7e5abd504f
Add three DBOS SDK skills with reference documentation for building reliable, fault-tolerant applications with durable workflows. Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
58 lines
1.5 KiB
Markdown
58 lines
1.5 KiB
Markdown
---
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title: Use Streams for Real-Time Data
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impact: MEDIUM
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impactDescription: Enables real-time progress and LLM streaming
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tags: streaming, write_stream, read_stream, realtime
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---
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## Use Streams for Real-Time Data
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Workflows can stream data in real-time to clients. Useful for LLM responses, progress reporting, or long-running results.
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**Incorrect (returning all data at end):**
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```python
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@DBOS.workflow()
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def llm_workflow(prompt):
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# Client waits for entire response
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response = call_llm(prompt)
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return response
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```
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**Correct (streaming results):**
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```python
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@DBOS.workflow()
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def llm_workflow(prompt):
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for chunk in call_llm_streaming(prompt):
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DBOS.write_stream("response", chunk)
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DBOS.close_stream("response")
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return "complete"
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# Client reads stream
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@app.get("/stream/{workflow_id}")
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def stream_response(workflow_id: str):
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def generate():
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for value in DBOS.read_stream(workflow_id, "response"):
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yield value
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return StreamingResponse(generate())
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```
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Stream characteristics:
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- Streams are immutable and append-only
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- Writes from workflows happen exactly-once
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- Writes from steps happen at-least-once (may duplicate on retry)
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- Streams auto-close when workflow terminates
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Close streams explicitly when done:
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```python
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@DBOS.workflow()
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def producer():
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DBOS.write_stream("data", {"step": 1})
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DBOS.write_stream("data", {"step": 2})
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DBOS.close_stream("data") # Signal completion
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```
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Reference: [Workflow Streaming](https://docs.dbos.dev/python/tutorials/workflow-communication#workflow-streaming)
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