mirror of
https://github.com/redis/go-redis.git
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5fdc947723
* add vector specific attributes in ftinfo * safer parsing * try to fix tests * oops, should test agains resp2 only * fix asserts * skip test for RE
371 lines
12 KiB
Go
371 lines
12 KiB
Go
package redis
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import (
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"testing"
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)
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// TestParseFTInfo tests the parseFTInfo function with a comprehensive FT.INFO response
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// This test uses the actual response structure from Redis with vector fields
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func TestParseFTInfo(t *testing.T) {
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// This is the data structure that would be returned by Redis for FT.INFO
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// Based on the redis-cli output provided by the user
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data := map[string]interface{}{
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"index_name": "rand:42d1f2820b3048b6bc783d4dcdb9094a",
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"index_options": []interface{}{},
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"index_definition": []interface{}{
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"key_type", "HASH",
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"prefixes", []interface{}{"rand:42d1f2820b3048b6bc783d4dcdb9094a"},
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"default_score", "1",
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"indexes_all", false,
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},
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"attributes": []interface{}{
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// prompt field (TEXT)
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[]interface{}{
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"identifier", "prompt",
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"attribute", "prompt",
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"type", "TEXT",
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"WEIGHT", "1",
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},
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// response field (TEXT)
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[]interface{}{
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"identifier", "response",
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"attribute", "response",
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"type", "TEXT",
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"WEIGHT", "1",
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},
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// exact_digest field (TAG)
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[]interface{}{
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"identifier", "exact_digest",
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"attribute", "exact_digest",
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"type", "TAG",
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"SEPARATOR", ",",
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},
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// prompt_vector field (VECTOR)
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[]interface{}{
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"identifier", "prompt_vector",
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"attribute", "prompt_vector",
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"type", "VECTOR",
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"algorithm", "HNSW",
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"data_type", "FLOAT32",
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"dim", int64(1536),
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"distance_metric", "COSINE",
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"M", int64(16),
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"ef_construction", int64(64),
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},
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},
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"num_docs": int64(0),
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"max_doc_id": int64(0),
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"num_terms": int64(0),
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"num_records": int64(0),
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"inverted_sz_mb": "0",
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"vector_index_sz_mb": "0",
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"total_inverted_index_blocks": int64(0),
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"offset_vectors_sz_mb": "0",
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"doc_table_size_mb": "0.01532745361328125",
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"sortable_values_size_mb": "0",
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"key_table_size_mb": "2.288818359375e-5",
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"tag_overhead_sz_mb": "0",
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"text_overhead_sz_mb": "0",
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"total_index_memory_sz_mb": "0.015350341796875",
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"geoshapes_sz_mb": "0",
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"records_per_doc_avg": "nan",
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"bytes_per_record_avg": "nan",
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"offsets_per_term_avg": "nan",
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"offset_bits_per_record_avg": "nan",
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"hash_indexing_failures": int64(0),
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"total_indexing_time": "0",
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"indexing": int64(0),
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"percent_indexed": "1",
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"number_of_uses": int64(2),
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"cleaning": int64(0),
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"gc_stats": []interface{}{
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"bytes_collected", "0",
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"total_ms_run", "0",
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"total_cycles", "0",
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"average_cycle_time_ms", "nan",
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"last_run_time_ms", "0",
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"gc_numeric_trees_missed", "0",
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"gc_blocks_denied", "0",
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},
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"cursor_stats": []interface{}{
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"global_idle", int64(0),
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"global_total", int64(0),
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"index_capacity", int64(128),
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"index_total", int64(0),
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},
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"dialect_stats": []interface{}{
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"dialect_1", int64(0),
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"dialect_2", int64(0),
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"dialect_3", int64(0),
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"dialect_4", int64(0),
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},
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"Index Errors": []interface{}{
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"indexing failures", int64(0),
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"last indexing error", "N/A",
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"last indexing error key", "N/A",
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"background indexing status", "OK",
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},
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"field statistics": []interface{}{
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[]interface{}{
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"identifier", "prompt",
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"attribute", "prompt",
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"Index Errors", []interface{}{
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"indexing failures", int64(0),
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"last indexing error", "N/A",
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"last indexing error key", "N/A",
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},
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},
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[]interface{}{
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"identifier", "response",
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"attribute", "response",
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"Index Errors", []interface{}{
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"indexing failures", int64(0),
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"last indexing error", "N/A",
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"last indexing error key", "N/A",
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},
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},
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[]interface{}{
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"identifier", "exact_digest",
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"attribute", "exact_digest",
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"Index Errors", []interface{}{
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"indexing failures", int64(0),
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"last indexing error", "N/A",
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"last indexing error key", "N/A",
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},
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},
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[]interface{}{
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"identifier", "prompt_vector",
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"attribute", "prompt_vector",
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"Index Errors", []interface{}{
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"indexing failures", int64(0),
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"last indexing error", "N/A",
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"last indexing error key", "N/A",
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},
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"memory", int64(0),
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"marked_deleted", int64(0),
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},
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},
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}
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// Parse the data
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result, err := parseFTInfo(data)
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if err != nil {
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t.Fatalf("parseFTInfo failed: %v", err)
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}
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// Validate index name
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if result.IndexName != "rand:42d1f2820b3048b6bc783d4dcdb9094a" {
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t.Errorf("IndexName = %v, want %v", result.IndexName, "rand:42d1f2820b3048b6bc783d4dcdb9094a")
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}
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// Validate index definition
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if result.IndexDefinition.KeyType != "HASH" {
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t.Errorf("IndexDefinition.KeyType = %v, want HASH", result.IndexDefinition.KeyType)
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}
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if len(result.IndexDefinition.Prefixes) != 1 || result.IndexDefinition.Prefixes[0] != "rand:42d1f2820b3048b6bc783d4dcdb9094a" {
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t.Errorf("IndexDefinition.Prefixes = %v, want [rand:42d1f2820b3048b6bc783d4dcdb9094a]", result.IndexDefinition.Prefixes)
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}
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if result.IndexDefinition.DefaultScore != 1.0 {
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t.Errorf("IndexDefinition.DefaultScore = %v, want 1.0", result.IndexDefinition.DefaultScore)
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}
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// Validate attributes
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if len(result.Attributes) != 4 {
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t.Fatalf("len(Attributes) = %v, want 4", len(result.Attributes))
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}
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// Check prompt field (TEXT)
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promptAttr := result.Attributes[0]
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if promptAttr.Identifier != "prompt" {
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t.Errorf("Attributes[0].Identifier = %v, want prompt", promptAttr.Identifier)
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}
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if promptAttr.Attribute != "prompt" {
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t.Errorf("Attributes[0].Attribute = %v, want prompt", promptAttr.Attribute)
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}
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if promptAttr.Type != "TEXT" {
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t.Errorf("Attributes[0].Type = %v, want TEXT", promptAttr.Type)
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}
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if promptAttr.Weight != 1.0 {
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t.Errorf("Attributes[0].Weight = %v, want 1.0", promptAttr.Weight)
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}
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// Check response field (TEXT)
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responseAttr := result.Attributes[1]
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if responseAttr.Identifier != "response" {
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t.Errorf("Attributes[1].Identifier = %v, want response", responseAttr.Identifier)
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}
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if responseAttr.Attribute != "response" {
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t.Errorf("Attributes[1].Attribute = %v, want response", responseAttr.Attribute)
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}
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if responseAttr.Type != "TEXT" {
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t.Errorf("Attributes[1].Type = %v, want TEXT", responseAttr.Type)
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}
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// Check exact_digest field (TAG)
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tagAttr := result.Attributes[2]
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if tagAttr.Identifier != "exact_digest" {
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t.Errorf("Attributes[2].Identifier = %v, want exact_digest", tagAttr.Identifier)
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}
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if tagAttr.Attribute != "exact_digest" {
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t.Errorf("Attributes[2].Attribute = %v, want exact_digest", tagAttr.Attribute)
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}
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if tagAttr.Type != "TAG" {
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t.Errorf("Attributes[2].Type = %v, want TAG", tagAttr.Type)
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}
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// Check prompt_vector field (VECTOR)
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vectorAttr := result.Attributes[3]
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if vectorAttr.Identifier != "prompt_vector" {
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t.Errorf("Attributes[3].Identifier = %v, want prompt_vector", vectorAttr.Identifier)
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}
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if vectorAttr.Attribute != "prompt_vector" {
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t.Errorf("Attributes[3].Attribute = %v, want prompt_vector", vectorAttr.Attribute)
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}
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if vectorAttr.Type != "VECTOR" {
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t.Errorf("Attributes[3].Type = %v, want VECTOR", vectorAttr.Type)
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}
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if vectorAttr.Algorithm != "HNSW" {
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t.Errorf("Attributes[3].Algorithm = %v, want HNSW", vectorAttr.Algorithm)
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}
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if vectorAttr.DataType != "FLOAT32" {
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t.Errorf("Attributes[3].DataType = %v, want FLOAT32", vectorAttr.DataType)
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}
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if vectorAttr.Dim != 1536 {
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t.Errorf("Attributes[3].Dim = %v, want 1536", vectorAttr.Dim)
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}
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if vectorAttr.DistanceMetric != "COSINE" {
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t.Errorf("Attributes[3].DistanceMetric = %v, want COSINE", vectorAttr.DistanceMetric)
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}
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if vectorAttr.M != 16 {
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t.Errorf("Attributes[3].M = %v, want 16", vectorAttr.M)
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}
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if vectorAttr.EFConstruction != 64 {
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t.Errorf("Attributes[3].EFConstruction = %v, want 64", vectorAttr.EFConstruction)
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}
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// Validate numeric fields
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if result.NumDocs != 0 {
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t.Errorf("NumDocs = %v, want 0", result.NumDocs)
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}
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if result.MaxDocID != 0 {
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t.Errorf("MaxDocID = %v, want 0", result.MaxDocID)
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}
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if result.NumTerms != 0 {
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t.Errorf("NumTerms = %v, want 0", result.NumTerms)
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}
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if result.NumRecords != 0 {
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t.Errorf("NumRecords = %v, want 0", result.NumRecords)
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}
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if result.Indexing != 0 {
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t.Errorf("Indexing = %v, want 0", result.Indexing)
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}
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if result.PercentIndexed != 1.0 {
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t.Errorf("PercentIndexed = %v, want 1.0", result.PercentIndexed)
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}
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if result.HashIndexingFailures != 0 {
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t.Errorf("HashIndexingFailures = %v, want 0", result.HashIndexingFailures)
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}
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if result.Cleaning != 0 {
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t.Errorf("Cleaning = %v, want 0", result.Cleaning)
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}
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if result.NumberOfUses != 2 {
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t.Errorf("NumberOfUses = %v, want 2", result.NumberOfUses)
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}
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// Validate average stats (should be "nan" for empty index)
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if result.RecordsPerDocAvg != "nan" {
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t.Errorf("RecordsPerDocAvg = %v, want nan", result.RecordsPerDocAvg)
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}
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if result.BytesPerRecordAvg != "nan" {
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t.Errorf("BytesPerRecordAvg = %v, want nan", result.BytesPerRecordAvg)
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}
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if result.OffsetsPerTermAvg != "nan" {
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t.Errorf("OffsetsPerTermAvg = %v, want nan", result.OffsetsPerTermAvg)
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}
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if result.OffsetBitsPerRecordAvg != "nan" {
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t.Errorf("OffsetBitsPerRecordAvg = %v, want nan", result.OffsetBitsPerRecordAvg)
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}
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// Validate cursor stats
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if result.CursorStats.GlobalIdle != 0 {
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t.Errorf("CursorStats.GlobalIdle = %v, want 0", result.CursorStats.GlobalIdle)
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}
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if result.CursorStats.GlobalTotal != 0 {
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t.Errorf("CursorStats.GlobalTotal = %v, want 0", result.CursorStats.GlobalTotal)
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}
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if result.CursorStats.IndexCapacity != 128 {
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t.Errorf("CursorStats.IndexCapacity = %v, want 128", result.CursorStats.IndexCapacity)
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}
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if result.CursorStats.IndexTotal != 0 {
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t.Errorf("CursorStats.IndexTotal = %v, want 0", result.CursorStats.IndexTotal)
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}
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// Validate dialect stats
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if result.DialectStats["dialect_1"] != 0 {
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t.Errorf("DialectStats[dialect_1] = %v, want 0", result.DialectStats["dialect_1"])
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}
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if result.DialectStats["dialect_2"] != 0 {
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t.Errorf("DialectStats[dialect_2] = %v, want 0", result.DialectStats["dialect_2"])
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}
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if result.DialectStats["dialect_3"] != 0 {
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t.Errorf("DialectStats[dialect_3] = %v, want 0", result.DialectStats["dialect_3"])
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}
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if result.DialectStats["dialect_4"] != 0 {
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t.Errorf("DialectStats[dialect_4] = %v, want 0", result.DialectStats["dialect_4"])
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}
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// Validate GC stats
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if result.GCStats.BytesCollected != 0 {
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t.Errorf("GCStats.BytesCollected = %v, want 0", result.GCStats.BytesCollected)
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}
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if result.GCStats.TotalMsRun != 0 {
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t.Errorf("GCStats.TotalMsRun = %v, want 0", result.GCStats.TotalMsRun)
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}
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if result.GCStats.TotalCycles != 0 {
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t.Errorf("GCStats.TotalCycles = %v, want 0", result.GCStats.TotalCycles)
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}
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if result.GCStats.AverageCycleTimeMs != "nan" {
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t.Errorf("GCStats.AverageCycleTimeMs = %v, want nan", result.GCStats.AverageCycleTimeMs)
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}
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// Validate Index Errors
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if result.IndexErrors.IndexingFailures != 0 {
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t.Errorf("IndexErrors.IndexingFailures = %v, want 0", result.IndexErrors.IndexingFailures)
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}
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if result.IndexErrors.LastIndexingError != "N/A" {
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t.Errorf("IndexErrors.LastIndexingError = %v, want N/A", result.IndexErrors.LastIndexingError)
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}
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if result.IndexErrors.LastIndexingErrorKey != "N/A" {
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t.Errorf("IndexErrors.LastIndexingErrorKey = %v, want N/A", result.IndexErrors.LastIndexingErrorKey)
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}
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// Validate field statistics
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if len(result.FieldStatistics) != 4 {
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t.Fatalf("len(FieldStatistics) = %v, want 4", len(result.FieldStatistics))
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}
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expectedIdentifiers := map[string]bool{
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"prompt": true,
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"response": true,
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"exact_digest": true,
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"prompt_vector": true,
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}
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for _, fieldStat := range result.FieldStatistics {
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if !expectedIdentifiers[fieldStat.Identifier] {
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t.Errorf("Unexpected field statistic identifier: %v", fieldStat.Identifier)
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}
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if fieldStat.IndexErrors.IndexingFailures != 0 {
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t.Errorf("FieldStatistic[%s].IndexErrors.IndexingFailures = %v, want 0", fieldStat.Identifier, fieldStat.IndexErrors.IndexingFailures)
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}
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if fieldStat.IndexErrors.LastIndexingError != "N/A" {
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t.Errorf("FieldStatistic[%s].IndexErrors.LastIndexingError = %v, want N/A", fieldStat.Identifier, fieldStat.IndexErrors.LastIndexingError)
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}
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if fieldStat.IndexErrors.LastIndexingErrorKey != "N/A" {
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t.Errorf("FieldStatistic[%s].IndexErrors.LastIndexingErrorKey = %v, want N/A", fieldStat.Identifier, fieldStat.IndexErrors.LastIndexingErrorKey)
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}
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}
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t.Logf("Successfully parsed FT.INFO response with %d attributes", len(result.Attributes))
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}
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