Add example

config/config.toml

@@ -158,11 +158,31 @@ filter = "(now() - item.Timestamp).Hours() < 168"
 # #   embedding: recommend by Euclidean distance of embeddings.
 # #   tags: recommend by number of common tags.
 # #   users: recommend by number of common users.
+# #   chat: recommend by chat completion model.
 # type = "embedding"
 
 # # The column of the item embeddings. Leave blank if type is "users".
 # column = "item.Labels.embedding"
 
+# [[recommend.item-to-item]]
+
+# # The name of the item-to-item recommender.
+# name = "chat_recommend"
+
+# # The type of the item-to-item recommender.
+# type = "chat"
+
+# # The column of the item embeddings. Leave blank if type is "users".
+# column = "item.Labels.embedding"
+
+# # The prompt for the chat completion model.
+# prompt = """
+# This is the description of GitHub repository https://github.com/{{ item.ItemId | replace(':','/') }}:
+# {{ item.Comment }}
+# Please find some similar repositores on GitHub and provide a brief description for each of them.
+# The output should be a JSON array.
+# """
+
 [recommend.user_neighbors]
 
 # The type of neighbors for users. There are three types:

logics/item_to_item.go

@@ -430,6 +430,8 @@ func (g *chatItemToItem) PopAll(i int) []cache.Score {
 		return nil
 	}
 	messages := parseMessage(resp.Choices[0].Message.Content)
+	log.Logger().Debug("chat based item-to-item recommendation",
+		zap.String("prompt", buf.String()), zap.Strings("response", messages))
 	// message embedding
 	embeddings := make([][]float32, len(messages))
 	for i, message := range messages {

storage/cache/database.go

@@ -72,10 +72,6 @@ const (
 	UserToUserUpdateTime = "user-to-user_update_time"
 	Neighbors            = "neighbors"
 
-	Chat           = "chat"
-	ChatDigest     = "chat_digest"
-	ChatUpdateTime = "chat_update_time"
-
 	// ItemCategories is the set of item categories. The format of key:
 	//	Global item categories - item_categories
 	ItemCategories = "item_categories"