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96 lines
2.4 KiB
Markdown
96 lines
2.4 KiB
Markdown
# LangGraph Checkpoint DuckDB
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Implementation of LangGraph CheckpointSaver that uses DuckDB.
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## Usage
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> [!IMPORTANT]
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> When using DuckDB checkpointers for the first time, make sure to call `.setup()` method on them to create required tables. See example below.
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```python
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from langgraph.checkpoint.duckdb import DuckDBSaver
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write_config = {"configurable": {"thread_id": "1", "checkpoint_ns": ""}}
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read_config = {"configurable": {"thread_id": "1"}}
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with DuckDBSaver.from_conn_string(":memory:") as checkpointer:
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# call .setup() the first time you're using the checkpointer
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checkpointer.setup()
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checkpoint = {
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"v": 1,
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"ts": "2024-07-31T20:14:19.804150+00:00",
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"id": "1ef4f797-8335-6428-8001-8a1503f9b875",
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"channel_values": {
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"my_key": "meow",
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"node": "node"
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},
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"channel_versions": {
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"__start__": 2,
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"my_key": 3,
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"start:node": 3,
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"node": 3
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},
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"versions_seen": {
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"__input__": {},
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"__start__": {
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"__start__": 1
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},
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"node": {
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"start:node": 2
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}
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},
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"pending_sends": [],
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}
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# store checkpoint
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checkpointer.put(write_config, checkpoint, {}, {})
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# load checkpoint
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checkpointer.get(read_config)
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# list checkpoints
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list(checkpointer.list(read_config))
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```
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### Async
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```python
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from langgraph.checkpoint.duckdb.aio import AsyncDuckDBSaver
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async with AsyncDuckDBSaver.from_conn_string(":memory:") as checkpointer:
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checkpoint = {
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"v": 1,
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"ts": "2024-07-31T20:14:19.804150+00:00",
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"id": "1ef4f797-8335-6428-8001-8a1503f9b875",
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"channel_values": {
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"my_key": "meow",
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"node": "node"
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},
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"channel_versions": {
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"__start__": 2,
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"my_key": 3,
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"start:node": 3,
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"node": 3
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},
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"versions_seen": {
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"__input__": {},
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"__start__": {
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"__start__": 1
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},
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"node": {
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"start:node": 2
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}
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},
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"pending_sends": [],
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}
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# store checkpoint
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await checkpointer.aput(write_config, checkpoint, {}, {})
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# load checkpoint
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await checkpointer.aget(read_config)
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# list checkpoints
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[c async for c in checkpointer.alist(read_config)]
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```
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