> ## Documentation Index
> Fetch the complete documentation index at: https://docs.vectorview.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Python Quickstart

> Connect to vectorview with 3 lines of code

## Install

```bash theme={null}
pip install vectorview
```

## Use

Get your `key` by logging in to the [vectorview dashboard](https://www.vectorview.ai/)

```python theme={null}
from vectorview import Vectorview
vv = Vectorview(key)
vv.event(query, docs_with_score)
```

## Example

```python theme={null}
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.text_splitter import TokenTextSplitter
from langchain.vectorstores import FAISS
from vectorview import Vectorview

# Setup
vv = Vectorview(key)

# Do semantic search
with open("./text.txt", "r") as f:
    text = f.read()
text_splitter = TokenTextSplitter(chunk_size=40, chunk_overlap=0)
texts = text_splitter.split_text(text)

embeddings = OpenAIEmbeddings()
db = FAISS.from_texts(texts, embeddings)

query = "What did the president say about Ketanji Brown Jackson"
docs_with_score = db.similarity_search_with_score(query, 3)

# Log vv event
vv.event(query, docs_with_score)

```

## Advanced Use

### Query metadata

Assign custom metadata to an `event()` by passing a `dict` as the third argument.

```python theme={null}
vv.event(query, docs_with_score, {"foo": "bar"})

```

### Document metadata

Documents in `vectorview` are [langchain Documents](https://docs.langchain.com/docs/components/schema/document) which has a `metadata` field. Any metadata added will show up in your `vectorview` dashboard.

```python theme={null}
docs_with_score[0][0].metadata = {"foo": "bar"}
vv.event(query, docs_with_score)
```

### Custom document id

Vectorview assigns an id to each document used in an `event()`. To assign a custom id, add an `id` field in the [Document's](https://docs.langchain.com/docs/components/schema/document) metadata.

```python theme={null}
docs_with_score[0][0].metadata = {"id": new_id}
vv.event(query, docs_with_score)
```