# "code":3,"message":"Dense vectors must contain at least one non-zero value"

**URL:** <https://community.pinecone.io/t/code-3-message-dense-vectors-must-contain-at-least-one-non-zero-value/4368>\
**Category:** Support\
**Tags:** vector-database\
**Created:** [January 31, 2024, 1:40pm UTC](https://community.pinecone.io/t/code-3-message-dense-vectors-must-contain-at-least-one-non-zero-value/4368 "2024-01-31T13:40:41Z")\
**Posts on this page:** 4\
**Page:** 1

<div class="post-metadata">

**Author:** ![pierre.curie.godinot](https://sea2.discourse-cdn.com/flex020/user_avatar/community.pinecone.io/pierre.curie.godinot/32/1641_2.png) [@pierre.curie.godinot](https://community.pinecone.io/u/pierre.curie.godinot)\
**Post date:** [January 31, 2024, 1:40pm UTC](https://community.pinecone.io/t/code-3-message-dense-vectors-must-contain-at-least-one-non-zero-value/4368/1 "2024-01-31T13:40:41Z")

</div>

Hello everyone,

Am trying to upsert and preprocess docs using haystack and pinecone.

```auto
from haystack.utils import fetch_archive_from_http

# This fetches some sample files to work with
doc_dir = "data/tutorial8"
s3_url = "https://s3.eu-central-1.amazonaws.com/deepset.ai-farm-qa/datasets/documents/preprocessing_tutorial8.zip"
fetch_archive_from_http(url=s3_url, output_dir=doc_dir)

all_docs = convert_files_to_docs(dir_path=doc_dir)

preprocessor = PreProcessor(
    clean_empty_lines=True,
    clean_whitespace=True,
    split_by="word",
    split_length=100,
    split_respect_sentence_boundary=True
)

docs_default = preprocessor.process(all_docs) #create a dictionary with the data in the 'content' key

document_store.write_documents(docs_default) #need a dictionary as arg

```

Then i got this error : ApiException: (400)  
Reason: Bad Request  
HTTP response headers: HTTPHeaderDict({‘content-type’: ‘application/json’, ‘Content-Length’: ‘155’, ‘x-pinecone-request-latency-ms’: ‘136’, ‘date’: ‘Wed, 31 Jan 2024 13:33:43 GMT’, ‘x-envoy-upstream-service-time’: ‘32’, ‘server’: ‘envoy’, ‘Via’: ‘1.1 google’, ‘Alt-Svc’: ‘h3=“:443”; ma=2592000,h3-29=“:443”; ma=2592000’})  
HTTP response body: {“code”:3,“message”:“Dense vectors must contain at least one non-zero value. Vector ID 1f6ca8a2bd6c9903813607120d8d48bc contains only zeros.”,“details”:}

But when i do this :

```auto
from pprint import pprint

pprint(docs_default[0])

```

its return : \<Document: {‘content’: 'BERT: Pre-training of Deep Bidirectional Transformers for\nLanguage Understanding\nJacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova\nGoogle AI Language[n{jacobdevlin,mingweichang,kentonl,kristout}@google.com](mailto:n%7Bjacobdevlin,mingweichang,kentonl,kristout%7D@google.com)\nAbstract\nWe introduce a new language representa-\ntion model called BERT, which stands for\nBidirectional Encoder Representations from\nTransformers. Unlike recent language repre-\nsentation models (Peters et al., 2018a; Rad-\nford et al., 2018), BERT is designed to pre-\ntrain deep bidirectional representations from\nunlabeled text by jointly conditioning on both\nleft and right context in all layers. ', ‘content\_type’: ‘text’, ‘score’: None, ‘meta’: {‘name’: ‘bert.pdf’, ‘\_split\_id’: 0}, ‘id\_hash\_keys’: [‘content’], ‘embedding’: None, ‘id’: ‘1f6ca8a2bd6c9903813607120d8d48bc’}\>

So i really don’t get why this vector is containing only zero values.

---

<div class="post-metadata">

**Author:** ![jesse](https://sea2.discourse-cdn.com/flex020/user_avatar/community.pinecone.io/jesse/32/1658_2.png) [@jesse](https://community.pinecone.io/u/jesse)\
**Post date:** [January 31, 2024, 4:21pm UTC](https://community.pinecone.io/t/code-3-message-dense-vectors-must-contain-at-least-one-non-zero-value/4368/2 "2024-01-31T16:21:37Z")

</div>

> [@pierre.curie.godinot](#):
>
> ‘embedding’: None

It does look like there’s no vector in the data you’re sending to Pinecone. You might want to check how the documents are getting preprocessed before upsert into Pinecone.

---

<div class="post-metadata">

**Author:** ![pierre.curie.godinot](https://sea2.discourse-cdn.com/flex020/user_avatar/community.pinecone.io/pierre.curie.godinot/32/1641_2.png) [@pierre.curie.godinot](https://community.pinecone.io/u/pierre.curie.godinot)\
**Post date:** [February 1, 2024, 11:31pm UTC](https://community.pinecone.io/t/code-3-message-dense-vectors-must-contain-at-least-one-non-zero-value/4368/3 "2024-02-01T23:31:30Z")

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Actually, we can generate embeddings for our context passages using the retriever later in the code. All we need to do is pass the retriever to `update_embeddings` method in the document store. This will generate embeddings and upsert it to Pinecone Index.

---

<div class="post-metadata">

**Author:** ![system](https://us1.discourse-cdn.com/flex020/uploads/pinecone/original/1X/d16664eba369eeee623700cf12feab5562b37eaf.jpeg) [@system](https://community.pinecone.io/u/system)\
**Post date:** [February 15, 2024, 11:32pm UTC](https://community.pinecone.io/t/code-3-message-dense-vectors-must-contain-at-least-one-non-zero-value/4368/4 "2024-02-15T23:32:21Z")

</div>

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