chat_service_integration_test.go

@@ -32,9 +32,6 @@ func (m *mockLLM) DisambiguateBestMatch(ctx context.Context, msg string, candida
 func (m *mockLLM) GetEmbeddings(ctx context.Context, input string) ([]float64, error) {
 	return m.embeddings, m.embeddingErr
 }
-func (m *mockLLM) TranslateToEnglish(ctx context.Context, msg string) (string, error) {
-	return msg, nil
-}
 
 // --- Test VisitDB ---
 type testVisitDB struct {

config.go

@@ -8,7 +8,6 @@ type Config struct {
 	LLM struct {
 		ExtractKeywordsPrompt string `yaml:"extract_keywords_prompt"`
 		DisambiguatePrompt    string `yaml:"disambiguate_prompt"`
-		TranslatePrompt       string `yaml:"translate_prompt"`
 	} `yaml:"llm"`
 }
 

config/config.yaml

@@ -1,4 +1,3 @@
 llm:
   extract_keywords_prompt: "You will extract structured data from the user input. Input text: {{.Message}}. Return ONLY valid minified JSON object with keys: translate (English translation of input), keyword (array of 3-5 concise English veterinary-related keywords derived strictly from the input), animal (animal mentioned or 'unknown'). Example: {\"translate\":\"dog has diarrhea\",\"keyword\":[\"diarrhea\",\"digestive\"],\"animal\":\"dog\"}. Do not add extra text, markdown, or quotes outside JSON."
   disambiguate_prompt: "Given candidate visit entries (JSON array): {{.Entries}} and user message: {{.Message}} choose the best matching visit's ID. Return ONLY JSON: {\"visitReason\":\"<one of the candidate IDs or empty string if none>\"}. No other text."
-  translate_prompt: "Translate the following veterinary-related sentence to English. Input: '{{.Message}}'. Return ONLY the English translation, no extra text, no markdown, no quotes. If already English, return as is."

handlechat_integration_test.go

@@ -33,9 +33,6 @@ func (m *mockHandleChatLLM) DisambiguateBestMatch(ctx context.Context, msg strin
 func (m *mockHandleChatLLM) GetEmbeddings(ctx context.Context, input string) ([]float64, error) {
 	return m.embeddings, m.embeddingErr
 }
-func (m *mockHandleChatLLM) TranslateToEnglish(ctx context.Context, msg string) (string, error) {
-	return msg, nil
-}
 
 // mapChatRepo is an in-memory implementation of ChatRepositoryAPI for tests.
 type mapChatRepo struct {

llm.go

@@ -15,7 +15,6 @@ type LLMClientAPI interface {
 	ExtractKeywords(ctx context.Context, message string) (map[string]interface{}, error)
 	DisambiguateBestMatch(ctx context.Context, message string, candidates []Visit) (string, error)
 	GetEmbeddings(ctx context.Context, input string) ([]float64, error)
-	TranslateToEnglish(ctx context.Context, message string) (string, error)
 }
 
 // --- Format Utilities ---

llm_test.go

@@ -47,10 +47,6 @@ func (m *MockLLMClient) GetEmbeddings(ctx context.Context, input string) ([]floa
 	return []float64{0.1, 0.2, 0.3}, nil
 }
 
-func (m *MockLLMClient) TranslateToEnglish(ctx context.Context, message string) (string, error) {
-	return message, nil
-}
-
 func TestNewLLMClientFromEnv(t *testing.T) {
 	tests := []struct {
 		name         string

migrations/0003_create_sentence_embeddings_table.up.sql

@@ -1,16 +0,0 @@
--- +goose Up
-CREATE EXTENSION IF NOT EXISTS vector;
-
-CREATE TABLE sentence_embeddings (
-    id SERIAL PRIMARY KEY,
-    visit_id INTEGER NOT NULL,
-    sentence TEXT NOT NULL,
-    translated TEXT,
-    embeddings VECTOR(1536) NOT NULL,
-    created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP
-);
-
--- +goose Down
-DROP TABLE IF EXISTS sentence_embeddings;
-DROP EXTENSION IF EXISTS vector;
-

ollama_client.go

@@ -166,19 +166,3 @@ func (llm *OllamaClient) GetEmbeddings(ctx context.Context, input string) ([]flo
 	}
 	return nil, fmt.Errorf("unrecognized embedding response: %.200s", string(raw))
 }
-
-func (llm *OllamaClient) TranslateToEnglish(ctx context.Context, message string) (string, error) {
-	prompt, err := renderPrompt(appConfig.LLM.TranslatePrompt, map[string]string{"Message": message})
-	if err != nil {
-		logrus.WithError(err).Error("[CONFIG] Failed to render Translate prompt")
-		return "", err
-	}
-	logrus.WithField("prompt", prompt).Info("[LLM] TranslateToEnglish prompt")
-
-	resp, err := llm.ollamaCompletion(ctx, prompt, nil)
-	logrus.WithFields(logrus.Fields{"response": resp, "err": err}).Info("[LLM] TranslateToEnglish response")
-	if err != nil {
-		return resp, err
-	}
-	return strings.TrimSpace(resp), nil
-}

openai_client.go

@@ -198,19 +198,3 @@ func (llm *OpenAIClient) GetEmbeddings(ctx context.Context, input string) ([]flo
 	}
 	return nil, fmt.Errorf("unrecognized embedding response: %.200s", string(raw))
 }
-
-func (llm *OpenAIClient) TranslateToEnglish(ctx context.Context, message string) (string, error) {
-	prompt, err := renderPrompt(appConfig.LLM.TranslatePrompt, map[string]string{"Message": message})
-	if err != nil {
-		logrus.WithError(err).Error("[CONFIG] Failed to render Translate prompt")
-		return "", err
-	}
-	logrus.WithField("prompt", prompt).Info("[LLM] TranslateToEnglish prompt")
-
-	resp, err := llm.openAICompletion(ctx, prompt, nil)
-	logrus.WithFields(logrus.Fields{"response": resp, "err": err}).Info("[LLM] TranslateToEnglish response")
-	if err != nil {
-		return resp, err
-	}
-	return strings.TrimSpace(resp), nil
-}