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74 lines
2.8 KiB
Markdown
74 lines
2.8 KiB
Markdown
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---
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title: Write Task-Specific Routing Preference Descriptions
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impact: HIGH
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impactDescription: Vague preference descriptions cause Plano's internal router LLM to misclassify requests, routing expensive tasks to cheap models and vice versa
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tags: routing, model-selection, preferences, llm-routing
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---
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## Write Task-Specific Routing Preference Descriptions
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Plano's `plano_orchestrator_v1` router uses a 1.5B preference-aligned LLM to classify incoming requests against your `routing_preferences` descriptions. It routes the request to the first provider whose preferences match. Description quality directly determines routing accuracy.
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**Incorrect (vague, overlapping descriptions):**
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```yaml
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model_providers:
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- model: openai/gpt-4o-mini
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access_key: $OPENAI_API_KEY
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default: true
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routing_preferences:
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- name: simple
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description: easy tasks # Too vague — what is "easy"?
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- model: openai/gpt-4o
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access_key: $OPENAI_API_KEY
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routing_preferences:
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- name: hard
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description: hard tasks # Too vague — overlaps with "easy"
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```
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**Correct (specific, distinct task descriptions):**
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```yaml
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model_providers:
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- model: openai/gpt-4o-mini
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access_key: $OPENAI_API_KEY
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default: true
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routing_preferences:
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- name: summarization
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description: >
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Summarizing documents, articles, emails, or meeting transcripts.
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Extracting key points, generating TL;DR sections, condensing long text.
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- name: classification
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description: >
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Categorizing inputs, sentiment analysis, spam detection,
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intent classification, labeling structured data fields.
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- name: translation
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description: >
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Translating text between languages, localization tasks.
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- model: openai/gpt-4o
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access_key: $OPENAI_API_KEY
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routing_preferences:
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- name: code_generation
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description: >
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Writing new functions, classes, or modules from scratch.
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Implementing algorithms, boilerplate generation, API integrations.
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- name: code_review
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description: >
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Reviewing code for bugs, security vulnerabilities, performance issues.
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Suggesting refactors, explaining complex code, debugging errors.
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- name: complex_reasoning
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description: >
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Multi-step math problems, logical deduction, strategic planning,
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research synthesis requiring chain-of-thought reasoning.
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```
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**Key principles for good preference descriptions:**
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- Use concrete action verbs: "writing", "reviewing", "translating", "summarizing"
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- List 3–5 specific sub-tasks or synonyms for each preference
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- Ensure preferences across providers are mutually exclusive in scope
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- Test with representative queries using `planoai trace` and `--where` filters to verify routing decisions
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Reference: https://github.com/katanemo/archgw
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