60 lines
2.0 KiB
Markdown
60 lines
2.0 KiB
Markdown
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# Task ID: 46
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**Title:** Implement LLM-based prompt selection service
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**Status:** done
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**Dependencies:** 45 ✓
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**Priority:** high
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**Description:** Create a service that uses the heavy LLM to intelligently select relevant prompts based on tags and the full prompt index, understanding synonyms and context.
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**Details:**
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1. Create `/src/mcplocal/src/services/llm-prompt-selector.service.ts`:
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```typescript
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export class LlmPromptSelectorService {
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constructor(
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private llmClient: LlmClient,
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private fastLlmClient: LlmClient | null,
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private tagMatcher: TagMatcherService // fallback
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) {}
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async selectPrompts(tags: string[], promptIndex: PromptIndex[]): Promise<{
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selected: Array<{ name: string; reason: string }>;
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priority10: PromptIndex[]; // Always included
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}> {
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// 1. Extract priority 10 prompts (always included)
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// 2. Generate missing summaries using fast LLM if needed
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// 3. Send to heavy LLM:
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const prompt = `
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Given these keywords: ${tags.join(', ')}
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And this prompt index:
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${promptIndex.map(p => `- ${p.name}: ${p.summary}`).join('\n')}
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Select the most relevant prompts for someone working on tasks
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related to these keywords. Consider synonyms and related concepts.
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Return a ranked JSON array: [{name: string, reason: string}]
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`;
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// 4. Parse LLM response
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// 5. On LLM error, fall back to tag matcher
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}
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}
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```
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2. Handle LLM timeouts and errors gracefully with fallback
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3. Validate LLM response format
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**Test Strategy:**
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- Unit test: Priority 10 prompts always returned regardless of LLM selection
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- Unit test: LLM called with correct prompt format (mock)
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- Unit test: LLM response parsed correctly
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- Unit test: Invalid LLM response falls back to tag matcher
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- Unit test: LLM timeout falls back to tag matcher
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- Unit test: Missing summaries trigger fast LLM generation
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- Unit test: No LLM available uses tag matcher directly
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- Integration test: End-to-end selection with mock LLM
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