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>
56 lines
1.3 KiB
Markdown
56 lines
1.3 KiB
Markdown
---
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title: Rate Limit Queue Execution
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impact: HIGH
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impactDescription: Prevents hitting API rate limits
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tags: queue, rate-limit, api, throttle
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---
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## Rate Limit Queue Execution
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Use rate limits when working with rate-limited APIs (like LLM APIs). Limits are global across all processes.
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**Incorrect (no rate limiting):**
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```python
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queue = Queue("llm_tasks")
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@DBOS.step()
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def call_llm(prompt):
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# May hit rate limits if too many calls
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return openai.chat.completions.create(...)
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```
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**Correct (with rate limit):**
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```python
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# Max 50 tasks started per 30 seconds
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queue = Queue("llm_tasks", limiter={"limit": 50, "period": 30})
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@DBOS.step()
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def call_llm(prompt):
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return openai.chat.completions.create(...)
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@DBOS.workflow()
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def process_prompts(prompts):
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handles = []
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for prompt in prompts:
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# Queue enforces rate limit
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handle = queue.enqueue(call_llm, prompt)
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handles.append(handle)
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return [h.get_result() for h in handles]
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```
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Rate limit parameters:
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- `limit`: Maximum number of functions to start in the period
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- `period`: Time period in seconds
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Rate limits can be combined with concurrency limits:
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```python
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queue = Queue("api_tasks",
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worker_concurrency=5,
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limiter={"limit": 100, "period": 60})
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```
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Reference: [Rate Limiting](https://docs.dbos.dev/python/tutorials/queue-tutorial#rate-limiting)
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