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.

pyproject.toml

@@ -16,6 +16,7 @@ dependencies = [
     "langchain-google-genai>=4.0.0",
     "langchain-openai>=0.3.23",
     "langgraph>=0.4.8",
+    "langgraph-checkpoint-sqlite>=2.0.0",
     "pandas>=2.3.0",
     "parsel>=1.10.0",
     "pytz>=2025.2",