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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.
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1.3 KiB