dekun
263 lines
9.8 KiB
Python
263 lines
9.8 KiB
Python
from __future__ import annotations
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import json
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import logging
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import re
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from typing import Any, Literal
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import httpx
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from .config import GemmaConfig
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LOGGER = logging.getLogger("onchain_scout.gemma_client")
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def _extract_json_object(text: str) -> dict[str, Any] | None:
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text = text.strip()
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m = re.search(r"\{[\s\S]*\}", text)
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if not m:
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return None
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raw = m.group(0)
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try:
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return json.loads(raw)
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except json.JSONDecodeError:
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return None
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def _resolve_api_style(conf: GemmaConfig) -> Literal["ollama", "openai"]:
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style = (conf.api_style or "ollama").strip().lower()
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if style == "openai":
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return "openai"
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if style == "ollama":
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return "ollama"
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if (conf.api_key or "").strip():
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return "openai"
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return "ollama"
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def _chat_url(conf: GemmaConfig, style: Literal["ollama", "openai"]) -> str:
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base = conf.ollama_base_url.rstrip("/")
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if style == "openai":
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if base.endswith("/v1"):
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return f"{base}/chat/completions"
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return f"{base}/v1/chat/completions"
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return f"{base}/api/chat"
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def _build_headers(conf: GemmaConfig, style: Literal["ollama", "openai"]) -> dict[str, str]:
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headers = {"Content-Type": "application/json"}
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if style == "openai":
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key = (conf.api_key or "").strip()
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if key:
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headers["Authorization"] = f"Bearer {key}"
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return headers
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def _strip_b64_prefix(raw: str) -> str:
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s = raw.strip()
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if "," in s and s.lower().startswith("data:"):
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return s.split(",", 1)[1]
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return s
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class OllamaGemmaClient:
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def __init__(self, conf: GemmaConfig) -> None:
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self.conf = conf
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self._style = _resolve_api_style(conf)
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self.timeout = httpx.Timeout(conf.timeout_seconds, read=conf.timeout_seconds + 30.0)
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async def _chat(
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self,
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*,
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system: str,
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user_text: str,
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image_base64: str | None,
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temperature: float,
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json_mode: bool,
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) -> str:
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url = _chat_url(self.conf, self._style)
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headers = _build_headers(self.conf, self._style)
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if self._style == "openai":
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user_content: str | list[dict[str, Any]] = user_text
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if image_base64 and self.conf.send_chart_image:
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b64 = _strip_b64_prefix(image_base64)
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user_content = [
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{"type": "text", "text": user_text},
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{
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"type": "image_url",
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"image_url": {"url": f"data:image/png;base64,{b64}"},
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},
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]
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payload: dict[str, Any] = {
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"model": self.conf.model,
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"messages": [
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{"role": "system", "content": system},
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{"role": "user", "content": user_content},
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],
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"temperature": temperature,
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"stream": False,
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}
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if json_mode:
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payload["response_format"] = {"type": "json_object"}
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else:
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message: dict[str, Any] = {"role": "user", "content": user_text}
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if image_base64 and self.conf.send_chart_image:
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message["images"] = [_strip_b64_prefix(image_base64)]
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payload = {
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"model": self.conf.model,
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"messages": [{"role": "system", "content": system}, message],
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"stream": False,
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"options": {"temperature": temperature},
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}
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if json_mode:
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payload["format"] = "json"
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async with httpx.AsyncClient(timeout=self.timeout, trust_env=False) as client:
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resp = await client.post(url, json=payload, headers=headers)
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resp.raise_for_status()
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data = resp.json()
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if self._style == "openai":
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choices = data.get("choices") or []
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if choices and isinstance(choices[0], dict):
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msg = (choices[0].get("message") or {}).get("content") or ""
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return str(msg)
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return ""
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return str((data.get("message") or {}).get("content") or "")
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async def rank_funnel(
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self,
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symbol: str,
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programmatic_text: str,
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ohlc_csv_block: str,
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image_base64: str | None,
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) -> dict[str, Any]:
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"""调用 Ollama 或 OpenAI 兼容网关，让 Gemma 按漏斗标准 JSON 回复。"""
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system = (
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"你是加密货币永续合约的日线结构分析师。只输出一个 JSON 对象，不要 Markdown，不要代码围栏。"
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"字段必须全部存在且为英文枚举/数字："
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'{"daily_structure":"strong|ok|weak",'
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'"volume_view":"high|mid|low",'
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'"upside_space":"high|mid|low",'
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'"mid_resistance":"low|mid|high",'
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'"priority":1-10整数,'
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'"one_liner":"中文一句"}。'
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"priority 越高越值得优先关注：成交大、日线结构好、上方空间大、中间阻力小则给高分。"
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)
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user_body = (
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f"标的 {symbol} USDT 永续。\n"
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f"程序化摘要:\n{programmatic_text}\n\n"
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f"最近日线 OHLCV（时间正序最后一行为最新）:\n{ohlc_csv_block}\n"
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)
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try:
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msg = await self._chat(
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system=system,
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user_text=user_body,
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image_base64=image_base64,
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temperature=self.conf.temperature,
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json_mode=self.conf.json_mode,
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)
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except httpx.HTTPStatusError as exc:
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LOGGER.warning(
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"gemma_http_error symbol=%s status=%s url=%s",
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symbol,
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exc.response.status_code,
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exc.request.url,
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)
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return {
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"error": f"http_{exc.response.status_code}",
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"raw": (exc.response.text or "")[:500],
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"daily_structure": "weak",
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"volume_view": "low",
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"upside_space": "low",
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"mid_resistance": "high",
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"priority": 1,
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"one_liner": f"模型网关 HTTP {exc.response.status_code}",
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}
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except Exception as exc: # noqa: BLE001
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LOGGER.warning("gemma_request_failed symbol=%s: %s", symbol, exc)
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return {
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"error": str(exc),
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"daily_structure": "weak",
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"volume_view": "low",
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"upside_space": "low",
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"mid_resistance": "high",
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"priority": 1,
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"one_liner": f"模型调用失败: {exc}",
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}
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parsed = _extract_json_object(msg) if msg else None
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if parsed is None:
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LOGGER.warning("gemma_parse_failed symbol=%s raw_len=%s", symbol, len(msg))
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return {
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"error": "parse_failed",
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"raw": msg[:2000],
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"daily_structure": "weak",
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"volume_view": "low",
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"upside_space": "low",
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"mid_resistance": "high",
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"priority": 1,
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"one_liner": "模型输出无法解析为 JSON",
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}
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return _normalize_gemma_dict(parsed)
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async def generate_daily_report(self, report_day_cn: str, btc_snapshot: dict, stats: dict) -> dict[str, Any]:
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system = (
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"你是加密交易复盘助手。输出严格 JSON 对象，不要 Markdown。字段必须存在："
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'{"headline":"...","btc_explain":"...","summary":"...","risk_points":["..."],"action_hint":"..."}。'
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"用中文，简洁专业，不写投资建议免责声明。"
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)
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user_body = (
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f"请生成 {report_day_cn} 的晨报。\n"
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f"BTC 快照: {json.dumps(btc_snapshot, ensure_ascii=False)}\n"
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f"昨日统计: {json.dumps(stats, ensure_ascii=False)}\n"
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"要求：1) headline 一句话；2) btc_explain 解释方向；"
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"3) summary 覆盖 WATCH/TRIGGER/漏斗；4) risk_points 给1-3条；5) action_hint 给执行提示。"
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)
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try:
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msg = await self._chat(
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system=system,
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user_text=user_body,
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image_base64=None,
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temperature=0.1,
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json_mode=True,
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)
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except Exception as exc: # noqa: BLE001
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return {"error": "parse_failed", "raw": str(exc)[:1200]}
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parsed = _extract_json_object(msg) if msg else None
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if parsed is None:
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return {"error": "parse_failed", "raw": msg[:1200]}
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risk = parsed.get("risk_points")
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if not isinstance(risk, list):
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risk = [str(risk or "")]
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risk = [str(x)[:120] for x in risk if str(x or "").strip()][:3] or ["注意高波动时的回撤风险。"]
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return {
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"headline": str(parsed.get("headline") or "")[:120],
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"btc_explain": str(parsed.get("btc_explain") or "")[:220],
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"summary": str(parsed.get("summary") or "")[:360],
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"risk_points": risk,
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"action_hint": str(parsed.get("action_hint") or "")[:220],
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}
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def _normalize_gemma_dict(d: dict[str, Any]) -> dict[str, Any]:
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def _enum(v: Any, choices: set[str], default: str) -> str:
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s = str(v or "").strip().lower()
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return s if s in choices else default
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try:
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pr = int(float(d.get("priority", 1)))
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except (TypeError, ValueError):
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pr = 1
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pr = max(1, min(10, pr))
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return {
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"daily_structure": _enum(d.get("daily_structure"), {"strong", "ok", "weak"}, "weak"),
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"volume_view": _enum(d.get("volume_view"), {"high", "mid", "low"}, "low"),
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"upside_space": _enum(d.get("upside_space"), {"high", "mid", "low"}, "low"),
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"mid_resistance": _enum(d.get("mid_resistance"), {"low", "mid", "high"}, "high"),
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"priority": pr,
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"one_liner": str(d.get("one_liner") or "")[:280],
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}
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