feat(chat): 会话详情显示 model/上下文占用 + 切回 rounds 计数

- 新增 get_session_usage Tauri 命令，按需读取 .jsonl 解析当前 session 真实用量
- SessionUsage 新增 model 与 context_tokens（peak 单回合 input+cache_read+cache_creation）
- 前端 inferModelInfo 推断 provider/上下文窗口（Anthropic/OpenAI/Google/未知）
- SessionDetail 底栏替换 cwd 为 "provider · model · ctx X (Y%)" 信息
- "messages" 计数改为 "rounds"（仅统计用户 prompt，不含工具/meta）

Author: MarkShawn2020

src-tauri/src/lib.rs

@@ -172,6 +172,15 @@ pub struct SessionUsage {
     pub cache_creation_tokens: u64,
     pub cache_read_tokens: u64,
     pub cost_usd: f64, // estimated cost in USD
+    /// Last model identifier seen in the session (e.g. "claude-opus-4-7"). Populated from
+    /// assistant message metadata; None for older sessions or non-Claude sources.
+    #[serde(default, skip_serializing_if = "Option::is_none")]
+    pub model: Option<String>,
+    /// Peak total input footprint across any single assistant turn — best proxy for "context
+    /// window occupancy" since each turn ships the full live transcript. = input + cache_read +
+    /// cache_creation tokens at that turn. 0 when unknown.
+    #[serde(default)]
+    pub context_tokens: u64,
 }
 
 #[derive(Debug, Serialize, Deserialize)]
@@ -268,6 +277,7 @@ struct RawMessage {
     role: Option<String>,
     content: Option<serde_json::Value>,
     usage: Option<RawUsage>,
+    model: Option<String>,
 }
 
 /// Entry from history.jsonl - used as fast session index
@@ -768,10 +778,20 @@ fn read_session_usage(path: &Path) -> SessionUsage {
             if is_assistant {
                 if let Some(msg) = &parsed.message {
                     if let Some(u) = &msg.usage {
-                        usage.input_tokens += u.input_tokens.unwrap_or(0);
+                        let inp = u.input_tokens.unwrap_or(0);
+                        let cw = u.cache_creation_input_tokens.unwrap_or(0);
+                        let cr = u.cache_read_input_tokens.unwrap_or(0);
+                        usage.input_tokens += inp;
                         usage.output_tokens += u.output_tokens.unwrap_or(0);
-                        usage.cache_creation_tokens += u.cache_creation_input_tokens.unwrap_or(0);
-                        usage.cache_read_tokens += u.cache_read_input_tokens.unwrap_or(0);
+                        usage.cache_creation_tokens += cw;
+                        usage.cache_read_tokens += cr;
+                        let turn_ctx = inp + cw + cr;
+                        if turn_ctx > usage.context_tokens {
+                            usage.context_tokens = turn_ctx;
+                        }
+                    }
+                    if let Some(m) = msg.model.as_ref().filter(|s| !s.is_empty()) {
+                        usage.model = Some(m.clone());
                     }
                 }
             }
@@ -788,6 +808,22 @@ pub struct SessionUsageEntry {
     pub usage: SessionUsage,
 }
 
+#[tauri::command]
+async fn get_session_usage(project_id: String, session_id: String) -> Result<SessionUsage, String> {
+    tauri::async_runtime::spawn_blocking(move || {
+        let path = get_claude_dir()
+            .join("projects")
+            .join(&project_id)
+            .join(format!("{}.jsonl", session_id));
+        if !path.exists() {
+            return Err("Session not found".to_string());
+        }
+        Ok(read_session_usage(&path))
+    })
+    .await
+    .map_err(|e| e.to_string())?
+}
+
 #[tauri::command]
 async fn get_sessions_usage(project_id: String) -> Result<Vec<SessionUsageEntry>, String> {
     tauri::async_runtime::spawn_blocking(move || {
@@ -9282,6 +9318,7 @@ pub fn run() {
             list_projects,
             list_sessions,
             get_sessions_usage,
+            get_session_usage,
             list_all_sessions,
             get_app_starred_session_ids,
             list_all_chats,

src/types/index.ts

@@ -52,6 +52,8 @@ export interface SessionUsage {
   cache_creation_tokens: number;
   cache_read_tokens: number;
   cost_usd: number;
+  model?: string;
+  context_tokens: number;
 }
 
 export interface Session {

src/views/Chat/ProjectList.tsx

@@ -21,7 +21,7 @@ import {
   importCollapsedAtom,
 } from "../../store";
 import { useAppConfig } from "../../context";
-import { useReadableText } from "./utils";
+import { useReadableText, formatTokens, inferModelInfo } from "./utils";
 import { useInvokeQuery, useQueryClient } from "../../hooks";
 import { CollapsibleContent } from "./CollapsibleContent";
 import { ContentBlockRenderer } from "./ContentBlockRenderer";
@@ -1270,6 +1270,13 @@ function SessionDetail({ session, onClose, highlight, scrollRef }: { session: Se
 
   const displaySummary = session.title || toReadable(session.summary) || "Untitled";
 
+  const { data: liveUsage } = useInvokeQuery<import("../../types").SessionUsage>(
+    ["session-usage", session.project_id, session.id],
+    "get_session_usage",
+    { projectId: session.project_id, sessionId: session.id },
+  );
+  const usage = liveUsage ?? session.usage;
+
   useEffect(() => {
     let cancelled = false;
     setLoading(true);
@@ -1290,6 +1297,13 @@ function SessionDetail({ session, onClose, highlight, scrollRef }: { session: Se
     return result;
   }, [messages, originalChat, userPromptsOnly]);
 
+  // A round = one user prompt (plus its following assistant turn). Count user messages from the
+  // chat-only view so meta/tool entries don't inflate the number.
+  const roundCount = useMemo(
+    () => messages.filter((m) => !m.is_meta && !m.is_tool && m.role === "user").length,
+    [messages],
+  );
+
   const handleCopyContent = (content: string) => {
     invoke("copy_to_clipboard", { text: content });
   };
@@ -1432,9 +1446,7 @@ function SessionDetail({ session, onClose, highlight, scrollRef }: { session: Se
           <p className="text-xs text-muted-foreground truncate">
             {session.project_path ? formatPath(session.project_path) : session.project_id}
             {" · "}
-            {userPromptsOnly
-              ? `${filteredMessages.length} prompts`
-              : `${session.message_count} messages`}
+            {`${roundCount} rounds`}
           </p>
         </div>
         <div className="flex items-center gap-3 shrink-0">
@@ -1646,9 +1658,30 @@ function SessionDetail({ session, onClose, highlight, scrollRef }: { session: Se
                     ))}
                   </DropdownMenuContent>
                 </DropdownMenu>
-                <span className="text-[10px] text-muted-foreground font-mono truncate max-w-[60%]" title={session.project_path ?? undefined}>
-                  cwd: {session.project_path ? formatPath(session.project_path) : "—"}
-                </span>
+                {(() => {
+                  const info = inferModelInfo(usage?.model);
+                  const ctx = usage?.context_tokens ?? 0;
+                  if (!info && ctx === 0) return null;
+                  const pct = info?.contextWindow && ctx > 0 ? Math.min(100, Math.round((ctx / info.contextWindow) * 100)) : null;
+                  const parts = [
+                    info?.provider,
+                    info?.name,
+                    ctx > 0 ? `ctx ${formatTokens(ctx)}${pct !== null ? ` (${pct}%)` : ""}` : null,
+                  ].filter(Boolean) as string[];
+                  if (parts.length === 0) return null;
+                  return (
+                    <div
+                      className="text-[10px] text-muted-foreground font-mono truncate min-w-0"
+                      title={[
+                        info?.provider && `Provider: ${info.provider}`,
+                        info?.name && `Model: ${info.name}`,
+                        ctx > 0 && `Peak context: ${ctx.toLocaleString()} tokens${info?.contextWindow ? ` / ${info.contextWindow.toLocaleString()} (${pct}%)` : ""}`,
+                      ].filter(Boolean).join("\n")}
+                    >
+                      {parts.join(" · ")}
+                    </div>
+                  );
+                })()}
               </div>
             </div>
           )}

src/views/Chat/utils.ts

@@ -24,6 +24,39 @@ export function formatDate(ts: number): string {
   return new Date(ts * 1000).toLocaleString();
 }
 
+export function formatTokens(n: number): string {
+  if (n >= 1_000_000) return `${(n / 1_000_000).toFixed(2)}M`;
+  if (n >= 1_000) return `${(n / 1_000).toFixed(1)}K`;
+  return n.toString();
+}
+
+// Best-effort provider/family/window inference from a raw model id seen in session usage.
+// Only covers the model families this app cares about today (Anthropic Claude + OpenAI/Codex).
+// Returns null fields when unknown rather than guessing.
+export interface ModelInfo {
+  provider: string | null;
+  name: string;
+  contextWindow: number | null;
+}
+
+export function inferModelInfo(model: string | undefined | null): ModelInfo | null {
+  if (!model) return null;
+  const m = model.toLowerCase();
+  if (m.includes("claude")) {
+    return { provider: "Anthropic", name: model, contextWindow: 200_000 };
+  }
+  if (m.startsWith("gpt-5") || m.startsWith("o3") || m.startsWith("o1") || m.includes("codex")) {
+    return { provider: "OpenAI", name: model, contextWindow: 128_000 };
+  }
+  if (m.startsWith("gpt-4")) {
+    return { provider: "OpenAI", name: model, contextWindow: 128_000 };
+  }
+  if (m.includes("gemini")) {
+    return { provider: "Google", name: model, contextWindow: 1_000_000 };
+  }
+  return { provider: null, name: model, contextWindow: null };
+}
+
 /** Hook that returns a function to convert text based on global readable setting */
 export function useReadableText(): (text: string | null | undefined) => string {
   const readable = useAtomValue(originalChatAtom);