Mikkel Georgsen
8c03780230
- internal/ai/types.go: IntakeRequest, IntakeResult, TierConfig, AIConfig domain types - internal/ai/client.go: AIClient interface + TierClient (go-openai, BaseURL tier-routing) - internal/ai/mock.go: MockAIClient test double with HighConfidenceResult/LowConfidenceResult fixtures - internal/ai/prompts/intake.go: BuildIntakePrompt() JSON-extraction prompt template - internal/config/config.go: Config.AI AIConfig field, tier defaults, env bindings, ai_config.json merge - ai_config.json: template config with placeholder Tier2 API key - .gitignore: add ai_config.local.json pattern for real keys (T-02-01 mitigation) - All tests pass: TestMockAIClient, TestMockAIClientError, TestTierClientConstruction, TestAIConfigDefaults
98 lines
2.9 KiB
Go
98 lines
2.9 KiB
Go
package ai
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import (
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"context"
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"encoding/json"
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"fmt"
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"time"
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openai "github.com/sashabaranov/go-openai"
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"git.georgsen.dk/hwlab/internal/ai/prompts"
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)
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// AIClient is the single abstraction over any OpenAI-compatible inference backend.
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// Production: TierClient wrapping sashabaranov/go-openai.
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// Tests: MockAIClient with canned responses.
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type AIClient interface {
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AnalyzePhotos(ctx context.Context, req IntakeRequest) (*IntakeResult, error)
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}
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// TierClient is the production AIClient backed by go-openai.
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type TierClient struct {
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client *openai.Client
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model string
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timeout time.Duration
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}
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// NewTierClient creates a TierClient from a TierConfig.
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// BaseURL is set directly on the openai.ClientConfig — this is the tier-routing mechanism.
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func NewTierClient(cfg TierConfig) *TierClient {
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oCfg := openai.DefaultConfig(cfg.APIKey)
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oCfg.BaseURL = cfg.BaseURL
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timeout := time.Duration(cfg.TimeoutSeconds) * time.Second
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if timeout == 0 {
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timeout = 30 * time.Second
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}
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return &TierClient{
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client: openai.NewClientWithConfig(oCfg),
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model: cfg.Model,
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timeout: timeout,
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}
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}
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// AnalyzePhotos sends 1-3 base64-encoded photos to the configured model and
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// parses the structured JSON response into an IntakeResult.
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// Falls back gracefully: if the model returns malformed JSON, returns a
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// zero-confidence IntakeResult (not an error) so the orchestrator can escalate.
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func (c *TierClient) AnalyzePhotos(ctx context.Context, req IntakeRequest) (*IntakeResult, error) {
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// Build vision message parts: text prompt first, then image URLs
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parts := []openai.ChatMessagePart{
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{
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Type: openai.ChatMessagePartTypeText,
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Text: buildIntakePromptWithCount(len(req.PhotosBase64)),
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},
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}
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for _, b64 := range req.PhotosBase64 {
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parts = append(parts, openai.ChatMessagePart{
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Type: openai.ChatMessagePartTypeImageURL,
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ImageURL: &openai.ChatMessageImageURL{
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URL: b64,
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Detail: openai.ImageURLDetailAuto,
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},
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})
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}
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tctx, cancel := context.WithTimeout(ctx, c.timeout)
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defer cancel()
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resp, err := c.client.CreateChatCompletion(tctx, openai.ChatCompletionRequest{
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Model: c.model,
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Messages: []openai.ChatCompletionMessage{
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{Role: openai.ChatMessageRoleUser, MultiContent: parts},
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},
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})
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if err != nil {
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return nil, fmt.Errorf("chat completion: %w", err)
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}
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if len(resp.Choices) == 0 {
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return nil, fmt.Errorf("no choices in response")
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}
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content := resp.Choices[0].Message.Content
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var result IntakeResult
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if err := json.Unmarshal([]byte(content), &result); err != nil {
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// JSON parse failure — return zero-confidence result so orchestrator escalates
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return &IntakeResult{
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AINotes: fmt.Sprintf("JSON parse failed: %v | raw: %.200s", err, content),
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Confidence: 0.0,
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ConfidenceNote: "model returned non-JSON response",
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}, nil
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}
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return &result, nil
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}
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// buildIntakePromptWithCount is a package-internal shim to the prompts package.
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func buildIntakePromptWithCount(n int) string {
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return prompts.BuildIntakePrompt(n)
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}
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