kroutony
1abfdefecd
- config.py: Add HTF_TIMEFRAME (1h) and HTF_CANDLE_LIMIT (50) - data_fetcher.py: Fetch both 5m and 1h candles per symbol - indicators.py: Add ADX, StochRSI, OBV+slope, CMF to 5m indicators; new functions for HTF indicators, pivot points, and their summaries - main.py: Wire up HTF data flow (1h indicators + pivots → LLM summary) - llm_analyzer.py: Rewrite prompt with MTF filter (1h trend alignment), require 2+ confirmations for BUY, confidence scoring guide Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
119 lines
3.7 KiB
Python
119 lines
3.7 KiB
Python
import json
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import logging
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import re
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import subprocess
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logger = logging.getLogger(__name__)
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def analyze_market(indicator_summary: str, account_status: str) -> list[dict]:
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"""Call Claude CLI to analyze market data and return trade signals."""
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prompt = f"""你是一位專業的加密貨幣短線交易分析師。
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## 帳戶狀態
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{account_status}
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## 目前市場指標摘要
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{indicator_summary}
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請根據以下策略分析每個幣種並給出交易建議：
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## 交易策略
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### 最高優先：多時間框架過濾（現貨，只做多）
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- 1小時趨勢為多頭（EMA9 > EMA21）時，才考慮 BUY
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- 1小時為空頭時，只持有或平倉（SELL），不開新倉
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- 1小時 ADX < 20（盤整）時，避免進場
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- 1小時 ADX > 25 且方向一致 = 高信心交易
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### 進場訊號 (BUY) — 需至少2個確認
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1. **超賣反彈**: StochRSI K < 0.2 且 K 上穿 D + RSI < 40
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2. **均值回歸**: 價格觸及 BB 下軌 + RSI < 40 + CMF > 0（有買壓）
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3. **趨勢啟動**: MACD 金叉 + EMA9 上穿 EMA21 + ADX > 20（有趨勢）
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4. **支撐反彈**: 價格接近樞紐支撐位（S1/S2）+ OBV 流入 + RSI < 45
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### 出場訊號 (SELL)
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1. **超買回落**: StochRSI K > 0.8 且 K 下穿 D + RSI > 65
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2. **阻力拒絕**: 價格接近樞紐阻力位（R1/R2）+ OBV 流出
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3. **趨勢反轉**: MACD 死叉 + EMA9 下穿 EMA21 + CMF < 0
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### 過濾條件（必須全部滿足）
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- 成交量需高於 20 期平均（確認動能）
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- 5分鐘 ADX > 15（排除極度盤整）
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- OBV 方向需與交易方向一致（量價確認）
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- ATR 過高時降低 suggested_amount_pct（波動風控）
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### 信心分數指引
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- 0.8+: 多時間框架對齊 + 3個以上確認指標
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- 0.6-0.8: 多時間框架對齊 + 2個確認
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- 0.4-0.6: 單一時間框架訊號，降低倉位
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- < 0.4: 不建議交易，回傳 HOLD
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請以 JSON 格式回傳，每個幣種一個物件：
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```json
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[
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{{
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"symbol": "tBTCUST",
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"action": "BUY" | "SELL" | "HOLD",
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"confidence": 0.0-1.0,
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"reason": "簡短理由（含觸發的指標）",
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"suggested_amount_pct": 0.05-0.20
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}}
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]
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```
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只回傳 JSON，不要其他文字。"""
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try:
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result = subprocess.run(
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["claude", "-p", prompt, "--output-format", "json"],
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capture_output=True,
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text=True,
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timeout=120,
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)
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if result.returncode != 0:
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logger.error("Claude CLI failed (rc=%d): %s", result.returncode, result.stderr)
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return []
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return _parse_llm_response(result.stdout)
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except subprocess.TimeoutExpired:
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logger.error("Claude CLI timed out")
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return []
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except FileNotFoundError:
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logger.error("Claude CLI not found — is 'claude' installed and in PATH?")
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return []
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except Exception as e:
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logger.error("LLM analysis error: %s", e)
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return []
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def _parse_llm_response(raw: str) -> list[dict]:
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"""Extract the JSON array from Claude's response."""
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# First try: the output-format json wraps response in {"result": "..."}
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try:
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wrapper = json.loads(raw)
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if isinstance(wrapper, dict) and "result" in wrapper:
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raw = wrapper["result"]
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except (json.JSONDecodeError, TypeError):
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pass
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# Try direct parse
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if isinstance(raw, list):
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return raw
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try:
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parsed = json.loads(raw)
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if isinstance(parsed, list):
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return parsed
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except (json.JSONDecodeError, TypeError):
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pass
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# Try extracting JSON array from markdown code block or mixed text
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match = re.search(r'\[[\s\S]*?\]', raw)
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if match:
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try:
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return json.loads(match.group())
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except json.JSONDecodeError:
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pass
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logger.warning("Could not parse LLM response as JSON array")
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return []
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