增加大模型

2026-05-26 09:38:23 +08:00
parent e0ec3f87a9
commit 27031ab676
14 changed files with 797 additions and 69 deletions
@@ -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())