rig_core/providers/anthropic/

completion.rs

//! Anthropic completion api implementation

use crate::completion::CompletionRequest;
use crate::providers::anthropic::streaming::StreamingCompletionResponse;
use crate::{
    OneOrMany,
    client::Provider,
    completion::{self, CompletionError, GetTokenUsage},
    http_client::HttpClientExt,
    message::{self, DocumentMediaType, DocumentSourceKind, MessageError, MimeType, Reasoning},
    one_or_many::string_or_one_or_many,
    telemetry::{ProviderResponseExt, SpanCombinator},
    wasm_compat::*,
};
use bytes::Bytes;
use serde::{Deserialize, Serialize};
use std::{convert::Infallible, str::FromStr};
use tracing::{Instrument, Level, enabled, info_span};

// ================================================================
// Anthropic Completion API
// ================================================================

/// `claude-opus-4-6` completion model
pub const CLAUDE_OPUS_4_6: &str = "claude-opus-4-6";
/// `claude-opus-4-7` completion model
pub const CLAUDE_OPUS_4_7: &str = "claude-opus-4-7";
/// `claude-opus-4-8` completion model
pub const CLAUDE_OPUS_4_8: &str = "claude-opus-4-8";
/// `claude-sonnet-4-6` completion model
pub const CLAUDE_SONNET_4_6: &str = "claude-sonnet-4-6";
/// `claude-haiku-4-5` completion model
pub const CLAUDE_HAIKU_4_5: &str = "claude-haiku-4-5";

pub const ANTHROPIC_VERSION_2023_01_01: &str = "2023-01-01";
pub const ANTHROPIC_VERSION_2023_06_01: &str = "2023-06-01";
pub const ANTHROPIC_VERSION_LATEST: &str = ANTHROPIC_VERSION_2023_06_01;
const EMPTY_RESPONSE_ERROR: &str = "Response contained no message or tool call (empty)";
pub(crate) const ANTHROPIC_RAW_CONTENT_KEY: &str = "anthropic_content";

pub trait AnthropicCompatibleProvider: Provider {
    const PROVIDER_NAME: &'static str;

    fn default_max_tokens(model: &str) -> Option<u64> {
        let _ = model;
        None
    }
}

impl AnthropicCompatibleProvider for super::client::AnthropicExt {
    const PROVIDER_NAME: &'static str = "anthropic";

    fn default_max_tokens(model: &str) -> Option<u64> {
        default_max_tokens_for_model(model)
    }
}

#[derive(Debug, Deserialize, Serialize)]
pub struct CompletionResponse {
    pub content: Vec<Content>,
    pub id: String,
    pub model: String,
    pub role: String,
    pub stop_reason: Option<String>,
    pub stop_sequence: Option<String>,
    pub usage: Usage,
}

impl ProviderResponseExt for CompletionResponse {
    type OutputMessage = Content;
    type Usage = Usage;

    fn get_response_id(&self) -> Option<String> {
        Some(self.id.to_owned())
    }

    fn get_response_model_name(&self) -> Option<String> {
        Some(self.model.to_owned())
    }

    fn get_output_messages(&self) -> Vec<Self::OutputMessage> {
        self.content.clone()
    }

    fn get_text_response(&self) -> Option<String> {
        let res = self
            .content
            .iter()
            .filter_map(|x| {
                if let Content::Text { text, .. } = x {
                    Some(text.as_str())
                } else {
                    None
                }
            })
            .collect::<String>();

        if res.is_empty() { None } else { Some(res) }
    }

    fn get_usage(&self) -> Option<Self::Usage> {
        Some(self.usage.clone())
    }
}

#[derive(Clone, Debug, Deserialize, Serialize)]
pub struct Usage {
    pub input_tokens: u64,
    pub cache_read_input_tokens: Option<u64>,
    pub cache_creation_input_tokens: Option<u64>,
    pub output_tokens: u64,
}

impl std::fmt::Display for Usage {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        write!(
            f,
            "Input tokens: {}\nCache read input tokens: {}\nCache creation input tokens: {}\nOutput tokens: {}",
            self.input_tokens,
            match self.cache_read_input_tokens {
                Some(token) => token.to_string(),
                None => "n/a".to_string(),
            },
            match self.cache_creation_input_tokens {
                Some(token) => token.to_string(),
                None => "n/a".to_string(),
            },
            self.output_tokens
        )
    }
}

impl GetTokenUsage for Usage {
    fn token_usage(&self) -> crate::completion::Usage {
        let mut usage = crate::completion::Usage::new();

        usage.input_tokens = self.input_tokens;
        usage.output_tokens = self.output_tokens;
        usage.cached_input_tokens = self.cache_read_input_tokens.unwrap_or_default();
        usage.cache_creation_input_tokens = self.cache_creation_input_tokens.unwrap_or_default();
        usage.total_tokens = self.input_tokens
            + self.cache_read_input_tokens.unwrap_or_default()
            + self.cache_creation_input_tokens.unwrap_or_default()
            + self.output_tokens;

        usage
    }
}

#[derive(Debug, Deserialize, Serialize)]
pub struct ToolDefinition {
    pub name: String,
    pub description: Option<String>,
    pub input_schema: serde_json::Value,
    /// Cache breakpoint marker. Set on the last tool in the array to cache
    /// the tools layer independently of the system prompt. Anthropic accepts
    /// up to 4 `cache_control` markers per request.
    #[serde(skip_serializing_if = "Option::is_none")]
    pub cache_control: Option<CacheControl>,
}

/// TTL for a cache control breakpoint.
///
/// The Anthropic API supports two TTL values:
/// - `"5m"` — 5 minutes (default when `ttl` is omitted)
/// - `"1h"` — 1 hour
#[derive(Debug, Deserialize, Serialize, Clone, PartialEq, Default)]
pub enum CacheTtl {
    /// 5-minute TTL (default).
    #[default]
    #[serde(rename = "5m")]
    FiveMinutes,
    /// 1-hour TTL.
    #[serde(rename = "1h")]
    OneHour,
}

/// Cache control directive for Anthropic prompt caching.
///
/// Serialises to `{"type":"ephemeral"}` (default TTL) or
/// `{"type":"ephemeral","ttl":"1h"}` (extended TTL).
#[derive(Debug, Deserialize, Serialize, Clone, PartialEq)]
#[serde(tag = "type", rename_all = "snake_case")]
pub enum CacheControl {
    Ephemeral {
        /// Optional TTL. Defaults to `"5m"` when omitted.
        #[serde(skip_serializing_if = "Option::is_none")]
        ttl: Option<CacheTtl>,
    },
}

impl CacheControl {
    /// Create a cache control with the default 5-minute TTL.
    pub fn ephemeral() -> Self {
        Self::Ephemeral { ttl: None }
    }

    /// Create a cache control with a 1-hour TTL.
    pub fn ephemeral_1h() -> Self {
        Self::Ephemeral {
            ttl: Some(CacheTtl::OneHour),
        }
    }
}

/// System message content block with optional cache control
#[derive(Debug, Deserialize, Serialize, Clone, PartialEq)]
#[serde(tag = "type", rename_all = "snake_case")]
pub enum SystemContent {
    Text {
        text: String,
        #[serde(skip_serializing_if = "Option::is_none")]
        cache_control: Option<CacheControl>,
    },
}

impl TryFrom<CompletionResponse> for completion::CompletionResponse<CompletionResponse> {
    type Error = CompletionError;

    fn try_from(response: CompletionResponse) -> Result<Self, Self::Error> {
        let content = response
            .content
            .iter()
            .map(|content| content.clone().try_into())
            .collect::<Result<Vec<_>, _>>()?;

        let choice = if content.is_empty() {
            // Anthropic documents empty `end_turn` responses after tool-result round trips.
            // The generic completion response still requires at least one assistant item, so
            // normalize that terminal no-op into the same empty-text sentinel used by streaming.
            if response.stop_reason.as_deref() == Some("end_turn") {
                OneOrMany::one(completion::AssistantContent::text(""))
            } else {
                return Err(CompletionError::ResponseError(
                    EMPTY_RESPONSE_ERROR.to_owned(),
                ));
            }
        } else {
            OneOrMany::many(content)
                .map_err(|_| CompletionError::ResponseError(EMPTY_RESPONSE_ERROR.to_owned()))?
        };

        let usage = completion::Usage {
            input_tokens: response.usage.input_tokens,
            output_tokens: response.usage.output_tokens,
            total_tokens: response.usage.input_tokens
                + response.usage.cache_read_input_tokens.unwrap_or(0)
                + response.usage.cache_creation_input_tokens.unwrap_or(0)
                + response.usage.output_tokens,
            cached_input_tokens: response.usage.cache_read_input_tokens.unwrap_or(0),
            cache_creation_input_tokens: response.usage.cache_creation_input_tokens.unwrap_or(0),
            tool_use_prompt_tokens: 0,
            reasoning_tokens: 0,
        };

        Ok(completion::CompletionResponse {
            choice,
            usage,
            raw_response: response,
            message_id: None,
        })
    }
}

#[derive(Debug, Deserialize, Serialize, Clone, PartialEq)]
pub struct Message {
    pub role: Role,
    #[serde(deserialize_with = "string_or_one_or_many")]
    pub content: OneOrMany<Content>,
}

#[derive(Debug, Deserialize, Serialize, Clone, PartialEq)]
#[serde(rename_all = "lowercase")]
pub enum Role {
    User,
    Assistant,
    System,
}

#[derive(Debug, Deserialize, Serialize, Clone, PartialEq)]
#[serde(tag = "type", rename_all = "snake_case")]
pub enum Content {
    Text {
        text: String,
        /// Citations returned by Claude pointing back into the source documents.
        /// Empty (and skipped during serialization) on request-side blocks.
        #[serde(default, skip_serializing_if = "Vec::is_empty")]
        citations: Vec<Citation>,
        #[serde(skip_serializing_if = "Option::is_none")]
        cache_control: Option<CacheControl>,
    },
    Image {
        source: ImageSource,
        #[serde(skip_serializing_if = "Option::is_none")]
        cache_control: Option<CacheControl>,
    },
    ToolUse {
        id: String,
        name: String,
        input: serde_json::Value,
    },
    ServerToolUse {
        id: String,
        name: String,
        #[serde(default)]
        input: serde_json::Value,
    },
    WebSearchToolResult {
        tool_use_id: String,
        content: serde_json::Value,
    },
    ToolResult {
        tool_use_id: String,
        #[serde(deserialize_with = "string_or_one_or_many")]
        content: OneOrMany<ToolResultContent>,
        #[serde(skip_serializing_if = "Option::is_none")]
        is_error: Option<bool>,
        #[serde(skip_serializing_if = "Option::is_none")]
        cache_control: Option<CacheControl>,
    },
    Document {
        source: DocumentSource,
        /// Optional document title, passed to the model but not citable.
        #[serde(default, skip_serializing_if = "Option::is_none")]
        title: Option<String>,
        /// Optional document context (e.g. metadata), passed to the model but
        /// not citable. Useful for storing additional information about the
        /// document that should not appear in citation `cited_text`.
        #[serde(default, skip_serializing_if = "Option::is_none")]
        context: Option<String>,
        /// Configuration for enabling citations on this document. When `enabled`
        /// is true, Claude returns citation metadata on response text blocks
        /// pointing back into this document's content.
        #[serde(default, skip_serializing_if = "Option::is_none")]
        citations: Option<CitationsConfig>,
        #[serde(skip_serializing_if = "Option::is_none")]
        cache_control: Option<CacheControl>,
    },
    Thinking {
        thinking: String,
        #[serde(skip_serializing_if = "Option::is_none")]
        signature: Option<String>,
    },
    RedactedThinking {
        data: String,
    },
}

impl FromStr for Content {
    type Err = Infallible;

    fn from_str(s: &str) -> Result<Self, Self::Err> {
        Ok(Content::Text {
            text: s.to_owned(),
            citations: Vec::new(),
            cache_control: None,
        })
    }
}

/// Configuration for enabling citations on a document content block.
///
/// When enabled, Claude returns citation metadata on response text blocks,
/// allowing applications to track where each piece of information in the
/// response came from. See the [Anthropic citations documentation][docs] for
/// details on the request/response shapes.
///
/// Citations must be enabled on **all or none** of the documents in a request —
/// the API returns an error if the setting is mixed.
///
/// [docs]: https://docs.anthropic.com/en/docs/build-with-claude/citations
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
pub struct CitationsConfig {
    /// Whether citation tracking is enabled for this document.
    pub enabled: bool,
}

/// A citation returned by Claude pointing back to source text.
///
/// The variant determines the locator shape, which depends on the source type:
///
/// - [`Citation::CharLocation`] — for plain text documents; character indices
///   are 0-indexed with an exclusive end.
/// - [`Citation::PageLocation`] — for PDF documents; page numbers are 1-indexed
///   with an exclusive end.
/// - [`Citation::ContentBlockLocation`] — for custom-content documents; block
///   indices are 0-indexed with an exclusive end.
/// - [`Citation::SearchResultLocation`] — for user-provided search-result
///   content blocks.
/// - [`Citation::WebSearchResultLocation`] — for Anthropic's server-side web
///   search tool results.
/// - [`Citation::Unknown`] — a forward-compatible fallback preserving raw
///   citation JSON for citation types this crate does not yet model.
///
/// See the [Anthropic citations documentation][docs] for the exact wire format.
///
/// [docs]: https://docs.anthropic.com/en/docs/build-with-claude/citations
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum Citation {
    /// A citation locating a character span in a plain text document.
    CharLocation {
        /// The exact text being cited. Not counted toward output tokens.
        cited_text: String,
        /// 0-indexed position of the source document in the request's document list.
        document_index: usize,
        /// Optional title of the source document, echoed back from the request.
        document_title: Option<String>,
        /// 0-indexed character offset where the cited span begins.
        start_char_index: usize,
        /// Character offset where the cited span ends (exclusive).
        end_char_index: usize,
    },
    /// A citation locating a page range in a PDF document.
    PageLocation {
        /// The exact text being cited. Not counted toward output tokens.
        cited_text: String,
        /// 0-indexed position of the source document in the request's document list.
        document_index: usize,
        /// Optional title of the source document, echoed back from the request.
        document_title: Option<String>,
        /// 1-indexed page number where the cited span begins.
        start_page_number: u32,
        /// 1-indexed page number where the cited span ends (exclusive).
        end_page_number: u32,
    },
    /// A citation locating a block range in a custom-content document.
    ContentBlockLocation {
        /// The exact text being cited. Not counted toward output tokens.
        cited_text: String,
        /// 0-indexed position of the source document in the request's document list.
        document_index: usize,
        /// Optional title of the source document, echoed back from the request.
        document_title: Option<String>,
        /// 0-indexed content block index where the cited span begins.
        start_block_index: usize,
        /// Content block index where the cited span ends (exclusive).
        end_block_index: usize,
    },
    /// A citation locating a block range in a user-provided search result.
    SearchResultLocation {
        /// The exact text being cited. Not counted toward output tokens.
        cited_text: String,
        /// Source URL or identifier from the original search result.
        source: String,
        /// Title from the original search result.
        title: Option<String>,
        /// 0-indexed position of the cited search result across all search
        /// result blocks in the request.
        search_result_index: usize,
        /// 0-indexed content block index where the cited span begins.
        start_block_index: usize,
        /// Content block index where the cited span ends (exclusive).
        end_block_index: usize,
    },
    /// A citation emitted by Anthropic's server-side web search tool.
    WebSearchResultLocation {
        /// The exact text being cited. Not counted toward output tokens.
        cited_text: String,
        /// URL of the cited source.
        url: String,
        /// Title of the cited source.
        title: Option<String>,
        /// Encrypted reference that must be preserved for multi-turn
        /// conversations.
        encrypted_index: String,
    },
    /// A forward-compatible raw citation payload for citation types this crate
    /// does not yet model.
    Unknown(serde_json::Value),
}

#[derive(Deserialize)]
struct CharLocationCitationFields {
    cited_text: String,
    document_index: usize,
    #[serde(default)]
    document_title: Option<String>,
    start_char_index: usize,
    end_char_index: usize,
}

#[derive(Deserialize)]
struct PageLocationCitationFields {
    cited_text: String,
    document_index: usize,
    #[serde(default)]
    document_title: Option<String>,
    start_page_number: u32,
    end_page_number: u32,
}

#[derive(Deserialize)]
struct ContentBlockLocationCitationFields {
    cited_text: String,
    document_index: usize,
    #[serde(default)]
    document_title: Option<String>,
    start_block_index: usize,
    end_block_index: usize,
}

#[derive(Deserialize)]
struct SearchResultLocationCitationFields {
    cited_text: String,
    source: String,
    #[serde(default)]
    title: Option<String>,
    search_result_index: usize,
    start_block_index: usize,
    end_block_index: usize,
}

#[derive(Deserialize)]
struct WebSearchResultLocationCitationFields {
    cited_text: String,
    url: String,
    title: Option<String>,
    encrypted_index: String,
}

impl Serialize for Citation {
    fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
    where
        S: serde::Serializer,
    {
        let mut value = serde_json::Map::new();
        match self {
            Citation::CharLocation {
                cited_text,
                document_index,
                document_title,
                start_char_index,
                end_char_index,
            } => {
                value.insert("type".into(), serde_json::json!("char_location"));
                value.insert("cited_text".into(), serde_json::json!(cited_text));
                value.insert("document_index".into(), serde_json::json!(document_index));
                if let Some(document_title) = document_title {
                    value.insert("document_title".into(), serde_json::json!(document_title));
                }
                value.insert(
                    "start_char_index".into(),
                    serde_json::json!(start_char_index),
                );
                value.insert("end_char_index".into(), serde_json::json!(end_char_index));
            }
            Citation::PageLocation {
                cited_text,
                document_index,
                document_title,
                start_page_number,
                end_page_number,
            } => {
                value.insert("type".into(), serde_json::json!("page_location"));
                value.insert("cited_text".into(), serde_json::json!(cited_text));
                value.insert("document_index".into(), serde_json::json!(document_index));
                if let Some(document_title) = document_title {
                    value.insert("document_title".into(), serde_json::json!(document_title));
                }
                value.insert(
                    "start_page_number".into(),
                    serde_json::json!(start_page_number),
                );
                value.insert("end_page_number".into(), serde_json::json!(end_page_number));
            }
            Citation::ContentBlockLocation {
                cited_text,
                document_index,
                document_title,
                start_block_index,
                end_block_index,
            } => {
                value.insert("type".into(), serde_json::json!("content_block_location"));
                value.insert("cited_text".into(), serde_json::json!(cited_text));
                value.insert("document_index".into(), serde_json::json!(document_index));
                if let Some(document_title) = document_title {
                    value.insert("document_title".into(), serde_json::json!(document_title));
                }
                value.insert(
                    "start_block_index".into(),
                    serde_json::json!(start_block_index),
                );
                value.insert("end_block_index".into(), serde_json::json!(end_block_index));
            }
            Citation::SearchResultLocation {
                cited_text,
                source,
                title,
                search_result_index,
                start_block_index,
                end_block_index,
            } => {
                value.insert("type".into(), serde_json::json!("search_result_location"));
                value.insert("cited_text".into(), serde_json::json!(cited_text));
                value.insert("source".into(), serde_json::json!(source));
                if let Some(title) = title {
                    value.insert("title".into(), serde_json::json!(title));
                }
                value.insert(
                    "search_result_index".into(),
                    serde_json::json!(search_result_index),
                );
                value.insert(
                    "start_block_index".into(),
                    serde_json::json!(start_block_index),
                );
                value.insert("end_block_index".into(), serde_json::json!(end_block_index));
            }
            Citation::WebSearchResultLocation {
                cited_text,
                url,
                title,
                encrypted_index,
            } => {
                value.insert(
                    "type".into(),
                    serde_json::json!("web_search_result_location"),
                );
                value.insert("cited_text".into(), serde_json::json!(cited_text));
                value.insert("url".into(), serde_json::json!(url));
                value.insert("title".into(), serde_json::json!(title));
                value.insert("encrypted_index".into(), serde_json::json!(encrypted_index));
            }
            Citation::Unknown(raw) => return raw.serialize(serializer),
        }

        serde_json::Value::Object(value).serialize(serializer)
    }
}

impl<'de> Deserialize<'de> for Citation {
    fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>
    where
        D: serde::Deserializer<'de>,
    {
        let value = serde_json::Value::deserialize(deserializer)?;
        let Some(citation_type) = value.get("type").and_then(serde_json::Value::as_str) else {
            return Ok(Citation::Unknown(value));
        };

        match citation_type {
            "char_location" => {
                let fields: CharLocationCitationFields =
                    serde_json::from_value(value).map_err(serde::de::Error::custom)?;
                Ok(Citation::CharLocation {
                    cited_text: fields.cited_text,
                    document_index: fields.document_index,
                    document_title: fields.document_title,
                    start_char_index: fields.start_char_index,
                    end_char_index: fields.end_char_index,
                })
            }
            "page_location" => {
                let fields: PageLocationCitationFields =
                    serde_json::from_value(value).map_err(serde::de::Error::custom)?;
                Ok(Citation::PageLocation {
                    cited_text: fields.cited_text,
                    document_index: fields.document_index,
                    document_title: fields.document_title,
                    start_page_number: fields.start_page_number,
                    end_page_number: fields.end_page_number,
                })
            }
            "content_block_location" => {
                let fields: ContentBlockLocationCitationFields =
                    serde_json::from_value(value).map_err(serde::de::Error::custom)?;
                Ok(Citation::ContentBlockLocation {
                    cited_text: fields.cited_text,
                    document_index: fields.document_index,
                    document_title: fields.document_title,
                    start_block_index: fields.start_block_index,
                    end_block_index: fields.end_block_index,
                })
            }
            "search_result_location" => {
                let fields: SearchResultLocationCitationFields =
                    serde_json::from_value(value).map_err(serde::de::Error::custom)?;
                Ok(Citation::SearchResultLocation {
                    cited_text: fields.cited_text,
                    source: fields.source,
                    title: fields.title,
                    search_result_index: fields.search_result_index,
                    start_block_index: fields.start_block_index,
                    end_block_index: fields.end_block_index,
                })
            }
            "web_search_result_location" => {
                let fields: WebSearchResultLocationCitationFields =
                    serde_json::from_value(value).map_err(serde::de::Error::custom)?;
                Ok(Citation::WebSearchResultLocation {
                    cited_text: fields.cited_text,
                    url: fields.url,
                    title: fields.title,
                    encrypted_index: fields.encrypted_index,
                })
            }
            _ => Ok(Citation::Unknown(value)),
        }
    }
}

/// Decoded Anthropic document fields lifted out of [`message::Document::additional_params`]:
/// optional `title`, optional `context`, and optional [`CitationsConfig`].
type AnthropicDocParams = (Option<String>, Option<String>, Option<CitationsConfig>);

/// Extract Anthropic-specific document fields (`title`, `context`, `citations`)
/// from the generic [`message::Document::additional_params`] JSON blob.
///
/// Returns `Ok((None, None, None))` if `additional_params` is empty. Returns
/// an error only if the `citations` field is present but is not a valid
/// [`CitationsConfig`] — invalid shapes are reported instead of being silently
/// dropped, so users notice typos.
fn extract_anthropic_doc_params(
    additional_params: Option<serde_json::Value>,
) -> Result<AnthropicDocParams, MessageError> {
    let Some(value) = additional_params else {
        return Ok((None, None, None));
    };
    let title = value
        .get("title")
        .and_then(|v| v.as_str())
        .map(String::from);
    let context = value
        .get("context")
        .and_then(|v| v.as_str())
        .map(String::from);
    let citations = value
        .get("citations")
        .cloned()
        .map(serde_json::from_value::<CitationsConfig>)
        .transpose()
        .map_err(|e| {
            MessageError::ConversionError(format!(
                "Document `additional_params.citations` is not a valid CitationsConfig: {e}",
            ))
        })?;
    Ok((title, context, citations))
}

/// Extract Anthropic citations attached to a generic [`message::Text`] block.
///
/// Citations are returned by Claude on assistant text blocks when the request
/// enabled them via [`CitationsConfig`]. Internally they are stored as JSON in
/// [`message::Text::additional_params`] so they survive conversion through the
/// generic [`message::AssistantContent`] surface.
///
/// Returns `Ok(vec![])` when no citations are attached. Unknown citation types
/// are preserved as [`Citation::Unknown`]. Returns an error if the `citations`
/// field is malformed or if a known citation type has an invalid shape.
///
/// # Example
///
/// ```no_run
/// use rig_core::completion::message::{self, AssistantContent};
/// use rig_core::providers::anthropic::completion::anthropic_citations;
///
/// fn print_citations(content: &AssistantContent) {
///     if let AssistantContent::Text(text) = content
///         && let Ok(citations) = anthropic_citations(text)
///         && !citations.is_empty()
///     {
///         println!("{citations:?}");
///     }
/// }
/// # let _ = message::Text::new("");
/// ```
pub fn anthropic_citations(text: &message::Text) -> Result<Vec<Citation>, serde_json::Error> {
    match text
        .additional_params
        .as_ref()
        .and_then(|v| v.get("citations"))
    {
        Some(c) => serde_json::from_value::<Vec<Citation>>(c.clone()),
        None => Ok(Vec::new()),
    }
}

fn extract_anthropic_text_citations(text: &message::Text) -> Result<Vec<Citation>, MessageError> {
    anthropic_citations(text).map_err(|err| {
        MessageError::ConversionError(format!(
            "Text `additional_params.citations` is not valid Anthropic citations: {err}"
        ))
    })
}

fn anthropic_text_content_from_message_text(text: message::Text) -> Result<Content, MessageError> {
    if let Some(raw_content) = extract_anthropic_raw_content(&text)? {
        if !text.text.is_empty() {
            return Err(MessageError::ConversionError(format!(
                "Text `{ANTHROPIC_RAW_CONTENT_KEY}` metadata cannot be combined with non-empty text"
            )));
        }

        return Ok(raw_content);
    }

    let citations = extract_anthropic_text_citations(&text)?;
    Ok(Content::Text {
        text: text.text,
        citations,
        cache_control: None,
    })
}

fn extract_anthropic_raw_content(text: &message::Text) -> Result<Option<Content>, MessageError> {
    let Some(raw_content) = text
        .additional_params
        .as_ref()
        .and_then(|value| value.get(ANTHROPIC_RAW_CONTENT_KEY))
    else {
        return Ok(None);
    };

    let content = serde_json::from_value::<Content>(raw_content.clone()).map_err(|err| {
        MessageError::ConversionError(format!(
            "Text `{ANTHROPIC_RAW_CONTENT_KEY}` metadata is not valid Anthropic content: {err}"
        ))
    })?;

    match content {
        Content::ServerToolUse { .. } | Content::WebSearchToolResult { .. } => Ok(Some(content)),
        _ => Err(MessageError::ConversionError(format!(
            "Text `{ANTHROPIC_RAW_CONTENT_KEY}` metadata only supports Anthropic server_tool_use and web_search_tool_result blocks"
        ))),
    }
}

fn anthropic_raw_content_to_message_text(content: Content) -> Result<message::Text, MessageError> {
    let raw_content = serde_json::to_value(content).map_err(|err| {
        MessageError::ConversionError(format!("Failed to preserve Anthropic content block: {err}"))
    })?;

    Ok(message::Text {
        text: String::new(),
        additional_params: Some(serde_json::json!({
            ANTHROPIC_RAW_CONTENT_KEY: raw_content
        })),
    })
}

fn anthropic_document_additional_params(
    title: Option<String>,
    context: Option<String>,
    citations: Option<CitationsConfig>,
) -> Result<Option<serde_json::Value>, MessageError> {
    let mut params = serde_json::Map::new();

    if let Some(title) = title {
        params.insert("title".to_string(), serde_json::Value::String(title));
    }
    if let Some(context) = context {
        params.insert("context".to_string(), serde_json::Value::String(context));
    }
    if let Some(citations) = citations {
        params.insert(
            "citations".to_string(),
            serde_json::to_value(citations).map_err(|err| {
                MessageError::ConversionError(format!(
                    "Failed to preserve Anthropic document citations metadata: {err}"
                ))
            })?,
        );
    }

    Ok((!params.is_empty()).then_some(serde_json::Value::Object(params)))
}

#[derive(Debug, Deserialize, Serialize, Clone, PartialEq)]
#[serde(tag = "type", rename_all = "snake_case")]
pub enum ToolResultContent {
    Text { text: String },
    Image { source: ImageSource },
}

impl FromStr for ToolResultContent {
    type Err = Infallible;

    fn from_str(s: &str) -> Result<Self, Self::Err> {
        Ok(ToolResultContent::Text { text: s.to_owned() })
    }
}

/// The source of an image content block.
///
/// Anthropic supports two source types for images:
/// - `Base64`: Base64-encoded image data with media type
/// - `Url`: URL reference to an image
///
/// See: <https://docs.anthropic.com/en/api/messages>
#[derive(Debug, Deserialize, Serialize, Clone, PartialEq)]
#[serde(tag = "type", rename_all = "snake_case")]
pub enum ImageSource {
    #[serde(rename = "base64")]
    Base64 {
        data: String,
        media_type: ImageFormat,
    },
    #[serde(rename = "url")]
    Url { url: String },
}

/// The source of a document content block.
///
/// Anthropic supports multiple source types for documents:
/// - `Base64`: Base64-encoded document data (used for PDFs)
/// - `Text`: Plain text document data
/// - `Url`: URL reference to a document
/// - `File`: Provider-side uploaded file reference from the Files API
#[derive(Debug, Deserialize, Serialize, Clone, PartialEq)]
#[serde(tag = "type", rename_all = "snake_case")]
pub enum DocumentSource {
    Base64 {
        data: String,
        media_type: DocumentFormat,
    },
    Text {
        data: String,
        media_type: PlainTextMediaType,
    },
    Url {
        url: String,
    },
    File {
        file_id: String,
    },
}

#[derive(Debug, Deserialize, Serialize, Clone, PartialEq)]
#[serde(rename_all = "lowercase")]
pub enum ImageFormat {
    #[serde(rename = "image/jpeg")]
    JPEG,
    #[serde(rename = "image/png")]
    PNG,
    #[serde(rename = "image/gif")]
    GIF,
    #[serde(rename = "image/webp")]
    WEBP,
}

/// The media type for base64-encoded documents.
///
/// Used with the `DocumentSource::Base64` variant. Currently only PDF is supported
/// for base64-encoded document sources.
///
/// See: <https://docs.anthropic.com/en/docs/build-with-claude/pdf-support>
#[derive(Debug, Deserialize, Serialize, Clone, PartialEq)]
#[serde(rename_all = "lowercase")]
pub enum DocumentFormat {
    #[serde(rename = "application/pdf")]
    PDF,
}

/// The media type for plain text document sources.
///
/// Used with the `DocumentSource::Text` variant.
///
/// See: <https://docs.anthropic.com/en/api/messages>
#[derive(Debug, Deserialize, Serialize, Clone, PartialEq)]
pub enum PlainTextMediaType {
    #[serde(rename = "text/plain")]
    Plain,
}

#[derive(Debug, Deserialize, Serialize, Clone, PartialEq)]
#[serde(rename_all = "lowercase")]
pub enum SourceType {
    BASE64,
    URL,
    TEXT,
}

impl From<String> for Content {
    fn from(text: String) -> Self {
        Content::Text {
            text,
            citations: Vec::new(),
            cache_control: None,
        }
    }
}

impl From<String> for ToolResultContent {
    fn from(text: String) -> Self {
        ToolResultContent::Text { text }
    }
}

impl TryFrom<message::ContentFormat> for SourceType {
    type Error = MessageError;

    fn try_from(format: message::ContentFormat) -> Result<Self, Self::Error> {
        match format {
            message::ContentFormat::Base64 => Ok(SourceType::BASE64),
            message::ContentFormat::Url => Ok(SourceType::URL),
            message::ContentFormat::String => Ok(SourceType::TEXT),
        }
    }
}

impl From<SourceType> for message::ContentFormat {
    fn from(source_type: SourceType) -> Self {
        match source_type {
            SourceType::BASE64 => message::ContentFormat::Base64,
            SourceType::URL => message::ContentFormat::Url,
            SourceType::TEXT => message::ContentFormat::String,
        }
    }
}

impl TryFrom<message::ImageMediaType> for ImageFormat {
    type Error = MessageError;

    fn try_from(media_type: message::ImageMediaType) -> Result<Self, Self::Error> {
        Ok(match media_type {
            message::ImageMediaType::JPEG => ImageFormat::JPEG,
            message::ImageMediaType::PNG => ImageFormat::PNG,
            message::ImageMediaType::GIF => ImageFormat::GIF,
            message::ImageMediaType::WEBP => ImageFormat::WEBP,
            _ => {
                return Err(MessageError::ConversionError(
                    format!("Unsupported image media type: {media_type:?}").to_owned(),
                ));
            }
        })
    }
}

impl From<ImageFormat> for message::ImageMediaType {
    fn from(format: ImageFormat) -> Self {
        match format {
            ImageFormat::JPEG => message::ImageMediaType::JPEG,
            ImageFormat::PNG => message::ImageMediaType::PNG,
            ImageFormat::GIF => message::ImageMediaType::GIF,
            ImageFormat::WEBP => message::ImageMediaType::WEBP,
        }
    }
}

impl TryFrom<DocumentMediaType> for DocumentFormat {
    type Error = MessageError;
    fn try_from(value: DocumentMediaType) -> Result<Self, Self::Error> {
        match value {
            DocumentMediaType::PDF => Ok(DocumentFormat::PDF),
            other => Err(MessageError::ConversionError(format!(
                "DocumentFormat only supports PDF for base64 sources, got: {}",
                other.to_mime_type()
            ))),
        }
    }
}

impl TryFrom<message::AssistantContent> for Content {
    type Error = MessageError;
    fn try_from(text: message::AssistantContent) -> Result<Self, Self::Error> {
        match text {
            message::AssistantContent::Text(text) => anthropic_text_content_from_message_text(text),
            message::AssistantContent::Image(_) => Err(MessageError::ConversionError(
                "Anthropic currently doesn't support images.".to_string(),
            )),
            message::AssistantContent::ToolCall(message::ToolCall { id, function, .. }) => {
                Ok(Content::ToolUse {
                    id,
                    name: function.name,
                    input: function.arguments,
                })
            }
            message::AssistantContent::Reasoning(reasoning) => Ok(Content::Thinking {
                thinking: reasoning.display_text(),
                signature: reasoning.first_signature().map(str::to_owned),
            }),
        }
    }
}

fn anthropic_content_from_assistant_content(
    content: message::AssistantContent,
) -> Result<Vec<Content>, MessageError> {
    match content {
        message::AssistantContent::Text(text) => {
            Ok(vec![anthropic_text_content_from_message_text(text)?])
        }
        message::AssistantContent::Image(_) => Err(MessageError::ConversionError(
            "Anthropic currently doesn't support images.".to_string(),
        )),
        message::AssistantContent::ToolCall(message::ToolCall { id, function, .. }) => {
            Ok(vec![Content::ToolUse {
                id,
                name: function.name,
                input: function.arguments,
            }])
        }
        message::AssistantContent::Reasoning(reasoning) => {
            let mut converted = Vec::new();
            for block in reasoning.content {
                match block {
                    message::ReasoningContent::Text { text, signature } => {
                        converted.push(Content::Thinking {
                            thinking: text,
                            signature,
                        });
                    }
                    message::ReasoningContent::Summary(summary) => {
                        converted.push(Content::Thinking {
                            thinking: summary,
                            signature: None,
                        });
                    }
                    message::ReasoningContent::Redacted { data }
                    | message::ReasoningContent::Encrypted(data) => {
                        converted.push(Content::RedactedThinking { data });
                    }
                }
            }

            if converted.is_empty() {
                return Err(MessageError::ConversionError(
                    "Cannot convert empty reasoning content to Anthropic format".to_string(),
                ));
            }

            Ok(converted)
        }
    }
}

impl TryFrom<message::Message> for Message {
    type Error = MessageError;

    fn try_from(message: message::Message) -> Result<Self, Self::Error> {
        Ok(match message {
            message::Message::User { content } => Message {
                role: Role::User,
                content: content.try_map(|content| match content {
                    message::UserContent::Text(message::Text { text, .. }) => Ok(Content::Text {
                        text,
                        citations: Vec::new(),
                        cache_control: None,
                    }),
                    message::UserContent::ToolResult(message::ToolResult {
                        id, content, ..
                    }) => Ok(Content::ToolResult {
                        tool_use_id: id,
                        content: content.try_map(|content| match content {
                            message::ToolResultContent::Text(message::Text { text, .. }) => {
                                Ok(ToolResultContent::Text { text })
                            }
                            message::ToolResultContent::Image(image) => {
                                let DocumentSourceKind::Base64(data) = image.data else {
                                    return Err(MessageError::ConversionError(
                                        "Only base64 strings can be used with the Anthropic API"
                                            .to_string(),
                                    ));
                                };
                                let media_type =
                                    image.media_type.ok_or(MessageError::ConversionError(
                                        "Image media type is required".to_owned(),
                                    ))?;
                                Ok(ToolResultContent::Image {
                                    source: ImageSource::Base64 {
                                        data,
                                        media_type: media_type.try_into()?,
                                    },
                                })
                            }
                        })?,
                        is_error: None,
                        cache_control: None,
                    }),
                    message::UserContent::Image(message::Image {
                        data, media_type, ..
                    }) => {
                        let source = match data {
                            DocumentSourceKind::Base64(data) => {
                                let media_type =
                                    media_type.ok_or(MessageError::ConversionError(
                                        "Image media type is required for Claude API".to_string(),
                                    ))?;
                                ImageSource::Base64 {
                                    data,
                                    media_type: ImageFormat::try_from(media_type)?,
                                }
                            }
                            DocumentSourceKind::Url(url) => ImageSource::Url { url },
                            DocumentSourceKind::Unknown => {
                                return Err(MessageError::ConversionError(
                                    "Image content has no body".into(),
                                ));
                            }
                            doc => {
                                return Err(MessageError::ConversionError(format!(
                                    "Unsupported document type: {doc:?}"
                                )));
                            }
                        };

                        Ok(Content::Image {
                            source,
                            cache_control: None,
                        })
                    }
                    message::UserContent::Document(message::Document {
                        data,
                        media_type,
                        additional_params,
                    }) => {
                        let (title, context, citations) =
                            extract_anthropic_doc_params(additional_params)?;

                        if let DocumentSourceKind::FileId(file_id) = data {
                            return Ok(Content::Document {
                                source: DocumentSource::File { file_id },
                                title,
                                context,
                                citations,
                                cache_control: None,
                            });
                        }

                        let media_type = media_type.ok_or(MessageError::ConversionError(
                            "Document media type is required".to_string(),
                        ))?;

                        let source = match media_type {
                            DocumentMediaType::PDF => {
                                let data = match data {
                                    DocumentSourceKind::Base64(data)
                                    | DocumentSourceKind::String(data) => data,
                                    _ => {
                                        return Err(MessageError::ConversionError(
                                            "Only base64 encoded data is supported for PDF documents".into(),
                                        ));
                                    }
                                };
                                DocumentSource::Base64 {
                                    data,
                                    media_type: DocumentFormat::PDF,
                                }
                            }
                            DocumentMediaType::TXT => {
                                let data = match data {
                                    DocumentSourceKind::String(data)
                                    | DocumentSourceKind::Base64(data) => data,
                                    _ => {
                                        return Err(MessageError::ConversionError(
                                            "Only string or base64 data is supported for plain text documents".into(),
                                        ));
                                    }
                                };
                                DocumentSource::Text {
                                    data,
                                    media_type: PlainTextMediaType::Plain,
                                }
                            }
                            other => {
                                return Err(MessageError::ConversionError(format!(
                                    "Anthropic only supports PDF and plain text documents, got: {}",
                                    other.to_mime_type()
                                )));
                            }
                        };

                        Ok(Content::Document {
                            source,
                            title,
                            context,
                            citations,
                            cache_control: None,
                        })
                    }
                    message::UserContent::Audio { .. } => Err(MessageError::ConversionError(
                        "Audio is not supported in Anthropic".to_owned(),
                    )),
                    message::UserContent::Video { .. } => Err(MessageError::ConversionError(
                        "Video is not supported in Anthropic".to_owned(),
                    )),
                })?,
            },

            message::Message::System { content } => Message {
                role: Role::System,
                content: OneOrMany::one(Content::Text {
                    text: content,
                    citations: Vec::new(),
                    cache_control: None,
                }),
            },

            message::Message::Assistant { content, .. } => {
                let converted_content = content.into_iter().try_fold(
                    Vec::new(),
                    |mut accumulated, assistant_content| {
                        accumulated
                            .extend(anthropic_content_from_assistant_content(assistant_content)?);
                        Ok::<Vec<Content>, MessageError>(accumulated)
                    },
                )?;

                Message {
                    content: OneOrMany::many(converted_content).map_err(|_| {
                        MessageError::ConversionError(
                            "Assistant message did not contain Anthropic-compatible content"
                                .to_owned(),
                        )
                    })?,
                    role: Role::Assistant,
                }
            }
        })
    }
}

impl TryFrom<Content> for message::AssistantContent {
    type Error = MessageError;

    fn try_from(content: Content) -> Result<Self, Self::Error> {
        Ok(match content {
            Content::Text {
                text, citations, ..
            } => {
                // Preserve citation metadata on the generic text block via
                // `additional_params` so callers going through the generic
                // `AssistantContent` surface can still recover them (see
                // [`anthropic_citations`]).
                let additional_params =
                    (!citations.is_empty()).then(|| serde_json::json!({ "citations": citations }));
                message::AssistantContent::Text(message::Text {
                    text,
                    additional_params,
                })
            }
            Content::ToolUse { id, name, input } => {
                message::AssistantContent::tool_call(id, name, input)
            }
            raw @ (Content::ServerToolUse { .. } | Content::WebSearchToolResult { .. }) => {
                message::AssistantContent::Text(anthropic_raw_content_to_message_text(raw)?)
            }
            Content::Thinking {
                thinking,
                signature,
            } => message::AssistantContent::Reasoning(Reasoning::new_with_signature(
                &thinking, signature,
            )),
            Content::RedactedThinking { data } => {
                message::AssistantContent::Reasoning(Reasoning::redacted(data))
            }
            _ => {
                return Err(MessageError::ConversionError(
                    "Content did not contain a message, tool call, or reasoning".to_owned(),
                ));
            }
        })
    }
}

impl From<ToolResultContent> for message::ToolResultContent {
    fn from(content: ToolResultContent) -> Self {
        match content {
            ToolResultContent::Text { text, .. } => message::ToolResultContent::text(text),
            ToolResultContent::Image { source } => match source {
                ImageSource::Base64 { data, media_type } => {
                    message::ToolResultContent::image_base64(data, Some(media_type.into()), None)
                }
                ImageSource::Url { url } => message::ToolResultContent::image_url(url, None, None),
            },
        }
    }
}

impl TryFrom<Message> for message::Message {
    type Error = MessageError;

    fn try_from(message: Message) -> Result<Self, Self::Error> {
        Ok(match message.role {
            Role::User => message::Message::User {
                content: message.content.try_map(|content| {
                    Ok(match content {
                        Content::Text { text, .. } => message::UserContent::text(text),
                        Content::ToolResult {
                            tool_use_id,
                            content,
                            ..
                        } => message::UserContent::tool_result(
                            tool_use_id,
                            content.map(|content| content.into()),
                        ),
                        Content::Image { source, .. } => match source {
                            ImageSource::Base64 { data, media_type } => {
                                message::UserContent::Image(message::Image {
                                    data: DocumentSourceKind::Base64(data),
                                    media_type: Some(media_type.into()),
                                    detail: None,
                                    additional_params: None,
                                })
                            }
                            ImageSource::Url { url } => {
                                message::UserContent::Image(message::Image {
                                    data: DocumentSourceKind::Url(url),
                                    media_type: None,
                                    detail: None,
                                    additional_params: None,
                                })
                            }
                        },
                        Content::Document {
                            source,
                            title,
                            context,
                            citations,
                            ..
                        } => {
                            let additional_params =
                                anthropic_document_additional_params(title, context, citations)?;

                            match source {
                                DocumentSource::Base64 { data, media_type } => {
                                    let rig_media_type = match media_type {
                                        DocumentFormat::PDF => message::DocumentMediaType::PDF,
                                    };
                                    message::UserContent::Document(message::Document {
                                        data: DocumentSourceKind::String(data),
                                        media_type: Some(rig_media_type),
                                        additional_params,
                                    })
                                }
                                DocumentSource::Text { data, .. } => {
                                    message::UserContent::Document(message::Document {
                                        data: DocumentSourceKind::String(data),
                                        media_type: Some(message::DocumentMediaType::TXT),
                                        additional_params,
                                    })
                                }
                                DocumentSource::Url { url } => {
                                    message::UserContent::Document(message::Document {
                                        data: DocumentSourceKind::Url(url),
                                        media_type: None,
                                        additional_params,
                                    })
                                }
                                DocumentSource::File { file_id } => {
                                    message::UserContent::Document(message::Document {
                                        data: DocumentSourceKind::FileId(file_id),
                                        media_type: None,
                                        additional_params,
                                    })
                                }
                            }
                        }
                        _ => {
                            return Err(MessageError::ConversionError(
                                "Unsupported content type for User role".to_owned(),
                            ));
                        }
                    })
                })?,
            },
            Role::Assistant => message::Message::Assistant {
                id: None,
                content: message.content.try_map(|content| content.try_into())?,
            },
            Role::System => {
                let content =
                    message
                        .content
                        .into_iter()
                        .try_fold(String::new(), |mut content, block| {
                            let Content::Text { text, .. } = block else {
                                return Err(MessageError::ConversionError(
                                    "Unsupported content type for System role".to_owned(),
                                ));
                            };

                            content.push_str(&text);
                            Ok(content)
                        })?;

                message::Message::System { content }
            }
        })
    }
}

#[doc(hidden)]
#[derive(Clone)]
pub struct GenericCompletionModel<Ext = super::client::AnthropicExt, T = reqwest::Client> {
    pub(crate) client: crate::client::Client<Ext, T>,
    pub model: String,
    pub default_max_tokens: Option<u64>,
    /// Enable manual prompt caching (adds cache_control breakpoints to system prompt,
    /// tools, and messages)
    pub prompt_caching: bool,
    /// Enable Anthropic's automatic prompt caching (adds a top-level `cache_control` field to the
    /// request). The API automatically places the breakpoint on the last cacheable block and moves
    /// it forward as the conversation grows. No beta header is required.
    pub automatic_caching: bool,
    /// TTL for automatic caching. `None` uses the API default (5 minutes).
    /// Set to `Some(CacheTtl::OneHour)` for a 1-hour TTL.
    pub automatic_caching_ttl: Option<CacheTtl>,
}

/// Anthropic completion model.
///
/// This preserves the historical public generic shape where the first generic
/// parameter is the HTTP client type.
pub type CompletionModel<T = reqwest::Client> =
    GenericCompletionModel<super::client::AnthropicExt, T>;

impl<Ext, T> GenericCompletionModel<Ext, T>
where
    T: HttpClientExt,
    Ext: AnthropicCompatibleProvider + Clone + 'static,
{
    pub fn new(client: crate::client::Client<Ext, T>, model: impl Into<String>) -> Self {
        let model = model.into();
        let default_max_tokens = Ext::default_max_tokens(&model);

        Self {
            client,
            model,
            default_max_tokens,
            prompt_caching: false,
            automatic_caching: false,
            automatic_caching_ttl: None,
        }
    }

    pub fn with_model(client: crate::client::Client<Ext, T>, model: &str) -> Self {
        Self {
            client,
            model: model.to_string(),
            default_max_tokens: Ext::default_max_tokens(model)
                .or_else(|| Some(default_max_tokens_with_fallback(model))),
            prompt_caching: false,
            automatic_caching: false,
            automatic_caching_ttl: None,
        }
    }

    /// Enable manual prompt caching.
    ///
    /// When enabled, cache_control breakpoints are automatically added to:
    /// - The system prompt (marked with ephemeral cache)
    /// - The final tool definition, when tools are present (marked with ephemeral cache)
    /// - The last content block of the last message (marked with ephemeral cache)
    ///
    /// This allows Anthropic to cache the system prompt, tools layer, and conversation
    /// history for cost savings. Use [`with_automatic_caching`] when you want Anthropic
    /// to choose and advance a single top-level cache breakpoint automatically.
    /// When combined with [`with_automatic_caching`], the top-level automatic breakpoint
    /// owns the moving message cache point while Rig still marks tools and system prompt
    /// blocks when budget permits.
    /// Existing `cache_control` markers in provider-specific tool definitions are preserved
    /// and count toward Anthropic's request limit of 4 cache breakpoints.
    ///
    /// [`with_automatic_caching`]: CompletionModel::with_automatic_caching
    pub fn with_prompt_caching(mut self) -> Self {
        self.prompt_caching = true;
        self
    }

    /// Enable Anthropic's automatic prompt caching.
    ///
    /// When enabled, a top-level `cache_control: { "type": "ephemeral" }` field is added to every
    /// request. Anthropic's API automatically applies the cache breakpoint to the last cacheable
    /// block and moves it forward as the conversation grows — no beta header and no manual
    /// breakpoint management are required.
    ///
    /// This is the recommended approach for multi-turn conversations. Use [`with_prompt_caching`]
    /// instead when you need fine-grained, per-block control over what is cached.
    ///
    /// To use a one-hour TTL instead of the default five minutes, use
    /// [`with_automatic_caching_1h`] or pass top-level `cache_control` with
    /// `ttl: "1h"` via `additional_params`. Rig normalizes raw top-level
    /// `cache_control` before budgeting and ordering manual prompt cache markers.
    ///
    /// ```ignore
    /// let model = client.completion_model(anthropic::completion::CLAUDE_SONNET_4_6)
    ///     .with_automatic_caching();
    /// ```
    ///
    /// ## Minimum cacheable prompt length
    ///
    /// The combined prompt (tools + system + messages up to the automatically chosen breakpoint)
    /// must meet the model-specific minimum or caching is silently skipped by the API:
    ///
    /// | Model | Minimum tokens |
    /// |-------|---------------|
    /// | `claude-opus-4-7`, `claude-opus-4-6`, `claude-opus-4-5` | 4 096 |
    /// | `claude-sonnet-4-6` | 2 048 |
    /// | `claude-sonnet-4-5`, `claude-opus-4-1`, `claude-opus-4`, `claude-sonnet-4` | 1 024 |
    /// | `claude-haiku-4-5` | 4 096 |
    ///
    /// [`with_prompt_caching`]: CompletionModel::with_prompt_caching
    /// [`with_automatic_caching_1h`]: CompletionModel::with_automatic_caching_1h
    pub fn with_automatic_caching(mut self) -> Self {
        self.automatic_caching = true;
        self
    }

    /// Enable Anthropic's automatic prompt caching with a 1-hour TTL.
    ///
    /// Identical to [`with_automatic_caching`] but sets `ttl: "1h"` on the
    /// top-level `cache_control` field:
    ///
    /// ```ignore
    /// let model = client.completion_model(anthropic::completion::CLAUDE_SONNET_4_6)
    ///     .with_automatic_caching_1h();
    /// ```
    ///
    /// [`with_automatic_caching`]: CompletionModel::with_automatic_caching
    pub fn with_automatic_caching_1h(mut self) -> Self {
        self.automatic_caching = true;
        self.automatic_caching_ttl = Some(CacheTtl::OneHour);
        self
    }
}

/// Anthropic requires a `max_tokens` parameter to be set, which is dependent on the model. If not
/// set or if set too high, the request will fail. The following values are based on Anthropic's
/// published synchronous Messages API output limits for current models.
fn default_max_tokens_for_model(model: &str) -> Option<u64> {
    if model.starts_with("claude-opus-4-8")
        || model.starts_with("claude-opus-4-7")
        || model.starts_with("claude-opus-4-6")
    {
        Some(128_000)
    } else if model.starts_with("claude-opus-4")
        || model.starts_with("claude-sonnet-4")
        || model.starts_with("claude-haiku-4-5")
    {
        Some(64_000)
    } else {
        None
    }
}

fn default_max_tokens_with_fallback(model: &str) -> u64 {
    default_max_tokens_for_model(model).unwrap_or(2_048)
}

pub(super) fn supports_mid_conversation_system_messages(model: &str) -> bool {
    model.starts_with(CLAUDE_OPUS_4_8)
}

#[derive(Debug, Deserialize, Serialize)]
pub struct Metadata {
    user_id: Option<String>,
}

#[derive(Default, Debug, Serialize, Deserialize)]
#[serde(tag = "type", rename_all = "snake_case")]
pub enum ToolChoice {
    #[default]
    Auto,
    Any,
    None,
    Tool {
        name: String,
    },
}
impl TryFrom<message::ToolChoice> for ToolChoice {
    type Error = CompletionError;

    fn try_from(value: message::ToolChoice) -> Result<Self, Self::Error> {
        let res = match value {
            message::ToolChoice::Auto => Self::Auto,
            message::ToolChoice::None => Self::None,
            message::ToolChoice::Required => Self::Any,
            message::ToolChoice::Specific { function_names } => {
                if function_names.len() != 1 {
                    return Err(CompletionError::ProviderError(
                        "Only one tool may be specified to be used by Claude".into(),
                    ));
                }

                let Some(name) = function_names.into_iter().next() else {
                    return Err(CompletionError::ProviderError(
                        "Only one tool may be specified to be used by Claude".into(),
                    ));
                };

                Self::Tool { name }
            }
        };

        Ok(res)
    }
}

/// Recursively ensures all object schemas respect Anthropic structured output restrictions:
/// - `additionalProperties` must be explicitly set to `false` on every object
/// - All properties must be listed in `required`
///
/// Source: <https://docs.anthropic.com/en/docs/build-with-claude/structured-outputs#json-schema-limitations>
fn sanitize_schema(schema: &mut serde_json::Value) {
    use serde_json::Value;

    if let Value::Object(obj) = schema {
        let is_object_schema = obj.get("type") == Some(&Value::String("object".to_string()))
            || obj.contains_key("properties");

        if is_object_schema && !obj.contains_key("additionalProperties") {
            obj.insert("additionalProperties".to_string(), Value::Bool(false));
        }

        if let Some(Value::Object(properties)) = obj.get("properties") {
            let prop_keys = properties.keys().cloned().map(Value::String).collect();
            obj.insert("required".to_string(), Value::Array(prop_keys));
        }

        // Anthropic does not support numerical constraints on integer/number types.
        let is_numeric_schema = obj.get("type") == Some(&Value::String("integer".to_string()))
            || obj.get("type") == Some(&Value::String("number".to_string()));

        if is_numeric_schema {
            for key in [
                "minimum",
                "maximum",
                "exclusiveMinimum",
                "exclusiveMaximum",
                "multipleOf",
            ] {
                obj.remove(key);
            }
        }

        if let Some(defs) = obj.get_mut("$defs")
            && let Value::Object(defs_obj) = defs
        {
            for (_, def_schema) in defs_obj.iter_mut() {
                sanitize_schema(def_schema);
            }
        }

        if let Some(properties) = obj.get_mut("properties")
            && let Value::Object(props) = properties
        {
            for (_, prop_value) in props.iter_mut() {
                sanitize_schema(prop_value);
            }
        }

        if let Some(items) = obj.get_mut("items") {
            sanitize_schema(items);
        }

        // Anthropic doesn't support oneOf, convert to anyOf
        if let Some(one_of) = obj.remove("oneOf") {
            match obj.get_mut("anyOf") {
                Some(Value::Array(existing)) => {
                    if let Value::Array(mut incoming) = one_of {
                        existing.append(&mut incoming);
                    }
                }
                _ => {
                    obj.insert("anyOf".to_string(), one_of);
                }
            }
        }

        for key in ["anyOf", "allOf"] {
            if let Some(variants) = obj.get_mut(key)
                && let Value::Array(variants_array) = variants
            {
                for variant in variants_array.iter_mut() {
                    sanitize_schema(variant);
                }
            }
        }
    }
}

/// Output format specifier for Anthropic's structured output.
/// Source: <https://docs.anthropic.com/en/api/messages>
#[derive(Debug, Deserialize, Serialize)]
#[serde(tag = "type", rename_all = "snake_case")]
enum OutputFormat {
    /// Constrains the model's response to conform to the provided JSON schema.
    JsonSchema { schema: serde_json::Value },
}

/// Configuration for the model's output format.
#[derive(Debug, Deserialize, Serialize)]
struct OutputConfig {
    format: OutputFormat,
}

#[derive(Debug, Deserialize, Serialize)]
struct AnthropicCompletionRequest {
    model: String,
    messages: Vec<Message>,
    max_tokens: u64,
    /// System prompt as array of content blocks to support cache_control
    #[serde(skip_serializing_if = "Vec::is_empty")]
    system: Vec<SystemContent>,
    #[serde(skip_serializing_if = "Option::is_none")]
    temperature: Option<f64>,
    #[serde(skip_serializing_if = "Option::is_none")]
    tool_choice: Option<ToolChoice>,
    #[serde(skip_serializing_if = "Vec::is_empty")]
    tools: Vec<serde_json::Value>,
    #[serde(skip_serializing_if = "Option::is_none")]
    output_config: Option<OutputConfig>,
    #[serde(flatten, skip_serializing_if = "Option::is_none")]
    additional_params: Option<serde_json::Value>,
    /// Top-level cache_control for Anthropic's automatic caching mode. When set, the API
    /// automatically places the cache breakpoint on the last cacheable block and advances it as
    /// the conversation grows. No beta header is required.
    #[serde(skip_serializing_if = "Option::is_none")]
    cache_control: Option<CacheControl>,
}

/// Helper to set cache_control on a Content block
fn set_content_cache_control(content: &mut Content, value: Option<CacheControl>) {
    match content {
        Content::Text { cache_control, .. } => *cache_control = value,
        Content::Image { cache_control, .. } => *cache_control = value,
        Content::ToolResult { cache_control, .. } => *cache_control = value,
        Content::Document { cache_control, .. } => *cache_control = value,
        _ => {}
    }
}

const MAX_CACHE_CONTROL_MARKERS: usize = 4;

/// Apply cache control breakpoints to system prompt and messages.
/// Strategy: cache the system prompt, and mark the last content block of the last message
/// for caching. This allows the conversation history to be cached while new messages
/// are added.
pub fn apply_cache_control(system: &mut [SystemContent], messages: &mut [Message]) {
    // Add cache_control to the system prompt (if non-empty)
    if let Some(SystemContent::Text { cache_control, .. }) = system.last_mut() {
        *cache_control = Some(CacheControl::ephemeral());
    }

    // Clear any existing cache_control from all message content blocks
    for msg in messages.iter_mut() {
        for content in msg.content.iter_mut() {
            set_content_cache_control(content, None);
        }
    }

    // Add cache_control to the last content block of the last message
    if let Some(last_msg) = messages.last_mut() {
        set_content_cache_control(last_msg.content.last_mut(), Some(CacheControl::ephemeral()));
    }
}

fn final_cacheable_tool_idx(tools: &[serde_json::Value]) -> Option<usize> {
    tools.iter().rposition(|tool| {
        tool.as_object().is_some_and(|tool| {
            !matches!(
                tool.get("defer_loading"),
                Some(serde_json::Value::Bool(true))
            )
        })
    })
}

fn tool_cache_control_count(tools: &[serde_json::Value]) -> usize {
    tools
        .iter()
        .filter(|tool| tool_cache_control_value(tool).is_some())
        .count()
}

fn tool_cache_control_value(tool: &serde_json::Value) -> Option<&serde_json::Value> {
    tool.get("cache_control")
        .filter(|cache_control| !cache_control.is_null())
}

fn normalize_tool_cache_control(tools: &mut [serde_json::Value]) {
    for tool in tools.iter_mut() {
        if let Some(tool) = tool.as_object_mut()
            && tool
                .get("cache_control")
                .is_some_and(serde_json::Value::is_null)
        {
            tool.remove("cache_control");
        }
    }
}

fn build_cache_control(ttl: Option<CacheTtl>) -> CacheControl {
    CacheControl::Ephemeral { ttl }
}

#[derive(Clone, Copy, PartialEq, Eq)]
enum CacheControlTtl {
    FiveMinutes,
    OneHour,
}

fn cache_control_ttl(cache_control: &CacheControl) -> CacheControlTtl {
    match cache_control {
        CacheControl::Ephemeral {
            ttl: Some(CacheTtl::OneHour),
        } => CacheControlTtl::OneHour,
        CacheControl::Ephemeral { .. } => CacheControlTtl::FiveMinutes,
    }
}

fn cache_control_ttl_from_json(cache_control: &serde_json::Value) -> CacheControlTtl {
    match cache_control.get("ttl") {
        Some(serde_json::Value::String(ttl)) if ttl == "1h" => CacheControlTtl::OneHour,
        _ => CacheControlTtl::FiveMinutes,
    }
}

fn content_cache_control(content: &Content) -> Option<&CacheControl> {
    match content {
        Content::Text { cache_control, .. }
        | Content::Image { cache_control, .. }
        | Content::ToolResult { cache_control, .. }
        | Content::Document { cache_control, .. } => cache_control.as_ref(),
        _ => None,
    }
}

fn validate_cache_control_ttl(
    ttl: CacheControlTtl,
    shorter_ttl_seen: &mut bool,
) -> Result<(), CompletionError> {
    match ttl {
        CacheControlTtl::OneHour if *shorter_ttl_seen => Err(CompletionError::RequestError(
            "Anthropic cache_control markers with ttl `1h` must appear before markers with \
                 the default 5-minute TTL"
                .into(),
        )),
        CacheControlTtl::OneHour => Ok(()),
        CacheControlTtl::FiveMinutes => {
            *shorter_ttl_seen = true;
            Ok(())
        }
    }
}

fn validate_cache_control_ttl_order(
    system: &[SystemContent],
    messages: &[Message],
    tools: &[serde_json::Value],
    top_level_cache_control: Option<&CacheControl>,
) -> Result<(), CompletionError> {
    let mut shorter_ttl_seen = false;

    for tool in tools {
        if let Some(cache_control) = tool_cache_control_value(tool) {
            validate_cache_control_ttl(
                cache_control_ttl_from_json(cache_control),
                &mut shorter_ttl_seen,
            )?;
        }
    }

    for SystemContent::Text { cache_control, .. } in system {
        if let Some(cache_control) = cache_control {
            validate_cache_control_ttl(cache_control_ttl(cache_control), &mut shorter_ttl_seen)?;
        }
    }

    for message in messages {
        for content in message.content.iter() {
            if let Some(cache_control) = content_cache_control(content) {
                validate_cache_control_ttl(
                    cache_control_ttl(cache_control),
                    &mut shorter_ttl_seen,
                )?;
            }
        }
    }

    if let Some(cache_control) = top_level_cache_control {
        validate_cache_control_ttl(cache_control_ttl(cache_control), &mut shorter_ttl_seen)?;
    }

    Ok(())
}

fn top_level_cache_control_ttl(cache_control: Option<&CacheControl>) -> Option<CacheTtl> {
    cache_control
        .map(|cache_control| match cache_control {
            CacheControl::Ephemeral { ttl } => ttl.clone(),
        })
        .unwrap_or_default()
}

/// Apply a cache-control breakpoint to the final cacheable tool definition in the request.
fn apply_tool_cache_control(
    tools: &mut [serde_json::Value],
    remaining_cache_markers: &mut usize,
    cache_control: &CacheControl,
) -> Result<(), CompletionError> {
    let Some(idx) = final_cacheable_tool_idx(tools) else {
        return Ok(());
    };

    let Some(tool) = tools
        .get_mut(idx)
        .and_then(serde_json::Value::as_object_mut)
    else {
        return Ok(());
    };

    if tool
        .get("cache_control")
        .is_some_and(|cache_control| !cache_control.is_null())
    {
        return Ok(());
    }

    if *remaining_cache_markers == 0 {
        return Err(CompletionError::RequestError(
            "Anthropic manual prompt caching requires a cache_control marker on the final \
             non-deferred tool, but explicit tool markers exhaust the available cache point budget"
                .into(),
        ));
    }

    tool.insert(
        "cache_control".to_string(),
        serde_json::to_value(cache_control)?,
    );
    *remaining_cache_markers -= 1;

    Ok(())
}

fn apply_system_cache_control(
    system: &mut [SystemContent],
    remaining_cache_markers: &mut usize,
    cache_control_value: &CacheControl,
) {
    if *remaining_cache_markers == 0 {
        return;
    }

    if let Some(SystemContent::Text { cache_control, .. }) = system.last_mut()
        && cache_control.is_none()
    {
        *cache_control = Some(cache_control_value.clone());
        *remaining_cache_markers -= 1;
    }
}

fn clear_message_cache_control(messages: &mut [Message]) {
    for msg in messages.iter_mut() {
        for content in msg.content.iter_mut() {
            set_content_cache_control(content, None);
        }
    }
}

fn apply_message_cache_control(
    messages: &mut [Message],
    remaining_cache_markers: &mut usize,
    cache_control: &CacheControl,
) {
    clear_message_cache_control(messages);

    if *remaining_cache_markers == 0 {
        return;
    }

    if let Some(last_msg) = messages.last_mut() {
        set_content_cache_control(last_msg.content.last_mut(), Some(cache_control.clone()));
        *remaining_cache_markers -= 1;
    }
}

pub(super) fn apply_prompt_cache_control(
    system: &mut [SystemContent],
    messages: &mut [Message],
    tools: &mut [serde_json::Value],
    prompt_caching: bool,
    top_level_cache_control: Option<&CacheControl>,
) -> Result<(), CompletionError> {
    normalize_tool_cache_control(tools);

    let max_cache_markers = if top_level_cache_control.is_some() {
        MAX_CACHE_CONTROL_MARKERS - 1
    } else {
        MAX_CACHE_CONTROL_MARKERS
    };
    let tool_cache_markers = tool_cache_control_count(tools);

    if tool_cache_markers > max_cache_markers {
        return Err(CompletionError::RequestError(
            format!(
                "Too many Anthropic tool `cache_control` markers: {tool_cache_markers} exceeds \
                 the available prompt caching budget of {max_cache_markers}"
            )
            .into(),
        ));
    }

    let mut remaining_cache_markers = max_cache_markers - tool_cache_markers;

    if prompt_caching {
        let generated_cache_control =
            build_cache_control(top_level_cache_control_ttl(top_level_cache_control));

        apply_tool_cache_control(
            tools,
            &mut remaining_cache_markers,
            &generated_cache_control,
        )?;
        apply_system_cache_control(
            system,
            &mut remaining_cache_markers,
            &generated_cache_control,
        );

        if top_level_cache_control.is_some() {
            clear_message_cache_control(messages);
        } else {
            apply_message_cache_control(
                messages,
                &mut remaining_cache_markers,
                &generated_cache_control,
            );
        }
    }

    validate_cache_control_ttl_order(system, messages, tools, top_level_cache_control)?;

    Ok(())
}

pub(super) fn extract_top_level_cache_control(
    additional_params: &mut serde_json::Value,
) -> Result<Option<CacheControl>, CompletionError> {
    if let Some(map) = additional_params.as_object_mut()
        && let Some(raw_cache_control) = map.remove("cache_control")
    {
        if raw_cache_control.is_null() {
            return Ok(None);
        }

        return serde_json::from_value::<CacheControl>(raw_cache_control)
            .map(Some)
            .map_err(|err| {
                CompletionError::RequestError(
                    format!("Invalid Anthropic `additional_params.cache_control` payload: {err}")
                        .into(),
                )
            });
    }

    Ok(None)
}

pub(super) fn resolve_top_level_cache_control(
    automatic_caching: bool,
    automatic_caching_ttl: Option<CacheTtl>,
    additional_params: &mut serde_json::Value,
) -> Result<Option<CacheControl>, CompletionError> {
    let raw_cache_control = extract_top_level_cache_control(additional_params)?;
    let typed_cache_control = automatic_caching.then_some(CacheControl::Ephemeral {
        ttl: automatic_caching_ttl.clone(),
    });

    match (typed_cache_control, raw_cache_control) {
        (Some(typed_cache_control), Some(raw_cache_control)) => {
            if automatic_caching_ttl.is_some()
                && cache_control_ttl(&typed_cache_control) != cache_control_ttl(&raw_cache_control)
            {
                return Err(CompletionError::RequestError(
                    "Anthropic `additional_params.cache_control` conflicts with the typed \
                     automatic caching TTL"
                        .into(),
                ));
            }

            Ok(Some(raw_cache_control))
        }
        (Some(typed_cache_control), None) => Ok(Some(typed_cache_control)),
        (None, raw_cache_control) => Ok(raw_cache_control),
    }
}

pub(super) fn split_system_messages_from_history(
    history: Vec<message::Message>,
    preserve_mid_conversation_system_messages: bool,
) -> (Vec<SystemContent>, Vec<message::Message>) {
    let mut system = Vec::new();
    let mut remaining = Vec::new();

    for (index, message) in history.iter().enumerate() {
        match message {
            message::Message::System { content } => {
                if !content.is_empty() {
                    if preserve_mid_conversation_system_messages
                        && is_valid_mid_conversation_system_message(&history, index)
                    {
                        remaining.push(message.clone());
                    } else {
                        system.push(SystemContent::Text {
                            text: content.clone(),
                            cache_control: None,
                        });
                    }
                }
            }
            other => remaining.push(other.clone()),
        }
    }

    (system, remaining)
}

fn is_valid_mid_conversation_system_message(history: &[message::Message], index: usize) -> bool {
    let follows_valid_turn = index > 0
        && history.get(index - 1).is_some_and(|message| {
            matches!(message, message::Message::User { .. })
                || assistant_ends_in_server_tool_block(message)
        });
    let is_last_or_precedes_assistant = history
        .get(index + 1)
        .is_none_or(|message| matches!(message, message::Message::Assistant { .. }));

    follows_valid_turn && is_last_or_precedes_assistant
}

fn assistant_ends_in_server_tool_block(message: &message::Message) -> bool {
    let message::Message::Assistant { content, .. } = message else {
        return false;
    };

    let Some(message::AssistantContent::Text(text)) = content.iter().last() else {
        return false;
    };

    let Some(raw_type) = text
        .additional_params
        .as_ref()
        .and_then(|params| params.get(ANTHROPIC_RAW_CONTENT_KEY))
        .and_then(|raw_content| raw_content.get("type"))
        .and_then(serde_json::Value::as_str)
    else {
        return false;
    };

    matches!(raw_type, "server_tool_use" | "web_search_tool_result")
}

/// Parameters for building an AnthropicCompletionRequest
pub struct AnthropicRequestParams<'a> {
    pub model: &'a str,
    pub request: CompletionRequest,
    pub prompt_caching: bool,
    /// Add a top-level `cache_control` field for Anthropic's automatic caching mode.
    pub automatic_caching: bool,
    /// TTL for the top-level cache_control. `None` omits the `ttl` field (API default is 5 min).
    pub automatic_caching_ttl: Option<CacheTtl>,
}

impl TryFrom<AnthropicRequestParams<'_>> for AnthropicCompletionRequest {
    type Error = CompletionError;

    fn try_from(params: AnthropicRequestParams<'_>) -> Result<Self, Self::Error> {
        let AnthropicRequestParams {
            model,
            request: mut req,
            prompt_caching,
            automatic_caching,
            automatic_caching_ttl,
        } = params;
        let chat_history = req.chat_history_with_documents();

        // Check if max_tokens is set, required for Anthropic
        let Some(max_tokens) = req.max_tokens else {
            return Err(CompletionError::RequestError(
                "`max_tokens` must be set for Anthropic".into(),
            ));
        };

        let (history_system, chat_history) = split_system_messages_from_history(
            chat_history,
            supports_mid_conversation_system_messages(model),
        );
        let mut full_history = vec![];
        full_history.extend(chat_history);

        let mut messages = full_history
            .into_iter()
            .map(Message::try_from)
            .collect::<Result<Vec<Message>, _>>()?;

        let mut additional_params_payload = req
            .additional_params
            .take()
            .unwrap_or(serde_json::Value::Null);
        let top_level_cache_control = resolve_top_level_cache_control(
            automatic_caching,
            automatic_caching_ttl,
            &mut additional_params_payload,
        )?;
        let mut tools = build_tool_definitions(req.tools, &mut additional_params_payload)?;

        // Convert system prompt to array format for cache_control support
        let mut system = if let Some(preamble) = req.preamble {
            if preamble.is_empty() {
                vec![]
            } else {
                vec![SystemContent::Text {
                    text: preamble,
                    cache_control: None,
                }]
            }
        } else {
            vec![]
        };
        system.extend(history_system);

        apply_prompt_cache_control(
            &mut system,
            &mut messages,
            &mut tools,
            prompt_caching,
            top_level_cache_control.as_ref(),
        )?;

        let output_config = if let Some(schema) = req.output_schema {
            let mut schema_value = schema.to_value();
            sanitize_schema(&mut schema_value);
            Some(OutputConfig {
                format: OutputFormat::JsonSchema {
                    schema: schema_value,
                },
            })
        } else {
            None
        };

        Ok(Self {
            model: model.to_string(),
            messages,
            max_tokens,
            system,
            temperature: req.temperature,
            tool_choice: req.tool_choice.and_then(|x| ToolChoice::try_from(x).ok()),
            tools,
            output_config,
            // Automatic caching: one top-level field; the API moves the breakpoint automatically.
            cache_control: top_level_cache_control,
            additional_params: if additional_params_payload.is_null() {
                None
            } else {
                Some(additional_params_payload)
            },
        })
    }
}

pub(super) fn extract_tools_from_additional_params(
    additional_params: &mut serde_json::Value,
) -> Result<Vec<serde_json::Value>, CompletionError> {
    if let Some(map) = additional_params.as_object_mut()
        && let Some(raw_tools) = map.remove("tools")
    {
        return serde_json::from_value::<Vec<serde_json::Value>>(raw_tools).map_err(|err| {
            CompletionError::RequestError(
                format!("Invalid Anthropic `additional_params.tools` payload: {err}").into(),
            )
        });
    }

    Ok(Vec::new())
}

pub(super) fn build_tool_definitions(
    tools: Vec<completion::ToolDefinition>,
    additional_params_payload: &mut serde_json::Value,
) -> Result<Vec<serde_json::Value>, CompletionError> {
    let mut additional_tools = extract_tools_from_additional_params(additional_params_payload)?;

    let mut tools = tools
        .into_iter()
        .map(|tool| ToolDefinition {
            name: tool.name,
            description: Some(tool.description),
            input_schema: tool.parameters,
            cache_control: None,
        })
        .map(serde_json::to_value)
        .collect::<Result<Vec<_>, _>>()?;
    tools.append(&mut additional_tools);

    Ok(tools)
}

impl<Ext, T> completion::CompletionModel for GenericCompletionModel<Ext, T>
where
    T: HttpClientExt + Clone + Default + WasmCompatSend + WasmCompatSync + 'static,
    Ext: AnthropicCompatibleProvider + Clone + WasmCompatSend + WasmCompatSync + 'static,
{
    type Response = CompletionResponse;
    type StreamingResponse = StreamingCompletionResponse;
    type Client = crate::client::Client<Ext, T>;

    fn make(client: &Self::Client, model: impl Into<String>) -> Self {
        Self::new(client.clone(), model.into())
    }

    async fn completion(
        &self,
        mut completion_request: completion::CompletionRequest,
    ) -> Result<completion::CompletionResponse<CompletionResponse>, CompletionError> {
        let request_model = completion_request
            .model
            .clone()
            .unwrap_or_else(|| self.model.clone());
        let span = if tracing::Span::current().is_disabled() {
            info_span!(
                target: "rig::completions",
                "chat",
                gen_ai.operation.name = "chat",
                gen_ai.provider.name = Ext::PROVIDER_NAME,
                gen_ai.request.model = &request_model,
                gen_ai.system_instructions = &completion_request.preamble,
                gen_ai.response.id = tracing::field::Empty,
                gen_ai.response.model = tracing::field::Empty,
                gen_ai.usage.output_tokens = tracing::field::Empty,
                gen_ai.usage.input_tokens = tracing::field::Empty,
                gen_ai.usage.cache_read.input_tokens = tracing::field::Empty,
                gen_ai.usage.cache_creation.input_tokens = tracing::field::Empty,
            )
        } else {
            tracing::Span::current()
        };

        // Check if max_tokens is set, required for Anthropic
        if completion_request.max_tokens.is_none() {
            if let Some(tokens) = self.default_max_tokens {
                completion_request.max_tokens = Some(tokens);
            } else {
                return Err(CompletionError::RequestError(
                    "`max_tokens` must be set for Anthropic".into(),
                ));
            }
        }

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: &request_model,
            request: completion_request,
            prompt_caching: self.prompt_caching,
            automatic_caching: self.automatic_caching,
            automatic_caching_ttl: self.automatic_caching_ttl.clone(),
        })?;

        if enabled!(Level::TRACE) {
            tracing::trace!(
                target: "rig::completions",
                "Anthropic completion request: {}",
                serde_json::to_string_pretty(&request)?
            );
        }

        async move {
            let request: Vec<u8> = serde_json::to_vec(&request)?;

            let req = self
                .client
                .post("/v1/messages")?
                .body(request)
                .map_err(|e| CompletionError::HttpError(e.into()))?;

            let response = self
                .client
                .send::<_, Bytes>(req)
                .await
                .map_err(CompletionError::HttpError)?;

            if response.status().is_success() {
                match serde_json::from_slice::<ApiResponse<CompletionResponse>>(
                    response
                        .into_body()
                        .await
                        .map_err(CompletionError::HttpError)?
                        .to_vec()
                        .as_slice(),
                )? {
                    ApiResponse::Message(completion) => {
                        let span = tracing::Span::current();
                        span.record_response_metadata(&completion);
                        span.record_token_usage(&completion.usage);
                        if enabled!(Level::TRACE) {
                            tracing::trace!(
                                target: "rig::completions",
                                "Anthropic completion response: {}",
                                serde_json::to_string_pretty(&completion)?
                            );
                        }
                        completion.try_into()
                    }
                    ApiResponse::Error(ApiErrorResponse { message }) => {
                        Err(CompletionError::ResponseError(message))
                    }
                }
            } else {
                let text: String = String::from_utf8_lossy(
                    &response
                        .into_body()
                        .await
                        .map_err(CompletionError::HttpError)?,
                )
                .into();
                Err(CompletionError::ProviderError(text))
            }
        }
        .instrument(span)
        .await
    }

    async fn stream(
        &self,
        request: CompletionRequest,
    ) -> Result<
        crate::streaming::StreamingCompletionResponse<Self::StreamingResponse>,
        CompletionError,
    > {
        GenericCompletionModel::stream(self, request).await
    }
}

#[derive(Debug, Deserialize)]
struct ApiErrorResponse {
    message: String,
}

#[derive(Debug, Deserialize)]
#[serde(tag = "type", rename_all = "snake_case")]
enum ApiResponse<T> {
    Message(T),
    Error(ApiErrorResponse),
}

#[cfg(test)]
mod tests {
    use super::*;
    use serde_json::json;
    use serde_path_to_error::deserialize;

    #[test]
    fn current_model_default_max_tokens_match_anthropic_limits() {
        assert_eq!(default_max_tokens_for_model(CLAUDE_OPUS_4_8), Some(128_000));
        assert_eq!(default_max_tokens_for_model(CLAUDE_OPUS_4_7), Some(128_000));
        assert_eq!(default_max_tokens_for_model(CLAUDE_OPUS_4_6), Some(128_000));
        assert_eq!(
            default_max_tokens_for_model(CLAUDE_SONNET_4_6),
            Some(64_000)
        );
        assert_eq!(default_max_tokens_for_model(CLAUDE_HAIKU_4_5), Some(64_000));
    }

    #[test]
    fn unknown_model_uses_conservative_default_max_tokens_fallback() {
        assert_eq!(default_max_tokens_for_model("claude-unknown"), None);
        assert_eq!(default_max_tokens_with_fallback("claude-unknown"), 2_048);
    }

    #[test]
    fn system_role_message_deserializes_and_round_trips() {
        let message: Message = serde_json::from_str(
            r#"
        {
            "role": "system",
            "content": "From now on, require explicit type annotations."
        }
        "#,
        )
        .unwrap();

        assert_eq!(message.role, Role::System);

        let generic: message::Message = message.try_into().unwrap();
        assert_eq!(
            generic,
            message::Message::System {
                content: "From now on, require explicit type annotations.".to_string()
            }
        );

        let provider: Message = generic.try_into().unwrap();
        assert_eq!(provider.role, Role::System);
    }

    #[test]
    fn test_deserialize_message() {
        let assistant_message_json = r#"
        {
            "role": "assistant",
            "content": "\n\nHello there, how may I assist you today?"
        }
        "#;

        let assistant_message_json2 = r#"
        {
            "role": "assistant",
            "content": [
                {
                    "type": "text",
                    "text": "\n\nHello there, how may I assist you today?"
                },
                {
                    "type": "tool_use",
                    "id": "toolu_01A09q90qw90lq917835lq9",
                    "name": "get_weather",
                    "input": {"location": "San Francisco, CA"}
                }
            ]
        }
        "#;

        let user_message_json = r#"
        {
            "role": "user",
            "content": [
                {
                    "type": "image",
                    "source": {
                        "type": "base64",
                        "media_type": "image/jpeg",
                        "data": "/9j/4AAQSkZJRg..."
                    }
                },
                {
                    "type": "text",
                    "text": "What is in this image?"
                },
                {
                    "type": "tool_result",
                    "tool_use_id": "toolu_01A09q90qw90lq917835lq9",
                    "content": "15 degrees"
                }
            ]
        }
        "#;

        let assistant_message: Message = {
            let jd = &mut serde_json::Deserializer::from_str(assistant_message_json);
            deserialize(jd).unwrap_or_else(|err| {
                panic!("Deserialization error at {}: {}", err.path(), err);
            })
        };

        let assistant_message2: Message = {
            let jd = &mut serde_json::Deserializer::from_str(assistant_message_json2);
            deserialize(jd).unwrap_or_else(|err| {
                panic!("Deserialization error at {}: {}", err.path(), err);
            })
        };

        let user_message: Message = {
            let jd = &mut serde_json::Deserializer::from_str(user_message_json);
            deserialize(jd).unwrap_or_else(|err| {
                panic!("Deserialization error at {}: {}", err.path(), err);
            })
        };

        let Message { role, content } = assistant_message;
        assert_eq!(role, Role::Assistant);
        assert_eq!(
            content.first(),
            Content::Text {
                text: "\n\nHello there, how may I assist you today?".to_owned(),
                citations: Vec::new(),
                cache_control: None,
            }
        );

        let Message { role, content } = assistant_message2;
        {
            assert_eq!(role, Role::Assistant);
            assert_eq!(content.len(), 2);

            let mut iter = content.into_iter();

            match iter.next().unwrap() {
                Content::Text { text, .. } => {
                    assert_eq!(text, "\n\nHello there, how may I assist you today?");
                }
                _ => panic!("Expected text content"),
            }

            match iter.next().unwrap() {
                Content::ToolUse { id, name, input } => {
                    assert_eq!(id, "toolu_01A09q90qw90lq917835lq9");
                    assert_eq!(name, "get_weather");
                    assert_eq!(input, json!({"location": "San Francisco, CA"}));
                }
                _ => panic!("Expected tool use content"),
            }

            assert_eq!(iter.next(), None);
        }

        let Message { role, content } = user_message;
        {
            assert_eq!(role, Role::User);
            assert_eq!(content.len(), 3);

            let mut iter = content.into_iter();

            match iter.next().unwrap() {
                Content::Image { source, .. } => {
                    assert_eq!(
                        source,
                        ImageSource::Base64 {
                            data: "/9j/4AAQSkZJRg...".to_owned(),
                            media_type: ImageFormat::JPEG,
                        }
                    );
                }
                _ => panic!("Expected image content"),
            }

            match iter.next().unwrap() {
                Content::Text { text, .. } => {
                    assert_eq!(text, "What is in this image?");
                }
                _ => panic!("Expected text content"),
            }

            match iter.next().unwrap() {
                Content::ToolResult {
                    tool_use_id,
                    content,
                    is_error,
                    ..
                } => {
                    assert_eq!(tool_use_id, "toolu_01A09q90qw90lq917835lq9");
                    assert_eq!(
                        content.first(),
                        ToolResultContent::Text {
                            text: "15 degrees".to_owned()
                        }
                    );
                    assert_eq!(is_error, None);
                }
                _ => panic!("Expected tool result content"),
            }

            assert_eq!(iter.next(), None);
        }
    }

    #[test]
    fn test_message_to_message_conversion() {
        let user_message: Message = serde_json::from_str(
            r#"
        {
            "role": "user",
            "content": [
                {
                    "type": "image",
                    "source": {
                        "type": "base64",
                        "media_type": "image/jpeg",
                        "data": "/9j/4AAQSkZJRg..."
                    }
                },
                {
                    "type": "text",
                    "text": "What is in this image?"
                },
                {
                    "type": "document",
                    "source": {
                        "type": "base64",
                        "data": "base64_encoded_pdf_data",
                        "media_type": "application/pdf"
                    }
                }
            ]
        }
        "#,
        )
        .unwrap();

        let assistant_message = Message {
            role: Role::Assistant,
            content: OneOrMany::one(Content::ToolUse {
                id: "toolu_01A09q90qw90lq917835lq9".to_string(),
                name: "get_weather".to_string(),
                input: json!({"location": "San Francisco, CA"}),
            }),
        };

        let tool_message = Message {
            role: Role::User,
            content: OneOrMany::one(Content::ToolResult {
                tool_use_id: "toolu_01A09q90qw90lq917835lq9".to_string(),
                content: OneOrMany::one(ToolResultContent::Text {
                    text: "15 degrees".to_string(),
                }),
                is_error: None,
                cache_control: None,
            }),
        };

        let converted_user_message: message::Message = user_message.clone().try_into().unwrap();
        let converted_assistant_message: message::Message =
            assistant_message.clone().try_into().unwrap();
        let converted_tool_message: message::Message = tool_message.clone().try_into().unwrap();

        match converted_user_message.clone() {
            message::Message::User { content } => {
                assert_eq!(content.len(), 3);

                let mut iter = content.into_iter();

                match iter.next().unwrap() {
                    message::UserContent::Image(message::Image {
                        data, media_type, ..
                    }) => {
                        assert_eq!(data, DocumentSourceKind::base64("/9j/4AAQSkZJRg..."));
                        assert_eq!(media_type, Some(message::ImageMediaType::JPEG));
                    }
                    _ => panic!("Expected image content"),
                }

                match iter.next().unwrap() {
                    message::UserContent::Text(message::Text { text, .. }) => {
                        assert_eq!(text, "What is in this image?");
                    }
                    _ => panic!("Expected text content"),
                }

                match iter.next().unwrap() {
                    message::UserContent::Document(message::Document {
                        data, media_type, ..
                    }) => {
                        assert_eq!(
                            data,
                            DocumentSourceKind::String("base64_encoded_pdf_data".into())
                        );
                        assert_eq!(media_type, Some(message::DocumentMediaType::PDF));
                    }
                    _ => panic!("Expected document content"),
                }

                assert_eq!(iter.next(), None);
            }
            _ => panic!("Expected user message"),
        }

        match converted_tool_message.clone() {
            message::Message::User { content } => {
                let message::ToolResult { id, content, .. } = match content.first() {
                    message::UserContent::ToolResult(tool_result) => tool_result,
                    _ => panic!("Expected tool result content"),
                };
                assert_eq!(id, "toolu_01A09q90qw90lq917835lq9");
                match content.first() {
                    message::ToolResultContent::Text(message::Text { text, .. }) => {
                        assert_eq!(text, "15 degrees");
                    }
                    _ => panic!("Expected text content"),
                }
            }
            _ => panic!("Expected tool result content"),
        }

        match converted_assistant_message.clone() {
            message::Message::Assistant { content, .. } => {
                assert_eq!(content.len(), 1);

                match content.first() {
                    message::AssistantContent::ToolCall(message::ToolCall {
                        id, function, ..
                    }) => {
                        assert_eq!(id, "toolu_01A09q90qw90lq917835lq9");
                        assert_eq!(function.name, "get_weather");
                        assert_eq!(function.arguments, json!({"location": "San Francisco, CA"}));
                    }
                    _ => panic!("Expected tool call content"),
                }
            }
            _ => panic!("Expected assistant message"),
        }

        let original_user_message: Message = converted_user_message.try_into().unwrap();
        let original_assistant_message: Message = converted_assistant_message.try_into().unwrap();
        let original_tool_message: Message = converted_tool_message.try_into().unwrap();

        assert_eq!(user_message, original_user_message);
        assert_eq!(assistant_message, original_assistant_message);
        assert_eq!(tool_message, original_tool_message);
    }

    #[test]
    fn test_content_format_conversion() {
        use crate::completion::message::ContentFormat;

        let source_type: SourceType = ContentFormat::Url.try_into().unwrap();
        assert_eq!(source_type, SourceType::URL);

        let content_format: ContentFormat = SourceType::URL.into();
        assert_eq!(content_format, ContentFormat::Url);

        let source_type: SourceType = ContentFormat::Base64.try_into().unwrap();
        assert_eq!(source_type, SourceType::BASE64);

        let content_format: ContentFormat = SourceType::BASE64.into();
        assert_eq!(content_format, ContentFormat::Base64);

        let source_type: SourceType = ContentFormat::String.try_into().unwrap();
        assert_eq!(source_type, SourceType::TEXT);

        let content_format: ContentFormat = SourceType::TEXT.into();
        assert_eq!(content_format, ContentFormat::String);
    }

    #[test]
    fn test_cache_control_serialization() {
        // Test SystemContent with cache_control
        let system = SystemContent::Text {
            text: "You are a helpful assistant.".to_string(),
            cache_control: Some(CacheControl::ephemeral()),
        };
        let json = serde_json::to_string(&system).unwrap();
        assert!(json.contains(r#""cache_control":{"type":"ephemeral"}"#));
        assert!(json.contains(r#""type":"text""#));

        // Test SystemContent without cache_control (should not have cache_control field)
        let system_no_cache = SystemContent::Text {
            text: "Hello".to_string(),
            cache_control: None,
        };
        let json_no_cache = serde_json::to_string(&system_no_cache).unwrap();
        assert!(!json_no_cache.contains("cache_control"));

        // Test Content::Text with cache_control
        let content = Content::Text {
            text: "Test message".to_string(),
            citations: Vec::new(),
            cache_control: Some(CacheControl::ephemeral()),
        };
        let json_content = serde_json::to_string(&content).unwrap();
        assert!(json_content.contains(r#""cache_control":{"type":"ephemeral"}"#));

        // Test apply_cache_control function
        let mut system_vec = vec![SystemContent::Text {
            text: "System prompt".to_string(),
            cache_control: None,
        }];
        let mut messages = vec![
            Message {
                role: Role::User,
                content: OneOrMany::one(Content::Text {
                    text: "First message".to_string(),
                    citations: Vec::new(),
                    cache_control: None,
                }),
            },
            Message {
                role: Role::Assistant,
                content: OneOrMany::one(Content::Text {
                    text: "Response".to_string(),
                    citations: Vec::new(),
                    cache_control: None,
                }),
            },
        ];

        apply_cache_control(&mut system_vec, &mut messages);

        // System should have cache_control
        match &system_vec[0] {
            SystemContent::Text { cache_control, .. } => {
                assert!(cache_control.is_some());
            }
        }

        // Only the last content block of last message should have cache_control
        // First message should NOT have cache_control
        for content in messages[0].content.iter() {
            if let Content::Text { cache_control, .. } = content {
                assert!(cache_control.is_none());
            }
        }

        // Last message SHOULD have cache_control
        for content in messages[1].content.iter() {
            if let Content::Text { cache_control, .. } = content {
                assert!(cache_control.is_some());
            }
        }
    }

    fn generic_tool(name: &str) -> completion::ToolDefinition {
        completion::ToolDefinition {
            name: name.to_string(),
            description: format!("{name} description"),
            parameters: json!({
                "type": "object",
                "properties": {}
            }),
        }
    }

    fn completion_request_with_tools(
        tools: Vec<completion::ToolDefinition>,
        additional_params: Option<serde_json::Value>,
    ) -> CompletionRequest {
        CompletionRequest {
            model: None,
            preamble: Some("System prompt".to_string()),
            chat_history: OneOrMany::one(message::Message::from("Hello")),
            documents: Vec::new(),
            tools,
            temperature: None,
            max_tokens: Some(64),
            tool_choice: None,
            additional_params,
            output_schema: None,
        }
    }

    fn completion_request_with_history(
        chat_history: Vec<message::Message>,
        preamble: Option<String>,
    ) -> CompletionRequest {
        CompletionRequest {
            model: None,
            preamble,
            chat_history: OneOrMany::many(chat_history).unwrap(),
            documents: Vec::new(),
            tools: Vec::new(),
            temperature: None,
            max_tokens: Some(64),
            tool_choice: None,
            additional_params: None,
            output_schema: None,
        }
    }

    fn system_has_cache_control(value: &serde_json::Value) -> bool {
        value["system"]
            .as_array()
            .and_then(|blocks| blocks.last())
            .and_then(|block| block.get("cache_control"))
            .is_some()
    }

    fn last_message_has_cache_control(value: &serde_json::Value) -> bool {
        value["messages"]
            .as_array()
            .and_then(|messages| messages.last())
            .and_then(|message| message["content"].as_array())
            .and_then(|content| content.last())
            .and_then(|content| content.get("cache_control"))
            .is_some()
    }

    #[test]
    fn opus_4_8_preserves_mid_conversation_system_message() {
        let request = completion_request_with_history(
            vec![
                message::Message::System {
                    content: "Global history instruction.".to_string(),
                },
                message::Message::from("Review this code."),
                message::Message::System {
                    content: "From now on, require explicit type annotations.".to_string(),
                },
            ],
            Some("Top-level instruction.".to_string()),
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: CLAUDE_OPUS_4_8,
            request,
            prompt_caching: false,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        assert_eq!(value["system"][0]["text"], "Top-level instruction.");
        assert_eq!(value["system"][1]["text"], "Global history instruction.");

        let messages = value["messages"].as_array().unwrap();
        assert_eq!(messages.len(), 2);
        assert_eq!(messages[0]["role"], "user");
        assert_eq!(messages[1]["role"], "system");
        assert_eq!(
            messages[1]["content"][0]["text"],
            "From now on, require explicit type annotations."
        );
    }

    #[test]
    fn opus_4_8_preserves_mid_conversation_system_message_before_assistant_turn() {
        let request = completion_request_with_history(
            vec![
                message::Message::user("Review this code."),
                message::Message::System {
                    content: "From now on, require explicit type annotations.".to_string(),
                },
                message::Message::assistant("I will enforce explicit type annotations."),
            ],
            None,
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: CLAUDE_OPUS_4_8,
            request,
            prompt_caching: false,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        let messages = value["messages"].as_array().unwrap();
        assert_eq!(messages.len(), 3);
        assert_eq!(messages[0]["role"], "user");
        assert_eq!(messages[1]["role"], "system");
        assert_eq!(messages[2]["role"], "assistant");
        assert!(value.get("system").is_none());
    }

    #[test]
    fn opus_4_8_hoists_leading_system_message_when_documents_are_present() {
        let mut request = completion_request_with_history(
            vec![
                message::Message::System {
                    content: "Global history instruction.".to_string(),
                },
                message::Message::assistant("Acknowledged."),
                message::Message::System {
                    content: "Mid-conversation instruction.".to_string(),
                },
                message::Message::user("Answer from the document."),
            ],
            None,
        );
        request.documents = vec![completion::Document {
            id: "doc".to_string(),
            text: "Document context.".to_string(),
            additional_props: Default::default(),
        }];

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: CLAUDE_OPUS_4_8,
            request,
            prompt_caching: false,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        assert_eq!(value["system"][0]["text"], "Global history instruction.");
        assert_eq!(value["system"][1]["text"], "Mid-conversation instruction.");

        let messages = value["messages"].as_array().unwrap();
        assert_eq!(messages.len(), 3);
        assert_eq!(messages[0]["role"], "user");
        assert_eq!(messages[1]["role"], "assistant");
        assert_eq!(messages[2]["role"], "user");
        assert!(
            messages[0].to_string().contains("<file id: doc>"),
            "document message should follow top-level system: {messages:?}"
        );
        assert_eq!(
            messages
                .iter()
                .filter(|message| message.to_string().contains("<file id: doc>"))
                .count(),
            1,
            "document message should appear exactly once: {messages:?}"
        );
        assert!(
            messages
                .iter()
                .all(|message| message["role"].as_str() != Some("system"))
        );
    }

    #[test]
    fn opus_4_8_preserves_system_message_after_assistant_server_tool_result() {
        let request = completion_request_with_history(
            vec![
                message::Message::Assistant {
                    id: None,
                    content: OneOrMany::many([
                        message::AssistantContent::Text(message::Text {
                            text: String::new(),
                            additional_params: Some(json!({
                                ANTHROPIC_RAW_CONTENT_KEY: {
                                    "type": "server_tool_use",
                                    "id": "srvtoolu_01",
                                    "name": "web_search",
                                    "input": {
                                        "query": "clear daytime sky color"
                                    }
                                }
                            })),
                        }),
                        message::AssistantContent::Text(message::Text {
                            text: String::new(),
                            additional_params: Some(json!({
                                ANTHROPIC_RAW_CONTENT_KEY: {
                                    "type": "web_search_tool_result",
                                    "tool_use_id": "srvtoolu_01",
                                    "content": {
                                        "type": "web_search_tool_result_error",
                                        "error_code": "unavailable"
                                    }
                                }
                            })),
                        }),
                    ])
                    .unwrap(),
                },
                message::Message::System {
                    content: "For the rest of this conversation, answer in Spanish.".to_string(),
                },
                message::Message::assistant("Entendido."),
            ],
            None,
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: CLAUDE_OPUS_4_8,
            request,
            prompt_caching: false,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        assert!(value.get("system").is_none());

        let messages = value["messages"].as_array().unwrap();
        assert_eq!(messages.len(), 3);
        assert_eq!(messages[0]["role"], "assistant");
        assert_eq!(messages[0]["content"][0]["type"], "server_tool_use");
        assert_eq!(messages[0]["content"][1]["type"], "web_search_tool_result");
        assert_eq!(messages[1]["role"], "system");
        assert_eq!(
            messages[1]["content"][0]["text"],
            "For the rest of this conversation, answer in Spanish."
        );
        assert_eq!(messages[2]["role"], "assistant");
    }

    #[test]
    fn opus_4_8_preserves_system_message_after_assistant_server_tool_use() {
        let request = completion_request_with_history(
            vec![
                message::Message::Assistant {
                    id: None,
                    content: OneOrMany::one(message::AssistantContent::Text(message::Text {
                        text: String::new(),
                        additional_params: Some(json!({
                            ANTHROPIC_RAW_CONTENT_KEY: {
                                "type": "server_tool_use",
                                "id": "srvtoolu_01",
                                "name": "web_search",
                                "input": {
                                    "query": "clear daytime sky color"
                                }
                            }
                        })),
                    })),
                },
                message::Message::System {
                    content: "For the rest of this conversation, answer in Spanish.".to_string(),
                },
                message::Message::assistant("Entendido."),
            ],
            None,
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: CLAUDE_OPUS_4_8,
            request,
            prompt_caching: false,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        assert!(value.get("system").is_none());

        let messages = value["messages"].as_array().unwrap();
        assert_eq!(messages.len(), 3);
        assert_eq!(messages[0]["role"], "assistant");
        assert_eq!(messages[0]["content"][0]["type"], "server_tool_use");
        assert_eq!(messages[1]["role"], "system");
        assert_eq!(
            messages[1]["content"][0]["text"],
            "For the rest of this conversation, answer in Spanish."
        );
        assert_eq!(messages[2]["role"], "assistant");
    }

    #[test]
    fn opus_4_8_hoists_system_message_in_invalid_mid_conversation_position() {
        let request = completion_request_with_history(
            vec![
                message::Message::user("Review this code."),
                message::Message::System {
                    content: "From now on, require explicit type annotations.".to_string(),
                },
                message::Message::user("Now review this other file."),
            ],
            None,
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: CLAUDE_OPUS_4_8,
            request,
            prompt_caching: false,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        assert_eq!(
            value["system"][0]["text"],
            "From now on, require explicit type annotations."
        );

        let messages = value["messages"].as_array().unwrap();
        assert_eq!(messages.len(), 2);
        assert_eq!(messages[0]["role"], "user");
        assert_eq!(messages[1]["role"], "user");
    }

    #[test]
    fn older_anthropic_models_hoist_mid_conversation_system_message() {
        let request = completion_request_with_history(
            vec![
                message::Message::from("Review this code."),
                message::Message::System {
                    content: "From now on, require explicit type annotations.".to_string(),
                },
            ],
            None,
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: CLAUDE_OPUS_4_7,
            request,
            prompt_caching: false,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        assert_eq!(
            value["system"][0]["text"],
            "From now on, require explicit type annotations."
        );

        let messages = value["messages"].as_array().unwrap();
        assert_eq!(messages.len(), 1);
        assert_eq!(messages[0]["role"], "user");
    }

    #[test]
    fn test_tool_definition_cache_control_serialization() {
        let tool = ToolDefinition {
            name: "cached_tool".to_string(),
            description: Some("Cached tool".to_string()),
            input_schema: json!({"type": "object"}),
            cache_control: Some(CacheControl::ephemeral()),
        };

        let value = serde_json::to_value(tool).unwrap();
        assert_eq!(value["cache_control"]["type"], "ephemeral");

        let tool_without_cache = ToolDefinition {
            name: "uncached_tool".to_string(),
            description: Some("Uncached tool".to_string()),
            input_schema: json!({"type": "object"}),
            cache_control: None,
        };

        let value = serde_json::to_value(tool_without_cache).unwrap();
        assert!(value.get("cache_control").is_none());
    }

    #[test]
    fn test_apply_tool_cache_control_marks_only_final_tool() {
        let mut tools = vec![
            json!({
                "name": "first_tool",
                "description": "First tool",
                "input_schema": {"type": "object"}
            }),
            json!({
                "name": "second_tool",
                "description": "Second tool",
                "input_schema": {"type": "object"}
            }),
        ];

        let mut remaining_cache_markers = 4;
        apply_tool_cache_control(
            &mut tools,
            &mut remaining_cache_markers,
            &CacheControl::ephemeral(),
        )
        .unwrap();

        assert!(tools[0].get("cache_control").is_none());
        assert_eq!(tools[1]["cache_control"]["type"], "ephemeral");
        assert_eq!(remaining_cache_markers, 3);
    }

    #[test]
    fn test_prompt_caching_skips_final_deferred_tool_in_request() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "tools": [
                    {
                        "name": "regular_tool",
                        "description": "Regular tool",
                        "input_schema": {"type": "object"}
                    },
                    {
                        "name": "deferred_tool",
                        "description": "Deferred tool",
                        "input_schema": {"type": "object"},
                        "defer_loading": true
                    }
                ]
            })),
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        let tools = value["tools"].as_array().unwrap();
        assert_eq!(tools[0]["name"], "regular_tool");
        assert_eq!(tools[0]["cache_control"]["type"], "ephemeral");
        assert_eq!(tools[1]["name"], "deferred_tool");
        assert!(tools[1].get("cache_control").is_none());
    }

    #[test]
    fn test_prompt_caching_preserves_existing_final_tool_cache_control() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "tools": [{
                    "name": "cached_tool",
                    "description": "Cached tool",
                    "input_schema": {"type": "object"},
                    "cache_control": {"type": "ephemeral", "ttl": "1h"}
                }]
            })),
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        let tools = value["tools"].as_array().unwrap();
        assert_eq!(tools[0]["cache_control"]["type"], "ephemeral");
        assert_eq!(tools[0]["cache_control"]["ttl"], "1h");
    }

    #[test]
    fn test_prompt_caching_all_deferred_tools_do_not_receive_cache_control() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "tools": [
                    {
                        "name": "first_deferred_tool",
                        "description": "First deferred tool",
                        "input_schema": {"type": "object"},
                        "defer_loading": true
                    },
                    {
                        "name": "second_deferred_tool",
                        "description": "Second deferred tool",
                        "input_schema": {"type": "object"},
                        "defer_loading": true
                    }
                ]
            })),
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        let tools = value["tools"].as_array().unwrap();
        assert!(tools[0].get("cache_control").is_none());
        assert!(tools[1].get("cache_control").is_none());
    }

    #[test]
    fn test_prompt_caching_preserves_earlier_tool_cache_control() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "tools": [
                    {
                        "name": "earlier_tool",
                        "description": "Earlier tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral", "ttl": "1h"}
                    },
                    {
                        "name": "later_tool",
                        "description": "Later tool",
                        "input_schema": {"type": "object"}
                    }
                ]
            })),
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        let tools = value["tools"].as_array().unwrap();
        assert_eq!(tools[0]["cache_control"]["type"], "ephemeral");
        assert_eq!(tools[0]["cache_control"]["ttl"], "1h");
        assert_eq!(tools[1]["cache_control"]["type"], "ephemeral");
    }

    #[test]
    fn test_prompt_caching_deferred_marker_does_not_suppress_loaded_tool_marker() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "tools": [
                    {
                        "name": "regular_tool",
                        "description": "Regular tool",
                        "input_schema": {"type": "object"}
                    },
                    {
                        "name": "deferred_cached_tool",
                        "description": "Deferred cached tool",
                        "input_schema": {"type": "object"},
                        "defer_loading": true,
                        "cache_control": {"type": "ephemeral"}
                    }
                ]
            })),
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        let tools = value["tools"].as_array().unwrap();
        assert_eq!(tools[0]["cache_control"]["type"], "ephemeral");
        assert_eq!(tools[1]["cache_control"]["type"], "ephemeral");
    }

    #[test]
    fn test_prompt_caching_errors_when_tool_cache_control_ttl_order_is_invalid() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "tools": [
                    {
                        "name": "first_cached_tool",
                        "description": "First cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "second_cached_tool",
                        "description": "Second cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral", "ttl": "1h"}
                    }
                ]
            })),
        );

        let err = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap_err();

        assert!(err.to_string().contains("ttl `1h`"));
    }

    #[test]
    fn test_prompt_caching_preserves_valid_mixed_ttl_tool_cache_controls() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "tools": [
                    {
                        "name": "first_cached_tool",
                        "description": "First cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral", "ttl": "1h"}
                    },
                    {
                        "name": "second_cached_tool",
                        "description": "Second cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    }
                ]
            })),
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        let tools = value["tools"].as_array().unwrap();
        assert_eq!(tools[0]["cache_control"]["type"], "ephemeral");
        assert_eq!(tools[0]["cache_control"]["ttl"], "1h");
        assert_eq!(tools[1]["cache_control"]["type"], "ephemeral");
        assert!(tools[1]["cache_control"].get("ttl").is_none());
    }

    #[test]
    fn test_prompt_caching_preserves_deferred_tool_cache_control() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "tools": [{
                    "name": "deferred_cached_tool",
                    "description": "Deferred cached tool",
                    "input_schema": {"type": "object"},
                    "defer_loading": true,
                    "cache_control": {"type": "ephemeral"}
                }]
            })),
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        let tools = value["tools"].as_array().unwrap();
        assert_eq!(tools[0]["cache_control"]["type"], "ephemeral");
    }

    #[test]
    fn test_prompt_caching_budget_preserves_three_tool_markers_and_skips_message() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "tools": [
                    {
                        "name": "first_cached_tool",
                        "description": "First cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "second_cached_tool",
                        "description": "Second cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "third_cached_tool",
                        "description": "Third cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    }
                ]
            })),
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        let tools = value["tools"].as_array().unwrap();
        assert_eq!(tools[0]["cache_control"]["type"], "ephemeral");
        assert_eq!(tools[1]["cache_control"]["type"], "ephemeral");
        assert_eq!(tools[2]["cache_control"]["type"], "ephemeral");
        assert!(system_has_cache_control(&value));
        assert!(!last_message_has_cache_control(&value));
    }

    #[test]
    fn test_prompt_caching_errors_when_explicit_tool_markers_exceed_budget() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "tools": [
                    {
                        "name": "first_cached_tool",
                        "description": "First cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "second_cached_tool",
                        "description": "Second cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "third_cached_tool",
                        "description": "Third cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "fourth_cached_tool",
                        "description": "Fourth cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "fifth_cached_tool",
                        "description": "Fifth cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    }
                ]
            })),
        );

        let err = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap_err();

        assert!(err.to_string().contains("Too many Anthropic tool"));
    }

    #[test]
    fn test_prompt_caching_errors_when_final_tool_marker_has_no_budget() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "tools": [
                    {
                        "name": "first_cached_tool",
                        "description": "First cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "second_cached_tool",
                        "description": "Second cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "third_cached_tool",
                        "description": "Third cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "fourth_cached_tool",
                        "description": "Fourth cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "final_uncached_tool",
                        "description": "Final uncached tool",
                        "input_schema": {"type": "object"}
                    }
                ]
            })),
        );

        let err = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap_err();

        assert!(err.to_string().contains("final non-deferred tool"));
    }

    #[test]
    fn test_prompt_caching_replaces_null_final_tool_cache_control() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "tools": [{
                    "name": "final_tool",
                    "description": "Final tool",
                    "input_schema": {"type": "object"},
                    "cache_control": null
                }]
            })),
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        let tools = value["tools"].as_array().unwrap();
        assert_eq!(tools[0]["cache_control"]["type"], "ephemeral");
    }

    #[test]
    fn test_prompt_caching_ignores_null_tool_cache_control_when_budgeting() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "tools": [
                    {
                        "name": "first_null_tool",
                        "description": "First null tool",
                        "input_schema": {"type": "object"},
                        "cache_control": null
                    },
                    {
                        "name": "second_null_tool",
                        "description": "Second null tool",
                        "input_schema": {"type": "object"},
                        "cache_control": null
                    },
                    {
                        "name": "third_null_tool",
                        "description": "Third null tool",
                        "input_schema": {"type": "object"},
                        "cache_control": null
                    },
                    {
                        "name": "fourth_null_tool",
                        "description": "Fourth null tool",
                        "input_schema": {"type": "object"},
                        "cache_control": null
                    },
                    {
                        "name": "final_uncached_tool",
                        "description": "Final uncached tool",
                        "input_schema": {"type": "object"}
                    }
                ]
            })),
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        let tools = value["tools"].as_array().unwrap();
        assert!(tools[0].get("cache_control").is_none());
        assert!(tools[1].get("cache_control").is_none());
        assert!(tools[2].get("cache_control").is_none());
        assert!(tools[3].get("cache_control").is_none());
        assert_eq!(tools[4]["cache_control"]["type"], "ephemeral");
    }

    #[test]
    fn test_prompt_caching_preserves_non_null_provider_tool_cache_control_escape_hatch() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "tools": [{
                    "name": "provider_tool",
                    "description": "Provider tool",
                    "input_schema": {"type": "object"},
                    "cache_control": {"type": "provider_specific"}
                }]
            })),
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        let tools = value["tools"].as_array().unwrap();
        assert_eq!(tools[0]["cache_control"]["type"], "provider_specific");
    }

    #[test]
    fn test_prompt_caching_automatic_mode_uses_reduced_marker_budget() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "tools": [
                    {
                        "name": "first_cached_tool",
                        "description": "First cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "second_cached_tool",
                        "description": "Second cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "third_cached_tool",
                        "description": "Third cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    }
                ]
            })),
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: true,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        let tools = value["tools"].as_array().unwrap();
        assert_eq!(tools[0]["cache_control"]["type"], "ephemeral");
        assert_eq!(tools[1]["cache_control"]["type"], "ephemeral");
        assert_eq!(tools[2]["cache_control"]["type"], "ephemeral");
        assert_eq!(value["cache_control"]["type"], "ephemeral");
        assert!(!system_has_cache_control(&value));
        assert!(!last_message_has_cache_control(&value));
    }

    #[test]
    fn test_prompt_caching_automatic_mode_errors_when_final_tool_marker_has_no_budget() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "tools": [
                    {
                        "name": "first_cached_tool",
                        "description": "First cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "second_cached_tool",
                        "description": "Second cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "third_cached_tool",
                        "description": "Third cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "final_uncached_tool",
                        "description": "Final uncached tool",
                        "input_schema": {"type": "object"}
                    }
                ]
            })),
        );

        let err = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: true,
            automatic_caching_ttl: None,
        })
        .unwrap_err();

        assert!(err.to_string().contains("final non-deferred tool"));
    }

    #[test]
    fn test_automatic_caching_errors_when_explicit_tool_markers_exhaust_budget() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "tools": [
                    {
                        "name": "first_cached_tool",
                        "description": "First cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "second_cached_tool",
                        "description": "Second cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "third_cached_tool",
                        "description": "Third cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "fourth_cached_tool",
                        "description": "Fourth cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    }
                ]
            })),
        );

        let err = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: false,
            automatic_caching: true,
            automatic_caching_ttl: None,
        })
        .unwrap_err();

        assert!(err.to_string().contains("Too many Anthropic tool"));
    }

    #[test]
    fn test_automatic_caching_1h_errors_with_explicit_five_minute_tool_marker() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "tools": [{
                    "name": "cached_tool",
                    "description": "Cached tool",
                    "input_schema": {"type": "object"},
                    "cache_control": {"type": "ephemeral"}
                }]
            })),
        );

        let err = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: false,
            automatic_caching: true,
            automatic_caching_ttl: Some(CacheTtl::OneHour),
        })
        .unwrap_err();

        assert!(err.to_string().contains("ttl `1h`"));
    }

    #[test]
    fn test_prompt_and_automatic_caching_1h_uses_1h_generated_markers() {
        let request = completion_request_with_tools(vec![generic_tool("cached_tool")], None);

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: true,
            automatic_caching_ttl: Some(CacheTtl::OneHour),
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        let tools = value["tools"].as_array().unwrap();
        assert_eq!(tools[0]["cache_control"]["type"], "ephemeral");
        assert_eq!(tools[0]["cache_control"]["ttl"], "1h");
        assert_eq!(
            value["system"]
                .as_array()
                .and_then(|blocks| blocks.last())
                .and_then(|block| block["cache_control"].get("ttl")),
            Some(&json!("1h"))
        );
        assert_eq!(value["cache_control"]["ttl"], "1h");
        assert!(!last_message_has_cache_control(&value));
    }

    #[test]
    fn test_prompt_and_raw_top_level_automatic_caching_1h_uses_1h_generated_markers() {
        let request = completion_request_with_tools(
            vec![generic_tool("cached_tool")],
            Some(json!({
                "cache_control": {"type": "ephemeral", "ttl": "1h"},
                "metadata": {"source": "test"}
            })),
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: true,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        let tools = value["tools"].as_array().unwrap();
        assert_eq!(tools[0]["cache_control"]["type"], "ephemeral");
        assert_eq!(tools[0]["cache_control"]["ttl"], "1h");
        assert_eq!(
            value["system"]
                .as_array()
                .and_then(|blocks| blocks.last())
                .and_then(|block| block["cache_control"].get("ttl")),
            Some(&json!("1h"))
        );
        assert_eq!(value["cache_control"]["ttl"], "1h");
        assert_eq!(value["metadata"]["source"], "test");
        assert!(!last_message_has_cache_control(&value));
    }

    #[test]
    fn test_prompt_caching_uses_raw_top_level_cache_control_ttl() {
        let request = completion_request_with_tools(
            vec![generic_tool("cached_tool")],
            Some(json!({
                "cache_control": {"type": "ephemeral", "ttl": "1h"},
                "metadata": {"source": "raw-cache-control"}
            })),
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        let tools = value["tools"].as_array().unwrap();
        assert_eq!(tools[0]["cache_control"]["type"], "ephemeral");
        assert_eq!(tools[0]["cache_control"]["ttl"], "1h");
        assert_eq!(
            value["system"]
                .as_array()
                .and_then(|blocks| blocks.last())
                .and_then(|block| block["cache_control"].get("ttl")),
            Some(&json!("1h"))
        );
        assert_eq!(value["cache_control"]["ttl"], "1h");
        assert_eq!(value["metadata"]["source"], "raw-cache-control");
        assert!(!last_message_has_cache_control(&value));
    }

    #[test]
    fn test_raw_top_level_automatic_caching_reduces_marker_budget() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "cache_control": {"type": "ephemeral"},
                "tools": [
                    {
                        "name": "first_cached_tool",
                        "description": "First cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "second_cached_tool",
                        "description": "Second cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "third_cached_tool",
                        "description": "Third cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    },
                    {
                        "name": "fourth_cached_tool",
                        "description": "Fourth cached tool",
                        "input_schema": {"type": "object"},
                        "cache_control": {"type": "ephemeral"}
                    }
                ]
            })),
        );

        let err = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: false,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap_err();

        assert!(err.to_string().contains("Too many Anthropic tool"));
    }

    #[test]
    fn test_raw_top_level_automatic_caching_1h_errors_after_explicit_five_minute_tool_marker() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "cache_control": {"type": "ephemeral", "ttl": "1h"},
                "tools": [{
                    "name": "cached_tool",
                    "description": "Cached tool",
                    "input_schema": {"type": "object"},
                    "cache_control": {"type": "ephemeral"}
                }]
            })),
        );

        let err = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: false,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap_err();

        assert!(err.to_string().contains("ttl `1h`"));
    }

    #[test]
    fn test_typed_automatic_caching_ttl_errors_on_conflicting_raw_top_level_ttl() {
        let request = completion_request_with_tools(
            Vec::new(),
            Some(json!({
                "cache_control": {"type": "ephemeral"}
            })),
        );

        let err = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: false,
            automatic_caching: true,
            automatic_caching_ttl: Some(CacheTtl::OneHour),
        })
        .unwrap_err();

        assert!(
            err.to_string()
                .contains("conflicts with the typed automatic caching TTL")
        );
    }

    #[test]
    fn test_prompt_caching_marks_final_tool_in_request() {
        let request = completion_request_with_tools(
            vec![generic_tool("first_tool"), generic_tool("second_tool")],
            None,
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        let tools = value["tools"].as_array().unwrap();
        assert_eq!(tools.len(), 2);
        assert!(tools[0].get("cache_control").is_none());
        assert_eq!(tools[1]["cache_control"]["type"], "ephemeral");
    }

    #[test]
    fn test_prompt_caching_marks_final_additional_tool_in_request() {
        let request = completion_request_with_tools(
            vec![generic_tool("rig_tool")],
            Some(json!({
                "tools": [{
                    "name": "provider_tool",
                    "description": "Provider tool",
                    "input_schema": {"type": "object"}
                }],
                "metadata": {"source": "test"}
            })),
        );

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        let tools = value["tools"].as_array().unwrap();
        assert_eq!(tools.len(), 2);
        assert!(tools[0].get("cache_control").is_none());
        assert_eq!(tools[1]["name"], "provider_tool");
        assert_eq!(tools[1]["cache_control"]["type"], "ephemeral");
        assert_eq!(value["metadata"]["source"], "test");
    }

    #[test]
    fn test_prompt_caching_without_tools_omits_tools() {
        let request = completion_request_with_tools(Vec::new(), None);

        let request = AnthropicCompletionRequest::try_from(AnthropicRequestParams {
            model: "claude-sonnet-4-6",
            request,
            prompt_caching: true,
            automatic_caching: false,
            automatic_caching_ttl: None,
        })
        .unwrap();

        let value = serde_json::to_value(request).unwrap();
        assert!(value.get("tools").is_none());
    }

    #[test]
    fn test_plaintext_document_serialization() {
        let content = Content::Document {
            source: DocumentSource::Text {
                data: "Hello, world!".to_string(),
                media_type: PlainTextMediaType::Plain,
            },
            title: None,
            context: None,
            citations: None,
            cache_control: None,
        };

        let json = serde_json::to_value(&content).unwrap();
        assert_eq!(json["type"], "document");
        assert_eq!(json["source"]["type"], "text");
        assert_eq!(json["source"]["media_type"], "text/plain");
        assert_eq!(json["source"]["data"], "Hello, world!");
    }

    #[test]
    fn test_plaintext_document_deserialization() {
        let json = r#"
        {
            "type": "document",
            "source": {
                "type": "text",
                "media_type": "text/plain",
                "data": "Hello, world!"
            }
        }
        "#;

        let content: Content = serde_json::from_str(json).unwrap();
        match content {
            Content::Document {
                source,
                cache_control,
                ..
            } => {
                assert_eq!(
                    source,
                    DocumentSource::Text {
                        data: "Hello, world!".to_string(),
                        media_type: PlainTextMediaType::Plain,
                    }
                );
                assert_eq!(cache_control, None);
            }
            _ => panic!("Expected Document content"),
        }
    }

    #[test]
    fn test_base64_pdf_document_serialization() {
        let content = Content::Document {
            source: DocumentSource::Base64 {
                data: "base64data".to_string(),
                media_type: DocumentFormat::PDF,
            },
            title: None,
            context: None,
            citations: None,
            cache_control: None,
        };

        let json = serde_json::to_value(&content).unwrap();
        assert_eq!(json["type"], "document");
        assert_eq!(json["source"]["type"], "base64");
        assert_eq!(json["source"]["media_type"], "application/pdf");
        assert_eq!(json["source"]["data"], "base64data");
    }

    #[test]
    fn test_base64_pdf_document_deserialization() {
        let json = r#"
        {
            "type": "document",
            "source": {
                "type": "base64",
                "media_type": "application/pdf",
                "data": "base64data"
            }
        }
        "#;

        let content: Content = serde_json::from_str(json).unwrap();
        match content {
            Content::Document { source, .. } => {
                assert_eq!(
                    source,
                    DocumentSource::Base64 {
                        data: "base64data".to_string(),
                        media_type: DocumentFormat::PDF,
                    }
                );
            }
            _ => panic!("Expected Document content"),
        }
    }

    #[test]
    fn test_file_id_document_serialization() {
        let content = Content::Document {
            source: DocumentSource::File {
                file_id: "file_abc".to_string(),
            },
            title: None,
            context: None,
            citations: None,
            cache_control: None,
        };

        let json = serde_json::to_value(&content).unwrap();
        assert_eq!(json["type"], "document");
        assert_eq!(json["source"]["type"], "file");
        assert_eq!(json["source"]["file_id"], "file_abc");
    }

    #[test]
    fn test_file_id_document_deserialization() {
        let json = r#"
        {
            "type": "document",
            "source": {
                "type": "file",
                "file_id": "file_abc"
            }
        }
        "#;

        let content: Content = serde_json::from_str(json).unwrap();
        match content {
            Content::Document { source, .. } => {
                assert_eq!(
                    source,
                    DocumentSource::File {
                        file_id: "file_abc".to_string(),
                    }
                );
            }
            _ => panic!("Expected Document content"),
        }
    }

    #[test]
    fn test_file_id_rig_to_anthropic_conversion() {
        use crate::completion::message as msg;

        let rig_message = msg::Message::User {
            content: OneOrMany::one(msg::UserContent::Document(msg::Document {
                data: DocumentSourceKind::FileId("file_abc".to_string()),
                media_type: None,
                additional_params: None,
            })),
        };

        let anthropic_message: Message = rig_message.try_into().unwrap();
        assert_eq!(anthropic_message.role, Role::User);

        let mut iter = anthropic_message.content.into_iter();
        match iter.next().unwrap() {
            Content::Document { source, .. } => {
                assert_eq!(
                    source,
                    DocumentSource::File {
                        file_id: "file_abc".to_string(),
                    }
                );
            }
            other => panic!("Expected Document content, got: {other:?}"),
        }
    }

    #[test]
    fn test_file_id_anthropic_to_rig_conversion() {
        use crate::completion::message as msg;

        let anthropic_message = Message {
            role: Role::User,
            content: OneOrMany::one(Content::Document {
                source: DocumentSource::File {
                    file_id: "file_abc".to_string(),
                },
                title: None,
                context: None,
                citations: None,
                cache_control: None,
            }),
        };

        let rig_message: msg::Message = anthropic_message.try_into().unwrap();
        match rig_message {
            msg::Message::User { content } => {
                let mut iter = content.into_iter();
                match iter.next().unwrap() {
                    msg::UserContent::Document(msg::Document {
                        data, media_type, ..
                    }) => {
                        assert_eq!(data, DocumentSourceKind::FileId("file_abc".to_string()));
                        assert_eq!(media_type, None);
                    }
                    other => panic!("Expected Document content, got: {other:?}"),
                }
            }
            _ => panic!("Expected User message"),
        }
    }

    #[test]
    fn test_plaintext_rig_to_anthropic_conversion() {
        use crate::completion::message as msg;

        let rig_message = msg::Message::User {
            content: OneOrMany::one(msg::UserContent::document(
                "Some plain text content".to_string(),
                Some(msg::DocumentMediaType::TXT),
            )),
        };

        let anthropic_message: Message = rig_message.try_into().unwrap();
        assert_eq!(anthropic_message.role, Role::User);

        let mut iter = anthropic_message.content.into_iter();
        match iter.next().unwrap() {
            Content::Document { source, .. } => {
                assert_eq!(
                    source,
                    DocumentSource::Text {
                        data: "Some plain text content".to_string(),
                        media_type: PlainTextMediaType::Plain,
                    }
                );
            }
            other => panic!("Expected Document content, got: {other:?}"),
        }
    }

    #[test]
    fn test_plaintext_anthropic_to_rig_conversion() {
        use crate::completion::message as msg;

        let anthropic_message = Message {
            role: Role::User,
            content: OneOrMany::one(Content::Document {
                source: DocumentSource::Text {
                    data: "Some plain text content".to_string(),
                    media_type: PlainTextMediaType::Plain,
                },
                title: None,
                context: None,
                citations: None,
                cache_control: None,
            }),
        };

        let rig_message: msg::Message = anthropic_message.try_into().unwrap();
        match rig_message {
            msg::Message::User { content } => {
                let mut iter = content.into_iter();
                match iter.next().unwrap() {
                    msg::UserContent::Document(msg::Document {
                        data, media_type, ..
                    }) => {
                        assert_eq!(
                            data,
                            DocumentSourceKind::String("Some plain text content".into())
                        );
                        assert_eq!(media_type, Some(msg::DocumentMediaType::TXT));
                    }
                    other => panic!("Expected Document content, got: {other:?}"),
                }
            }
            _ => panic!("Expected User message"),
        }
    }

    #[test]
    fn test_plaintext_roundtrip_rig_to_anthropic_and_back() {
        use crate::completion::message as msg;

        let original = msg::Message::User {
            content: OneOrMany::one(msg::UserContent::document(
                "Round trip text".to_string(),
                Some(msg::DocumentMediaType::TXT),
            )),
        };

        let anthropic: Message = original.clone().try_into().unwrap();
        let back: msg::Message = anthropic.try_into().unwrap();

        match (&original, &back) {
            (
                msg::Message::User {
                    content: orig_content,
                },
                msg::Message::User {
                    content: back_content,
                },
            ) => match (orig_content.first(), back_content.first()) {
                (
                    msg::UserContent::Document(msg::Document {
                        media_type: orig_mt,
                        ..
                    }),
                    msg::UserContent::Document(msg::Document {
                        media_type: back_mt,
                        ..
                    }),
                ) => {
                    assert_eq!(orig_mt, back_mt);
                }
                _ => panic!("Expected Document content in both"),
            },
            _ => panic!("Expected User messages"),
        }
    }

    #[test]
    fn test_unsupported_document_type_returns_error() {
        use crate::completion::message as msg;

        let rig_message = msg::Message::User {
            content: OneOrMany::one(msg::UserContent::Document(msg::Document {
                data: DocumentSourceKind::String("data".into()),
                media_type: Some(msg::DocumentMediaType::HTML),
                additional_params: None,
            })),
        };

        let result: Result<Message, _> = rig_message.try_into();
        assert!(result.is_err());
        let err = result.unwrap_err().to_string();
        assert!(
            err.contains("Anthropic only supports PDF and plain text documents"),
            "Unexpected error: {err}"
        );
    }

    #[test]
    fn test_plaintext_document_url_source_returns_error() {
        use crate::completion::message as msg;

        let rig_message = msg::Message::User {
            content: OneOrMany::one(msg::UserContent::Document(msg::Document {
                data: DocumentSourceKind::Url("https://example.com/doc.txt".into()),
                media_type: Some(msg::DocumentMediaType::TXT),
                additional_params: None,
            })),
        };

        let result: Result<Message, _> = rig_message.try_into();
        assert!(result.is_err());
        let err = result.unwrap_err().to_string();
        assert!(
            err.contains("Only string or base64 data is supported for plain text documents"),
            "Unexpected error: {err}"
        );
    }

    #[test]
    fn test_plaintext_document_with_cache_control() {
        let content = Content::Document {
            source: DocumentSource::Text {
                data: "cached text".to_string(),
                media_type: PlainTextMediaType::Plain,
            },
            title: None,
            context: None,
            citations: None,
            cache_control: Some(CacheControl::ephemeral()),
        };

        let json = serde_json::to_value(&content).unwrap();
        assert_eq!(json["source"]["type"], "text");
        assert_eq!(json["source"]["media_type"], "text/plain");
        assert_eq!(json["cache_control"]["type"], "ephemeral");
    }

    #[test]
    fn test_message_with_plaintext_document_deserialization() {
        let json = r#"
        {
            "role": "user",
            "content": [
                {
                    "type": "document",
                    "source": {
                        "type": "text",
                        "media_type": "text/plain",
                        "data": "Hello from a text file"
                    }
                },
                {
                    "type": "text",
                    "text": "Summarize this document."
                }
            ]
        }
        "#;

        let message: Message = serde_json::from_str(json).unwrap();
        assert_eq!(message.role, Role::User);
        assert_eq!(message.content.len(), 2);

        let mut iter = message.content.into_iter();

        match iter.next().unwrap() {
            Content::Document { source, .. } => {
                assert_eq!(
                    source,
                    DocumentSource::Text {
                        data: "Hello from a text file".to_string(),
                        media_type: PlainTextMediaType::Plain,
                    }
                );
            }
            _ => panic!("Expected Document content"),
        }

        match iter.next().unwrap() {
            Content::Text { text, .. } => {
                assert_eq!(text, "Summarize this document.");
            }
            _ => panic!("Expected Text content"),
        }
    }

    #[test]
    fn test_assistant_reasoning_multiblock_to_anthropic_content() {
        let reasoning = message::Reasoning {
            id: None,
            content: vec![
                message::ReasoningContent::Text {
                    text: "step one".to_string(),
                    signature: Some("sig-1".to_string()),
                },
                message::ReasoningContent::Summary("summary".to_string()),
                message::ReasoningContent::Text {
                    text: "step two".to_string(),
                    signature: Some("sig-2".to_string()),
                },
                message::ReasoningContent::Redacted {
                    data: "redacted block".to_string(),
                },
            ],
        };

        let msg = message::Message::Assistant {
            id: None,
            content: OneOrMany::one(message::AssistantContent::Reasoning(reasoning)),
        };
        let converted: Message = msg.try_into().expect("convert assistant message");
        let converted_content = converted.content.iter().cloned().collect::<Vec<_>>();

        assert_eq!(converted.role, Role::Assistant);
        assert_eq!(converted_content.len(), 4);
        assert!(matches!(
            converted_content.first(),
            Some(Content::Thinking { thinking, signature: Some(signature) })
                if thinking == "step one" && signature == "sig-1"
        ));
        assert!(matches!(
            converted_content.get(1),
            Some(Content::Thinking { thinking, signature: None }) if thinking == "summary"
        ));
        assert!(matches!(
            converted_content.get(2),
            Some(Content::Thinking { thinking, signature: Some(signature) })
                if thinking == "step two" && signature == "sig-2"
        ));
        assert!(matches!(
            converted_content.get(3),
            Some(Content::RedactedThinking { data }) if data == "redacted block"
        ));
    }

    #[test]
    fn test_redacted_thinking_content_to_assistant_reasoning() {
        let content = Content::RedactedThinking {
            data: "opaque-redacted".to_string(),
        };
        let converted: message::AssistantContent =
            content.try_into().expect("convert redacted thinking");

        assert!(matches!(
            converted,
            message::AssistantContent::Reasoning(message::Reasoning { content, .. })
                if matches!(
                    content.first(),
                    Some(message::ReasoningContent::Redacted { data }) if data == "opaque-redacted"
                )
        ));
    }

    #[test]
    fn test_assistant_encrypted_reasoning_maps_to_redacted_thinking() {
        let reasoning = message::Reasoning {
            id: None,
            content: vec![message::ReasoningContent::Encrypted(
                "ciphertext".to_string(),
            )],
        };
        let msg = message::Message::Assistant {
            id: None,
            content: OneOrMany::one(message::AssistantContent::Reasoning(reasoning)),
        };

        let converted: Message = msg.try_into().expect("convert assistant message");
        let converted_content = converted.content.iter().cloned().collect::<Vec<_>>();

        assert_eq!(converted_content.len(), 1);
        assert!(matches!(
            converted_content.first(),
            Some(Content::RedactedThinking { data }) if data == "ciphertext"
        ));
    }

    #[test]
    fn empty_end_turn_response_normalizes_to_empty_text_choice() {
        let response = CompletionResponse {
            content: vec![],
            id: "msg_123".to_string(),
            model: CLAUDE_SONNET_4_6.to_string(),
            role: "assistant".to_string(),
            stop_reason: Some("end_turn".to_string()),
            stop_sequence: None,
            usage: Usage {
                input_tokens: 7,
                cache_read_input_tokens: None,
                cache_creation_input_tokens: None,
                output_tokens: 2,
            },
        };

        let parsed: completion::CompletionResponse<CompletionResponse> = response
            .try_into()
            .expect("empty end_turn should not error");

        assert_eq!(parsed.choice.len(), 1);
        assert!(matches!(
            parsed.choice.first(),
            completion::AssistantContent::Text(text) if text.text.is_empty()
        ));
    }

    #[test]
    fn empty_non_end_turn_response_still_errors() {
        let response = CompletionResponse {
            content: vec![],
            id: "msg_123".to_string(),
            model: CLAUDE_SONNET_4_6.to_string(),
            role: "assistant".to_string(),
            stop_reason: Some("tool_use".to_string()),
            stop_sequence: None,
            usage: Usage {
                input_tokens: 7,
                cache_read_input_tokens: None,
                cache_creation_input_tokens: None,
                output_tokens: 2,
            },
        };

        let err = completion::CompletionResponse::<CompletionResponse>::try_from(response)
            .expect_err("empty non-end_turn should remain an error");

        assert!(matches!(
            err,
            CompletionError::ResponseError(message) if message == EMPTY_RESPONSE_ERROR
        ));
    }

    #[test]
    fn test_tool_result_content_in_message_roundtrip() {
        let message_json = r#"{
            "role": "user",
            "content": [
                {
                    "type": "tool_result",
                    "tool_use_id": "toolu_01A09q90qw90lq917835lq9",
                    "content": [
                        {
                            "type": "text",
                            "text": "Here is the screenshot:"
                        },
                        {
                            "type": "image",
                            "source": {
                                "type": "base64",
                                "media_type": "image/png",
                                "data": "iVBORw0KGgo..."
                            }
                        }
                    ]
                }
            ]
        }"#;

        let message: Message = serde_json::from_str(message_json).unwrap();
        let serialized = serde_json::to_value(&message).unwrap();

        let tool_result = &serialized["content"][0];
        assert_eq!(tool_result["type"], "tool_result");

        let image_content = &tool_result["content"][1];
        assert_eq!(image_content["type"], "image");
        assert_eq!(image_content["source"]["type"], "base64");
        assert_eq!(image_content["source"]["media_type"], "image/png");
        assert_eq!(image_content["source"]["data"], "iVBORw0KGgo...");
    }

    // -------------------------------------------------------------------
    // Citations (#1767)
    // -------------------------------------------------------------------

    #[test]
    fn document_serializes_citations_and_metadata() {
        let doc = Content::Document {
            source: DocumentSource::Text {
                data: "hello".into(),
                media_type: PlainTextMediaType::Plain,
            },
            title: Some("My Doc".into()),
            context: None,
            citations: Some(CitationsConfig { enabled: true }),
            cache_control: None,
        };
        let value = serde_json::to_value(&doc).unwrap();
        assert_eq!(value["citations"]["enabled"], true);
        assert_eq!(value["title"], "My Doc");
        assert!(
            value.get("context").is_none(),
            "context should be skipped when None"
        );
    }

    #[test]
    fn text_serializes_without_citations_when_empty() {
        let content = Content::Text {
            text: "hello".into(),
            citations: Vec::new(),
            cache_control: None,
        };
        let value = serde_json::to_value(&content).unwrap();
        assert!(
            value.get("citations").is_none(),
            "empty citations vec must be skipped"
        );
    }

    #[test]
    fn text_deserializes_char_location_citation() {
        let value = json!({
            "type": "text",
            "text": "the grass is green",
            "citations": [{
                "type": "char_location",
                "cited_text": "The grass is green.",
                "document_index": 0,
                "document_title": "Example",
                "start_char_index": 0,
                "end_char_index": 20
            }]
        });
        let parsed: Content = serde_json::from_value(value).unwrap();
        let Content::Text { citations, .. } = parsed else {
            panic!("expected Content::Text");
        };
        assert_eq!(citations.len(), 1);
        let Citation::CharLocation {
            start_char_index,
            end_char_index,
            ..
        } = &citations[0]
        else {
            panic!("expected CharLocation");
        };
        assert_eq!(*start_char_index, 0);
        assert_eq!(*end_char_index, 20);
    }

    #[test]
    fn text_deserializes_search_result_location_citation() {
        let value = json!({
            "type": "text",
            "text": "API keys are required.",
            "citations": [{
                "type": "search_result_location",
                "cited_text": "All API requests must include an API key.",
                "source": "https://docs.example.com/api-reference",
                "title": "API Reference",
                "search_result_index": 0,
                "start_block_index": 0,
                "end_block_index": 1
            }]
        });

        let parsed: Content = serde_json::from_value(value).unwrap();
        let Content::Text { citations, .. } = parsed else {
            panic!("expected Content::Text");
        };

        assert!(matches!(
            &citations[0],
            Citation::SearchResultLocation {
                source,
                title: Some(title),
                search_result_index: 0,
                start_block_index: 0,
                end_block_index: 1,
                ..
            } if source == "https://docs.example.com/api-reference" && title == "API Reference"
        ));
    }

    #[test]
    fn text_deserializes_web_search_result_location_citation() {
        let value = json!({
            "type": "text",
            "text": "Claude Shannon worked at Bell Labs.",
            "citations": [{
                "type": "web_search_result_location",
                "cited_text": "Claude Shannon was a mathematician.",
                "url": "https://example.com/shannon",
                "title": "Claude Shannon",
                "encrypted_index": "encrypted-reference"
            }]
        });

        let parsed: Content = serde_json::from_value(value).unwrap();
        let Content::Text { citations, .. } = parsed else {
            panic!("expected Content::Text");
        };

        assert!(matches!(
            &citations[0],
            Citation::WebSearchResultLocation {
                url,
                title,
                encrypted_index,
                ..
            } if url == "https://example.com/shannon"
                && title.as_deref() == Some("Claude Shannon")
                && encrypted_index == "encrypted-reference"
        ));
    }

    #[test]
    fn text_deserializes_web_search_result_location_citation_with_null_title() {
        let value = json!({
            "type": "text",
            "text": "Claude Shannon worked at Bell Labs.",
            "citations": [{
                "type": "web_search_result_location",
                "cited_text": "Claude Shannon was a mathematician.",
                "url": "https://example.com/shannon",
                "title": null,
                "encrypted_index": "encrypted-reference"
            }]
        });

        let parsed: Content = serde_json::from_value(value).unwrap();
        let Content::Text { citations, .. } = parsed else {
            panic!("expected Content::Text");
        };

        let Citation::WebSearchResultLocation { title, .. } = &citations[0] else {
            panic!("expected WebSearchResultLocation");
        };
        assert_eq!(title, &None);

        let serialized = serde_json::to_value(&citations[0]).unwrap();
        assert!(serialized.get("title").is_some());
        assert!(serialized["title"].is_null());
    }

    #[test]
    fn web_search_response_preserves_raw_blocks_and_citations() {
        let value = json!({
            "id": "msg_web_search",
            "model": CLAUDE_SONNET_4_6,
            "role": "assistant",
            "stop_reason": "end_turn",
            "stop_sequence": null,
            "usage": {
                "input_tokens": 10,
                "output_tokens": 20
            },
            "content": [
                {
                    "type": "server_tool_use",
                    "id": "srvtoolu_01",
                    "name": "web_search",
                    "input": {
                        "query": "claude shannon birth date"
                    }
                },
                {
                    "type": "web_search_tool_result",
                    "tool_use_id": "srvtoolu_01",
                    "content": [
                        {
                            "type": "web_search_result",
                            "url": "https://example.com/shannon",
                            "title": "Claude Shannon",
                            "encrypted_content": "encrypted-content",
                            "page_age": "April 30, 2025"
                        }
                    ]
                },
                {
                    "type": "text",
                    "text": "Claude Shannon was born on April 30, 1916.",
                    "citations": [{
                        "type": "web_search_result_location",
                        "cited_text": "Claude Shannon was born on April 30, 1916.",
                        "url": "https://example.com/shannon",
                        "title": "Claude Shannon",
                        "encrypted_index": "encrypted-index"
                    }]
                }
            ]
        });

        let response: CompletionResponse = serde_json::from_value(value).unwrap();
        let converted: completion::CompletionResponse<CompletionResponse> =
            response.try_into().unwrap();
        assert_eq!(converted.choice.len(), 3);
        assert_eq!(
            converted.raw_response.get_text_response().as_deref(),
            Some("Claude Shannon was born on April 30, 1916.")
        );

        let items = converted.choice.iter().collect::<Vec<_>>();
        let message::AssistantContent::Text(server_tool_use) = items[0] else {
            panic!("expected raw server_tool_use metadata");
        };
        assert_eq!(server_tool_use.text, "");
        assert_eq!(
            server_tool_use.additional_params.as_ref().unwrap()[ANTHROPIC_RAW_CONTENT_KEY]["type"],
            "server_tool_use"
        );

        let message::AssistantContent::Text(web_search_result) = items[1] else {
            panic!("expected raw web_search_tool_result metadata");
        };
        assert_eq!(
            web_search_result.additional_params.as_ref().unwrap()[ANTHROPIC_RAW_CONTENT_KEY]["content"]
                [0]["encrypted_content"],
            "encrypted-content"
        );

        let message::AssistantContent::Text(answer) = items[2] else {
            panic!("expected text answer");
        };
        let citations = anthropic_citations(answer).unwrap();
        assert!(matches!(
            citations.first(),
            Some(Citation::WebSearchResultLocation {
                encrypted_index,
                ..
            }) if encrypted_index == "encrypted-index"
        ));

        let round_trip: Message = message::Message::Assistant {
            id: converted.message_id.clone(),
            content: converted.choice,
        }
        .try_into()
        .unwrap();

        let round_trip_items = round_trip.content.iter().collect::<Vec<_>>();
        assert!(matches!(
            round_trip_items.first(),
            Some(Content::ServerToolUse { id, name, input })
                if id == "srvtoolu_01"
                    && name == "web_search"
                    && input["query"] == "claude shannon birth date"
        ));
        assert!(matches!(
            round_trip_items.get(1),
            Some(Content::WebSearchToolResult {
                tool_use_id,
                content
            }) if tool_use_id == "srvtoolu_01"
                && content[0]["encrypted_content"] == "encrypted-content"
        ));
    }

    #[test]
    fn web_search_tool_result_error_object_is_preserved_raw() {
        let value = json!({
            "id": "msg_web_search_error",
            "model": CLAUDE_SONNET_4_6,
            "role": "assistant",
            "stop_reason": "end_turn",
            "stop_sequence": null,
            "usage": {
                "input_tokens": 10,
                "output_tokens": 2
            },
            "content": [{
                "type": "web_search_tool_result",
                "tool_use_id": "srvtoolu_01",
                "content": {
                    "type": "web_search_tool_result_error",
                    "error_code": "max_uses_exceeded"
                }
            }]
        });

        let response: CompletionResponse = serde_json::from_value(value).unwrap();
        let converted: completion::CompletionResponse<CompletionResponse> =
            response.try_into().unwrap();
        let message::AssistantContent::Text(web_search_result) = converted.choice.first() else {
            panic!("expected raw web_search_tool_result metadata");
        };

        let raw_content =
            &web_search_result.additional_params.as_ref().unwrap()[ANTHROPIC_RAW_CONTENT_KEY];
        assert_eq!(raw_content["type"], "web_search_tool_result");
        assert_eq!(raw_content["content"]["error_code"], "max_uses_exceeded");
        assert_eq!(
            raw_content["content"]["type"],
            "web_search_tool_result_error"
        );

        let round_trip: Message = message::Message::Assistant {
            id: converted.message_id,
            content: converted.choice,
        }
        .try_into()
        .unwrap();

        assert!(matches!(
            round_trip.content.first(),
            Content::WebSearchToolResult {
                tool_use_id,
                content
            } if tool_use_id == "srvtoolu_01"
                && content["error_code"] == "max_uses_exceeded"
        ));
    }

    #[test]
    fn text_deserializes_unknown_citation_without_failing() {
        let value = json!({
            "type": "text",
            "text": "future citation",
            "citations": [{
                "type": "future_location",
                "cited_text": "future text",
                "new_field": "kept"
            }]
        });

        let parsed: Content = serde_json::from_value(value).unwrap();
        let Content::Text { citations, .. } = parsed else {
            panic!("expected Content::Text");
        };

        assert!(matches!(
            &citations[0],
            Citation::Unknown(raw)
                if raw["type"] == "future_location" && raw["new_field"] == "kept"
        ));
    }

    #[test]
    fn page_location_citation_roundtrips() {
        let citation = Citation::PageLocation {
            cited_text: "Water is essential for life.".into(),
            document_index: 1,
            document_title: Some("PDF Doc".into()),
            start_page_number: 5,
            end_page_number: 6,
        };
        let value = serde_json::to_value(&citation).unwrap();
        assert_eq!(value["type"], "page_location");
        assert_eq!(value["start_page_number"], 5);
        let back: Citation = serde_json::from_value(value).unwrap();
        assert_eq!(back, citation);
    }

    #[test]
    fn content_block_location_citation_roundtrips() {
        let citation = Citation::ContentBlockLocation {
            cited_text: "These are important findings.".into(),
            document_index: 2,
            document_title: None,
            start_block_index: 0,
            end_block_index: 1,
        };
        let value = serde_json::to_value(&citation).unwrap();
        assert_eq!(value["type"], "content_block_location");
        assert!(value.get("document_title").is_none());
        let back: Citation = serde_json::from_value(value).unwrap();
        assert_eq!(back, citation);
    }

    #[test]
    fn anthropic_citations_extracts_from_additional_params() {
        let text = message::Text {
            text: "the grass is green".into(),
            additional_params: Some(json!({
                "citations": [{
                    "type": "char_location",
                    "cited_text": "The grass is green.",
                    "document_index": 0,
                    "start_char_index": 0,
                    "end_char_index": 20
                }]
            })),
        };
        let citations = anthropic_citations(&text).unwrap();
        assert_eq!(citations.len(), 1);
    }

    #[test]
    fn anthropic_citations_returns_empty_when_absent() {
        let text = message::Text::new("hello".to_string());
        assert!(anthropic_citations(&text).unwrap().is_empty());
    }

    #[test]
    fn content_text_with_citations_survives_assistant_conversion() {
        let content = Content::Text {
            text: "the grass is green".into(),
            citations: vec![Citation::CharLocation {
                cited_text: "The grass is green.".into(),
                document_index: 0,
                document_title: None,
                start_char_index: 0,
                end_char_index: 20,
            }],
            cache_control: None,
        };
        let assistant: message::AssistantContent = content.try_into().unwrap();
        let message::AssistantContent::Text(text) = assistant else {
            panic!("expected text variant");
        };
        let recovered = anthropic_citations(&text).unwrap();
        assert_eq!(recovered.len(), 1);
    }

    #[test]
    fn provider_text_response_concatenates_text_blocks_without_inserted_newlines() {
        let response = CompletionResponse {
            content: vec![
                Content::Text {
                    text: "According to the document, ".into(),
                    citations: Vec::new(),
                    cache_control: None,
                },
                Content::Text {
                    text: "the grass is green".into(),
                    citations: Vec::new(),
                    cache_control: None,
                },
                Content::Text {
                    text: " and the sky is blue.".into(),
                    citations: Vec::new(),
                    cache_control: None,
                },
            ],
            id: "msg_1".into(),
            model: "claude-test".into(),
            role: "assistant".into(),
            stop_reason: Some("end_turn".into()),
            stop_sequence: None,
            usage: Usage {
                input_tokens: 1,
                cache_read_input_tokens: None,
                cache_creation_input_tokens: None,
                output_tokens: 1,
            },
        };

        assert_eq!(
            response.get_text_response().as_deref(),
            Some("According to the document, the grass is green and the sky is blue.")
        );
    }

    #[test]
    fn assistant_text_citations_survive_anthropic_request_conversion() {
        let assistant = message::Message::Assistant {
            id: None,
            content: OneOrMany::one(message::AssistantContent::Text(message::Text {
                text: "the grass is green".into(),
                additional_params: Some(json!({
                    "citations": [{
                        "type": "char_location",
                        "cited_text": "The grass is green.",
                        "document_index": 0,
                        "start_char_index": 0,
                        "end_char_index": 20
                    }]
                })),
            })),
        };

        let converted: Message = assistant.try_into().unwrap();
        let Content::Text {
            citations, text, ..
        } = converted.content.first()
        else {
            panic!("expected assistant text content");
        };

        assert_eq!(text, "the grass is green");
        assert_eq!(
            citations,
            vec![Citation::CharLocation {
                cited_text: "The grass is green.".into(),
                document_index: 0,
                document_title: None,
                start_char_index: 0,
                end_char_index: 20,
            }]
        );
    }

    #[test]
    fn assistant_text_invalid_known_citations_are_rejected_for_anthropic_request_conversion() {
        let text = message::AssistantContent::Text(message::Text {
            text: "bad citation".into(),
            additional_params: Some(json!({
                "citations": [{
                    "type": "char_location",
                    "cited_text": "bad"
                }]
            })),
        });

        let result = Content::try_from(text);

        assert!(
            result.is_err(),
            "invalid Anthropic citation metadata should not be silently dropped"
        );
    }

    #[test]
    fn document_additional_params_forward_to_anthropic_document() {
        let doc = message::UserContent::Document(message::Document {
            data: message::DocumentSourceKind::String("Hello world.".into()),
            media_type: Some(message::DocumentMediaType::TXT),
            additional_params: Some(json!({
                "title": "Doc1",
                "context": "ctx",
                "citations": { "enabled": true }
            })),
        });
        let msg = message::Message::User {
            content: OneOrMany::one(doc),
        };
        let converted: Message = msg.try_into().unwrap();
        let block = converted.content.first();
        let Content::Document {
            title,
            context,
            citations,
            ..
        } = block
        else {
            panic!("expected Content::Document");
        };
        assert_eq!(title.as_deref(), Some("Doc1"));
        assert_eq!(context.as_deref(), Some("ctx"));
        assert_eq!(citations, Some(CitationsConfig { enabled: true }));
    }

    fn assert_reverse_document_metadata(
        source: DocumentSource,
        expected_data: DocumentSourceKind,
        expected_media_type: Option<message::DocumentMediaType>,
    ) -> message::Message {
        let provider_message = Message {
            role: Role::User,
            content: OneOrMany::one(Content::Document {
                source,
                title: Some("Doc1".into()),
                context: Some("ctx".into()),
                citations: Some(CitationsConfig { enabled: true }),
                cache_control: None,
            }),
        };

        let generic: message::Message = provider_message.try_into().unwrap();
        let message::Message::User { content } = &generic else {
            panic!("expected generic user message");
        };
        let message::UserContent::Document(document) = content.first() else {
            panic!("expected generic document");
        };

        assert_eq!(document.data, expected_data);
        assert_eq!(document.media_type, expected_media_type);
        let additional_params = document
            .additional_params
            .as_ref()
            .expect("expected Anthropic document metadata");
        assert_eq!(additional_params["title"], "Doc1");
        assert_eq!(additional_params["context"], "ctx");
        assert_eq!(additional_params["citations"]["enabled"], true);

        generic
    }

    #[test]
    fn anthropic_document_metadata_survives_reverse_conversion_for_all_sources() {
        assert_reverse_document_metadata(
            DocumentSource::Text {
                data: "Hello world.".into(),
                media_type: PlainTextMediaType::Plain,
            },
            DocumentSourceKind::String("Hello world.".into()),
            Some(message::DocumentMediaType::TXT),
        );
        assert_reverse_document_metadata(
            DocumentSource::Base64 {
                data: "base64-pdf".into(),
                media_type: DocumentFormat::PDF,
            },
            DocumentSourceKind::String("base64-pdf".into()),
            Some(message::DocumentMediaType::PDF),
        );
        assert_reverse_document_metadata(
            DocumentSource::Url {
                url: "https://example.com/doc.pdf".into(),
            },
            DocumentSourceKind::Url("https://example.com/doc.pdf".into()),
            None,
        );
        assert_reverse_document_metadata(
            DocumentSource::File {
                file_id: "file_abc".into(),
            },
            DocumentSourceKind::FileId("file_abc".into()),
            None,
        );
    }

    #[test]
    fn anthropic_document_metadata_survives_reverse_round_trip() {
        let provider_message = Message {
            role: Role::User,
            content: OneOrMany::one(Content::Document {
                source: DocumentSource::Text {
                    data: "Hello world.".into(),
                    media_type: PlainTextMediaType::Plain,
                },
                title: Some("Doc1".into()),
                context: Some("ctx".into()),
                citations: Some(CitationsConfig { enabled: true }),
                cache_control: None,
            }),
        };

        let generic: message::Message = provider_message.try_into().unwrap();
        let message::Message::User { content } = &generic else {
            panic!("expected generic user message");
        };
        let message::UserContent::Document(document) = content.first() else {
            panic!("expected generic document");
        };
        let additional_params = document
            .additional_params
            .as_ref()
            .expect("expected Anthropic document metadata");
        assert_eq!(additional_params["title"], "Doc1");
        assert_eq!(additional_params["context"], "ctx");
        assert_eq!(additional_params["citations"]["enabled"], true);

        let round_trip: Message = generic.try_into().unwrap();
        let Content::Document {
            title,
            context,
            citations,
            ..
        } = round_trip.content.first()
        else {
            panic!("expected Anthropic document");
        };
        assert_eq!(title.as_deref(), Some("Doc1"));
        assert_eq!(context.as_deref(), Some("ctx"));
        assert_eq!(citations, Some(CitationsConfig { enabled: true }));
    }

    #[test]
    fn anthropic_document_empty_metadata_stays_none_on_reverse_conversion() {
        let provider_message = Message {
            role: Role::User,
            content: OneOrMany::one(Content::Document {
                source: DocumentSource::Text {
                    data: "Hello world.".into(),
                    media_type: PlainTextMediaType::Plain,
                },
                title: None,
                context: None,
                citations: None,
                cache_control: None,
            }),
        };

        let generic: message::Message = provider_message.try_into().unwrap();
        let message::Message::User { content } = &generic else {
            panic!("expected generic user message");
        };
        let message::UserContent::Document(document) = content.first() else {
            panic!("expected generic document");
        };

        assert_eq!(document.additional_params, None);
    }
}