rig-core 0.36.0

//! 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-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 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.to_owned())
                } else {
                    None
                }
            })
            .collect::<Vec<String>>()
            .join("\n");

        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) -> Option<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;

        Some(usage)
    }
}

#[derive(Debug, Deserialize, Serialize)]
pub struct ToolDefinition {
    pub name: String,
    pub description: Option<String>,
    pub input_schema: serde_json::Value,
}

/// TTL for a cache control breakpoint.
///
/// The Anthropic API supports two TTL values:
/// - `"5m"` — 5 minutes (default when `ttl` is omitted)
/// - `"1h"` — 1 hour (requires the `extended-cache-ttl-2025-04-11` beta header)
#[derive(Debug, Deserialize, Serialize, Clone, PartialEq, Default)]
pub enum CacheTtl {
    /// 5-minute TTL (default).
    #[default]
    #[serde(rename = "5m")]
    FiveMinutes,
    /// 1-hour TTL. Requires the `extended-cache-ttl-2025-04-11` beta header.
    #[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),
        };

        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,
}

#[derive(Debug, Deserialize, Serialize, Clone, PartialEq)]
#[serde(tag = "type", rename_all = "snake_case")]
pub enum Content {
    Text {
        text: String,
        #[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,
    },
    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,
        #[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(),
            cache_control: None,
        })
    }
}

#[derive(Debug, Deserialize, Serialize, Clone, PartialEq)]
#[serde(tag = "type", rename_all = "snake_case")]
pub enum ToolResultContent {
    Text { text: String },
    Image(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. Currently implemented:
/// - `Base64`: Base64-encoded document data (used for PDFs)
/// - `Text`: Plain text document data
///
/// Future variants (not yet implemented):
/// - URL-based PDF sources
/// - Content block sources
/// - File API sources
#[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,
    },
}

#[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,
            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(message::Text { text }) => Ok(Content::Text {
                text,
                cache_control: None,
            }),
            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(message::Text { text }) => Ok(vec![Content::Text {
            text,
            cache_control: None,
        }]),
        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,
                        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(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, ..
                    }) => {
                        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,
                            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::User,
                content: OneOrMany::one(Content::Text {
                    text: content,
                    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, .. } => message::AssistantContent::text(text),
            Content::ToolUse { id, name, input } => {
                message::AssistantContent::tool_call(id, name, input)
            }
            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, .. } => match source {
                            DocumentSource::Base64 { data, media_type } => {
                                let rig_media_type = match media_type {
                                    DocumentFormat::PDF => message::DocumentMediaType::PDF,
                                };
                                message::UserContent::document(data, Some(rig_media_type))
                            }
                            DocumentSource::Text { data, .. } => message::UserContent::document(
                                data,
                                Some(message::DocumentMediaType::TXT),
                            ),
                            DocumentSource::Url { url } => {
                                message::UserContent::document_url(url, None)
                            }
                        },
                        _ => {
                            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())?,
            },
        })
    }
}

#[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 automatic prompt caching (adds cache_control breakpoints to system prompt 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 (requires the
    /// `extended-cache-ttl-2025-04-11` beta header).
    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 automatic prompt caching.
    ///
    /// When enabled, cache_control breakpoints are automatically added to:
    /// - The system prompt (marked with ephemeral cache)
    /// - The last content block of the last message (marked with ephemeral cache)
    ///
    /// This allows Anthropic to cache the conversation history for cost savings.
    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, pass `ttl: "1h"` via
    /// `additional_params` or combine with an explicit block-level breakpoint that carries the
    /// extended TTL.
    ///
    /// ```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
    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. Requires the
    /// `extended-cache-ttl-2025-04-11` beta header to be sent with the client:
    ///
    /// ```ignore
    /// let client = anthropic::Client::builder()
    ///     .api_key(std::env::var("ANTHROPIC_API_KEY").unwrap())
    ///     .anthropic_beta("extended-cache-ttl-2025-04-11")
    ///     .build()?;
    /// 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-4-7") || 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)
}

#[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,
        _ => {}
    }
}

/// 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()));
    }
}

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

    for message in history {
        match message {
            message::Message::System { content } => {
                if !content.is_empty() {
                    system.push(SystemContent::Text {
                        text: content,
                        cache_control: None,
                    });
                }
            }
            other => remaining.push(other),
        }
    }

    (system, remaining)
}

/// 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;

        // 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 mut full_history = vec![];
        if let Some(docs) = req.normalized_documents() {
            full_history.push(docs);
        }
        full_history.extend(req.chat_history);
        let (history_system, full_history) = split_system_messages_from_history(full_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 mut additional_tools =
            extract_tools_from_additional_params(&mut additional_params_payload)?;

        let mut tools = req
            .tools
            .into_iter()
            .map(|tool| ToolDefinition {
                name: tool.name,
                description: Some(tool.description),
                input_schema: tool.parameters,
            })
            .map(serde_json::to_value)
            .collect::<Result<Vec<_>, _>>()?;
        tools.append(&mut additional_tools);

        // 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 cache control breakpoints only if prompt_caching is enabled
        if prompt_caching {
            apply_cache_control(&mut system, &mut messages);
        }

        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: if automatic_caching {
                Some(CacheControl::Ephemeral {
                    ttl: automatic_caching_ttl,
                })
            } else {
                None
            },
            additional_params: if additional_params_payload.is_null() {
                None
            } else {
                Some(additional_params_payload)
            },
        })
    }
}

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())
}

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_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 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(),
                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(),
            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(),
                    cache_control: None,
                }),
            },
            Message {
                role: Role::Assistant,
                content: OneOrMany::one(Content::Text {
                    text: "Response".to_string(),
                    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());
            }
        }
    }

    #[test]
    fn test_plaintext_document_serialization() {
        let content = Content::Document {
            source: DocumentSource::Text {
                data: "Hello, world!".to_string(),
                media_type: PlainTextMediaType::Plain,
            },
            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,
            },
            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_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,
                },
                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,
            },
            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
        ));
    }
}