mirror of
https://github.com/langchain-ai/langgraph.git
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25dce1ff583020f570fdbfb882794e707519da86
permchain
Get started
pip install permchain
Usage
from permchain import Pregel, channels
value = channels.LastValue[str]("value")
grow_value = (
Pregel.subscribe_to(value)
| (lambda x: x + x)
| Pregel.send_to({value: lambda x: x if len(x) < 10 else None})
)
pubsub = Pregel(grow_value, input=value, output=value)
assert pubsub.invoke("a") == "aaaaaaaa"
Check examples for more examples.
Near-term Roadmap
- Iterate on API
- do we want api to receive output from multiple channels in invoke()
- do we want api to send input to multiple channels in invoke()
- Implement checkpointing
- Save checkpoints at end of each step
- Load checkpoint at start of invocation
- API to specify storage backend and save key
- Add more examples
- human in the loop
- combine documents
- agent executor
- run over dataset
- Fault tolerance
- Retry individual processes in a step
- Retry entire step?
Description
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agentsaiai-agentschatgptdeepagentsenterpriseframeworkgeminigenerative-ailangchainlanggraphllmmultiagentopen-sourceopenaipydanticpythonrag
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