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//! Anthropic Claude Protocol Implementation - V2 Architecture
//!
//! This module implements the Anthropic Claude API protocol specification.
use crate::core::Protocol;
use crate::types::{ChatRequest, ChatResponse, Message, Role, Choice, Usage};
use crate::error::LlmConnectorError;
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) -> String {
format!("{}/v1/messages", base_url.trim_end_matches('/'))
}
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}]),
});
}
}
}
Ok(AnthropicRequest {
model: request.model.clone(),
max_tokens: request.max_tokens.unwrap_or(1024), // Anthropic requires this to be set
messages,
system: system_message,
temperature: request.temperature,
top_p: request.top_p,
stream: request.stream,
})
}
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: None,
prompt_cache_miss_tokens: None,
prompt_tokens_details: None,
});
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");
match status {
400 => LlmConnectorError::InvalidRequest(format!("Anthropic: {}", message)),
401 => LlmConnectorError::AuthenticationError(format!("Anthropic: {}", message)),
403 => LlmConnectorError::PermissionError(format!("Anthropic: {}", message)),
429 => LlmConnectorError::RateLimitError(format!("Anthropic: {}", message)),
500..=599 => LlmConnectorError::ServerError(format!("Anthropic: {}", message)),
_ => LlmConnectorError::ApiError(format!("Anthropic HTTP {}: {}", status, message)),
}
}
fn auth_headers(&self) -> Vec<(String, String)> {
vec![
("x-api-key".to_string(), self.api_key.clone()),
("Content-Type".to_string(), "application/json".to_string()),
("anthropic-version".to_string(), "2023-06-01".to_string()),
]
}
/// 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 crate::types::{StreamingResponse, StreamingChoice, Delta, Usage};
use futures_util::StreamExt;
use std::sync::{Arc, Mutex};
// Use standard SSE parser
let events_stream = crate::sse::sse_events(response);
// 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()) {
if let Ok(mut id) = message_id.lock() {
*id = msg_id.to_string();
}
}
// message_start does not return content
None
}
"content_block_delta" => {
// Extract text delta
if let Some(text) = event.get("delta")
.and_then(|d| d.get("text"))
.and_then(|t| t.as_str()) {
let id = message_id.lock().ok()
.map(|id| id.clone())
.unwrap_or_default();
// Construct StreamingResponse
Some(Ok(StreamingResponse {
id,
object: "chat.completion.chunk".to_string(),
created: std::time::SystemTime::now()
.duration_since(std::time::UNIX_EPOCH)
.unwrap_or_default()
.as_secs(),
model: "anthropic".to_string(),
choices: vec![StreamingChoice {
index: 0,
delta: Delta {
role: Some(crate::types::Role::Assistant),
content: Some(text.to_string()),
tool_calls: None,
reasoning_content: None,
reasoning: None,
thought: None,
thinking: None,
},
finish_reason: None,
logprobs: None,
}],
content: text.to_string(),
reasoning_content: None,
usage: None,
system_fingerprint: None,
}))
} else {
None
}
}
"message_delta" => {
// Extract usage and stop_reason
let stop_reason = event.get("delta")
.and_then(|d| d.get("stop_reason"))
.and_then(|s| s.as_str())
.map(|s| s.to_string());
let usage = event.get("usage").and_then(|u| {
let input_tokens = u.get("input_tokens").and_then(|t| t.as_u64()).unwrap_or(0) as u32;
let output_tokens = u.get("output_tokens").and_then(|t| t.as_u64()).unwrap_or(0) as u32;
Some(Usage {
prompt_tokens: input_tokens,
completion_tokens: output_tokens,
total_tokens: input_tokens + output_tokens,
completion_tokens_details: None,
prompt_cache_hit_tokens: None,
prompt_cache_miss_tokens: None,
prompt_tokens_details: None,
})
});
let id = message_id.lock().ok()
.map(|id| id.clone())
.unwrap_or_default();
// Return final response (contains finish_reason and usage)
Some(Ok(StreamingResponse {
id,
object: "chat.completion.chunk".to_string(),
created: std::time::SystemTime::now()
.duration_since(std::time::UNIX_EPOCH)
.unwrap_or_default()
.as_secs(),
model: "anthropic".to_string(),
choices: vec![StreamingChoice {
index: 0,
delta: Delta {
role: None,
content: None,
tool_calls: None,
reasoning_content: None,
reasoning: None,
thought: None,
thinking: None,
},
finish_reason: stop_reason,
logprobs: None,
}],
content: String::new(),
reasoning_content: None,
usage,
system_fingerprint: None,
}))
}
_ => {
// 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, 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>,
}
#[derive(Serialize, 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,
}