llm-connector 1.1.3

//! Anthropic Claude Protocol Implementation - V2 Architecture
//!
//! This module implements the Anthropic Claude API protocol specification.

use crate::core::Protocol;
use crate::error::LlmConnectorError;
use crate::types::{ChatRequest, ChatResponse, Choice, Message, Role, Usage};
use async_trait::async_trait;
use serde::{Deserialize, Serialize};

/// Anthropic Claudeprotocolimplementation
#[derive(Clone, Debug)]
pub struct AnthropicProtocol {
    api_key: String,
}

impl AnthropicProtocol {
    /// Create new Anthropic Protocol instance
    pub fn new(api_key: &str) -> Self {
        Self {
            api_key: api_key.to_string(),
        }
    }

    /// GetAPI key
    pub fn api_key(&self) -> &str {
        &self.api_key
    }
}

#[async_trait]
impl Protocol for AnthropicProtocol {
    type Request = AnthropicRequest;
    type Response = AnthropicResponse;

    fn name(&self) -> &str {
        "anthropic"
    }

    fn chat_endpoint(&self, base_url: &str, _model: &str) -> String {
        let base = base_url.trim_end_matches('/');
        if base.ends_with("/v1") {
            format!("{}/messages", base)
        } else {
            format!("{}/v1/messages", base)
        }
    }

    fn build_request(&self, request: &ChatRequest) -> Result<Self::Request, LlmConnectorError> {
        // Anthropic API requires separating system messages
        let mut system_message = None;
        let mut messages = Vec::new();

        for msg in &request.messages {
            match msg.role {
                Role::System => {
                    // Anthropic only supports one system message, placed in a separate field
                    let text = msg.content_as_text();
                    if system_message.is_none() {
                        system_message = Some(text);
                    } else {
                        // If there are multiple system messages, merge them
                        let existing = system_message.take().unwrap_or_default();
                        system_message = Some(format!("{}\n\n{}", existing, text));
                    }
                }
                Role::User => {
                    // Anthropic always uses array format
                    let content = serde_json::to_value(&msg.content).unwrap();
                    messages.push(AnthropicMessage {
                        role: "user".to_string(),
                        content,
                    });
                }
                Role::Assistant => {
                    // Anthropic always uses array format
                    let content = serde_json::to_value(&msg.content).unwrap();
                    messages.push(AnthropicMessage {
                        role: "assistant".to_string(),
                        content,
                    });
                }
                Role::Tool => {
                    // Anthropic does not support tool role yet, convert to user
                    let text = format!("Tool result: {}", msg.content_as_text());
                    messages.push(AnthropicMessage {
                        role: "user".to_string(),
                        content: serde_json::json!([{"type": "text", "text": text}]),
                    });
                }
            }
        }

        // Handle thinking/budget
        let mut max_tokens = request.max_tokens.unwrap_or(1024);
        let thinking = if let Some(budget) = request.thinking_budget {
            // If budget is set, enable thinking
            // Ensure max_tokens is larger than budget (Anthropic requirement)
            if max_tokens <= budget {
                // If user didn't set enough max_tokens, bump it
                max_tokens = budget + 4096;
            }
            Some(AnthropicThinking {
                thinking_type: "enabled".to_string(),
                budget_tokens: budget,
            })
        } else {
            None
        };

        Ok(AnthropicRequest {
            model: request.model.clone(),
            max_tokens,
            messages,
            system: system_message,
            temperature: request.temperature,
            top_p: request.top_p,
            stream: request.stream,
            thinking,
        })
    }

    fn parse_response(&self, response: &str) -> Result<ChatResponse, LlmConnectorError> {
        let anthropic_response: AnthropicResponse =
            serde_json::from_str(response).map_err(|e| {
                LlmConnectorError::ParseError(format!("Failed to parse Anthropic response: {}", e))
            })?;

        // Anthropic returns single content chunk
        // Convert Anthropic content to MessageBlock
        let message_blocks: Vec<crate::types::MessageBlock> = anthropic_response
            .content
            .iter()
            .map(|c| crate::types::MessageBlock::text(&c.text))
            .collect();

        let content = anthropic_response
            .content
            .first()
            .map(|c| c.text.clone())
            .unwrap_or_default();

        let choices = vec![Choice {
            index: 0,
            message: Message {
                role: Role::Assistant,
                content: message_blocks,
                name: None,
                tool_calls: None,
                tool_call_id: None,
                reasoning_content: None,
                reasoning: None,
                thought: None,
                thinking: None,
            },
            finish_reason: Some(
                anthropic_response
                    .stop_reason
                    .unwrap_or_else(|| "stop".to_string()),
            ),
            logprobs: None,
        }];

        let usage = Some(Usage {
            prompt_tokens: anthropic_response.usage.input_tokens,
            completion_tokens: anthropic_response.usage.output_tokens,
            total_tokens: anthropic_response.usage.input_tokens
                + anthropic_response.usage.output_tokens,
            completion_tokens_details: None,
            prompt_cache_hit_tokens: anthropic_response.usage.cache_read_input_tokens,
            prompt_cache_miss_tokens: None,
            prompt_tokens_details: Some(crate::types::PromptTokensDetails {
                cached_tokens: anthropic_response.usage.cache_read_input_tokens,
                cache_read_input_tokens: anthropic_response.usage.cache_read_input_tokens,
                cache_creation_input_tokens: anthropic_response.usage.cache_creation_input_tokens,
            }),
        });

        Ok(ChatResponse {
            id: anthropic_response.id,
            object: "chat.completion".to_string(),
            created: std::time::SystemTime::now()
                .duration_since(std::time::UNIX_EPOCH)
                .unwrap_or_default()
                .as_secs(),
            model: anthropic_response.model,
            choices,
            content,
            reasoning_content: None,
            usage,
            system_fingerprint: None,
        })
    }

    fn map_error(&self, status: u16, body: &str) -> LlmConnectorError {
        let error_info = serde_json::from_str::<serde_json::Value>(body)
            .ok()
            .and_then(|v| v.get("error").cloned())
            .unwrap_or_else(|| serde_json::json!({"message": body}));

        let message = error_info
            .get("message")
            .and_then(|m| m.as_str())
            .unwrap_or("Unknown Anthropic error");

        let error_type = error_info
            .get("type")
            .and_then(|t| t.as_str())
            .unwrap_or("");

        let msg = format!("Anthropic: {}", message);

        // Detect context length exceeded
        if error_type == "invalid_request_error"
            && (message.contains("too long")
                || message.contains("maximum")
                || message.contains("context"))
        {
            return LlmConnectorError::ContextLengthExceeded(msg);
        }

        match status {
            400 => LlmConnectorError::InvalidRequest(msg),
            401 => LlmConnectorError::AuthenticationError(msg),
            403 => LlmConnectorError::PermissionError(msg),
            429 => LlmConnectorError::RateLimitError(msg),
            500..=599 => LlmConnectorError::ServerError(msg),
            _ => LlmConnectorError::ApiError(format!("Anthropic HTTP {}: {}", status, message)),
        }
    }

    fn auth_headers(&self) -> Vec<(String, String)> {
        let mut headers =
            crate::protocols::common::auth::api_key_header(&self.api_key, "x-api-key");
        headers.push(("anthropic-version".to_string(), "2023-06-01".to_string()));
        headers
    }

    /// Parse Anthropic streamingresponse
    ///
    /// Anthropic uses different streaming format:
    /// - message_start: Contains message object (with id)
    /// - content_block_start: Start content chunk
    /// - content_block_delta: contentdelta（Contains text）
    /// - content_block_stop: End content chunk
    /// - message_delta: Message delta (contains usage)
    /// - message_stop: Message end
    #[cfg(feature = "streaming")]
    async fn parse_stream_response(
        &self,
        response: reqwest::Response,
    ) -> Result<crate::types::ChatStream, LlmConnectorError> {
        use futures_util::StreamExt;
        use std::sync::{Arc, Mutex};

        // Use standard SSE parser with Auto format detection (Anthropic uses standard SSE)
        let events_stream = crate::sse::create_text_stream(response, crate::sse::StreamFormat::Sse);

        // Shared state: save message_id
        let message_id = Arc::new(Mutex::new(String::new()));

        // Convert event stream
        let response_stream = events_stream.filter_map(move |result| {
            let message_id = message_id.clone();
            async move {
                match result {
                    Ok(json_str) => {
                        // Parse Anthropic streaming event
                        match serde_json::from_str::<serde_json::Value>(&json_str) {
                            Ok(event) => {
                                let event_type =
                                    event.get("type").and_then(|t| t.as_str()).unwrap_or("");

                                match event_type {
                                    "message_start" => {
                                        // Extract and save message id
                                        if let Some(msg_id) = event
                                            .get("message")
                                            .and_then(|m| m.get("id"))
                                            .and_then(|id| id.as_str())
                                            && let Ok(mut id) = message_id.lock()
                                        {
                                            *id = msg_id.to_string();
                                        }
                                        // message_start does not return content
                                        None
                                    }
                                    "content_block_delta" | "message_delta" => {
                                        let id = message_id.lock().map(|id| id.clone()).unwrap_or_default();
                                        crate::protocols::common::streamers::interpret_anthropic_event(&event, &id).transpose()
                                    }

                                    _ => {
                                        // Ignore other event types
                                        None
                                    }
                                }
                            }
                            Err(e) => Some(Err(LlmConnectorError::ParseError(format!(
                                "Failed to parse Anthropic streaming event: {}. JSON: {}",
                                e, json_str
                            )))),
                        }
                    }
                    Err(e) => Some(Err(e)),
                }
            }
        });

        Ok(Box::pin(response_stream))
    }
}

// Anthropicrequesttype
#[derive(Serialize, Deserialize, Debug)]
pub struct AnthropicRequest {
    pub model: String,
    pub max_tokens: u32,
    pub messages: Vec<AnthropicMessage>,
    #[serde(skip_serializing_if = "Option::is_none")]
    pub system: Option<String>,
    #[serde(skip_serializing_if = "Option::is_none")]
    pub temperature: Option<f32>,
    #[serde(skip_serializing_if = "Option::is_none")]
    pub top_p: Option<f32>,
    #[serde(skip_serializing_if = "Option::is_none")]
    pub stream: Option<bool>,
    #[serde(skip_serializing_if = "Option::is_none")]
    pub thinking: Option<AnthropicThinking>,
}

#[derive(Serialize, Deserialize, Debug)]
pub struct AnthropicThinking {
    #[serde(rename = "type")]
    pub thinking_type: String,
    pub budget_tokens: u32,
}

#[derive(Serialize, Deserialize, Debug)]
pub struct AnthropicMessage {
    pub role: String,
    pub content: serde_json::Value, // Support String or Array
}

// Anthropicresponsetype
#[derive(Deserialize, Debug)]
pub struct AnthropicResponse {
    pub id: String,
    pub model: String,
    pub content: Vec<AnthropicContent>,
    pub stop_reason: Option<String>,
    pub usage: AnthropicUsage,
}

#[derive(Deserialize, Debug)]
pub struct AnthropicContent {
    #[serde(rename = "type")]
    pub content_type: String,
    pub text: String,
}

#[derive(Deserialize, Debug)]
pub struct AnthropicUsage {
    pub input_tokens: u32,
    pub output_tokens: u32,
    pub cache_creation_input_tokens: Option<u32>,
    pub cache_read_input_tokens: Option<u32>,
}