a4069d5755
Backend (internal/llm): backend-agnostic LLMClient interface + factory
with vLLM (OpenAI-compat) and Ollama (native) clients, each Complete +
Stream. prompts.go holds the checkpoint and Ask Petal templates;
checkpoint.go salvages JSON from model output (brace-matched), enforces a
per-doc 30s RateLimiter, and truncates the doc to a latency cap.
internal/suggestions: POST /api/docs/:id/check runs a checkpoint and
replaces the doc's pending suggestions in one tx (accepted/rejected kept
as history); GET /api/docs/:id/suggestions lists pending;
POST /api/suggestions/:id/{accept,dismiss} resolves one. Throttled checks
return the current set rather than erroring.
Frontend: useCheckpoint (4s debounce, loads existing on open, stale-guard
tokens); SuggestionHighlight renders ProseMirror decorations re-anchored
by the `original` string on every doc change (not stored marks), with
precise textblock-offset→PM-position mapping; SuggestionCard shows the
type tag + diff + explanation and applies the replacement in-editor on
accept; breathing rose checkpoint dot in the StatusBar; fade-float +
breathe animations.
Tests: llm parse/rate-limit/truncate; suggestions full flow + rate-limit
over httptest with a stub client. Smoke-tested end-to-end against a fake
vLLM endpoint (anchoring verified) and the LLM-unreachable 502 path.
Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd
64 lines
2.7 KiB
Go
64 lines
2.7 KiB
Go
package llm
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import "fmt"
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// checkpointSystemPrompt is the grammar-checkpoint instruction. It asks for
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// strict JSON (no fences, no preamble) so Complete's output parses directly.
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const checkpointSystemPrompt = `You are a warm, encouraging writing assistant helping someone who speaks English as a second language. ` +
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`Analyze the text below and identify up to 5 issues: grammar errors, unnatural phrasing, ` +
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`incorrect idiom usage, or unclear sentences that are common ESL patterns.
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Be specific, friendly, and explain WHY each suggestion improves the writing.
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Respond ONLY with valid JSON. No preamble, no markdown fences. Format:
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{
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"suggestions": [
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{
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"original": "exact text from the document that needs fixing",
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"replacement": "corrected version",
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"explanation": "friendly one-sentence explanation",
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"type": "grammar|phrasing|idiom|clarity"
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}
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]
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}
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If the writing looks good, return: {"suggestions": []}`
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// CheckpointMessages builds the message array for a grammar checkpoint over the
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// given (already-truncated) document text.
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func CheckpointMessages(contentText string) []Message {
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return []Message{
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{Role: "system", Content: checkpointSystemPrompt},
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{Role: "user", Content: contentText},
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}
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}
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// askPetalSystemTemplate is the Ask Petal tutor prompt. The suggestion context
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// is interpolated in; the user's own messages are appended after this system
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// turn by the caller.
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const askPetalSystemTemplate = `You are Petal, a warm and patient English writing tutor helping someone who is learning English ` +
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`as a second language. You are currently discussing a specific writing suggestion.
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Suggestion context:
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- Original text: "%s"
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- Suggested replacement: "%s"
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- Issue type: %s
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- Initial explanation: "%s"
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- Surrounding paragraph: "%s"
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The user wants to understand this suggestion better. Detect the language of the user's message ` +
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`and respond in that same language. If they write in Mandarin Chinese, respond entirely in ` +
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`Mandarin. If they write in English, respond in English. Never mix languages in a single response.
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Explain clearly and kindly. Use simple language appropriate to the user's message. Give examples ` +
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`when helpful. If they ask "why" (or "为什么"), explain the grammar rule or idiom behind it. ` +
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`If they suggest an alternative phrasing, evaluate it honestly.
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Keep responses concise (2-4 sentences). This is a chat, not an essay. Be encouraging — ` +
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`learning a language is hard and they're doing great.`
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// AskPetalSystemPrompt fills the tutor prompt with one suggestion's context.
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func AskPetalSystemPrompt(original, replacement, suggestionType, explanation, paragraph string) string {
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return fmt.Sprintf(askPetalSystemTemplate, original, replacement, suggestionType, explanation, paragraph)
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}
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