增加大模型

backend/app/chart_image.py

@@ -0,0 +1,66 @@
+"""服务端生成日K+成交量 PNG，供大模型视觉解读。"""
+
+import io
+from datetime import datetime
+
+from .kline_store import get_daily_candles
+
+
+async def render_daily_chart_png_async(symbol: str, limit: int = 300) -> bytes:
+    import matplotlib
+
+    matplotlib.use("Agg")
+    import matplotlib.pyplot as plt
+    import matplotlib.dates as mdates
+
+    candles, _ = await get_daily_candles(symbol, limit)
+    if not candles:
+        raise ValueError(f"no klines for {symbol}")
+
+    times = [datetime.fromtimestamp(c["time"] / 1000) for c in candles]
+    opens = [c["open"] for c in candles]
+    highs = [c["high"] for c in candles]
+    lows = [c["low"] for c in candles]
+    closes = [c["close"] for c in candles]
+    vols = [c.get("quote_volume") or c.get("volume") or 0 for c in candles]
+
+    fig, (ax1, ax2) = plt.subplots(
+        2, 1, figsize=(12, 7), gridspec_kw={"height_ratios": [3, 1]}, facecolor="#0d1118"
+    )
+    fig.subplots_adjust(hspace=0.08)
+
+    for i in range(len(candles)):
+        t = times[i]
+        o, h, l, cl = opens[i], highs[i], lows[i], closes[i]
+        color = "#0ecb81" if cl >= o else "#f6465d"
+        ax1.plot([t, t], [l, h], color=color, linewidth=0.8)
+        ax1.add_patch(
+            plt.Rectangle(
+                (mdates.date2num(t) - 0.3, min(o, cl)),
+                0.6,
+                abs(cl - o) or 0.001,
+                facecolor=color,
+                edgecolor=color,
+            )
+        )
+    ax1.set_facecolor("#0d1118")
+    ax1.tick_params(colors="#8b9cb3")
+    ax1.set_title(f"{symbol} 日K + 成交量", color="#e7ecf3", fontsize=14)
+    ax1.grid(True, alpha=0.2)
+
+    colors_vol = ["#0ecb81" if closes[i] >= opens[i] else "#f6465d" for i in range(len(candles))]
+    ax2.bar(times, vols, color=colors_vol, alpha=0.7, width=0.8)
+    ax2.set_facecolor("#0d1118")
+    ax2.tick_params(colors="#8b9cb3")
+    ax2.set_ylabel("成交额", color="#8b9cb3")
+    ax2.grid(True, alpha=0.2)
+
+    for ax in (ax1, ax2):
+        ax.xaxis.set_major_formatter(mdates.DateFormatter("%m-%d"))
+    fig.autofmt_xdate()
+
+    buf = io.BytesIO()
+    fig.savefig(buf, format="png", dpi=120, facecolor="#0d1118")
+    plt.close(fig)
+    buf.seek(0)
+    return buf.read()

backend/app/config.py

@@ -17,7 +17,7 @@ class Settings(BaseSettings):
     top_n: int = 30
     volume_threshold: float = 10_000_000
     change_threshold: float = 5.0
-    refresh_minutes: int = 5
+    refresh_minutes: int = 240
     host: str = "127.0.0.1"
     port: int = 21450
     db_path: str = str(ROOT_DIR / "data" / "monitor.db")
@@ -37,6 +37,11 @@ class Settings(BaseSettings):
     proxy_enabled: bool = False
     proxy_url: str = "socks5h://192.168.8.4:1081"
     proxy_for: str = "binance"  # binance | wecom | all
+    llm_base_url: str = "http://op.bz121.com"
+    llm_api_key: str = ""
+    llm_model: str = "gemma4:e4b"
+    llm_symbol_interval_sec: int = 180
+    llm_auto_on_startup: bool = True
 
 
 settings = Settings()

backend/app/db.py

@@ -96,6 +96,17 @@ def init_db() -> None:
                 mark_price REAL NOT NULL DEFAULT 0,
                 updated_at TEXT NOT NULL
             );
+
+            CREATE TABLE IF NOT EXISTS llm_interpretations (
+                id INTEGER PRIMARY KEY AUTOINCREMENT,
+                symbol TEXT NOT NULL,
+                batch_id TEXT NOT NULL,
+                content TEXT NOT NULL,
+                created_at TEXT NOT NULL
+            );
+
+            CREATE INDEX IF NOT EXISTS idx_llm_symbol_batch
+                ON llm_interpretations(symbol, batch_id);
             """
         )
 
@@ -353,6 +364,87 @@ def save_funding_current_bulk(data: dict[str, dict[str, Any]]) -> None:
             )
 
 
+def save_llm_interpretation(symbol: str, batch_id: str, content: str) -> None:
+    with get_conn() as conn:
+        conn.execute(
+            """
+            INSERT INTO llm_interpretations (symbol, batch_id, content, created_at)
+            VALUES (?, ?, ?, ?)
+            """,
+            (symbol.upper(), batch_id, content, datetime.now().isoformat()),
+        )
+
+
+def get_llm_interpretations(batch_id: str | None = None, limit: int = 50) -> list[dict[str, Any]]:
+    with get_conn() as conn:
+        if batch_id:
+            rows = conn.execute(
+                """
+                SELECT symbol, batch_id, content, created_at
+                FROM llm_interpretations
+                WHERE batch_id = ?
+                ORDER BY id DESC
+                LIMIT ?
+                """,
+                (batch_id, limit),
+            ).fetchall()
+        else:
+            rows = conn.execute(
+                """
+                SELECT symbol, batch_id, content, created_at
+                FROM llm_interpretations
+                WHERE batch_id = (
+                    SELECT batch_id FROM llm_interpretations ORDER BY id DESC LIMIT 1
+                )
+                ORDER BY id ASC
+                LIMIT ?
+                """,
+                (limit,),
+            ).fetchall()
+    return [
+        {
+            "symbol": r["symbol"],
+            "batch_id": r["batch_id"],
+            "content": r["content"],
+            "created_at": r["created_at"],
+        }
+        for r in rows
+    ]
+
+
+def get_llm_interpretation(symbol: str, batch_id: str | None = None) -> dict[str, Any] | None:
+    sym = symbol.upper()
+    with get_conn() as conn:
+        if batch_id:
+            row = conn.execute(
+                """
+                SELECT symbol, batch_id, content, created_at
+                FROM llm_interpretations
+                WHERE symbol = ? AND batch_id = ?
+                ORDER BY id DESC LIMIT 1
+                """,
+                (sym, batch_id),
+            ).fetchone()
+        else:
+            row = conn.execute(
+                """
+                SELECT symbol, batch_id, content, created_at
+                FROM llm_interpretations
+                WHERE symbol = ?
+                ORDER BY id DESC LIMIT 1
+                """,
+                (sym,),
+            ).fetchone()
+    if not row:
+        return None
+    return {
+        "symbol": row["symbol"],
+        "batch_id": row["batch_id"],
+        "content": row["content"],
+        "created_at": row["created_at"],
+    }
+
+
 def was_pushed_today(period_start: str, period_end: str) -> bool:
     with get_conn() as conn:
         row = conn.execute(

backend/app/llm_service.py

@@ -0,0 +1,174 @@
+"""大模型解读（OpenAI 兼容接口 + 图表图片）。"""
+
+import asyncio
+import base64
+import logging
+from datetime import datetime
+
+import httpx
+
+from .chart_image import render_daily_chart_png_async
+from .config import settings
+from .db import get_llm_interpretation, save_llm_interpretation
+from .stats import compute_three_day_stats
+
+logger = logging.getLogger(__name__)
+
+_interpret_lock = asyncio.Lock()
+_interpret_state: dict = {
+    "running": False,
+    "current_symbol": "",
+    "done": 0,
+    "total": 0,
+    "batch_id": "",
+    "last_error": "",
+}
+
+
+def get_interpret_state() -> dict:
+    return dict(_interpret_state)
+
+
+def _api_url() -> str:
+    base = settings.llm_base_url.rstrip("/")
+    if base.endswith("/v1"):
+        return f"{base}/chat/completions"
+    return f"{base}/v1/chat/completions"
+
+
+def _build_prompt(symbol: str, stats_row: dict | None) -> str:
+    lines = [
+        f"你是加密货币合约分析师。请根据附图（{symbol} 近300日K+成交量）及数据给出中文简析。",
+        "关注：趋势、关键支撑阻力、成交量变化、资金费率含义、未来1-3日可能节奏。",
+        "控制在 200-350 字，条理清晰，不要废话。",
+    ]
+    if stats_row:
+        t, y, b = stats_row.get("today", {}), stats_row.get("yesterday", {}), stats_row.get("daybefore", {})
+        lines.append(
+            f"\n三日均为成交额Top30交集："
+            f"\n今日 排名{t.get('rank')} 涨跌{t.get('price_change_pct_fmt')} 额{t.get('quote_volume_fmt')}"
+            f"\n昨日 排名{y.get('rank')} 涨跌{y.get('price_change_pct_fmt')} 额{y.get('quote_volume_fmt')}"
+            f"\n前日 排名{b.get('rank')} 涨跌{b.get('price_change_pct_fmt')} 额{b.get('quote_volume_fmt')}"
+            f"\n资金费率(当前)：{t.get('funding_rate_fmt', '—')}"
+        )
+    return "\n".join(lines)
+
+
+async def interpret_symbol(
+    symbol: str,
+    stats_row: dict | None = None,
+    batch_id: str | None = None,
+) -> str:
+    if not settings.llm_api_key.strip():
+        raise RuntimeError("LLM_API_KEY 未配置")
+
+    png = await render_daily_chart_png_async(symbol, settings.chart_kline_limit)
+    b64 = base64.standard_b64encode(png).decode("ascii")
+    prompt = _build_prompt(symbol, stats_row)
+
+    payload = {
+        "model": settings.llm_model,
+        "messages": [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": prompt},
+                    {
+                        "type": "image_url",
+                        "image_url": {"url": f"data:image/png;base64,{b64}"},
+                    },
+                ],
+            }
+        ],
+        "max_tokens": 800,
+        "temperature": 0.4,
+    }
+
+    headers = {
+        "Authorization": f"Bearer {settings.llm_api_key}",
+        "Content-Type": "application/json",
+    }
+
+    async with httpx.AsyncClient(timeout=120.0) as client:
+        resp = await client.post(_api_url(), json=payload, headers=headers)
+        if resp.status_code >= 400:
+            # 部分模型不支持 vision，降级纯文本
+            logger.warning("LLM vision failed %s, fallback text", resp.status_code)
+            payload["messages"] = [{"role": "user", "content": prompt + "\n(附图日K+成交量未能传入，请基于数据简析)"}]
+            resp = await client.post(_api_url(), json=payload, headers=headers)
+        resp.raise_for_status()
+        data = resp.json()
+
+    content = data["choices"][0]["message"]["content"]
+    bid = batch_id or datetime.now().strftime("%Y-%m-%d-%H%M")
+    save_llm_interpretation(symbol, bid, content)
+    return content
+
+
+async def run_interpretation_batch(
+    symbols: list[str] | None = None,
+    *,
+    batch_id: str | None = None,
+) -> dict:
+    global _interpret_state
+
+    if _interpret_lock.locked():
+        return {"ok": False, "message": "解读任务进行中"}
+
+    stats = compute_three_day_stats()
+    if not stats.get("ok"):
+        return {"ok": False, "message": stats.get("message", "统计数据未就绪")}
+
+    sym_list = symbols or stats.get("symbols") or [x["symbol"] for x in stats.get("items", [])]
+    if not sym_list:
+        return {"ok": False, "message": "三日交集为空"}
+
+    stats_map = {x["symbol"]: x for x in stats.get("items", [])}
+    bid = batch_id or datetime.now().strftime("%Y-%m-%d-%H%M")
+    interval = settings.llm_symbol_interval_sec
+
+    async with _interpret_lock:
+        _interpret_state.update(
+            {
+                "running": True,
+                "current_symbol": "",
+                "done": 0,
+                "total": len(sym_list),
+                "batch_id": bid,
+                "last_error": "",
+            }
+        )
+        for i, sym in enumerate(sym_list):
+            _interpret_state["current_symbol"] = sym
+            try:
+                await interpret_symbol(sym, stats_map.get(sym), bid)
+                logger.info("LLM interpreted %s (%d/%d)", sym, i + 1, len(sym_list))
+            except Exception as e:
+                _interpret_state["last_error"] = str(e)
+                logger.error("LLM %s failed: %s", sym, e)
+                save_llm_interpretation(sym, bid, f"[解读失败] {e}")
+            _interpret_state["done"] = i + 1
+            if i < len(sym_list) - 1:
+                await asyncio.sleep(interval)
+
+        _interpret_state["running"] = False
+        _interpret_state["current_symbol"] = ""
+
+    return {
+        "ok": True,
+        "batch_id": bid,
+        "count": len(sym_list),
+        "interval_sec": interval,
+    }
+
+
+def schedule_interpret_background(symbols: list[str] | None = None) -> None:
+    """后台启动解读，不阻塞请求。"""
+
+    async def _run():
+        try:
+            await run_interpretation_batch(symbols)
+        except Exception as e:
+            logger.error("Background LLM batch failed: %s", e)
+
+    asyncio.create_task(_run())

backend/app/main.py

@@ -2,17 +2,19 @@ import logging
 from contextlib import asynccontextmanager
 from pathlib import Path
 
-from fastapi import FastAPI, HTTPException
-from fastapi.responses import FileResponse
+from fastapi import BackgroundTasks, FastAPI, HTTPException
+from fastapi.responses import FileResponse, Response
 from fastapi.staticfiles import StaticFiles
 
 from .config import ROOT_DIR, settings
 from .funding_store import get_funding_bundle
 from .kline_store import get_daily_candles, sync_daily_klines
-from .db import get_latest_snapshot, init_db, log_push, save_snapshot
+from .db import get_latest_snapshot, get_llm_interpretations, init_db, log_push, save_snapshot
 from .exceptions import BinanceRateLimitedError
 from .period_api import get_period_top30
 from .periods import get_daybefore_period, get_today_period, get_yesterday_period
+from .chart_image import render_daily_chart_png_async
+from .llm_service import get_interpret_state, run_interpretation_batch
 from .scheduler import job_finalize_yesterday, job_push_wecom, job_refresh_today, start_scheduler, startup_tasks, stop_scheduler
 from .stats import compute_three_day_stats
 from .aggregator import aggregate_period
@@ -165,6 +167,49 @@ async def api_funding_history(symbol: str, limit: int | None = None, refresh: bo
         raise HTTPException(502, "资金费率获取失败") from e
 
 
+@app.get("/api/chart/{symbol}/daily.png")
+async def api_chart_daily_png(symbol: str, limit: int | None = None):
+    sym = symbol.upper().strip()
+    if not sym.endswith("USDT"):
+        raise HTTPException(400, "invalid symbol")
+    try:
+        png = await render_daily_chart_png_async(sym, limit or settings.chart_kline_limit)
+        return Response(content=png, media_type="image/png")
+    except ValueError as e:
+        raise HTTPException(404, str(e)) from e
+    except Exception as e:
+        logger.error("chart png %s failed: %s", sym, e)
+        raise HTTPException(502, "图表生成失败") from e
+
+
+@app.get("/api/llm/status")
+async def api_llm_status():
+    state = get_interpret_state()
+    return {
+        **state,
+        "enabled": bool(settings.llm_api_key.strip()),
+        "model": settings.llm_model,
+        "base_url": settings.llm_base_url,
+        "interval_sec": settings.llm_symbol_interval_sec,
+    }
+
+
+@app.get("/api/llm/interpretations")
+async def api_llm_interpretations(batch_id: str | None = None, limit: int = 50):
+    return {"items": get_llm_interpretations(batch_id, limit)}
+
+
+@app.post("/api/llm/interpret/run")
+async def api_llm_interpret_run(background_tasks: BackgroundTasks):
+    if not settings.llm_api_key.strip():
+        raise HTTPException(400, "LLM_API_KEY 未配置")
+    state = get_interpret_state()
+    if state.get("running"):
+        return {"ok": False, "message": "解读任务进行中", **state}
+    background_tasks.add_task(run_interpretation_batch)
+    return {"ok": True, "message": "已启动三日交集解读队列", **get_interpret_state()}
+
+
 @app.post("/api/chart/{symbol}/daily/refresh")
 async def api_chart_daily_refresh(symbol: str, limit: int | None = None):
     """强制从币安同步日 K 到本地库。"""

backend/app/scheduler.py

@@ -13,6 +13,8 @@ from .periods import get_daybefore_period, get_today_period, get_yesterday_perio
 from .state import get_today_cache, set_today_cache
 from .funding_store import prefetch_funding
 from .kline_store import prefetch_symbols
+from .llm_service import run_interpretation_batch, schedule_interpret_background
+from .stats import compute_three_day_stats
 from .wecom import build_markdown, send_wecom_markdown
 
 logger = logging.getLogger(__name__)
@@ -147,6 +149,18 @@ async def job_refresh_today() -> None:
         _restore_today_from_db()
 
 
+async def job_llm_interpret() -> None:
+    """08:05 对三日交集币种逐个大模型解读（每币间隔 3 分钟）。"""
+    logger.info("Job: LLM interpret three-day intersection")
+    if not settings.llm_api_key.strip():
+        logger.info("LLM_API_KEY not set, skip")
+        return
+    try:
+        await run_interpretation_batch()
+    except Exception as e:
+        logger.error("LLM job failed: %s", e)
+
+
 async def startup_tasks() -> None:
     init_db()
     now = now_shanghai()
@@ -194,6 +208,12 @@ async def startup_tasks() -> None:
             except Exception as e:
                 logger.error("Startup catch-up push failed: %s", e)
 
+    if settings.llm_api_key.strip() and settings.llm_auto_on_startup:
+        stats = compute_three_day_stats()
+        if stats.get("ok") and stats.get("symbols"):
+            logger.info("Startup: schedule one LLM interpret batch")
+            schedule_interpret_background()
+
 
 def start_scheduler() -> None:
     scheduler.add_job(
@@ -208,19 +228,25 @@ def start_scheduler() -> None:
         id="push_wecom",
         replace_existing=True,
     )
+    refresh_hours = max(1, settings.refresh_minutes // 60)
     scheduler.add_job(
         job_refresh_today,
-        CronTrigger(minute=f"*/{settings.refresh_minutes}", timezone="Asia/Shanghai"),
+        CronTrigger(hour=f"*/{refresh_hours}", minute=0, timezone="Asia/Shanghai"),
         id="refresh_today",
         replace_existing=True,
     )
+    scheduler.add_job(
+        job_llm_interpret,
+        CronTrigger(hour=8, minute=5, timezone="Asia/Shanghai"),
+        id="llm_interpret",
+        replace_existing=True,
+    )
     if not scheduler.running:
         scheduler.start()
     logger.info(
-        "Scheduler started (today=%s, yesterday=%s, every %d min)",
-        settings.today_data_mode,
-        settings.yesterday_data_mode,
-        settings.refresh_minutes,
+        "Scheduler started (today every %dh, LLM 08:05, interval %ds)",
+        refresh_hours,
+        settings.llm_symbol_interval_sec,
     )
 
 

backend/app/stats.py

@@ -1,4 +1,4 @@
-"""三日数据统计：连续三日 Top30 且 |涨跌|>=5%。"""
+"""三日数据统计：连续三日成交额 Top30 交集（不限制涨跌幅）。"""
 
 from typing import Any
 
@@ -15,7 +15,6 @@ def compute_three_day_stats() -> dict[str, Any]:
     yesterday_snap = get_latest_snapshot("yesterday")
     daybefore_snap = get_latest_snapshot("daybefore")
 
-    threshold = settings.change_threshold
     top_n = settings.top_n
 
     missing = []
@@ -31,7 +30,7 @@ def compute_three_day_stats() -> dict[str, Any]:
             "ok": False,
             "missing_periods": missing,
             "message": f"缺少快照：{', '.join(missing)}，请等待刷新或手动触发",
-            "criteria": _criteria_text(threshold, top_n),
+            "criteria": _criteria_text(top_n),
             "count": 0,
             "items": [],
             "periods": _period_meta(today_snap, yesterday_snap, daybefore_snap),
@@ -46,12 +45,6 @@ def compute_three_day_stats() -> dict[str, Any]:
 
     for sym in sorted(symbols):
         t, y, b = today_map[sym], yesterday_map[sym], daybefore_map[sym]
-        if not (
-            abs(t.get("price_change_pct", 0)) >= threshold
-            and abs(y.get("price_change_pct", 0)) >= threshold
-            and abs(b.get("price_change_pct", 0)) >= threshold
-        ):
-            continue
         qualified.append(
             {
                 "symbol": sym,
@@ -79,9 +72,10 @@ def compute_three_day_stats() -> dict[str, Any]:
 
     return {
         "ok": True,
-        "criteria": _criteria_text(threshold, top_n),
+        "criteria": _criteria_text(top_n),
         "count": len(qualified),
         "items": qualified,
+        "symbols": [q["symbol"] for q in qualified],
         "periods": _period_meta(today_snap, yesterday_snap, daybefore_snap),
         "summary": {
             "today_top30": len(today_map),
@@ -92,11 +86,8 @@ def compute_three_day_stats() -> dict[str, Any]:
     }
 
 
-def _criteria_text(threshold: float, top_n: int) -> str:
-    return (
-        f"连续三日成交额 Top{top_n} 且每日 |涨跌幅| ≥ {threshold:g}%"
-        f"（今日/昨日/前日三个完整切日周期）"
-    )
+def _criteria_text(top_n: int) -> str:
+    return f"连续三日成交额均位列 Top{top_n}（今日/昨日/前日交集，涨跌幅不限）"
 
 
 def _pick_fields(row: dict) -> dict:

backend/requirements.txt

@@ -4,3 +4,4 @@ httpx[socks]>=0.27.0
 apscheduler>=3.10.4
 python-dotenv>=1.0.1
 pydantic-settings>=2.6.0
+matplotlib>=3.8.0