feat: 记录并展示每次生成消耗的LLM调用次数（llm_calls）

backend/database.py

@@ -83,6 +83,7 @@ CREATE TABLE IF NOT EXISTS ai_reports (
   model TEXT NOT NULL,
   tokens_used INTEGER,
   generation_count INTEGER NOT NULL DEFAULT 1,
+  llm_calls INTEGER,
   created_at TEXT NOT NULL DEFAULT (datetime('now','localtime')),
   updated_at TEXT,
   UNIQUE(trade_date, report_type)
@@ -121,6 +122,7 @@ def init_db():
     for alter_sql in (
         "ALTER TABLE ai_reports ADD COLUMN generation_count INTEGER NOT NULL DEFAULT 1",
         "ALTER TABLE ai_reports ADD COLUMN updated_at TEXT",
+        "ALTER TABLE ai_reports ADD COLUMN llm_calls INTEGER",
     ):
         try:
             conn.execute(alter_sql)

backend/routes/admin.py

@@ -144,7 +144,7 @@ async def admin_list_reports(request: Request):
     try:
         rows = conn.execute(
             "SELECT id, trade_date, report_type, title, summary, tools_used, model, tokens_used, "
-            "generation_count, created_at, updated_at "
+            "generation_count, llm_calls, created_at, updated_at "
             "FROM ai_reports ORDER BY trade_date DESC, id DESC LIMIT 50"
         ).fetchall()
         items = []

backend/routes/ai_analysis.py

@@ -64,7 +64,7 @@ async def list_reports():
     try:
         rows = conn.execute(
             "SELECT id, trade_date, report_type, title, summary, tools_used, model, tokens_used, "
-            "generation_count, created_at, updated_at "
+            "generation_count, llm_calls, created_at, updated_at "
             "FROM ai_reports ORDER BY trade_date DESC, id DESC LIMIT 50"
         ).fetchall()
         items = []

backend/services/ai_service.py

@@ -227,11 +227,13 @@ async def collect_ai_analysis(trade_date: str) -> dict:
     # ── 阶段一：工具轮（只获取数据，模型若直接开写报告则丢弃，由阶段二重写） ──
     tools_used = []
     total_tokens = 0
+    llm_calls = 0
     was_truncated = False
     max_rounds = 8
 
     for i in range(max_rounds):
         response = await call_llm(messages, tools=TOOLS)
+        llm_calls += 1
         total_tokens += response.get("usage", {}).get("total_tokens", 0)
 
         choice = response["choices"][0]
@@ -277,6 +279,7 @@ async def collect_ai_analysis(trade_date: str) -> dict:
                 "content": part_prompt.format(title=trade_date) if part_idx == 0 else part_prompt,
             }]
             response = await call_llm(part_messages)
+            llm_calls += 1
             total_tokens += response.get("usage", {}).get("total_tokens", 0)
             choice = response["choices"][0]
             part_content = choice["message"].get("content") or ""
@@ -292,9 +295,10 @@ async def collect_ai_analysis(trade_date: str) -> dict:
         final_content += (final_content and "\n\n" or "") + part_content
 
     summary = _extract_summary(final_content)
-    report_id = _save_report(trade_date, final_content, summary, tools_used, total_tokens)
+    report_id = _save_report(trade_date, final_content, summary, tools_used, total_tokens, llm_calls)
+    print(f"[ai-service] 生成完成：LLM调用 {llm_calls} 次，tokens {total_tokens}")
 
-    return {"id": report_id, "tokens_used": total_tokens, "tools_used": tools_used, "truncated": was_truncated}
+    return {"id": report_id, "tokens_used": total_tokens, "llm_calls": llm_calls, "tools_used": tools_used, "truncated": was_truncated}
 
 
 def _extract_summary(content: str) -> str:
@@ -416,14 +420,14 @@ def _get_prev_snapshot_section(trade_date: str) -> str:
         conn.close()
 
 
-def _save_report(trade_date: str, content: str, summary: str, tools_used: list, tokens_used: int) -> int:
+def _save_report(trade_date: str, content: str, summary: str, tools_used: list, tokens_used: int, llm_calls: int = 0) -> int:
     """保存报告到数据库（同日重生成：覆盖内容、generation_count+1、tokens 记当次消耗）"""
     conn = get_connection()
     try:
         conn.execute(
             """INSERT INTO ai_reports
-               (trade_date, report_type, title, content, summary, tools_used, model, tokens_used, updated_at)
-               VALUES (?, 'daily', ?, ?, ?, ?, ?, ?, datetime('now','localtime'))
+               (trade_date, report_type, title, content, summary, tools_used, model, tokens_used, llm_calls, updated_at)
+               VALUES (?, 'daily', ?, ?, ?, ?, ?, ?, ?, datetime('now','localtime'))
                ON CONFLICT(trade_date, report_type) DO UPDATE SET
                  title = excluded.title,
                  content = excluded.content,
@@ -431,6 +435,7 @@ def _save_report(trade_date: str, content: str, summary: str, tools_used: list,
                  tools_used = excluded.tools_used,
                  model = excluded.model,
                  tokens_used = excluded.tokens_used,
+                 llm_calls = excluded.llm_calls,
                  updated_at = excluded.updated_at,
                  generation_count = ai_reports.generation_count + 1""",
             (
@@ -441,6 +446,7 @@ def _save_report(trade_date: str, content: str, summary: str, tools_used: list,
                 json.dumps(tools_used),
                 AI_MODEL,
                 tokens_used,
+                llm_calls,
             ),
         )
         conn.commit()

src/lib/ai-analysis-api.ts

@@ -15,6 +15,7 @@ export interface AiReport {
   model: string;
   tokens_used: number;
   generation_count?: number;
+  llm_calls?: number | null;
   issue_number?: number;
   created_at: string;
   updated_at?: string | null;

src/routes/ai-analysis.tsx

@@ -132,6 +132,7 @@ function AiAnalysisPage() {
                     <span className="truncate">{report.updated_at || report.created_at}</span>
                   </span>
                   <span>{report.tokens_used?.toLocaleString()} tokens</span>
+                  {report.llm_calls ? <span>{report.llm_calls} 次 LLM 调用</span> : null}
                   {(report.generation_count ?? 1) > 1 && (
                     <span>第 {report.generation_count} 次生成</span>
                   )}