feat: add LangGraph checkpoint resume for crash recovery (#594)

Long analyses can take many minutes; a crash or interruption forced users
to re-run from scratch and re-pay every LLM call.  This adds an opt-in
checkpoint layer backed by per-ticker SQLite databases so the graph
resumes from the last successful node.

How to use:
- CLI:    tradingagents analyze --checkpoint
- CLI:    tradingagents analyze --clear-checkpoints
- Python: config["checkpoint_enabled"] = True

Lifecycle:
- propagate() recompiles the graph with a SqliteSaver when enabled and
  injects a deterministic thread_id derived from ticker+date so the
  same ticker+date resumes while a different date starts fresh.
- On successful completion the per-thread checkpoint rows are cleared.
- The context manager is closed in a try/finally so a crash never
  leaks the SQLite connection or leaves the graph in checkpoint mode.

Storage: ~/.tradingagents/cache/checkpoints/<TICKER>.db
(override via TRADINGAGENTS_CACHE_DIR).

The checkpointer module is new (tradingagents/graph/checkpointer.py)
and the GraphSetup now returns the uncompiled workflow so it can be
recompiled with a saver when needed.

Adds langgraph-checkpoint-sqlite>=2.0.0 dependency. 3 new tests verify
the crash/resume cycle and that a different date starts fresh.

tests/test_memory_log.py

@@ -629,7 +629,9 @@ class TestLegacyRemoval:
             create_portfolio_manager(mock_llm, memory=MagicMock())
 
     def test_full_pipeline_no_regression(self, tmp_path):
-        """propagate() completes without AttributeError after legacy cleanup."""
+        """propagate() completes and stores the decision after the redesign."""
+        import functools
+
         fake_state = {
             "final_trade_decision": "Rating: Buy\nBuy NVDA.",
             "company_of_interest": "NVDA",
@@ -660,6 +662,11 @@ class TestLegacyRemoval:
         mock_graph.propagator.create_initial_state.return_value = fake_state
         mock_graph.propagator.get_graph_args.return_value = {}
         mock_graph.signal_processor.process_signal.return_value = "Buy"
+        # Bind the real _run_graph so propagate's call to self._run_graph executes
+        # the actual write path instead of the auto-MagicMock.
+        mock_graph._run_graph = functools.partial(
+            TradingAgentsGraph._run_graph, mock_graph
+        )
         TradingAgentsGraph.propagate(mock_graph, "NVDA", "2026-01-10")
         entries = mock_graph.memory_log.load_entries()
         assert len(entries) == 1