feat: portfolio context injection + AI call log viewer

Portfolio context (portfolio_context.py):
- get_open_trades_with_moves(): fetches open trades + 1d/5d yfinance price moves
- get_portfolio_concentration(): counts by asset_class
- build_portfolio_context_block(): formatted prompt block with strict AI instructions
  (no double positions, flag contradictions, avoid overweight classes)

AI call logging:
- ai_call_logs table in DB (run_id, call_type, system/user prompt, response, tokens, ms)
- _chat() now accepts log_meta dict → saves call to DB non-blocking after each call
- suggest and score_batch calls pass run_id + call_type for full traceability

auto_cycle.py:
- Builds portfolio context before snapshot and both AI calls
- Context snapshot now includes portfolio_open_positions key

SystemLogs.tsx:
- "Contexte IA" tab gains sub-tabs: Contexte / Appels IA
- AiCallRow: expandable with 3 panes (user prompt / system prompt / response)
  shows model, tokens breakdown, duration, call type badge

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

backend/services/database.py

@@ -407,6 +407,26 @@ def init_db():
         context_json TEXT NOT NULL
     )""")
 
+    c.execute("""CREATE TABLE IF NOT EXISTS ai_call_logs (
+        id INTEGER PRIMARY KEY AUTOINCREMENT,
+        run_id TEXT NOT NULL,
+        call_type TEXT NOT NULL,
+        pattern_id TEXT,
+        pattern_name TEXT,
+        system_prompt TEXT,
+        user_prompt TEXT,
+        response_json TEXT,
+        model TEXT DEFAULT 'gpt-4o',
+        tokens_prompt INTEGER DEFAULT 0,
+        tokens_completion INTEGER DEFAULT 0,
+        duration_ms INTEGER DEFAULT 0,
+        called_at TEXT NOT NULL DEFAULT (datetime('now'))
+    )""")
+    try:
+        c.execute("CREATE INDEX IF NOT EXISTS idx_acl_run ON ai_call_logs(run_id, called_at DESC)")
+    except Exception:
+        pass
+
     c.execute("""CREATE TABLE IF NOT EXISTS news_price_snapshots (
         id INTEGER PRIMARY KEY AUTOINCREMENT,
         article_hash TEXT NOT NULL,
@@ -2239,6 +2259,60 @@ def list_cycle_context_snapshots(limit: int = 30) -> list:
     return [{"run_id": r["run_id"], "ts": r["ts"]} for r in rows]
 
 
+# ── AI Call Logs ──────────────────────────────────────────────────────────────
+
+def save_ai_call_log(
+    run_id: str,
+    call_type: str,
+    system_prompt: str,
+    user_prompt: str,
+    response_json: str,
+    model: str = "gpt-4o",
+    tokens_prompt: int = 0,
+    tokens_completion: int = 0,
+    duration_ms: int = 0,
+    pattern_id: str = None,
+    pattern_name: str = None,
+) -> None:
+    import json as _json
+    conn = get_conn()
+    conn.execute(
+        """INSERT INTO ai_call_logs
+           (run_id, call_type, pattern_id, pattern_name, system_prompt, user_prompt,
+            response_json, model, tokens_prompt, tokens_completion, duration_ms)
+           VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)""",
+        (run_id, call_type, pattern_id, pattern_name,
+         system_prompt[:8000],   # cap system prompt at 8KB
+         user_prompt[:80000],    # cap user prompt at 80KB
+         response_json[:50000],  # cap response at 50KB
+         model, tokens_prompt, tokens_completion, duration_ms)
+    )
+    conn.commit()
+    conn.close()
+
+
+def get_ai_call_logs(run_id: str) -> list:
+    import json as _json
+    conn = get_conn()
+    rows = conn.execute(
+        """SELECT id, call_type, pattern_id, pattern_name, system_prompt, user_prompt,
+                  response_json, model, tokens_prompt, tokens_completion, duration_ms, called_at
+           FROM ai_call_logs WHERE run_id = ? ORDER BY called_at ASC""",
+        (run_id,)
+    ).fetchall()
+    conn.close()
+    result = []
+    for r in rows:
+        d = dict(r)
+        # Try to parse response_json for display
+        try:
+            d["response"] = _json.loads(d["response_json"]) if d["response_json"] else None
+        except Exception:
+            d["response"] = d["response_json"]
+        result.append(d)
+    return result
+
+
 # ── News Price Snapshots (Phase 4 — Price Discovery) ─────────────────────────
 
 def save_news_price_snapshot(