Files
DevFlow/crates/df-ai/src/anthropic_compat.rs
绝尘 55bc1e1b23 重构: audit第三批cache + anthropic_compat拆分(strategy并行)
- audit 第三批: 新建 audit/cache.rs(151行 find_cached_high_risk_result/canonical_args_key/sort_object_keys/PENDING_APPROVAL_PLACEHOLDER), audit/mod.rs 586→451(-135); pub(crate) re-export, F-09 per_conv保留
- anthropic_compat 拆分: 新建 df-ai/anthropic_helpers.rs(223行 apply_anthropic_event + 5 struct + 2常量), anthropic_compat.rs 1036→842; Provider impl保留(impl块约束), 字段pub(crate)
主代兜底: cargo check --workspace 0 + test df-ai 119 + test devflow 98
strategy: 核心库自底向上, 单批1-2文件原子, impl块约束(Provider方法保留只抽纯函数/类型)
git add指定(audit/* + df-ai/*, 不含其他会话)
2026-06-19 04:31:19 +08:00

843 lines
39 KiB
Rust
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//! Anthropic 兼容 Provider — 通过 /v1/messages 端点实现
//!
//! 覆盖: Claude 官方 / GLM 订阅端点 (open.bigmodel.cn/api/anthropic) / 任意 Messages API 网关
//! 支持: 同步调用 + SSE 流式 + Tool Use
//!
//! 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
//! 上层 (Agentic Loop / AiNode) 无需感知协议。
//!
//! 协议数据结构(请求/响应 struct与 SSE 事件解析纯函数已抽至 `anthropic_helpers`
//! 本模块仅保留 Provider struct + implHTTP 调用Rust impl 块不可跨文件故作此切分。
use async_trait::async_trait;
use eventsource_stream::Eventsource;
use futures::StreamExt;
use reqwest::Client;
use std::time::Duration;
use tracing::{debug, error, warn};
use crate::provider::{
CompletionRequest, CompletionResponse, LlmProvider, MessageRole,
StreamResult, TokenUsage, ToolCall,
};
// ChatMessage 仅单测构造 CompletionRequest 用,避免非 test 构建的 unused import 警告。
#[cfg(test)]
use crate::provider::ChatMessage;
use crate::retry::{
retry_with_backoff, AttemptOutcome, is_reqwest_error_retryable, is_status_retryable,
};
// 协议数据结构 + SSE 纯解析apply_anthropic_event / AnthropicRequest 等)抽至 anthropic_helpers
// 此处 use 引入以保持本模块内引用路径不变(零行为变更搬迁)。
use crate::anthropic_helpers::{
apply_anthropic_event, AnthropicRequest, AnthropicResponse, AnthropicToolDef,
ANTHROPIC_VERSION, DEFAULT_MAX_TOKENS,
};
// ============================================================
// Provider 实现
// ============================================================
/// Anthropic 兼容 LLM Provider
pub struct AnthropicCompatProvider {
client: Client,
api_key: String,
base_url: String,
default_model: String,
}
impl AnthropicCompatProvider {
/// 创建 Provider
///
/// - `base_url`: 如 `https://api.anthropic.com`、`https://open.bigmodel.cn/api/anthropic`
/// - `api_key`: API 密钥Anthropic 用 x-api-key 头,非 Bearer
/// - `default_model`: 默认模型名称
pub fn new(base_url: impl Into<String>, api_key: impl Into<String>, default_model: impl Into<String>) -> Self {
// SW-260618-10: reqwest Client 构建抽 crate::build_provider_client与 OpenAI 共用 DRY
let client = crate::build_provider_client();
Self {
client,
api_key: api_key.into(),
base_url: base_url.into(),
default_model: default_model.into(),
}
}
/// 构建 messages 端点 URL
///
/// - 已含 `/v1/messages` → 直接用
/// - 以 `/v1` 结尾 → 补 `/messages`
/// - 否则(如 `.../api/anthropic`、`api.anthropic.com`)→ 补 `/v1/messages`
fn messages_url(&self) -> String {
let base = self.base_url.trim_end_matches('/');
if base.ends_with("/v1/messages") {
return base.to_string();
}
if base.ends_with("/v1") {
return format!("{}/messages", base);
}
format!("{}/v1/messages", base)
}
/// 将统一 CompletionRequest 转换为 Anthropic 请求体
///
/// 转换要点:
/// - system 消息从 messages 抽离到顶层 system 字段
/// - assistant 带 tool_calls → content 数组含 text + tool_use 块
/// - tool_resultrole=Tool→ user 消息含 tool_result 块;连续多个合并为一条 user
/// - tool_definitions 的 parameters → input_schema
fn convert_request(&self, req: CompletionRequest) -> AnthropicRequest {
let model = if req.model.is_empty() {
self.default_model.clone()
} else {
req.model
};
// 抽离 system 消息
let system: Option<String> = {
let sys: Vec<String> = req
.messages
.iter()
.filter(|m| matches!(m.role, MessageRole::System))
.map(|m| m.content.clone())
.collect();
if sys.is_empty() {
None
} else {
Some(sys.join("\n\n"))
}
};
// 构建非 system 消息(保留顺序,合并连续 tool_result
let mut messages: Vec<serde_json::Value> = Vec::new();
let mut pending_tool_results: Vec<serde_json::Value> = Vec::new();
for m in req.messages.iter() {
match m.role {
MessageRole::System => continue,
MessageRole::Tool => {
// 累积 tool_result 块,遇到非 Tool 消息时 flush。
// tool_use_id 为 None 时绝不能发 nullGLM anthropic 端点会 500
// 报 'ClaudeContentBlockToolResult' object has no attribute 'id'
// 致会话卡死持续 500跳过该块并告警。
match &m.tool_call_id {
Some(tid) if !tid.is_empty() => {
pending_tool_results.push(serde_json::json!({
"type": "tool_result",
"tool_use_id": tid,
"content": m.content,
}));
}
_ => {
warn!(
content_preview = %m.content.chars().take(80).collect::<String>(),
"Anthropic tool_result 缺少 tool_use_id已跳过该块发 null 会触发 GLM 500"
);
}
}
}
MessageRole::User => {
Self::flush_tool_results(&mut messages, &mut pending_tool_results);
// F-260614-05 Phase 2a: 多模态 user 消息 → content blocks 数组text/image
// 含图时把 content + parts 拍平成 blocksText 片 → {type:text}
// Image 片 → {type:image, source:{type:base64, media_type, data}}。
// Anthropic 协议要求 image 必须内嵌 base64不接受 URL 直传)。
// 现状前端Phase2b只产 base64 模式图片片url 模式当前不可达。
// 未来若加 url 图片输入,必须在 commands 层补 url→base64 预拉
//provider 不发额外 HTTP否则下方兜底会发空 data 致 Anthropic 400。
// 纯文本消息(无图)保持原字符串简写,与现有端点零回归。
if m.has_image() {
let blocks: Vec<serde_json::Value> = m
.flattened_parts()
.into_iter()
.map(|p| match p {
crate::provider::ContentPart::Text { text } => serde_json::json!({
"type": "text",
"text": text,
}),
crate::provider::ContentPart::Image { url, base64, media_type, alt: _ } => {
// p 已被 match 取得所有权,直接 move media_type/base64 避免大 base64 clone。
let mt = media_type.unwrap_or_else(|| "image/png".into());
let data = base64.unwrap_or_else(|| {
// 完整性兜底:当前 url 模式不可达(前端 Phase2b 只产 base64 图片片)。
// 若未来接入 url 图片输入而 commands 层未补 url→base64 预拉,
// 此处会发空 data 致 Anthropic 400warn 留痕但不阻塞(避免静默吞数据)。
if url.is_some() {
warn!(
url = ?url,
"Anthropic user 消息含 Image(url) 但 base64 缺失,将发空 datacommands 层未补 url→base64 预拉)"
);
}
String::new()
});
serde_json::json!({
"type": "image",
"source": {
"type": "base64",
"media_type": mt,
"data": data,
}
})
}
})
.collect();
messages.push(serde_json::json!({ "role": "user", "content": blocks }));
} else {
messages.push(serde_json::json!({ "role": "user", "content": m.content }));
}
}
MessageRole::Assistant => {
Self::flush_tool_results(&mut messages, &mut pending_tool_results);
let mut content: Vec<serde_json::Value> = Vec::new();
if !m.content.is_empty() {
content.push(serde_json::json!({ "type": "text", "text": m.content }));
}
if let Some(calls) = &m.tool_calls {
for tc in calls {
// B-260618-25: arguments 非法 JSON(流式中断残留 / ToolCall::new 默认空串)
// → 空 object 兜底。Anthropic/GLM 要求 tool_use.input 必为 object,
// null 直触发 1214「messages 参数非法」。
let input: serde_json::Value = serde_json::from_str(&tc.function.arguments)
.unwrap_or_else(|_| serde_json::json!({}));
content.push(serde_json::json!({
"type": "tool_use",
"id": tc.id,
"name": tc.function.name,
"input": input,
}));
}
}
if content.is_empty() {
content.push(serde_json::json!({ "type": "text", "text": "" }));
}
messages.push(serde_json::json!({ "role": "assistant", "content": content }));
}
}
}
Self::flush_tool_results(&mut messages, &mut pending_tool_results);
let tools = req.tools.map(|defs| {
defs.into_iter()
.map(|d| AnthropicToolDef {
name: d.function.name,
description: Some(d.function.description).filter(|s| !s.is_empty()),
// B-260618-25: input_schema 非 object(未来误用)→ 兜底 {"type":"object"},
// 防 Anthropic 拒非法 tool schema(当前全走 object_schema 恒 object,纯防御)。
input_schema: if d.function.parameters.is_object() {
d.function.parameters
} else {
serde_json::json!({"type": "object"})
},
})
.collect()
});
AnthropicRequest {
model,
messages,
max_tokens: req.max_tokens.unwrap_or(DEFAULT_MAX_TOKENS),
system,
temperature: req.temperature,
stream: req.stream,
tools,
tool_choice: req.tool_choice,
}
}
/// 将累积的 tool_result 块作为一条 user 消息 flush 进消息列表
fn flush_tool_results(
messages: &mut Vec<serde_json::Value>,
pending: &mut Vec<serde_json::Value>,
) {
if pending.is_empty() {
return;
}
let blocks: Vec<serde_json::Value> = pending.drain(..).collect();
messages.push(serde_json::json!({ "role": "user", "content": blocks }));
}
/// 生成 messages 诊断摘要(每条 role + content 形态 + tool 标记),不含敏感数据。
/// B-260618-27: 1214 类错误时随 bail 文案直达前端 raw,定位哪条/字段非法。
fn summarize_messages(messages: &[serde_json::Value]) -> String {
let lines: Vec<String> = messages
.iter()
.enumerate()
.map(|(i, m)| {
let role = m.get("role").and_then(|r| r.as_str()).unwrap_or("?");
let desc = match m.get("content") {
Some(serde_json::Value::String(s)) => format!("text({}B)", s.len()),
Some(serde_json::Value::Array(blocks)) => {
let parts: Vec<String> = blocks
.iter()
.map(|b| {
let ty = b.get("type").and_then(|t| t.as_str()).unwrap_or("?");
match ty {
"text" => format!(
"text({}B)",
b.get("text").and_then(|t| t.as_str()).map(|s| s.len()).unwrap_or(0)
),
"tool_use" => format!(
"tool_use[id={},input_obj={}]",
b.get("id").and_then(|t| t.as_str()).unwrap_or(""),
b.get("input").map(|v| v.is_object()).unwrap_or(false)
),
"tool_result" => format!(
"tool_result[tid={}]",
b.get("tool_use_id").and_then(|t| t.as_str()).unwrap_or("")
),
"image" => "image".to_string(),
_ => ty.to_string(),
}
})
.collect();
format!("[{}]", parts.join(","))
}
_ => "?".to_string(),
};
format!("#{}:{} {}", i, role, desc)
})
.collect();
format!("{} msgs: {}", lines.len(), lines.join(" | "))
}
/// B-260618-27: 协议预检——扫 messages 发现确定非法形态,命中返回原因(仅诊断不修复)。
/// 覆盖:首条非 user / 连续同 role / tool_use input 非 object / 空 content / orphan tool_result
/// (tool_use_id 无前置 tool_use,常见于裁剪/过滤后 assistant 被删但 tool_result 留)。
fn precheck_messages(messages: &[serde_json::Value]) -> Result<(), String> {
if messages.is_empty() {
return Err("messages 为空".into());
}
let first_role = messages[0].get("role").and_then(|r| r.as_str()).unwrap_or("");
if first_role != "user" {
return Err(format!("首条 role={} 非法(须 user)", first_role));
}
for w in messages.windows(2) {
let r0 = w[0].get("role").and_then(|r| r.as_str()).unwrap_or("");
let r1 = w[1].get("role").and_then(|r| r.as_str()).unwrap_or("");
if r0 == r1 && (r0 == "user" || r0 == "assistant") {
return Err(format!("连续同 role={}", r0));
}
}
let mut tool_use_ids: Vec<&str> = Vec::new();
for (i, m) in messages.iter().enumerate() {
let role = m.get("role").and_then(|r| r.as_str()).unwrap_or("");
match m.get("content") {
Some(serde_json::Value::String(s)) if s.is_empty() && role == "user" => {
return Err(format!("#{} user content 空", i));
}
Some(serde_json::Value::Array(blocks)) => {
if blocks.is_empty() && role == "user" {
return Err(format!("#{} user content 空数组", i));
}
for b in blocks {
match b.get("type").and_then(|t| t.as_str()).unwrap_or("") {
"tool_use" => {
let id = b.get("id").and_then(|t| t.as_str()).unwrap_or("");
tool_use_ids.push(id);
if !b.get("input").map(|v| v.is_object()).unwrap_or(false) {
return Err(format!("#{} tool_use input 非 object", i));
}
}
"tool_result" => {
let tid = b.get("tool_use_id").and_then(|t| t.as_str()).unwrap_or("");
if !tid.is_empty() && !tool_use_ids.contains(&tid) {
return Err(format!(
"#{} orphan tool_result(tid={} 无前置 tool_use)",
i, tid
));
}
}
_ => {}
}
}
}
_ => {}
}
}
Ok(())
}
/// 统一鉴权头x-api-key + anthropic-version
fn auth_headers(&self, rb: reqwest::RequestBuilder) -> reqwest::RequestBuilder {
rb.header("x-api-key", &self.api_key)
.header("anthropic-version", ANTHROPIC_VERSION)
.header("Content-Type", "application/json")
}
}
#[async_trait]
impl LlmProvider for AnthropicCompatProvider {
async fn complete(&self, request: CompletionRequest) -> anyhow::Result<CompletionResponse> {
let mut req = request;
req.stream = false;
let body = self.convert_request(req);
// B-260618-27: 协议预检——命中非法 bail 含 messages 摘要,把 GLM 模糊 1214 转明确诊断
if let Err(reason) = Self::precheck_messages(&body.messages) {
let summary = Self::summarize_messages(&body.messages);
warn!(%reason, %summary, "Anthropic messages 协议预检失败");
anyhow::bail!("messages 预检失败: {} | 摘要: {}", reason, summary);
}
debug!(model = %body.model, "Anthropic 同步调用");
// 指数退避重试(B-260616-07): 包裹 send + 状态码判定。
// 同时补 FR-R4 遗漏: Anthropic 同步路径此前无单请求 timeout(建连后挂起会无限 hang)
// 此处加 60s timeout与 OpenAI 路径对齐。
let label = format!("Anthropic[{}]", body.model);
retry_with_backoff(&label, move |_| {
let client = self.client.clone();
let url = self.messages_url();
let api_key = self.api_key.clone();
let body = body.clone();
async move {
// send: 补 60s 单请求 timeout(此前缺失FR-R4 遗漏)
let rb = client
.post(url)
.header("x-api-key", &api_key)
.header("anthropic-version", ANTHROPIC_VERSION)
.header("Content-Type", "application/json")
.timeout(Duration::from_secs(60))
.version(reqwest::Version::HTTP_11)
.json(&body);
let resp = match rb.send().await {
Ok(r) => r,
Err(e) => {
// B-260618-26: 记 reqwest 错误源因链(is_*/source)。原仅 Display
// "error sending request for url" 无法定位 reset/TLS/超时/body 真因。
tracing::error!(
is_timeout = e.is_timeout(),
is_connect = e.is_connect(),
is_body = e.is_body(),
is_request = e.is_request(),
url = ?e.url(),
source = ?std::error::Error::source(&e),
"Anthropic 同步 send 失败"
);
if is_reqwest_error_retryable(&e) {
return AttemptOutcome::Retryable(format!("请求失败(可重试): {}", e));
}
return AttemptOutcome::Fatal(format!(
"请求失败(不可重试): {} [timeout={} connect={} body={} src={:?}]",
e,
e.is_timeout(),
e.is_connect(),
e.is_body(),
std::error::Error::source(&e)
));
}
};
if !resp.status().is_success() {
let status = resp.status().as_u16();
let text = resp.text().await.unwrap_or_default();
let msg = format!("Anthropic API 错误 {}: {}", status, text);
if is_status_retryable(status) {
warn!(%status, "Anthropic 同步调用可重试状态码");
return AttemptOutcome::Retryable(msg);
}
error!(%status, %text, "Anthropic API 调用失败(不可重试)");
return AttemptOutcome::Fatal(msg);
}
let resp: AnthropicResponse = match resp.json().await {
Ok(r) => r,
Err(e) => return AttemptOutcome::Fatal(format!("响应解析失败: {}", e)),
};
// content 块中拼接 text收集 tool_use
let mut text = String::new();
let mut tool_calls: Vec<ToolCall> = Vec::new();
for block in resp.content {
match block.block_type.as_str() {
"text" => {
if let Some(t) = block.text {
text.push_str(&t);
}
}
"tool_use" => {
let id = match block.id {
Some(id) if !id.is_empty() => id,
_ => {
warn!(
name = ?block.name,
"Anthropic tool_use 块缺少 id已跳过空 id 会回传空 tool_use_id 触发 500"
);
continue;
}
};
let name = block.name.unwrap_or_default();
let args = block
.input
.map(|v| serde_json::to_string(&v).unwrap_or_default())
.unwrap_or_default();
tool_calls.push(ToolCall::new(id, name, args));
}
other => warn!(block_type = other, "Anthropic 响应含未知 content 块类型,已忽略"),
}
}
let usage = TokenUsage {
prompt_tokens: resp.usage.input_tokens,
completion_tokens: resp.usage.output_tokens,
total_tokens: resp.usage.input_tokens + resp.usage.output_tokens,
};
AttemptOutcome::Ok(CompletionResponse {
text,
model: resp.model,
usage,
tool_calls: if tool_calls.is_empty() { None } else { Some(tool_calls) },
reasoning_content: None,
})
}
})
.await
}
async fn stream(&self, request: CompletionRequest) -> anyhow::Result<StreamResult> {
let mut req = request;
req.stream = true;
let body = self.convert_request(req);
// B-260618-27: 协议预检——命中非法 bail 含 messages 摘要,把 GLM 模糊 1214 转明确诊断
if let Err(reason) = Self::precheck_messages(&body.messages) {
let summary = Self::summarize_messages(&body.messages);
warn!(%reason, %summary, "Anthropic messages 协议预检失败");
anyhow::bail!("messages 预检失败: {} | 摘要: {}", reason, summary);
}
debug!(model = %body.model, "Anthropic 流式调用");
let resp = match self
.auth_headers(self.client.post(self.messages_url()))
.json(&body)
.version(reqwest::Version::HTTP_11)
.send()
.await
{
Ok(r) => r,
Err(e) => {
// B-260618-26: 记 reqwest 错误源因链。原 ? 转 anyhow 仅 Display
// "error sending request for url" 无法定位 reset/TLS/超时/body 真因。
tracing::error!(
is_timeout = e.is_timeout(),
is_connect = e.is_connect(),
is_body = e.is_body(),
is_request = e.is_request(),
url = %self.messages_url(),
source = ?std::error::Error::source(&e),
"Anthropic 流式 send 失败"
);
anyhow::bail!(
"send 失败: {} [timeout={} connect={} body={} request={} src={:?}]",
e,
e.is_timeout(),
e.is_connect(),
e.is_body(),
e.is_request(),
std::error::Error::source(&e)
);
}
};
if !resp.status().is_success() {
let status = resp.status();
let text = resp.text().await.unwrap_or_default();
error!(%status, %text, "Anthropic 流式 API 调用失败");
anyhow::bail!("Anthropic 流式 API 错误 {}: {}", status, text);
}
// 流式解析eventsource 逐事件处理,按 type 字段分发转 StreamChunk。
// 事件解析/usage 累积逻辑抽到 apply_anthropic_event 纯函数,便于单测;此处闭包只负责传 data。
// usage 累积message_start 给 input_tokensmessage_delta 给累计 output_tokens非增量message_stop 带出。
let mut usage_accum: Option<TokenUsage> = None;
// B-260618-28: MidStream error(如 GLM 1214 messages 非法)时附 messages 摘要定位哪条非法。
// precheck(Init 路径,发送前)漏的 case,靠此在 SSE error 事件暴露实际 messages 结构到前端 raw。
let messages_summary = Self::summarize_messages(&body.messages);
let stream = resp
.bytes_stream()
.eventsource()
.map(move |event| match event {
Ok(ev) => {
let mut chunk = apply_anthropic_event(&ev.data, &mut usage_accum);
// GLM 中途 error(如 1214)→ chunk.error 附 messages 摘要,经 stream_recv MidStream
// 路径 emit AiError raw,前端直接看到实际 messages 结构定位非法字段。
if let Some(err) = chunk.error.as_mut() {
*err = format!("{} | messages 摘要: {}", err, messages_summary);
}
Ok(chunk)
}
Err(e) => {
// 保留 #[source] 因果链: anyhow!("...{}", e) 仅把 e 的 Display 塞进 message,
// 丢掉 source(无法 downcast/遍历)。改用 Error::from(e).context(...):
// Display 不变(仍为 "Anthropic SSE 错误: {e}"), 且 e 作为 .source() 可追溯。
// 顺序: 先 format(e) 构造 context 文案, 再 Error::from(e) move e 进 source。
let ctx = format!("Anthropic SSE 错误: {}", e);
error!(error = %e, "Anthropic SSE 事件流错误");
Err(anyhow::Error::from(e).context(ctx))
}
});
Ok(Box::pin(stream))
}
fn name(&self) -> &str {
"anthropic-compat"
}
fn endpoint(&self) -> String {
self.messages_url()
}
}
// ============================================================
// 单测(不发真实 HTTP喂构造的 SSE data 字符串序列)
// ============================================================
#[cfg(test)]
mod tests {
use super::*;
// apply_anthropic_event / TokenUsage 经 super::*(含 anthropic_helpers::apply_anthropic_event 的 use可见。
/// 辅助:构造 message_start 事件
fn message_start(input_tokens: u32) -> String {
format!(
r#"{{"type":"message_start","message":{{"usage":{{"input_tokens":{},"output_tokens":0}}}}}}"#,
input_tokens
)
}
/// 辅助:构造 message_delta 事件output_tokens 为累计值)
fn message_delta(output_tokens: u32) -> String {
format!(
r#"{{"type":"message_delta","delta":{{"stop_reason":"end_turn"}},"usage":{{"output_tokens":{}}}}}"#,
output_tokens
)
}
/// 辅助:构造文本增量 content_block_delta
fn text_delta(text: &str) -> String {
format!(
r#"{{"type":"content_block_delta","index":0,"delta":{{"type":"text_delta","text":"{}"}}}}"#,
text
)
}
/// 辅助:构造 message_stop 事件
fn message_stop() -> &'static str {
r#"{"type":"message_stop"}"#
}
/// 完整流message_start 初始化 input + 多次 message_delta 累计覆盖 output + message_stop 带出
#[test]
fn anthropic_full_stream_accumulates_usage() {
let mut acc: Option<TokenUsage> = None;
// 1) message_startinput=42output=0
let c = apply_anthropic_event(&message_start(42), &mut acc);
assert!(!c.finished);
assert!(c.usage.is_none());
let a = acc.as_ref().expect("message_start 应初始化累加器");
assert_eq!(a.prompt_tokens, 42);
assert_eq!(a.completion_tokens, 0);
assert_eq!(a.total_tokens, 42);
// 2) 文本增量不影响 usage
let c = apply_anthropic_event(&text_delta("Hello"), &mut acc);
assert_eq!(c.delta, "Hello");
assert!(!c.finished);
assert_eq!(acc.as_ref().unwrap().completion_tokens, 0, "文本增量不应改 output");
// 3) message_deltaoutput_tokens=10累计值覆盖
let c = apply_anthropic_event(&message_delta(10), &mut acc);
assert!(!c.finished);
let a = acc.as_ref().unwrap();
assert_eq!(a.prompt_tokens, 42, "input 保持");
assert_eq!(a.completion_tokens, 10, "output 被覆盖为累计值");
assert_eq!(a.total_tokens, 52, "total 重算 = input+output");
// 4) 再次 message_deltaoutput_tokens=30更大累计值再覆盖
let _ = apply_anthropic_event(&message_delta(30), &mut acc);
let a = acc.as_ref().unwrap();
assert_eq!(a.completion_tokens, 30, "后续累计值覆盖前值");
assert_eq!(a.total_tokens, 72);
// 5) message_stop带出累积 usagefinished=true累加器清空
let c = apply_anthropic_event(message_stop(), &mut acc);
assert!(c.finished);
let u = c.usage.expect("message_stop 应带出累积 usage");
assert_eq!(u.prompt_tokens, 42);
assert_eq!(u.completion_tokens, 30);
assert_eq!(u.total_tokens, 72);
assert!(acc.is_none(), "take() 后累加器应清空");
}
/// message_delta 在没有 message_start 时也能补全累加器get_or_insert 兜底)
#[test]
fn anthropic_message_delta_without_start_uses_default_input() {
let mut acc: Option<TokenUsage> = None;
let _ = apply_anthropic_event(&message_delta(15), &mut acc);
let a = acc.as_ref().unwrap();
assert_eq!(a.prompt_tokens, 0, "无 message_start 时 input 兜底为 0");
assert_eq!(a.completion_tokens, 15);
assert_eq!(a.total_tokens, 15);
}
/// message_delta 的 output_tokens 必须是累计覆盖(非累加):连续两个 delta 5 和 8结果应是 8 不是 13
#[test]
fn anthropic_message_delta_output_is_cumulative_not_incremental() {
let mut acc: Option<TokenUsage> = None;
apply_anthropic_event(&message_start(100), &mut acc);
apply_anthropic_event(&message_delta(5), &mut acc);
apply_anthropic_event(&message_delta(8), &mut acc);
let c = apply_anthropic_event(message_stop(), &mut acc);
let u = c.usage.unwrap();
assert_eq!(u.completion_tokens, 8, "output_tokens 是累计值,覆盖而非累加");
assert_eq!(u.total_tokens, 108);
}
/// 无 usage 字段的流message_stop 时 usage 为 None
#[test]
fn anthropic_message_stop_without_any_usage() {
let mut acc: Option<TokenUsage> = None;
let _ = apply_anthropic_event(&text_delta("hi"), &mut acc);
assert!(acc.is_none(), "文本增量不初始化累加器");
let c = apply_anthropic_event(message_stop(), &mut acc);
assert!(c.finished);
assert!(c.usage.is_none(), "无 usage 时 message_stop usage 为 None");
}
/// content_block_start (tool_use) 带 id+name
#[test]
fn anthropic_content_block_start_tool_use() {
let mut acc: Option<TokenUsage> = None;
let data = r#"{"type":"content_block_start","index":1,"content_block":{"type":"tool_use","id":"tool_1","name":"get_weather"}}"#;
let c = apply_anthropic_event(data, &mut acc);
assert!(acc.is_none(), "content_block_start 不动 usage");
let tcs = c.tool_calls.expect("应有 tool_calls");
assert_eq!(tcs.len(), 1);
assert_eq!(tcs[0].index, 1);
assert_eq!(tcs[0].id.as_deref(), Some("tool_1"));
assert_eq!(tcs[0].function_name.as_deref(), Some("get_weather"));
assert!(tcs[0].function_arguments.is_none());
assert!(!c.finished);
}
/// content_block_delta (input_json_delta) → 工具入参增量
#[test]
fn anthropic_content_block_delta_input_json() {
let mut acc: Option<TokenUsage> = None;
let data = r#"{"type":"content_block_delta","index":2,"delta":{"type":"input_json_delta","partial_json":"{\"q\":"}}"#;
let c = apply_anthropic_event(data, &mut acc);
let tcs = c.tool_calls.expect("应有 tool_calls 增量");
assert_eq!(tcs[0].index, 2);
assert_eq!(tcs[0].function_arguments.as_deref(), Some("{\"q\":"));
assert!(tcs[0].id.is_none());
assert_eq!(c.delta, "");
assert!(!c.finished);
}
/// error 事件 → error=Some + finished=falseR-P1-1避免残缺响应被当正常完成入库
/// 由 stream_llm 识别 error 非空发 AiError + 丢弃残缺,与 OpenAI 路径 Err 一致)
#[test]
fn anthropic_error_event_yields_error_not_finished() {
let mut acc: Option<TokenUsage> = None;
apply_anthropic_event(&message_start(10), &mut acc);
let c = apply_anthropic_event(r#"{"type":"error","error":{"message":"overloaded"}}"#, &mut acc);
assert!(!c.finished, "error 不走 finished 完成路径,否则残缺响应会被当正常完成");
assert_eq!(c.error.as_deref(), Some("overloaded"), "error 事件应携带错误消息");
assert!(c.usage.is_none(), "error 不带出 usage");
assert!(c.delta.is_empty(), "error 不带文本增量");
assert!(acc.is_some(), "error 不应清空已累积的 usage与原实现一致");
}
/// error 事件无 error.message 字段时兜底为 "stream error"
#[test]
fn anthropic_error_event_missing_message_falls_back() {
let mut acc: Option<TokenUsage> = None;
let c = apply_anthropic_event(r#"{"type":"error"}"#, &mut acc);
assert_eq!(c.error.as_deref(), Some("stream error"));
assert!(!c.finished);
}
/// ping / content_block_stop 等事件 → 空且不 finished
#[test]
fn anthropic_ping_and_block_stop_yield_empty_chunk() {
let mut acc: Option<TokenUsage> = None;
let c = apply_anthropic_event(r#"{"type":"ping"}"#, &mut acc);
assert!(!c.finished);
assert_eq!(c.delta, "");
assert!(acc.is_none());
let c = apply_anthropic_event(r#"{"type":"content_block_stop","index":0}"#, &mut acc);
assert!(!c.finished);
assert_eq!(c.delta, "");
}
/// 非法 JSON → 空 chunk不 panic
#[test]
fn anthropic_malformed_json_yields_empty_chunk() {
let mut acc: Option<TokenUsage> = None;
let c = apply_anthropic_event("not json", &mut acc);
assert!(!c.finished);
assert_eq!(c.delta, "");
assert!(acc.is_none());
}
// ---------- F-260614-05 Phase 2a 多模态 convert_request ----------
/// 含图 user 消息 → content blockstext + image source.base64
#[test]
fn anthropic_convert_multimodal_user_blocks() {
let provider = AnthropicCompatProvider::new("https://api.anthropic.com", "k", "claude-3-5-sonnet");
let req = CompletionRequest {
model: "claude-3-5-sonnet".into(),
messages: vec![ChatMessage::user_parts(
"看图",
vec![crate::provider::ContentPart::image_base64("image/png", "iVBOR")],
)],
temperature: None,
max_tokens: None,
stream: false,
tools: None,
tool_choice: None,
reasoning_content: None,
};
let body = provider.convert_request(req);
// user 消息 content 应为数组形态
let user_msg = body
.messages
.iter()
.find(|m| m.get("role").and_then(|r| r.as_str()) == Some("user"))
.expect("应有 user 消息");
let content = user_msg.get("content").and_then(|c| c.as_array()).expect("user content 应为数组");
// 顺序content "看图" → text 块image 片 → image 块
assert_eq!(content.len(), 2);
assert_eq!(content[0]["type"], "text");
assert_eq!(content[0]["text"], "看图");
assert_eq!(content[1]["type"], "image");
assert_eq!(content[1]["source"]["type"], "base64");
assert_eq!(content[1]["source"]["media_type"], "image/png");
assert_eq!(content[1]["source"]["data"], "iVBOR");
}
/// 纯文本 user 消息 → content 仍是字符串简写(无图不数组化)
#[test]
fn anthropic_convert_text_only_user_remains_string() {
let provider = AnthropicCompatProvider::new("https://api.anthropic.com", "k", "claude-3-5-sonnet");
let req = CompletionRequest {
model: "claude-3-5-sonnet".into(),
messages: vec![ChatMessage::user("hello")],
temperature: None,
max_tokens: None,
stream: false,
tools: None,
tool_choice: None,
reasoning_content: None,
};
let body = provider.convert_request(req);
let user_msg = body
.messages
.iter()
.find(|m| m.get("role").and_then(|r| r.as_str()) == Some("user"))
.expect("应有 user 消息");
// 纯文本 → 字符串简写(非数组)
assert_eq!(user_msg.get("content").and_then(|c| c.as_str()), Some("hello"));
}
}