rig-core 0.42.0

//! Moonshot AI (Kimi) API client and Rig integration
//!
//! # Example
//! ```no_run
//! use rig_core::providers::moonshot;
//! use rig_core::client::CompletionClient;
//!
//! let client = moonshot::Client::new("YOUR_API_KEY").expect("Failed to build client");
//!
//! let kimi_model = client.completion_model(moonshot::KIMI_K2_5);
//! ```
//!
//! # Custom base URL
//! The default base URL is `https://api.moonshot.ai/v1`. For China access,
//! use `https://api.moonshot.cn/v1`:
//! ```no_run
//! use rig_core::providers::moonshot;
//!
//! let client = moonshot::Client::builder()
//!     .api_key("YOUR_API_KEY")
//!     .base_url("https://api.moonshot.ai/v1")
//!     .build()
//!     .expect("Failed to build Moonshot client");
//! ```
use crate::client;
use crate::providers::internal::anthropic_compatible::{
    AnthropicBaseUrl, impl_dual_dialect_provider,
};
use crate::{completion::CompletionError, providers::openai};

// ================================================================
// Main Moonshot Client
// ================================================================
/// Global OpenAI-compatible base URL.
pub const GLOBAL_API_BASE_URL: &str = "https://api.moonshot.ai/v1";
/// China OpenAI-compatible base URL.
pub const CHINA_API_BASE_URL: &str = "https://api.moonshot.cn/v1";
/// Anthropic-compatible base URL.
pub const ANTHROPIC_API_BASE_URL: &str = "https://api.moonshot.ai/anthropic";

impl_dual_dialect_provider!(
    ext = MoonshotExt,
    builder = MoonshotBuilder,
    anthropic_ext = MoonshotAnthropicExt,
    anthropic_builder = MoonshotAnthropicBuilder,
    client_input = String,
    api_key_env = "MOONSHOT_API_KEY",
    base_url = GLOBAL_API_BASE_URL,
    base_url_env = "MOONSHOT_API_BASE",
    anthropic_provider_name = "moonshot",
    anthropic_base_url = ANTHROPIC_API_BASE_URL,
    anthropic_base_url_env = "MOONSHOT_ANTHROPIC_API_BASE",
);

client::impl_capabilities!(
    MoonshotExt,
    completion = CompletionModel<H>,
    model_listing = MoonshotModelLister<H>,
);

crate::providers::internal::model_listing::impl_model_lister!(
    /// [`ModelLister`](crate::client::ModelLister) implementation for the
    /// Moonshot API (`GET /models`).
    ///
    /// Moonshot documents the OpenAI-style `{"object":"list","data":[…]}`
    /// envelope; its entries carry extra fields (`context_length`,
    /// `supports_image_in`, …) that the shared entry ignores.
    MoonshotModelLister,
    Client<H>,
    crate::providers::internal::model_listing::ListModelEntry,
    "Moonshot",
    "/models"
);

impl<H> ClientBuilder<H> {
    pub fn global(self) -> Self {
        self.base_url(GLOBAL_API_BASE_URL)
    }

    pub fn china(self) -> Self {
        self.base_url(CHINA_API_BASE_URL)
    }
}

impl<H> AnthropicClientBuilder<H> {
    pub fn global(self) -> Self {
        self.base_url(ANTHROPIC_API_BASE_URL)
    }
}

const ANTHROPIC_BASE_URLS: AnthropicBaseUrl = AnthropicBaseUrl::new(
    &[
        (GLOBAL_API_BASE_URL, ANTHROPIC_API_BASE_URL),
        (CHINA_API_BASE_URL, "https://api.moonshot.cn/anthropic"),
    ],
    &["/v1", "/v1/"],
    "/anthropic",
);

// ================================================================
// Moonshot Completion API
// ================================================================

/// Moonshot v1 128K context model (legacy)
pub const MOONSHOT_CHAT: &str = "moonshot-v1-128k";

/// Kimi K2 — Mixture-of-Experts model (1T total params, 32B active)
pub const KIMI_K2: &str = "kimi-k2";

/// Kimi K2.5 — Native multimodal agentic model with 256K context
pub const KIMI_K2_5: &str = "kimi-k2.5";

/// Moonshot completion model, driven by the shared OpenAI Chat Completions path.
pub type CompletionModel<H = reqwest::Client> =
    openai::completion::GenericCompletionModel<MoonshotExt, H>;

impl openai::completion::OpenAICompatibleProvider for MoonshotExt {
    const PROVIDER_NAME: &'static str = "moonshot";

    type StreamingUsage = openai::Usage;

    // Moonshot's API rejects the `json_schema` response format; keep the
    // pre-migration behavior of dropping `output_schema` with a warning.
    const SUPPORTS_RESPONSE_FORMAT: bool = false;

    type Response = openai::CompletionResponse;

    fn prepare_request(
        &self,
        request: &mut openai::completion::CompletionRequest,
    ) -> Result<(), CompletionError> {
        // Moonshot only supports `auto`/`none` tool choices. Forcing one
        // specific tool has no workaround; fail fast like the pre-migration
        // conversion did (on main, `openai::ToolChoice::try_from` returned
        // "Provider doesn't support only using specific tools" for every
        // `ToolChoice::Specific`, single- or multi-name).
        if matches!(
            request.tool_choice,
            Some(openai::completion::ToolChoice::Function { .. })
        ) {
            return Err(CompletionError::ProviderError(
                "Moonshot does not support forcing a specific tool".to_string(),
            ));
        }

        // Moonshot does not support `tool_choice: "required"`; coerce it to
        // `auto` and steer the model with an extra user message instead.
        if matches!(
            request.tool_choice,
            Some(openai::completion::ToolChoice::Required)
        ) {
            tracing::warn!(
                "Moonshot does not support tool_choice=required; coercing to auto with an additional steering message"
            );
            request.tool_choice = Some(openai::completion::ToolChoice::Auto);
            request.messages.push(openai::Message::User {
                content: vec![openai::UserContent::Text {
                    text: "Please select a tool to handle the current issue.".to_string(),
                }],
                name: None,
            });
        }

        Ok(())
    }
}

#[cfg(test)]
mod tests {
    use super::{ANTHROPIC_BASE_URLS, MoonshotExt};
    use crate::completion::CompletionRequest;
    use crate::message::{
        AssistantContent, Message, Reasoning, ToolCall, ToolChoice, ToolFunction,
    };
    use crate::providers::openai::completion::{
        CompletionRequest as OpenAICompletionRequest, OpenAICompatibleProvider, OpenAIRequestParams,
    };

    fn prepared_body(request: CompletionRequest, model: &str) -> serde_json::Value {
        let mut request = OpenAICompletionRequest::try_from(OpenAIRequestParams {
            model: model.to_string(),
            request,
            strict_tools: false,
            tool_result_array_content: false,
            supports_response_format: MoonshotExt::SUPPORTS_RESPONSE_FORMAT,
            supports_tools: true,
        })
        .expect("request should convert");
        MoonshotExt
            .prepare_request(&mut request)
            .expect("prepare_request should succeed");
        serde_json::to_value(request).expect("request should serialize")
    }

    #[test]
    fn test_client_initialization() {
        let _client =
            crate::providers::moonshot::Client::new("dummy-key").expect("Client::new() failed");
        let _client_from_builder = crate::providers::moonshot::Client::builder()
            .api_key("dummy-key")
            .build()
            .expect("Client::builder() failed");
        let _anthropic_client = crate::providers::moonshot::AnthropicClient::new("dummy-key")
            .expect("AnthropicClient::new() failed");
        let _anthropic_client_from_builder = crate::providers::moonshot::AnthropicClient::builder()
            .api_key("dummy-key")
            .build()
            .expect("AnthropicClient::builder() failed");
    }

    #[test]
    fn moonshot_preserves_reasoning_content_in_assistant_history() {
        let assistant = Message::Assistant {
            id: None,
            content: vec![
                AssistantContent::Reasoning(Reasoning::new("tool planning")),
                AssistantContent::ToolCall(ToolCall::from_wire(
                    "call_1",
                    ToolFunction {
                        name: "lookup".to_string(),
                        arguments: serde_json::json!({}),
                    },
                )),
            ],
        };

        let request = CompletionRequest {
            model: Some("kimi-k2-thinking".to_string()),
            preamble: None,
            chat_history: vec![assistant],
            documents: vec![],
            tools: vec![],
            temperature: None,
            max_tokens: None,
            tool_choice: None,
            additional_params: None,
            output_schema: None,
            record_telemetry_content: false,
        };

        let body = prepared_body(request, "kimi-k2-thinking");
        assert_eq!(
            body["messages"][0]["reasoning_content"],
            serde_json::json!("tool planning")
        );
    }

    #[test]
    fn moonshot_joins_multiple_reasoning_blocks_with_newline() {
        // A replayed assistant turn carrying two distinct reasoning blocks must
        // keep them newline-separated on the wire, not glued together.
        let assistant = Message::Assistant {
            id: None,
            content: vec![
                AssistantContent::Reasoning(Reasoning::new("first thought")),
                AssistantContent::Reasoning(Reasoning::new("second thought")),
                AssistantContent::Text("done".into()),
            ],
        };

        let request = CompletionRequest {
            model: Some("kimi-k2-thinking".to_string()),
            preamble: None,
            chat_history: vec![assistant],
            documents: vec![],
            tools: vec![],
            temperature: None,
            max_tokens: None,
            tool_choice: None,
            additional_params: None,
            output_schema: None,
            record_telemetry_content: false,
        };

        let body = prepared_body(request, "kimi-k2-thinking");
        assert_eq!(
            body["messages"][0]["reasoning_content"],
            serde_json::json!("first thought\nsecond thought")
        );
    }

    #[test]
    fn moonshot_specific_tool_choice_is_rejected() {
        let request = CompletionRequest {
            model: Some("kimi-k2.5".to_string()),
            preamble: None,
            chat_history: vec![Message::user("Use a tool.")],
            documents: vec![],
            tools: vec![],
            temperature: None,
            max_tokens: None,
            tool_choice: Some(ToolChoice::Specific {
                function_names: vec!["lookup".to_string()],
            }),
            additional_params: None,
            output_schema: None,
            record_telemetry_content: false,
        };

        let mut request = OpenAICompletionRequest::try_from(OpenAIRequestParams {
            model: "kimi-k2.5".to_string(),
            request,
            strict_tools: false,
            tool_result_array_content: false,
            supports_response_format: MoonshotExt::SUPPORTS_RESPONSE_FORMAT,
            supports_tools: true,
        })
        .expect("request should convert");

        let error = MoonshotExt
            .prepare_request(&mut request)
            .expect_err("specific tool choice should be rejected");
        assert!(error.to_string().contains("specific tool"));
    }

    #[test]
    fn moonshot_required_tool_choice_is_coerced() {
        let request = CompletionRequest {
            model: Some("kimi-k2.5".to_string()),
            preamble: None,
            chat_history: vec![Message::user("Use a tool.")],
            documents: vec![],
            tools: vec![],
            temperature: None,
            max_tokens: None,
            tool_choice: Some(ToolChoice::Required),
            additional_params: None,
            output_schema: None,
            record_telemetry_content: false,
        };

        let body = prepared_body(request, "kimi-k2.5");
        assert_eq!(body["tool_choice"], "auto");
        assert_eq!(
            body["messages"]
                .as_array()
                .and_then(|messages| messages.last())
                .and_then(|message| message.get("content"))
                .and_then(|content| content.as_str()),
            Some("Please select a tool to handle the current issue.")
        );
    }

    #[test]
    fn normalize_openai_style_base_to_anthropic_base() {
        assert_eq!(
            ANTHROPIC_BASE_URLS
                .normalize("https://api.moonshot.ai/v1")
                .as_deref(),
            Some("https://api.moonshot.ai/anthropic")
        );
        assert_eq!(
            ANTHROPIC_BASE_URLS
                .normalize("https://api.moonshot.cn/v1")
                .as_deref(),
            Some("https://api.moonshot.cn/anthropic")
        );
        assert_eq!(
            ANTHROPIC_BASE_URLS
                .normalize("https://proxy.example.com/v1")
                .as_deref(),
            Some("https://proxy.example.com/anthropic")
        );
    }

    #[test]
    fn normalize_preserves_existing_anthropic_base() {
        assert_eq!(
            ANTHROPIC_BASE_URLS
                .normalize("https://proxy.example.com/anthropic")
                .as_deref(),
            Some("https://proxy.example.com/anthropic")
        );
    }

    #[test]
    fn anthropic_primary_override_wins() {
        let override_url = ANTHROPIC_BASE_URLS.resolve(
            Some("https://primary.example.com/anthropic"),
            Some("https://api.moonshot.cn/v1"),
        );

        assert_eq!(
            override_url.as_deref(),
            Some("https://primary.example.com/anthropic")
        );
    }
}