update
This commit is contained in:
aaron
parent
562246e949
commit
a53d8dc9f9
@ -63,6 +63,7 @@ def default_llm_config():
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"recommendations": _env_bool("ALPHAX_LLM_RECOMMENDATIONS_ENABLED", True),
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"sentiment": _env_bool("ALPHAX_LLM_SENTIMENT_ENABLED", True),
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"review": _env_bool("ALPHAX_LLM_REVIEW_ENABLED", True),
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"chat": _env_bool("ALPHAX_LLM_CHAT_ENABLED", True),
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},
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}
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324
app/db/chat_assistant_db.py
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324
app/db/chat_assistant_db.py
Normal file
@ -0,0 +1,324 @@
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"""Chat assistant persistence helpers."""
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from __future__ import annotations
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import json
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from datetime import datetime
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from app.db.llm_insights import repair_mojibake_json, repair_mojibake_text
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from app.db.postgres_connection import ensure_migrations_once
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from app.db.schema import get_conn
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def _now() -> str:
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return datetime.now().isoformat(timespec="seconds")
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def _loads(value, fallback=None):
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try:
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if isinstance(value, str) and value.strip():
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return repair_mojibake_json(json.loads(value))
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if value is not None:
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return repair_mojibake_json(value)
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except Exception:
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pass
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return fallback if fallback is not None else {}
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def _dumps(value) -> str:
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return json.dumps(repair_mojibake_json(value if value is not None else {}), ensure_ascii=False, sort_keys=True, default=str)
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def init_chat_tables():
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ensure_migrations_once()
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def _normalize_title(title: str) -> str:
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title = str(title or "").strip()
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return title[:32] or "新对话"
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def _load_session(row):
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if not row:
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return None
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item = dict(row)
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item["memory"] = _loads(item.pop("memory_json", "{}"), {})
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return item
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def _load_message(row):
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if not row:
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return None
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item = dict(row)
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item["content_text"] = repair_mojibake_text(item.get("content_text", ""))
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item["content"] = _loads(item.pop("content_json", "{}"), {})
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item["context"] = _loads(item.pop("context_json", "{}"), {})
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return item
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def get_user_preferences(user_id: int) -> dict:
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init_chat_tables()
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conn = get_conn()
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try:
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row = conn.execute("SELECT * FROM chat_user_preferences WHERE user_id=%s", (int(user_id),)).fetchone()
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finally:
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conn.close()
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if not row:
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return {
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"preferred_symbols": [],
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"preferred_timeframes": ["15m", "1h", "4h", "1d"],
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"answer_style": "two_stage",
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"risk_profile": "balanced",
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"last_intent": "",
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"last_symbol": "",
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"recent_topics": [],
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}
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prefs = _loads(row.get("preferences_json"), {})
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prefs.setdefault("preferred_symbols", [])
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prefs.setdefault("preferred_timeframes", ["15m", "1h", "4h", "1d"])
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prefs.setdefault("answer_style", "two_stage")
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prefs.setdefault("risk_profile", "balanced")
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prefs.setdefault("last_intent", "")
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prefs.setdefault("last_symbol", "")
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prefs.setdefault("recent_topics", [])
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return prefs
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def update_user_preferences(user_id: int, patch: dict) -> dict:
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init_chat_tables()
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current = get_user_preferences(user_id)
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patch = patch or {}
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for key, value in patch.items():
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if key in ("preferred_symbols", "preferred_timeframes", "recent_topics") and isinstance(value, list):
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merged = list(dict.fromkeys([str(x) for x in current.get(key, []) if str(x).strip()] + [str(x) for x in value if str(x).strip()]))
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current[key] = merged[-12:]
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elif value is not None:
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current[key] = value
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now = _now()
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conn = get_conn()
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try:
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conn.execute(
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"""
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INSERT INTO chat_user_preferences (user_id, preferences_json, updated_at)
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VALUES (%s, %s, %s)
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ON CONFLICT(user_id) DO UPDATE SET
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preferences_json=excluded.preferences_json,
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updated_at=excluded.updated_at
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""",
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(int(user_id), _dumps(current), now),
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)
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conn.commit()
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finally:
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conn.close()
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return current
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def create_chat_session(user_id: int, title: str = "", summary: str = "", last_symbol: str = "", last_intent: str = "") -> dict:
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init_chat_tables()
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now = _now()
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conn = get_conn()
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try:
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row = conn.execute(
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"""
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INSERT INTO chat_sessions (user_id, title, summary, memory_json, last_symbol, last_intent, created_at, updated_at)
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VALUES (%s, %s, %s, %s, %s, %s, %s, %s)
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RETURNING *
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""",
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(int(user_id), _normalize_title(title), summary or "", _dumps({}), last_symbol or "", last_intent or "", now, now),
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).fetchone()
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conn.commit()
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finally:
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conn.close()
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return _load_session(row)
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def list_chat_sessions(user_id: int, limit: int = 20, offset: int = 0) -> dict:
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init_chat_tables()
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limit = max(1, min(int(limit or 20), 100))
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offset = max(0, int(offset or 0))
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conn = get_conn()
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try:
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total = conn.execute("SELECT COUNT(*) FROM chat_sessions WHERE user_id=%s AND COALESCE(archived_at, '')=''", (int(user_id),)).fetchone()[0]
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rows = conn.execute(
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"""
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SELECT s.*,
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(SELECT m.content_text FROM chat_messages m WHERE m.session_id=s.id ORDER BY m.id DESC LIMIT 1) AS last_message_text,
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(SELECT m.role FROM chat_messages m WHERE m.session_id=s.id ORDER BY m.id DESC LIMIT 1) AS last_message_role,
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(SELECT m.created_at FROM chat_messages m WHERE m.session_id=s.id ORDER BY m.id DESC LIMIT 1) AS last_message_at,
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(SELECT COUNT(*) FROM chat_messages m WHERE m.session_id=s.id) AS message_count
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FROM chat_sessions s
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WHERE s.user_id=%s AND COALESCE(s.archived_at, '')=''
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ORDER BY s.updated_at DESC, s.id DESC
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LIMIT %s OFFSET %s
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""",
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(int(user_id), limit, offset),
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).fetchall()
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finally:
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conn.close()
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items = []
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for row in rows:
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item = _load_session(row)
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item["last_message_text"] = item.pop("last_message_text", "")
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item["last_message_role"] = item.pop("last_message_role", "")
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item["last_message_at"] = item.pop("last_message_at", "")
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item["message_count"] = int(item.pop("message_count", 0) or 0)
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items.append(item)
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return {
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"items": items,
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"total": int(total or 0),
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"limit": limit,
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"offset": offset,
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"has_more": offset + len(items) < int(total or 0),
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}
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def get_chat_session(session_id: int, user_id: int) -> dict | None:
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init_chat_tables()
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conn = get_conn()
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try:
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row = conn.execute(
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"SELECT * FROM chat_sessions WHERE id=%s AND user_id=%s AND COALESCE(archived_at, '')=''",
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(int(session_id), int(user_id)),
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).fetchone()
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finally:
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conn.close()
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return _load_session(row)
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def update_chat_session(session_id: int, user_id: int, **fields) -> dict | None:
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init_chat_tables()
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session = get_chat_session(session_id, user_id)
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if not session:
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return None
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allowed = {"title", "summary", "memory_json", "last_symbol", "last_intent", "archived_at"}
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updates = {}
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for key, value in fields.items():
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if key not in allowed or value is None:
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continue
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updates[key] = value
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if not updates:
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return session
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updates["updated_at"] = _now()
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if "title" in updates:
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updates["title"] = _normalize_title(updates["title"])
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if "memory_json" in updates and not isinstance(updates["memory_json"], str):
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updates["memory_json"] = _dumps(updates["memory_json"])
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if updates.get("archived_at") == "now":
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updates["archived_at"] = _now()
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sets = ", ".join(f"{key}=%s" for key in updates)
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params = list(updates.values()) + [int(session_id), int(user_id)]
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conn = get_conn()
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try:
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row = conn.execute(
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f"UPDATE chat_sessions SET {sets} WHERE id=%s AND user_id=%s RETURNING *",
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tuple(params),
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).fetchone()
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conn.commit()
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finally:
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conn.close()
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return _load_session(row)
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def list_chat_messages(session_id: int, user_id: int, limit: int = 50, offset: int = 0) -> dict:
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init_chat_tables()
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limit = max(1, min(int(limit or 50), 200))
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offset = max(0, int(offset or 0))
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conn = get_conn()
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try:
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total = conn.execute(
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"SELECT COUNT(*) FROM chat_messages WHERE session_id=%s AND user_id=%s",
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(int(session_id), int(user_id)),
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).fetchone()[0]
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rows = conn.execute(
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"""
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SELECT * FROM chat_messages
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WHERE session_id=%s AND user_id=%s
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ORDER BY id ASC
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LIMIT %s OFFSET %s
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""",
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(int(session_id), int(user_id), limit, offset),
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).fetchall()
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finally:
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conn.close()
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return {
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"items": [_load_message(row) for row in rows],
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"total": int(total or 0),
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"limit": limit,
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"offset": offset,
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"has_more": offset + len(rows) < int(total or 0),
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}
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def append_chat_message(
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session_id: int,
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user_id: int,
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role: str,
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content_text: str = "",
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content_json=None,
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context_json=None,
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intent: str = "",
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symbol: str = "",
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timeframe: str = "",
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model: str = "",
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) -> dict:
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init_chat_tables()
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now = _now()
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conn = get_conn()
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try:
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row = conn.execute(
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"""
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INSERT INTO chat_messages (
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session_id, user_id, role, content_text, content_json, context_json,
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intent, symbol, timeframe, model, created_at
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) VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)
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RETURNING *
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""",
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(
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int(session_id),
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int(user_id),
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str(role or "user"),
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repair_mojibake_text(str(content_text or "")),
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_dumps(content_json or {}),
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_dumps(context_json or {}),
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str(intent or ""),
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str(symbol or ""),
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str(timeframe or ""),
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str(model or ""),
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now,
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),
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).fetchone()
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conn.commit()
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finally:
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conn.close()
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return _load_message(row)
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def bootstrap_chat(user_id: int) -> dict:
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prefs = get_user_preferences(user_id)
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sessions = list_chat_sessions(user_id=user_id, limit=20, offset=0)
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prompts = [
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"分析 BTC/USDT 现在的技术面",
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"解释当前看板里这条推荐为什么是等回踩",
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"看一下市场总览，今天是偏强还是偏弱",
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"这个币的链上异动有哪些",
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"帮我复盘最近一次纸面交易",
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]
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return {
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"preferences": prefs,
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"sessions": sessions,
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"suggested_prompts": prompts,
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}
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__all__ = [
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"append_chat_message",
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"bootstrap_chat",
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"create_chat_session",
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"get_chat_session",
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"get_user_preferences",
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"init_chat_tables",
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"list_chat_messages",
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"list_chat_sessions",
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"update_chat_session",
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"update_user_preferences",
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]
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37
app/db/migrations/0009_chat_assistant.sql
Normal file
37
app/db/migrations/0009_chat_assistant.sql
Normal file
@ -0,0 +1,37 @@
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CREATE TABLE IF NOT EXISTS chat_sessions (
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id BIGSERIAL PRIMARY KEY,
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user_id BIGINT NOT NULL,
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title TEXT NOT NULL DEFAULT '新对话',
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summary TEXT DEFAULT '',
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memory_json TEXT NOT NULL DEFAULT '{}',
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last_symbol TEXT DEFAULT '',
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last_intent TEXT DEFAULT '',
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created_at TEXT NOT NULL,
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updated_at TEXT NOT NULL,
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archived_at TEXT DEFAULT ''
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);
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CREATE INDEX IF NOT EXISTS idx_chat_sessions_user_updated ON chat_sessions(user_id, updated_at DESC);
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CREATE TABLE IF NOT EXISTS chat_messages (
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id BIGSERIAL PRIMARY KEY,
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session_id BIGINT NOT NULL,
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user_id BIGINT NOT NULL,
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role TEXT NOT NULL,
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content_text TEXT DEFAULT '',
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content_json TEXT NOT NULL DEFAULT '{}',
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context_json TEXT NOT NULL DEFAULT '{}',
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intent TEXT DEFAULT '',
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symbol TEXT DEFAULT '',
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timeframe TEXT DEFAULT '',
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model TEXT DEFAULT '',
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created_at TEXT NOT NULL
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);
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CREATE INDEX IF NOT EXISTS idx_chat_messages_session_time ON chat_messages(session_id, created_at ASC);
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CREATE INDEX IF NOT EXISTS idx_chat_messages_user_time ON chat_messages(user_id, created_at DESC);
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CREATE TABLE IF NOT EXISTS chat_user_preferences (
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user_id BIGINT PRIMARY KEY,
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preferences_json TEXT NOT NULL DEFAULT '{}',
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updated_at TEXT NOT NULL
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);
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CREATE INDEX IF NOT EXISTS idx_chat_user_preferences_updated ON chat_user_preferences(updated_at DESC);
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@ -187,6 +187,7 @@ def _push_event_card(event_type: str, trade: dict, result: dict, event_time: str
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if not title:
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return
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card = {
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"metadata": {"source": "paper_trading", "event_type": event_type},
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"config": {"wide_screen_mode": True},
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"header": {
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"template": "blue" if event_type == "open" else ("yellow" if event_type.startswith("trailing") else "red"),
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@ -1,12 +1,9 @@
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"""
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山寨币监控飞书卡片推送模块
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"""Feishu push transport for paper trading only."""
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通过飞书机器人 Webhook 直发，不经过 Hermes Agent 的飞书通道。
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Webhook 支持 v2 interactive cards。
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"""
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from __future__ import annotations
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import os
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import json
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import requests
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from app.config.system_config import notification_config
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@ -29,441 +26,31 @@ def _feishu_settings():
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def push_card(card_content):
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"""通过 webhook 推送飞书交互式卡片"""
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payload = {
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"msg_type": "interactive",
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"card": card_content,
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}
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try:
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settings = _feishu_settings()
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if not settings["enabled"]:
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return False, "feishu notification disabled"
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if not settings["webhook_url"]:
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return False, f"{settings['webhook_env']} not configured"
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r = requests.post(settings["webhook_url"], json=payload, timeout=settings["timeout"])
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result = r.json()
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ok = (r.status_code == 200 and result.get("StatusCode") == 0)
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return ok, result
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except Exception as e:
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return False, str(e)
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"""Paper trading cards only.
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def push_altcoin_burst_alert(symbol, price, signals, entry_plan, sector="", leader_status="", direction="多头启动"):
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Non-paper-trading cards are rejected by construction so no other channel can
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continue using this transport by accident.
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"""
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推荐确认爆发推送 — 只做做多，方向永远多头🟢
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"""
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dir_emoji = "🟢"
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dir_color = "green"
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coin_name = symbol.replace('/USDT', '')
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if not isinstance(card_content, dict):
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return False, {"skipped": True, "reason": "invalid_card"}
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metadata = card_content.get("metadata") or {}
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if str(metadata.get("source") or "").strip().lower() != "paper_trading":
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return False, {"skipped": True, "reason": "paper_trading_only"}
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entry_lines = ""
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if entry_plan:
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rr_ok = "✅" if entry_plan.get("risk_reward_ok") else "❌"
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entry_lines = f"""---
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**入场方案**:
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• 入场价: ${entry_plan['entry_price']}
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• 入场方式: {entry_plan['entry_method']}
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• 止损价: ${entry_plan['stop_loss']} ({entry_plan['stop_pct']}%)
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• 止盈1: ${entry_plan['tp1']} (RR={entry_plan['rr1']} {rr_ok})
|
||||
• 止盈2: ${entry_plan['tp2']} (RR={entry_plan['rr2']})
|
||||
• 当前价: ${entry_plan['current_price']}"""
|
||||
|
||||
sector_line = f"\n**板块**: {sector}" if sector else ""
|
||||
leader_line = f"\n**龙头状态**: {leader_status}" if leader_status else ""
|
||||
signal_lines = "\n".join([f" • {s}" for s in signals])
|
||||
|
||||
card = {
|
||||
"config": {"wide_screen_mode": True},
|
||||
"header": {
|
||||
"template": dir_color,
|
||||
"title": {"tag": "plain_text", "content": f"{dir_emoji} {direction}确认 — {coin_name}"},
|
||||
},
|
||||
"elements": [
|
||||
{
|
||||
"tag": "div",
|
||||
"text": {
|
||||
"tag": "lark_md",
|
||||
"content": f"**方向**: {dir_emoji} {direction}\n**价格**: ${price}{sector_line}{leader_line}\n\n**确认信号**:\n{signal_lines}{entry_lines}",
|
||||
},
|
||||
},
|
||||
{
|
||||
"tag": "action",
|
||||
"actions": [
|
||||
{
|
||||
"tag": "button",
|
||||
"text": {"tag": "plain_text", "content": f"🔥 {symbol.replace('/USDT','')} 爆发确认"},
|
||||
"type": "danger",
|
||||
}
|
||||
],
|
||||
},
|
||||
],
|
||||
}
|
||||
return push_card(card)
|
||||
|
||||
|
||||
def push_recommendation_state_alert(item, title_prefix=None):
|
||||
"""主链路推荐状态推送：只渲染 DB/API 已派生好的状态，不做推荐判断。"""
|
||||
card = build_recommendation_state_card(item, title_prefix=title_prefix)
|
||||
if isinstance(card, tuple):
|
||||
ok, reason = card
|
||||
return ok, reason
|
||||
return push_card(card)
|
||||
|
||||
|
||||
def build_recommendation_state_card(item, title_prefix=None):
|
||||
"""只构建卡片，不负责是否推送、冷却或落库。"""
|
||||
if not item:
|
||||
return True, {"skipped": True, "reason": "empty_mainline_item"}
|
||||
symbol = item.get("symbol", "")
|
||||
coin = symbol.replace("/USDT", "")
|
||||
execution_status = item.get("execution_status", "")
|
||||
action_status = item.get("action_status", "")
|
||||
execution_label = item.get("execution_label", "") or action_status or execution_status
|
||||
if execution_status == "buy_now":
|
||||
color, title = "blue", title_prefix or "入场窗口"
|
||||
elif execution_status == "wait_pullback":
|
||||
color, title = "yellow", title_prefix or "观察池：等回踩"
|
||||
elif execution_status == "observe":
|
||||
color, title = "blue", title_prefix or "观察池更新"
|
||||
else:
|
||||
color, title = "grey", title_prefix or "状态更新"
|
||||
|
||||
entry_plan = item.get("entry_plan") or {}
|
||||
price = item.get("current_price") or item.get("entry_price") or 0
|
||||
entry_ref = entry_plan.get("entry_price") if execution_status == "wait_pullback" else item.get("entry_price")
|
||||
if not entry_ref:
|
||||
entry_ref = item.get("entry_price") or entry_plan.get("entry_price") or 0
|
||||
risk_line = entry_plan.get("stop_loss") or item.get("stop_loss") or 0
|
||||
space_ref = entry_plan.get("tp1") or item.get("tp1") or 0
|
||||
signals = item.get("signals") or []
|
||||
if isinstance(signals, str):
|
||||
try:
|
||||
signals = json.loads(signals)
|
||||
except Exception:
|
||||
signals = [signals]
|
||||
signal_lines = "\n".join([f" • {x}" for x in signals[:5]]) or " • 主链路状态更新"
|
||||
rec_id = item.get("id", "")
|
||||
reason = item.get("execution_reason", "")
|
||||
ver = item.get("strategy_version", "")
|
||||
return {
|
||||
"config": {"wide_screen_mode": True},
|
||||
"header": {
|
||||
"template": color,
|
||||
"title": {"tag": "plain_text", "content": f"{title} — {coin}"},
|
||||
},
|
||||
"elements": [
|
||||
{
|
||||
"tag": "div",
|
||||
"text": {
|
||||
"tag": "lark_md",
|
||||
"content": (
|
||||
f"**币种**: {symbol}\n"
|
||||
f"**主链路状态**: {execution_label}\n"
|
||||
f"**当前价**: ${price}\n"
|
||||
f"**参考价**: ${entry_ref} | **风险边界**: ${risk_line} | **上方空间参考**: ${space_ref}\n"
|
||||
f"**推荐ID**: #{rec_id} | **版本**: {ver}\n"
|
||||
f"**说明**: {reason}\n\n"
|
||||
f"**信号摘要**:\n{signal_lines}"
|
||||
),
|
||||
},
|
||||
}
|
||||
],
|
||||
}
|
||||
|
||||
|
||||
def push_altcoin_accelerating_alert(symbol, price, signals, score, sector="", leader_status="", direction="多头启动"):
|
||||
"""
|
||||
加速信号推送 — 只做做多🟢
|
||||
⚠️ 用户要求：不再推送到飞书，此函数保留但只写日志
|
||||
"""
|
||||
coin_name = symbol.replace('/USDT', '')
|
||||
print(f"[飞书跳过] 🟠 加速信号 — {coin_name} @ ${price} 评分{score}/20 (用户要求不推送)")
|
||||
return True, {"skipped": True, "reason": "用户要求不推送加速信号"}
|
||||
|
||||
|
||||
def push_altcoin_sector_alert(hot_sectors, leaders_info):
|
||||
"""
|
||||
推送板块联动告警
|
||||
⚠️ 用户要求：不再推送到飞书，此函数保留但只写日志
|
||||
"""
|
||||
print(f"[飞书跳过] 🔵 板块联动信号 — {len(hot_sectors)}个板块 (用户要求不推送)")
|
||||
return True, {"skipped": True, "reason": "用户要求不推送板块联动"}
|
||||
|
||||
|
||||
def push_altcoin_tp_sl_alert(symbol, current_price, entry_price, pnl_pct, action_status, signals, stop_loss=0, tp1=0, tp2=0):
|
||||
"""推送交易执行告警 — 可即刻买入 + 🆕v1.7.8 跟踪止盈触发。止盈/止损/衰减只落库展示，不发飞书。"""
|
||||
card = build_trade_action_card(
|
||||
symbol=symbol,
|
||||
current_price=current_price,
|
||||
entry_price=entry_price,
|
||||
pnl_pct=pnl_pct,
|
||||
action_status=action_status,
|
||||
signals=signals,
|
||||
stop_loss=stop_loss,
|
||||
tp1=tp1,
|
||||
tp2=tp2,
|
||||
)
|
||||
if isinstance(card, tuple):
|
||||
ok, reason = card
|
||||
return ok, reason
|
||||
return push_card(card)
|
||||
|
||||
|
||||
def build_trade_action_card(symbol, current_price, entry_price, pnl_pct, action_status, signals, stop_loss=0, tp1=0, tp2=0):
|
||||
"""只构建交易执行卡片，不做冷却判断或落库。"""
|
||||
if action_status not in ("可即刻买入", "跟踪止盈", "移动止盈保护"):
|
||||
print(f"[飞书跳过] {symbol} {action_status} — 用户要求止盈/止损/衰减不推送，只在网站展示")
|
||||
return True, {"skipped": True, "reason": "only_buy_now_and_trailing_stop_push_enabled"}
|
||||
|
||||
if action_status == "移动止盈保护":
|
||||
coin = symbol.replace("/USDT", "")
|
||||
signal_lines = "\n".join([f" • {s}" for s in signals]) or " • 移动止盈保护已启动"
|
||||
trail_info = f"入场${entry_price:.4f} → 当前${current_price:.4f}"
|
||||
if pnl_pct > 0:
|
||||
trail_info += f"\n**当前浮盈: +{pnl_pct:.2f}%**"
|
||||
return {
|
||||
"config": {"wide_screen_mode": True},
|
||||
"header": {
|
||||
"template": "yellow",
|
||||
"title": {"tag": "plain_text", "content": f"🛡️ 移动止盈保护启动 — {coin}"},
|
||||
},
|
||||
"elements": [
|
||||
{
|
||||
"tag": "div",
|
||||
"text": {
|
||||
"tag": "lark_md",
|
||||
"content": f"{trail_info}\n\n**保护详情**:\n{signal_lines}\n\n💡 已进入利润保护阶段，后续跌破保护位会触发跟踪止盈。",
|
||||
},
|
||||
}
|
||||
],
|
||||
}
|
||||
|
||||
# v1.7.8: 跟踪止盈用独立的醒目卡片
|
||||
if action_status == "跟踪止盈":
|
||||
coin = symbol.replace("/USDT", "")
|
||||
signal_lines = "\n".join([f" • {s}" for s in signals])
|
||||
trail_info = f"入场${entry_price:.4f} → 当前${current_price:.4f}"
|
||||
if pnl_pct > 0:
|
||||
trail_info += f"\n**累计盈利: +{pnl_pct:.2f}%** 📈"
|
||||
elif pnl_pct < 0:
|
||||
trail_info += f"\n**保本出场: {pnl_pct:.2f}%**"
|
||||
|
||||
return {
|
||||
"config": {"wide_screen_mode": True},
|
||||
"header": {
|
||||
"template": "red",
|
||||
"title": {"tag": "plain_text", "content": f"🎯 跟踪止盈触发 — {coin}"},
|
||||
},
|
||||
"elements": [
|
||||
{
|
||||
"tag": "div",
|
||||
"text": {
|
||||
"tag": "lark_md",
|
||||
"content": f"{trail_info}\n\n**信号详情**:\n{signal_lines}\n\n💡 跟踪止盈触发，建议立即平仓锁定利润！",
|
||||
},
|
||||
},
|
||||
{
|
||||
"tag": "action",
|
||||
"actions": [
|
||||
{
|
||||
"tag": "button",
|
||||
"text": {"tag": "plain_text", "content": f"🎯 {coin} 跟踪止盈"},
|
||||
"type": "danger",
|
||||
}
|
||||
],
|
||||
},
|
||||
],
|
||||
}
|
||||
|
||||
# 当前只保留入场时机到位推送
|
||||
event_config = {
|
||||
"可即刻买入": ("blue", "🟢", "入场时机到位"),
|
||||
}
|
||||
cfg = event_config.get(action_status, ("blue", "⚠️", action_status))
|
||||
color, emoji, title_prefix = cfg
|
||||
|
||||
coin = symbol.replace("/USDT", "")
|
||||
signal_lines = "\n".join([f" • {s}" for s in signals])
|
||||
|
||||
pnl_emoji = "📈" if pnl_pct > 0 else "📉" if pnl_pct < 0 else "➡️"
|
||||
price_lines = f"**入场价**: ${entry_price} → **当前价**: ${current_price} → **盈亏**: {pnl_emoji} {pnl_pct}%"
|
||||
if stop_loss > 0:
|
||||
price_lines += f"\n**止损**: ${stop_loss}"
|
||||
if tp1 > 0:
|
||||
price_lines += f"\n**止盈1**: ${tp1}"
|
||||
|
||||
return {
|
||||
"config": {"wide_screen_mode": True},
|
||||
"header": {
|
||||
"template": color,
|
||||
"title": {"tag": "plain_text", "content": f"{emoji} {title_prefix} — {coin}"},
|
||||
},
|
||||
"elements": [
|
||||
{
|
||||
"tag": "div",
|
||||
"text": {
|
||||
"tag": "lark_md",
|
||||
"content": f"{price_lines}\n\n**操作建议**: {action_status}\n\n**信号详情**:\n{signal_lines}",
|
||||
},
|
||||
},
|
||||
],
|
||||
}
|
||||
|
||||
|
||||
def push_altcoin_exhaustion_alert(symbol, current_price, pnl_pct, exhaustion):
|
||||
"""
|
||||
推送趋势衰减告警 — ⚠️ 橙色卡片
|
||||
"""
|
||||
coin = symbol.replace("/USDT", "")
|
||||
severity = exhaustion.get("severity", "low")
|
||||
sev_emoji = "⚠️" if severity == "medium" else "🔴"
|
||||
ex_signals = exhaustion.get("signals", [])
|
||||
signal_lines = "\n".join([f" • {s}" for s in ex_signals])
|
||||
|
||||
card = {
|
||||
"config": {"wide_screen_mode": True},
|
||||
"header": {
|
||||
"template": "orange",
|
||||
"title": {"tag": "plain_text", "content": f"{sev_emoji} 趋势衰减 — {coin}"},
|
||||
},
|
||||
"elements": [
|
||||
{
|
||||
"tag": "div",
|
||||
"text": {
|
||||
"tag": "lark_md",
|
||||
"content": f"**当前价**: ${current_price} | **盈亏**: {pnl_pct}%\n\n**衰减信号**:\n{signal_lines}\n\n💡 建议：关注止盈机会，趋势可能即将反转",
|
||||
},
|
||||
},
|
||||
],
|
||||
}
|
||||
return push_card(card)
|
||||
|
||||
|
||||
def push_sentiment_alert(alert):
|
||||
"""
|
||||
推送舆情异动卡片 — 📢 蓝色信息卡
|
||||
alert: {"type": "holding_trending"|"new_trending", "symbol", "name", "trend_rank", "alert"}
|
||||
"""
|
||||
coin = alert["symbol"].replace("/USDT", "")
|
||||
alert_type = alert["type"]
|
||||
emoji = "🔔" if alert_type == "holding_trending" else "🆕"
|
||||
color = "red" if alert_type == "holding_trending" else "blue"
|
||||
|
||||
extra = ""
|
||||
if alert_type == "holding_trending":
|
||||
extra = f"\n⚠️ 持仓币进入热搜，关注价格异动"
|
||||
|
||||
card = {
|
||||
"config": {"wide_screen_mode": True},
|
||||
"header": {
|
||||
"template": color,
|
||||
"title": {"tag": "plain_text", "content": f"{emoji} 舆情异动 — {coin}"},
|
||||
},
|
||||
"elements": [
|
||||
{
|
||||
"tag": "div",
|
||||
"text": {
|
||||
"tag": "lark_md",
|
||||
"content": (
|
||||
f"**{alert['name']}** 进入 CoinGecko Trending #{alert['trend_rank']}\n"
|
||||
f"{alert['alert']}{extra}\n\n"
|
||||
f"💡 消息面热度上升，建议结合技术面判断入场时机"
|
||||
),
|
||||
},
|
||||
},
|
||||
],
|
||||
}
|
||||
return push_card(card)
|
||||
|
||||
|
||||
def push_event_driven_alert(event, result, rec_id=0):
|
||||
"""事件驱动舆情触发选币推送。重大消息触发后，根据技术检查结果分为推荐/观察/风险。"""
|
||||
symbol = event.get("symbol", "")
|
||||
coin = symbol.replace("/USDT", "")
|
||||
decision = result.get("decision", "observe")
|
||||
importance = event.get("importance", "")
|
||||
title = event.get("title", "")
|
||||
source = event.get("source", "")
|
||||
url = event.get("url", "")
|
||||
published_at = event.get("published_at", "")
|
||||
price = result.get("price", 0)
|
||||
score = result.get("score", 0)
|
||||
reason = result.get("reason", "")
|
||||
signals = result.get("signals", [])
|
||||
entry_plan = result.get("entry_plan", {}) or {}
|
||||
|
||||
if decision == "recommend":
|
||||
color, emoji, headline = "red", "🚨", "重大舆情触发：可交易机会"
|
||||
elif decision == "risk":
|
||||
color, emoji, headline = "orange", "⚠️", "重大舆情风险：不建议追"
|
||||
else:
|
||||
color, emoji, headline = "blue", "👀", "重大舆情观察：等待技术确认"
|
||||
|
||||
signal_lines = "\n".join([f" • {s}" for s in signals[:8]])
|
||||
link_line = f"\n**来源链接**: [查看原文]({url})" if url else ""
|
||||
entry_lines = ""
|
||||
if entry_plan:
|
||||
entry_lines = (
|
||||
f"\n---\n**交易计划**:\n"
|
||||
f"• 动作: {entry_plan.get('entry_action', '')}\n"
|
||||
f"• 入场: ${entry_plan.get('entry_price', '')}\n"
|
||||
f"• 止损: ${entry_plan.get('stop_loss', '')} ({entry_plan.get('stop_pct', '')}%)\n"
|
||||
f"• TP1/TP2: ${entry_plan.get('tp1', '')} / ${entry_plan.get('tp2', '')}"
|
||||
)
|
||||
rec_line = f"\n**推荐ID**: #{rec_id}" if rec_id else ""
|
||||
|
||||
card = {
|
||||
"config": {"wide_screen_mode": True},
|
||||
"header": {
|
||||
"template": color,
|
||||
"title": {"tag": "plain_text", "content": f"{emoji} {headline} — {coin}"},
|
||||
},
|
||||
"elements": [
|
||||
{
|
||||
"tag": "div",
|
||||
"text": {
|
||||
"tag": "lark_md",
|
||||
"content": (
|
||||
f"**币种**: {symbol}\n"
|
||||
f"**重要性**: {importance}级 | **来源**: {source}\n"
|
||||
f"**发布时间**: {published_at}\n"
|
||||
f"**消息**: {title}{link_line}\n\n"
|
||||
f"**技术决策**: {reason}\n"
|
||||
f"**当前价**: ${price} | **技术分**: {score}\n"
|
||||
f"{rec_line}\n\n"
|
||||
f"**触发信号**:\n{signal_lines}"
|
||||
f"{entry_lines}"
|
||||
),
|
||||
},
|
||||
},
|
||||
],
|
||||
}
|
||||
return push_card(card)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
# 测试推送
|
||||
settings = _feishu_settings()
|
||||
print(f"Webhook env: {settings['webhook_env']} configured={bool(settings['webhook_url'])}")
|
||||
print("\n测试爆发卡片推送...")
|
||||
ok, result = push_altcoin_burst_alert(
|
||||
"FET/USDT", 2.15,
|
||||
["1H放量突破阻力(2.3倍)", "1H MACD金叉", "1H 均线多头初成", "15min 5阳线+量递增"],
|
||||
{"entry_price": 2.10, "entry_method": "回踩确认", "stop_loss": 1.95,
|
||||
"stop_pct": 3.0, "tp1": 2.55, "tp2": 2.80, "rr1": 3.0, "rr2": 5.0,
|
||||
"risk_reward_ok": True, "current_price": 2.15, "atr_1h": 0.10},
|
||||
sector="AI_DePIN", leader_status="板块龙头(AI_DePIN)",
|
||||
)
|
||||
print(f"爆发卡片: ok={ok}, result={result}")
|
||||
if not settings["enabled"]:
|
||||
return False, "feishu notification disabled"
|
||||
if not settings["webhook_url"]:
|
||||
return False, f"{settings['webhook_env']} not configured"
|
||||
|
||||
print("\n测试加速卡片推送（应被跳过）...")
|
||||
ok2, result2 = push_altcoin_accelerating_alert(
|
||||
"ARB/USDT", 0.125,
|
||||
["4H MACD金叉", "4H RSI拐点(35→52)", "板块联动: Layer2龙头启动"],
|
||||
score=10, sector="Layer2",
|
||||
)
|
||||
print(f"加速卡片: ok={ok2}, result={result2}")
|
||||
payload = {"msg_type": "interactive", "card": card_content}
|
||||
try:
|
||||
resp = requests.post(settings["webhook_url"], json=payload, timeout=settings["timeout"])
|
||||
result = resp.json()
|
||||
ok = resp.status_code == 200 and result.get("StatusCode") == 0
|
||||
return ok, result
|
||||
except Exception as exc:
|
||||
return False, str(exc)
|
||||
|
||||
print("\n测试板块联动推送（应被跳过）...")
|
||||
ok4, result4 = push_altcoin_sector_alert(["AI"], {"AI": {"leader": "FET/USDT", "leader_pct": 12.5, "is_leader_hot": True}})
|
||||
print(f"板块联动: ok={ok4}, result={result4}")
|
||||
|
||||
__all__ = ["push_card"]
|
||||
|
||||
@ -1,298 +0,0 @@
|
||||
"""
|
||||
飞书复盘报告推送模块
|
||||
|
||||
推送三类卡片：
|
||||
1. push_review_report — 策略复盘报告（蓝色主题）
|
||||
2. push_reverse_analysis_report — 逆向分析报告（紫色主题）
|
||||
3. push_rule_update_notification — 新规律通知（绿色主题）
|
||||
|
||||
复用 feishu_push.py 的认证模式（load_feishu_creds → get_token → push_card）
|
||||
"""
|
||||
|
||||
import os
|
||||
import sys
|
||||
import json
|
||||
|
||||
sys.path.insert(0, os.path.dirname(__file__))
|
||||
from app.integrations.feishu_push import push_card
|
||||
|
||||
CHAT_ID = "oc_2c597ad94167102922de142928e2917a"
|
||||
|
||||
|
||||
# ==================== 1. 策略复盘报告 ====================
|
||||
|
||||
def push_review_report(review_results):
|
||||
"""
|
||||
推送策略复盘报告卡片 — 📊 蓝色主题
|
||||
|
||||
Section 1: 推荐命中统计 (hit/fail/flat counts, hit rate %)
|
||||
Section 2: 信号绩效TOP5 (best performing signals)
|
||||
Section 3: 遗漏爆炸 (missed coins, why, what features)
|
||||
Section 4: 权重调整 (weight changes)
|
||||
"""
|
||||
reviews = review_results.get("review_details", [])
|
||||
weight_adj = review_results.get("weight_adjustments", [])
|
||||
missed = review_results.get("missed_explosions", [])
|
||||
|
||||
# Section 1: 命中统计
|
||||
hit_count = sum(1 for r in reviews if r.get("outcome") == "爆发")
|
||||
fail_count = sum(1 for r in reviews if r.get("outcome") == "失败")
|
||||
flat_count = sum(1 for r in reviews if r.get("outcome") == "横盘")
|
||||
total = len(reviews)
|
||||
hit_rate_pct = round(hit_count / total * 100, 1) if total > 0 else 0
|
||||
|
||||
# 命中统计文案
|
||||
hit_emoji = "🔥" if hit_rate_pct >= 50 else "⚠️" if hit_rate_pct >= 30 else "❌"
|
||||
stats_line = (
|
||||
f"本次复盘 **{total}** 条推荐:\n"
|
||||
f" • 爆发(命中): **{hit_count}** ({hit_emoji})\n"
|
||||
f" • 横盘: **{flat_count}**\n"
|
||||
f" • 失败: **{fail_count}**\n"
|
||||
f" • 命中率: **{hit_rate_pct}%**"
|
||||
)
|
||||
|
||||
# Section 2: 信号绩效TOP5
|
||||
# 从review_results中提取信号绩效信息
|
||||
from app.db.altcoin_db import get_signal_weights
|
||||
weights = get_signal_weights()
|
||||
sig_perf_list = sorted(
|
||||
[(sig, data) for sig, data in weights.items() if data.get("total_count", 0) >= 3],
|
||||
key=lambda x: x[1].get("hit_rate", 0),
|
||||
reverse=True,
|
||||
)[:5]
|
||||
|
||||
sig_lines = ""
|
||||
if sig_perf_list:
|
||||
for sig, data in sig_perf_list:
|
||||
hr = data.get("hit_rate", 0)
|
||||
w = data.get("weight", 0)
|
||||
total_n = data.get("total_count", 0)
|
||||
cat = data.get("category", "")
|
||||
emoji = "✅" if hr >= 50 else "⚠️" if hr >= 30 else "❌"
|
||||
sig_lines += f"\n • {emoji} **{sig}**({cat}): 命中率{hr}% | 权重{w} | 样本{total_n}"
|
||||
else:
|
||||
sig_lines = "\n • 样本不足，暂无绩效数据"
|
||||
|
||||
# Section 3: 遗漏爆炸
|
||||
missed_lines = ""
|
||||
if missed:
|
||||
for m in missed[:5]: # 最多展示5只
|
||||
symbol = m.get("symbol", "")
|
||||
gain = m.get("gain_pct", 0)
|
||||
reason = m.get("reason_missed", m.get("reason", ""))
|
||||
features = m.get("features_detected", [])
|
||||
if isinstance(features, str):
|
||||
try:
|
||||
features = json.loads(features)
|
||||
except:
|
||||
features = [features]
|
||||
feat_str = ", ".join(str(f) for f in features[:3]) if features else "无"
|
||||
missed_lines += f"\n • 💥 **{symbol}** 涨{gain}% | 原因: {reason} | 特征: {feat_str}"
|
||||
else:
|
||||
missed_lines = "\n • ✅ 无遗漏爆炸"
|
||||
|
||||
# Section 4: 权重调整
|
||||
adj_lines = ""
|
||||
if weight_adj:
|
||||
for adj in weight_adj:
|
||||
adj_lines += f"\n • {adj}"
|
||||
else:
|
||||
adj_lines = "\n • 无权重调整"
|
||||
|
||||
# 构建卡片
|
||||
card = {
|
||||
"config": {"wide_screen_mode": True},
|
||||
"header": {
|
||||
"template": "blue",
|
||||
"title": {"tag": "plain_text", "content": "📊 山寨币策略复盘报告"},
|
||||
},
|
||||
"elements": [
|
||||
{
|
||||
"tag": "div",
|
||||
"text": {
|
||||
"tag": "lark_md",
|
||||
"content": (
|
||||
f"**=== 推荐命中统计 ===**\n{stats_line}\n\n"
|
||||
f"**=== 信号绩效TOP5 ===**\n{sig_lines}\n\n"
|
||||
f"**=== 遗漏爆炸 ===**\n{missed_lines}\n\n"
|
||||
f"**=== 权重调整 ===**\n{adj_lines}"
|
||||
),
|
||||
},
|
||||
},
|
||||
{
|
||||
"tag": "action",
|
||||
"actions": [
|
||||
{
|
||||
"tag": "button",
|
||||
"text": {"tag": "plain_text", "content": f"📊 命中率{hit_rate_pct}%"},
|
||||
"type": "primary" if hit_rate_pct >= 50 else "warning" if hit_rate_pct >= 30 else "danger",
|
||||
}
|
||||
],
|
||||
},
|
||||
],
|
||||
}
|
||||
return push_card(card)
|
||||
|
||||
|
||||
# ==================== 2. 逆向分析报告 ====================
|
||||
|
||||
def push_reverse_analysis_report(reverse_results):
|
||||
"""
|
||||
推送逆向分析报告卡片 — 🔍 紫色主题
|
||||
|
||||
Section 1: 今日涨幅榜TOP10 (symbol, gain%, sector)
|
||||
Section 2: 起爆前共性特征 (pattern summary with percentages)
|
||||
Section 3: 新发现规律 (any new rules)
|
||||
"""
|
||||
top_gainers = reverse_results.get("top_gainers", [])
|
||||
pattern_summary = reverse_results.get("pattern_summary", [])
|
||||
new_rules = reverse_results.get("new_rules", [])
|
||||
total_unrecommended = reverse_results.get("total_unrecommended", 0)
|
||||
total_analyzed = reverse_results.get("total_analyzed", 0)
|
||||
|
||||
# Section 1: 涨幅榜TOP10
|
||||
gainer_lines = ""
|
||||
for i, g in enumerate(top_gainers[:10], 1):
|
||||
symbol = g.get("symbol", "").replace("/USDT", "")
|
||||
gain = g.get("gain_pct", 0)
|
||||
sector = g.get("sector", [])
|
||||
sector_str = sector[0] if isinstance(sector, list) and sector else (sector if sector else "未知")
|
||||
volume = g.get("volume_24h", 0)
|
||||
vol_str = f"${volume / 1e6:.1f}M" if volume > 0 else ""
|
||||
gainer_lines += f"\n {i}. **{symbol}** +{gain}% | {sector_str} | {vol_str}"
|
||||
|
||||
if not gainer_lines:
|
||||
gainer_lines = "\n • 今日无明显涨幅"
|
||||
|
||||
# Section 2: 起爆前共性特征
|
||||
pattern_lines = ""
|
||||
for p in pattern_summary[:8]: # 最多展示8个特征
|
||||
label = p.get("label", p.get("feature", ""))
|
||||
pct = p.get("percentage", 0)
|
||||
count = p.get("count", 0)
|
||||
total = p.get("total", 0)
|
||||
bar = "█" * int(pct / 10) + "░" * (10 - int(pct / 10))
|
||||
emoji = "🔥" if pct >= 60 else "✅" if pct >= 40 else "⚠️" if pct >= 20 else "❌"
|
||||
pattern_lines += f"\n • {emoji} **{label}**: {pct}%({count}/{total}) {bar}"
|
||||
|
||||
if not pattern_lines:
|
||||
pattern_lines = "\n • 分析样本不足"
|
||||
|
||||
# Section 3: 新发现规律
|
||||
rule_lines = ""
|
||||
if new_rules:
|
||||
for r in new_rules:
|
||||
rule_id = r.get("rule_id", "")
|
||||
desc = r.get("description", "")
|
||||
score_adj = r.get("score_adjust", 0)
|
||||
rule_type = r.get("type", "")
|
||||
rule_lines += f"\n • 🧠 **{rule_id}**: {desc} → 评分{score_adj}({rule_type})"
|
||||
else:
|
||||
rule_lines = "\n • 暂无新规律达到显著性阈值"
|
||||
|
||||
# 分析概况
|
||||
overview = (
|
||||
f"涨幅榜共{len(top_gainers)}只 ≥10%\n"
|
||||
f"未被推荐: {total_unrecommended}只\n"
|
||||
f"已做PA分析: {total_analyzed}只"
|
||||
)
|
||||
|
||||
# 构建卡片（紫色主题用 "violet" — 飞书卡片没有purple，用indigo近似）
|
||||
card = {
|
||||
"config": {"wide_screen_mode": True},
|
||||
"header": {
|
||||
"template": "indigo",
|
||||
"title": {"tag": "plain_text", "content": "🔍 逆向分析报告 — 涨幅榜复盘"},
|
||||
},
|
||||
"elements": [
|
||||
{
|
||||
"tag": "div",
|
||||
"text": {
|
||||
"tag": "lark_md",
|
||||
"content": (
|
||||
f"**{overview}**\n\n"
|
||||
f"**=== 今日涨幅榜TOP10 ===**\n{gainer_lines}\n\n"
|
||||
f"**=== 起爆前共性特征 ===**\n{pattern_lines}\n\n"
|
||||
f"**=== 新发现规律 ===**\n{rule_lines}"
|
||||
),
|
||||
},
|
||||
},
|
||||
{
|
||||
"tag": "action",
|
||||
"actions": [
|
||||
{
|
||||
"tag": "button",
|
||||
"text": {"tag": "plain_text", "content": f"🔍 分析{total_analyzed}只暴涨币"},
|
||||
"type": "primary",
|
||||
}
|
||||
],
|
||||
},
|
||||
],
|
||||
}
|
||||
return push_card(card)
|
||||
|
||||
|
||||
# ==================== 3. 新规律通知 ====================
|
||||
|
||||
def push_rule_update_notification(rule_id, description, status="候选规则，未生效"):
|
||||
"""
|
||||
推送新规律学习通知 — 🧠 绿色主题
|
||||
简洁卡片，告知策略自动迭代
|
||||
"""
|
||||
card = {
|
||||
"config": {"wide_screen_mode": True},
|
||||
"header": {
|
||||
"template": "green",
|
||||
"title": {"tag": "plain_text", "content": "🧠 策略自学习 — 候选规则发现"},
|
||||
},
|
||||
"elements": [
|
||||
{
|
||||
"tag": "div",
|
||||
"text": {
|
||||
"tag": "lark_md",
|
||||
"content": (
|
||||
f"规则ID: **{rule_id}**\n\n"
|
||||
f"状态: **{status}**\n\n"
|
||||
f"描述: {description}\n\n"
|
||||
f"说明: 该规则仅进入候选池/灰度评估，未通过发布闸门前不会写入正式规则库，也不会影响下次选币。"
|
||||
),
|
||||
},
|
||||
},
|
||||
{
|
||||
"tag": "action",
|
||||
"actions": [
|
||||
{
|
||||
"tag": "button",
|
||||
"text": {"tag": "plain_text", "content": f"🧠 {rule_id}"},
|
||||
"type": "primary",
|
||||
}
|
||||
],
|
||||
},
|
||||
],
|
||||
}
|
||||
return push_card(card)
|
||||
|
||||
|
||||
# ==================== 测试 ====================
|
||||
|
||||
if __name__ == "__main__":
|
||||
print("测试复盘报告推送...")
|
||||
|
||||
# 测试review report
|
||||
test_review = {
|
||||
"review_details": [
|
||||
{"symbol": "FET/USDT", "outcome": "爆发", "pnl_48h": 12.5},
|
||||
{"symbol": "ARB/USDT", "outcome": "横盘", "pnl_48h": 1.2},
|
||||
{"symbol": "PEPE/USDT", "outcome": "失败", "pnl_48h": -4.5},
|
||||
],
|
||||
"weight_adjustments": ["量价齐飞: 3→4.0 (命中率67%)"],
|
||||
"missed_explosions": [
|
||||
{"symbol": "INJ/USDT", "gain_pct": 25, "reason_missed": "细筛淘汰(score=4)", "features_detected": ["ignition_point", "Q7_zone"]},
|
||||
],
|
||||
}
|
||||
ok1, r1 = push_review_report(test_review)
|
||||
print(f"复盘报告: ok={ok1}")
|
||||
|
||||
# 测试rule notification
|
||||
ok2, r2 = push_rule_update_notification("rule_20260429_001", "涨幅榜60%有起爆点 → 起爆点是爆发前必现信号")
|
||||
print(f"规律通知: ok={ok2}")
|
||||
@ -1,43 +0,0 @@
|
||||
"""Push orchestration helpers.
|
||||
|
||||
Separates eligibility / cooldown decisions from payload rendering and transport.
|
||||
"""
|
||||
|
||||
from app.db.recommendation_queries import log_push, should_push
|
||||
from app.integrations.feishu_push import build_trade_action_card, push_card
|
||||
|
||||
|
||||
def push_mainline_state_update(symbol: str, rec_id: int, mainline_item: dict, title_prefix: str | None = None, entry_push_type: str = "entry", watch_push_type: str = "watch_pool") -> bool:
|
||||
"""主链路状态只记录，不再飞书推送。"""
|
||||
status = mainline_item.get("execution_status") if mainline_item else "missing"
|
||||
action = mainline_item.get("action_status", "") if mainline_item else ""
|
||||
print(f"[push] skip {symbol}: mainline notifications disabled (status={status}, action={action})")
|
||||
return False
|
||||
|
||||
|
||||
def push_trade_action_update(symbol: str, rec_id: int, state_decision: dict, final_action: str, push_type: str = "entry") -> bool:
|
||||
if not state_decision.get("push_required"):
|
||||
return False
|
||||
if not should_push(symbol, push_type, final_action):
|
||||
print(f"⏭ 跳过推送({symbol}): {push_type}/{final_action} 12h冷却中")
|
||||
return False
|
||||
card = build_trade_action_card(
|
||||
state_decision["push_symbol"],
|
||||
state_decision["push_current_price"],
|
||||
state_decision["push_entry_price"],
|
||||
state_decision["push_pnl_pct"],
|
||||
final_action,
|
||||
state_decision.get("push_signals", []),
|
||||
state_decision.get("stop_loss", 0),
|
||||
state_decision.get("tp1", 0),
|
||||
state_decision.get("tp2", 0),
|
||||
)
|
||||
if isinstance(card, tuple):
|
||||
ok, resp = card
|
||||
else:
|
||||
ok, resp = push_card(card)
|
||||
if ok:
|
||||
log_push(symbol, push_type, final_action, rec_id=rec_id)
|
||||
return True
|
||||
print(f"飞书推送失败({symbol}): {resp}")
|
||||
return False
|
||||
@ -29,9 +29,8 @@ from app.core.sector_map import get_burst_threshold, is_meme_coin, get_sector_fo
|
||||
from app.db.altcoin_db import (
|
||||
init_db, expire_old_states, expire_old_recommendations,
|
||||
get_candidates_for_confirm, update_state, get_conn, create_recommendation, log_screening,
|
||||
log_cron_run, update_latest_price_cache, get_recommendation_for_push,
|
||||
log_cron_run, update_latest_price_cache,
|
||||
)
|
||||
from app.integrations.push_orchestrator import push_mainline_state_update
|
||||
from app.config.config_loader import (
|
||||
get_strategy_direction,
|
||||
vp_fly_params,
|
||||
@ -1334,8 +1333,6 @@ def main(compact: bool = False):
|
||||
update_latest_price_cache(symbol, result["price"], updated_at=datetime.now().isoformat(), source="confirm")
|
||||
result["rec_id"] = rec_id
|
||||
|
||||
mainline_item = get_recommendation_for_push(rec_id)
|
||||
push_mainline_state_update(symbol, rec_id, mainline_item)
|
||||
else:
|
||||
cand_detail = json.loads(cand.get("detail_json", "{}"))
|
||||
log_screening(
|
||||
|
||||
755
app/services/chat_assistant.py
Normal file
755
app/services/chat_assistant.py
Normal file
@ -0,0 +1,755 @@
|
||||
"""Conversational crypto research assistant.
|
||||
|
||||
The assistant is read-only: it can inspect AlphaX data and Binance OHLCV, but
|
||||
it never mutates recommendations, strategy state, or trading state.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import math
|
||||
import os
|
||||
import re
|
||||
from datetime import datetime, timedelta
|
||||
import ccxt
|
||||
import pandas as pd
|
||||
import requests
|
||||
|
||||
from app.config.system_config import llm_config
|
||||
from app.core.pa_engine import calc_atr, full_pa_analysis
|
||||
from app.db import chat_assistant_db
|
||||
from app.db.analytics import get_pipeline_runs
|
||||
from app.db.llm_insights import compute_input_hash, repair_mojibake_json, repair_mojibake_text
|
||||
from app.db.onchain_db import get_onchain_token_detail, get_onchain_overview
|
||||
from app.db.paper_trading import get_paper_trading_summary, list_paper_trade_events, list_paper_trades
|
||||
from app.db.schema import get_conn
|
||||
from app.services.llm_insights import get_llm_params
|
||||
from app.services.market_overview import get_crypto_market_overview
|
||||
|
||||
|
||||
exchange = ccxt.binance({"enableRateLimit": True})
|
||||
|
||||
CRYPTO_TERMS = {
|
||||
"btc", "eth", "bnb", "sol", "xrp", "doge", "ada", "sui", "link", "qnt",
|
||||
"币", "加密", "crypto", "usdt", "binance", "行情", "链上", "舆情", "推荐", "复盘",
|
||||
"k线", "k 线", "技术面", "止盈", "止损", "纸面", "模拟交易", "仓位", "山寨",
|
||||
}
|
||||
|
||||
INTENT_LABELS = {
|
||||
"coin_analysis": "单币分析",
|
||||
"market_overview": "市场问答",
|
||||
"recommendation_explain": "推荐解释",
|
||||
"sentiment": "舆情解读",
|
||||
"onchain": "链上异动",
|
||||
"review": "复盘查询",
|
||||
"paper_trading": "模拟交易",
|
||||
"help": "帮助",
|
||||
"unsupported": "范围外",
|
||||
}
|
||||
|
||||
TIMEFRAMES = ("15m", "1h", "4h", "1d")
|
||||
|
||||
|
||||
def _now() -> str:
|
||||
return datetime.now().isoformat(timespec="seconds")
|
||||
|
||||
|
||||
def _safe_float(value, default=0.0) -> float:
|
||||
try:
|
||||
if value is None or value == "":
|
||||
return default
|
||||
return float(value)
|
||||
except Exception:
|
||||
return default
|
||||
|
||||
|
||||
def _safe_int(value, default=0) -> int:
|
||||
try:
|
||||
return int(value or 0)
|
||||
except Exception:
|
||||
return default
|
||||
|
||||
|
||||
def _json(value):
|
||||
return json.dumps(value or {}, ensure_ascii=False, sort_keys=True, default=str)
|
||||
|
||||
|
||||
def _compact_json(value, max_len=18000):
|
||||
text = _json(value)
|
||||
if len(text) <= max_len:
|
||||
return text
|
||||
return text[:max_len] + "...[truncated]"
|
||||
|
||||
|
||||
def _normalize_symbol(value: str) -> str:
|
||||
text = str(value or "").strip().upper()
|
||||
text = text.replace(" ", "")
|
||||
if not text:
|
||||
return ""
|
||||
if "/" in text:
|
||||
base, quote = text.split("/", 1)
|
||||
quote = quote or "USDT"
|
||||
return f"{base}/USDT" if quote in ("USD", "USDT", "BUSD", "FDUSD") else f"{base}/{quote}"
|
||||
text = re.sub(r"[^A-Z0-9]", "", text)
|
||||
if text.endswith("USDT") and len(text) > 4:
|
||||
text = text[:-4]
|
||||
return f"{text}/USDT" if text else ""
|
||||
|
||||
|
||||
def extract_symbol(message: str, session=None, preferences=None) -> str:
|
||||
text = str(message or "")
|
||||
patterns = [
|
||||
r"\b([A-Z0-9]{2,15})\s*/\s*USDT\b",
|
||||
r"\b([A-Z0-9]{2,15})USDT\b",
|
||||
r"\$([A-Z][A-Z0-9]{1,12})\b",
|
||||
]
|
||||
for pat in patterns:
|
||||
m = re.search(pat, text, flags=re.I)
|
||||
if m:
|
||||
return _normalize_symbol(m.group(1))
|
||||
|
||||
upper_tokens = re.findall(r"(?<![A-Za-z0-9])([A-Z][A-Z0-9]{1,12})(?![A-Za-z0-9])", text)
|
||||
skip = {"AI", "API", "LLM", "K", "PA", "TP", "SL", "USDT", "USD", "BTCUSDT", "ETHUSDT"}
|
||||
for token in upper_tokens:
|
||||
if token.upper() not in skip:
|
||||
return _normalize_symbol(token)
|
||||
|
||||
for source in (session or {}, preferences or {}):
|
||||
value = source.get("last_symbol") if isinstance(source, dict) else ""
|
||||
if value:
|
||||
return _normalize_symbol(value)
|
||||
preferred = (preferences or {}).get("preferred_symbols") or []
|
||||
return _normalize_symbol(preferred[-1]) if preferred else ""
|
||||
|
||||
|
||||
def detect_intent(message: str, symbol: str = "") -> str:
|
||||
text = str(message or "").lower()
|
||||
if not _is_crypto_question(text, symbol):
|
||||
return "unsupported"
|
||||
if any(k in text for k in ("怎么用", "能做什么", "帮助", "help", "问什么")):
|
||||
return "help"
|
||||
if any(k in text for k in ("模拟交易", "paper", "开仓", "平仓", "持仓", "收益", "仓位")):
|
||||
return "paper_trading"
|
||||
if any(k in text for k in ("链上", "onchain", "鲸鱼", "转账", "dex", "流动性", "合约")):
|
||||
return "onchain"
|
||||
if any(k in text for k in ("舆情", "新闻", "消息", "情绪", "热点", "叙事", "ai 舆情")):
|
||||
return "sentiment"
|
||||
if any(k in text for k in ("复盘", "历史", "亏损", "失败", "胜率", "漏选")):
|
||||
return "review"
|
||||
if any(k in text for k in ("推荐", "看板", "为什么", "等回踩", "可买", "观察", "信号")) and symbol:
|
||||
return "recommendation_explain"
|
||||
if any(k in text for k in ("市场", "大盘", "全市场", "资金费率", "涨幅榜", "广度")) and not symbol:
|
||||
return "market_overview"
|
||||
if symbol:
|
||||
return "coin_analysis"
|
||||
return "market_overview"
|
||||
|
||||
|
||||
def _is_crypto_question(text: str, symbol: str = "") -> bool:
|
||||
if symbol:
|
||||
return True
|
||||
return any(term in text for term in CRYPTO_TERMS)
|
||||
|
||||
|
||||
def _binance_symbol_id(symbol: str) -> str:
|
||||
return _normalize_symbol(symbol).replace("/", "")
|
||||
|
||||
|
||||
def fetch_binance_klines(symbol: str, timeframe: str, limit: int = 160):
|
||||
symbol = _normalize_symbol(symbol)
|
||||
try:
|
||||
ohlcv = exchange.fetch_ohlcv(symbol, timeframe, limit=limit)
|
||||
except Exception:
|
||||
return None
|
||||
if not ohlcv:
|
||||
return None
|
||||
df = pd.DataFrame(ohlcv, columns=["timestamp", "open", "high", "low", "close", "volume"])
|
||||
df["timestamp"] = pd.to_datetime(df["timestamp"], unit="ms")
|
||||
return df
|
||||
|
||||
|
||||
def _ma(series, n):
|
||||
if series is None or len(series) < n:
|
||||
return 0.0
|
||||
value = series.rolling(n).mean().iloc[-1]
|
||||
return 0.0 if pd.isna(value) else float(value)
|
||||
|
||||
|
||||
def _rsi(closes, period=14):
|
||||
if closes is None or len(closes) < period + 2:
|
||||
return 0.0
|
||||
delta = closes.diff()
|
||||
gain = delta.clip(lower=0).rolling(period).mean()
|
||||
loss = (-delta.clip(upper=0)).rolling(period).mean()
|
||||
rs = gain / loss.replace(0, math.nan)
|
||||
value = 100 - (100 / (1 + rs.iloc[-1]))
|
||||
return 50.0 if pd.isna(value) else round(float(value), 2)
|
||||
|
||||
|
||||
def _support_resistance(df):
|
||||
if df is None or len(df) < 20:
|
||||
return {"support": 0, "resistance": 0, "range_position_pct": 0}
|
||||
recent = df.tail(48 if len(df) >= 48 else len(df))
|
||||
support = float(recent["low"].min())
|
||||
resistance = float(recent["high"].max())
|
||||
price = float(df["close"].iloc[-1])
|
||||
position = (price - support) / (resistance - support) * 100 if resistance > support else 50
|
||||
return {
|
||||
"support": round(support, 8),
|
||||
"resistance": round(resistance, 8),
|
||||
"range_position_pct": round(max(0, min(100, position)), 2),
|
||||
}
|
||||
|
||||
|
||||
def _technical_summary_for_df(df, timeframe: str) -> dict:
|
||||
if df is None or len(df) < 30:
|
||||
return {"timeframe": timeframe, "available": False, "reason": "kline_unavailable"}
|
||||
closes = df["close"].astype(float)
|
||||
volumes = df["volume"].astype(float)
|
||||
price = float(closes.iloc[-1])
|
||||
prev = float(closes.iloc[-2]) if len(closes) >= 2 else price
|
||||
change = ((price / prev) - 1) * 100 if prev > 0 else 0
|
||||
change_window = ((price / float(closes.iloc[0])) - 1) * 100 if float(closes.iloc[0]) > 0 else 0
|
||||
ma20 = _ma(closes, 20)
|
||||
ma60 = _ma(closes, 60)
|
||||
avg_vol20 = _ma(volumes, 20)
|
||||
vol_ratio = float(volumes.iloc[-1]) / avg_vol20 if avg_vol20 > 0 else 0
|
||||
atr = calc_atr(df, 14)
|
||||
pa = full_pa_analysis(df, timeframe)
|
||||
sr = _support_resistance(df)
|
||||
last_candle = {
|
||||
"open": round(float(df["open"].iloc[-1]), 8),
|
||||
"high": round(float(df["high"].iloc[-1]), 8),
|
||||
"low": round(float(df["low"].iloc[-1]), 8),
|
||||
"close": round(price, 8),
|
||||
"volume": round(float(volumes.iloc[-1]), 4),
|
||||
"is_bullish": price >= float(df["open"].iloc[-1]),
|
||||
}
|
||||
trend = "sideways"
|
||||
if ma20 > 0 and ma60 > 0 and price > ma20 > ma60:
|
||||
trend = "uptrend"
|
||||
elif ma20 > 0 and ma60 > 0 and price < ma20 < ma60:
|
||||
trend = "downtrend"
|
||||
elif ma20 > 0 and price > ma20:
|
||||
trend = "rebound"
|
||||
elif ma20 > 0 and price < ma20:
|
||||
trend = "weak"
|
||||
return {
|
||||
"timeframe": timeframe,
|
||||
"available": True,
|
||||
"last_time": str(df["timestamp"].iloc[-1]),
|
||||
"price": round(price, 8),
|
||||
"change_last_bar_pct": round(change, 2),
|
||||
"change_window_pct": round(change_window, 2),
|
||||
"trend": trend,
|
||||
"ma20": round(ma20, 8),
|
||||
"ma60": round(ma60, 8),
|
||||
"rsi14": _rsi(closes, 14),
|
||||
"atr14": round(float(atr or 0), 8),
|
||||
"volume_ratio_20": round(vol_ratio, 2),
|
||||
"support": sr["support"],
|
||||
"resistance": sr["resistance"],
|
||||
"range_position_pct": sr["range_position_pct"],
|
||||
"last_candle": last_candle,
|
||||
"pa": {
|
||||
"dynamic_count_recent": sum(1 for x in (pa.get("candles_class") or [])[-10:] if x.get("type") == "dynamic"),
|
||||
"static_count_recent": sum(1 for x in (pa.get("candles_class") or [])[-10:] if x.get("type") == "static"),
|
||||
"top_zones": (pa.get("zones") or [])[:3],
|
||||
"continuous_k": (pa.get("continuous_k") or [])[-3:],
|
||||
"ignition_points": (pa.get("ignition_points") or [])[-3:],
|
||||
"trend_exhaustion": pa.get("trend_exhaustion") or {},
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def analyze_symbol_technicals(symbol: str) -> dict:
|
||||
symbol = _normalize_symbol(symbol)
|
||||
result = {
|
||||
"symbol": symbol,
|
||||
"source": "binance_spot",
|
||||
"binance_tradable": False,
|
||||
"timeframes": {},
|
||||
"summary": {},
|
||||
"errors": [],
|
||||
}
|
||||
for tf in TIMEFRAMES:
|
||||
df = fetch_binance_klines(symbol, tf, limit=180 if tf == "1d" else 160)
|
||||
if df is None or len(df) < 30:
|
||||
result["timeframes"][tf] = {"timeframe": tf, "available": False, "reason": "binance_kline_unavailable"}
|
||||
result["errors"].append(f"{tf}: kline_unavailable")
|
||||
continue
|
||||
result["binance_tradable"] = True
|
||||
result["timeframes"][tf] = _technical_summary_for_df(df, tf)
|
||||
|
||||
available = [x for x in result["timeframes"].values() if x.get("available")]
|
||||
if not available:
|
||||
result["summary"] = {"stance": "no_data", "headline": "未拿到 Binance K 线，无法做实时技术面判断。", "risk_level": "unknown"}
|
||||
return result
|
||||
|
||||
h1 = result["timeframes"].get("1h") or {}
|
||||
h4 = result["timeframes"].get("4h") or {}
|
||||
d1 = result["timeframes"].get("1d") or {}
|
||||
bullish = sum(1 for x in available if x.get("trend") in ("uptrend", "rebound") and _safe_float(x.get("volume_ratio_20")) >= 0.8)
|
||||
bearish = sum(1 for x in available if x.get("trend") in ("downtrend", "weak") and _safe_float(x.get("change_window_pct")) < 0)
|
||||
chase_risk = any(_safe_float(x.get("range_position_pct")) >= 85 and _safe_float(x.get("rsi14")) >= 70 for x in (h1, h4, d1) if x.get("available"))
|
||||
exhaustion = (h1.get("pa") or {}).get("trend_exhaustion") or {}
|
||||
if bullish >= 3 and not chase_risk:
|
||||
stance = "bullish_watch"
|
||||
headline = "多周期结构偏强，但仍需要结合入场窗口和风险收益比。"
|
||||
elif chase_risk:
|
||||
stance = "chase_risk"
|
||||
headline = "价格处在区间高位或 RSI 偏热，追高风险需要优先处理。"
|
||||
elif bearish >= 2 or exhaustion.get("exhausted"):
|
||||
stance = "weak_or_exhausted"
|
||||
headline = "短线结构偏弱或出现衰减，不适合直接按强势机会处理。"
|
||||
else:
|
||||
stance = "neutral"
|
||||
headline = "结构还不够一致，适合观察等待更清晰触发。"
|
||||
result["summary"] = {
|
||||
"stance": stance,
|
||||
"headline": headline,
|
||||
"risk_level": "high" if chase_risk or exhaustion.get("severity") == "high" else "medium" if bearish else "normal",
|
||||
"bullish_timeframe_count": bullish,
|
||||
"bearish_timeframe_count": bearish,
|
||||
"chase_risk": chase_risk,
|
||||
"latest_price": h1.get("price") or available[0].get("price"),
|
||||
}
|
||||
return result
|
||||
|
||||
|
||||
def _latest_recommendations(symbol: str = "", limit=5):
|
||||
conn = get_conn()
|
||||
params = []
|
||||
where = "1=1"
|
||||
if symbol:
|
||||
where += " AND symbol=%s"
|
||||
params.append(_normalize_symbol(symbol))
|
||||
rows = conn.execute(
|
||||
f"""
|
||||
SELECT * FROM recommendation
|
||||
WHERE {where}
|
||||
ORDER BY id DESC
|
||||
LIMIT %s
|
||||
""",
|
||||
tuple(params + [int(limit)]),
|
||||
).fetchall()
|
||||
conn.close()
|
||||
items = []
|
||||
from app.db.altcoin_db import _derive_execution_fields
|
||||
|
||||
for row in rows:
|
||||
item = _derive_execution_fields(dict(row))
|
||||
for key in ("market_context_json", "derivatives_context_json", "sector_context_json", "entry_plan_json", "signal_codes_json", "signal_labels_json"):
|
||||
value = item.get(key)
|
||||
if isinstance(value, str):
|
||||
try:
|
||||
if value:
|
||||
parsed = json.loads(value)
|
||||
elif key.endswith("context_json") or key == "entry_plan_json":
|
||||
parsed = {}
|
||||
else:
|
||||
parsed = []
|
||||
item[key.replace("_json", "")] = parsed
|
||||
except Exception:
|
||||
pass
|
||||
items.append(item)
|
||||
return items
|
||||
|
||||
|
||||
def _sentiment_context(symbol: str = "", limit=8):
|
||||
conn = get_conn()
|
||||
params = []
|
||||
where = "detected_at >= %s"
|
||||
params.append((datetime.now() - timedelta(hours=72)).isoformat())
|
||||
if symbol:
|
||||
where += " AND symbol=%s"
|
||||
params.append(_normalize_symbol(symbol))
|
||||
rows = conn.execute(
|
||||
f"""
|
||||
SELECT id, source, symbol, title, url, published_at, detected_at, importance, event_type, decision, tech_score, rec_id
|
||||
FROM event_news
|
||||
WHERE {where}
|
||||
ORDER BY detected_at DESC, id DESC
|
||||
LIMIT %s
|
||||
""",
|
||||
tuple(params + [int(limit)]),
|
||||
).fetchall()
|
||||
conn.close()
|
||||
return [dict(row) for row in rows]
|
||||
|
||||
|
||||
def _review_context(symbol: str = "", limit=8):
|
||||
conn = get_conn()
|
||||
params = []
|
||||
where = "1=1"
|
||||
if symbol:
|
||||
where += " AND rl.symbol=%s"
|
||||
params.append(_normalize_symbol(symbol))
|
||||
rows = conn.execute(
|
||||
f"""
|
||||
SELECT rl.*, r.execution_status, r.display_bucket, r.action_status, r.entry_triggered
|
||||
FROM review_log rl
|
||||
LEFT JOIN recommendation r ON r.id=rl.rec_id
|
||||
WHERE {where}
|
||||
ORDER BY rl.review_time DESC, rl.id DESC
|
||||
LIMIT %s
|
||||
""",
|
||||
tuple(params + [int(limit)]),
|
||||
).fetchall()
|
||||
conn.close()
|
||||
return [dict(row) for row in rows]
|
||||
|
||||
|
||||
def _paper_context(symbol: str = ""):
|
||||
if symbol:
|
||||
trades = list_paper_trades(limit=10, status="")
|
||||
symbol_norm = _normalize_symbol(symbol)
|
||||
items = [x for x in trades.get("items", []) if x.get("symbol") == symbol_norm][:5]
|
||||
events = list_paper_trade_events(limit=20, symbol=symbol_norm)
|
||||
return {"trades": items, "events": events.get("items", [])}
|
||||
return {
|
||||
"summary": get_paper_trading_summary(days=30),
|
||||
"trades": list_paper_trades(limit=5).get("items", []),
|
||||
"events": list_paper_trade_events(limit=8).get("items", []),
|
||||
}
|
||||
|
||||
|
||||
def _market_context():
|
||||
try:
|
||||
market = get_crypto_market_overview()
|
||||
except Exception as exc:
|
||||
market = {"error": str(exc)[:300]}
|
||||
try:
|
||||
onchain = get_onchain_overview(hours=24)
|
||||
except Exception:
|
||||
onchain = {}
|
||||
try:
|
||||
from app.services.llm_insights import get_latest_sentiment_batch_analysis
|
||||
|
||||
sentiment = get_latest_sentiment_batch_analysis() or {}
|
||||
except Exception:
|
||||
sentiment = {}
|
||||
return {"market": market, "onchain": onchain, "ai_sentiment": sentiment}
|
||||
|
||||
|
||||
def build_context(intent: str, message: str, symbol: str, preferences=None) -> dict:
|
||||
symbol = _normalize_symbol(symbol)
|
||||
ctx = {
|
||||
"intent": intent,
|
||||
"intent_label": INTENT_LABELS.get(intent, intent),
|
||||
"symbol": symbol,
|
||||
"generated_at": _now(),
|
||||
"preferences": preferences or {},
|
||||
"sources": [],
|
||||
}
|
||||
if intent == "unsupported":
|
||||
return ctx
|
||||
if intent in ("coin_analysis", "recommendation_explain", "onchain", "sentiment") and symbol:
|
||||
ctx["technicals"] = analyze_symbol_technicals(symbol)
|
||||
ctx["recommendations"] = _latest_recommendations(symbol=symbol, limit=5)
|
||||
ctx["sentiment_events"] = _sentiment_context(symbol=symbol, limit=8)
|
||||
try:
|
||||
ctx["onchain"] = get_onchain_token_detail(symbol=symbol, hours=168)
|
||||
except Exception as exc:
|
||||
ctx["onchain"] = {"error": str(exc)[:200]}
|
||||
ctx["reviews"] = _review_context(symbol=symbol, limit=8)
|
||||
ctx["paper"] = _paper_context(symbol=symbol)
|
||||
ctx["sources"] = ["binance_klines", "recommendation", "event_news", "onchain", "review_log", "paper_trading"]
|
||||
elif intent == "market_overview":
|
||||
ctx.update(_market_context())
|
||||
ctx["pipeline"] = get_pipeline_runs(limit=5, hours=24, offset=0)
|
||||
ctx["sources"] = ["market_overview", "onchain_overview", "llm_sentiment", "pipeline_runs"]
|
||||
elif intent == "paper_trading":
|
||||
ctx["paper"] = _paper_context(symbol=symbol)
|
||||
ctx["sources"] = ["paper_trading"]
|
||||
elif intent == "review":
|
||||
ctx["reviews"] = _review_context(symbol=symbol, limit=12)
|
||||
ctx["recommendations"] = _latest_recommendations(symbol=symbol, limit=8) if symbol else _latest_recommendations(limit=8)
|
||||
ctx["paper"] = _paper_context(symbol=symbol)
|
||||
ctx["sources"] = ["review_log", "recommendation", "paper_trading"]
|
||||
elif intent == "sentiment":
|
||||
ctx["sentiment_events"] = _sentiment_context(symbol=symbol, limit=20)
|
||||
try:
|
||||
from app.services.llm_insights import get_latest_sentiment_batch_analysis
|
||||
|
||||
ctx["ai_sentiment"] = get_latest_sentiment_batch_analysis() or {}
|
||||
except Exception:
|
||||
ctx["ai_sentiment"] = {}
|
||||
ctx["sources"] = ["event_news", "llm_sentiment"]
|
||||
elif intent == "onchain":
|
||||
if symbol:
|
||||
try:
|
||||
ctx["onchain"] = get_onchain_token_detail(symbol=symbol, hours=168)
|
||||
except Exception as exc:
|
||||
ctx["onchain"] = {"error": str(exc)[:200]}
|
||||
else:
|
||||
ctx["onchain"] = get_onchain_overview(hours=24)
|
||||
ctx["sources"] = ["onchain"]
|
||||
else:
|
||||
ctx["capabilities"] = [
|
||||
"单币技术面：自动拉取 Binance 15m/1h/4h/1d K 线",
|
||||
"推荐解释：结合当前看板状态、入场窗口、TP/SL、风险理由",
|
||||
"舆情和链上：读取当前系统已采集与 AI 解读的结果",
|
||||
"复盘和模拟交易：区分信号表现与纸面交易收益",
|
||||
]
|
||||
return ctx
|
||||
|
||||
|
||||
def _fallback_answer(intent: str, message: str, context: dict) -> dict:
|
||||
if intent == "unsupported":
|
||||
return {
|
||||
"summary": "我只能回答加密货币和 AlphaX 当前数据相关的问题。",
|
||||
"answer": "这个问题超出了 Crypto 研究助手的范围。你可以问某个币的技术面、看板推荐原因、链上异动、舆情影响、复盘或模拟交易表现。",
|
||||
"evidence": [],
|
||||
"related_records": [],
|
||||
"followups": ["分析 BTC/USDT 的技术面", "今天市场适合追强势币吗？"],
|
||||
}
|
||||
symbol = context.get("symbol") or ""
|
||||
tech = context.get("technicals") or {}
|
||||
tech_summary = tech.get("summary") or {}
|
||||
recommendations = context.get("recommendations") or []
|
||||
sentiment = context.get("sentiment_events") or []
|
||||
onchain = context.get("onchain") or {}
|
||||
paper = context.get("paper") or {}
|
||||
evidence = []
|
||||
if tech_summary:
|
||||
evidence.append(f"技术面：{tech_summary.get('headline', '')}")
|
||||
if recommendations:
|
||||
r = recommendations[0]
|
||||
evidence.append(f"主链路：{r.get('execution_label') or r.get('action_status') or r.get('execution_status')}，原因：{r.get('execution_reason') or r.get('state_reason') or '--'}")
|
||||
if sentiment:
|
||||
evidence.append(f"舆情：近 72h 有 {len(sentiment)} 条相关事件，最新为「{sentiment[0].get('title', '')[:60]}」。")
|
||||
if isinstance(onchain, dict) and (onchain.get("events") or onchain.get("metrics")):
|
||||
evidence.append(f"链上：近 7 天有 {len(onchain.get('events') or [])} 条映射事件。")
|
||||
if isinstance(paper, dict) and paper.get("trades"):
|
||||
latest = paper["trades"][0]
|
||||
evidence.append(f"模拟交易：最新状态 {latest.get('status')}，收益 {latest.get('pnl_pct') or latest.get('realized_pnl_pct') or 0}%。")
|
||||
if not evidence:
|
||||
evidence.append("当前数据库没有足够样本，结论需要降级为观察。")
|
||||
|
||||
if intent == "market_overview":
|
||||
market = (context.get("market") or {})
|
||||
state = market.get("state") or {}
|
||||
summary = state.get("label") or "市场数据已读取"
|
||||
answer = state.get("summary") or "我读取了全市场行情，但当前没有足够信息形成强结论。"
|
||||
elif symbol:
|
||||
summary = tech_summary.get("headline") or f"{symbol} 需要继续观察"
|
||||
answer = "结论：" + summary + " 证据区已汇总技术面、推荐、舆情、链上和模拟交易上下文。"
|
||||
else:
|
||||
summary = "已读取当前系统数据"
|
||||
answer = "我已经按你的问题读取了当前数据库，但没有识别到明确币种；可以继续追问具体币种。"
|
||||
|
||||
return {
|
||||
"summary": summary,
|
||||
"answer": answer,
|
||||
"evidence": evidence[:8],
|
||||
"related_records": _related_records(context),
|
||||
"followups": _followups(intent, symbol),
|
||||
}
|
||||
|
||||
|
||||
def _related_records(context: dict) -> list[dict]:
|
||||
records = []
|
||||
for item in (context.get("recommendations") or [])[:3]:
|
||||
records.append({"type": "recommendation", "label": f"推荐 #{item.get('id')}", "symbol": item.get("symbol"), "status": item.get("execution_status")})
|
||||
for item in (context.get("sentiment_events") or [])[:3]:
|
||||
records.append({"type": "sentiment", "label": item.get("title"), "symbol": item.get("symbol"), "status": item.get("importance")})
|
||||
for item in ((context.get("paper") or {}).get("trades") or [])[:3]:
|
||||
records.append({"type": "paper_trade", "label": f"模拟交易 #{item.get('id')}", "symbol": item.get("symbol"), "status": item.get("status")})
|
||||
return records
|
||||
|
||||
|
||||
def _compact_technical_context(context: dict) -> dict:
|
||||
tech = context.get("technicals") or {}
|
||||
tfs = {}
|
||||
for tf, item in (tech.get("timeframes") or {}).items():
|
||||
if not item.get("available"):
|
||||
tfs[tf] = {"available": False, "reason": item.get("reason") or ""}
|
||||
continue
|
||||
tfs[tf] = {
|
||||
"available": True,
|
||||
"price": item.get("price"),
|
||||
"trend": item.get("trend"),
|
||||
"rsi14": item.get("rsi14"),
|
||||
"volume_ratio_20": item.get("volume_ratio_20"),
|
||||
"range_position_pct": item.get("range_position_pct"),
|
||||
"support": item.get("support"),
|
||||
"resistance": item.get("resistance"),
|
||||
"pa": {
|
||||
"dynamic_count_recent": (item.get("pa") or {}).get("dynamic_count_recent"),
|
||||
"static_count_recent": (item.get("pa") or {}).get("static_count_recent"),
|
||||
"ignition_count": len((item.get("pa") or {}).get("ignition_points") or []),
|
||||
"zone_count": len((item.get("pa") or {}).get("top_zones") or []),
|
||||
},
|
||||
}
|
||||
return {
|
||||
"summary": tech.get("summary") or {},
|
||||
"binance_tradable": bool(tech.get("binance_tradable")),
|
||||
"timeframes": tfs,
|
||||
}
|
||||
|
||||
|
||||
def _followups(intent: str, symbol: str = "") -> list[str]:
|
||||
if symbol:
|
||||
base = symbol.replace("/USDT", "")
|
||||
return [
|
||||
f"{base} 现在追高风险大吗？",
|
||||
f"{base} 的链上和舆情有没有共振？",
|
||||
f"{base} 如果要等回踩，关键价位在哪里？",
|
||||
]
|
||||
if intent == "market_overview":
|
||||
return ["今天市场更适合做日内还是 1-3 天波段？", "当前涨幅榜有什么共性？"]
|
||||
return ["分析 BTC/USDT 现在的技术面", "解释最新推荐为什么不是可买"]
|
||||
|
||||
|
||||
def _call_chat_llm(message: str, context: dict, history=None) -> dict:
|
||||
cfg = llm_config()
|
||||
params = get_llm_params()
|
||||
if not bool(cfg.get("enabled", False)) or not os.getenv(str(params.get("api_key_env") or "ALPHAX_LLM_API_KEY"), "").strip():
|
||||
return {"status": "skipped", "error": "llm_disabled"}
|
||||
if not bool((cfg.get("modules") or {}).get("chat", True)):
|
||||
return {"status": "skipped", "error": "chat_module_disabled"}
|
||||
api_key = os.getenv(str(params.get("api_key_env") or "ALPHAX_LLM_API_KEY"), "").strip()
|
||||
base_url = str(params.get("base_url") or "https://api.openai.com/v1").rstrip("/")
|
||||
model = str(params.get("model") or "gpt-4o-mini").strip()
|
||||
payload = {
|
||||
"user_question": message,
|
||||
"context": context,
|
||||
"recent_history": (history or [])[-8:],
|
||||
"rules": [
|
||||
"只回答加密货币、AlphaX 当前数据、技术面、链上、舆情、复盘和模拟交易相关问题。",
|
||||
"不要给真实下单指令，不要修改推荐状态，不要承诺收益。",
|
||||
"回答使用中文，采用两段式：先结论，再证据。",
|
||||
"输出严格 JSON：summary, answer, evidence[], risk_flags[], related_records[], followups[]。",
|
||||
],
|
||||
}
|
||||
system_prompt = "你是 AlphaX Agent 的 Crypto 研究助手。你只能基于提供的结构化数据回答，不能编造数据。"
|
||||
try:
|
||||
resp = requests.post(
|
||||
f"{base_url}/chat/completions",
|
||||
headers={"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"},
|
||||
json={
|
||||
"model": model,
|
||||
"messages": [
|
||||
{"role": "system", "content": system_prompt},
|
||||
{"role": "user", "content": _compact_json(payload)},
|
||||
],
|
||||
"temperature": 0.15,
|
||||
"max_tokens": int(params.get("max_tokens") or 900),
|
||||
"response_format": {"type": "json_object"},
|
||||
},
|
||||
timeout=int(params.get("timeout") or 20),
|
||||
)
|
||||
if resp.status_code >= 400:
|
||||
return {"status": "failed", "error": f"http_{resp.status_code}:{resp.text[:300]}", "model": model}
|
||||
data = resp.json()
|
||||
content = (((data.get("choices") or [{}])[0]).get("message") or {}).get("content") or "{}"
|
||||
content = repair_mojibake_text(content)
|
||||
parsed = repair_mojibake_json(json.loads(content))
|
||||
if not isinstance(parsed, dict):
|
||||
raise ValueError("llm_output_not_object")
|
||||
parsed.setdefault("summary", parsed.get("answer", "")[:80])
|
||||
parsed.setdefault("evidence", [])
|
||||
parsed.setdefault("risk_flags", [])
|
||||
parsed.setdefault("related_records", _related_records(context))
|
||||
parsed.setdefault("followups", _followups(context.get("intent"), context.get("symbol")))
|
||||
return {"status": "success", "content": parsed, "model": model}
|
||||
except Exception as exc:
|
||||
return {"status": "failed", "error": str(exc)[:500], "model": model}
|
||||
|
||||
|
||||
def answer_chat(user_id: int, message: str, session_id: int = 0) -> dict:
|
||||
message = str(message or "").strip()
|
||||
if not message:
|
||||
raise ValueError("message_required")
|
||||
prefs = chat_assistant_db.get_user_preferences(user_id)
|
||||
session = chat_assistant_db.get_chat_session(session_id, user_id) if session_id else None
|
||||
symbol = extract_symbol(message, session=session, preferences=prefs)
|
||||
intent = detect_intent(message, symbol=symbol)
|
||||
if not session:
|
||||
title = symbol or message[:24]
|
||||
session = chat_assistant_db.create_chat_session(user_id, title=title, last_symbol=symbol, last_intent=intent)
|
||||
user_msg = chat_assistant_db.append_chat_message(
|
||||
session["id"],
|
||||
user_id,
|
||||
"user",
|
||||
content_text=message,
|
||||
content_json={"text": message},
|
||||
intent=intent,
|
||||
symbol=symbol,
|
||||
)
|
||||
history = chat_assistant_db.list_chat_messages(session["id"], user_id, limit=12).get("items", [])
|
||||
context = build_context(intent, message, symbol, preferences=prefs)
|
||||
llm_result = _call_chat_llm(message, context, history=history)
|
||||
if llm_result.get("status") == "success":
|
||||
answer = repair_mojibake_json(llm_result.get("content") or {})
|
||||
model = llm_result.get("model") or ""
|
||||
else:
|
||||
answer = repair_mojibake_json(_fallback_answer(intent, message, context))
|
||||
answer["llm_status"] = llm_result.get("status")
|
||||
answer["llm_error"] = llm_result.get("error", "")
|
||||
model = llm_result.get("model") or ""
|
||||
answer.setdefault("related_records", _related_records(context))
|
||||
answer.setdefault("followups", _followups(intent, symbol))
|
||||
answer.setdefault("evidence", [])
|
||||
assistant_text = repair_mojibake_text(answer.get("answer") or answer.get("summary") or "")
|
||||
assistant_msg = chat_assistant_db.append_chat_message(
|
||||
session["id"],
|
||||
user_id,
|
||||
"assistant",
|
||||
content_text=assistant_text,
|
||||
content_json=answer,
|
||||
context_json={
|
||||
"intent": intent,
|
||||
"symbol": symbol,
|
||||
"context_hash": compute_input_hash(context),
|
||||
"sources": context.get("sources") or [],
|
||||
"technical_summary": (context.get("technicals") or {}).get("summary") or {},
|
||||
"technicals": _compact_technical_context(context),
|
||||
},
|
||||
intent=intent,
|
||||
symbol=symbol,
|
||||
model=model,
|
||||
)
|
||||
memory = session.get("memory") or {}
|
||||
if symbol:
|
||||
memory["last_symbol"] = symbol
|
||||
memory["last_intent"] = intent
|
||||
chat_assistant_db.update_chat_session(
|
||||
session["id"],
|
||||
user_id,
|
||||
title=session.get("title") if session.get("title") != "新对话" else (symbol or message[:24]),
|
||||
memory_json=memory,
|
||||
last_symbol=symbol,
|
||||
last_intent=intent,
|
||||
)
|
||||
pref_patch = {"last_intent": intent, "recent_topics": [intent]}
|
||||
if symbol:
|
||||
pref_patch["last_symbol"] = symbol
|
||||
pref_patch["preferred_symbols"] = [symbol]
|
||||
chat_assistant_db.update_user_preferences(user_id, pref_patch)
|
||||
return {
|
||||
"ok": True,
|
||||
"session": chat_assistant_db.get_chat_session(session["id"], user_id),
|
||||
"user_message": user_msg,
|
||||
"assistant_message": assistant_msg,
|
||||
"answer": answer,
|
||||
"intent": intent,
|
||||
"intent_label": INTENT_LABELS.get(intent, intent),
|
||||
"symbol": symbol,
|
||||
"context": {
|
||||
"sources": context.get("sources") or [],
|
||||
"technicals": context.get("technicals") or {},
|
||||
"related_records": answer.get("related_records") or [],
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
__all__ = [
|
||||
"analyze_symbol_technicals",
|
||||
"answer_chat",
|
||||
"build_context",
|
||||
"detect_intent",
|
||||
"extract_symbol",
|
||||
"fetch_binance_klines",
|
||||
]
|
||||
@ -25,7 +25,7 @@ import yaml
|
||||
sys.path.insert(0, os.path.dirname(__file__))
|
||||
|
||||
from app.config.config_loader import load_rules, get_meta, get_strategy_direction
|
||||
from app.db.altcoin_db import init_db, get_conn, create_recommendation, log_screening, log_cron_run, get_recommendation_for_push
|
||||
from app.db.altcoin_db import init_db, get_conn, create_recommendation, log_screening, log_cron_run
|
||||
from app.db.postgres_connection import ensure_migrations_once
|
||||
from app.db.llm_insights import repair_mojibake_json, repair_mojibake_text
|
||||
from app.core.opportunity_funnel import build_screening_detail
|
||||
@ -41,7 +41,6 @@ from app.services.altcoin_screener import (
|
||||
)
|
||||
from app.services.altcoin_confirm import fetch_derivatives_context
|
||||
from app.core.pa_engine import full_pa_analysis, calc_atr
|
||||
from app.integrations.push_orchestrator import push_mainline_state_update
|
||||
|
||||
exchange = ccxt.binance({"enableRateLimit": True})
|
||||
|
||||
@ -838,21 +837,6 @@ def process_event(event):
|
||||
sector_context={"event_title": event.get("title"), "event_url": event.get("url"), "event_source": event.get("source"), "event_importance": event.get("importance"), "trigger_context": result.get("trigger_context", {})},
|
||||
)
|
||||
|
||||
# 飞书只是通知层：事件脚本不再直接推 observe/risk，也不允许 rec_id=0 的事件旁路进通知。
|
||||
# 只有 decision=recommend 且已创建主推荐记录后，消费主链路派生状态进行通知。
|
||||
if decision == "recommend" and rec_id and _cfg().get("push", {}).get(decision, True):
|
||||
mainline_item = get_recommendation_for_push(rec_id)
|
||||
pushed = push_mainline_state_update(
|
||||
symbol,
|
||||
rec_id,
|
||||
mainline_item,
|
||||
title_prefix="事件触发机会",
|
||||
entry_push_type="event_entry",
|
||||
watch_push_type="event_watch_pool",
|
||||
)
|
||||
elif decision in ("observe", "risk"):
|
||||
print(f"[event] skip push {symbol}: decision={decision} is not a主链路推荐通知")
|
||||
|
||||
conn = get_conn()
|
||||
conn.execute("""
|
||||
UPDATE event_news SET processed=1, decision=%s, tech_score=%s, rec_id=%s, pushed=%s
|
||||
|
||||
@ -30,7 +30,6 @@ from app.db.altcoin_db import (
|
||||
update_latest_price_cache,
|
||||
)
|
||||
from app.db.paper_trading import sync_recommendation as sync_paper_trade
|
||||
from app.integrations.push_orchestrator import push_trade_action_update
|
||||
from app.core.pa_engine import (
|
||||
calc_atr, full_pa_analysis, detect_trend_exhaustion,
|
||||
analyze_entry_point,
|
||||
|
||||
@ -32,7 +32,6 @@ from app.config.config_loader import (
|
||||
promote_candidate_rule_to_learned_rule, bump_strategy_patch_version,
|
||||
)
|
||||
from app.analysis import reverse_analysis
|
||||
from app.integrations import feishu_review_push
|
||||
import requests
|
||||
|
||||
BINANCE_API = "https://api.binance.com/api/v3"
|
||||
@ -1499,26 +1498,6 @@ def run_review(push_enabled: bool = True, compact: bool = False):
|
||||
f"\n信号淘汰: {'; '.join(results['signal_deprecations'][:5])}"
|
||||
)
|
||||
|
||||
# 7. 飞书推送
|
||||
if push_enabled:
|
||||
try:
|
||||
ok1, r1 = feishu_review_push.push_review_report(results)
|
||||
print(f"[review_engine] 复盘报告推送: ok={ok1}")
|
||||
|
||||
if results["reverse_analysis"] and not results["reverse_analysis"].get("error"):
|
||||
ok2, r2 = feishu_review_push.push_reverse_analysis_report(results["reverse_analysis"])
|
||||
print(f"[review_engine] 逆向分析报告推送: ok={ok2}")
|
||||
|
||||
for rule in new_pattern_rules:
|
||||
feishu_review_push.push_rule_update_notification(rule.get("candidate_id"), rule.get("description", ""), status="候选规则，未生效")
|
||||
|
||||
if results["reverse_analysis"] and results["reverse_analysis"].get("new_rules"):
|
||||
for rule in results["reverse_analysis"]["new_rules"]:
|
||||
feishu_review_push.push_rule_update_notification(rule.get("candidate_id"), rule.get("description", ""), status="逆向候选，未生效")
|
||||
|
||||
except Exception as e:
|
||||
print(f"[review_engine] 飞书推送失败: {e}")
|
||||
|
||||
# 8. 更新meta（迭代元数据）
|
||||
update_meta("last_review", now.isoformat())
|
||||
meta = get_review_params() # 先读当前meta
|
||||
|
||||
54
app/web/routes_chat.py
Normal file
54
app/web/routes_chat.py
Normal file
@ -0,0 +1,54 @@
|
||||
from fastapi import APIRouter, Cookie, HTTPException
|
||||
|
||||
from app.db import chat_assistant_db
|
||||
from app.services.chat_assistant import answer_chat
|
||||
from app.web.shared import ChatSendRequest, ChatSessionRequest, require_api_user_with_subscription
|
||||
|
||||
|
||||
router = APIRouter()
|
||||
|
||||
|
||||
@router.get("/api/chat/bootstrap")
|
||||
async def api_chat_bootstrap(altcoin_session: str = Cookie(default="")):
|
||||
user = require_api_user_with_subscription(altcoin_session)
|
||||
return chat_assistant_db.bootstrap_chat(user["id"])
|
||||
|
||||
|
||||
@router.get("/api/chat/sessions")
|
||||
async def api_chat_sessions(limit: int = 20, offset: int = 0, altcoin_session: str = Cookie(default="")):
|
||||
user = require_api_user_with_subscription(altcoin_session)
|
||||
return chat_assistant_db.list_chat_sessions(user["id"], limit=limit, offset=offset)
|
||||
|
||||
|
||||
@router.post("/api/chat/sessions")
|
||||
async def api_chat_create_session(req: ChatSessionRequest, altcoin_session: str = Cookie(default="")):
|
||||
user = require_api_user_with_subscription(altcoin_session)
|
||||
return {"ok": True, "session": chat_assistant_db.create_chat_session(user["id"], title=req.title)}
|
||||
|
||||
|
||||
@router.get("/api/chat/sessions/{session_id}")
|
||||
async def api_chat_session_detail(session_id: int, altcoin_session: str = Cookie(default="")):
|
||||
user = require_api_user_with_subscription(altcoin_session)
|
||||
session = chat_assistant_db.get_chat_session(session_id, user["id"])
|
||||
if not session:
|
||||
raise HTTPException(status_code=404, detail="对话不存在")
|
||||
messages = chat_assistant_db.list_chat_messages(session_id, user["id"], limit=200)
|
||||
return {"ok": True, "session": session, "messages": messages}
|
||||
|
||||
|
||||
@router.delete("/api/chat/sessions/{session_id}")
|
||||
async def api_chat_archive_session(session_id: int, altcoin_session: str = Cookie(default="")):
|
||||
user = require_api_user_with_subscription(altcoin_session)
|
||||
session = chat_assistant_db.update_chat_session(session_id, user["id"], archived_at="now")
|
||||
if not session:
|
||||
raise HTTPException(status_code=404, detail="对话不存在")
|
||||
return {"ok": True}
|
||||
|
||||
|
||||
@router.post("/api/chat/send")
|
||||
async def api_chat_send(req: ChatSendRequest, altcoin_session: str = Cookie(default="")):
|
||||
user = require_api_user_with_subscription(altcoin_session)
|
||||
try:
|
||||
return answer_chat(user["id"], req.message, session_id=req.session_id)
|
||||
except ValueError as exc:
|
||||
raise HTTPException(status_code=400, detail=str(exc))
|
||||
@ -49,6 +49,13 @@ def build_router(templates, repo_root: Path, stock_report_template: str):
|
||||
return redirect
|
||||
return render_page("pipeline.html", request, active_nav="pipeline")
|
||||
|
||||
@router.get("/chat", response_class=HTMLResponse)
|
||||
async def chat_page(request: Request):
|
||||
user, redirect = require_page_user(request)
|
||||
if redirect:
|
||||
return redirect
|
||||
return render_page("chat.html", request, active_nav="chat")
|
||||
|
||||
@router.get("/llm-insights", response_class=HTMLResponse)
|
||||
async def llm_insights_page(request: Request):
|
||||
user, redirect = require_page_user(request)
|
||||
|
||||
@ -84,6 +84,15 @@ class RuntimeConfigRequest(BaseModel):
|
||||
description: str = ""
|
||||
|
||||
|
||||
class ChatSessionRequest(BaseModel):
|
||||
title: str = ""
|
||||
|
||||
|
||||
class ChatSendRequest(BaseModel):
|
||||
session_id: int = 0
|
||||
message: str
|
||||
|
||||
|
||||
def auth_error(exc: Exception, status_code: int = 400):
|
||||
raise HTTPException(status_code=status_code, detail=str(exc))
|
||||
|
||||
|
||||
@ -16,6 +16,7 @@ from app.db.analytics import get_all_recommendations, get_cron_run_logs, get_cro
|
||||
from app.db.recommendation_queries import get_active_recommendations, get_active_recommendations_deduped
|
||||
from app.web.routes_admin import build_router as build_admin_router
|
||||
from app.web.routes_auth import router as auth_router
|
||||
from app.web.routes_chat import router as chat_router
|
||||
from app.web.routes_content import build_router as build_content_router
|
||||
from app.web.routes_market import router as market_router
|
||||
from app.web.routes_onchain import router as onchain_router
|
||||
@ -44,6 +45,7 @@ app = FastAPI(title="AlphaX Agent", lifespan=lifespan)
|
||||
templates = Jinja2Templates(directory=str(REPO_ROOT / "static"))
|
||||
|
||||
app.include_router(auth_router)
|
||||
app.include_router(chat_router)
|
||||
app.include_router(recommendations_router)
|
||||
app.include_router(strategy_router)
|
||||
app.include_router(onchain_router)
|
||||
|
||||
@ -155,6 +155,7 @@ a { color: inherit; text-decoration: none; }
|
||||
<symbol id="svg-pipeline" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><circle cx="5" cy="6" r="2"/><circle cx="19" cy="6" r="2"/><circle cx="12" cy="18" r="2"/><path d="M7 6h10"/><path d="M6.5 7.7 11 16"/><path d="M17.5 7.7 13 16"/></symbol>
|
||||
<symbol id="svg-cron" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><circle cx="12" cy="12" r="9"/><path d="M12 7v5l3 2"/><path d="M4 4l3 3"/><path d="M20 4l-3 3"/></symbol>
|
||||
<symbol id="svg-ai" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><rect x="5" y="5" width="14" height="14" rx="3"/><path d="M9 1v4"/><path d="M15 1v4"/><path d="M9 19v4"/><path d="M15 19v4"/><path d="M1 9h4"/><path d="M1 15h4"/><path d="M19 9h4"/><path d="M19 15h4"/><path d="M9 15l1.5-6h3L15 15"/><path d="M10 13h4"/></symbol>
|
||||
<symbol id="svg-chat" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M21 15a4 4 0 0 1-4 4H8l-5 3V7a4 4 0 0 1 4-4h10a4 4 0 0 1 4 4z"/><path d="M8 9h8"/><path d="M8 13h5"/></symbol>
|
||||
<symbol id="svg-iterate" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><polyline points="1 4 1 10 7 10"/><polyline points="23 20 23 14 17 14"/><path d="M20.49 9A9 9 0 0 0 5.64 5.64L1 10m22 4l-4.64 4.36A9 9 0 0 1 3.51 15"/></symbol>
|
||||
<symbol id="svg-sentiment" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3H14z"/><path d="M7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"/></symbol>
|
||||
<symbol id="svg-onchain" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><circle cx="6" cy="7" r="3"/><circle cx="18" cy="7" r="3"/><circle cx="12" cy="18" r="3"/><path d="M8.6 8.8 10.7 15"/><path d="M15.4 8.8 13.3 15"/><path d="M9 7h6"/></symbol>
|
||||
@ -175,6 +176,7 @@ a { color: inherit; text-decoration: none; }
|
||||
<nav class="sidebar-nav">
|
||||
<div class="sidebar-section-label">交易</div>
|
||||
<a class="sidebar-link {% if active_nav | default('app') == 'app' %}active{% endif %}" href="/app"><svg class="link-icon"><use href="#svg-dashboard"/></svg>看板</a>
|
||||
<a class="sidebar-link {% if active_nav == 'chat' %}active{% endif %}" href="/chat"><svg class="link-icon"><use href="#svg-chat"/></svg>智能问答</a>
|
||||
<a class="sidebar-link admin-link {% if active_nav == 'paper_trading' %}active{% endif %}" href="/paper-trading" style="display:none"><svg class="link-icon"><use href="#svg-paper"/></svg>模拟交易</a>
|
||||
<div class="sidebar-section-label">研究</div>
|
||||
<a class="sidebar-link {% if active_nav == 'market' %}active{% endif %}" href="/market"><svg class="link-icon"><use href="#svg-target"/></svg>市场总览</a>
|
||||
|
||||
127
static/chat.html
Normal file
127
static/chat.html
Normal file
@ -0,0 +1,127 @@
|
||||
{% extends "base.html" %}
|
||||
{% block title %}AlphaX Agent — 智能问答{% endblock %}
|
||||
{% block extra_head_css %}
|
||||
<style>
|
||||
.chat-shell{height:100vh;max-height:100vh;display:grid;grid-template-columns:300px minmax(0,1fr);background:#f4f5f7;overflow:hidden}
|
||||
.session-pane{border-right:1px solid var(--hairline-soft);background:var(--canvas);display:flex;flex-direction:column;min-width:0}
|
||||
.session-head{padding:18px 16px;border-bottom:1px solid var(--hairline-soft);display:flex;align-items:center;justify-content:space-between;gap:10px}
|
||||
.session-title{font-size:17px;font-weight:950;letter-spacing:-.3px}
|
||||
.icon-btn{width:34px;height:34px;border:1px solid var(--hairline);border-radius:var(--radius-md);background:var(--canvas);display:grid;place-items:center;cursor:pointer;color:var(--ink);font-weight:950}
|
||||
.session-list{overflow:auto;min-height:0;flex:1;padding:8px}
|
||||
.session-row{padding:12px;border-radius:var(--radius-md);cursor:pointer;border:1px solid transparent;background:transparent;transition:.12s}
|
||||
.session-row:hover{background:var(--surface)}
|
||||
.session-row.active{background:#1c1c1e;color:#fff}
|
||||
.session-row b{display:block;font-size:13px;white-space:nowrap;overflow:hidden;text-overflow:ellipsis}
|
||||
.session-row span{display:block;margin-top:4px;color:var(--stone);font-size:11px;line-height:1.4;display:-webkit-box;-webkit-line-clamp:2;-webkit-box-orient:vertical;overflow:hidden}
|
||||
.session-row.active span{color:rgba(255,255,255,.66)}
|
||||
.chat-main{display:grid;grid-template-rows:auto minmax(0,1fr) auto;min-width:0;max-height:100vh}
|
||||
.hero{border-bottom:1px solid var(--hairline-soft);background:linear-gradient(180deg,#fff,#fafafa);padding:18px 22px;display:flex;justify-content:space-between;gap:16px;align-items:flex-start}
|
||||
.hero h1{font-size:23px;font-weight:950;letter-spacing:-.7px;margin:0}
|
||||
.hero p{margin-top:4px;color:var(--slate);font-size:13px;line-height:1.6}
|
||||
.status-pill{display:inline-flex;align-items:center;height:30px;padding:0 10px;border:1px solid var(--hairline-soft);border-radius:999px;background:var(--surface);color:var(--stone);font-size:11px;font-weight:900;white-space:nowrap}
|
||||
.messages{overflow:auto;min-height:0;padding:18px 22px 24px;display:flex;flex-direction:column;gap:14px}
|
||||
.msg{display:grid;grid-template-columns:36px minmax(0,1fr);gap:10px;max-width:1120px}
|
||||
.avatar{width:36px;height:36px;border-radius:10px;display:grid;place-items:center;font-weight:950;font-size:12px;background:var(--yellow);color:#1c1c1e}
|
||||
.avatar.ai{background:#1c1c1e;color:#fff}
|
||||
.bubble{border:1px solid var(--hairline-soft);border-radius:var(--radius-md);background:var(--canvas);padding:14px;box-shadow:0 8px 24px rgba(5,0,56,.035);min-width:0}
|
||||
.msg.user .bubble{background:#1c1c1e;color:#fff;border-color:#1c1c1e}
|
||||
.bubble-text{font-size:14px;line-height:1.75;white-space:pre-wrap}
|
||||
.answer-head{display:flex;align-items:flex-start;justify-content:space-between;gap:12px;margin-bottom:10px}
|
||||
.answer-head b{font-size:16px;color:var(--ink);line-height:1.35}
|
||||
.tag{display:inline-flex;align-items:center;border-radius:999px;padding:4px 8px;background:rgba(66,98,255,.08);color:var(--blue);font-size:11px;font-weight:950;white-space:nowrap}
|
||||
.answer-text{font-size:14px;color:var(--slate);line-height:1.75;margin-bottom:12px}
|
||||
.progress-box{border:1px solid var(--hairline-soft);border-radius:var(--radius-md);background:var(--surface);padding:11px 12px;margin-bottom:12px}
|
||||
.progress-row{display:flex;align-items:center;justify-content:space-between;gap:12px;font-size:12px;color:var(--slate);padding:5px 0}
|
||||
.progress-row strong{color:var(--ink);font-size:12px}
|
||||
.progress-dots{display:inline-flex;gap:4px;align-items:center}
|
||||
.progress-dots i{width:6px;height:6px;border-radius:50%;background:var(--stone);animation:pulse .9s infinite ease-in-out}
|
||||
.progress-dots i:nth-child(2){animation-delay:.15s}
|
||||
.progress-dots i:nth-child(3){animation-delay:.3s}
|
||||
.evidence-grid{display:grid;grid-template-columns:1.1fr .9fr;gap:10px;margin-top:10px}
|
||||
.panel{border:1px solid var(--hairline-soft);border-radius:var(--radius-md);background:var(--surface);padding:11px;min-width:0}
|
||||
.panel h3{font-size:12px;font-weight:950;color:var(--ink);margin-bottom:8px}
|
||||
.ev-list{display:grid;gap:7px}
|
||||
.ev{font-size:12px;color:var(--slate);line-height:1.55;padding-left:11px;position:relative}
|
||||
.ev:before{content:"";position:absolute;left:0;top:.65em;width:4px;height:4px;border-radius:50%;background:var(--blue)}
|
||||
.record-list{display:flex;gap:6px;flex-wrap:wrap}
|
||||
.record{border:1px solid var(--hairline);background:#fff;border-radius:999px;padding:5px 8px;font-size:11px;font-weight:850;color:var(--slate)}
|
||||
.tf-grid{display:grid;grid-template-columns:repeat(4,minmax(0,1fr));gap:8px;margin-top:10px}
|
||||
.tf{border:1px solid var(--hairline-soft);background:#fff;border-radius:var(--radius-md);padding:9px;min-width:0}
|
||||
.tf span{display:block;color:var(--stone);font-size:10px;font-weight:950}
|
||||
.tf b{display:block;margin-top:3px;font-size:13px;color:var(--ink);white-space:nowrap;overflow:hidden;text-overflow:ellipsis}
|
||||
.tf small{display:block;margin-top:3px;color:var(--stone);font-size:10px;white-space:nowrap;overflow:hidden;text-overflow:ellipsis}
|
||||
.composer{border-top:1px solid var(--hairline-soft);background:var(--canvas);padding:12px 18px 14px}
|
||||
.composer-inner{max-width:1120px;display:grid;grid-template-columns:minmax(0,1fr) auto;gap:10px;align-items:end}
|
||||
.input{min-height:48px;max-height:120px;resize:none;border:1px solid var(--hairline-strong);border-radius:var(--radius-md);padding:13px 14px;font-size:14px;line-height:1.55;outline:none;background:#fff;color:var(--ink);font-family:inherit}
|
||||
.input:focus{border-color:var(--blue);box-shadow:0 0 0 3px rgba(66,98,255,.08)}
|
||||
.send{height:48px;border:0;border-radius:var(--radius-md);background:#1c1c1e;color:#fff;padding:0 18px;font-weight:950;cursor:pointer}
|
||||
.send:disabled{opacity:.45;cursor:not-allowed}
|
||||
.empty{padding:40px 20px;text-align:center;color:var(--stone);font-size:13px}
|
||||
.empty h2{font-size:24px;color:var(--ink);letter-spacing:-.7px;margin-bottom:8px}
|
||||
.loading-dots{display:inline-flex;gap:4px}
|
||||
.loading-dots i{width:6px;height:6px;border-radius:50%;background:var(--stone);animation:pulse .9s infinite ease-in-out}
|
||||
.loading-dots i:nth-child(2){animation-delay:.15s}
|
||||
.loading-dots i:nth-child(3){animation-delay:.3s}
|
||||
@keyframes pulse{0%,80%,100%{opacity:.25;transform:translateY(0)}40%{opacity:1;transform:translateY(-3px)}}
|
||||
@media(max-width:980px){.chat-shell{grid-template-columns:1fr}.session-pane{display:none}.hero{padding:14px}.messages{padding:14px}.evidence-grid{grid-template-columns:1fr}.tf-grid{grid-template-columns:repeat(2,minmax(0,1fr))}.composer{padding:10px}.chat-main{height:calc(100vh - 48px)}}
|
||||
@media(max-width:520px){.composer-inner{grid-template-columns:1fr}.send{width:100%}.hero{display:block}.status-pill{margin-top:8px}.msg{grid-template-columns:30px minmax(0,1fr)}.avatar{width:30px;height:30px;border-radius:8px}.bubble{padding:12px}}
|
||||
</style>
|
||||
{% endblock %}
|
||||
{% block content %}
|
||||
<div class="chat-shell">
|
||||
<aside class="session-pane">
|
||||
<div class="session-head">
|
||||
<div class="session-title">智能问答</div>
|
||||
<button class="icon-btn" onclick="newSession()" title="新对话">+</button>
|
||||
</div>
|
||||
<div class="session-list" id="sessionList"><div class="empty">加载中...</div></div>
|
||||
</aside>
|
||||
<main class="chat-main">
|
||||
<header class="hero">
|
||||
<div>
|
||||
<h1>Crypto 研究助手</h1>
|
||||
<p>结合 AlphaX 现有数据与 Binance 多周期行情，提供 Crypto 研究参考。</p>
|
||||
</div>
|
||||
<span class="status-pill" id="chatStatus">研究参考</span>
|
||||
</header>
|
||||
<section class="messages" id="messages"></section>
|
||||
<footer class="composer">
|
||||
<div class="composer-inner">
|
||||
<textarea class="input" id="messageInput" placeholder="问一个加密市场问题，比如：分析 SUI/USDT 现在的技术面，或者解释 DOGE 为什么等回踩。" onkeydown="handleKey(event)"></textarea>
|
||||
<button class="send" id="sendBtn" onclick="sendMessage()">发送</button>
|
||||
</div>
|
||||
</footer>
|
||||
</main>
|
||||
</div>
|
||||
{% endblock %}
|
||||
{% block extra_script %}
|
||||
<script>
|
||||
var state={sessions:[],sessionId:0,messages:[],loading:false};
|
||||
function esc(v){return String(v==null?'':v).replace(/[&<>"']/g,function(c){return {'&':'&','<':'<','>':'>','"':'"',"'":'''}[c];});}
|
||||
function fixMojibake(v){if(typeof v!=='string'||!/[ÃÂçèéåæäï¼ã]/.test(v))return v;try{var bytes=Uint8Array.from(Array.prototype.map.call(v,function(ch){return ch.charCodeAt(0)&255;}));var fixed=new TextDecoder('utf-8',{fatal:false}).decode(bytes);if(/[\u4e00-\u9fff，。；：！？（）《》]/.test(fixed))return fixed;}catch(e){}return v;}
|
||||
function deepFix(v){if(typeof v==='string')return fixMojibake(v);if(Array.isArray(v))return v.map(deepFix);if(v&&typeof v==='object'){Object.keys(v).forEach(function(k){v[k]=deepFix(v[k]);});}return v;}
|
||||
function short(v,n){v=String(v||'');return v.length>n?v.slice(0,n)+'...':v;}
|
||||
function fmtNum(v){v=Number(v||0);if(!v)return'--';if(v>=100)return v.toFixed(2);if(v>=1)return v.toFixed(3);if(v>=0.01)return v.toFixed(4);return v.toFixed(8);}
|
||||
function normMessages(items){return (items||[]).map(function(m){m=deepFix(m||{});return {id:m.id,role:m.role,text:m.content_text||'',content:m.content||{},context:m.context||{},created_at:m.created_at,intent:m.intent,symbol:m.symbol};});}
|
||||
function renderSessions(){if(!state.sessions.length){sessionList.innerHTML='<div class="empty">暂无对话</div>';return;}sessionList.innerHTML=state.sessions.map(function(s){var active=s.id===state.sessionId?' active':'';return '<div class="session-row'+active+'" onclick="loadSession('+s.id+')"><b>'+esc(s.title||'新对话')+'</b><span>'+esc(short(s.last_message_text||s.summary||'还没有消息',88))+'</span></div>';}).join('');}
|
||||
function renderEmpty(){messages.innerHTML='<div class="empty"><h2>问 AlphaX 一个 Crypto 问题</h2><p>直接输入你的问题即可，支持单币技术面、推荐解释、链上异动、舆情影响、复盘和模拟交易。</p></div>';}
|
||||
function renderMessages(){if(!state.messages.length){renderEmpty();return;}messages.innerHTML=state.messages.map(renderMessage).join('');messages.scrollTop=messages.scrollHeight;}
|
||||
function renderMessage(m){if(m.role==='user'){return '<div class="msg user"><div class="avatar">你</div><div class="bubble"><div class="bubble-text">'+esc(m.text)+'</div></div></div>';}return '<div class="msg"><div class="avatar ai">AI</div><div class="bubble">'+renderAnswer(m)+'</div></div>';}
|
||||
function renderProgress(lines){if(!lines||!lines.length)return'';return '<div class="progress-box">'+lines.map(function(line,idx){return '<div class="progress-row"><span>'+esc(line)+'</span>'+(idx===0?'<span class="progress-dots"><i></i><i></i><i></i></span>':'')+'</div>';}).join('')+'</div>';}
|
||||
function renderEvidenceList(items){if(!items||!items.length)return '<div class="ev">暂无明确证据，已降级为空态回答。</div>';return items.slice(0,8).map(function(x){if(typeof x==='string')return '<div class="ev">'+esc(x)+'</div>';if(Array.isArray(x))return '<div class="ev">'+esc(x.map(function(v){return typeof v==='string'?v:JSON.stringify(v);}).join(' · '))+'</div>';if(x&&typeof x==='object'){var label=x.label||x.name||x.title||x.reason||x.summary||x.key||'';var value=x.value||x.text||x.detail||x.note||x.signal||x.message||'';var extra=x.timeframe||x.symbol||x.period||x.source||'';var text=(label?label:'证据')+(value?('：'+value):'')+(extra?(' · '+extra):'');return '<div class="ev">'+esc(text||JSON.stringify(x))+'</div>';}return '<div class="ev">'+esc(String(x))+'</div>';}).join('');}
|
||||
function renderRecords(items){if(!items||!items.length)return '<span class="record">无直接记录</span>';return items.slice(0,8).map(function(r){if(typeof r==='string')return '<span class="record">'+esc(r)+'</span>';if(r&&typeof r==='object'){var parts=[];if(r.type)parts.push(r.type);if(r.label||r.title||r.name)parts.push(r.label||r.title||r.name);if(r.symbol)parts.push(r.symbol);if(r.status)parts.push(r.status);if(r.timeframe)parts.push(r.timeframe);if(r.created_at||r.detected_at)parts.push((r.created_at||r.detected_at).slice(0,16).replace('T',' '));var text=parts.filter(Boolean).join(' · ');return '<span class="record">'+esc(text||'记录')+'</span>';}return '<span class="record">'+esc(String(r))+'</span>';}).join('');}
|
||||
function renderTfGrid(ctx){var tech=(ctx&&ctx.technicals)||{},tfs=tech.timeframes||{},order=['15m','1h','4h','1d'];var has=order.some(function(tf){return tfs[tf]&&tfs[tf].available;});if(!has)return'';return '<div class="tf-grid">'+order.map(function(tf){var x=tfs[tf]||{};if(!x.available)return '<div class="tf"><span>'+tf+'</span><b>无数据</b><small>'+esc(x.reason||'Binance 未返回')+'</small></div>';var trend={uptrend:'上行',rebound:'反弹',weak:'偏弱',downtrend:'下行',sideways:'震荡'}[x.trend]||x.trend||'--';var sub='RSI '+(x.rsi14||'--')+' · 量 '+(x.volume_ratio_20||0)+'x';return '<div class="tf"><span>'+tf+'</span><b>'+esc(trend)+' · $'+fmtNum(x.price)+'</b><small>'+esc(sub)+'</small></div>';}).join('')+'</div>';}
|
||||
function renderAnswer(m){var c=m.content||{},ctx=m.context||{},answer=String(c.answer||m.text||c.summary||'--');var evidence=Array.isArray(c.evidence)?c.evidence:[];var risks=Array.isArray(c.risk_flags)?c.risk_flags:[];var records=Array.isArray(c.related_records)?c.related_records:[];var progressHtml=m.intent==='loading'?renderProgress(['正在读取 AlphaX 数据','正在拉取当前币种行情','正在汇总推荐 / 舆情 / 链上 / 复盘上下文']):'';var tfHtml=renderTfGrid(ctx);return '<div class="answer-head"><b>'+esc(c.summary||'研究结论')+'</b><span class="tag">'+esc((m.intent||ctx.intent||'回答'))+'</span></div>'+progressHtml+'<div class="answer-text">'+esc(answer)+'</div>'+tfHtml+'<div class="evidence-grid"><div class="panel"><h3>证据</h3><div class="ev-list">'+renderEvidenceList(evidence)+(risks.length?renderEvidenceList(risks):'')+'</div></div><div class="panel"><h3>相关记录</h3><div class="record-list">'+renderRecords(records)+'</div></div></div>';}
|
||||
async function init(){try{var d=await (await fetch('/api/chat/bootstrap')).json();state.sessions=(d.sessions&&d.sessions.items)||[];renderSessions();if(state.sessions[0])loadSession(state.sessions[0].id);else renderEmpty();}catch(e){messages.innerHTML='<div class="empty">聊天助手加载失败</div>';}}
|
||||
async function refreshSessions(){var d=await (await fetch('/api/chat/sessions?limit=20')).json();state.sessions=d.items||[];renderSessions();}
|
||||
async function newSession(){state.sessionId=0;state.messages=[];renderSessions();renderEmpty();messageInput.focus();}
|
||||
async function loadSession(id){state.sessionId=id;renderSessions();messages.innerHTML='<div class="empty">加载对话...</div>';try{var d=await (await fetch('/api/chat/sessions/'+id)).json();state.messages=normMessages((d.messages&&d.messages.items)||[]);renderMessages();}catch(e){messages.innerHTML='<div class="empty">读取对话失败</div>';}}
|
||||
function handleKey(e){if(e.key==='Enter'&&!e.shiftKey){e.preventDefault();sendMessage();}}
|
||||
function appendLoading(){state.messages.push({role:'assistant',text:'',content:{summary:'正在读取数据',answer:'',evidence:[]},context:{},created_at:new Date().toISOString(),intent:'loading'});renderMessages();}
|
||||
function removeLoading(){state.messages=state.messages.filter(function(m){return m.intent!=='loading';});}
|
||||
async function sendMessage(){var text=messageInput.value.trim();if(!text||state.loading)return;state.loading=true;sendBtn.disabled=true;chatStatus.textContent='分析中';state.messages.push({role:'user',text:text,content:{text:text},created_at:new Date().toISOString()});messageInput.value='';appendLoading();try{var d=deepFix(await (await fetch('/api/chat/send',{method:'POST',headers:{'Content-Type':'application/json'},body:JSON.stringify({session_id:state.sessionId||0,message:text})})).json());removeLoading();state.sessionId=(d.session&&d.session.id)||state.sessionId;state.messages.push(d.assistant_message);renderMessages();await refreshSessions();}catch(e){removeLoading();state.messages.push({role:'assistant',content:{summary:'回答失败',answer:'这次请求没有完成，请稍后重试。',evidence:[]},context:{},created_at:new Date().toISOString(),intent:'error'});renderMessages();}finally{state.loading=false;sendBtn.disabled=false;chatStatus.textContent='研究参考';}}
|
||||
var _renderAnswer=renderAnswer;
|
||||
renderAnswer=function(m){if(m.intent==='loading'){return '<div class="answer-head"><b>正在读取 AlphaX 数据</b><span class="tag">分析中</span></div><div class="answer-text"><span class="loading-dots"><i></i><i></i><i></i></span></div>';}return _renderAnswer(m);}
|
||||
init();
|
||||
</script>
|
||||
{% endblock %}
|
||||
@ -104,6 +104,9 @@ _ID_TABLES = {
|
||||
"scheduler_manual_trigger",
|
||||
"strategy_runtime_config",
|
||||
"system_config",
|
||||
"chat_sessions",
|
||||
"chat_messages",
|
||||
"chat_user_preferences",
|
||||
}
|
||||
|
||||
|
||||
|
||||
130
tests/test_chat_assistant.py
Normal file
130
tests/test_chat_assistant.py
Normal file
@ -0,0 +1,130 @@
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
import pandas as pd
|
||||
from fastapi.testclient import TestClient
|
||||
|
||||
from app.db import auth_db, chat_assistant_db
|
||||
from app.services import chat_assistant
|
||||
from app.web import web_server
|
||||
|
||||
|
||||
def _login_user(email: str = "chat-user@example.com", password: str = "StrongPass123") -> str:
|
||||
reg = auth_db.register_user(email, password)
|
||||
auth_db.verify_email(email, reg["verification_code"])
|
||||
user = auth_db.get_user_by_email(email)
|
||||
auth_db.claim_free_trial(user["id"])
|
||||
return auth_db.login_user(email, password)["token"]
|
||||
|
||||
|
||||
def _fake_ohlcv(rows=180, start=100.0):
|
||||
now = datetime(2026, 5, 1, 12, 0, 0)
|
||||
data = []
|
||||
price = start
|
||||
for i in range(rows):
|
||||
ts = now + timedelta(minutes=i * 15)
|
||||
open_p = price
|
||||
close_p = price * (1 + 0.001)
|
||||
high = max(open_p, close_p) * 1.004
|
||||
low = min(open_p, close_p) * 0.996
|
||||
vol = 1000 + i * 3
|
||||
data.append([ts, open_p, high, low, close_p, vol])
|
||||
price = close_p
|
||||
return pd.DataFrame(data, columns=["timestamp", "open", "high", "low", "close", "volume"])
|
||||
|
||||
|
||||
def test_chat_page_and_bootstrap_require_subscription():
|
||||
token = _login_user("chat-page@example.com")
|
||||
client = TestClient(web_server.app)
|
||||
client.cookies.set("altcoin_session", token)
|
||||
|
||||
page = client.get("/chat")
|
||||
boot = client.get("/api/chat/bootstrap")
|
||||
|
||||
assert page.status_code == 200
|
||||
assert "Crypto 研究助手" in page.text
|
||||
assert boot.status_code == 200
|
||||
assert "suggested_prompts" in boot.json()
|
||||
|
||||
|
||||
def test_single_coin_chat_fetches_multi_timeframe_technicals(monkeypatch):
|
||||
token = _login_user("chat-coin@example.com")
|
||||
seen = []
|
||||
|
||||
def fake_fetch(symbol, timeframe, limit=160):
|
||||
seen.append((symbol, timeframe))
|
||||
return _fake_ohlcv(rows=180, start=100.0)
|
||||
|
||||
monkeypatch.setattr(chat_assistant, "fetch_binance_klines", fake_fetch)
|
||||
monkeypatch.setattr(chat_assistant, "_call_chat_llm", lambda message, context, history=None: {"status": "skipped", "error": "disabled"})
|
||||
|
||||
client = TestClient(web_server.app)
|
||||
client.cookies.set("altcoin_session", token)
|
||||
resp = client.post("/api/chat/send", json={"message": "分析 SUI/USDT 现在的技术面"})
|
||||
|
||||
assert resp.status_code == 200
|
||||
data = resp.json()
|
||||
assert data["intent"] == "coin_analysis"
|
||||
assert data["symbol"] == "SUI/USDT"
|
||||
assert {tf for _, tf in seen} >= {"15m", "1h", "4h", "1d"}
|
||||
tfs = data["assistant_message"]["context"]["technicals"]["timeframes"]
|
||||
assert tfs["15m"]["available"] is True
|
||||
assert tfs["1h"]["pa"]["zone_count"] >= 0
|
||||
|
||||
|
||||
def test_non_crypto_question_is_rejected(monkeypatch):
|
||||
token = _login_user("chat-scope@example.com")
|
||||
monkeypatch.setattr(chat_assistant, "_call_chat_llm", lambda message, context, history=None: {"status": "skipped", "error": "disabled"})
|
||||
client = TestClient(web_server.app)
|
||||
client.cookies.set("altcoin_session", token)
|
||||
|
||||
resp = client.post("/api/chat/send", json={"message": "帮我写一份旅游攻略"})
|
||||
|
||||
assert resp.status_code == 200
|
||||
data = resp.json()
|
||||
assert data["intent"] == "unsupported"
|
||||
assert "只能回答加密货币" in data["answer"]["summary"]
|
||||
|
||||
|
||||
def test_chat_user_memory_tracks_last_symbol(monkeypatch):
|
||||
token = _login_user("chat-memory@example.com")
|
||||
user = auth_db.get_user_by_email("chat-memory@example.com")
|
||||
monkeypatch.setattr(chat_assistant, "fetch_binance_klines", lambda symbol, timeframe, limit=160: _fake_ohlcv())
|
||||
monkeypatch.setattr(chat_assistant, "_call_chat_llm", lambda message, context, history=None: {"status": "skipped", "error": "disabled"})
|
||||
|
||||
client = TestClient(web_server.app)
|
||||
client.cookies.set("altcoin_session", token)
|
||||
client.post("/api/chat/send", json={"message": "分析 LINK/USDT 技术面"})
|
||||
resp = client.post("/api/chat/send", json={"message": "那它现在追高风险大吗？"})
|
||||
|
||||
prefs = chat_assistant_db.get_user_preferences(user["id"])
|
||||
assert prefs["last_symbol"] == "LINK/USDT"
|
||||
assert resp.json()["symbol"] == "LINK/USDT"
|
||||
|
||||
|
||||
def test_chat_repairs_llm_mojibake_output(monkeypatch):
|
||||
token = _login_user("chat-mojibake@example.com")
|
||||
monkeypatch.setattr(chat_assistant, "fetch_binance_klines", lambda symbol, timeframe, limit=160: _fake_ohlcv())
|
||||
monkeypatch.setattr(
|
||||
chat_assistant,
|
||||
"_call_chat_llm",
|
||||
lambda message, context, history=None: {
|
||||
"status": "success",
|
||||
"model": "mock",
|
||||
"content": {
|
||||
"summary": "BTC/USDT å½åææ¯é¢åå¼±",
|
||||
"answer": "ç»è®ºï¼BTC ç线åå¼±",
|
||||
"evidence": ["è¯æ®ï¼1h ä½äº MA20"],
|
||||
},
|
||||
},
|
||||
)
|
||||
|
||||
client = TestClient(web_server.app)
|
||||
client.cookies.set("altcoin_session", token)
|
||||
resp = client.post("/api/chat/send", json={"message": "分析 BTC/USDT 技术面"})
|
||||
|
||||
assert resp.status_code == 200
|
||||
data = resp.json()
|
||||
content = data["assistant_message"]["content"]
|
||||
assert "当前技术面偏弱" in content["summary"]
|
||||
assert "结论：BTC 短线偏弱" in content["answer"]
|
||||
assert "证据：1h 低于 MA20" in content["evidence"][0]
|
||||
@ -35,8 +35,6 @@ def test_watch_only_recommendation_is_skipped_before_take_profit_push(monkeypatc
|
||||
"pnl_pct": 0.0,
|
||||
})
|
||||
monkeypatch.setattr(price_tracker, "apply_recommendation_state_transition", lambda *args, **kwargs: {"action_status": "观察", "push_required": False})
|
||||
pushed = []
|
||||
monkeypatch.setattr(price_tracker, "push_trade_action_update", lambda *args, **kwargs: pushed.append((args, kwargs)) or True)
|
||||
monkeypatch.setattr(price_tracker, "expire_old_recommendations", lambda: None)
|
||||
monkeypatch.setattr(price_tracker, "get_stats", lambda: {"active_count": 1})
|
||||
|
||||
@ -44,4 +42,3 @@ def test_watch_only_recommendation_is_skipped_before_take_profit_push(monkeypatc
|
||||
|
||||
assert output["tracked_count"] == 0
|
||||
assert output["results"][0]["status"] == "skipped_watch_only"
|
||||
assert pushed == []
|
||||
|
||||
Loading…
Reference in New Issue
Block a user