新增: 初始化 DevFlow 项目仓库
Tauri 2 + Vue 3 + Vite 6 桌面应用，Rust workspace 含 13 个 crate (df-ai / df-storage / df-workflow / df-core / df-execute 等)。 核心能力：AI 聊天 agentic 循环(工具调用+人工审批)、工作流引擎、 任务/想法/项目/阶段管理、可追溯性，及配套前端组件。
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426
crates/df-ai/src/anthropic_compat.rs
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426
crates/df-ai/src/anthropic_compat.rs
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//! Anthropic 兼容 Provider — 通过 /v1/messages 端点实现
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//!
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//! 覆盖: Claude 官方 / GLM 订阅端点 (open.bigmodel.cn/api/anthropic) / 任意 Messages API 网关
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//! 支持: 同步调用 + SSE 流式 + Tool Use
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//!
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//! 与 OpenAI 协议的关键差异由本模块内部完成转换，对外仍暴露统一的 LlmProvider trait，
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//! 上层 (Agentic Loop / AiNode) 无需感知协议。
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use async_trait::async_trait;
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use eventsource_stream::Eventsource;
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use futures::{Stream, StreamExt};
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use reqwest::Client;
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use serde::{Deserialize, Serialize};
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use tracing::{debug, error, warn};
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use crate::provider::{
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CompletionRequest, CompletionResponse, LlmProvider, MessageRole, ProviderFeatures,
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StreamChunk, StreamResult, TokenUsage, ToolCall, ToolCallDelta,
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};
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// ============================================================
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// Anthropic API 请求/响应结构体
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// ============================================================
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/// Anthropic 请求体
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#[derive(Debug, Serialize)]
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struct AnthropicRequest {
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model: String,
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messages: Vec<serde_json::Value>,
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max_tokens: u32,
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#[serde(skip_serializing_if = "Option::is_none")]
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system: Option<String>,
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#[serde(skip_serializing_if = "Option::is_none")]
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temperature: Option<f32>,
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stream: bool,
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#[serde(skip_serializing_if = "Option::is_none")]
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tools: Option<Vec<AnthropicToolDef>>,
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#[serde(skip_serializing_if = "Option::is_none")]
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tool_choice: Option<serde_json::Value>,
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}
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/// Anthropic 工具定义（input_schema 对应 OpenAI 的 parameters）
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#[derive(Debug, Serialize)]
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struct AnthropicToolDef {
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name: String,
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#[serde(skip_serializing_if = "Option::is_none")]
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description: Option<String>,
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input_schema: serde_json::Value,
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}
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/// Anthropic 同步响应
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#[derive(Debug, Deserialize)]
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struct AnthropicResponse {
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#[allow(dead_code)]
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id: String,
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model: String,
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content: Vec<AnthropicContentBlock>,
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#[allow(dead_code)]
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stop_reason: Option<String>,
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usage: AnthropicUsage,
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}
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/// 响应 content 块（text 或 tool_use）
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#[derive(Debug, Deserialize)]
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struct AnthropicContentBlock {
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#[serde(rename = "type")]
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block_type: String,
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#[serde(default)]
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text: Option<String>,
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/// tool_use 块字段
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id: Option<String>,
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name: Option<String>,
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input: Option<serde_json::Value>,
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}
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#[derive(Debug, Deserialize)]
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struct AnthropicUsage {
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input_tokens: u32,
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output_tokens: u32,
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}
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// ============================================================
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// Provider 实现
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// ============================================================
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/// Anthropic 兼容 LLM Provider
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pub struct AnthropicCompatProvider {
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client: Client,
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api_key: String,
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base_url: String,
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default_model: String,
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}
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/// Anthropic 流式协议版本头
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const ANTHROPIC_VERSION: &str = "2023-06-01";
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/// Anthropic max_tokens 必填，缺省时的兜底值
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const DEFAULT_MAX_TOKENS: u32 = 4096;
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impl AnthropicCompatProvider {
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/// 创建 Provider
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///
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/// - `base_url`: 如 `https://api.anthropic.com`、`https://open.bigmodel.cn/api/anthropic`
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/// - `api_key`: API 密钥（Anthropic 用 x-api-key 头，非 Bearer）
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/// - `default_model`: 默认模型名称
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pub fn new(base_url: impl Into<String>, api_key: impl Into<String>, default_model: impl Into<String>) -> Self {
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let client = Client::builder()
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.connect_timeout(std::time::Duration::from_secs(30))
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.build()
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.unwrap_or_else(|e| {
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warn!("reqwest builder 失败，降级为默认 client: {}", e);
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Client::new()
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});
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Self {
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client,
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api_key: api_key.into(),
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base_url: base_url.into(),
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default_model: default_model.into(),
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}
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}
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/// 构建 messages 端点 URL
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///
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/// - 已含 `/v1/messages` → 直接用
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/// - 以 `/v1` 结尾 → 补 `/messages`
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/// - 否则（如 `.../api/anthropic`、`api.anthropic.com`）→ 补 `/v1/messages`
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fn messages_url(&self) -> String {
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let base = self.base_url.trim_end_matches('/');
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if base.ends_with("/v1/messages") {
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return base.to_string();
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}
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if base.ends_with("/v1") {
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return format!("{}/messages", base);
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}
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format!("{}/v1/messages", base)
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}
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/// 将统一 CompletionRequest 转换为 Anthropic 请求体
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///
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/// 转换要点：
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/// - system 消息从 messages 抽离到顶层 system 字段
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/// - assistant 带 tool_calls → content 数组含 text + tool_use 块
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/// - tool_result（role=Tool）→ user 消息含 tool_result 块；连续多个合并为一条 user
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/// - tool_definitions 的 parameters → input_schema
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fn convert_request(&self, req: CompletionRequest) -> AnthropicRequest {
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let model = if req.model.is_empty() {
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self.default_model.clone()
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} else {
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req.model
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};
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// 抽离 system 消息
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let system: Option<String> = {
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let sys: Vec<String> = req
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.messages
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.iter()
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.filter(|m| matches!(m.role, MessageRole::System))
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.map(|m| m.content.clone())
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.collect();
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if sys.is_empty() {
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None
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} else {
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Some(sys.join("\n\n"))
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}
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};
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// 构建非 system 消息（保留顺序，合并连续 tool_result）
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let mut messages: Vec<serde_json::Value> = Vec::new();
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let mut pending_tool_results: Vec<serde_json::Value> = Vec::new();
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for m in req.messages.iter() {
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match m.role {
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MessageRole::System => continue,
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MessageRole::Tool => {
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// 累积 tool_result 块，遇到非 Tool 消息时 flush
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pending_tool_results.push(serde_json::json!({
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"type": "tool_result",
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"tool_use_id": m.tool_call_id,
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"content": m.content,
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}));
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}
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MessageRole::User => {
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Self::flush_tool_results(&mut messages, &mut pending_tool_results);
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messages.push(serde_json::json!({ "role": "user", "content": m.content }));
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}
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MessageRole::Assistant => {
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Self::flush_tool_results(&mut messages, &mut pending_tool_results);
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let mut content: Vec<serde_json::Value> = Vec::new();
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if !m.content.is_empty() {
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content.push(serde_json::json!({ "type": "text", "text": m.content }));
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}
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if let Some(calls) = &m.tool_calls {
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for tc in calls {
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let input: serde_json::Value =
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serde_json::from_str(&tc.function.arguments).unwrap_or(serde_json::Value::Null);
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content.push(serde_json::json!({
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"type": "tool_use",
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"id": tc.id,
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"name": tc.function.name,
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"input": input,
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}));
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}
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}
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if content.is_empty() {
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content.push(serde_json::json!({ "type": "text", "text": "" }));
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}
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messages.push(serde_json::json!({ "role": "assistant", "content": content }));
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}
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}
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}
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Self::flush_tool_results(&mut messages, &mut pending_tool_results);
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let tools = req.tools.map(|defs| {
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defs.into_iter()
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.map(|d| AnthropicToolDef {
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name: d.function.name,
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description: Some(d.function.description).filter(|s| !s.is_empty()),
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input_schema: d.function.parameters,
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})
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.collect()
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});
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AnthropicRequest {
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model,
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messages,
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max_tokens: req.max_tokens.unwrap_or(DEFAULT_MAX_TOKENS),
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system,
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temperature: req.temperature,
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stream: req.stream,
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tools,
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tool_choice: req.tool_choice,
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}
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}
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/// 将累积的 tool_result 块作为一条 user 消息 flush 进消息列表
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fn flush_tool_results(
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messages: &mut Vec<serde_json::Value>,
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pending: &mut Vec<serde_json::Value>,
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) {
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if pending.is_empty() {
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return;
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}
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let blocks: Vec<serde_json::Value> = pending.drain(..).collect();
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messages.push(serde_json::json!({ "role": "user", "content": blocks }));
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}
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/// 统一鉴权头：x-api-key + anthropic-version
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fn auth_headers(&self, rb: reqwest::RequestBuilder) -> reqwest::RequestBuilder {
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rb.header("x-api-key", &self.api_key)
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.header("anthropic-version", ANTHROPIC_VERSION)
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.header("Content-Type", "application/json")
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}
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}
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#[async_trait]
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impl LlmProvider for AnthropicCompatProvider {
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async fn complete(&self, request: CompletionRequest) -> anyhow::Result<CompletionResponse> {
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let mut req = request;
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req.stream = false;
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let body = self.convert_request(req);
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debug!(model = %body.model, "Anthropic 同步调用");
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let resp = self
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.auth_headers(self.client.post(self.messages_url()))
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.json(&body)
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.send()
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.await?;
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if !resp.status().is_success() {
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let status = resp.status();
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let text = resp.text().await.unwrap_or_default();
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error!(%status, %text, "Anthropic API 调用失败");
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anyhow::bail!("Anthropic API 错误 {}: {}", status, text);
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}
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let resp: AnthropicResponse = resp.json().await?;
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// content 块中拼接 text，收集 tool_use
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let mut text = String::new();
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let mut tool_calls: Vec<ToolCall> = Vec::new();
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for block in resp.content {
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match block.block_type.as_str() {
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"text" => {
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if let Some(t) = block.text {
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text.push_str(&t);
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}
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}
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"tool_use" => {
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let id = block.id.unwrap_or_default();
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let name = block.name.unwrap_or_default();
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let args = block
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.input
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.map(|v| serde_json::to_string(&v).unwrap_or_default())
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.unwrap_or_default();
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tool_calls.push(ToolCall::new(id, name, args));
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}
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other => warn!(block_type = other, "Anthropic 响应含未知 content 块类型，已忽略"),
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}
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}
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let usage = TokenUsage {
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prompt_tokens: resp.usage.input_tokens,
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completion_tokens: resp.usage.output_tokens,
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total_tokens: resp.usage.input_tokens + resp.usage.output_tokens,
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};
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Ok(CompletionResponse {
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text,
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model: resp.model,
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usage,
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tool_calls: if tool_calls.is_empty() { None } else { Some(tool_calls) },
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})
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}
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async fn stream(&self, request: CompletionRequest) -> anyhow::Result<StreamResult> {
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let mut req = request;
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req.stream = true;
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let body = self.convert_request(req);
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debug!(model = %body.model, "Anthropic 流式调用");
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let resp = self
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.auth_headers(self.client.post(self.messages_url()))
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.json(&body)
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.send()
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.await?;
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if !resp.status().is_success() {
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let status = resp.status();
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let text = resp.text().await.unwrap_or_default();
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error!(%status, %text, "Anthropic 流式 API 调用失败");
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anyhow::bail!("Anthropic 流式 API 错误 {}: {}", status, text);
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}
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// 流式解析：eventsource 逐事件处理，按 type 字段分发转 StreamChunk
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let stream = resp
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.bytes_stream()
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.eventsource()
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.map(move |event| match event {
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Ok(ev) => {
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// 解析 data 中的 JSON，按 type 字段决定如何转 StreamChunk
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let v: serde_json::Value = match serde_json::from_str(&ev.data) {
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Ok(v) => v,
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Err(_) => return Ok(StreamChunk { delta: String::new(), finished: false, tool_calls: None }),
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};
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let ty = v.get("type").and_then(|t| t.as_str()).unwrap_or("");
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match ty {
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// 文本增量
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"content_block_delta" => {
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if let Some(delta) = v.get("delta") {
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if delta.get("type").and_then(|t| t.as_str()) == Some("text_delta") {
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let text = delta.get("text").and_then(|t| t.as_str()).unwrap_or("").to_string();
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return Ok(StreamChunk { delta: text, finished: false, tool_calls: None });
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}
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// 工具入参增量
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if delta.get("type").and_then(|t| t.as_str()) == Some("input_json_delta") {
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let partial = delta.get("partial_json").and_then(|t| t.as_str()).unwrap_or("").to_string();
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let idx = v.get("index").and_then(|i| i.as_u64()).unwrap_or(0) as u32;
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return Ok(StreamChunk {
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delta: String::new(),
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finished: false,
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tool_calls: Some(vec![ToolCallDelta {
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index: idx,
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id: None,
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function_name: None,
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function_arguments: Some(partial),
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}]),
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});
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}
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}
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Ok(StreamChunk { delta: String::new(), finished: false, tool_calls: None })
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}
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// 工具块开始：带 id + name
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"content_block_start" => {
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if let Some(cb) = v.get("content_block") {
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if cb.get("type").and_then(|t| t.as_str()) == Some("tool_use") {
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let idx = v.get("index").and_then(|i| i.as_u64()).unwrap_or(0) as u32;
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let id = cb.get("id").and_then(|t| t.as_str()).map(|s| s.to_string());
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let name = cb.get("name").and_then(|t| t.as_str()).map(|s| s.to_string());
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return Ok(StreamChunk {
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delta: String::new(),
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finished: false,
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tool_calls: Some(vec![ToolCallDelta {
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index: idx,
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id,
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function_name: name,
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function_arguments: None,
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}]),
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});
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}
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}
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Ok(StreamChunk { delta: String::new(), finished: false, tool_calls: None })
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}
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// 消息结束
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"message_stop" => Ok(StreamChunk { delta: String::new(), finished: true, tool_calls: None }),
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// 错误事件
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"error" => {
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let msg = v.get("error").and_then(|e| e.get("message")).and_then(|m| m.as_str()).unwrap_or("stream error");
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error!(%msg, "Anthropic 流式错误事件");
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Ok(StreamChunk { delta: String::new(), finished: true, tool_calls: None })
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}
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// message_start / content_block_stop / message_delta 等不产出 chunk
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_ => Ok(StreamChunk { delta: String::new(), finished: false, tool_calls: None }),
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}
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}
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Err(e) => {
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error!(error = %e, "Anthropic SSE 事件流错误");
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Err(anyhow::anyhow!("Anthropic SSE 错误: {}", e))
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}
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});
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Ok(Box::pin(stream))
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}
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fn name(&self) -> &str {
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"anthropic-compat"
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}
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fn supported_features(&self) -> ProviderFeatures {
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ProviderFeatures {
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streaming: true,
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function_calling: true,
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vision: false,
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}
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}
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}
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