Add derivatives tool, trim provider fields, widen model call retries

- New chat tool get_derivatives: funding rate (next estimate and recent
  settlements), premium, open interest change vs price, global and top
  trader long/short ratios, taker buy/sell ratio from Binance public
  endpoints. Each part fails independently.
- Strip whitespace from provider name and model; a leading space in the
  model name made the upstream return 404.
- Retry connection failures and mid-stream disconnects (raw httpx /
  httpx2 errors are not wrapped by the SDKs) up to 3 times while no
  output has been emitted, and surface them as chat errors.
- Return 30 recent bars from get_klines instead of 60 to cut tokens.

backend/src/alphapulse/ai/llm.py

@@ -14,6 +14,8 @@ from dataclasses import dataclass, field
 from typing import Any, Literal
 
 import anthropic
+import httpx
+import httpx2  # anthropic SDK 使用的 HTTP 客户端，异常类与 httpx 不通用
 import openai
 
 from alphapulse.core.crypto import decrypt
@@ -25,7 +27,8 @@ TIMEOUT_SECONDS = 600
 Effort = Literal["low", "medium", "high", "xhigh", "max"]
 # SDK 自带重试只针对连接错误、429 和 5xx
 MAX_RETRIES = 2
-# 流内错误（上游过载等）SDK 不重试，由这里重试；只在还没有输出内容时重试
+# 流内错误（上游过载等）和流式读取中的网络中断 SDK 不重试；连接失败 SDK 重试后仍可能失败（上游短暂不可达）。
+# 这些都由这里再重试，且只在还没有输出内容时重试
 STREAM_RETRIES = 3
 STREAM_RETRY_DELAY_SECONDS = 2
 
@@ -84,11 +87,12 @@ async def stream(
                 output = True
                 yield event
             return
-        except (openai.APIError, anthropic.APIError) as e:
-            # 已经推送过内容再重试会重复输出，只重试还没有输出时的流内错误
-            if output or attempt == STREAM_RETRIES or not _in_stream_error(e):
+        # 流式读取过程中的网络错误 SDK 不包装，以原始的 httpx / httpx2 异常抛出
+        except (openai.APIError, anthropic.APIError, httpx.TransportError, httpx2.TransportError) as e:
+            # 已经推送过内容再重试会重复输出
+            if output or attempt == STREAM_RETRIES or not _retryable(e):
                 raise _llm_error(e) from e
-            logger.warning("模型流内出错，%ss 后第 %s 次重试：%s", STREAM_RETRY_DELAY_SECONDS, attempt + 1, _llm_error(e))
+            logger.warning("模型调用失败，%ss 后第 %s 次重试：%s", STREAM_RETRY_DELAY_SECONDS, attempt + 1, _llm_error(e))
             await asyncio.sleep(STREAM_RETRY_DELAY_SECONDS)
 
 
@@ -100,6 +104,15 @@ def _in_stream_error(e: Exception) -> bool:
     return isinstance(e, anthropic.APIStatusError) and e.status_code == 200
 
 
+def _retryable(e: Exception) -> bool:
+    """流内错误事件、连接失败、读取中断可重试；超时不重试（单次已等 TIMEOUT_SECONDS）"""
+    if isinstance(e, (openai.APITimeoutError, anthropic.APITimeoutError, httpx.TimeoutException, httpx2.TimeoutException)):
+        return False
+    return _in_stream_error(e) or isinstance(
+        e, (openai.APIConnectionError, anthropic.APIConnectionError, httpx.TransportError, httpx2.TransportError),
+    )
+
+
 def _llm_error(e: Exception) -> LlmError:
     if _in_stream_error(e):
         error = e.body.get("error") if isinstance(e.body, dict) else None
@@ -107,10 +120,12 @@ def _llm_error(e: Exception) -> LlmError:
         return LlmError(f"模型接口出错：{message or e.message}")
     if isinstance(e, (openai.APIStatusError, anthropic.APIStatusError)):
         return LlmError(f"模型接口返回 {e.status_code}：{e.message}")
-    if isinstance(e, (openai.APITimeoutError, anthropic.APITimeoutError)):
+    if isinstance(e, (openai.APITimeoutError, anthropic.APITimeoutError, httpx.TimeoutException, httpx2.TimeoutException)):
         return LlmError(f"模型接口超时（{TIMEOUT_SECONDS}s）")
     if isinstance(e, (openai.APIConnectionError, anthropic.APIConnectionError)):
         return LlmError(f"无法连接模型接口：{e}")
+    if isinstance(e, (httpx.TransportError, httpx2.TransportError)):
+        return LlmError(f"模型接口连接中断：{e!r}")
     return LlmError(f"模型接口出错：{e}")
 
 

backend/src/alphapulse/ai/prompt.py

@@ -12,7 +12,7 @@ from alphapulse.models import ContextVersion, MarketSymbol, NewsItem
 BASE_INSTRUCTIONS = """你是用户的个人投资研究助手，服务于 AlphaPulse 系统。
 
 ## 工作方式
-- 先用工具取证据，再下结论：新闻用 search_news / get_news，行情用 search_symbols / get_klines / get_ticker。不要凭记忆给出价格、日期或新闻内容。
+- 先用工具取证据，再下结论：新闻用 search_news / get_news，行情用 search_symbols / get_klines / get_ticker / get_derivatives。不要凭记忆给出价格、日期或新闻内容。
 - 引用新闻时写明 [新闻 id] 和发布时间；引用 K 线时写明交易对和周期。
 - 点位（抄底区间、止损、止盈）必须给出依据：来自 get_klines 的高低点、均线、ATR、波段高低点，并说明失效条件。
 - 数据不足或互相矛盾时如实说明缺什么，不编造。

backend/src/alphapulse/ai/tools.py

@@ -4,6 +4,7 @@
 工具出错时把错误文本返回给模型，不编造数据。
 """
 
+import asyncio
 import json
 from collections.abc import Awaitable, Callable
 from dataclasses import dataclass
@@ -26,7 +27,7 @@ from alphapulse.models.market import INTERVALS
 LOCAL_TZ = ZoneInfo("Asia/Shanghai")
 NEWS_BODY_LIMIT = 4000
 # 返回给模型的逐根 K 线数量；统计指标基于全部取到的 K 线计算
-BARS_IN_RESULT = 60
+BARS_IN_RESULT = 30
 SOURCE_NAMES = {"cls_telegraph": "财联社电报", "cls_depth": "财联社深度", "wscn_live": "华尔街见闻快讯", "wscn_news": "华尔街见闻文章"}
 
 
@@ -195,6 +196,114 @@ async def get_ticker(args: GetTicker) -> ToolOutcome:
     }))
 
 
+# ---------- 衍生品数据 ----------
+
+# 每个序列返回给模型的最近点数；窗口统计基于全部取到的数据
+POINTS_IN_RESULT = 12
+FUNDING_HISTORY = 30
+
+
+class GetDerivatives(BaseModel):
+    symbol: Annotated[str, Field(description="U 本位永续交易对，如 BTCUSDT")]
+    period: Annotated[
+        Literal["5m", "15m", "30m", "1h", "2h", "4h", "6h", "12h", "1d"],
+        Field(description="持仓量、多空比、主动买卖比的统计周期"),
+    ] = "1h"
+    limit: Annotated[int, Field(ge=2, le=500, description="统计窗口的周期数，如 1h × 24 为最近一天；币安只提供最近 30 天")] = 24
+
+
+def pct(value: float) -> float:
+    return round(value * 100, 4)
+
+
+def ratio_summary(rows: list[dict], key: str) -> dict:
+    values = [float(r[key]) for r in rows]
+    return {
+        "latest": values[-1], "window_avg": round(sum(values) / len(values), 4), "window_min": min(values), "window_max": max(values),
+        "recent": [[ms_local(r["timestamp"]), float(r[key])] for r in rows[-POINTS_IN_RESULT:]],
+    }
+
+
+async def funding_part(symbol: str) -> dict:
+    premium, history = await asyncio.gather(
+        call_binance(client.get("um", "premium_index", {"symbol": symbol})),
+        call_binance(client.get("um", "funding_rate", {"symbol": symbol, "limit": FUNDING_HISTORY})),
+    )
+    mark, index = float(premium["markPrice"]), float(premium["indexPrice"])
+    rates = [float(r["fundingRate"]) for r in history]
+    return {
+        "unit": "%",
+        # premiumIndex 的 lastFundingRate 随行情实时变化，是下次结算的预估值
+        "next_rate_estimate_pct": pct(float(premium["lastFundingRate"])),
+        "next_funding_time": ms_local(premium["nextFundingTime"]),
+        "interval_hours": round((history[-1]["fundingTime"] - history[-2]["fundingTime"]) / 3_600_000) if len(history) >= 2 else None,
+        "mark_price": mark, "index_price": index, "premium_pct": pct((mark - index) / index),
+        "history_count": len(rates),
+        "history_avg_pct": pct(sum(rates) / len(rates)) if rates else None,
+        "history_max_pct": pct(max(rates)) if rates else None,
+        "history_min_pct": pct(min(rates)) if rates else None,
+        "recent_settled": [[ms_local(r["fundingTime"]), pct(float(r["fundingRate"]))] for r in history[-8:]],
+    }
+
+
+async def open_interest_part(symbol: str, period: str, limit: int) -> dict:
+    rows = await call_binance(client.get("um", "open_interest_hist", {"symbol": symbol, "period": period, "limit": limit}))
+    if not rows:
+        return {"error": "无数据"}
+    first, last = rows[0], rows[-1]
+
+    def price(r: dict) -> float:
+        return float(r["sumOpenInterestValue"]) / float(r["sumOpenInterest"])
+
+    return {
+        "latest_contracts": float(last["sumOpenInterest"]), "latest_value_usdt": round(float(last["sumOpenInterestValue"])),
+        "window_change_pct": pct(float(last["sumOpenInterest"]) / float(first["sumOpenInterest"]) - 1),
+        # 由持仓价值 / 持仓量推算的同窗口价格变化，用于对照持仓量与价格的方向
+        "window_price_change_pct": pct(price(last) / price(first) - 1),
+        "recent": [[ms_local(r["timestamp"]), float(r["sumOpenInterest"])] for r in rows[-POINTS_IN_RESULT:]],
+    }
+
+
+async def ratio_part(path_key: str, symbol: str, period: str, limit: int, key: str) -> dict:
+    rows = await call_binance(client.get("um", path_key, {"symbol": symbol, "period": period, "limit": limit}))
+    return ratio_summary(rows, key) if rows else {"error": "无数据"}
+
+
+async def taker_part(symbol: str, period: str, limit: int) -> dict:
+    rows = await call_binance(client.get("um", "taker_buy_sell", {"symbol": symbol, "period": period, "limit": limit}))
+    if not rows:
+        return {"error": "无数据"}
+    buy, sell = sum(float(r["buyVol"]) for r in rows), sum(float(r["sellVol"]) for r in rows)
+    return {**ratio_summary(rows, "buySellRatio"), "window_buy_vol": buy, "window_sell_vol": sell}
+
+
+async def settle(request: Awaitable[dict]) -> dict:
+    """单项失败只标记该项，其余照常返回"""
+    try:
+        return await request
+    except HTTPException as e:
+        return {"error": e.detail}
+
+
+async def get_derivatives(args: GetDerivatives) -> ToolOutcome:
+    symbol = args.symbol.strip().upper()
+    funding, oi, accounts, top, taker = await asyncio.gather(
+        settle(funding_part(symbol)),
+        settle(open_interest_part(symbol, args.period, args.limit)),
+        settle(ratio_part("global_long_short", symbol, args.period, args.limit, "longShortRatio")),
+        settle(ratio_part("top_long_short_position", symbol, args.period, args.limit, "longShortRatio")),
+        settle(taker_part(symbol, args.period, args.limit)),
+    )
+    return ToolOutcome(dump({
+        "symbol": symbol, "period": args.period, "window": f"最近 {args.limit} 个 {args.period}",
+        "funding_rate": funding,
+        "open_interest": oi,
+        "long_short_account_ratio": accounts,
+        "top_trader_position_ratio": top,
+        "taker_buy_sell_ratio": taker,
+    }))
+
+
 # ---------- Skills 与 CONTEXT.md ----------
 
 class NoArgs(BaseModel):
@@ -286,6 +395,10 @@ TOOLS: dict[str, Tool] = {
     "search_symbols": Tool(SearchSymbols, search_symbols, "在币安 U 本位永续（含美股/韩股等 TradFi 永续）中查找交易对代码。"),
     "get_klines": Tool(GetKlines, get_klines, "取 U 本位永续 K 线和确定性统计（涨跌幅、高低点、MA20/60、ATR14、波段高低点、量比），用于判断支撑阻力和止损位。"),
     "get_ticker": Tool(GetTicker, get_ticker, "取 U 本位永续 24h 行情和最后成交时间。"),
+    "get_derivatives": Tool(GetDerivatives, get_derivatives, (
+        "取 U 本位永续的衍生品数据，用于判断多空拥挤程度：资金费率（下次预估、近 30 次结算，单位 %）、"
+        "溢价、持仓量（窗口变化及同期价格变化）、全市场账户多空比、大户持仓多空比、主动买卖比（>1 表示主动买入多）。"
+    )),
     "list_skills": Tool(NoArgs, list_skills, "列出全部 skills 的路径、优先级和版本状态。"),
     "read_skill": Tool(ReadSkill, read_skill, "读取 skill 的某个版本（默认最新，可能是草稿）。"),
     "propose_skill_edit": Tool(ProposeSkillEdit, propose_skill_edit, "修改已有 skill：保存为草稿版本，用户发布后才生效。content 必须是完整内容。"),