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npentrel
57 lines
1.8 KiB
Plaintext
57 lines
1.8 KiB
Plaintext
```python
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import time
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from langchain_core.utils.uuid import uuid7
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from langgraph.checkpoint.memory import InMemorySaver
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from langgraph.func import entrypoint, task
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from langgraph.types import Command, interrupt
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@task
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def write_essay(topic: str) -> str:
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"""Write an essay about the given topic."""
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time.sleep(1) # This is a placeholder for a long-running task.
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return f"An essay about topic: {topic}"
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@entrypoint(checkpointer=InMemorySaver())
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def workflow(topic: str) -> dict:
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"""A simple workflow that writes an essay and asks for a review."""
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essay = write_essay("cat").result()
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is_approved = interrupt(
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{
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# Any json-serializable payload provided to interrupt as argument.
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# It will be surfaced on the client side as an Interrupt when streaming data
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# from the workflow.
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"essay": essay, # The essay we want reviewed.
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# We can add any additional information that we need.
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# For example, introduce a key called "action" with some instructions.
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"action": "Please approve/reject the essay",
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}
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)
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return {
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"essay": essay, # The essay that was generated
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"is_approved": is_approved, # Response from HIL
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}
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thread_id = str(uuid7())
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config = {"configurable": {"thread_id": thread_id}}
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stream = workflow.stream_events("cat", config, version="v3")
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_ = stream.output
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print({"write_essay": stream.interrupts[0].value["essay"]})
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print({"__interrupt__": stream.interrupts})
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# {'write_essay': 'An essay about topic: cat'}
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# {
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# '__interrupt__': [
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# Interrupt(
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# value={
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# 'essay': 'An essay about topic: cat',
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# 'action': 'Please approve/reject the essay'
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# },
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# id='369d44b3d93d4a631ae583367ac6b5cc'
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# )
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# ]
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# }
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```
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