增加大模型

backend/app/db.py

@@ -96,6 +96,17 @@ def init_db() -> None:
                 mark_price REAL NOT NULL DEFAULT 0,
                 updated_at TEXT NOT NULL
             );
+
+            CREATE TABLE IF NOT EXISTS llm_interpretations (
+                id INTEGER PRIMARY KEY AUTOINCREMENT,
+                symbol TEXT NOT NULL,
+                batch_id TEXT NOT NULL,
+                content TEXT NOT NULL,
+                created_at TEXT NOT NULL
+            );
+
+            CREATE INDEX IF NOT EXISTS idx_llm_symbol_batch
+                ON llm_interpretations(symbol, batch_id);
             """
         )
 
@@ -353,6 +364,87 @@ def save_funding_current_bulk(data: dict[str, dict[str, Any]]) -> None:
             )
 
 
+def save_llm_interpretation(symbol: str, batch_id: str, content: str) -> None:
+    with get_conn() as conn:
+        conn.execute(
+            """
+            INSERT INTO llm_interpretations (symbol, batch_id, content, created_at)
+            VALUES (?, ?, ?, ?)
+            """,
+            (symbol.upper(), batch_id, content, datetime.now().isoformat()),
+        )
+
+
+def get_llm_interpretations(batch_id: str | None = None, limit: int = 50) -> list[dict[str, Any]]:
+    with get_conn() as conn:
+        if batch_id:
+            rows = conn.execute(
+                """
+                SELECT symbol, batch_id, content, created_at
+                FROM llm_interpretations
+                WHERE batch_id = ?
+                ORDER BY id DESC
+                LIMIT ?
+                """,
+                (batch_id, limit),
+            ).fetchall()
+        else:
+            rows = conn.execute(
+                """
+                SELECT symbol, batch_id, content, created_at
+                FROM llm_interpretations
+                WHERE batch_id = (
+                    SELECT batch_id FROM llm_interpretations ORDER BY id DESC LIMIT 1
+                )
+                ORDER BY id ASC
+                LIMIT ?
+                """,
+                (limit,),
+            ).fetchall()
+    return [
+        {
+            "symbol": r["symbol"],
+            "batch_id": r["batch_id"],
+            "content": r["content"],
+            "created_at": r["created_at"],
+        }
+        for r in rows
+    ]
+
+
+def get_llm_interpretation(symbol: str, batch_id: str | None = None) -> dict[str, Any] | None:
+    sym = symbol.upper()
+    with get_conn() as conn:
+        if batch_id:
+            row = conn.execute(
+                """
+                SELECT symbol, batch_id, content, created_at
+                FROM llm_interpretations
+                WHERE symbol = ? AND batch_id = ?
+                ORDER BY id DESC LIMIT 1
+                """,
+                (sym, batch_id),
+            ).fetchone()
+        else:
+            row = conn.execute(
+                """
+                SELECT symbol, batch_id, content, created_at
+                FROM llm_interpretations
+                WHERE symbol = ?
+                ORDER BY id DESC LIMIT 1
+                """,
+                (sym,),
+            ).fetchone()
+    if not row:
+        return None
+    return {
+        "symbol": row["symbol"],
+        "batch_id": row["batch_id"],
+        "content": row["content"],
+        "created_at": row["created_at"],
+    }
+
+
 def was_pushed_today(period_start: str, period_end: str) -> bool:
     with get_conn() as conn:
         row = conn.execute(