test(providers): real-endpoint-log regressions for Responses reasoning
Based on the user's actual deepseek-v4-flash debug log (Responses protocol): - real_log_captures_reasoning_and_tools: replays turn 1 of the real SSE (reasoning item + reasoning_text.delta + two function calls) and asserts the Done message is [Thinking, ToolCall, ToolCall] with usage mapped (input 850 / output 157 / cache-read 768) - agent_multi_turn_replays_reasoning: drives a 3-turn agent over the real protocol (turn 1 + turn 2 from the log, plus a terminating text turn), asserting thinking lands in the transcript and the second request's replay carries a reasoning item with the captured text and matching call ids MockTransport gains requests() to inspect all recorded requests.
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DaiChaoXiong
parent
80333ee127
commit
6257f4f6b8
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@ -61,6 +61,13 @@ impl MockTransport {
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.expect("no request recorded")
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}
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/// 已记录的全部请求克隆（按顺序）。
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/// Clones of all recorded requests (in order).
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#[allow(dead_code)]
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pub fn requests(&self) -> Vec<HttpRequest> {
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self.requests.lock().unwrap().clone()
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}
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/// 已记录的请求数量。
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/// Number of recorded requests.
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#[allow(dead_code)]
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@ -618,3 +618,222 @@ fn responses_replays_reasoning_item() {
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assert_eq!(content[0].get_str("type"), Some("reasoning_text"));
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assert_eq!(content[0].get_str("text"), Some("思考内容"));
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}
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// ---- 基于真实端点日志的回归测试 ----
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// ---- regressions built from a real endpoint log (deepseek-v4-flash,
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// Responses API with reasoning items) --------------------------------
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/// 真实日志第 1 轮的 SSE（reasoning + 两个 shell 调用）。
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/// Turn 1 of the real log: reasoning + two shell calls.
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const REAL_TURN1: &str = "event: response.created\ndata: {\"type\":\"response.created\",\"response\":{\"id\":\"r1\",\"status\":\"in_progress\"}}\n\n\
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event: response.output_item.added\ndata: {\"type\":\"response.output_item.added\",\"item\":{\"type\":\"reasoning\",\"id\":\"rr1\",\"status\":\"in_progress\",\"content\":[],\"summary\":[]},\"output_index\":0}\n\n\
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event: response.content_part.added\ndata: {\"type\":\"response.content_part.added\",\"content_index\":0,\"item_id\":\"rr1\",\"output_index\":0,\"part\":{\"type\":\"reasoning_text\",\"text\":\"\"}}\n\n\
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event: response.reasoning_text.delta\ndata: {\"type\":\"response.reasoning_text.delta\",\"content_index\":0,\"delta\":\"The user is asking in Chinese: \\\"Hello, what does this project do?\\\" Let me explore\",\"item_id\":\"rr1\",\"output_index\":0}\n\n\
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event: response.reasoning_text.delta\ndata: {\"type\":\"response.reasoning_text.delta\",\"content_index\":0,\"delta\":\" the repository to understand what it is.\",\"item_id\":\"rr1\",\"output_index\":0}\n\n\
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event: response.reasoning_text.done\ndata: {\"type\":\"response.reasoning_text.done\",\"content_index\":0,\"item_id\":\"rr1\",\"output_index\":0,\"text\":\"The user is asking in Chinese: \\\"Hello, what does this project do?\\\" Let me explore the repository to understand what it is.\"}\n\n\
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event: response.output_item.added\ndata: {\"type\":\"response.output_item.added\",\"item\":{\"type\":\"function_call\",\"id\":\"f1\",\"status\":\"in_progress\",\"arguments\":\"\",\"call_id\":\"call_00_wyQ\",\"name\":\"shell\"},\"output_index\":1}\n\n\
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event: response.function_call_arguments.delta\ndata: {\"type\":\"response.function_call_arguments.delta\",\"delta\":\"{\\\"command\\\": \\\"ls -la /home/focus/Desktop/Project/focus && cat /home/focus/Desktop/Project/focus/README.md 2>/dev/null\",\"item_id\":\"f1\",\"output_index\":1}\n\n\
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event: response.function_call_arguments.delta\ndata: {\"type\":\"response.function_call_arguments.delta\",\"delta\":\" | head -50\\\"}\",\"item_id\":\"f1\",\"output_index\":1}\n\n\
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event: response.output_item.added\ndata: {\"type\":\"response.output_item.added\",\"item\":{\"type\":\"function_call\",\"id\":\"f2\",\"status\":\"in_progress\",\"arguments\":\"\",\"call_id\":\"call_01_wUr\",\"name\":\"shell\"},\"output_index\":2}\n\n\
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event: response.function_call_arguments.delta\ndata: {\"type\":\"response.function_call_arguments.delta\",\"delta\":\"{\\\"command\\\": \\\"find /home/focus/Desktop/Project/focus -maxdepth 2 -type f | head -50\\\"}\",\"item_id\":\"f2\",\"output_index\":2}\n\n\
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event: response.completed\ndata: {\"type\":\"response.completed\",\"response\":{\"status\":\"completed\",\"usage\":{\"input_tokens\":850,\"input_tokens_details\":{\"cached_tokens\":768},\"output_tokens\":157,\"output_tokens_details\":{\"reasoning_tokens\":27},\"total_tokens\":1007}}}\n\n";
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/// 真实日志第 2 轮的 SSE（reasoning + read + shell）。
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/// Turn 2 of the real log: reasoning + read + shell.
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const REAL_TURN2: &str = "event: response.output_item.added\ndata: {\"type\":\"response.output_item.added\",\"item\":{\"type\":\"reasoning\",\"id\":\"rr2\",\"status\":\"in_progress\",\"content\":[],\"summary\":[]},\"output_index\":0}\n\n\
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event: response.reasoning_text.delta\ndata: {\"type\":\"response.reasoning_text.delta\",\"content_index\":0,\"delta\":\"Let me look at the Cargo.toml and AGENTS.md to understand what this project is.\",\"item_id\":\"rr2\",\"output_index\":0}\n\n\
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event: response.output_item.added\ndata: {\"type\":\"response.output_item.added\",\"item\":{\"type\":\"function_call\",\"id\":\"f3\",\"status\":\"in_progress\",\"arguments\":\"\",\"call_id\":\"call_00_nK3\",\"name\":\"read\"},\"output_index\":1}\n\n\
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event: response.function_call_arguments.delta\ndata: {\"type\":\"response.function_call_arguments.delta\",\"delta\":\"{\\\"path\\\": \\\"/home/focus/Desktop/Project/focus/Cargo.toml\\\"}\",\"item_id\":\"f3\",\"output_index\":1}\n\n\
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event: response.output_item.added\ndata: {\"type\":\"response.output_item.added\",\"item\":{\"type\":\"function_call\",\"id\":\"f4\",\"status\":\"in_progress\",\"arguments\":\"\",\"call_id\":\"call_01_1IR\",\"name\":\"shell\"},\"output_index\":2}\n\n\
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event: response.function_call_arguments.delta\ndata: {\"type\":\"response.function_call_arguments.delta\",\"delta\":\"{\\\"command\\\": \\\"ls /home/focus/Desktop/Project/focus/crates /home/focus/Desktop/Project/focus/docs /home/focus/Desktop/Project/focus/examples\\\"}\",\"item_id\":\"f4\",\"output_index\":2}\n\n\
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event: response.completed\ndata: {\"type\":\"response.completed\",\"response\":{\"status\":\"completed\",\"usage\":{\"input_tokens\":1601,\"input_tokens_details\":{\"cached_tokens\":896},\"output_tokens\":142,\"output_tokens_details\":{\"reasoning_tokens\":21},\"total_tokens\":1743}}}\n\n";
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/// 终止轮：reasoning + 文本回答。
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/// A terminating turn: reasoning + text answer.
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const REAL_TURN3: &str = "event: response.output_item.added\ndata: {\"type\":\"response.output_item.added\",\"item\":{\"type\":\"reasoning\",\"id\":\"rr3\",\"status\":\"in_progress\",\"content\":[],\"summary\":[]},\"output_index\":0}\n\n\
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event: response.reasoning_text.delta\ndata: {\"type\":\"response.reasoning_text.delta\",\"content_index\":0,\"delta\":\"Now I can answer.\",\"item_id\":\"rr3\",\"output_index\":0}\n\n\
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event: response.output_item.added\ndata: {\"type\":\"response.output_item.added\",\"item\":{\"type\":\"message\",\"id\":\"m1\",\"status\":\"in_progress\",\"role\":\"assistant\",\"content\":[{\"type\":\"output_text\",\"text\":\"\",\"annotations\":[]}]},\"output_index\":1}\n\n\
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event: response.output_text.delta\ndata: {\"type\":\"response.output_text.delta\",\"item_id\":\"m1\",\"output_index\":1,\"delta\":\"这是一个 Rust 项目。\"}\n\n\
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event: response.completed\ndata: {\"type\":\"response.completed\",\"response\":{\"status\":\"completed\",\"usage\":{\"input_tokens\":900,\"output_tokens\":30}}}\n\n";
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/// provider 级：真实第 1 轮 → 捕获推理（思考块）+ 两个工具调用 + usage。
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/// Provider level: real turn 1 → reasoning captured (thinking block) + two
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/// tool calls + usage.
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#[test]
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fn real_log_captures_reasoning_and_tools() {
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let mut mock = common::MockTransport::new();
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mock.push_body(REAL_TURN1);
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let provider = provider(mock, OpenAiProtocol::Responses);
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let events = common::collect(&provider, &request());
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let msg = final_message(&events);
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assert_eq!(msg.content.len(), 3, "thinking + 2 tool calls");
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match &msg.content[0] {
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ContentBlock::Thinking(t) => {
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assert_eq!(
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t.thinking,
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"The user is asking in Chinese: \"Hello, what does this project do?\" Let me explore the repository to understand what it is."
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);
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}
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other => panic!("expected thinking block, got {:?}", other),
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}
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let tc1 = msg.content[1].as_tool_call().expect("tool call 1");
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assert_eq!(tc1.name, "shell");
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let cmd1 = tc1.arguments.get_str("command").unwrap_or("");
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assert!(cmd1.contains("ls -la"), "got: {}", cmd1);
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let tc2 = msg.content[2].as_tool_call().expect("tool call 2");
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assert_eq!(tc2.name, "shell");
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let cmd2 = tc2.arguments.get_str("command").unwrap_or("");
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assert!(cmd2.contains("find"), "got: {}", cmd2);
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// usage 映射：input / output / cache-read。
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// Usage mapping: input / output / cache-read.
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assert_eq!(msg.usage.input_tokens, 850);
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assert_eq!(msg.usage.output_tokens, 157);
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assert_eq!(msg.usage.cache_read_tokens, 768);
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}
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/// agent 级全链路：真实日志的三轮 → 思考进入 transcript + 历史回传 reasoning item。
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/// Agent-level end-to-end: three real-log turns → thinking lands in the
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/// transcript + the replay carries the reasoning item.
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#[test]
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fn agent_multi_turn_replays_reasoning() {
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use focus_core::event::VecSink;
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use focus_core::tool::{ToolEffects, ToolRegistry};
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use focus_core::{Agent, AgentConfig, CoreError};
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#[derive(Debug)]
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struct NoopTool {
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name: String,
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}
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impl Tool for NoopTool {
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fn name(&self) -> &str {
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&self.name
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}
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fn description(&self) -> &str {
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"does nothing"
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}
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fn parameters(&self) -> focus_json::JsonValue {
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focus_json::JsonValue::obj()
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}
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fn effects(&self) -> ToolEffects {
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ToolEffects::NONE
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}
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fn execute(
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&self,
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_id: &str,
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_args: &focus_json::JsonValue,
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_u: Option<&ToolUpdateSink>,
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) -> Result<ToolResult, CoreError> {
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Ok(ToolResult::text("ok"))
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}
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}
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let mut mock = common::MockTransport::new();
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mock.push_body(REAL_TURN1);
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mock.push_body(REAL_TURN2);
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mock.push_body(REAL_TURN3);
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let provider = OpenAiProvider::with_transport(
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ProviderConfig::new("sk-test"),
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OpenAiProtocol::Responses,
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Arc::new(mock.clone()),
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);
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let config = AgentConfig {
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model: "deepseek-v4-flash".into(),
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system_prompt: "sys".into(),
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max_tokens: Some(4096),
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..Default::default()
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};
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let mut registry = ToolRegistry::new();
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registry.register(Box::new(NoopTool {
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name: "shell".into(),
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}));
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registry.register(Box::new(NoopTool {
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name: "read".into(),
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}));
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let mut agent = Agent::new(config, Box::new(provider), registry);
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let mut sink = VecSink::new();
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agent
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.prompt("你好，本项目是干什么的", &mut sink)
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.expect("run failed");
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// 三轮：user + [assistant, tool, tool] ×2 + [assistant(text)]。
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// Three turns: user + [assistant, tool, tool] ×2 + [assistant(text)].
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let msgs = agent.messages();
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assert_eq!(msgs.len(), 8, "1 user + 3 assistant + 4 tool results");
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// 第 1 条 assistant 消息：思考块（真实日志文本）在前。
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// The first assistant message: a thinking block (real log text) first.
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let first_assistant = msgs
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.iter()
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.find_map(|m| match m {
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Message::Assistant(a) => Some(a),
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_ => None,
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})
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.expect("assistant message");
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match &first_assistant.content[0] {
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ContentBlock::Thinking(t) => {
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assert!(
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t.thinking.contains("The user is asking in Chinese"),
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"got: {}",
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t.thinking
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);
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}
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other => panic!("expected thinking, got {:?}", other),
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}
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// 第 2 条 assistant 消息的思考（真实日志第 2 轮）。
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// The second assistant's thinking (real log turn 2).
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let second_assistant = msgs
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.iter()
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.filter_map(|m| match m {
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Message::Assistant(a) => Some(a),
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_ => None,
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})
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.nth(1)
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.expect("second assistant");
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match &second_assistant.content[0] {
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ContentBlock::Thinking(t) => {
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assert!(
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t.thinking.contains("Cargo.toml and AGENTS.md"),
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"got: {}",
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t.thinking
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);
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}
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other => panic!("expected thinking, got {:?}", other),
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}
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// 三个请求都发出了。
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// All three requests were sent.
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assert_eq!(mock.request_count(), 3);
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// 第 2 个请求（回放第 1 轮历史）必须携带 reasoning item。
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// The second request (replaying turn-1 history) must carry a reasoning
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// item.
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let reqs = mock.requests();
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let body2: focus_json::JsonValue =
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focus_json::parse(&String::from_utf8_lossy(&reqs[1].body)).unwrap();
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let input = body2.get_arr("input").expect("input items");
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let reasoning = input
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.iter()
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.find(|i| i.get_str("type") == Some("reasoning"))
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.expect("reasoning item in replay");
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let content = reasoning.get_arr("content").unwrap();
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let text = content[0].get_str("text").unwrap_or("");
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assert!(
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text.contains("The user is asking in Chinese"),
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"got: {}",
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text
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);
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// function_call 与 function_call_output 的 call_id 一致。
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// The function_call and function_call_output call ids match.
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let fc = input
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.iter()
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.find(|i| i.get_str("type") == Some("function_call"))
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.expect("function_call item");
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let fco = input
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.iter()
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.find(|i| i.get_str("type") == Some("function_call_output"))
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.expect("function_call_output item");
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assert_eq!(fc.get_str("call_id"), fco.get_str("call_id"));
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}
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