Add default behaviour for AI.MODELGET + documentation

Author: alonre24

docs/commands.md

@@ -222,8 +222,8 @@ AI.MODELGET <key> [META] [BLOB]
 _Arguments
 
 * **key**: the model's key name
-* **META**: will return the model's meta information on backend, device, tag and batching parameters
-* **BLOB**: will return the model's blob containing the serialized model
+* **META**: will return only the model's meta information on backend, device, tag and batching parameters
+* **BLOB**: will return only the model's blob containing the serialized model
 
 _Return_
 
@@ -237,7 +237,7 @@ An array of alternating key-value pairs as follows:
 1. **INPUTS**: array reply with one or more names of the model's input nodes (applicable only for TensorFlow models)
 1. **OUTPUTS**: array reply with one or more names of the model's output nodes (applicable only for TensorFlow models)
 1. **MINBATCHTIMEOUT**: The time in milliseconds for which the engine will wait before executing a request to run the model, when the number of incoming requests is lower than `MINBATCHSIZE`. When `MINBATCHTIMEOUT` is 0, the engine will not run the model before it receives at least `MINBATCHSIZE` requests.
-1. **BLOB**: a blob containing the serialized model (when called with the `BLOB` argument) as a String. If the size of the serialized model exceeds `MODEL_CHUNK_SIZE` (see `AI.CONFIG` command), then an array of chunks is returned. The full serialized model can be obtained by concatenating the chunks.
+1. **BLOB**: a blob containing the serialized model as a String. If the size of the serialized model exceeds `MODEL_CHUNK_SIZE` (see `AI.CONFIG` command), then an array of chunks is returned. The full serialized model can be obtained by concatenating the chunks.
 
 **Examples**
 

src/redisai.c

@@ -416,31 +416,24 @@ int RedisAI_ModelGet_RedisCommand(RedisModuleCtx *ctx, RedisModuleString **argv,
         return REDISMODULE_ERR;
     }
 
-    int meta = 0;
-    int blob = 0;
+    int meta = false;
+    int blob = false;
     for (int i = 2; i < argc; i++) {
         const char *optstr = RedisModule_StringPtrLen(argv[i], NULL);
         if (!strcasecmp(optstr, "META")) {
-            meta = 1;
+            meta = true;
         } else if (!strcasecmp(optstr, "BLOB")) {
-            blob = 1;
+            blob = true;
         }
     }
 
-    if (!meta && !blob) {
-        return RedisModule_ReplyWithError(ctx, "ERR no META or BLOB specified");
-    }
-
     char *buffer = NULL;
     size_t len = 0;
 
-    if (blob) {
+    if (!meta || blob) {
         RAI_ModelSerialize(mto, &buffer, &len, &err);
-        if (err.code != RAI_OK) {
-#ifdef RAI_PRINT_BACKEND_ERRORS
-            printf("ERR: %s\n", err.detail);
-#endif
-            int ret = RedisModule_ReplyWithError(ctx, err.detail);
+        if (RAI_GetErrorCode(&err) != RAI_OK) {
+            int ret = RedisModule_ReplyWithError(ctx, RAI_GetErrorOneLine(&err));
             RAI_ClearError(&err);
             if (*buffer) {
                 RedisModule_Free(buffer);
@@ -455,12 +448,14 @@ int RedisAI_ModelGet_RedisCommand(RedisModuleCtx *ctx, RedisModuleString **argv,
         return REDISMODULE_OK;
     }
 
-    const int outentries = blob ? 18 : 16;
-    RedisModule_ReplyWithArray(ctx, outentries);
+    // The only case where we return only META, is when META is given but BLOB
+    // was not. Otherwise, we return both META+SOURCE
+    const int out_entries = (meta && !blob) ? 16 : 18;
+    RedisModule_ReplyWithArray(ctx, out_entries);
 
     RedisModule_ReplyWithCString(ctx, "backend");
-    const char *backendstr = RAI_GetBackendName(mto->backend);
-    RedisModule_ReplyWithCString(ctx, backendstr);
+    const char *backend_str = RAI_GetBackendName(mto->backend);
+    RedisModule_ReplyWithCString(ctx, backend_str);
 
     RedisModule_ReplyWithCString(ctx, "device");
     RedisModule_ReplyWithCString(ctx, mto->devicestr);
@@ -495,7 +490,8 @@ int RedisAI_ModelGet_RedisCommand(RedisModuleCtx *ctx, RedisModuleString **argv,
     RedisModule_ReplyWithCString(ctx, "minbatchtimeout");
     RedisModule_ReplyWithLongLong(ctx, (long)mto->opts.minbatchtimeout);
 
-    if (meta && blob) {
+    // This condition is the negation of (meta && !blob)
+    if (!meta || blob) {
         RedisModule_ReplyWithCString(ctx, "blob");
         RAI_ReplyWithChunks(ctx, buffer, len);
         RedisModule_Free(buffer);

tests/flow/tests_commands.py

@@ -54,7 +54,7 @@ def test_modelstore_errors(env):
                         'AI.MODELSTORE', 'm{1}', 'TORCH', DEVICE, 'BATCHSIZE', 2, 'BLOB')
 
 
-def test_modelget_errors(env):
+def test_modelget(env):
     if not TEST_TF:
         env.debugPrint("Skipping test since TF is not available", force=True)
         return
@@ -69,8 +69,17 @@ def test_modelget_errors(env):
 
     # ERR model key is empty
     con.execute_command('DEL', 'DONT_EXIST{1}')
-    check_error_message(env, con, "model key is empty",
-                        'AI.MODELGET', 'DONT_EXIST{1}')
+    check_error_message(env, con, "model key is empty", 'AI.MODELGET', 'DONT_EXIST{1}')
+
+    # The default behaviour on success is return META+BLOB
+    model_pb = load_file_content('graph.pb')
+    con.execute_command('AI.MODELSTORE', 'm{1}', 'TF', DEVICE, 'INPUTS', 2, 'a', 'b', 'OUTPUTS', 1, 'mul',
+                              'BLOB', model_pb)
+    _, backend, _, device, _, tag, _, batchsize, _, minbatchsize, _, inputs, _, outputs, _, minbatchtimeout, _, blob = \
+            con.execute_command('AI.MODELGET', 'm{1}')
+    env.assertEqual([backend, device, tag, batchsize, minbatchsize, minbatchtimeout, inputs, outputs],
+                         [b"TF", bytes(DEVICE, "utf8"), b"", 0, 0, 0, [b"a", b"b"], [b"mul"]])
+    env.assertEqual(blob, model_pb)
 
 
 def test_modelexecute_errors(env):