49 lines
1.8 KiB
Plaintext
49 lines
1.8 KiB
Plaintext
---
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description: Guidelines for using PocketFlow, Design Pattern, Workflow
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globs:
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alwaysApply: false
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---
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# Workflow
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Many real-world tasks are too complex for one LLM call. The solution is to **Task Decomposition**: decompose them into a [chain](../core_abstraction/flow.md) of multiple Nodes.
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> - You don't want to make each task **too coarse**, because it may be *too complex for one LLM call*.
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> - You don't want to make each task **too granular**, because then *the LLM call doesn't have enough context* and results are *not consistent across nodes*.
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>
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> You usually need multiple *iterations* to find the *sweet spot*. If the task has too many *edge cases*, consider using [Agents](mdc:./agent.md).
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{: .best-practice }
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### Example: Article Writing
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```python
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class GenerateOutline(Node):
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def prep(self, shared): return shared["topic"]
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def exec(self, topic): return call_llm(f"Create a detailed outline for an article about {topic}")
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def post(self, shared, prep_res, exec_res): shared["outline"] = exec_res
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class WriteSection(Node):
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def prep(self, shared): return shared["outline"]
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def exec(self, outline): return call_llm(f"Write content based on this outline: {outline}")
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def post(self, shared, prep_res, exec_res): shared["draft"] = exec_res
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class ReviewAndRefine(Node):
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def prep(self, shared): return shared["draft"]
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def exec(self, draft): return call_llm(f"Review and improve this draft: {draft}")
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def post(self, shared, prep_res, exec_res): shared["final_article"] = exec_res
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# Connect nodes
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outline = GenerateOutline()
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write = WriteSection()
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review = ReviewAndRefine()
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outline >> write >> review
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# Create and run flow
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writing_flow = Flow(start=outline)
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shared = {"topic": "AI Safety"}
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writing_flow.run(shared)
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```
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For *dynamic cases*, consider using [Agents](mdc:./agent.md). |