop.
    pub context_management: Option<serde_json::Value>,
    /// Messages request `mcp_servers` array. Chat, Responses, Gemini,
    /// and Converse drop.
    pub mcp_servers: Option<serde_json::Value>,
    /// Gemini `generationConfig.mediaResolution`
    /// (`MEDIA_RESOLUTION_LOW`, `MEDIA_RESOLUTION_MEDIUM`,
    /// `MEDIA_RESOLUTION_HIGH`). Chat, Messages, Responses, and
    /// Converse drop.
    pub media_resolution: Option<String>,
    /// Gemini `generationConfig.imageConfig` (`aspectRatio`, `imageSize`).
    /// Chat, Messages, Responses, and Converse drop.
    pub image_config: Option<serde_json::Value>,
    /// Gemini `generationConfig.audioTranscriptionConfig`.
    /// Chat, Messages, Responses, and Converse drop.
    pub audio_transcription_config: Option<serde_json::Value>,
    /// Gemini `generationConfig.translationConfig`.
    /// Chat, Messages, Responses, and Converse drop.
    pub translation_config: Option<serde_json::Value>,
    /// Gemini `generationConfig.enableAffectiveDialog`.
    /// Chat, Messages, Responses, and Converse drop.
    pub affective_dialog: Option<bool>,
    /// Gemini `generationConfig.enableEnhancedCivicAnswers`.
    /// Chat, Messages, Responses, and Converse drop.
    pub enhanced_civic_answers: Option<bool>,
    /// Gemini `generationConfig.speechConfig` when it uses
    /// `multiSpeakerVoiceConfig`. A single `voiceConfig` stays on
    /// `audio_voice`. Chat, Messages, Responses, and Converse drop.
    pub multi_speaker_speech: Option<serde_json::Value>,
    /// Gemini request-root `cachedContent` (`cachedContents/{id}`).
    /// Chat, Messages, Responses, and Converse drop.
    pub cached_content: Option<String>,
    /// Gemini request-root `safetySettings` array.
    /// Chat, Messages, Responses, and Converse drop.
    pub safety_settings: Option<serde_json::Value>,
    /// Gemini request-root `labels` object.
    /// Chat, Messages, Responses, and Converse drop.
    pub request_labels: Option<serde_json::Value>,
    /// Responses request `truncation` (`auto`, `disabled`, or a vendor
    /// token). Empty is absent. Chat, Messages, Gemini, and Converse drop.
    pub truncation: Option<String>,
    /// Responses request `max_tool_calls`. `0` is a real cap.
    /// Chat, Messages, Gemini, and Converse drop.
    pub max_tool_calls: Option<u32>,
    /// Responses request `background`. `false` is explicit foreground and
    /// is preserved. Chat, Messages, Gemini, and Converse drop.
    pub background: Option<bool>,
    /// Responses request `conversation`: a non-empty string id or an
    /// object. Numbers, arrays, null, and empty strings are absent.
    /// Chat, Messages, Gemini, and Converse drop.
    pub conversation: Option<serde_json::Value>,
    /// Responses request `context_management` array (compaction).
    /// Distinct from the Messages `context_management` object.
    /// Chat, Messages, Gemini, and Converse drop.
    pub responses_context_management: Option<serde_json::Value>,
    /// Messages request `thinking` when `type` is `adaptive` or
    /// `between_tools`, including `display`. `enabled` and `disabled`
    /// stay on `include_thoughts`. Chat, Responses, Gemini, and
    /// Converse drop.
    pub messages_thinking: Option<serde_json::Value>,
}

impl IrSampling {
    /// Build sampling by mutating defaults.
    ///
    /// External crates cannot use struct literals on this type.
    pub fn patch(update: impl FnOnce(&mut Self)) -> Self {
        let mut sampling = Self::default();
        update(&mut sampling);
        sampling
    }
}

#[derive(Clone, Debug, Default, Eq, PartialEq)]
#[non_exhaustive]
pub enum IrToolChoice {
    #[default]
    Auto,
    None,
    Required,
    Named(String),
}

#[derive(Clone, Debug, Default, Eq, PartialEq)]
#[non_exhaustive]
pub struct IrCache {
    pub enabled: bool,
    /// "5m" or "1h" when the target dialect has a TTL slot.
    pub retention: Option<String>,
    /// Skip `cache_control` when [`estimate_prompt_tokens`] is below this floor.
    /// `None` or `0` means no floor.
    pub min_cacheable_tokens: Option<u32>,
}

impl IrCache {
    /// Enabled cache with no TTL and no token floor.
    #[must_use]
    pub fn enabled() -> Self {
        Self {
            enabled: true,
            ..Self::default()
        }
    }

    /// Set Messages-style TTL (`5m` / `1h`).
    ///
    /// Pass a string slice (`"5m"`). Do not write `retention.into()`.
    #[must_use]
    pub fn with_retention(mut self, retention: impl AsRef<str>) -> Self {
        self.retention = Some(retention.as_ref().to_owned());
        self
    }

    /// Skip `cache_control` below this estimated prompt-token floor.
    #[must_use]
    pub fn with_min_cacheable_tokens(mut self, tokens: u32) -> Self {
        self.min_cacheable_tokens = Some(tokens);
        self
    }
}

/// One conversation turn.
///
/// `System`, `Developer`, and `Assistant` name every field.
/// `#[non_exhaustive]` does not let an outside crate skip one.
/// A 0.11.1 literal that omits the fields below does not compile.
///
/// ```
/// use wiremux::{IrItem, IrPart};
/// let system = IrItem::System {
///     text: "You are concise.".into(),
///     prompt_cache_breakpoint: None,
///     content_parts: vec![],
/// };
/// let developer = IrItem::Developer {
///     text: "Prefer short answers.".into(),
///     prompt_cache_breakpoint: None,
///     content_parts: vec![],
/// };
/// let assistant = IrItem::Assistant {
///     parts: vec![IrPart::Text("Hi".into())],
///     phase: None,
/// };
/// let image = IrPart::ImageUrl {
///     url: "https://example.com/a.png".into(),
///     detail: None,
///     bucket_owner: None,
///     file_id: None,
/// };
/// assert!(matches!(system, IrItem::System { prompt_cache_breakpoint: None, .. }));
/// assert!(matches!(
///     developer,
///     IrItem::Developer { content_parts, .. } if content_parts.is_empty()
/// ));
/// assert!(matches!(assistant, IrItem::Assistant { phase: None, .. }));
/// assert!(matches!(
///     image,
///     IrPart::ImageUrl { file_id: None, bucket_owner: None, .. }
/// ));
/// ```
#[derive(Clone, Debug, PartialEq)]
#[non_exhaustive]
pub enum IrItem {
    System {
        text: String,
        /// Chat system `prompt_cache_breakpoint` mode.
        /// Set when that role is one text part carrying the marker.
        /// Other wires keep `text` and record that the marker has no slot.
        prompt_cache_breakpoint: Option<String>,
        /// Ordered parts when a multi-part role must keep a breakpoint.
        /// Empty means `text` and `prompt_cache_breakpoint` are the whole role.
        /// Messages, Gemini, and Converse send the text parts from this
        /// list and drop image, document, audio, and raw parts.
        content_parts: Vec<IrPart>,
    },
    /// Converse system `cachePoint`. Other wires drop it.
    /// It stays between the system texts that surround it.
    SystemCache {
        raw: serde_json::Value,
    },
    /// Converse system `guardContent`. Other wires drop it.
    /// Once present, the guardrail assesses only these blocks.
    SystemGuard {
        raw: serde_json::Value,
    },
    /// Chat Completions `developer` degrades to this on Messages.
    Developer {
        text: String,
        /// Chat developer `prompt_cache_breakpoint` mode.
        /// Set when that role is one text part carrying the marker.
        /// Other wires keep `text` and record that the marker has no slot.
        prompt_cache_breakpoint: Option<String>,
        /// Ordered parts when a multi-part role must keep a breakpoint.
        /// Empty means `text` and `prompt_cache_breakpoint` are the whole role.
        /// Messages, Gemini, and Converse send the text parts from this
        /// list and drop image, document, audio, and raw parts.
        content_parts: Vec<IrPart>,
    },
    User {
        parts: Vec<IrPart>,
    },
    Assistant {
        parts: Vec<IrPart>,
        /// Responses assistant `phase` (`commentary` or `final_answer`).
        /// A later Responses turn must send it again. Other wires drop it.
        /// User messages never carry it.
        phase: Option<String>,
    },
    FunctionCall {
        call_id: String,
        name: String,
        arguments: String,
        /// Gemini `thoughtSignature` on the same functionCall part.
        thought_signature: Option<String>,
    },
    /// Chat `type: custom` and Responses `custom_tool_call`.
    /// Messages, Converse, and Gemini have no custom-tool frame, so
    /// those encoders reuse the function tool and keep this name and input.
    /// `responses_item` is the original Responses object so same-wire
    /// keeps `id`, `namespace`, `status`, `created_by`, and `caller`.
    CustomToolCall {
        call_id: String,
        name: String,
        input: String,
        responses_item: Option<serde_json::Value>,
    },
    FunctionOutput {
        call_id: String,
        /// Joined text. Images and other blocks live in `parts`.
        output: String,
        parts: Vec<IrPart>,
        is_error: bool,
    },
    Reasoning {
        encrypted: Option<String>,
        summary: Option<String>,
        raw: Option<serde_json::Value>,
    },
    HostedToolCall {
        kind: String,
        raw: serde_json::Value,
    },
    Unknown {
        type_name: String,
        raw: serde_json::Value,
    },
}

#[derive(Clone, Debug, PartialEq)]
#[non_exhaustive]
pub enum IrPart {
    Text(String),
    /// Chat `image_url`. `detail` is `low`, `high`, or `auto`.
    /// `bucket_owner` is the Converse S3 account id.
    /// `file_id` is the Responses `input_image.file_id`.
    /// Chat, Messages, Converse, and Gemini have no slot for it.
    /// Other dest wires keep the URL and drop `detail` and `bucket_owner`.
    ImageUrl {
        url: String,
        detail: Option<String>,
        bucket_owner: Option<String>,
        file_id: Option<String>,
    },
    ImageBase64 {
        media_type: String,
        data: String,
    },
    /// Messages replay needs a nonempty signature. Responses remaps
    /// signed thinking to a reasoning item. Unsigned thinking is dropped
    /// on Messages, Responses, and Chat Completions.
    Thinking {
        text: String,
        signature: Option<String>,
    },
    /// Dialect-native block (Anthropic `redacted_thinking`).
    Raw {
        type_name: String,
        raw: serde_json::Value,
    },
    /// Messages `document`, Chat/Responses `file`/`input_file`,
    /// Gemini PDF `inlineData`/`fileData`, Converse `document`.
    /// `citations_enabled` and `context` are kept on Messages and Converse.
    /// Chat and Gemini drop them.
    Document {
        source: IrDocumentSource,
        media_type: String,
        name: Option<String>,
        /// Messages `citations.enabled`. `None` omits the object.
        citations_enabled: Option<bool>,
        /// Messages document `context`.
        context: Option<String>,
    },
    /// Chat `input_audio` and Gemini `inlineData` with `audio/*`.
    Audio {
        data: String,
        format: String,
    },
    /// Chat and Responses `prompt_cache_breakpoint` on `inner`.
    /// Other wires keep `inner` and record that the marker has no slot.
    /// `mode` is the breakpoint mode. The API documents `explicit`.
    PromptCacheBreakpoint {
        mode: String,
        inner: Box<IrPart>,
    },
}

/// Where a document payload lives.
#[derive(Clone, Debug, PartialEq)]
#[non_exhaustive]
pub enum IrDocumentSource {
    Base64(String),
    /// Messages PlainTextSource `data`. The string is the document text, not base64.
    Text(String),
    Url(String),
    /// Converse `s3Location`. `bucket_owner` is the AWS account id when the
    /// request included `bucketOwner`.
    S3 {
        uri: String,
        bucket_owner: Option<String>,
    },
    FileId(String),
}

#[derive(Clone, Debug, PartialEq)]
#[non_exhaustive]
pub enum IrTool {
    Function {
        name: String,
        description: String,
        parameters: serde_json::Value,
        /// Chat Completions and Responses `strict`. Other dests drop when `Some`.
        strict: Option<bool>,
    },
    Namespace {
        name: String,
        raw: serde_json::Value,
    },
    Hosted {
        kind: String,
        raw: serde_json::Value,
    },
    Unknown {
        type_name: String,
        raw: serde_json::Value,
    },
    /// Converse `toolConfig.tools` cachePoint. Other wires drop it.
    /// It stays between the tool specs that surround it.
    CachePoint { raw: serde_json::Value },
}

#[derive(Clone, Debug, PartialEq)]
#[non_exhaustive]
pub enum IrStreamEvent {
    TextDelta {
        text: String,
    },
    /// Dest Chat `delta.refusal` / `message.refusal`, dest Responses
    /// `response.refusal.delta` / output content `{ "type": "refusal" }`,
    /// dest Messages complete `stop_details.explanation`, dest Messages
    /// STREAM `message_delta.delta.stop_details.explanation`, and dest
    /// Gemini `candidates[].finishMessage`.
    RefusalDelta {
        text: String,
    },
    ReasoningDelta {
        text: String,
    },
    ReasoningSignature {
        signature: String,
    },
    ToolCallStart {
        id: String,
        name: String,
        /// Gemini `thoughtSignature` bound to this function call.
        thought_signature: Option<String>,
        /// Parallel tool-call slot. Chat Completions `tool_calls[].index`.
        /// Other dialects use a block/output index or 0.
        index: u32,
    },
    ToolCallArgDelta {
        delta: String,
        /// Same slot as the matching [`Self::ToolCallStart`].
        index: u32,
    },
    ToolCallEnd,
    /// Dest Chat `message.annotations` url_citation and dest Responses
    /// `response.output_text.annotation.added`.
    AnnotationAdded {
        annotation: serde_json::Value,
    },
    /// Dest Gemini `candidates[].groundingMetadata.searchEntryPoint.renderedContent`.
    /// HTML a Grounding with Google Search client must display.
    /// Other wires omit it. `webSearchQueries` stays dropped.
    SearchEntryPoint {
        rendered_content: String,
    },
    /// Dest Chat `message.audio.data` and dest Responses `response.audio.delta`.
    AudioDelta {
        data: String,
    },
    /// Generated image bytes. Dest Gemini `inlineData` with `image/*`,
    /// dest Chat `image_url` data URL, dest Messages image block,
    /// dest Responses `output_image`, and dest Converse `image`.
    ImageDelta {
        media_type: String,
        data: String,
    },
    /// Dest Chat `message.audio.transcript` and dest Responses
    /// `response.audio.transcript.delta`.
    AudioTranscriptDelta {
        text: String,
    },
    /// Dest Chat `tool_calls[].type=custom` and dest Responses
    /// `custom_tool_call` output item.
    CustomToolCallStart {
        id: String,
        name: String,
        index: u32,
    },
    /// Dest Chat custom tool `custom.input` and dest Responses
    /// `response.custom_tool_call_input.delta`.
    CustomToolCallInputDelta {
        delta: String,
        index: u32,
    },
    /// Dest Chat STREAM `choices[].logprobs.content` and dest Responses
    /// `response.output_text.delta.logprobs`. Dest Gemini
    /// `candidates[].logprobsResult` is one list, so encode appends
    /// `refusal` tokens there. Dest Responses logprobs is one array and
    /// gets the same append.
    /// `refusal` is Chat `logprobs.refusal`. Other wires do not have that key.
    Logprobs {
        content: serde_json::Value,
        /// Chat `logprobs.refusal`. Other wires do not have that key.
        refusal: Option<serde_json::Value>,
    },
    /// Dest Chat `created` and dest Responses `created_at` (unix seconds).
    Created {
        unix: i64,
    },
    /// Dest Chat `service_tier`, dest Responses `service_tier`, and dest
    /// Messages `usage.service_tier`.
    ServiceTier {
        tier: String,
    },
    /// Dest Chat `metadata` and dest Responses `metadata` string map.
    Metadata {
        metadata: BTreeMap<String, String>,
    },
    /// Dest Chat `moderation.input` / `moderation.output` (Chat-shaped
    /// `moderation_results` or `error`) and dest Responses the same keys.
    Moderation {
        input: Option<serde_json::Value>,
        output: Option<serde_json::Value>,
    },
    /// Messages response `diagnostics.cache_miss_reason`. Other wires omit it.
    Diagnostics {
        cache_miss_reason: serde_json::Value,
    },
    /// Messages response `container`. Other wires omit it.
    Container {
        value: serde_json::Value,
    },
    /// Messages response `context_management`. Other wires omit it.
    ContextManagement {
        value: serde_json::Value,
    },
    /// Messages response `stop_sequence`. Other wires omit it.
    StopSequence {
        text: String,
    },
    /// Exclusive buckets: prompt excludes cache
    /// read, completion excludes reasoning. Encoders re-inflate inclusive
    /// wire totals for Chat and Responses.
    /// `audio_tokens` is dest Chat `prompt_tokens_details.audio_tokens`
    /// and dest Gemini `promptTokensDetails` modality AUDIO. It is a
    /// subset of prompt, not subtracted from `prompt_tokens`. Dest Chat
    /// has no `image_tokens`; Gemini IMAGE details are an official Drop.
    /// `completion_audio_tokens` is dest Chat
    /// `completion_tokens_details.audio_tokens` and dest Gemini
    /// `candidatesTokensDetails` modality AUDIO. It is a subset of
    /// completion, not subtracted from `completion_tokens`.
    /// Messages response `usage.inference_geo`. Other wires omit it.
    Usage {
        prompt_tokens: u32,
        completion_tokens: u32,
        cache_read_tokens: u32,
        cache_write_tokens: u32,
        reasoning_tokens: u32,
        audio_tokens: u32,
        completion_audio_tokens: u32,
        /// Messages response `usage.inference_geo`. Other wires omit it.
        inference_geo: Option<String>,
    },
    /// Mapped stop reason. `vendor` is the original Gemini token when the
    /// mapped word is not that token (`MALFORMED_FUNCTION_CALL`, `SAFETY`).
    /// Other wires leave `vendor` empty. Unknown Gemini `finishReason`
    /// values stay in `reason` and are not rewritten to `stop`.
    FinishReason {
        reason: String,
        vendor: Option<String>,
    },
    Protocol {
        item_type: String,
        payload: serde_json::Value,
    },
    Unknown {
        event: String,
        raw: serde_json::Value,
    },
    Done,
}

#[derive(Clone, Debug, Default, Eq, PartialEq)]
#[non_exhaustive]
pub struct LossReport {
    pub events: Vec<LossEvent>,
}

impl LossReport {
    /// Append a loss event.
    pub fn record(
        &mut self,
        path: impl Into<String>,
        action: LossAction,
        detail: impl Into<String>,
    ) {
        self.events.push(LossEvent {
            path: path.into(),
            action,
            detail: detail.into(),
        });
    }

    /// Events whose action is not [`LossAction::Preserve`], in record order.
    #[must_use]
    pub fn lossy(&self) -> Vec<LossEvent> {
        self.events
            .iter()
            .filter(|event| event.action != LossAction::Preserve)
            .cloned()
            .collect()
    }
}

#[derive(Clone, Debug, Eq, PartialEq)]
#[non_exhaustive]
pub struct LossEvent {
    pub path: String,
    pub action: LossAction,
    pub detail: String,
}

impl std::fmt::Display for LossEvent {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        let action = match self.action {
            LossAction::Preserve => "preserve",
            LossAction::Degrade => "degrade",
            LossAction::Drop => "drop",
            LossAction::HardError => "harderror",
        };
        write!(f, "{action} {}: {}", self.path, self.detail)
    }
}

#[derive(Clone, Copy, Debug, Eq, PartialEq)]
#[non_exhaustive]
pub enum LossAction {
    Preserve,
    Degrade,
    Drop,
    HardError,
}

/// Estimate prompt tokens as `chars / 4` for the Messages cache floor.
///
/// Counts system and developer text, user and assistant text, signed
/// thinking text, image bytes, document text, and document base64.
/// An image URL, a document URL, and a document file id count as at
/// least 4096 characters (1024 tokens) so a short handle still meets
/// the shipped Messages floor. A longer handle counts its own length.
/// Titles, context, function-call names and arguments, custom-tool
/// names and inputs, function-output text and parts, reasoning text
/// that becomes a thinking block, and function-tool names,
/// descriptions, and parameters also count.
///
/// Unsigned thinking is not replayed, so that text is not counted.
/// Whitespace-only text parts are omitted. Audio is dropped. A custom
/// tool's `responses_item` is the same input again, so it is not
/// counted. A reasoning or thinking signature is not prompt text.
/// Image detail is dropped. Hosted items and unknown raw JSON stay out
/// so a short prompt is not treated as long. Inline image and document
/// bytes that Messages rewrites from a raw part are counted.
#[must_use]
pub fn estimate_prompt_tokens(req: &IrRequest) -> u32 {
    crate::map::messages_cache_floor_tokens(req)
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn ir_request_holds_system_user_and_function_tool() {
        let req = IrRequest {
            model: "gpt-4".into(),
            items: vec![
                IrItem::System {
                    text: "You are helpful.".into(),
                    prompt_cache_breakpoint: None,
                    content_parts: vec![],
                },
                IrItem::User {
                    parts: vec![IrPart::Text("Hi".into())],
                },
            ],
            tools: vec![IrTool::Function {
                name: "lookup".into(),
                description: "Look up a term.".into(),
                parameters: serde_json::json!({"type": "object"}),
                strict: None,
            }],
            sampling: IrSampling::default(),
        };

        assert_eq!(req.model, "gpt-4");
        assert_eq!(req.items.len(), 2);
        assert!(matches!(req.items[0], IrItem::System { .. }));
        assert!(matches!(
            &req.items[1],
            IrItem::User { parts } if parts == &[IrPart::Text("Hi".into())]
        ));
        assert_eq!(req.tools.len(), 1);
        assert!(matches!(
            &req.tools[0],
            IrTool::Function { name, description, .. }
                if name == "lookup" && description == "Look up a term."
        ));
        assert!(matches!(req.sampling.tool_choice, IrToolChoice::Auto));
    }

    #[test]
    fn loss_report_records_all_actions() {
        let mut report = LossReport::default();
        report.record("items[0]", LossAction::Preserve, "kept as-is");
        report.record("items[1]", LossAction::Degrade, "developer to system");
        report.record("sampling.store", LossAction::Drop, "no slot");
        report.record("tools[0]", LossAction::HardError, "namespace");

        assert_eq!(
            report.events,
            [
                LossEvent {
                    path: "items[0]".into(),
                    action: LossAction::Preserve,
                    detail: "kept as-is".into(),
                },
                LossEvent {
                    path: "items[1]".into(),
                    action: LossAction::Degrade,
                    detail: "developer to system".into(),
                },
                LossEvent {
                    path: "sampling.store".into(),
                    action: LossAction::Drop,
                    detail: "no slot".into(),
                },
                LossEvent {
                    path: "tools[0]".into(),
                    action: LossAction::HardError,
                    detail: "namespace".into(),
                },
            ]
        );
    }

    #[test]
    fn ir_tool_namespace_is_first_class() {
        let tool = IrTool::Namespace {
            name: "apply_patch".into(),
            raw: serde_json::json!({"type": "namespace"}),
        };
        assert!(matches!(
            &tool,
            IrTool::Namespace { name, .. } if name == "apply_patch"
        ));
        assert!(!matches!(tool, IrTool::Function { .. }));
    }

    #[test]
    fn ir_item_developer_is_distinct_from_system() {
        let system = IrItem::System {
            text: "rules".into(),
            prompt_cache_breakpoint: None,
            content_parts: vec![],
        };
        let developer = IrItem::Developer {
            text: "rules".into(),
            prompt_cache_breakpoint: None,
            content_parts: vec![],
        };
        assert_ne!(system, developer);
        assert!(matches!(system, IrItem::System { .. }));
        assert!(matches!(developer, IrItem::Developer { .. }));
    }

    #[test]
    fn estimate_prompt_tokens_counts_developer_text() {
        let req = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::Developer {
                text: "x".repeat(5000),
                prompt_cache_breakpoint: None,
                content_parts: vec![],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&req) >= 1024,
            "5000 developer chars must meet a 1024-token floor"
        );
    }

    #[test]
    fn estimate_prompt_tokens_counts_function_output() {
        let req = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::FunctionOutput {
                call_id: "c1".into(),
                output: "x".repeat(5000),
                parts: Vec::new(),
                is_error: false,
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&req) >= 1024,
            "5000 tool-result chars must meet a 1024-token floor"
        );
    }

    #[test]
    fn estimate_prompt_tokens_counts_signed_thinking_not_unsigned() {
        let signed = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::Assistant {
                phase: None,
                parts: vec![IrPart::Thinking {
                    text: "x".repeat(5000),
                    signature: Some("sig".into()),
                }],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&signed) >= 1024,
            "5000 signed thinking chars must meet a 1024-token floor"
        );

        let unsigned = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::User {
                parts: vec![
                    IrPart::Text("hi".into()),
                    IrPart::Thinking {
                        text: "x".repeat(5000),
                        signature: None,
                    },
                ],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&unsigned) < 1024,
            "unsigned thinking is not replayed and must stay under the floor"
        );

        let blank_signature = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::Assistant {
                phase: None,
                parts: vec![IrPart::Thinking {
                    text: "x".repeat(5000),
                    signature: Some(String::new()),
                }],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&blank_signature) < 1024,
            "an empty thinking signature is unsigned and must stay under the floor"
        );

        let signature_only = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::Assistant {
                phase: None,
                parts: vec![IrPart::Thinking {
                    text: "hi".into(),
                    signature: Some("y".repeat(5000)),
                }],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&signature_only) < 1024,
            "a thinking signature is not prompt text"
        );
    }

    #[test]
    fn estimate_prompt_tokens_counts_images_documents_and_tool_result_parts() {
        let long = "x".repeat(5000);
        let image = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::User {
                parts: vec![IrPart::ImageBase64 {
                    media_type: "image/png".into(),
                    data: long.clone(),
                }],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&image) >= 1024,
            "5000 image bytes must meet a 1024-token floor"
        );

        let image_url = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::User {
                parts: vec![IrPart::ImageUrl {
                    url: long.clone(),
                    detail: Some("y".repeat(5000)),
                    bucket_owner: None,
                    file_id: None,
                }],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&image_url) >= 1024,
            "a long image URL must meet a 1024-token floor"
        );
        let detail_only = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::User {
                parts: vec![IrPart::ImageUrl {
                    url: "https://cdn.example/a.png".into(),
                    detail: Some(long.clone()),
                    bucket_owner: None,
                    file_id: None,
                }],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&detail_only) >= 1024,
            "a normal image URL meets a 1024-token floor"
        );
        let url_only = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::User {
                parts: vec![IrPart::ImageUrl {
                    url: "https://cdn.example/a.png".into(),
                    detail: None,
                    bucket_owner: None,
                    file_id: None,
                }],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert_eq!(
            estimate_prompt_tokens(&detail_only),
            estimate_prompt_tokens(&url_only),
            "image detail is dropped"
        );
        let file_id = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::User {
                parts: vec![IrPart::Document {
                    source: IrDocumentSource::FileId("file_abc".into()),
                    media_type: "application/pdf".into(),
                    name: None,
                    citations_enabled: None,
                    context: None,
                }],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&file_id) >= 1024,
            "a file id meets a 1024-token floor"
        );
        let short_base64 = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::User {
                parts: vec![IrPart::Document {
                    source: IrDocumentSource::Base64("0123456789".into()),
                    media_type: "application/pdf".into(),
                    name: None,
                    citations_enabled: None,
                    context: None,
                }],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&short_base64) < 1024,
            "short document base64 stays under the floor"
        );

        let document_text = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::User {
                parts: vec![IrPart::Document {
                    source: IrDocumentSource::Text(long.clone()),
                    media_type: "text/plain".into(),
                    name: None,
                    citations_enabled: None,
                    context: None,
                }],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&document_text) >= 1024,
            "5000 document text chars must meet a 1024-token floor"
        );

        let document_base64 = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::User {
                parts: vec![IrPart::Document {
                    source: IrDocumentSource::Base64(long.clone()),
                    media_type: "application/pdf".into(),
                    name: None,
                    citations_enabled: None,
                    context: None,
                }],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&document_base64) >= 1024,
            "5000 document base64 chars must meet a 1024-token floor"
        );

        let document_url = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::User {
                parts: vec![IrPart::Document {
                    source: IrDocumentSource::Url(long.clone()),
                    media_type: "application/pdf".into(),
                    name: None,
                    citations_enabled: None,
                    context: None,
                }],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&document_url) >= 1024,
            "a long document URL must meet a 1024-token floor"
        );

        let document_context = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::User {
                parts: vec![IrPart::Document {
                    source: IrDocumentSource::FileId("file-short".into()),
                    media_type: "text/plain".into(),
                    name: None,
                    citations_enabled: None,
                    context: Some(long.clone()),
                }],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&document_context) >= 1024,
            "document context Messages writes must meet a 1024-token floor"
        );

        let tool_image = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::FunctionOutput {
                call_id: "c1".into(),
                output: String::new(),
                parts: vec![IrPart::ImageBase64 {
                    media_type: "image/png".into(),
                    data: long.clone(),
                }],
                is_error: false,
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&tool_image) >= 1024,
            "a tool-result image must meet a 1024-token floor"
        );

        let tool_text = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::FunctionOutput {
                call_id: "c1".into(),
                output: String::new(),
                parts: vec![IrPart::Text(long.clone())],
                is_error: false,
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&tool_text) >= 1024,
            "tool-result text Messages writes must meet a 1024-token floor"
        );

        let raw_image = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::User {
                parts: vec![IrPart::Raw {
                    type_name: "inline".into(),
                    raw: serde_json::json!({
                        "inlineData": {
                            "mimeType": "image/png",
                            "data": long,
                        }
                    }),
                }],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&raw_image) >= 1024,
            "inline image bytes Messages writes must meet a 1024-token floor"
        );

        let hinted_pdf = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::User {
                parts: vec![IrPart::Raw {
                    type_name: "inline".into(),
                    raw: serde_json::json!({
                        "inlineData": {
                            "mimeType": "application/pdf",
                            "data": "y".repeat(5000),
                        },
                        "mediaResolution": { "level": "media_resolution_high" }
                    }),
                }],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&hinted_pdf) >= 1024,
            "a media-hint PDF Messages writes must meet a 1024-token floor"
        );
    }

    #[test]
    fn estimate_prompt_tokens_skips_text_messages_does_not_send() {
        let long = "x".repeat(5000);
        let whitespace = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::User {
                parts: vec![IrPart::Text(" \n".repeat(2500))],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&whitespace) < 1024,
            "whitespace-only text is omitted and must stay under the floor"
        );

        let audio = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::User {
                parts: vec![IrPart::Audio {
                    data: long.clone(),
                    format: "mp3".into(),
                }],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&audio) < 1024,
            "audio has no Messages slot and must stay under the floor"
        );

        let raw_json = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::Unknown {
                type_name: "redacted_thinking".into(),
                raw: serde_json::json!({
                    "type": "redacted_thinking",
                    "data": long.clone(),
                }),
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&raw_json) < 1024,
            "unknown raw JSON must not meet the floor"
        );

        let hosted = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::HostedToolCall {
                kind: "web_search".into(),
                raw: serde_json::json!({ "query": long }),
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&hosted) < 1024,
            "hosted raw JSON must not meet the floor"
        );

        let raw_part = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::User {
                parts: vec![IrPart::Raw {
                    type_name: "redacted_thinking".into(),
                    raw: serde_json::json!({
                        "type": "redacted_thinking",
                        "data": long.clone(),
                    }),
                }],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&raw_part) < 1024,
            "a raw Messages block is not prompt text"
        );

        let raw_audio = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::User {
                parts: vec![IrPart::Raw {
                    type_name: "inline".into(),
                    raw: serde_json::json!({
                        "inlineData": {
                            "mimeType": "audio/mp3",
                            "data": long,
                        },
                        "mediaResolution": { "level": "media_resolution_high" }
                    }),
                }],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&raw_audio) < 1024,
            "audio bytes inside a raw part must stay under the floor"
        );

        let hinted_blank = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::User {
                parts: vec![IrPart::Raw {
                    type_name: "inline".into(),
                    raw: serde_json::json!({
                        "text": " \n".repeat(2500),
                        "mediaResolution": { "level": "media_resolution_high" }
                    }),
                }],
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&hinted_blank) < 1024,
            "whitespace inside a hinted raw part must stay under the floor"
        );
    }

    #[test]
    fn estimate_prompt_tokens_counts_custom_tool_input_not_responses_item() {
        let long = "x".repeat(5000);
        let counted = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::CustomToolCall {
                call_id: "c1".into(),
                name: "lookup".into(),
                input: long.clone(),
                responses_item: None,
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&counted) >= 1024,
            "5000 custom-tool input chars must meet a 1024-token floor"
        );

        let wrapper_only = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::CustomToolCall {
                call_id: "c1".into(),
                name: "lookup".into(),
                input: "{}".into(),
                responses_item: Some(serde_json::json!({ "input": long })),
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&wrapper_only) < 1024,
            "responses_item must not double-count the custom-tool input"
        );
    }

    #[test]
    fn estimate_prompt_tokens_counts_reasoning_summary_not_signature() {
        let long = "x".repeat(5000);
        let summary = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::Reasoning {
                encrypted: Some("y".repeat(5000)),
                summary: Some(long.clone()),
                raw: None,
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&summary) >= 1024,
            "5000 reasoning-summary chars must meet a 1024-token floor"
        );

        let signature_only = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::Reasoning {
                encrypted: Some(long.clone()),
                summary: None,
                raw: None,
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&signature_only) < 1024,
            "a reasoning signature must not meet the floor by itself"
        );

        let raw_thinking = IrRequest {
            model: "claude".into(),
            items: vec![IrItem::Reasoning {
                encrypted: None,
                summary: None,
                raw: Some(serde_json::json!({
                    "type": "thinking",
                    "thinking": long,
                    "signature": "y".repeat(5000),
                })),
            }],
            tools: vec![],
            sampling: IrSampling::default(),
        };
        assert!(
            estimate_prompt_tokens(&raw_thinking) >= 1024,
            "a raw thinking string must meet a 1024-token floor"
        );
    }

    #[test]
    fn new_and_retention_take_str_next_to_bytes() {
        let _owned = bytes::Bytes::from_static(b"x");
        let req = IrRequest::new("gpt-4o", vec![]).with_sampling(IrSampling::patch(|s| {
            s.cache = IrCache::enabled().with_retention("5m");
        }));
        assert_eq!(req.model, "gpt-4o");
        assert_eq!(req.sampling.cache.retention.as_deref(), Some("5m"));
        let owned = IrRequest::new(String::from("gpt-4o"), vec![]);
        assert_eq!(owned.model, "gpt-4o");
    }
}