Implement RAG-based recommenders

Author: zhenghaoz

config/config.go

@@ -62,6 +62,7 @@ type Config struct {
 	Tracing      TracingConfig      `mapstructure:"tracing"`
 	Experimental ExperimentalConfig `mapstructure:"experimental"`
 	OIDC         OIDCConfig         `mapstructure:"oidc"`
+	OpenAI       OpenAIConfig       `mapstructure:"openai"`
 }
 
 // DatabaseConfig is the configuration for the database.
@@ -213,6 +214,13 @@ type OIDCConfig struct {
 	RedirectURL  string `mapstructure:"redirect_url" validate:"omitempty,endswith=/callback/oauth2"`
 }
 
+type OpenAIConfig struct {
+	BaseURL             string `mapstructure:"base_url"`
+	AuthToken           string `mapstructure:"auth_token"`
+	ChatCompletionModel string `mapstructure:"chat_completion_model"`
+	EmbeddingsModel     string `mapstructure:"embeddings_model"`
+}
+
 func GetDefaultConfig() *Config {
 	return &Config{
 		Database: DatabaseConfig{

config/config.toml

@@ -309,3 +309,17 @@ client_secret = ""
 # Gorse dashboard URL and "/callback/oauth2". For example, if the Gorse dashboard URL is 
 # http://localhost:8088, the redirect URL should be: http://localhost:8088/callback/oauth2
 redirect_url = ""
+
+[openai]
+
+# Base URL of OpenAI API.
+base_url = "http://localhost:11434/v1"
+
+# API key of OpenAI API.
+auth_token = "ollama"
+
+# Name of chat completion model.
+chat_completion_model = "qwen2.5"
+
+# Name of embeddings model.
+embeddings_model = "mxbai-embed-large"

config/config_test.go

@@ -156,6 +156,11 @@ func TestUnmarshal(t *testing.T) {
 			assert.Equal(t, "client_id", config.OIDC.ClientID)
 			assert.Equal(t, "client_secret", config.OIDC.ClientSecret)
 			assert.Equal(t, "http://localhost:8088/callback/oauth2", config.OIDC.RedirectURL)
+			// [openai]
+			assert.Equal(t, "http://localhost:11434/v1", config.OpenAI.BaseURL)
+			assert.Equal(t, "ollama", config.OpenAI.AuthToken)
+			assert.Equal(t, "qwen2.5", config.OpenAI.ChatCompletionModel)
+			assert.Equal(t, "mxbai-embed-large", config.OpenAI.EmbeddingsModel)
 		})
 	}
 }