[multires-lyrics-search] "TypeError: Cannot read property 'length' and 'map' of undefined"

[yiouyou]

I'm trying to tweak multires-lyrics-search example to deal with chinese sentense. Here is what I've done:

1. change pods/encode.yml

   !TextPaddlehubEncoder
   with:
   model_name: chinese-roberta-wwm-ext-large
   requests:
   on:
   ControlRequest:
     - !ControlReqDriver {}
   [SearchRequest, TrainRequest, IndexRequest]:
     - !EncodeDriver
       with:
         traversal_paths: ['c']

2. change requirements.txt

   jina[hub,http]==0.9.16
   torch==1.7.1
   transformers==4.2.0
   requests==2.25.1
   pytest==6.2.1
   paddlehub==1.7.1
   paddlepaddle==1.8.5

3. prepare chinese text (basically translate the name and lyrics of songs to chinese by google translate)
4. run 'python app.py index' successfully
5. run 'python app.py search' successfully
6. run 'curl --request POST -d '{"top_k": 2, "mode": "search", "data": ["text:没有办法知道"]}' -H 'Content-Type: application/json' 'http://0.0.0.0:65481/api/search'', get back as below:

   {
   "requestId": "2e03c3f6-57e3-11eb-afe2-00155dabdd5c",
   "search": {
   "docs": [
     {
       "id": "f6db17e89d334605",
       "chunks": [
         {
           "id": "5162c61930f55b37",
           "weight": 1.0,
           "length": 1,
           "matches": [
             {
               "id": "c786f6141e906879",
               "weight": 1.0,
               "length": 4,
               "mimeType": "text/plain",
               "text": "21",
               "granularity": 1,
               "parentId": "c167946b50917635",
               "location": [
                 272,
                 290
               ],
               "offset": 18,
               "embedding": {
                 "dense": {
                   "buffer": "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",
                   "shape": [
                     1024
                   ],
                   "dtype": "<f4"
                 }
               },
               "score": {
                 "value": 7.0089135,
                 "opName": "NumpyIndexer",
                 "refId": "5162c61930f55b37"
               },
               "adjacency": 1,
               "contentHash": "bb90f7f108e9e789"
             },
   ...
             {
               "id": "6e0b715ae315d03d",
               "weight": 1.0,
               "length": 1,
               "mimeType": "text/plain",
               "text": "chant",
               "granularity": 1,
               "parentId": "0026739b5535fa29",
               "location": [
                 146,
                 168
               ],
               "offset": 14,
               "embedding": {
                 "dense": {
                   "buffer": 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           "score": {
             "value": 0.11926709,
             "opName": "MinRanker",
             "refId": "f6db17e89d334605"
           },
           "adjacency": 1,
           "contentHash": "d6ee70f9d2d5bb00"
         }
       ],
       "mimeType": "text/plain",
       "text": "text:\u6ca1\u6709\u529e\u6cd5\u77e5\u9053",
       "contentHash": "6dbba5670df1e560"
     }
   ]
   },
   "status": {},
   "queryset": [
   {
     "name": "SliceQL",
     "parameters": {
       "end": 2.0,
       "traversal_paths": [
         "c",
         "r"
       ],
       "priority": 1.0,
       "start": 0.0
     },
     "priority": 1
   },
   {
     "name": "VectorSearchDriver",
     "parameters": {
       "method": "query",
       "top_k": 2.0,
       "priority": 1.0,
       "executor": null,
       "fill_embedding": false,
       "traversal_paths": [
         "r",
         "c"
       ]
     },
     "priority": 1
   }
   ],
   "routes": [
   {
     "pod": "gateway",
     "podId": "c58c1a58-57e2-11eb-afe2-00155dabdd5c",
     "startTime": "2021-01-16T10:11:20.613417Z",
     "endTime": "2021-01-16T10:12:43.009817Z"
   },
   ...
   {
     "pod": "gateway",
     "podId": "c58c1a58-57e2-11eb-afe2-00155dabdd5c",
     "startTime": "2021-01-16T10:12:43.009783Z"
   }
   ]
   }

   'search' log as below:

       gateway@20005[I]:input tcp://0.0.0.0:59455 (PULL_CONNECT) output tcp://0.0.0.0:46453 (PUSH_CONNECT) control over ipc:///tmp/tmpn_6h4h0h (PAIR_BIND)
       gateway@20005[I]:prefetching 50 requests...
       gateway@20005[W]:if this takes too long, you may want to take smaller "--prefetch" or ask client to reduce "--request-size"
       gateway@20005[I]:prefetching 50 requests takes 0 seconds (0.00s)
       gateway@20005[I]:send: 0 recv: 0 pending: 0
   chunk_seg/ZEDRuntime@19898[I]:recv SearchRequest  from gateway▸chunk_seg/ZEDRuntime▸⚐
   chunk_seg/ZEDRuntime@19898[I]:#sent: 0 #recv: 1 sent_size: 0 Bytes recv_size: 645 Bytes
   tf_encode/ZEDRuntime@19904[I]:recv SearchRequest  from gateway▸chunk_seg/ZEDRuntime▸tf_encode/ZEDRuntime▸⚐
   [2021-01-17 17:57:51,038] [    INFO] - Load pretraining parameters from /home/sz/.paddlehub/modules/chinese_roberta_wwm_ext_large/assets/params.
   [2021-01-17 17:57:51,046] [    INFO] - Dataset is None or it has not any labels, label map = {}
   [2021-01-17 17:57:51,062] [    INFO] - Checkpoint dir: ckpt_20210117175751
   [2021-01-17 17:58:05,696] [    INFO] - PaddleHub predict start
   [2021-01-17 17:58:05,696] [    INFO] - Load the best model from ckpt_20210117175751/best_model
   /mnt/d/py37-sz-lyrics/lib/python3.7/site-packages/paddle/fluid/executor.py:1093: UserWarning: There are no operators in the program to be executed. If you pass Program manually, please use fluid.program_guard to ensure the current Program is being used.
   warnings.warn(error_info)
   [2021-01-17 17:58:35,121] [    INFO] - Try loading checkpoint from ckpt_20210117175751/ckpt.meta
   [2021-01-17 17:58:35,121] [    INFO] - PaddleHub model checkpoint not found, start from scratch...
   [2021-01-17 17:58:49,305] [    INFO] - PaddleHub predict finished.
   tf_encode/ZEDRuntime@19904[I]:#sent: 0 #recv: 1 sent_size: 0 Bytes recv_size: 828 Bytes
   chunk_idx/head/ZEDRuntime@19949[I]:recv SearchRequest  from gateway▸chunk_seg/ZEDRuntime▸tf_encode/ZEDRuntime▸chunk_idx/head/ZEDRuntime▸⚐
   chunk_idx/head/ZEDRuntime@19949[I]:#sent: 0 #recv: 1 sent_size: 0 Bytes recv_size: 4.9 KB
   chunk_idx/1/ZEDRuntime@19961[I]:recv SearchRequest  from gateway▸chunk_seg/ZEDRuntime▸tf_encode/ZEDRuntime▸chunk_idx/head/ZEDRuntime▸chunk_idx/1/ZEDRuntime▸⚐
   chunk_idx/2/ZEDRuntime@19969[I]:recv SearchRequest  from gateway▸chunk_seg/ZEDRuntime▸tf_encode/ZEDRuntime▸chunk_idx/head/ZEDRuntime▸chunk_idx/2/ZEDRuntime▸⚐
   chunk_idx/3/ZEDRuntime@19977[I]:recv SearchRequest  from gateway▸chunk_seg/ZEDRuntime▸tf_encode/ZEDRuntime▸chunk_idx/head/ZEDRuntime▸chunk_idx/3/ZEDRuntime▸⚐
   chunk_idx/4/ZEDRuntime@19985[I]:recv SearchRequest  from gateway▸chunk_seg/ZEDRuntime▸tf_encode/ZEDRuntime▸chunk_idx/head/ZEDRuntime▸chunk_idx/4/ZEDRuntime▸⚐
   chunk_idx/1/ZEDRuntime@19961[I]:#sent: 0 #recv: 1 sent_size: 0 Bytes recv_size: 5.0 KB
   chunk_idx/tail/ZEDRuntime@19955[I]:recv SearchRequest (1/4 parts) from gateway▸chunk_seg/ZEDRuntime▸tf_encode/ZEDRuntime▸chunk_idx/head/ZEDRuntime▸chunk_idx/1/ZEDRuntime▸chunk_idx/tail/ZEDRuntime▸⚐
   NumpyIndexer@19985[S]:memmap is enabled for ./workspace/chunk_compound_indexer-4/vec.gz
   NumpyIndexer@19969[S]:memmap is enabled for ./workspace/chunk_compound_indexer-2/vec.gz
   NumpyIndexer@19977[S]:memmap is enabled for ./workspace/chunk_compound_indexer-3/vec.gz
   NumpyIndexer@19985[I]:indexer size: 7
   NumpyIndexer@19969[I]:indexer size: 3
   NumpyIndexer@19977[I]:indexer size: 7
   BinaryPbIndexer@19977[I]:indexer size: 7
   chunk_idx/3/ZEDRuntime@19977[I]:#sent: 0 #recv: 1 sent_size: 0 Bytes recv_size: 5.0 KB
   BinaryPbIndexer@19985[I]:indexer size: 7
   BinaryPbIndexer@19969[I]:indexer size: 3
   chunk_idx/tail/ZEDRuntime@19955[I]:recv SearchRequest (2/4 parts) from gateway▸chunk_seg/ZEDRuntime▸tf_encode/ZEDRuntime▸chunk_idx/head/ZEDRuntime▸chunk_idx/3/ZEDRuntime▸chunk_idx/tail/ZEDRuntime▸⚐
   chunk_idx/2/ZEDRuntime@19969[I]:#sent: 0 #recv: 1 sent_size: 0 Bytes recv_size: 5.0 KB
   chunk_idx/tail/ZEDRuntime@19955[I]:recv SearchRequest (3/4 parts) from gateway▸chunk_seg/ZEDRuntime▸tf_encode/ZEDRuntime▸chunk_idx/head/ZEDRuntime▸chunk_idx/2/ZEDRuntime▸chunk_idx/tail/ZEDRuntime▸⚐
   chunk_idx/4/ZEDRuntime@19985[I]:#sent: 0 #recv: 1 sent_size: 0 Bytes recv_size: 5.0 KB
   chunk_idx/tail/ZEDRuntime@19955[I]:recv SearchRequest (4/4 parts) from gateway▸chunk_seg/ZEDRuntime▸tf_encode/ZEDRuntime▸chunk_idx/head/ZEDRuntime▸chunk_idx/4/ZEDRuntime▸chunk_idx/tail/ZEDRuntime▸⚐
   chunk_idx/tail/ZEDRuntime@19955[I]:#sent: 0 #recv: 4 sent_size: 0 Bytes recv_size: 45.3 KB
   ranker/ZEDRuntime@19993[I]:recv SearchRequest  from gateway▸chunk_seg/ZEDRuntime▸tf_encode/ZEDRuntime▸chunk_idx/head/ZEDRuntime▸chunk_idx/1/ZEDRuntime▸chunk_idx/2/ZEDRuntime▸chunk_idx/3/ZEDRuntime▸chunk_idx/4/ZEDRuntime▸chunk_idx/tail/ZEDRuntime▸ranker/ZEDRuntime▸⚐
   ranker/ZEDRuntime@19993[I]:#sent: 0 #recv: 1 sent_size: 0 Bytes recv_size: 30.4 KB
   doc_idx/ZEDRuntime@19999[I]:recv SearchRequest  from gateway▸chunk_seg/ZEDRuntime▸tf_encode/ZEDRuntime▸chunk_idx/head/ZEDRuntime▸chunk_idx/1/ZEDRuntime▸chunk_idx/2/ZEDRuntime▸chunk_idx/3/ZEDRuntime▸chunk_idx/4/ZEDRuntime▸chunk_idx/tail/ZEDRuntime▸ranker/ZEDRuntime▸doc_idx/ZEDRuntime▸⚐
   doc_idx/ZEDRuntime@19999[I]:indexer size: 50
   doc_idx/ZEDRuntime@19999[I]:#sent: 0 #recv: 1 sent_size: 0 Bytes recv_size: 30.8 KB
       gateway@20005[I]:#sent: 1 #recv: 1 sent_size: 714 Bytes recv_size: 37.1 KB

7. go to static folder, then run 'python -m http.server'
8. But when typing '没有办法知道', there is no response on web and when click F12, get errors as below:

When looking up the problem, I can't find the place to define 'map' and 'length'. Need some help to fix the issue.

Thanks!

[JoanFM]

So to have a clear understanding, do u get results when querying without using http.server option?

[yiouyou]

So to have a clear understanding, do u get results when querying without using http.server option?

Yes, by using 'curl' command line, I can get the results.

[yiouyou]

Some update:

It seems, when typing query, most of time, it won't work, occasionally it will work (show as below).

[JoanFM]

according to the description, the problem seems to be with the http.server option. that is just a custom component to show results in a nice way. It may not be ready to work with Chinese language.

It would be good if someone could adapt that to work with Chinese language, but that is not a component of Jina

[JoanFM]

Hello @yiouyou ,

Since this component is not a core element of Jina (it is just a helper to show results) we cannot guarantee it works with any custom input. I will close the issue, but keep in mind that we will welcome any external contribution that can adapt this front end component to work with Chinese language. Otherwise you are welcome to adapt it to your own custom design or web component